WO2012154935A1 - Biomarkers that are predictive of responsiveness or non-responsiveness to treatment with lenvatinib or a pharmaceutically acceptable salt thereof - Google Patents

Biomarkers that are predictive of responsiveness or non-responsiveness to treatment with lenvatinib or a pharmaceutically acceptable salt thereof Download PDF

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Publication number
WO2012154935A1
WO2012154935A1 PCT/US2012/037281 US2012037281W WO2012154935A1 WO 2012154935 A1 WO2012154935 A1 WO 2012154935A1 US 2012037281 W US2012037281 W US 2012037281W WO 2012154935 A1 WO2012154935 A1 WO 2012154935A1
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WIPO (PCT)
Prior art keywords
subject
lenvatinib
expression level
pharmaceutically acceptable
acceptable salt
Prior art date
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PCT/US2012/037281
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French (fr)
Inventor
Andrew Eisen
Yasuhiro Funahashi
Tadashi Kadowaki
Iya G. Khalil
Paul D. Mcdonagh
John J. Nemunaitis
Min Ren
Jason S. Simon
Natalie C. Twine
Heming Xing
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Eisai R&D Management Co., Ltd.
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Application filed by Eisai R&D Management Co., Ltd. filed Critical Eisai R&D Management Co., Ltd.
Publication of WO2012154935A1 publication Critical patent/WO2012154935A1/en

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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/106—Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers

Definitions

  • the present invention relates to biomarkers that are useful in predicting the responsiveness or non-responsiveness of a subject to an antitumor agent such as lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • an antitumor agent such as lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • kinase inhibitors have been developed as antitumor agents.
  • a group of compounds having inhibitory activity against receptor tyrosine kinases such as vascular endothelial growth factor receptor (VEGFR)
  • VEGFR vascular endothelial growth factor receptor
  • Lenvatinib mesylate also known as E7080
  • FGFR fibroblast growth factor receptor
  • RET transfection receptor
  • KIT platelet derived growth factor receptor
  • PDGFR platelet derived growth factor receptor
  • the present application is based, at least in part, on the identification of biomarkers that are predictive of a subject's responsiveness or non-responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof e.g., lenvatinib mesylate.
  • the expression level of one or more of the genes depicted in Table 1 can predict the likelihood that a given subject will or will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • biomarkers and compositions described herein are useful, for example, in identifying and/or selecting a patient or a subset of patients that could benefit from treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • a pharmaceutically acceptable salt thereof e.g., lenvatinib mesylate.
  • biomarkers and compositions described herein are useful in identifying and/or selecting a patient or a subset of patients who are unlikely to benefit from a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • the methods described herein are useful, for example, in selecting appropriate treatment modalities (e.g., therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) or a non-lenvatinib therapy) for a subject suffering from a cancer or at risk of developing a cancer.
  • appropriate treatment modalities e.g., therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) or a non-lenvatinib therapy
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of ADAMTS9 in the biological sample, wherein an elevated expression level, as compared to a control, of ADAMTS9 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of AMIGOl in the biological sample, wherein an elevated expression level, as compared to a control, of AMIGOl is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes 'providing a biological sample obtained from a subject and measuring the expression level of ANKRD13D in the biological sample, wherein an elevated expression level, as compared to a control, of AN RD13D is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the ANK D13D gene.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of ARRDC4 in the biological sample, wherein an elevated expression level, as compared to a control, of ARRDC4 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the ARRDC4 gene.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of ATF3 in the biological sample, wherein an elevated expression level, as compared to a control, of ATF3 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of ATP11C in the biological sample, wherein an elevated expression level, as compared to a control, of ATP11C is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of CACNAII in the biological sample,' wherein an elevated expression level, as compared to a control, of CACNAII is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of CCBLl in the biological sample, wherein an elevated expression level, as compared to'a control, of CCBLl is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological samp le t obtained from a subject and measuring the expression level of CHKA in the biological sample, wherein an elevated expression level, as compared to a control, of CHKA is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the CHKA gene.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of COPS7B in the biological sample, wherein an elevated expression level, as compared to a control, of COPS7B is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the COPS7B gene.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes ⁇ providing a biological sample obtained from a subject and measuring the expression level of C70RF in the biological sample, wherein an elevated expression level, as compared to a control, of C70RF is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the C70RF gene.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of DSCCl in the biological sample, wherein an elevated expression level, as compared to a control, of DSCCl is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the DSCC1 gene.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of EML6 in the biological sample, wherein an elevated expression level, as compared to a control, of EML6 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of ERG in the biological sample, wherein an elevated expression level, as compared to a control, of ERG is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of FAM122A in the biological sample, wherein an elevated expression level, as. compared to a control, of FAM122A is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of GDPD5 in the biological sample, wherein an elevated expression level, as compared to a control, of GDPD5 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the GDPD5 gene.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of GJB2 in the biological sample, wherein an elevated expression level, as compared to a control, of GJB2 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the GJB2 gene.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of GNB5 in the biological sample, wherein an elevated expression level, as compared to a control, of GNB5 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of HIPK2 in the biological sample, wherein an elevated expression level, as compared to a control, of HIPK2 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the HIPK2 gene.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of IGJ. in the biological sample, wherein an elevated expression level, as compared to a control, of IGJ is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample, obtained from a subject and measuring the expression leVel of IL22RA2 in the biological sample, wherein an elevated expression level, as compared to a control, of IL22RA2 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the IL22RA2 gene.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of INSR in the biological sample, wherein an elevated expression level, as compared to a control, of INSR is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of MDM1 in the biological sample, wherein an elevated expression level, as compared to a control, of MDM1 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the MDM1 gene.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of MSRB2 in the biological sample, wherein an elevated expression level, as compared to a control, of MSRB2 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the MSRB2 gene.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of NAPEPLD in the biological sample, wherein an elevated expression level, as compared to a control, of NAPEPLD is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the NAPEPLD gene.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of NEIL2 in the biological sample, wherein an elevated expression level, as compared to a control, of NEIL2 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the NEIL2 gene.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of NPY6R in the biological sample, wherein an elevated expression level, as compared to a control, of NPY6R is predictive that the subject will respond to a therapy gap comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of UP188 in the biological sample, wherein an elevated expression level, as compared to a control, of NTJP188 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of OSBPL10 in the biological sample, wherein an elevated expression level, as compared to a control, of OSBPL10 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the OSBPL10 gene.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of PDXDC1 PDXDC2 in the biological sample, wherein an elevated expression level, as'compared to a control, of PDXDC1/PDXDC2 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the PDXDC1/PDXDC2 genes.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of PFKFB2 in the biological sample, wherein an elevated expression level, as compared to a control, of PFKFB2 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of PGCP in the biological sample, wherein an elevated expression level, as compared to a control, of PGCP is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of PIP5K1B in the biological sample, wherein an elevated expression level, as compared to a control, of PIP5K1B is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of PPARD in the biological sample, wherein an elevated expression level, as compared to a control, of PPARD is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of PSPH in the biological sample, wherein an elevated expression level, as compared to a control, of PSPH is predictive that the subject will not- respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the PSPH gene.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of RAP2A in the biological sample, wherein an elevated expression level, as compared to a control, of RAP2A is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of RORA in the biological sample, wherein an elevated expression level, as compared to a control, of RORA is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of SHMTl in the biological sample, wherein an elevated expression level, as compared to a control, of SHMTl is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of SLC31A1 in the biological sample, wherein an elevated expression level, as compared to a control, of SLC31A1 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of SSPN in the biological sample, wherein an elevated expression level, as compared to a control, of SSPN is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the SSPN gene.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of STAG3L4 in the biological sample, wherein an elevated expression level, as compared to a control, of STAG3L4 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the STAG3L4 gene.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of SURF4 in the biological sample, wherein an elevated expression level, as compared to a control, of SURF4 is predictive that the subject will respond to a therapy, comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of TARBP2 in the biological sample, wherein an elevated expression level, as compared to a control, of TARBP2 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the TARBP2 gene.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of TMEM2 in the biological sample, wherein an elevated expression level, as compared to a control, of TMEM2 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of T KS in the biological sample, wherein an elevated expression level, as compared to a control, of TNKS is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the TNKS gene.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of TTLL4 in the biological sample, wherein an elevated expression level, as compared to a control, of TTLL4 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the TTLL4 gene.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of TUBBP5 in the biological sample, wherein an elevated expression level, as compared to a control, of TUBBP5 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of UBA6 in the biological sample, wherein an elevated expression level, as compared to a control, of UBA6 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of VPS37A in the biological sample, wherein an elevated expression level, as compared to a control, of VPS37A is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the VPS37A gene.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of ZC3HllA in the biological sample, wherein an elevated expression level, as compared to a control, of ZC3HllA is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of ZC3H6 in the biological sample, wherein an elevated expression level, as compared to a control, of ZC3H6 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the ZC3H6 gene.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of Z F529 in the biological sample, wherein an elevated expression level, as compared to a control, of ZNF529 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of ZNF542 in the biological sample, wherein an elevated expression level, as compared to a control, of ZNF542 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of SNRNP70 in the biological sample, wherein an elevated expression level, as compared to a control, of SNRNP70 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of CLINTl in the biological sample, wherein an elevated expression level, as compared to a control, of CLINTl is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of CPM in the biological sample, wherein an elevated expression level, as compared to a control, of CPM is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the CPM gene.
  • the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of one or more genes in the biological sample, wherein the one or more genes comprise at least one gene selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R, IGJ, NUP188, ERG, MDM1, HIPK2, INSR, ZNF529, DSCC1, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, ADAMTS9, SSPN, ZC3H6, VPS37A, OSBPLIO, PDXDC1/PDXDC2, RORA, ANKRD13D
  • the subject has, or is at risk of developing, a cancer.
  • the cancer is selected from the group consisting of a skin cancer, a liver cancer, a lung cancer, a brain tumor, a thyroid cancer, an ovarian cancer, a renal cancer and an endometrial cancer.
  • the cancer is a melanoma.
  • the subject is a human.
  • the biological sample is selected from the group consisting of a blood sample, circulating tumor cells, circulating DNA, a plasma sample, a serum sample, a urine sample, a skin sample and a tumor sample.
  • the method further includes communicating the test results to the subject's health care provider.
  • the method further includes modifying the subject's medical record to indicate that the subject is likely to respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, if the expression level of one or more of SLC31A1, PFKFB2, NPY6R, IGJ, NUP188, ERG, INSR, ZNF529, PIP5K1, TMEM2, TUBBP5, UBA6, SURF4, FAM122A, AMIGOl, ADAMTS9, RORA, ZNF542, PPARD, ATP11C, EML6, GNB5, ATF3, ZC3H11A, CCBLl, SHMT1, RAP2A, CACNA1I, PGCP, SNRNP70, and CLINT1 is elevated, as compared to a control.
  • the method further includes modifying the subject's medical record to indicate that the subject is not likely to respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, if the expression level of one or more of TNKS, TARBP2, TTLL4, CHKA, PSPH, CPM, , MDMl, HIPK2, DSCCl, STAG3L4, MSRB2, GDPD5, GJB2, ARRDC4, COPS7B, NEIL2, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDC1/PDXDC2, ANKRD13D, NAPEPLD, C70RF and IL22RA2 is elevated, as compared to a control.
  • the record is created on a computer readable medium.
  • the method further includes prescribing a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof for the subject if the expression level of one or more genes in the biological sample is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the method further includes
  • the method involves determining that the expression level of one or more of SLC31A1, PFKFB2, PY6R, IGJ, NUP188, ERG, INSR, ZNF529, PIP5K1, TMEM2, TUBBP5, UBA6, SURF4, FAM122A, AMIGOl, ADAMTS9, RORA, ZNF542, PPARD, ATP11C, EML6, GNB5, ATF3, ZC3H11A, CCBL1, SHMTl, RAP2A, CACNAII, PGCP, SNRNP70, and CLINTl is elevated, as compared to a control and selecting a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof for the subject.
  • the method involves determining that the expression level of one or more of TNKS, TARBP2, TTLL4, CHKA, PSPH, CPM, MDM1, HIPK2, DSCC1, STAG3L4, MSRB2, GDPD5, GJB2, ARRDC4, COPS7B, NEIL2, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDC 1/PDXDC2, ANKRD13D, NAPEPLD, C70RF, and IL22RA2 is elevated, as compared to a control and selecting a therapy comprising an agent that is not lenvatinib for the subject.
  • the RNA level of the one or more genes is measured.
  • the protein level of, the one or more genes is measured.
  • the method further includes administering to the subject a therapy that does not comprise lenvatinib if the expression level of one or more genes in the biological sample is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the method comprises measuring the expression level of at least five genes selected from the group consisting of TNKS, TTLL4, PGCP, ERG, GJB2, INSR, FAM122A, SSPN, VPS37A, PDXDC 1/PDXDC2, ZNF542, ATP11C, CPM, SNRNP70, CLINTl, and
  • the method comprises measuring the expression level of at least eight genes selected from the group consisting of TNKS, TTLL4, PGCP, ERG, GJB2, INSR, FAM122A, SSPN, VPS37A, PDXDC 1/PDXDC2, ZNF542, ATP11C, CPM, SNRNP70, CLINTl, and ZC3H11A.
  • the method comprises measuring the expression level of at least five genes selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R, IGJ, NUP188, ERG, MDM1, HIPK2, INSR, ZNF529, DSCC1, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, ADAMTS9, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDC 1/PDXDC2, RORA, ANK D13D, ZNF542, PPARD, NAPEPLD, ATPllC, EML6, GNB5, ATF3, ZC3H11A, CPM, SNRNP70, CLINT1, and CCBLl.
  • TNKS TNKS
  • TARBP2
  • the method comprises measuring the expression level of at least eight genes selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R IGJ, NUP188, ERG, MDMl, HIPK2, INSR, ZNF529, DSCCl, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, ADAMTS 9, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDC1/PDXDC2, RORA, ANKRD13D, ZNF542, PPARD, NAPEPLD, ATPllC, EML6, GNB5, ATF3, ZC3H11A, CPM, SNRNP70, CLINT1 and CCBLl.
  • the method includes measuring the expression level of at least eight genes selected
  • the disclosure provides a method of selecting a subject having, or at risk of developing, a cancer that would benefit from treatment comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • the method includes the steps of determining the expression level in a biological sample obtained from a subject of at least one gene selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R, IGJ, NUP188, ERG, MDMl, HIPK2, INSR, ZNF529, DSCCl, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, AD AMTS9, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDC1/PDXDC2, RORA, ANKRD13D, ZNF542,
  • the method involves measuring the expression level of SHMT1. In another embodiment of this aspect, the method involves measuring the expression level of C70RF. In another embodiment of this aspect, the method involves measuring the expression level of IL22RA2. In another embodiment of this aspect, the method involves measuring the expression level of TARBP2. In another embodiment of this aspect, the method involves measuring the expression level of RAP2A. In another embodiment of this aspect, the method involves measuring the expression level of CACNA1I.
  • the method comprises measuring the expression level of at least five genes selected from the group consisting of TNKS, TTLL4, PGCP, ERG, GJB2, INSR, FAM122A, SSPN, VPS37A, PDXDC1/PDXDC2, ZNF542, ATP11C, CPM, SNRNP70, CLINT1, and ZC3H11A.
  • the method comprises measuring the expression level of at least eight genes selected from the group consisting of TNKS, TTLL4, PGCP, ERG, GJB2, INSR, FAM122A, SSPN, VPS37A, PDXDC 1/PDXDC2, ZNF542, ATP11C, CPM, SNRNP70, CLINT1, and ZC3H11A.
  • the method involves measuring the expression level of at least five genes selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R, IGJ, NUP188, ERG, MDMl, HIPK2, INSR, ZNF529, DSCC1, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, ADAMTS9, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDC1 PDXDC2, RORA, ANKRD13D, ZNF542, PPARD, NAPEPLD, ATP11C, EML6, GNB5, ATF3, ZC3H11A, CPM, SNRNP70, CLINT1, and CCBL1.
  • genes selected from the group consisting of TNKS,
  • the method involves measuring the expression level of at least eight genes selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R, IGJ, NUP188, ERG, MDMl, HIPK2, INSR, ZNF529, DSCC1, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, ADAMTS9, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDC 1 PDXDC2, RORA, ANKRD13D, ZNF542, PPARD, NAPEPLD, ATP11C, EML6, GNB5, ATF3, ZC3H11A, CPM, SNRNP70, CLINT1, and CCBLl.
  • genes selected from the group consisting of TNKS
  • the method comprises measuring the expression level of SHMTl, C70RF, IL22RA2, TARBP2, RAP2A, and CACNAII.
  • the RNA level of the one or more genes is measured.
  • the protein level of the one or more genes is measured.
  • the disclosure provides a method of treating a cancer, the method including the step of administering to a subject in need thereof an effective amount of a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, wherein the subject has been identified as having an elevated expression level, as compared to a control, of one or more of SLC31A1, PFKFB2, NPY6R, IGJ, NUP188, ERG, INSR, ZNF529, PIP5K1, TMEM2, TUBBP5, UBA6, SURF4, FAM122A, AMIGOl, ADAMTS9, RORA, ZNF542, PPARD, ATP11C, EML6, GNB5, ATF3, ZC3H11A, CCBLl, SHMTl, RAP2A, CACNAII, PGCP, SNRNP70, and CLINTl.
  • the disclosure provides a method of treating a cancer, the method comprising determining the expression level of one or more of SLC31A1, PFKFB2, NPY6R, IGJ, NUP188, ERG, INSR, ZNF529, PIP5K1, TMEM2, TUBBP5, UBA6, SURF4, FAM122A, AMIGOl, ADAMTS9, RORA, ZNF542, PPARD, ATP11C, EML6, GNB5, ATF3, ZC3H11A CCBLl, SHMTl, RAP2A, CACNAII, PGCP, SNRNP70, and CLINTl; and administering to a subject having an elevated expression level, as compared to a control, of one or more of SLC31A1, PFKFB2, NPY6R, IGJ, NUP188, ERG, INSR, ZNF529, PIP5K1, TMEM2, TUBBP5, UBA6, SURF4, FAM122A, AMIGOl
  • the subject is a human.
  • the cancer is selected from the group consisting of a skin cancer, a liver cancer, a lung cancer, a brain tumor, a thyroid cancer, an ovarian cancer, a renal cancer and an endometrial cancer.
  • the cancer is a melanoma.
  • the RNA level of the one or more genes is measured.
  • the protein level of the one or more genes is measured.
  • the subject has been identified as having an elevated expression level, as compared to a control, of SHMTl.
  • the subject has been identified as having an elevated expression level, as compared to a control, of RAP2A.
  • the subject has been identified as having an elevated expression level, as compared to a control, of CACNAII.
  • the disclosure provides a composition comprising at least five polynucleotides that selectively hybridize to each of at least five genes selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R, IGJ, NUP188, ERG, MDMl, HIPK2, INSR, ZNF529, DSCCl, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, ADAMTS9, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDC 1/PDXDC2, RORA, ANKRD13D, ZNF542, PPARD, NAPEPLD, ATPllC, EML6, GNB5, ATF3, ZC3H11A, CCBLl, SHMTl
  • the at least five genes are selected from the group consisting of TNKS, TTLL4, PGCP, ERG, GJB2, INSR, FAM122A, SSPN, VPS37A, PDXDC 1/PDXDC2, ZNF542, ATPllC, SNRNP70, CLINTl, and ZC3H11A.
  • the at least five genes are selected from the group consisting of SHMTl, C70RF, IL22RA2, TARBP2, RAP2A, and CACNA1I.
  • the at least five polynucleotides are bound to a solid support.
  • the disclosure provides a composition comprising at least three polynucleotides that selectively hybridize to each of at least three genes selected from the group consisting of SHMTl, C70RF, IL22RA2, TARBP2, RAP2A, and
  • the at least three polynucleotides are bound to a solid support.
  • the disclosure provides a kit comprising an array including a plurality of polynucleotides bound to a solid support, wherein the plurality comprises at least five polynucleotides that selectively hybridize to each of at least five genes selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R, IGJ, NTJP188, ERG, MDMl, HIPK2, INSR, ZNF529, DSCCl, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, AD AMTS9, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDC 1/PDXDC2, RORA, ANKRD13D, ZNF542, PPARD, NAPEPLD,
  • the kit further includes one or more reagents for isolating nucleic acid from a sample. In other embodiments, the kit further includes a means for amplifying a nucleic acid.
  • the disclosure provides a kit comprising an array.
  • the array includes a plurality of polynucleotides bound to a solid support, wherein the plurality comprises at least three polynucleotides that selectively hybridize to each of at least three genes selected from the group consisting of SHMTl, C70RF, IL22RA2, RAP2A, TARBP2, and CACNA1I.
  • the kit also includes instructions for detecting the presence or amount of one of more of the polynucleotides in a sample.
  • Fig. 1 is a schematic diagram of building Bayesian BioModelTM and Monte Carlo simulations.
  • D. Diversity in network structures identified during network reconstruction captures uncertainty in the model. Hypotheses are extracted from the network ensemble by competing Monte Carlo simulations of "what- if ' scenarios. The change in the gene that is circled would be expected to impact phenotypic endpoints.
  • Fig. 2 is a schematic diagram of the consensus topology of the ensemble of networks. Snapshot of the network ensemble at 0.1% consensus topology. White pads are phenotypic endpoints, transcripts (connected with grey lines), and pharmacokinetic measures (connected with black lines).
  • Fig. 3 shows simulation results of four candidate markers for maximal tumor shrinkage (MTS). Distributions of simulated values of MTS if a marker gene expression is modulated are plotted (broken line curve: baseline; solid line curve: 10- fold knockdown). A. C70RF B. TARBP2 C. RAP2A D. CACNA1I. Fig. 4 shows simulation results of six candidate markers for progression free survival (PFS). Distributions of simulated values of PFS if a marker gene expression is modulated are plotted (broken line curve: baseline; solid line curve: 10-fold knockdown). A. SHMT1 B. IL22RA2 C. C70RF/D. TARBP2 E. RAP2A F. CACNA1I.
  • MTS maximal tumor shrinkage
  • compositions for predicting the response of a subject (such as a human patient) to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • predictive biomarkers e.g., gene expression levels
  • identify those subjects for whom administering a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof e.g., lenvatinib mesylate
  • Such biomarkers, compositions, and methods are useful in selecting appropriate therapeutic modalities (e.g., a lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) therapy or a non- lenvatinib therapy) for subjects suffering from diseases such as cancer.
  • appropriate therapeutic modalities e.g., a lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) therapy or a non- lenvatinib therapy
  • this application provides methods of selecting patients that could benefit from a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) as well as methods of treatment.
  • CTCs circulating tumor cells
  • circulating DNA refers to DNA that is present in increased amounts in plasma or serum of cancer patients. Cancer patients have higher levels of circulating DNA than healthy controls (Leon et al., Cancer Res., 37: 646 650 (1977); Chuang et al., Head & Neck, 229-234 (2010)).
  • decreased/reduced expression level means an expression level that is lower than the expression level in a control.
  • Elevated expression level means an expression level that is higher than the expression level in a control.
  • salts include, but are not limited to, inorganic acid addition salt such as hydrochloric acid salt, sulfuric acid salt, carbonic acid salt, bicarnobate salt, hydrobromic acid salt and hydriodic acid salt; organic carboxylic acid addition salt such as acetic acid salt, maleic acid salt, lactic acid salt, tartaric acid salt and trifluoroacetic acid salt; organic sulfonic acid addition salt such as methanesulfonic acid salt, hydroxymethanesulfonic acid salt, hydroxyethanesulfonic acid salt, benzenesulfonic acid salt, toluenesulfonic acid salt and taurine salt; amine addition salt such as trimethylamine salt, triethylamine salt, pyridine salt, procaine salt, picoline salt, dicyclohexylamine salt, ⁇ , ⁇ '-dibenzylethylenediamine salt, N
  • the pharmaceutically acceptable salt is a methanesulfonic acid salt ("mesylate").
  • the methanesulfonic acid salt form (i.e., the mesylate) of 4-(3-chloro-4 (cyclopropylaminocarbony0aminophenoxy)-7- methoxy-6-quinolinecarboxamide is disclosed in US Patent 7,612,208, which is incorporated by reference herein in its entirety.
  • nucleic acid and “polynucleotide” are used interchangeably herein, and refer to both RNA and DNA, including cDNA, genomic DNA, synthetic DNA, and DNA (or RNA) containing nucleic acid analogs. Polynucleotides can have any three- dimensional structure. A nucleic acid can be double-stranded or single-stranded (i.e., a sense strand or an antiserise strand).
  • Non-limiting examples of polynucleotides include genes, gene fragments, exons, introns, messenger RNA (mRNA), transfer RNA, ribosomal RNA, siRNA, micro-RNA, ribozymes, cDNA, recombinant polynucleotides, branched polynucleotides, plasmids, vectors, isolated DNA of any sequence, isolated RNA of any sequence, nucleic acid probes, and primers, as well as nucleic acid analogs.
  • mRNA messenger RNA
  • transfer RNA transfer RNA
  • ribosomal RNA siRNA
  • micro-RNA micro-RNA
  • ribozymes cDNA
  • recombinant polynucleotides branched polynucleotides
  • plasmids vectors, isolated DNA of any sequence, isolated RNA of any sequence, nucleic acid probes, and primers, as well as nucleic acid analogs.
  • Polypeptide and “protein” are used interchangeably herein and mean any peptide-linked chain of amino acids, regardless of length or post-translational modification.
  • a polypeptide described herein is “isolated” when it constitutes at least 60%, by weight, of the total protein in a preparation, e.g., 60% of the total protein in a sample.
  • a polypeptide described herein consists of at least 75%, at least 90%, or at least 99%, by weight, of the total protein in a preparation.
  • subject means a mammal, including but not limited to, a human, a chimpanzee, an orangutan, a gorilla, a baboon, a monkey, a mouse, a rat, a pig, a horse, a dog, and a cow.
  • genes have been identified whose expression levels (e.g., mRNA or protein expression levels) are predictive of the responsiveness or non-responsiveness of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). These genes and their representative Genbank® Accession Nos. are listed in Table 1. The sequences provided herein for these genes are merely representative of the sequences for the biomarker genes listed below. This disclosure also encompasses defection of expression levels of a gene using partial sequences, allelic variants and mutations (among others) of the sequences provided herein.
  • sequence provided herein is a partial sequence of a full length sequence of a gene
  • this disclosure also encompasses detection of expression levels of a gene using the entire sequence of the gene or other partial sequences of the gene which may or may not overlap with the sequence provided herein.
  • An elevated expression level of a gene listed in Table 1 can be predictive of either responsiveness or non-responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • Information concerning the expression of as few as one gene listed in Table 1 is useful in predicting responsiveness or lack thereof to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • Biological samples e.g., tumors
  • an elevated expression level (compared to a control) of any one or more of the genes Usted in Table 2 is predictive that a subject wiU respond to a therapy comprising lenvatinib or a pharmaceutical 'acceptable salt thereof (e.g., lenvatinib mesylate).
  • control means a sample (or samples) from the same ceU type or tissue type as that of the test sample that is obtained from a subject (or subjects) who has not responded to treatment with lenvatinib or a pharmaceuticaUy acceptable salt thereof (e.g., lenvatinib mesylate).
  • control includes a sample obtained in the past and used as a reference for future comparisons to test samples taken from subjects for which therapeutic responsiveness is to be predicted.
  • the "control" expression level for a particular gene in a particular cell type or tissue may be pre-estabUshed by an analysis of gene expression in one or more subjects that have not responded to treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). This pre-established reference value (which may be an average expression level taken from multiple subjects that have not responded to the therapy) may then be used for the "control" expression level in the comparison with the test sample.
  • control expression level for a particular gene in a particular cell type or tissue may alternatively be pre-established by an analysis of gene expression in one or more subjects that have responded to treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • This pre-established reference value (which may be an average expression level taken from multiple subjects that have responded to the therapy) may then be used as the "control" expression level in the comparison with the test sample.
  • the subject is predicted to respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) if the expression level of any one or more of the genes listed in Table 2 is comparable to or higher than, for example is higher than, the same as, or about the same as (at least 85% but less than 100% of), the pre-established reference value.
  • a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) if the expression level of any one or more of the genes listed in Table 2 is comparable to or higher than, for example is higher than, the same as, or about the same as (at least 85% but less than 100% of), the pre-established reference value.
  • a level of expression that is the same as or about the same (at least 85% but less than 100% of the expression level) when compared to a sample (or samples) of any one or more of the genes listed in Table 2 from the same cell type or tissue type as that of the test sample that is obtained from a subject (or subjects) who has not responded to treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) is predictive that a subject will not respond to a therapy comprising lenvatinib or a. pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • a level of expression that is reduced when compared to a sample (or samples) of any one or more of the genes listed in Table 2 from the same cell type or tissue type as that of the test sample that is obtained from a subject (or subjects) who has responded to treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) is predictive that a subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • G GNB5 BC011671 protein Guanine Nucleotide Binding Protein (G GNB5 BC011671 protein), Beta 5
  • Neuropeptide Y Receptor Y6 NPY6R U59431 (pseudogene)
  • RAP2A member of RAS oncogene family RAP2A BE669921
  • Solute Carrier Family 31 (copper SLC31A1 NM_001859 transporters), member 1
  • Plasma Glutamate Carboxypeptidase PGCP NM 016134 An elevated expression level of one or more of the genes listed in Table 3 (relative to a control) is predictive that a subject will not respond to therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) or that a subject will respond less effectively compared to a subject having a
  • control means a sample (or samples) from the same cell type or tissue type as that of the test sample that is obtained from a subject (or subjects) who has responded to treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • control includes a sample obtained in the past and used as a reference for future comparisons to test samples taken from subjects for which therapeutic responsiveness is to be predicted.
  • control expression level for a particular gene in a particular cell type or tissue may be pre-established by an analysis of gene expression in one or more subjects that have responded to treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • This pre-established reference value (which may be an average expression level taken from multiple subjects that have responded to the therapy) may then be used for the "control" expression level in the comparison with the test sample.
  • control expressiori level for a particular gene in a particular cell type or tissue may alternatively be pre-established by an analysis of gene expression in one or more subjects that have not responded to treatment with lenvatinib or a
  • This pre- established reference value (which may be an average expression level taken from multiple subjects that have not ' responded to the therapy) may then be used as the "control" expression level in the comparison with the test sample.
  • the subject is predicted to not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) if the expression level of any one or more of the genes listed in Table 3 is comparable to or higher than, for example is higher than, the same as, or about the same as (at least 85% but less than 100% of), the pre-established reference.
  • a level of expression that is the same as or about the same (at least 85% but less than 100% of the expression leveD when compared to a sample (or samples) of any one or more of the genes listed in Table 3 from the same cell type or tissue type as that of the test sample that is obtained from a subject (or subjects) who has responded to treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) is predictive that a subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • a level of expression that is reduced when compared to a sample (or samples) of any one or more of the genes hsted in Table 3 from the same cell type or tissue type as that of the test sample that is obtained from a subject (or subjects) who has not responded to treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) is predictive that a subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • the expression level of one or more of the genes depicted in Tables 2 or 3 can be elevated (or decreased as the case may be) by 1.15 fold, 1.2 fold, 1.3 fold, 1.4 fold, 1.5 fold, 2 fold, 2.5 fold, 3 fold, 3.5 fold, 4 fold, 5 fold, or by at least about 1.15 fold, at least about 1.2 fold, at least about 1.3 fold, at least about 1.4 fold, at least about 1.5 fold, at least about 2 fold, at least about 2.5 fold, at least about 3.0 fold, at least about 3.5 fold, at least about 4.0 fold, or at least about 5 fold or more compared to a control.
  • Gene expression can be detected as, e.g., protein or mRNA expression of a target gene. That is, the presence" or expression level (amount) of a gene can be determined by detecting and/or measuring the level of mRNA or protein expression of the gene. In some embodiments, gene expression can be detected as the activity of a protein encoded by a gene such as a gene depicted in Table 1.
  • mRNA expression can be determined using Northern blot or dot blot analysis, reverse transcriptase-PCR (RT-PCR; e.g., quantitative RT-PCR), in situ hybridization (e.g., quantitative in situ hybridization) or nucleic acid array (e.g., oligonucleotide arrays or gene chips) analysis. Details of such methods are described below and in, e.g., Sambrook et al., Molecular Cloning: A Laboratory Manual Second Edition vol. 1, 2 and 3. Cold Spring Harbor Laboratory Press: Cold Spring Harbor, New York, USA, Nov. 1989; Gibson et al.
  • the presence or amount of one or more discrete mRNA populations in a biological sample can be determined by isolating total mRNA from the biological sample (see, e.g., Sambrook et al. (supra) and U.S. Patent No. 6,812,341) and subjecting the isolated mRNA to agarose gel electrophoresis to separate the mRNA by size. The size-separated mRNAs are then transferred (e.g., by diffusion) to a solid support such as a nitrocellulose membrane.
  • the presence or amount of one or more mRNA populations in the biological sample can then be determined using one or more detectably labeled-polynucleotide probes, complementary to the mRNA sequence of interest, which bind to and thus render detectable their corresponding mRNA populations.
  • Detectable-labels include, e.g., fluorescent (e.g., umbelliferone, fluorescein, fluorescein isothiocyanate, rhodamine, dichlorotriazinylamine fluorescein, dansyl chloride, allophycocyanin (APC), or phycoerythrin), luminescent (e.g., europium, terbium, QdotTM nanoparticles supplied by the Quantum Dot Corporation, Palo Alto, CA), radiological (e.g., 125 I, 131 I, 35S, 32p ( 33 ⁇ or 3H), and enzymatic (horseradish peroxidase, alkaline phosphatase, beta-galactosidase, or acetylcholinesterase) labels.
  • fluorescent e.g., umbelliferone, fluorescein, fluorescein isothiocyanate, rhodamine, dichlorotria
  • the presence or amount of discrete populations of mRNA (e.g., mRNA encoded by one or more genes depicted in Table l) in a biological sample can be determined using nucleic acid (or oligonucleotide) arrays (e.g., an array described below under "Arrays and Kits").
  • nucleic acid (or oligonucleotide) arrays e.g., an array described below under "Arrays and Kits”
  • isolated mRNA from a biological sample can be amplified using RT PCR with, e.g., random hexamer or oligo(dT)-primer mediated first strand synthesis. The amplicons can be fragmented into shorter segments.
  • the RT-PCR step can be used to detectablylabel the amplicons, or, optionally, the amplicons can be detectably-labeled subsequent to the RT-PCR step.
  • the detectable-label can be enzymatically (e.g., by nick-translation or kinase such as T4 polynucleotide kinase) or chemically conjugated to the amplicons using any of a variety of suitable techniques (see, e.g., Sambrook et al., supra).
  • the detectablylabeled-amplicons are then contacted with a plurality of polynucleotide probe sets, each set containing one or more of a polynucleotide (e.g., an oligonucleotide) probe specific for (and capable of binding to) a corresponding amplicon, and where the plurality contains many probe sets each corresponding to a different amplicon.
  • a polynucleotide e.g., an oligonucleotide
  • the probe sets are bound to a solid support and the position of each probe set is predetermined on the solid support.
  • the binding of a detectably-labeled amplicon to a corresponding probe of a probe set indicates the presence or amount of a target mRNA in the biological sample. Additional methods for detecting mRNA expression using nucleic acid arrays are described in, e.g., U.S. Patent Nos. 5,445,934; 6,027,880; 6,057,100; 6, 156,501; 6,261,776; and 6,576,424; the disclosures of each of which are incorporated herein by reference in their entirety.
  • Methods of detecting and/or for quantifying a detectable label depend on the nature of the label.
  • the products of reactions catalyzed by appropriate enzymes can be, without limitation, fluorescent, luminescent, or radioactive or they may absorb visible or ultraviolet light.
  • detectors suitable for detecting such detectable labels include, without limitation, x ray film, radioactivity counters, scintillation counters, spectrophotometers, colorimeters, fluorometers, luminometers, and densitometers.
  • the expression of a gene can also be determined by detecting and/or measuring expression of a protein encoded by the gene.
  • Methods of determining protein expression are well known in the art.
  • a generally used method involves the use of antibodies specific for the target protein of interest.
  • methods of determining protein expression include, but are not limited to, western blot or dot blot analysis, immunohistochemistry (e.g., quantitative immunohistochemistry), immunocytochemistry, enzyme-linked immunosorbent assay (ELISA), enzyme-linked immunosorbent spot (ELISPOT; Coligan, J. E., et al., eds. (1995) Current Protocols in Immunology. Wiley, New York), or antibody array analysis (see, e.g., U.S. Publication Nos.
  • the presence or amount of protein expression of a gene can be determined using a western blotting technique.
  • a lysate can be prepared from a biological sample, or the biological sample itself, can be contacted with Laemmli buffer and subjected to sodium-dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). SDS-PAGE-resolved proteins, separated by size, can then be transferred to a filter membrane (e.g., nitrocellulose) and subjected to immunoblotting techniques using a detectably-labeled antibody specific to the protein of interest. The presence or amount of bound detectably-labeled antibody indicates the presence or amount of protein in the biological sample.
  • a filter membrane e.g., nitrocellulose
  • an immunoassay can be used for detecting and/or measuring the protein expression of a gene (e.g., a gene depicted in Table l).
  • a gene e.g., a gene depicted in Table l.
  • an immunoassay can be performed with an antibody that bears a detection moiety (e.g., a fluorescent agent or enzyme).
  • Proteins from a biological sample can be conjugated directly to a solid-phase matrix (e.g., a multi-well assay plate, nitrocellulose, agarose, sepharose, encoded particles, or magnetic beads) or it can be conjugated to a first member of a specific binding pair (e.g., biotin or streptavidin) that attaches to a solid-phase matrix upon binding to a second member of the specific binding pair (e.g., streptavidin or biotin).
  • a specific binding pair e.g., biotin or streptavidin
  • Such attachment to a solid-phase matrix allows the proteins to be purified away from other interfering or irrelevant components of the biological sample prior to contact with the detection antibody and also allows for subsequent washing of unbound antibody.
  • the presence or amount of bound detectably-labeled antibody indicates the presence or amount of protein in the biological sample.
  • the present disclosure includes polyclonal antibodies, as well as monoclonal antibodies.
  • the antiserum obtained by immunizing animals such as rabbits with a protein of the invention, as well polyclonal and monoclonal antibodies of all classes, human antibodies, and humanized antibodies produced by genetic recombination, are also included.
  • an intact protein or its partial peptide may be used as the antigen for immunization.
  • partial peptides of the proteins for example, the amino (N)-terminal fragment of the protein, and the carboxy (C)-terminal fragment can be given.
  • a gene encoding a protein of interest or a fragment thereof is inserted into a known expression vector, and, by transforming the host cells with the vector described herein, the desired protein or a fragment thereof is recovered from outside or inside the host cells using standard methods.
  • This protein can be used as the sensitizing antigen.
  • cells expressing the protein, cell lysates, or a chemically synthesized protein of the invention may be also used as a sensitizing antigen.
  • the mammal that is immunized by the sensitizing antigen is not restricted; however, it is preferable to select animals by considering the compatibility with the parent cells used in cell fusion.
  • animals belonging to the orders rodentia, lagomorpha, or primates are used.
  • animals belonging to the order of rodentia that may be used include, for example, mice, rats, and hamsters.
  • animals belonging to the order of lagomorpha that may be used include, for example, rabbits.
  • animals belonging to the order of primates that may be used include, for example, monkeys.
  • monkeys to be used include the infraorder catarrhini (old world monkeys), for example, Macaca fascicularis, rhesus monkeys, sacred baboons, and chimpanzees.
  • the sensitizing antigen is injected intraperitoneally or subcutaneously into mammals.
  • the sensitizing antigen is suitably diluted and suspended in physiological saline, phosphate-buffered saline (PBS), and so on, and mixed with a suitable amount of general adjuvant if desired, for example, with Freund's complete adjuvant.
  • PBS phosphate-buffered saline
  • the solution is emulsified and injected into the mammal.
  • the sensitizing antigen suitably mixed with Freund's incomplete adjuvant is preferably given several times every 4 to 21 days.
  • a suitable carrier can also be used when immunizing and animal with the sensitizing antigen.
  • the elevation in the' level of serum antibody is detected by usual methods.
  • Polyclonal antibodies against the proteins of the present disclosure can be prepared as follows. After verifying that the desired serum antibody level has been reached, blood is withdrawn from the mammal sensitized with antigen. Serum is isolated from this blood using conventional methods. The serum containing the polyclonal antibody may be used as the polyclonal antibody, or according to needs, the polyclonal antibody-containing fraction may be further isolated from the serum. For example, a fraction of antibodies that specifically recognize the protein of the invention may be prepared by using an affinity column to which the protein is coupled. Then, the fraction may be further purified by using a Protein A or Protein G column in order to prepare immunoglobulin G or M.
  • immunocytes are taken from the mammal and used for cell fusion.
  • splenocytes can be mentioned as preferable immunocytes.
  • parent cells fused with the above immunocytes mammalian myeloma cells are preferably used. More preferably, myeloma cells that have acquired the feature, which can be used to distinguish fusion cells by agents, are used as the parent cell.
  • the cell fusion between the above immunocytes and myeloma cells can be conducted according to known methods, for example, the method by Milstein et al. (Galfre et al., Methods Enzymol. 73:3-46, 1981).
  • the hybridoma obtained from cell fusion is selected by culturing the cells in a standard selection medium, for example, HAT culture medium (medium containing hypoxanthine, aminopterin, and thymidine).
  • HAT culture medium medium containing hypoxanthine, aminopterin, and thymidine.
  • the culture in this HAT medium is continued for a period sufficient enough for cells (non-fusion cells) other than the objective hybridoma to perish, usually from a few days to a few weeks.
  • the usual limiting dilution method is carried out, and the hybridoma producing the objective antibody is screened and cloned.
  • a hybridoma producing the objective human antibodies having the activity to bind to proteins can be obtained by the method of sensitizing human lymphocytes, for example, human lymphocytes infected with the EB virus, with proteins, proteiri-expressing cells, or lysates thereof in vitro and fusing the sensitized lymphocytes with inyeloma cells derived from human, for example, U266, having a permanent cell division ability.
  • the monoclonal antibodies obtained by transplanting the obtained hybridomas into the abdominal cavity of a mouse and extracting ascites can be purified by, for example, ammonium sulfate precipitation, protein A or protein G column, DEAE ion exchange chromatography, an affinity column to which the protein of the present disclosure is coupled, and so on. :
  • Monoclonal antibodies can be also obtained as recombinant antibodies produced by using the genetic engineering technique (see, for example, Borrebaeck C.A.K. and Larrick, J.W., THERAPEUTIC MONOCLONAL ANTIBODIES, Published in the United Kingdom by MACMILLAN PUBLISHERS LTD (1990)).
  • Recombinant antibodies are produced by cloning the encoding DNA from immunocytes, such as hybridoma or antibody-producing sensitized lymphocytes, incorporating into a suitable vector, and introducing this vector into a host to produce the antibody.
  • the present disclosure encompasses such recombinant antibodies as well.
  • Antibodies or antibody fragments specific for a protein encoded by one or more biomarkers can also be generated by in vitro methods such as phage display.
  • the antibody of the present disclosure may be an antibody fragment or modified-antibody, so long as it binds to a protein encoded by a biomarker of the invention.
  • Fab, F (ab 2, Fv, or single chain Fv (scFv) in which the H chain Fv and the L chain Fv are suitably linked by a linker can be given as antibody fragments.
  • antibody fragments are generated by treating antibodies with enzymes, for example, papain or pepsin.
  • they may be generated by constructing a gene encoding an antibody fragment, introducing this into an expression vector, and expressing this vector in suitable host cells (see, for example, Co et al., J. Immunol., 152:2968-2976, 1994; Better et al., Methods EnzymoL, 178:476 496, 1989; Pluckthun et al., Methods EnzymoL, 178:497-515, 1989; Lamoyi, Methods EnzymoL, 121:652 663, 1986; Rousseaux et al., Methods EnzymoL, 121:663-669, 1986; Bird et al., Trends BiotechnoL, 9:132- 137, 1991).
  • the antibodies may be conjugated to various molecules, such as polyethylene glycol (PEG), fluorescent substances, radioactive substances, and luminescent substances.
  • PEG polyethylene glycol
  • Methods to attach such moieties to an antibody are already established and conventional in the field (see, e.g., US 5,057,313 and 5, 156,840).
  • Examples of methods that assay the antigen-binding activity of the antibodies include, for example, measurement of absorbance, enzyme-linked immunosorbent assay (ELISA), enzyme immunoassay (EIA), radioimmunoassay (RIA), and/or immunofluorescence.
  • ELISA enzyme-linked immunosorbent assay
  • EIA enzyme immunoassay
  • RIA radioimmunoassay
  • immunofluorescence when using ELISA, a protein encoded by a biomarker of the invention is added to a plate coated with the antibodies of the present disclosure, and then, the antibody sample, for example, culture supernatants of antibody-producing cells, or purified antibodies are added.
  • a protein fragment for example, a fragment comprising a C-terminus, or a fragment comprising an N-terminus may be used.
  • BIAcore Pharmacia
  • the antibody of the invention and a sample presumed to contain a protein of the invention are contacted, and the protein encoded by a biomarker of the invention is detected or assayed by detecting or assaying the immune complex formed between the above-mentioned antibody and the protein.
  • Mass spectrometry based quantitation assay methods for example, but not limited to, multiple reaction monitoring (MRM)-based approaches in combination with stable-isotope labeled internal standards, are an alternative to immunoassays for quantitative measurement of proteins. These approaches do not require the use of antibodies and so the analysis can be performed in a cost- and time- efficient manner (see, for example, Addona et al., Nat. Biotechnol., 27:633-641, 2009, " Kuzyk et al., Mol Cell Proteomics, 8U860-1877, 2009; Paulovich et al., Proteomics Clin. Appl, 2 1386- 1402, 2008).
  • MRM offers superior multiplexing capabilities, allowing for the simultaneous quantification of numerous proteins in parallel. The basic theory of these methods have been well-established and widely utilized for drug metabolism and pharmacokinetics analysis of small molecules.
  • Methods for detecting or measuring gene expression can optionally be performed in formats that allow for rapid preparation, processing, and analysis of multiple samples. This can be, for example, in multi-welled assay plates (e.g., 96 wells or 386 wells) or arrays (e.g., nucleic acid chips or protein chips).
  • Stock solutions for various reagents can be provided manually or robotically, and subsequent sample preparation (e.g., RT-PCR, labeling, or cell fixation), pipetting, diluting, mixing, distribution, washing, incubating (e.g., hybridization), sample readout, data collection (optical data) and/or analysis (computer aided image analysis) can be done robotically using commercially available analysis software, robotics, and detection instrumentation capable of detecting the signal generated from the assay. Examples of such detectors include, but are not limited to, spectrophotometers, luminometers, fluorimeters, and devices that measure radioisotope decay.
  • Exemplary high- throughput cell-based assays can utilize ArrayScan® VTI HCS Reader or KineticScan® HCS Reader technology (Cellomics Inc., Pittsburg, PA).
  • the expression level of two genes, three genes, four genes, five genes, six genes, seven genes, eight genes, nine genes, 10 genes, 11 genes, 12 genes, 13 genes, 14 genes, 15 genes, 16 genes, 17 genes, 18 genes, 19 genes, 20 genes, 21 genes, 22 genes, 23 genes, at least 24 genes, at least 25 genes or more, or at least two genes, at least three genes, at least four genes, at least five genes, at least six genes, at least seven genes, at least eight genes, at least nine genes, at least 10 genes, at least 11 genes, at least 12 genes, at least 13 genes, at least 14 genes, at least 15 genes, at least 16 genes, at least 17 genes, at least 18 genes, at least 19 genes, at least 20 genes, at least 21 genes, at least 22 genes, at least 23 genes, at least 24 genes, or at least 25 genes or more can be assessed and/or measured.
  • any part of the nucleic acid sequence of the genes can be used, e.g., as hybridization polynucleotide probes or primers (e.g., for amplification or reverse transcription).
  • the probes and primers can be oligonucleotides of sufficient length to provide specific hybridization to an RNA , DNA, cDNA, or fragments thereof derived from a biological sample.
  • varying hybridization conditions can be employed to achieve varying degrees of selectivity of a probe or primer towards target sequence.
  • the primers and probes can be detectably- labeled with reagents that facilitate detection (e.g., fluorescent labels, chemical labels (see, e.g., U.S. Patent Nos. 4,582,789 and 4,563,417), or modified bases).
  • reagents e.g., fluorescent labels, chemical labels (see, e.g., U.S. Patent Nos. 4,582,789 and 4,563,417), or modified bases).
  • nucleic acid molecule In order for a nucleic acid molecule to serve as a primer or probe it need only be sufficiently complementary in sequence to be able to form a stable double-stranded structure under the particular hybridization conditions (e.g., solvent and salt concentrations) employed.
  • particular hybridization conditions e.g., solvent and salt concentrations
  • Hybridization can be used to assess homology between two nucleic acid sequences.
  • a nucleic acid sequence described herein, or a fragment thereof can be used as a hybridization probe according to standard hybridization techniques.
  • the hybridization of a probe of interest e.g., a probe containing a portion of a nucleotide sequence described herein or its complement
  • DNA, RNA, cDNA, or fragments thereof from a test source is an indication of the presence of DNA or RNA
  • Hybridization conditions are known to those skilled in the art and can be found in Current Protocols in Molecular Biology, John Wiley & Sons, N.Y., 6.3.1-6.3.6, 1991.
  • Moderate hybridization conditions are defined as hybridization in 2X sodium chloride/sodium citrate (SSC) at 30°C, followed by a wash in 1 X SSC, 0.1% SDS at 50°C.
  • Highly stringent conditions are defined as hybridization in 6X SSC at 45°C, followed by a wash in 0.2 X SSC, 0.1% SDS at 65°C.
  • Primers can be used in in a variety of PCR type methods. For example, polymerase chain reaction (PCR) techniques can be used to amplify specific sequences from DNA as well as RNA, including sequences from total genomic DNA or total cellular RNA.
  • the PCR primers are designed to flank the region that one is interested in amplifying. Primers can be located near the 5' end, the 3' end or anywhere within the nucleotide sequence that is to be amplified.
  • the amplicon length is dictated by the experimental goals. For qPCR, the target length is closer to 100 bp and for standard PCR, it is near 500 bp.
  • PCR primers can be chemically synthesized, either as a single nucleic acid molecule (e.g., using automated DNA synthesis in the 3' to 5' direction using phosphoramidite technology) or as a series of oligonucleotides.
  • one or more pairs of long oligonucleotides can be synthesized that contain the desired sequence, with each pair containing a short segment of complementarity (e.g., about 15 nucleotides) such that a duplex is formed when the oligonucleotide pair is annealed.
  • DNA polymerase is used to extend the oligonucleotides, resulting in a single, double-stranded nucleic acid molecule per oligonucleotide pair.
  • nucleic acid sequences or fragments thereof e.g., amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids, amino acids
  • oligonucleotide probes can be used in nucleic acid arrays (such as the nucleic acid arrays described below under "Arrays") for detection and/or quantitation of gene expression.
  • Nucleic acid arrays including the nucleic acid biomarkers disclosed herein are useful in, e.g., detecting gene expression and/or measuring gene expression levels.
  • the arrays are also useful for e.g., in predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), for identifying subjects who can benefit from a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), and for steering subjects who would not likely benefit from a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) to other cancer therapies.
  • a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof e.g., lenvatinib mesylate
  • An array is an orderly arrangement of samples where matching of known and unknown DNA samples is done based on base pairing rules (e.g., Adenosine pairs with Thymine or Uracil; Guanosine pairs with Cytosine).
  • a typical microarray experiment involves the hybridization of an mRNA, a cDNA molecule, or fragments thereof, to a DNA template from which it is originated or derived. Many DNA samples are used to construct an array.
  • An array experiment makes use of common assay systems such as microplates or standard blotting membranes. The sample spot sizes are typically less than 200 microns in diameter and the array usually contains thousands of spots.
  • spotted samples known as probes are immobilized on a substrate (e.g., a microscope glass slides, silicon chips, nylon membrane).
  • the spots can be DNA, cDNA, or oligonucleotides. These are used to determine complementary binding of the unknown sequences thus allowing parallel analysis for gene expression and gene discovery.
  • An experiment with a single DNA chip can provide information on thousands of genes simultaneously.
  • An orderly arrangement of the probes on the support is important as the location of each spot on the array is used for the identification of a gene.
  • the amount of mRNA bound to each site on the array indicates the expression level of the various genes that are included on the array.
  • cDNA microarrays are made with long double-stranded DNA molecules generated by enzymatic reactions such as PCR (Schena.M. et al., Science, 270 : 467-470 (1995)), while oligonucleotide microarrays employ oligonucleotide probes spotted by either robotic deposition or in situ synthesis on a substrate
  • the arrays are generally designed to include oligonucleotide probes targeting regions of low sequence similarity.
  • the nucleic acid arrays can include two, three, four five, six, seven, eight, nine, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, or 53 polynucleotides that hybridize to each of the two, three, four five, six, seven, eight, nine, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, or 53 genes respectively listed in Table 1, or any nucleic acid derived therefrom (e.g., mRNA, cDNA, or fragments of mRNA or cDNA).
  • nucleic acid derived therefrom e.g., mRNA, cDNA, or fragments
  • the nucleic acid arrays can include at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least 10, at least 11, at least 12, at least 15, at least 20, at least 22, at least 24, at least 25, at least 26, at least 27, at least 28, at least 29, at least 30, at least 31, at least 32, at least 33, at least 34, at least 35, at least 36, at least 37, at least 38, at least 39, at least 40, at least 41, at least 42, at least 43, at least 44, at least 45, at least 46, at least 47, at least 48, at least 49, at least 50, at least 51, or at least 52 polynucleotides that hybridize to each of at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least 10, at least 11, at least 12, at least 15, at least 20, at least 22, at least 24, at least 25, at least 26, at least 27, at least 28, at least 29, at least 30, at least 31,
  • a polynucleotide of the array can include coding sequence or non-coding sequence (e.g., exons, introns, or 5' or 3' regulatory sequences), e.g., of a gene depicted in Table 1.
  • the polynucleotide can include a sequence of the sense strand or the anti- sense strand of the coding sequence of a gene depicted in Table 1.
  • the polynucleotide can also be single or double-stranded and of variable length.
  • the length of one strand of a polynucleotide that hybridizes to a gene can be six nucleotides, seven nucleotides, eight nucleotides, nine nucleotides, 10 nucleotides, 11 nucleotides, 12 nucleotides, 13 nucleotides, 14 nucleotides, 15 nucleotides, 20 nucleotides, 25 nucleotides, 30 nucleotides, 35 nucleotides, 40 nucleotides, 45 nucleotides, 50 nucleotides, 55 nucleotides, 60 nucleotides, 65 nucleotides, 70 nucleotides, 75 nucleotides, 80 nucleotides, 85 nucleotides, 90 nucleot
  • the length of one strand of a polynucleotide that hybridizes to a gene can be about six nucleotides, about seven nucleotides, about eight nucleotides, about nine nucleotides, about 10 nucleotides, about 12 nucleotides, about 13 nucleotides, about 14 nucleotides, about 15 nucleotides, about 20 nucleotides, about 25 nucleotides, about 30 nucleotides, about 35 nucleotides, about 40 nucleotides, about 50 nucleotides, about 75 nucleotides, about 100 nucleotides, about 150, about 155, about 160, about 165, about 170, about 175, about 180, about 190, or about 200 or more nucleotides in
  • the probe is between 25 and 35 nucleotides, between 35 and 45 nucleotides, between 65 and 75 nucleotides, between 25 and 200 nucleotides, between 50 and 175 nucleotides, between 75 and 165 nucleotides, between 100 and 200, nucleotides, between 125 and 250 nucleotides, or between 125 and 1000 nucleotides in length.
  • a longer polynucleotide often allows for higher stringency hybridization and wash conditions.
  • the polynucleotide can be DNA, RNA, modified DNA or RNA, or a hybrid, where the nucleic acid contains any combination of deoxyribo- and ribo-nucleotides, and any combination of uracil, adenine, thymine, cytosine and guanine, as well as other bases such as inosine, xanthine, and hypoxanthine.
  • the polynucleotide arrays can be attached to a solid support, e.g., a porous or non-porous material that is insoluble.
  • the substrate can be associated with the support in variety of ways, e.g., covalently or non-covalently bound.
  • a support can be composed of a natural or synthetic material, an organic or inorganic material.
  • the composition of the solid support on which the polynucleotide sequences are attached generally depend on the method of attachment (e.g., covalent attachment).
  • Suitable solid supports include, but are not limited to, plastics, resins, polysaccharides, silica or silica-based materials, functionalized glass, modified silicon, carbon, metals, inorganic glasses, membranes, nylon, natural fibers such as silk, wool and cotton, or polymers.
  • the material comprising the solid support can .have reactive groups such as carboxy, amino, or hydroxyl groups, which are used for attachment of the polynucleotides.
  • Polymeric solid supports can include, e.g., polystyrene, polyethylene glycol tetraphthalate, polyvinyl acetate, polyvinyl chloride, polyvinyl pyrrolidone, polyacrylonitrile, polymethyl methacrylate, polytetrafluoroethylene, butyl rubber, styrenebutadiene rubber, natural rubber, polyethylene, polypropylene, (poly)tetrafluoroethylene, (poly)vinylidenefluoride, polycarbonate, or polymethylpentene (see, e.g., U.S. Patent No. 5,427,779, the disclosure of which is hereby incorporated by reference in its entirety).
  • the polynucleotide sequences can be attached to the solid support without the use of such functional groups.
  • Each polynucleotide (of a plurality of polynucleotides) on an array can be immobilized at predetermined positions such that each polynucleotide can be identified by its position.
  • Exemplary polynucleotide arrays for use in the methods and kits described herein are described in, e.g., U.S. Patent Nos. 6,197,599; 5,902,723; and 5,871,928; the disclosures of each of which are incorporated herein by reference in their entirety).
  • the arrays can contain multiple nucleic acids derived from a single gene. These multiple nucleic acids may be from one or more regions of the gene of interest.
  • the array of polynucleotides can have less than 100,000 (e.g., less than 90,000; less than 80,000; less than 70,000; less than 60,000; less than 50,000; less than 40,000; less than 30,000; less than 20,000; less than 15,000; less than 10,000; less than 5,000; less than 4,000.” less than 3,000; less than 2,000; less than 1,500; less than 1,000; less than 750; less than 500, less than 200, less than 100, or less than 50) different polynucleotides.
  • the polynucleotide arrays s can also be conjugated to microscopic beads or solid support particles.
  • suitable solid support particles are known in the art and illustratively include, e.g., particles, such as Luminex®-type encoded particles, magnetic particles, and glass particles.
  • Exemplary particles that can be used can have a variety of sizes and physical properties.
  • Particles can be selected to have a variety of properties useful for particular experimental formats. For example, particles can be selected that remain suspended in a solution of desired viscosity or to readily precipitate in a solution of desired viscosity. Particles can be selected for ease of separation from sample constituents, for example, by including purification tags for separation with a suitable tag-binding material, paramagnetic properties for magnetic separation, and the like.
  • kits include that can be used to identify or detect any of the biomarkers of Table 1 or thei expression or expression levels.
  • the kits include any of the nucleic acid arrays described herein.
  • the kits can, optionally, contain instructions for detecting and or measuring the level of one or more genes in a biological sample.
  • kits can optionally include, e.g., a control biological sample or control labeled-amplicon set containing known amounts of one or more amplicons recognized by nucleic acid probes of the array.
  • the control can be an insert (e.g., a paper insert or electronic medium such as a CD, DVD, or floppy disk) containing expression level ranges of one or more genes predictive of a response to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • kits can include one or more reagents for processing a biological sample.
  • a kit can include reagents for isolating mRNA from a biological sample and/or reagents for converting the isolated mRNA to cDNA (e.g., reverse transcriptase, primers for reverse transcription or PCR amplification, or dNTPs).
  • cDNA e.g., reverse transcriptase, primers for reverse transcription or PCR amplification, or dNTPs.
  • kits can also, optionally, contain one or more reagents for detectably labeling an mRNA, an mRNA amplicon, genomic DNA or DNA amplicon, which reagents can include, e.g., an enzyme such as a Klenow fragment of DNA polymerase, T4 polynucleotide kinase, one or more detectablylabeled dNTPs, or detectablylabeled gamma phosphate ATP (e.g., 33 P-ATP).
  • an enzyme such as a Klenow fragment of DNA polymerase, T4 polynucleotide kinase, one or more detectablylabeled dNTPs, or detectablylabeled gamma phosphate ATP (e.g., 33 P-ATP).
  • kits can include a software package for analyzing the results of, e.g., a microarray analysis or expression profile.
  • kits can also include one or more antibodies for detecting the protein expression of any of the genes described herein.
  • a kit can include (or in some cases consist of) a plurality of antibodies capable of specifically binding to one or more proteins encoded by any of the genes depicted in Table 1 and optionally, instructions for detecting the one or more proteins and/or a detection antibody comprising a detectablylabeled. antibody that is capable of binding to at least one antibody of the plurality.
  • kits can include antibodies that recognize one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, or 52 proteins encoded by genes depicted in Table 1.
  • kits described herein can also, optionally, include instructions for administering a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), where the expression level of one or more genes detectable by the array predicts that a subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • the kits can contain instructions for administering a variety of non lenvatinib therapies where the expression level of one or more genes detectable by the array predicts that a subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • Suitable biological samples for the methods described herein include any biological fluid, cell, tissue, or fraction thereof, which includes analyte biomolecules of interest such as nucleic acid (e.g., DNA or mRNA) or protein.
  • a biological sample can be, for example, a specimen obtained from a subject (e.g., a mammal such as a human) or can be derived from such a subject.
  • a sample can be a tissue section obtained by biopsy, or cells that are placed in or adapted to tissue culture.
  • a biological sample can also be a biological fluid such as urine, blood, plasma, serum, saliva, semen, sputum, cerebral spinal fluid, tears, or mucus, or such a sample absorbed onto a paper or polymer substrate.
  • a biological sample can also include a skin sample, a tumor sample, circulating tumor cells, and circulating DNA.
  • the biological sample is a tumor cell(s) or a cell(s) obtained from a region of the subject suspected of containing a tumor or a pre-cancerous lesion.
  • a biological sample can be further fractionated, if desired, to a fraction containing particular cell types.
  • a blood sample can be fractionated into serum or into fractions containing particular types of blood cells such as red blood cells or white blood cells (leukocytes).
  • a sample can be a combination of samples from a subject such as a combination of a tissue and fluid sample.
  • the biological samples can be obtained from a subject, e.g., a subject having, suspected of having, or at risk of developing, a cancer. Any suitable methods for obtaining the biological samples can be employed, although exemplary methods include, e.g., phlebotomy, swab (e.g., buccal swab), or fine needle aspirate biopsy procedure.
  • exemplary methods include, e.g., phlebotomy, swab (e.g., buccal swab), or fine needle aspirate biopsy procedure.
  • tissues susceptible to fine needle aspiration include lymph node, lung, thyroid, breast, skin, and liver.
  • Samples can also be collected, e.g., by microdissection (e.g., laser capture microdissection (LCM) or laser microdissection (LMD)), bladder wash, smear (PAP smear), or ductal lavage.
  • microdissection e.g., laser capture microdissection (LCM) or laser microdissection (LMD)
  • LCM laser capture microdissection
  • LMD laser microdissection
  • bladder wash e.g., smear (PAP smear)
  • smear smear
  • ductal lavage e.g., ductal lavage.
  • a biological sample can be further contacted with one or more additional agents such as appropriate buffers and/or inhibitors, including nuclease, protease and phosphatase inhibitors, which preserve or minimize changes in the molecules (e.g., nucleic acids or proteins) in the sample.
  • additional agents such as appropriate buffers and/or inhibitors, including nuclease, protease and phosphatase inhibitors, which preserve or minimize changes in the molecules (e.g., nucleic acids or proteins) in the sample.
  • Such inhibitors include, for example, chelators such as ethylenediamine tetraacetic acid (EDTA), ethylene glycol bis(P-aminoethyl ether) ⁇ , ⁇ , ⁇ , ⁇ -tetraacetic acid (EGTA), protease inhibitors such as phenylmethylsulfonyl fluoride (PMSF), aprotinin, leupeptin, antipain and the like, and phosphatase inhibitors such as phosphate, sodium fluoride, vanadate and the like.
  • chelators such as ethylenediamine tetraacetic acid (EDTA), ethylene glycol bis(P-aminoethyl ether) ⁇ , ⁇ , ⁇ , ⁇ -tetraacetic acid (EGTA), protease inhibitors such as phenylmethylsulfonyl fluoride (PMSF), aprotinin, leupeptin, antipain and the like, and phosphatase inhibitors such as phosphat
  • a sample also can be processed to eliminate or minimize the presence of interfering substances.
  • a biological sample can be fractionated or purified to remove one or more materials that are not of interest. Methods of fractionating or purifying a biological sample include, but are not limited to, chromatographic methods such as liquid chromatography, ion-exchange
  • a sample can be in a variety of physical states.
  • a sample can be a liquid or solid, can be dissolved or suspended in a liquid, can be in an emulsion or gel, or can be absorbed onto a material.
  • This disclosure also provides methods of predicting whether a subject will respond, or have reduced or no response, to treatment with lenvatinib or a
  • the methods involve assessing the expression level of one or more genes listed in Table 1 in a biological sample from a subject. If the expression level of certain genes in the biological sample is elevated or decreased (compared to a control), it is possible to determine whether the subject would benefit from treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • a pharmaceutically acceptable salt thereof e.g., lenvatinib mesylate
  • an expression level of these genes that is decreased or at a level that is about the same as (at least 85% but less than 100% of) a control is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • an elevated expression level as compared to a control, of any one or more of the following genes: TNKS, TARBP2, TTLL4, CHKA, PSPH, CPM, MDM1, HIPK2, DSCCl, STAG3L4, MSRB2, GDPD5, GJB2, ARRDC4, COPS7B, NEIL2, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDC1/PDXDC2, ANKRD13D, NAPEPLD, C70RF and IL22RA2 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), or will have a reduced responsiveness to a therapy comprising lenvatinib or a
  • an expression level of these genes that is decreased or at a level that is about the same as (at least 85% but less than 100% of) a control is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • the methods described herein can involve, assessing the expression level (e.g., mRNA or protein expression level) of one or more genes (e.g., one or more genes depicted in Table l), wherein the expression level of one or more of the genes predicts the response of a' subject. to treatment comprising a lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • “Assessing” can include, e.g., comparing the expression of one or more genes in a test biological sample with a known or a control expression level (e.g., in a reference biological sample) of the particular gene(s) of interest.
  • the expression level of one or more genes in a test biological sample can be compared to the corresponding expression levels in a subject who has responded or failed to respond to lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), or an average expression level of multiple (e.g., two, three, four, five, six, seven, eight, nine, 10, 15, 20, 25, 30, 35, or 40 or more) subjects, of the same species, who have responded or have failed to respond to lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • lenvatinib mesylate e.g., lenvatinib mesylate
  • Assessing can also include determining if the expression level of one or more genes (e.g., one or more genes as depicted in Table l) falls within a range of values predetermined as predictive of responsiveness or non-responsiveness of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • assessing can be, or include, determining if the expression of one or more genes (e.g., one or more of the genes depicted in Table l) falls above or below a predetermined cut-off value.
  • a cut-off value is typically an expression level of a gene, or ratio of the expression level of a gene with the expression level of another gene, above or below which is considered predictive of responsiveness or non- responsiveness of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • a reference expression level of a gene e.g., a gene depicted in Table 1 is identified as a cut-off value, above or below of which is predictive of responsiveness or non-responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • a lenvatinib e.g., lenvatinib mesylate
  • therapy response profile can be interpreted as a whole (the expression level of all genes in the profile), in parts (certain collections or groups of genes (e.g., 8 or 24 genes) within the profile), or on a gene-by-gene basis.
  • cut-off values are not absolute in that clinical correlations can still remain significant over a range of values on either side of the cutoff; however, it is possible to select an optimal cut-off value (e.g. varying H-scores) of expression levels of genes for a particular sample types. Cut-off values determined for use in the methods described herein can be compared with, e.g., published ranges of expression levels but can be individualized to the methodology used and patient population. It is understood that improvements in optimal cut-off values could be determined depending on the sophistication of statistical methods used and on the number and source of samples used to determine reference level values for the different genes and sample types. Therefore, established cut-off values can be adjusted up or down, on the basis of periodic re-evaluations or changes in methodology or population distribution.
  • the reference expression level of one or more genes can be determined by a variety of methods.
  • the reference level can be determined by comparison of the expression level of a gene of interest in, e.g., populations of subjects (e.g., patients) that are responsive to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) or not responsive to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
  • This can be accomplished, for example, by histogram analysis, in which an entire cohort of patients are graphically presented, wherein a first axis represents the expression level of a gene and a second axis represents the number of subjects in the cohort whose sample contain one or more expression levels at a given amount.
  • the reference level can be a single number, equally applicable to every subject, or the reference level can vary, according to specific subpopulations of subjects. For example, older subjects can have a different reference level than younger subjects for the same metabolic disorder.
  • a subject with more advanced disease e.g., a more advanced form of a disease treatable by lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate)
  • lenvatinib mesylate can have a different reference value than one with a milder form of the disease.
  • a medical practitioner e.g., a doctor
  • the appropriate therapeutic modality for the subject e.g., lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) or a hon-lenvatinib therapy, respectively.
  • Selecting a therapy for a subject can be, e.g.: (i) writing a prescription for a medicament; (ii) giving (but not necessarily administering) a medicament to a subject (e.g., handing a sample of a prescription medication to a patient while the patient is at the physician's office); (iii) communication (verbal, written (other than a prescription), or electronic (email, post to a secure site)) to the patient of the suggested or recommended therapeutic modality (e.g., lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) or a non-lenvatinib therapy); or (iv) identifying a suitable therapeutic modality for ; a subject and disseminating the information to other medical personnel, e.g., by way of patient record.
  • the latter (iv) can be useful in a case where, e.g., more than one therapeutic agent are to be administered to a patient by
  • the methods described herein can also be used to generate a lenvatinib (e.g., lenvatinib mesylate) therapy response profile for a subject.
  • the profile can include information that indicates whether one or more genes, such as one or more genes depicted in Table 1, are expressed (e.g., yes or no) and/or information that indicates the expression level of one or more genes (e.g., one or more genes depicted in Table 1).
  • a lenvatinib therapy response profile can include the expression level of one or more additional genes and/or other proteomic markers, serum markers (e.g., lactate dehydrogenase dosage), or clinical markers.
  • the response profiles described herein can contain information on the expression or expression level of at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least 10, at least 11, at least 12, at least 13, at least 14, at least 15, at least 16, at least 17, at least 18, at least 19, at least 20, at least 21, at least 22, at least 23, at least 24, or at least 25 genes listed in Table 1.
  • the resultant information (lenvatinib therapy response profile) can be used for predicting the response of a subject (e.g., a human patient) to a treatment comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • the response profiles can be used in predicting the response of a subject to a variety of therapies and/or a variety of disease states since, e.g., the expression levels of one or more of the genes (e.g., one or more of the genes depicted in Table l) examined can be indicative of such responses or disorders, whether or not physiologic or behavioral symptoms of the disorder have become apparent.
  • Responsiveness (and, conversely, non-responsiveness) of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) can be classified in several ways and classification is dependent on the subject's disease (e.g., skin cancer, a liver cancer, a lung cancer, a brain tumor, a thyroid cancer, an ovarian cancer, a renal cancer, an endometrial cancer, or any other of the diseases treatable by therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate)), the severity of the disease, and the particular medicament the subject is administered.
  • the subject's disease e.g., skin cancer, a liver cancer, a lung cancer, a brain tumor, a thyroid cancer, an ovarian cancer, a renal cancer, an endometrial cancer, or any other of the diseases treatable by therapy comprising lenvatinib or
  • Responsiveness of a subject e.g., a human
  • a cancer can be classified based on one or more of a number of objective clinical indicia such as, but not limited to, tumor size, Clinical Benefit (CB), Progression Free Survival (PFS), Complete Response (CR), Overall Survival (OS), and Time-to-Progression (TTP).
  • CB Clinical Benefit
  • PFS Progression Free Survival
  • CR Complete Response
  • OS Overall Survival
  • TTP Time-to-Progression
  • Chronic benefit refers to having one of the following statuses— Complete Response (CR), Partial Response (PR); or Stable Disease (SD) with 6 months or more progression free survival (PFS).
  • Complete Response means complete disappearance of all target lesions.
  • Partial Response means at least 30% decrease in the sum of the longest diameter (LD) of target lesions, taking as reference the baseline summed LD.
  • Progressive Disease means at least 20% increase in the sum of the LD of target lesions, taking as reference the smallest summed LD recorded since the treatment started, or the appearance of one or more new lesions.
  • Stable Disease means neither sufficient shrinkage of the target lesions to qualify for PR nor sufficient increase to qualify for progressive disease (PD), taking as reference the smallest summed LD since the treatment started.
  • PFS progression Free Survival
  • Tumor shrinkage means percent change of sum of diameters of target lesions, taking as reference the baseline sum diameters.
  • Time to Progression is defined as the time from randomization until objective tumor progression.
  • Randomization means randomization of a patient into a test group or a control group when therapy plan for a patient is determined.
  • OS Overall Survival
  • a lenvatinib (e.g., lenvatinib mesylate) response profile can be in electronic form (e.g., an electronic patient record stored on a computer or other electronic (computer-readable) media such as a DVD, CD, or floppy disk) or written form.
  • the lenvatinib (e.g., lenvatinib mesylate) response profile can also include information for several (e.g., two, three, four, five, 10, 20, 30, 50, or 100 or more) subjects (e.g., human patients).
  • Such multi-subject response profiles can be used, e.g., in analyses (e.g., statistical analyses) of particular characteristics of subject cohorts.
  • the methods disclosed herein enable the assessment of a subject for responsiveness and non-responsiveness to lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • a subject who is likely to respond to lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) can be administered lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), whereas subjects who are unlikely to respond to lenvatinib or a
  • pharmaceutically acceptable salt thereof can be administered a non-lenvatinib therapy.
  • the methods of this disclosure also enable the classification of subjects into groups of subjects that are likely to benefit, and groups of subjects that are unlikely to benefit, from treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • lenvatinib or a pharmaceutically acceptable salt thereof e.g., lenvatinib mesylate.
  • the ability to select such subjects from a pool of subjects who are being considered for treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) is beneficial for effective treatment and reduction of adverse side effects of treatment.
  • Lenvatinib or a pharmaceutically acceptable salt thereof shows potent anti-tumor effects in xenograft models of various tumors by inhibiting angiogenesis.
  • the subjects who are considered for treatment with lenvatinib or a pharmaceutically acceptable salt thereof include, but are not limited to, subjects having, suspected of having, or likely to develop a skin cancer (e.g., melanoma), a liver cancer (e.g., hepatocellular carcinoma), a lung cancer (e.g., a non-small lung cancer), a brain tumor (e.g., a glioma), a thyroid cancer, an ovarian cancer, a renal cancer (e.g., renal cell carcinoma), or an endometrial cancer.
  • a skin cancer e.g., melanoma
  • a liver cancer e.g., hepatocellular carcinoma
  • a lung cancer e.g., a non-small lung cancer
  • a brain tumor e.g.,
  • a skin cancer is the uncontrolled growth of abnormal skin cells. If left unchecked, these cancer cells can spread from the skin into other tissues and organs.
  • skin cancer There are different types of skin cancer such as basal cell carcinoma (the most common skin cancer), squamous cell carcinoma, Kaposi's sarcoma, Merkel cell carcinoma, cutaneous lymphoma, and melanoma.
  • Melanoma is a malignant tumor of melanocytes that is less common than other skin cancers, but is more dangerous and causes the majority of skin cancer-related deaths.
  • the subject to be treated with lenvatinib or a pharmaceutically acceptable salt thereof e.g., lenvatinib mesylate
  • lenvatinib mesylate has, is suspected of having, or is likely to develop a melanoma.
  • the subject can then be administered an effective amount of the lenvatinib compound (e.g., lenvatinib mesylate).
  • an effective amount of the compound can suitably be determined by a health care practitioner taking into account, for example, the characteristics of the patient (age, sex, weight, etc.), the progression of the disease, and prior exposure to the drug. If the subject is unlikely or less likely to respond to a therapy comprising lenvatinib or a
  • lenvatinib mesylate a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) (based on the determination of expression or expression levels of the biomarkers in Table 3)
  • the subject can then be administered a therapy that does not comprise lenvatinib.
  • therapies include, but are not limited to, dacarbazine, temozolomide, ipilimumab, interleukin-2, interferon, inhibitors of BRAF kinase, and "standard of care" treatment (i.e., prevailing standard of care as determined by the health care practitioner or as specified in the clinical study) such as investigational drugs and chemotherapy.
  • a biological sample used in a methods described herein can be obtained from a subject (e.g., a human) of any age, including a child, an adolescent, or an adult, such as an adult having, or suspected of having, a disease (e.g., melanoma) treatable by lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • the methods can also be applied to individuals at risk of developing a cancer treatable by lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • Such individuals include those who have (i) a family history of (a genetic predisposition for) such disorders or Gi) one or more risk factors for developing such disorders.
  • a medical practitioner e.g., a doctor
  • can administer the appropriate therapeutic modality to the subject e.g., a lenvatinib (e.g., lenvatinib mesylate) therapy or a non-lenvatinib therapy, respectively.
  • a lenvatinib e.g., lenvatinib mesylate
  • a non-lenvatinib therapy e.g., lenvatinib mesylate
  • Methods of administering lenvatinib and non-lenvatinib therapies are well known in the art.
  • any therapy described herein can include one or more additional therapeutic agents. That is, any therapy described herein can be co ⁇ administered (administered in combination) with one or more additional therapeutic agents such as, but not limited to, dacarbazine (DTIC), temozolomide (TMZ), carboplatin, paclitaxel, ipilimuma3 ⁇ 4 (Yervoy), everolimus, gemcitabine, interleukin-2, and interferon.
  • DTIC dacarbazine
  • TMZ temozolomide
  • carboplatin paclitaxel
  • ipilimuma3 ⁇ 4 Yervoy
  • everolimus gemcitabine
  • gemcitabine interleukin-2, and interferon.
  • any therapy described herein can include one or more agents for treating, for example, pain, nausea, and/or one or more side-effects of a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) or a non-lenvatinib agent.
  • a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) or a non-lenvatinib agent.
  • Combination therapies e.g., co-administration of a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) or a non-lenvatinib agent and one or more additional therapeutic agents
  • a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) or a non-lenvatinib agent and one or more additional therapeutic agents
  • lenvatinib or a pharmaceutically acceptable salt thereof e.g., lenvatinib mesylate
  • one or more additional therapeutic agents can be administered at the same time or a lenvatinib compound (e.g., lenvatinib mesylate) can be administered first in time and the one or more additional therapeutic agents administered second in time.
  • the one or more additional therapeutic agents can be administered first in time and lenvatinib or a
  • pharmaceutically acceptable salt thereof e.g., lenvatinib mesylate administered second in time.
  • the therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof can replace or augment a previously or currently administered therapy.
  • administration of the one non lenvatinib therapies can cease or diminish, e.g., be administered at lower levels.
  • Administration of the previous therapy can be maintained while the therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) is administered.
  • a previous therapy can be maintained until the level of the therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) reaches a level sufficient to provide a therapeutic effect.
  • the subject can be monitored for a first pre-selected result, e.g., an improvement in one or more symptoms of a disease treatable by a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), e.g., melanoma or any other diseases treatable by therapy comprising a lenvatinib.
  • a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof e.g., lenvatinib mesylate
  • treatment with the therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof e.g., lenvatinib mesylate
  • the subject can then be monitored for a second pre-selected result after treatment with the therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) is halted, e.g., a worsening (e.g., a worsening of a symptom) of a disease treatable by a lenvatinib (e.g., lenvatinib mesylate).
  • a worsening e.g., a worsening of a symptom
  • administering comprising lenvatinib or a pharmaceutically ' -acceptable salt thereof (e.g., lenvatinib mesylate) to the subject can be reinstated or increased, or administration of the first therapy can be reinstated, or the subject can be administered both a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), or an increased amount of a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), and the first therapeutic regimen.
  • a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof e.g., lenvatinib mesylate
  • an increased amount of a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof e.g., lenvatinib mesylate
  • Example l Gene Expression Profiling of Melanoma Tumor Biopsies to Identify a Response Signature to the Multi-RTK Inhibitor.
  • RNA quality metrics For blocks with passing RNA quality metrics and those determined to have adequate viable tumor on which to focus collection, slides were stained with hematoxylin and eosin (H&E) and LCM of an estimated 5,000 neoplastic cells was performed with catapulting into' RLT buffer with BME. Collections were restricted to a 30 minute period following staining to maintain good quality RNA. Before and after images were taken to document the collection and were reviewed by a pathologist as a quality control measure.
  • H&E hematoxylin and eosin
  • RNA isolation Following RNA isolation, the quantity and purity of the RNA was determined by absorbance at 260 nm and 260/280 absorbance ratio respectively. Each of the total RNA preparations was individually assessed for RNA quality based on the 28S/18S ratio and RIN measured on an Bioanalyzer (Agilent) system using the RNA 6000 Nano LabChip Kit.
  • Amplified ss-cDNA was created using WT vation Pico RNA Amplification system V2 (Cat# 3300, NuGen Corp).
  • the cDNA was purified using magnetic beads (Agencourt RNAClean, Beckman).
  • the quantity and purity of the cDNA was determined by absorbance at 260nm and 260nm 280nm absorbance ratio respectively.
  • the quality of the cDNA was evaluated by assessing size distribution using
  • the cDNA was fragmented and biotin-labeled using FL-OvationTM cDNA Biotin module (NuGEN, order no. 4200) and 4.0 to 4.8 ⁇ loaded onto individual human U133 plus 2.0 GeneChips (Affymetrix) as the hybridization cocktail (200 ⁇ ).
  • FL-OvationTM cDNA Biotin module NuGEN, order no. 4200
  • 4.0 to 4.8 ⁇ loaded onto individual human U133 plus 2.0 GeneChips (Affymetrix) as the hybridization cocktail (200 ⁇ ).
  • microarrays were hybridized at 45°C for 16 ⁇ 24 hours and washed and stained on an FS450 fluidics station according to manufacturer recommendations (Affymetrix®, FS450_0004). The microarrays were scanned on a GeneChip Scanner 3000
  • GeneChip were globally normalized and scaled to an average signal intensity of 100.
  • residual slide material was used for two cases to evaluate the feasibility of collecting endothelial cells within tumor regions as identified by immunostaining for CD31.
  • tumor cells highlighted by a hematoxylin counterstain were captured into 30 mM Tris- HC1, pH 7.5, 150 mM NaCl, 0.1% Triton X- 100, 0.1% SDS buffer.
  • Vascular collections were suspended after the two cases as it became apparent such processing would deplete the material and would likely prove inadequate for most donors.
  • the collection of up to an estimated 30,000 tumor cells into the above buffer was performed for all cases with available slides over a 1 hour period following standard H&E staining.
  • the genomic data was analyzed using Student's T-test based on: clinical benefit (CB); regression analysis for the continuous measure of tumor shrinkage (TS); and by Cox propd tional regression based on progression free survival (PFS).
  • CB Clinical benefit
  • CB refers to having one of the following statuses - Complete Response (CR), Partial Response (PR); or Stable Disease (SD) with 6 months or more progression free survival (PFS).
  • CRS progression free survival
  • Complete Response means complete disappearance of all target lesions.
  • Partial Response means at least 30% decrease in the sum of the longest diameter (LD) of target lesions, taking as reference the baseline summed LD.
  • LD longest diameter
  • PD 'Trogressive Disease
  • Stable Disease means neither sufficient shrinkage of the target lesions to qualify for PR nor sufficient increase to qualify for progressive disease (PD), taking as reference the smallest summed LD since the treatment started.
  • PFS Progression Free Survival
  • Tumor shrinkage means percent change of sum of diameters of target lesions, taking as reference the baseline sum diameters.
  • the above analysis identified genes encoding elements of the target receptor tyrosine kinase signaling pathways.
  • biomarkers 13 of the identified biomarkers were associated with improved clinical benefit, tumor shrinkage, and progression free survival.
  • the criteria used to select genes as biomarkers in this category are as follows:
  • CB (l) average expression level is 100 or more for either CB or non CB
  • Table 4 provides a listing of genes that fall within this category.
  • This example describes a data and supercomputer driven analysis strategy for predicting gene expression measures that are critical for maximal tumor shrinkage (MTS) and progression free survival (PFS).
  • MTS maximal tumor shrinkage
  • PFS progression free survival
  • the GNS Healthcare REFSTM Reverse Engineering and Forward Simulation
  • REFSTM simulation analyses identified four candidate marker genes for MTS and six candidate marker genes for PFS.
  • P(Xi, ..., Xn; ⁇ ) a joint multivariate probability distribution function
  • full specification of such joint probability distributions requires a large number of parameters ⁇ .
  • Such a global joint probability distribution admits the following factorization into a product of local conditional probability distributions 1
  • each variable X ' is independent of its nondescendants given its &parents Yji,..., 3 ⁇ 4K(local Markov condition) and 0/are parameters for Pi.
  • the variables are simply a subset of the Xs, we use the ⁇ notation to indicate they are inputs to the conditional probability.
  • This approach yields a framework where each particular factorization and choice of parameters is a distinct probabilistic model Moi the structure of the process that created the observed data (Pearl, J., Models, reasoning and inference, (Cambridge University Press, Cambridge, New York, Melbourne, Madrid, Cape Town, Singapore, Sao Paulo, 2000)).
  • Each factorization of P(Xi, AW into model M(as in Eq. l) is represented by a unique Directed Acyclic Graph (DAG) Cwith a vertex for each .A? and directed edges between vertices to represent the dependencies between variables embedded in the local conditional distributions, Pif-Xi/ Yji, YjKi).
  • DAG Directed Acyclic Graph
  • l also specifies distributions for all 6>/the parameters of local conditional distributions Pi.
  • Subgraphs of G consisting of a vertex and a set of all its incoming edges, and associated local conditional distributions and parameters ⁇ , are referred to here as "network fragments".
  • the parameters ⁇ , 9ji, ..., 6jKj can be thought of as adjusted to best fit the data in the Maximum Likelihood Estimation (MLE) sense.
  • MLE Maximum Likelihood Estimation
  • the likelihood function gives the posterior distribution of the parameter values about the MLE point.
  • P(D) is the probability of D
  • P(M) is the prior probability of the model
  • P(D I M) J P(D I ⁇ ( ⁇ )) ⁇ ⁇ I M)d® (5) is the integral of the data likelihood over the prior distribution of parameters ⁇ .
  • P(D) is constant, we factor P(M ID) in Eq. 4 into the product of integrals over the parameters local to each network fragment Mi Eq. 4 now becomes
  • Model Intervention Simulations - Stochastic simulation of a probabilistic model M allows predictions about the distribution of a variable Xito be made under different conditions.
  • the conditions can be interventions with variables in the model and/or different values of inputs to the model.
  • a simulation routine iteratively sweeps the network and generates samples of variables whose parents have already acquired a value in previous iterations until all variables have values. One full sweep produces one sample (one vector of values of all variables). Interventions such as a knockdown of gene transcript expression level variables are done by removal of the network fragment from M that outputs to the variable and the network is swept as described previously.
  • Modeling Strategy and Survival Analysis - Transcripts as well as pharmacokinetic measures are used to predict phenotypes (maximal tumor shrinkage and progression free survival) in this study.
  • An ensemble of 1000 networks is used to capture the statistical sample of models consistent with the data.
  • a survival regression analysis (R/survival package) is used to model progression free survival time (days).
  • the microarray data set was normalized using the PLIER (Probe Logarithm Intensity Error) algorithm developed and released by Affymetrix (Team, A.T. Affymetrix technical notes : Guide to Probe Logarithmic Intensity Error (PLIER) estimation. (Accessed 11 March 2011, Available- ' http://www.affymetrix.com/support/technical technotes/pUer_technote.pdf)).
  • This normalization technique has outperformed previously developed methods in the Affycomp II competition in detecting differential gene expression as well as quantitation.
  • PK Pharmacokinetics Analysis -' The period during which a patient takes E7080 is artificially divided into different Cycles for ease of evaluation and tracking.
  • each Cycle is 28 days (4 weeks) so Day 1-28 is cycle l; Day 29 is Day 1 of Cycle 2; and Day 57 is the Day 1 of Cycle 3.
  • Blood samples were collected for PK analysis on Day 1 of the first cycle immediately prior to the first dose of E7080, and at 0.25, 0.5, 1, 1.5, 2, 2.5, 3, 4, 6 and 24 hours following the first dose of E7080 (single dose PK).
  • MTS Maximal Tumor Shrinkage
  • the REFSTM predictive framework involves three phases. In the first phase, the data are processed so that probabilistic modeling methods can be applied to it (See Methods). In the second phase, we estimate an ensemble of network models based on data from the experiment. In the third phase we use forward simulation of networks in the ensemble to generate predictions of effects of modulating genes to phenotypic endpoints. The process is summarized in Figure 1. Summaries of data processing and the mathematical assessment of the quality of the model generated by the framework are provided in the Methods section.
  • the model was built using all 54,675 gene expression values, pharmacokinetic and phenotypic measurements from melanoma patients in Phase I clinical trial. More than 7 x 10 9 (billion) network fragments are enumerated and 40,000 best network fragments are used by the parallel sampler to build an ensemble model of networks to predict maximal tumor shrinkage (MTS).
  • MTS maximal tumor shrinkage
  • R survival package R survival package
  • PFS progression free survival
  • Model interventional strategy and identification of candidate marker genes for maximal tumor shrinkage and progression free survival can simultaneously query all types of relationship models that exist. For example, genes that are significant regulators, or candidate marker genes, of phenotypes can be identified via in silico simulations of the REFSTM model. To identify candidate marker genes, systematic in silico simulations of 10-fold knockdown of all genes connected to phenotypes were completed to provide quantitative predictions of how the modulation of a particular gene expression measure would affect maximal tumor shrinkage or progression free survival.
  • Simulation analysis predicts four genes as candidate marker genes for maximal tumor shrinkage - With REFSTM simulation, four genes are identified as candidate marker genes for maximal tumor shrinkage.
  • the four genes are TARBP2, RAP2A, CACNA1I, and a hypothetical gene from chromosome 7 (C70RF).
  • the effects of how candidate marker genes associate with maximal tumor shrinkage are predicted via network simulation and shown in Figure 3. For example, lower level of TARBP2 (red distribution) is associated with more tumor shrinkage ( Figure 3B) and on the contrary lower level of RAP2A is associated with less tumor shrinkage ( Figure 3C).
  • RNA binding protein2 is a protein related to DICERl and has been recently identified to be required for processing of miRNAs to regulate tumorigenesis (Melo, S.A. et al. A TARBP2 mutation in human cancer impairs microRNA processing and DICERl function. Nat Genet 41, 365-70 (2009)).
  • MAP kinase signaling pathway plays important roles in cell growth, differentiation, and survival to be involved in cancer growth.
  • RAP2A a member of RAS oncogene family, as a candidate marker for maximal tumor shrinkage.
  • Simulation analysis predicts 6 genes as candidate marker genes for progression free survival - Since maximal tumor shrinkage is predictive of progression free survival, it is not surprising that four candidate marker genes of maximum tumor shrinkage (MTS) are also candidate marker genes of progression free survival.
  • MTS maximum tumor shrinkage
  • SHMT1 and IL22RA2 are identified as candidate marker genes of progression free survival (PFS).
  • the REFSTM model predicts that lower level of IL22RA2 is associated with longer progression free survival time ( Figure 4B) while lower level of SHMT1 is associated with shorter progression free survival time ( Figure 4A).
  • IL22RA2 is a soluble cytokine receptor, which binds to and inhibits IL-22 activity.
  • IL-22 is a cytokine that has complex pro inflammatory, anti inflammatory, and auto immune effects (Aujla, S.J. & Kolls, J.K. IL-22: a critical mediator in mucosal host defense. J. Mol. Med., 87, 451-4 (2009)), suggesting the importance of immune system in progression free survival time.
  • SHMTl is serine hydroxymethyltransferase 1 and its S P has been reported to be associated with cancer ( Komlosi, V. et al. SHMTl 1420 and MTHFR 677 variants are associated with rectal but not colon cancer. BMC Cancer, 10:525).
  • the maximal tolerable dosing or maximal PK values are set for each individual patient and the clinical phenotypic responses are predicted for the group of patients. A higher response rate of E7080 treatment was predicted if maximal E7080 tolerable dosing is applied to patients. If 84 day of progression free survival time is used as cutoff, REFSTM predicts the number of good responder would increase from 13 to 17.
  • REFSTM model predictive of E7080 responsiveness The data used to construct the model are gene expression profiles before E7080 treatment and pharmacokinetic measures of E7080 from day 1 of cycle 1. All 54,675 genes are used to build the REFSTM model and in silico simulation analyses were done to identify candidate marker genes. Four genes were predicted as candidate marker genes for maximal tumor shrinkage and six genes were predicted as candidate marker genes for progression free survival.
  • candidate marker genes traditional signaling pathway components such as RAP2A in MAPK pathway were identified as a candidate marker gene for both maximal tumor shrinkage and progression free survival.
  • Genes involved in miRNA regulation, such as TARBP2 are also identified as candidate marker genes of maximal tumor shrinkage and progression free survival.
  • genes such as CACNA1I and C70RF which are considered as "novel" in melanoma disease are also identified as candidate marker genes for maximal tumor shrinkage and/or progression free survival. Identification of IL22RA2 as a candidate marker gene suggests that immune status also plays a role in progression free survival.
  • Archived, fixed tumor tissue from cancer patients are collected for the assessment of biomarkers that can serve as signatures for responsiveness or non-responsiveness to therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • biomarkers that can serve as signatures for responsiveness or non-responsiveness to therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • GEP Gene-expression profiling
  • proteomic proteomic
  • immunohistochemical (IHC) immunohistochemical
  • All analyses are performed to correlate clinical outcomes related to treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
  • Biomarker samples e.g., serum or plasma, blood mRNA, free circulating tumor DNA/miRNA are also collected for biomarker analysis at baseline, Cycle 1/Day 15, Day 1 of all subsequent cycles, and at the off-treatment assessment in the clinical study.
  • Biomarker discovery' and 'evaluation is performed to identify blood, genetic, or tumor biomarkers which may be useful to predict subject response to lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), as determined by the evaluation of clinical endpoints, such as CR (complete response) or PR (partial response), PFS (progression free survivaD, OS (overall survival), DCR (disease control rate) (CR or PR or SD (stable disease) for 7 weeks) , CBR (clinical benefit rate) (CR or PR or durable SD; SD lasting for 23 weeks), and the durable SD (SD lasting > 23 weeks) rate.
  • CR complete response
  • PR partial response
  • PFS progression free survivaD
  • OS overall survival
  • DCR disease control rate
  • CBR clinical benefit rate
  • SD durable SD lasting > 23 weeks
  • Lysates were prepared from macro-dissected FFPE slides (macro-dissection performed at Gentris). Briefly, 1ml of Xylene was added and vortexed for 10 sec, followed by centrifugation for 4 min at maximum speed (all centrifuge steps were carried out at room temp with benchtop microcentrifuge). Supernatant was removed by pipetting, leaving 200 ⁇ of supernatant behind (without disturbing the pellet). 1ml of 100% ethanol was added and vortexed. This was followed by a spin down at maximum speed for 2min. The ethanol wash step was repeated. Maximum supernatant was then removed without disturbing the pellet.
  • the pellet was allowed to dry at room temperature for 30 min with the tube open and then re-suspended in 45 ⁇ 10 mM MES pH 6.5, 0.5% SDS, and 5 ⁇ Proteinase K (20 mg/ml) and vortexed. The resulting solution was incubated at 55 degrees for 15 min, tapped gently to mix, and then incubated at 80 degrees for 15min. This was followed by centrifugation at maximum speed for 30 sec, and the supernatant was retrieved and 5 ⁇ was used as template for each nCounter reaction and processed according to standard protocol.
  • the final data was normalized for lane to lane variation using the positive spike in controls which are part of the probe set and then content normalized to Actin-B (the least variant endogenous gene) and checked for Quality Control. Any raw count ⁇ 50 was considered background, and-50 wa's set as lower limit of detection.
  • baseline SNRNP70, CLINTl, PGCP and SHMT1 were significantly associated with longer progression free survival. Also the lower gene expression level of baseline CPM was significantly associated with longer progression free survival (Table 10).
  • PGCP is associated with responsiveness to E7080.
  • the lysate that was used was directly prepared ⁇ from FFPE slides and analyzed for expression of

Abstract

Biomarkers are provided that are predictive of a subject's responsiveness or non-responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). The biomarkers, compositions, and methods described herein are useful in selecting and administering appropriate treatment modalities for a subject having cancer (e.g., melanoma), suspected of having cancer, or at risk of developing cancer.

Description

BIOMARKERS THAT ARE PREDICTIVE OF RESPONSIVENESS OR NON-RESPONSIVENESS TO TREATMENT WITH LENVATINIB OR A
PHARMACEUTICALLY ACCEPTABLE SALT THEREOF
CROSS REFERENCE TO RELATED APPLICATIONS
This application claims the benefit of U.S. Provisional Application No.
61/485,604, filed May 12, 2011, the content of which is incorporated by reference in its entirety herein.
FIELD OF THE INVENTION
The present invention relates to biomarkers that are useful in predicting the responsiveness or non-responsiveness of a subject to an antitumor agent such as lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
BACKGROUND OF THE INVENTION
A number of kinase inhibitors have been developed as antitumor agents. For example, a group of compounds having inhibitory activity against receptor tyrosine kinases, such as vascular endothelial growth factor receptor (VEGFR), are known to inhibit angiogenesis and are regarded as a new class of antitumor agents. Lenvatinib mesylate (also known as E7080)'is an oral tyrosine kinase inhibitor targeting VEGFR 1- 3, fibroblast growth factor receptor (FGFR) 1-4, rearranged during transfection receptor (RET), KIT, and platelet derived growth factor receptor (PDGFR). In phase I clinical studies of lenvatinib mesylate, response to treatment was observed in melanoma, as well as endometrial, thyroid, and renal cancers.
Unfortunately, most anti-tumor treatments are associated with undesirable side effects, such as profound nausea, vomiting, or severe fatigue. Also, while anti-tumor treatments have been successful, they do not produce significant clinical responses in all patients who receive them resulting in undesirable side effects, delays, and costs associated with ineffective treatment. Therefore, biomarkers that can be used to predict the response of a subject to an antitumor agent prior to administration thereof are greatly needed.
SUMMARY
The present application is based, at least in part, on the identification of biomarkers that are predictive of a subject's responsiveness or non-responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). For example, the expression level of one or more of the genes depicted in Table 1 can predict the likelihood that a given subject will or will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). Thus, several of the biomarkers and compositions described herein are useful, for example, in identifying and/or selecting a patient or a subset of patients that could benefit from treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). Several of the biomarkers and compositions described herein are useful in identifying and/or selecting a patient or a subset of patients who are unlikely to benefit from a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). In addition, the methods described herein are useful, for example, in selecting appropriate treatment modalities (e.g., therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) or a non-lenvatinib therapy) for a subject suffering from a cancer or at risk of developing a cancer.
In one aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of ADAMTS9 in the biological sample, wherein an elevated expression level, as compared to a control, of ADAMTS9 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of AMIGOl in the biological sample, wherein an elevated expression level, as compared to a control, of AMIGOl is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes 'providing a biological sample obtained from a subject and measuring the expression level of ANKRD13D in the biological sample, wherein an elevated expression level, as compared to a control, of AN RD13D is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the ANK D13D gene.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of ARRDC4 in the biological sample, wherein an elevated expression level, as compared to a control, of ARRDC4 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the ARRDC4 gene.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of ATF3 in the biological sample, wherein an elevated expression level, as compared to a control, of ATF3 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of ATP11C in the biological sample, wherein an elevated expression level, as compared to a control, of ATP11C is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of CACNAII in the biological sample,' wherein an elevated expression level, as compared to a control, of CACNAII is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of CCBLl in the biological sample, wherein an elevated expression level, as compared to'a control, of CCBLl is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological samp let obtained from a subject and measuring the expression level of CHKA in the biological sample, wherein an elevated expression level, as compared to a control, of CHKA is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the CHKA gene.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of COPS7B in the biological sample, wherein an elevated expression level, as compared to a control, of COPS7B is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the COPS7B gene.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes ^providing a biological sample obtained from a subject and measuring the expression level of C70RF in the biological sample, wherein an elevated expression level, as compared to a control, of C70RF is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the C70RF gene.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of DSCCl in the biological sample, wherein an elevated expression level, as compared to a control, of DSCCl is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the DSCC1 gene.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of EML6 in the biological sample, wherein an elevated expression level, as compared to a control, of EML6 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of ERG in the biological sample, wherein an elevated expression level, as compared to a control, of ERG is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of FAM122A in the biological sample, wherein an elevated expression level, as. compared to a control, of FAM122A is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of GDPD5 in the biological sample, wherein an elevated expression level, as compared to a control, of GDPD5 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the GDPD5 gene.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of GJB2 in the biological sample, wherein an elevated expression level, as compared to a control, of GJB2 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the GJB2 gene.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of GNB5 in the biological sample, wherein an elevated expression level, as compared to a control, of GNB5 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of HIPK2 in the biological sample, wherein an elevated expression level, as compared to a control, of HIPK2 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the HIPK2 gene.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of IGJ. in the biological sample, wherein an elevated expression level, as compared to a control, of IGJ is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample, obtained from a subject and measuring the expression leVel of IL22RA2 in the biological sample, wherein an elevated expression level, as compared to a control, of IL22RA2 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the IL22RA2 gene.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of INSR in the biological sample, wherein an elevated expression level, as compared to a control, of INSR is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of MDM1 in the biological sample, wherein an elevated expression level, as compared to a control, of MDM1 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the MDM1 gene.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of MSRB2 in the biological sample, wherein an elevated expression level, as compared to a control, of MSRB2 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the MSRB2 gene.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of NAPEPLD in the biological sample, wherein an elevated expression level, as compared to a control, of NAPEPLD is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the NAPEPLD gene.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of NEIL2 in the biological sample, wherein an elevated expression level, as compared to a control, of NEIL2 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the NEIL2 gene.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of NPY6R in the biological sample, wherein an elevated expression level, as compared to a control, of NPY6R is predictive that the subject will respond to a therapy„ comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of UP188 in the biological sample, wherein an elevated expression level, as compared to a control, of NTJP188 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of OSBPL10 in the biological sample, wherein an elevated expression level, as compared to a control, of OSBPL10 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the OSBPL10 gene.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of PDXDC1 PDXDC2 in the biological sample, wherein an elevated expression level, as'compared to a control, of PDXDC1/PDXDC2 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the PDXDC1/PDXDC2 genes.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of PFKFB2 in the biological sample, wherein an elevated expression level, as compared to a control, of PFKFB2 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of PGCP in the biological sample, wherein an elevated expression level, as compared to a control, of PGCP is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of PIP5K1B in the biological sample, wherein an elevated expression level, as compared to a control, of PIP5K1B is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of PPARD in the biological sample, wherein an elevated expression level, as compared to a control, of PPARD is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of PSPH in the biological sample, wherein an elevated expression level, as compared to a control, of PSPH is predictive that the subject will not- respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the PSPH gene.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of RAP2A in the biological sample, wherein an elevated expression level, as compared to a control, of RAP2A is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of RORA in the biological sample, wherein an elevated expression level, as compared to a control, of RORA is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of SHMTl in the biological sample, wherein an elevated expression level, as compared to a control, of SHMTl is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof. -
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of SLC31A1 in the biological sample, wherein an elevated expression level, as compared to a control, of SLC31A1 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of SSPN in the biological sample, wherein an elevated expression level, as compared to a control, of SSPN is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the SSPN gene.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of STAG3L4 in the biological sample, wherein an elevated expression level, as compared to a control, of STAG3L4 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the STAG3L4 gene.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of SURF4 in the biological sample, wherein an elevated expression level, as compared to a control, of SURF4 is predictive that the subject will respond to a therapy, comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of TARBP2 in the biological sample, wherein an elevated expression level, as compared to a control, of TARBP2 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the TARBP2 gene.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of TMEM2 in the biological sample, wherein an elevated expression level, as compared to a control, of TMEM2 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of T KS in the biological sample, wherein an elevated expression level, as compared to a control, of TNKS is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the TNKS gene.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of TTLL4 in the biological sample, wherein an elevated expression level, as compared to a control, of TTLL4 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the TTLL4 gene.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of TUBBP5 in the biological sample, wherein an elevated expression level, as compared to a control, of TUBBP5 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of UBA6 in the biological sample, wherein an elevated expression level, as compared to a control, of UBA6 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of VPS37A in the biological sample, wherein an elevated expression level, as compared to a control, of VPS37A is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the VPS37A gene.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of ZC3HllA in the biological sample, wherein an elevated expression level, as compared to a control, of ZC3HllA is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of ZC3H6 in the biological sample, wherein an elevated expression level, as compared to a control, of ZC3H6 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the ZC3H6 gene.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of Z F529 in the biological sample, wherein an elevated expression level, as compared to a control, of ZNF529 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof. ' ''· *■: .'
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of ZNF542 in the biological sample, wherein an elevated expression level, as compared to a control, of ZNF542 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of SNRNP70 in the biological sample, wherein an elevated expression level, as compared to a control, of SNRNP70 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of CLINTl in the biological sample, wherein an elevated expression level, as compared to a control, of CLINTl is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of CPM in the biological sample, wherein an elevated expression level, as compared to a control, of CPM is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the CPM gene.
In another aspect, the disclosure provides a method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, which method includes providing a biological sample obtained from a subject and measuring the expression level of one or more genes in the biological sample, wherein the one or more genes comprise at least one gene selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R, IGJ, NUP188, ERG, MDM1, HIPK2, INSR, ZNF529, DSCC1, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, ADAMTS9, SSPN, ZC3H6, VPS37A, OSBPLIO, PDXDC1/PDXDC2, RORA, ANKRD13D, ZNF542, PPARD, NAPEPLD, ATPllC, EML6, GNB5, ATF3, ZC3H11A, CCBLl/ SHMTl, C70RF, IL22RA2, RAP2A, CACNA1I, SNRNP70, CLINTl, and CPM. An elevated expression level, as compared to a control, of one or more of SLC31A1, PFKFB2, NPY6R, IGJ, NUP188, ERG, INSR, ZNF529, PIP5K1, TMEM2, TUBBP5, UBA6, SURF4, FAM122A, AMIGOl, ADAMTS9, RORA, ZNF542, PPARD, ATP11C, EML6, GNB5, ATF3, ZC3H11A, CCBL1, SHMT1, RAP2A, CACNA1I, PGCP, SNR P70, and CLINT1 is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, whereas an elevated expression level, as compared to a control, of one or more of TNKS, TARBP2, TTLL4, CHKA, PSPH.CPM, MDMl, HIPK2, DSCC1, STAG3L4, MSRB2, GDPD5, GJB2, ARRDC4, COPS7B, NEIL2, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDC1 PDXDC2, ANKRD13D, NAPEPLD, C70RF or IL22RA2 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the one or more genes.
The following embodiments relate to all of the methods described above. In some embodiments the subject has, or is at risk of developing, a cancer. In specific embodiments, the cancer is selected from the group consisting of a skin cancer, a liver cancer, a lung cancer, a brain tumor, a thyroid cancer, an ovarian cancer, a renal cancer and an endometrial cancer. In one embodiment, the cancer is a melanoma. In certain embodiments, the subject is a human. In some embodiments, the biological sample is selected from the group consisting of a blood sample, circulating tumor cells, circulating DNA, a plasma sample, a serum sample, a urine sample, a skin sample and a tumor sample. In some embodiments, the method further includes communicating the test results to the subject's health care provider. In certain embodiments, the method further includes modifying the subject's medical record to indicate that the subject is likely to respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, if the expression level of one or more of SLC31A1, PFKFB2, NPY6R, IGJ, NUP188, ERG, INSR, ZNF529, PIP5K1, TMEM2, TUBBP5, UBA6, SURF4, FAM122A, AMIGOl, ADAMTS9, RORA, ZNF542, PPARD, ATP11C, EML6, GNB5, ATF3, ZC3H11A, CCBLl, SHMT1, RAP2A, CACNA1I, PGCP, SNRNP70, and CLINT1 is elevated, as compared to a control. In certain embodiments, the method further includes modifying the subject's medical record to indicate that the subject is not likely to respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, if the expression level of one or more of TNKS, TARBP2, TTLL4, CHKA, PSPH, CPM, , MDMl, HIPK2, DSCCl, STAG3L4, MSRB2, GDPD5, GJB2, ARRDC4, COPS7B, NEIL2, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDC1/PDXDC2, ANKRD13D, NAPEPLD, C70RF and IL22RA2 is elevated, as compared to a control. In specific embodiments, the record is created on a computer readable medium. In certain embodiments, the method further includes prescribing a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof for the subject if the expression level of one or more genes in the biological sample is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof. In some embodiments, the method further includes
administering to the subject a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof. In some embodiments, the method involves determining that the expression level of one or more of SLC31A1, PFKFB2, PY6R, IGJ, NUP188, ERG, INSR, ZNF529, PIP5K1, TMEM2, TUBBP5, UBA6, SURF4, FAM122A, AMIGOl, ADAMTS9, RORA, ZNF542, PPARD, ATP11C, EML6, GNB5, ATF3, ZC3H11A, CCBL1, SHMTl, RAP2A, CACNAII, PGCP, SNRNP70, and CLINTl is elevated, as compared to a control and selecting a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof for the subject. In some embodiments, the method involves determining that the expression level of one or more of TNKS, TARBP2, TTLL4, CHKA, PSPH, CPM, MDM1, HIPK2, DSCC1, STAG3L4, MSRB2, GDPD5, GJB2, ARRDC4, COPS7B, NEIL2, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDC 1/PDXDC2, ANKRD13D, NAPEPLD, C70RF, and IL22RA2 is elevated, as compared to a control and selecting a therapy comprising an agent that is not lenvatinib for the subject. In some
embodiments, the RNA level of the one or more genes is measured. In other embodiments, the protein level of, the one or more genes is measured. In certain embodiments, the method further includes administering to the subject a therapy that does not comprise lenvatinib if the expression level of one or more genes in the biological sample is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof. In certain embodiments, the method comprises measuring the expression level of at least five genes selected from the group consisting of TNKS, TTLL4, PGCP, ERG, GJB2, INSR, FAM122A, SSPN, VPS37A, PDXDC 1/PDXDC2, ZNF542, ATP11C, CPM, SNRNP70, CLINTl, and
ZC3H11A. In other embodiments, the method comprises measuring the expression level of at least eight genes selected from the group consisting of TNKS, TTLL4, PGCP, ERG, GJB2, INSR, FAM122A, SSPN, VPS37A, PDXDC 1/PDXDC2, ZNF542, ATP11C, CPM, SNRNP70, CLINTl, and ZC3H11A. In certain embodiments, the method comprises measuring the expression level of at least five genes selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R, IGJ, NUP188, ERG, MDM1, HIPK2, INSR, ZNF529, DSCC1, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, ADAMTS9, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDC 1/PDXDC2, RORA, ANK D13D, ZNF542, PPARD, NAPEPLD, ATPllC, EML6, GNB5, ATF3, ZC3H11A, CPM, SNRNP70, CLINT1, and CCBLl. In other
embodiments, the method comprises measuring the expression level of at least eight genes selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R IGJ, NUP188, ERG, MDMl, HIPK2, INSR, ZNF529, DSCCl, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, ADAMTS 9, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDC1/PDXDC2, RORA, ANKRD13D, ZNF542, PPARD, NAPEPLD, ATPllC, EML6, GNB5, ATF3, ZC3H11A, CPM, SNRNP70, CLINT1 and CCBLl. In yet other embodiments, the method includes measuring the expression level of the following genes: SHMTl, C70RF, IL22RA2, TARBP2, RAP2A, and CACNA1I.
In another aspect the disclosure provides a method of selecting a subject having, or at risk of developing, a cancer that would benefit from treatment comprising lenvatinib or a pharmaceutically acceptable salt thereof. The method includes the steps of determining the expression level in a biological sample obtained from a subject of at least one gene selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R, IGJ, NUP188, ERG, MDMl, HIPK2, INSR, ZNF529, DSCCl, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, AD AMTS9, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDC1/PDXDC2, RORA, ANKRD13D, ZNF542, PPARD, NAPEPLD, ATPllC, EML6, GNB5, ATF3, ZC3H11A, CCBLl, SHMTl, C70RF, IL22RA2, RAP2A, CPM, SNRNP70, CLINT1, and CACNAlI; and comparing the expression level of the at least one gene selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R, IGJ, NUP188, ERG, MDMl, HIPK2, INSR, ZNF529, DSCCl, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, ADAMTS9, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDC 1/PDXDC2, RORA, ANKRD13D, ZNF542, PPARD, NAPEPLD, ATPllC, EML6, GNB5, ATF3, ZC3H11A, CCBLl, SHMTl, C70RF, IL22RA2, RAP2A, CPM, SNRNP70, CLINT1, and CACNAlI in the biological sample from the subject to that in a control. An elevated expression level of one or more of SLC31A1 PFKFB2, NPY6R, IGJ, NUP188, ERG, INSR, ZNF529, PIP5K1, TMEM2, TUBBP5, UBA6/ SURF4, FAM122A, AMIGOl, ADAMTS9, RORA, ZNF542, PPARD, ATPllC, EML6, GNB5, ATF3, ZC3H11A, CCBLl, SHMTl, RAP2A, CACNAlI, PGCP, SNRNP70, and CLINT1, compared to the control is indicative that the subject would benefit from treatment comprising lenvatinib or a pharmaceutically acceptable salt thereof, whereas an elevated expression level of one or more of TNKS, TARBP2, TTLL4, CHKA, PSPH; CPM, , MDMl, HIPK2, DSCC1, STAG3L4, MSRB2, GDPD5, GJB2, ARRDC4, COPS7B, NEIL2, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDC1/PDXDC2, ANK D13D, NAPEPLD, C70RF and IL22RA2 compared to the control is indicative that the subject would not benefit from treatment comprising lenvatinib or a pharmaceutically acceptable salt thereof. The method further includes the step of selecting the subject who would benefit from treatment comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In one embodiment of this aspect, the method involves measuring the expression level of SHMT1. In another embodiment of this aspect, the method involves measuring the expression level of C70RF. In another embodiment of this aspect, the method involves measuring the expression level of IL22RA2. In another embodiment of this aspect, the method involves measuring the expression level of TARBP2. In another embodiment of this aspect, the method involves measuring the expression level of RAP2A. In another embodiment of this aspect, the method involves measuring the expression level of CACNA1I. In some embodiments of this aspect the method comprises measuring the expression level of at least five genes selected from the group consisting of TNKS, TTLL4, PGCP, ERG, GJB2, INSR, FAM122A, SSPN, VPS37A, PDXDC1/PDXDC2, ZNF542, ATP11C, CPM, SNRNP70, CLINT1, and ZC3H11A. In other embodiments of this aspect the method comprises measuring the expression level of at least eight genes selected from the group consisting of TNKS, TTLL4, PGCP, ERG, GJB2, INSR, FAM122A, SSPN, VPS37A, PDXDC 1/PDXDC2, ZNF542, ATP11C, CPM, SNRNP70, CLINT1, and ZC3H11A. In some embodiments of this aspect the method involves measuring the expression level of at least five genes selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R, IGJ, NUP188, ERG, MDMl, HIPK2, INSR, ZNF529, DSCC1, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, ADAMTS9, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDC1 PDXDC2, RORA, ANKRD13D, ZNF542, PPARD, NAPEPLD, ATP11C, EML6, GNB5, ATF3, ZC3H11A, CPM, SNRNP70, CLINT1, and CCBL1. In other
embodiments of this aspect the method involves measuring the expression level of at least eight genes selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R, IGJ, NUP188, ERG, MDMl, HIPK2, INSR, ZNF529, DSCC1, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, ADAMTS9, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDC 1 PDXDC2, RORA, ANKRD13D, ZNF542, PPARD, NAPEPLD, ATP11C, EML6, GNB5, ATF3, ZC3H11A, CPM, SNRNP70, CLINT1, and CCBLl. In one embodiment, the method comprises measuring the expression level of SHMTl, C70RF, IL22RA2, TARBP2, RAP2A, and CACNAII. In certain embodiments of this aspect, the RNA level of the one or more genes is measured. In other embodiments of this aspect, the protein level of the one or more genes is measured.
In a different aspect, the disclosure provides a method of treating a cancer, the method including the step of administering to a subject in need thereof an effective amount of a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, wherein the subject has been identified as having an elevated expression level, as compared to a control, of one or more of SLC31A1, PFKFB2, NPY6R, IGJ, NUP188, ERG, INSR, ZNF529, PIP5K1, TMEM2, TUBBP5, UBA6, SURF4, FAM122A, AMIGOl, ADAMTS9, RORA, ZNF542, PPARD, ATP11C, EML6, GNB5, ATF3, ZC3H11A, CCBLl, SHMTl, RAP2A, CACNAII, PGCP, SNRNP70, and CLINTl.
In another aspect, the disclosure provides a method of treating a cancer, the method comprising determining the expression level of one or more of SLC31A1, PFKFB2, NPY6R, IGJ, NUP188, ERG, INSR, ZNF529, PIP5K1, TMEM2, TUBBP5, UBA6, SURF4, FAM122A, AMIGOl, ADAMTS9, RORA, ZNF542, PPARD, ATP11C, EML6, GNB5, ATF3, ZC3H11A CCBLl, SHMTl, RAP2A, CACNAII, PGCP, SNRNP70, and CLINTl; and administering to a subject having an elevated expression level, as compared to a control, of one or more of SLC31A1, PFKFB2, NPY6R, IGJ, NUP188, ERG, INSR, ZNF529, PIP5K1, TMEM2, TUBBP5, UBA6, SURF4, FAM122A, AMIGOl, ADAMTS9, RORA, ZNF542, PPARD, ATP11C, EML6, GNB5, ATF3, ZC3H11A, CCBLl, SHMTl, RAP2A, CACNAII; PGCP, SNRNP70, and CLINTl an effective amount of a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
In some embodiments of the above two aspects drawn to methods of treating a cancer, the subject is a human. In some embodiments, the cancer is selected from the group consisting of a skin cancer, a liver cancer, a lung cancer, a brain tumor, a thyroid cancer, an ovarian cancer, a renal cancer and an endometrial cancer. In one
embodiment, the cancer is a melanoma. In some embodiments, the RNA level of the one or more genes is measured. In other embodiments, the protein level of the one or more genes is measured. In one embodiment, the subject has been identified as having an elevated expression level, as compared to a control, of SHMTl. In another embodiment, the subject has been identified as having an elevated expression level, as compared to a control, of RAP2A. In yet another embodiment, the subject has been identified as having an elevated expression level, as compared to a control, of CACNAII. In another aspect, the disclosure provides a composition comprising at least five polynucleotides that selectively hybridize to each of at least five genes selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R, IGJ, NUP188, ERG, MDMl, HIPK2, INSR, ZNF529, DSCCl, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, ADAMTS9, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDC 1/PDXDC2, RORA, ANKRD13D, ZNF542, PPARD, NAPEPLD, ATPllC, EML6, GNB5, ATF3, ZC3H11A, CCBLl, SHMTl, C70RF, IL22RA2, RAP2A, CACNA1I, SNRNP70, and CLINTl,.
In one embodiment of this aspect, the at least five genes are selected from the group consisting of TNKS, TTLL4, PGCP, ERG, GJB2, INSR, FAM122A, SSPN, VPS37A, PDXDC 1/PDXDC2, ZNF542, ATPllC, SNRNP70, CLINTl, and ZC3H11A. In another embodiment, the at least five genes are selected from the group consisting of SHMTl, C70RF, IL22RA2, TARBP2, RAP2A, and CACNA1I. In another embodiment, the at least five polynucleotides are bound to a solid support.
In another aspect, the disclosure provides a composition comprising at least three polynucleotides that selectively hybridize to each of at least three genes selected from the group consisting of SHMTl, C70RF, IL22RA2, TARBP2, RAP2A, and
CACNA1I. In one embodiment, the at least three polynucleotides are bound to a solid support.
In another aspect, the disclosure provides a kit comprising an array including a plurality of polynucleotides bound to a solid support, wherein the plurality comprises at least five polynucleotides that selectively hybridize to each of at least five genes selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R, IGJ, NTJP188, ERG, MDMl, HIPK2, INSR, ZNF529, DSCCl, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, AD AMTS9, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDC 1/PDXDC2, RORA, ANKRD13D, ZNF542, PPARD, NAPEPLD, ATPllC, EML6, GNB5, ATF3, ZC3H11A, CCBLl, SHMTl, C70RF, IL22RA2, RAP2A, SNRNP70, CLINTl, and CACNA1I. In addition, the kit includes instructions for detecting the presence or amount of one of more of the polynucleotides in a sample.
In some embodiments of this aspect, the kit further includes one or more reagents for isolating nucleic acid from a sample. In other embodiments, the kit further includes a means for amplifying a nucleic acid.
In another aspect, the disclosure provides a kit comprising an array. The array includes a plurality of polynucleotides bound to a solid support, wherein the plurality comprises at least three polynucleotides that selectively hybridize to each of at least three genes selected from the group consisting of SHMTl, C70RF, IL22RA2, RAP2A, TARBP2, and CACNA1I. The kit also includes instructions for detecting the presence or amount of one of more of the polynucleotides in a sample.
Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, the exemplary methods and materials are described below. All publications, patent applications, patents, and other references mentioned herein are incorporated by reference in their entirety. In case of conflict, the present application, including definitions, will control. The materials, methods, and examples are illustrative only and not intended to be limiting.
Other features and advantages of the invention will be apparent from the following detailed description, and from the claims.
BRIEF DESCRIPTION OF THE DRAWINGS
Fig. 1 is a schematic diagram of building Bayesian BioModel™ and Monte Carlo simulations. A. Pharmacokinetic measures, gene expression and phenotypic data are prepared for modeling. B. Likely fragments for network reconstruction are identified by scoring all 2-, 3-, and 4-variable combinations. The top ranked fragments with the most likely Bayesian scores for phenotypes were identified and retained for network reconstruction. C. Parallel global network sampling constructs an ensemble of 1000 network structure that explains the data. D. Diversity in network structures identified during network reconstruction captures uncertainty in the model. Hypotheses are extracted from the network ensemble by competing Monte Carlo simulations of "what- if ' scenarios. The change in the gene that is circled would be expected to impact phenotypic endpoints.
Fig. 2 is a schematic diagram of the consensus topology of the ensemble of networks. Snapshot of the network ensemble at 0.1% consensus topology. White pads are phenotypic endpoints, transcripts (connected with grey lines), and pharmacokinetic measures (connected with black lines).
Fig. 3 shows simulation results of four candidate markers for maximal tumor shrinkage (MTS). Distributions of simulated values of MTS if a marker gene expression is modulated are plotted (broken line curve: baseline; solid line curve: 10- fold knockdown). A. C70RF B. TARBP2 C. RAP2A D. CACNA1I. Fig. 4 shows simulation results of six candidate markers for progression free survival (PFS). Distributions of simulated values of PFS if a marker gene expression is modulated are plotted (broken line curve: baseline; solid line curve: 10-fold knockdown). A. SHMT1 B. IL22RA2 C. C70RF/D. TARBP2 E. RAP2A F. CACNA1I.
DETAILED DESCRIPTION
This disclosure provides methods and compositions (e.g., nucleic acid arrays and kits) for predicting the response of a subject (such as a human patient) to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). In addition, the disclosure provides predictive biomarkers (e.g., gene expression levels) to identify those subjects for whom administering a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) is likely to be effective or ineffective. Such biomarkers, compositions, and methods are useful in selecting appropriate therapeutic modalities (e.g., a lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) therapy or a non- lenvatinib therapy) for subjects suffering from diseases such as cancer. Furthermore, this application provides methods of selecting patients that could benefit from a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) as well as methods of treatment.
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Definitions P' '
The term "circulating tumor cells" (CTCs) refers to cells that have detached from a primary tumor and circulate in the bloodstream. CTCs may constitute seeds for subsequent growth of additional tumors (metastasis) in different tissues (Kitago et al., Clin. Chem., 55(4):757:764 (2009)).
The term "circulating DNA" refers to DNA that is present in increased amounts in plasma or serum of cancer patients. Cancer patients have higher levels of circulating DNA than healthy controls (Leon et al., Cancer Res., 37: 646 650 (1977); Chuang et al., Head & Neck, 229-234 (2010)).
The term "decreased/reduced expression level" means an expression level that is lower than the expression level in a control.
The term "elevated expression level" means an expression level that is higher than the expression level in a control.
The term "lenvatinib" refers to
4 (3-chloro-4(cyclopropylaminocarbony0aminophenoxy)-7-methoxy6- quinolinecarboxamide. This compound is disclosed in Example 368 (see, column 270) of U.S. Patent No.
7,253,286. U.S. Patent No. 7,253,286 is incorporated by reference in its entirety herein. Lenvatinib mesylate is also referred to as E7080.
The term "pharmaceutically acceptable salt" is not particularly restricted as to the type of salt. Examples of such salts include, but are not limited to, inorganic acid addition salt such as hydrochloric acid salt, sulfuric acid salt, carbonic acid salt, bicarnobate salt, hydrobromic acid salt and hydriodic acid salt; organic carboxylic acid addition salt such as acetic acid salt, maleic acid salt, lactic acid salt, tartaric acid salt and trifluoroacetic acid salt; organic sulfonic acid addition salt such as methanesulfonic acid salt, hydroxymethanesulfonic acid salt, hydroxyethanesulfonic acid salt, benzenesulfonic acid salt, toluenesulfonic acid salt and taurine salt; amine addition salt such as trimethylamine salt, triethylamine salt, pyridine salt, procaine salt, picoline salt, dicyclohexylamine salt, Ν,Ν'-dibenzylethylenediamine salt, N- methylglucamine salt, diethanolamine salt, trie thanola mine salt,
tris(hydroxymethylamino)methane salt and phenethylbenzylamine salt." and amino acid addition salt such as arginine salt, lysine salt, serine salt, glycine salt, aspartic acid salt and glutamic acid salt. In one embodiment, the pharmaceutically acceptable salt is a methanesulfonic acid salt ("mesylate"). The methanesulfonic acid salt form (i.e., the mesylate) of 4-(3-chloro-4 (cyclopropylaminocarbony0aminophenoxy)-7- methoxy-6-quinolinecarboxamide is disclosed in US Patent 7,612,208, which is incorporated by reference herein in its entirety.
The terms "nucleic acid" and "polynucleotide" are used interchangeably herein, and refer to both RNA and DNA, including cDNA, genomic DNA, synthetic DNA, and DNA (or RNA) containing nucleic acid analogs. Polynucleotides can have any three- dimensional structure. A nucleic acid can be double-stranded or single-stranded (i.e., a sense strand or an antiserise strand). Non-limiting examples of polynucleotides include genes, gene fragments, exons, introns, messenger RNA (mRNA), transfer RNA, ribosomal RNA, siRNA, micro-RNA, ribozymes, cDNA, recombinant polynucleotides, branched polynucleotides, plasmids, vectors, isolated DNA of any sequence, isolated RNA of any sequence, nucleic acid probes, and primers, as well as nucleic acid analogs.
"Polypeptide" and "protein" are used interchangeably herein and mean any peptide-linked chain of amino acids, regardless of length or post-translational modification. Typically, a polypeptide described herein is "isolated" when it constitutes at least 60%, by weight, of the total protein in a preparation, e.g., 60% of the total protein in a sample. In some embodiments, a polypeptide described herein consists of at least 75%, at least 90%, or at least 99%, by weight, of the total protein in a preparation.
The term "subject" means a mammal, including but not limited to, a human, a chimpanzee, an orangutan, a gorilla, a baboon, a monkey, a mouse, a rat, a pig, a horse, a dog, and a cow.
Biomarkers for Responsiveness and Non-Responsiveness to Therapy Comprising Lenvatinib or a Pharmaceutically Acceptable Salt Thereof
A number of genes have been identified whose expression levels (e.g., mRNA or protein expression levels) are predictive of the responsiveness or non-responsiveness of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). These genes and their representative Genbank® Accession Nos. are listed in Table 1. The sequences provided herein for these genes are merely representative of the sequences for the biomarker genes listed below. This disclosure also encompasses defection of expression levels of a gene using partial sequences, allelic variants and mutations (among others) of the sequences provided herein. Where a sequence provided herein is a partial sequence of a full length sequence of a gene, this disclosure also encompasses detection of expression levels of a gene using the entire sequence of the gene or other partial sequences of the gene which may or may not overlap with the sequence provided herein.
Table 1: Biomarkers for E7080 Responsiveness or Non-responsiveness
Figure imgf000026_0001
Figure imgf000027_0001
Figure imgf000028_0001
Figure imgf000029_0001
An elevated expression level of a gene listed in Table 1 (compared to a control) can be predictive of either responsiveness or non-responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). Information concerning the expression of as few as one gene listed in Table 1 is useful in predicting responsiveness or lack thereof to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). Biological samples (e.g., tumors) may be analyzed with respect to the expression of groups of the genes Usted in Table 1, including from 1 to 53 of the genes Usted in Table 1, in any combination. It is well within the ability of one of skill in the art to select genes for analysis from among the genes listed in Table 1. In the interest of brevity, every possible combination of genes from Table 1 suitable for use in the invention is not expressly Usted herein. Nevertheless, it should be understood that every such combination is contemplated and is within the scope of the invention. It is specifically envisioned that any combination of the genes in Table 1, all of which were found to be differentiaUy expressed between responders and non-responders to lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) treatment, can be used in the methods and compositions described herein.
An elevated expression level (compared to a control) of any one or more of the genes Usted in Table 2 is predictive that a subject wiU respond to a therapy comprising lenvatinib or a pharmaceutical 'acceptable salt thereof (e.g., lenvatinib mesylate). In this context, the term "control" means a sample (or samples) from the same ceU type or tissue type as that of the test sample that is obtained from a subject (or subjects) who has not responded to treatment with lenvatinib or a pharmaceuticaUy acceptable salt thereof (e.g., lenvatinib mesylate). The term "control" includes a sample obtained in the past and used as a reference for future comparisons to test samples taken from subjects for which therapeutic responsiveness is to be predicted. For example, the "control" expression level for a particular gene in a particular cell type or tissue may be pre-estabUshed by an analysis of gene expression in one or more subjects that have not responded to treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). This pre-established reference value (which may be an average expression level taken from multiple subjects that have not responded to the therapy) may then be used for the "control" expression level in the comparison with the test sample.
The "control" expression level for a particular gene in a particular cell type or tissue may alternatively be pre-established by an analysis of gene expression in one or more subjects that have responded to treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). This pre-established reference value (which may be an average expression level taken from multiple subjects that have responded to the therapy) may then be used as the "control" expression level in the comparison with the test sample. In such a comparison, the subject is predicted to respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) if the expression level of any one or more of the genes listed in Table 2 is comparable to or higher than, for example is higher than, the same as, or about the same as (at least 85% but less than 100% of), the pre-established reference value.
A level of expression that is the same as or about the same (at least 85% but less than 100% of the expression level) when compared to a sample (or samples) of any one or more of the genes listed in Table 2 from the same cell type or tissue type as that of the test sample that is obtained from a subject (or subjects) who has not responded to treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) is predictive that a subject will not respond to a therapy comprising lenvatinib or a. pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). Furthermore, a level of expression that is reduced when compared to a sample (or samples) of any one or more of the genes listed in Table 2 from the same cell type or tissue type as that of the test sample that is obtained from a subject (or subjects) who has responded to treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) is predictive that a subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
Table 2' List of Biomarkers for E7080 Responsiveness
Figure imgf000030_0001
Gene Name Symbol Genbank®
Accession No.
Adhesion Molecule with Ig like Domain AMIGOl AA001423
1 ..
Activating Transcription Factor 3 ATF3 AB066566
ATPase, class VI, type 11C ATP11C AI371849
Calcium Channel, Voltage-Dependent, T CACNA1I AB032946 type, Alpha 11 Subunit
Cysteine Conjugate-Beta Lyase, CCBL1 BC022468 Cytoplasmic
Echinoderm Microtubule Associated EML6 BF663308 Protein Like 6
vets Erythroblastosis Virus E26 ERG AI351043 Oncogene Homolog
Family with Sequence Similarity 122A FAM122A BG397561
Guanine Nucleotide Binding Protein (G GNB5 BC011671 protein), Beta 5
Immunoglobulin J Polypeptide, Linker IGJ AV733266 Protein for Immunoglobulin Alpha and
Mu Polypeptides
Insulin Receptor INSR AA485908 and
W84556
Neuropeptide Y Receptor Y6 NPY6R U59431 (pseudogene)
Nucleoporin 188kDa NUP188 AW131863
6 Phosphofructo-2-Kinase/Fructose-2,6- PFKFB2 AB044805 Biphosphatase 2
Phosphatidylinositol-4-Phpsphate 5- PIP5K1 U78581 Kinase, Type I, Beta
Peroxisome Proliferator- Activated PPARD AI201116 Receptor Delta
RAP2A, member of RAS oncogene family RAP2A BE669921
RAR related orphan receptor A RORA AA034012
Serine Hydroxymethyltransferase 1 SHMT1 L23928
(soluble)
Solute Carrier Family 31 (copper SLC31A1 NM_001859 transporters), member 1
Surfeit 4 SURF4 AF078866
Transmembrane Protein 2 TMEM2 NM 013390
Tubulin, Beta Pseudogene 5 TUBBP5 AI433261
Ubiquitin-like Modifier Activating UBA6 AB014773 Enzyme 6
Zinc Finger CCCH-type Containing 11A ZC3H11A W01876
Zinc Finger Protein 529 ZNF529 AL109722
Zinc Finger Protein 542 ZNF542 BE966038
Small Nuclear Ribonucleoprotein 70kDa SNRNP70 NM 003089.4
Clathrin Interactor 1 CLINT1 NM 001195555.1
Plasma Glutamate Carboxypeptidase PGCP NM 016134 An elevated expression level of one or more of the genes listed in Table 3 (relative to a control) is predictive that a subject will not respond to therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) or that a subject will respond less effectively compared to a subject having a
decreased/reduced expression level of one or more of the genes listed in Table 3. In this context, the term "control" means a sample (or samples) from the same cell type or tissue type as that of the test sample that is obtained from a subject (or subjects) who has responded to treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). The term "control" includes a sample obtained in the past and used as a reference for future comparisons to test samples taken from subjects for which therapeutic responsiveness is to be predicted. For example, the "control" expression level for a particular gene in a particular cell type or tissue may be pre-established by an analysis of gene expression in one or more subjects that have responded to treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). This pre-established reference value (which may be an average expression level taken from multiple subjects that have responded to the therapy) may then be used for the "control" expression level in the comparison with the test sample.
The "control" expressiori level for a particular gene in a particular cell type or tissue may alternatively be pre-established by an analysis of gene expression in one or more subjects that have not responded to treatment with lenvatinib or a
pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). This pre- established reference value (which may be an average expression level taken from multiple subjects that have not' responded to the therapy) may then be used as the "control" expression level in the comparison with the test sample. In such a comparison, the subject is predicted to not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) if the expression level of any one or more of the genes listed in Table 3 is comparable to or higher than, for example is higher than, the same as, or about the same as (at least 85% but less than 100% of), the pre-established reference.
A level of expression that is the same as or about the same (at least 85% but less than 100% of the expression leveD when compared to a sample (or samples) of any one or more of the genes listed in Table 3 from the same cell type or tissue type as that of the test sample that is obtained from a subject (or subjects) who has responded to treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) is predictive that a subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). Furthermore, a level of expression that is reduced when compared to a sample (or samples) of any one or more of the genes hsted in Table 3 from the same cell type or tissue type as that of the test sample that is obtained from a subject (or subjects) who has not responded to treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) is predictive that a subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
Table 3: List of Biomarkers for E7080 Non-Responsiveness
Figure imgf000033_0001
No. Gene Name Symbol Genbank®
Accession No.
23 Vacuolar Protein Sorting 37 homolog A VPS37A AW028100
24 Zinc Finger CCCH-Type Containing 6 ZC3H6 AI703114
25 Carboxypeptidase M CPM NM 001874.4
In predicting responsiveness or non-responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), the expression level of one or more of the genes depicted in Tables 2 or 3 can be elevated (or decreased as the case may be) by 1.15 fold, 1.2 fold, 1.3 fold, 1.4 fold, 1.5 fold, 2 fold, 2.5 fold, 3 fold, 3.5 fold, 4 fold, 5 fold, or by at least about 1.15 fold, at least about 1.2 fold, at least about 1.3 fold, at least about 1.4 fold, at least about 1.5 fold, at least about 2 fold, at least about 2.5 fold, at least about 3.0 fold, at least about 3.5 fold, at least about 4.0 fold, or at least about 5 fold or more compared to a control.
Assessing Expression of Biomarkers
Gene expression can be detected as, e.g., protein or mRNA expression of a target gene. That is, the presence" or expression level (amount) of a gene can be determined by detecting and/or measuring the level of mRNA or protein expression of the gene. In some embodiments, gene expression can be detected as the activity of a protein encoded by a gene such as a gene depicted in Table 1.
A variety of suitable methods can be employed to detect and/or measure the level of mRNA expression of a gene. For example, mRNA expression can be determined using Northern blot or dot blot analysis, reverse transcriptase-PCR (RT-PCR; e.g., quantitative RT-PCR), in situ hybridization (e.g., quantitative in situ hybridization) or nucleic acid array (e.g., oligonucleotide arrays or gene chips) analysis. Details of such methods are described below and in, e.g., Sambrook et al., Molecular Cloning: A Laboratory Manual Second Edition vol. 1, 2 and 3. Cold Spring Harbor Laboratory Press: Cold Spring Harbor, New York, USA, Nov. 1989; Gibson et al. (1999) Genome Res., 6(10):995-I00i; and Zhang et al. (2005) Environ. Sci. TechnoL, 39(8):2777-2785," U.S. Publication No. 2004086915,' European Patent No. 0543942," and U.S. Patent No. 7,101,663; the disclosures of each of which are incorporated herein by reference in their entirety.
In one example, the presence or amount of one or more discrete mRNA populations in a biological sample can be determined by isolating total mRNA from the biological sample (see, e.g., Sambrook et al. (supra) and U.S. Patent No. 6,812,341) and subjecting the isolated mRNA to agarose gel electrophoresis to separate the mRNA by size. The size-separated mRNAs are then transferred (e.g., by diffusion) to a solid support such as a nitrocellulose membrane. The presence or amount of one or more mRNA populations in the biological sample can then be determined using one or more detectably labeled-polynucleotide probes, complementary to the mRNA sequence of interest, which bind to and thus render detectable their corresponding mRNA populations. Detectable-labels include, e.g., fluorescent (e.g., umbelliferone, fluorescein, fluorescein isothiocyanate, rhodamine, dichlorotriazinylamine fluorescein, dansyl chloride, allophycocyanin (APC), or phycoerythrin), luminescent (e.g., europium, terbium, Qdot™ nanoparticles supplied by the Quantum Dot Corporation, Palo Alto, CA), radiological (e.g., 125I, 131I, 35S, 32p( 33^ or 3H), and enzymatic (horseradish peroxidase, alkaline phosphatase, beta-galactosidase, or acetylcholinesterase) labels.
In another example, the presence or amount of discrete populations of mRNA (e.g., mRNA encoded by one or more genes depicted in Table l) in a biological sample can be determined using nucleic acid (or oligonucleotide) arrays (e.g., an array described below under "Arrays and Kits"). For example, isolated mRNA from a biological sample can be amplified using RT PCR with, e.g., random hexamer or oligo(dT)-primer mediated first strand synthesis. The amplicons can be fragmented into shorter segments. The RT-PCR step can be used to detectablylabel the amplicons, or, optionally, the amplicons can be detectably-labeled subsequent to the RT-PCR step. For example, the detectable-label can be enzymatically (e.g., by nick-translation or kinase such as T4 polynucleotide kinase) or chemically conjugated to the amplicons using any of a variety of suitable techniques (see, e.g., Sambrook et al., supra). The detectablylabeled-amplicons are then contacted with a plurality of polynucleotide probe sets, each set containing one or more of a polynucleotide (e.g., an oligonucleotide) probe specific for (and capable of binding to) a corresponding amplicon, and where the plurality contains many probe sets each corresponding to a different amplicon.
Generally, the probe sets are bound to a solid support and the position of each probe set is predetermined on the solid support. The binding of a detectably-labeled amplicon to a corresponding probe of a probe set indicates the presence or amount of a target mRNA in the biological sample. Additional methods for detecting mRNA expression using nucleic acid arrays are described in, e.g., U.S. Patent Nos. 5,445,934; 6,027,880; 6,057,100; 6, 156,501; 6,261,776; and 6,576,424; the disclosures of each of which are incorporated herein by reference in their entirety.
Methods of detecting and/or for quantifying a detectable label depend on the nature of the label. The products of reactions catalyzed by appropriate enzymes (where the detectable label is an enzyme,' see above) can be, without limitation, fluorescent, luminescent, or radioactive or they may absorb visible or ultraviolet light. Examples of detectors suitable for detecting such detectable labels include, without limitation, x ray film, radioactivity counters, scintillation counters, spectrophotometers, colorimeters, fluorometers, luminometers, and densitometers.
The expression of a gene can also be determined by detecting and/or measuring expression of a protein encoded by the gene. Methods of determining protein expression are well known in the art. A generally used method involves the use of antibodies specific for the target protein of interest. For example, methods of determining protein expression include, but are not limited to, western blot or dot blot analysis, immunohistochemistry (e.g., quantitative immunohistochemistry), immunocytochemistry, enzyme-linked immunosorbent assay (ELISA), enzyme-linked immunosorbent spot (ELISPOT; Coligan, J. E., et al., eds. (1995) Current Protocols in Immunology. Wiley, New York), or antibody array analysis (see, e.g., U.S. Publication Nos. 20030013208 and 2004171068, the disclosures of each of which are incorporated herein by reference in their entirety). Further description of many of the methods above and additional methods for detecting protein expression can be found in, e.g., Sambrook et al. (supra).
In one example, the presence or amount of protein expression of a gene (e.g., a gene depicted in Table l) can be determined using a western blotting technique. For example, a lysate can be prepared from a biological sample, or the biological sample itself, can be contacted with Laemmli buffer and subjected to sodium-dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). SDS-PAGE-resolved proteins, separated by size, can then be transferred to a filter membrane (e.g., nitrocellulose) and subjected to immunoblotting techniques using a detectably-labeled antibody specific to the protein of interest. The presence or amount of bound detectably-labeled antibody indicates the presence or amount of protein in the biological sample.
In another example, an immunoassay can be used for detecting and/or measuring the protein expression of a gene (e.g., a gene depicted in Table l). As above, for the purposes of detection, an immunoassay can be performed with an antibody that bears a detection moiety (e.g., a fluorescent agent or enzyme). Proteins from a biological sample can be conjugated directly to a solid-phase matrix (e.g., a multi-well assay plate, nitrocellulose, agarose, sepharose, encoded particles, or magnetic beads) or it can be conjugated to a first member of a specific binding pair (e.g., biotin or streptavidin) that attaches to a solid-phase matrix upon binding to a second member of the specific binding pair (e.g., streptavidin or biotin). Such attachment to a solid-phase matrix allows the proteins to be purified away from other interfering or irrelevant components of the biological sample prior to contact with the detection antibody and also allows for subsequent washing of unbound antibody. Here as above, the presence or amount of bound detectably-labeled antibody indicates the presence or amount of protein in the biological sample.
There is no particular restriction as to the form of the antibody and the present disclosure includes polyclonal antibodies, as well as monoclonal antibodies. The antiserum obtained by immunizing animals such as rabbits with a protein of the invention, as well polyclonal and monoclonal antibodies of all classes, human antibodies, and humanized antibodies produced by genetic recombination, are also included.
An intact protein or its partial peptide may be used as the antigen for immunization. As partial peptides of the proteins, for example, the amino (N)-terminal fragment of the protein, and the carboxy (C)-terminal fragment can be given.
A gene encoding a protein of interest or a fragment thereof is inserted into a known expression vector, and, by transforming the host cells with the vector described herein, the desired protein or a fragment thereof is recovered from outside or inside the host cells using standard methods. This protein can be used as the sensitizing antigen. Also, cells expressing the protein, cell lysates, or a chemically synthesized protein of the invention may be also used as a sensitizing antigen.
The mammal that is immunized by the sensitizing antigen is not restricted; however, it is preferable to select animals by considering the compatibility with the parent cells used in cell fusion. Generally, animals belonging to the orders rodentia, lagomorpha, or primates are used. Examples of animals belonging to the order of rodentia that may be used include, for example, mice, rats, and hamsters. Examples of animals belonging to the order of lagomorpha that may be used include, for example, rabbits. Examples of animals belonging to the order of primates that may be used include, for example, monkeys. Examples of monkeys to be used include the infraorder catarrhini (old world monkeys), for example, Macaca fascicularis, rhesus monkeys, sacred baboons, and chimpanzees.
Well-known methods may be used to immunize animals with the sensitizing antigen. For example, the sensitizing antigen is injected intraperitoneally or subcutaneously into mammals. Specifically, the sensitizing antigen is suitably diluted and suspended in physiological saline, phosphate-buffered saline (PBS), and so on, and mixed with a suitable amount of general adjuvant if desired, for example, with Freund's complete adjuvant. Then, the solution is emulsified and injected into the mammal. Thereafter, the sensitizing antigen suitably mixed with Freund's incomplete adjuvant is preferably given several times every 4 to 21 days. A suitable carrier can also be used when immunizing and animal with the sensitizing antigen. After the immunization, the elevation in the' level of serum antibody is detected by usual methods.
Polyclonal antibodies against the proteins of the present disclosure can be prepared as follows. After verifying that the desired serum antibody level has been reached, blood is withdrawn from the mammal sensitized with antigen. Serum is isolated from this blood using conventional methods. The serum containing the polyclonal antibody may be used as the polyclonal antibody, or according to needs, the polyclonal antibody-containing fraction may be further isolated from the serum. For example, a fraction of antibodies that specifically recognize the protein of the invention may be prepared by using an affinity column to which the protein is coupled. Then, the fraction may be further purified by using a Protein A or Protein G column in order to prepare immunoglobulin G or M.
To obtain monoclonal antibodies, after verifying that the desired serum antibody level has been reached in the mammal sensitized with the above-described antigen, immunocytes are taken from the mammal and used for cell fusion. For this purpose, splenocytes can be mentioned as preferable immunocytes. As parent cells fused with the above immunocytes, mammalian myeloma cells are preferably used. More preferably, myeloma cells that have acquired the feature, which can be used to distinguish fusion cells by agents, are used as the parent cell.
The cell fusion between the above immunocytes and myeloma cells can be conducted according to known methods, for example, the method by Milstein et al. (Galfre et al., Methods Enzymol. 73:3-46, 1981).
The hybridoma obtained from cell fusion is selected by culturing the cells in a standard selection medium, for example, HAT culture medium (medium containing hypoxanthine, aminopterin, and thymidine). The culture in this HAT medium is continued for a period sufficient enough for cells (non-fusion cells) other than the objective hybridoma to perish, usually from a few days to a few weeks. Then, the usual limiting dilution method is carried out, and the hybridoma producing the objective antibody is screened and cloned.
Other than the above method for obtaining hybridomas, by immunizing an animal other than humans with the antigen, a hybridoma producing the objective human antibodies having the activity to bind to proteins can be obtained by the method of sensitizing human lymphocytes, for example, human lymphocytes infected with the EB virus, with proteins, proteiri-expressing cells, or lysates thereof in vitro and fusing the sensitized lymphocytes with inyeloma cells derived from human, for example, U266, having a permanent cell division ability.
The monoclonal antibodies obtained by transplanting the obtained hybridomas into the abdominal cavity of a mouse and extracting ascites can be purified by, for example, ammonium sulfate precipitation, protein A or protein G column, DEAE ion exchange chromatography, an affinity column to which the protein of the present disclosure is coupled, and so on. :
Monoclonal antibodies can be also obtained as recombinant antibodies produced by using the genetic engineering technique (see, for example, Borrebaeck C.A.K. and Larrick, J.W., THERAPEUTIC MONOCLONAL ANTIBODIES, Published in the United Kingdom by MACMILLAN PUBLISHERS LTD (1990)). Recombinant antibodies are produced by cloning the encoding DNA from immunocytes, such as hybridoma or antibody-producing sensitized lymphocytes, incorporating into a suitable vector, and introducing this vector into a host to produce the antibody. The present disclosure encompasses such recombinant antibodies as well.
Antibodies or antibody fragments specific for a protein encoded by one or more biomarkers can also be generated by in vitro methods such as phage display.
Moreover, the antibody of the present disclosure may be an antibody fragment or modified-antibody, so long as it binds to a protein encoded by a biomarker of the invention. For instance, Fab, F (ab 2, Fv, or single chain Fv (scFv) in which the H chain Fv and the L chain Fv are suitably linked by a linker (Huston et al., Proa Natl. Acad. Sci. USA, 85:5879-5883, (1988)) can be given as antibody fragments. Specifically, antibody fragments are generated by treating antibodies with enzymes, for example, papain or pepsin. Alternatively, they may be generated by constructing a gene encoding an antibody fragment, introducing this into an expression vector, and expressing this vector in suitable host cells (see, for example, Co et al., J. Immunol., 152:2968-2976, 1994; Better et al., Methods EnzymoL, 178:476 496, 1989; Pluckthun et al., Methods EnzymoL, 178:497-515, 1989; Lamoyi, Methods EnzymoL, 121:652 663, 1986; Rousseaux et al., Methods EnzymoL, 121:663-669, 1986; Bird et al., Trends BiotechnoL, 9:132- 137, 1991).
The antibodies may be conjugated to various molecules, such as polyethylene glycol (PEG), fluorescent substances, radioactive substances, and luminescent substances. Methods to attach such moieties to an antibody are already established and conventional in the field (see, e.g., US 5,057,313 and 5, 156,840).
Examples of methods that assay the antigen-binding activity of the antibodies include, for example, measurement of absorbance, enzyme-linked immunosorbent assay (ELISA), enzyme immunoassay (EIA), radioimmunoassay (RIA), and/or immunofluorescence. For example, when using ELISA, a protein encoded by a biomarker of the invention is added to a plate coated with the antibodies of the present disclosure, and then, the antibody sample, for example, culture supernatants of antibody-producing cells, or purified antibodies are added. Then, secondary antibody recognizing the primary antibody, which is labeled by alkaline phosphatase and such enzymes, is added, the plate is incubated and washed, and the absorbance is measured to evaluate the antigen-binding activity after adding an enzyme substrate such as p- nitrophenyl phosphate. As the protein, a protein fragment, for example, a fragment comprising a C-terminus, or a fragment comprising an N-terminus may be used. To evaluate the activity of the antibody of the invention, BIAcore (Pharmacia) may be used.
By using these methods, the antibody of the invention and a sample presumed to contain a protein of the invention are contacted, and the protein encoded by a biomarker of the invention is detected or assayed by detecting or assaying the immune complex formed between the above-mentioned antibody and the protein.
Mass spectrometry based quantitation assay methods, for example, but not limited to, multiple reaction monitoring (MRM)-based approaches in combination with stable-isotope labeled internal standards, are an alternative to immunoassays for quantitative measurement of proteins. These approaches do not require the use of antibodies and so the analysis can be performed in a cost- and time- efficient manner (see, for example, Addona et al., Nat. Biotechnol., 27:633-641, 2009," Kuzyk et al., Mol Cell Proteomics, 8U860-1877, 2009; Paulovich et al., Proteomics Clin. Appl, 2 1386- 1402, 2008). In addition, MRM offers superior multiplexing capabilities, allowing for the simultaneous quantification of numerous proteins in parallel. The basic theory of these methods have been well-established and widely utilized for drug metabolism and pharmacokinetics analysis of small molecules.
Methods for detecting or measuring gene expression (e.g., mRNA or protein expression) can optionally be performed in formats that allow for rapid preparation, processing, and analysis of multiple samples. This can be, for example, in multi-welled assay plates (e.g., 96 wells or 386 wells) or arrays (e.g., nucleic acid chips or protein chips). Stock solutions for various reagents can be provided manually or robotically, and subsequent sample preparation (e.g., RT-PCR, labeling, or cell fixation), pipetting, diluting, mixing, distribution, washing, incubating (e.g., hybridization), sample readout, data collection (optical data) and/or analysis (computer aided image analysis) can be done robotically using commercially available analysis software, robotics, and detection instrumentation capable of detecting the signal generated from the assay. Examples of such detectors include, but are not limited to, spectrophotometers, luminometers, fluorimeters, and devices that measure radioisotope decay. Exemplary high- throughput cell-based assays (e.g., detecting the presence or level of a target protein in a cell) can utilize ArrayScan® VTI HCS Reader or KineticScan® HCS Reader technology (Cellomics Inc., Pittsburg, PA).
In some embodiments, the expression level of two genes, three genes, four genes, five genes, six genes, seven genes, eight genes, nine genes, 10 genes, 11 genes, 12 genes, 13 genes, 14 genes, 15 genes, 16 genes, 17 genes, 18 genes, 19 genes, 20 genes, 21 genes, 22 genes, 23 genes, at least 24 genes, at least 25 genes or more, or at least two genes, at least three genes, at least four genes, at least five genes, at least six genes, at least seven genes, at least eight genes, at least nine genes, at least 10 genes, at least 11 genes, at least 12 genes, at least 13 genes, at least 14 genes, at least 15 genes, at least 16 genes, at least 17 genes, at least 18 genes, at least 19 genes, at least 20 genes, at least 21 genes, at least 22 genes, at least 23 genes, at least 24 genes, or at least 25 genes or more can be assessed and/or measured.
To aid in detecting the presence or level of expression of one or more of the genes depicted in Table 1, any part of the nucleic acid sequence of the genes can be used, e.g., as hybridization polynucleotide probes or primers (e.g., for amplification or reverse transcription). The probes and primers can be oligonucleotides of sufficient length to provide specific hybridization to an RNA , DNA, cDNA, or fragments thereof derived from a biological sample. Depending on the specific application, varying hybridization conditions can be employed to achieve varying degrees of selectivity of a probe or primer towards target sequence. The primers and probes can be detectably- labeled with reagents that facilitate detection (e.g., fluorescent labels, chemical labels (see, e.g., U.S. Patent Nos. 4,582,789 and 4,563,417), or modified bases).
Standard stringency conditions are described by Sambrook, et al. (supra) and Haymes, et al. Nucleic Acid Hybridization, A Practical Approach, IRL Press,
Washington, D.C. (1985). In order for a nucleic acid molecule to serve as a primer or probe it need only be sufficiently complementary in sequence to be able to form a stable double-stranded structure under the particular hybridization conditions (e.g., solvent and salt concentrations) employed.
Hybridization can be used to assess homology between two nucleic acid sequences. A nucleic acid sequence described herein, or a fragment thereof, can be used as a hybridization probe according to standard hybridization techniques. The hybridization of a probe of interest (e.g., a probe containing a portion of a nucleotide sequence described herein or its complement) to DNA, RNA, cDNA, or fragments thereof from a test source is an indication of the presence of DNA or RNA
corresponding to the probe in the test source. Hybridization conditions are known to those skilled in the art and can be found in Current Protocols in Molecular Biology, John Wiley & Sons, N.Y., 6.3.1-6.3.6, 1991. Moderate hybridization conditions are defined as hybridization in 2X sodium chloride/sodium citrate (SSC) at 30°C, followed by a wash in 1 X SSC, 0.1% SDS at 50°C. Highly stringent conditions are defined as hybridization in 6X SSC at 45°C, followed by a wash in 0.2 X SSC, 0.1% SDS at 65°C.
Primers can be used in in a variety of PCR type methods. For example, polymerase chain reaction (PCR) techniques can be used to amplify specific sequences from DNA as well as RNA, including sequences from total genomic DNA or total cellular RNA. The PCR primers are designed to flank the region that one is interested in amplifying. Primers can be located near the 5' end, the 3' end or anywhere within the nucleotide sequence that is to be amplified. The amplicon length is dictated by the experimental goals. For qPCR, the target length is closer to 100 bp and for standard PCR, it is near 500 bp. Generally, sequence information from the ends of the region of interest or beyond is employed to design oligonucleotide primers that are identical or similar in sequence to opposite strands of the template to be amplified. PCR primers can be chemically synthesized, either as a single nucleic acid molecule (e.g., using automated DNA synthesis in the 3' to 5' direction using phosphoramidite technology) or as a series of oligonucleotides. For example, one or more pairs of long oligonucleotides (e.g., >100 nucleotides) can be synthesized that contain the desired sequence, with each pair containing a short segment of complementarity (e.g., about 15 nucleotides) such that a duplex is formed when the oligonucleotide pair is annealed. DNA polymerase is used to extend the oligonucleotides, resulting in a single, double-stranded nucleic acid molecule per oligonucleotide pair.
In addition, the nucleic acid sequences or fragments thereof (e.g.,
oligonucleotide probes) can be used in nucleic acid arrays (such as the nucleic acid arrays described below under "Arrays") for detection and/or quantitation of gene expression.
Arrays
Nucleic acid arrays including the nucleic acid biomarkers disclosed herein are useful in, e.g., detecting gene expression and/or measuring gene expression levels. The arrays are also useful for e.g., in predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), for identifying subjects who can benefit from a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), and for steering subjects who would not likely benefit from a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) to other cancer therapies.
An array is an orderly arrangement of samples where matching of known and unknown DNA samples is done based on base pairing rules (e.g., Adenosine pairs with Thymine or Uracil; Guanosine pairs with Cytosine). A typical microarray experiment involves the hybridization of an mRNA, a cDNA molecule, or fragments thereof, to a DNA template from which it is originated or derived. Many DNA samples are used to construct an array. An array experiment makes use of common assay systems such as microplates or standard blotting membranes. The sample spot sizes are typically less than 200 microns in diameter and the array usually contains thousands of spots. Thousands of spotted samples known as probes (with known identity) are immobilized on a substrate (e.g., a microscope glass slides, silicon chips, nylon membrane). The spots can be DNA, cDNA, or oligonucleotides. These are used to determine complementary binding of the unknown sequences thus allowing parallel analysis for gene expression and gene discovery. An experiment with a single DNA chip can provide information on thousands of genes simultaneously. An orderly arrangement of the probes on the support is important as the location of each spot on the array is used for the identification of a gene. The amount of mRNA bound to each site on the array indicates the expression level of the various genes that are included on the array. By using an array containing many DNA samples, one can determine, in a single experiment, the expression levels of hundreds or thousands of genes by measuring the amount of mRNA bound to, each site on the array. With the aid of a computer, the amount of mRNA bound to the spots on the microarray can be precisely measured, generating a profile of gene expression in the cell.
The two main DNA microarray platforms that are generally used are cDNA and oligonucleotide microarrays. cDNA microarrays are made with long double-stranded DNA molecules generated by enzymatic reactions such as PCR (Schena.M. et al., Science, 270:467-470 (1995)), while oligonucleotide microarrays employ oligonucleotide probes spotted by either robotic deposition or in situ synthesis on a substrate
(Lockhart,D.J. et al., Nat. Biotechnol., 14, 1675-1680 (1996)). The arrays are generally designed to include oligonucleotide probes targeting regions of low sequence similarity.
The nucleic acid arrays can include two, three, four five, six, seven, eight, nine, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, or 53 polynucleotides that hybridize to each of the two, three, four five, six, seven, eight, nine, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, or 53 genes respectively listed in Table 1, or any nucleic acid derived therefrom (e.g., mRNA, cDNA, or fragments of mRNA or cDNA).
The nucleic acid arrays can include at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least 10, at least 11, at least 12, at least 15, at least 20, at least 22, at least 24, at least 25, at least 26, at least 27, at least 28, at least 29, at least 30, at least 31, at least 32, at least 33, at least 34, at least 35, at least 36, at least 37, at least 38, at least 39, at least 40, at least 41, at least 42, at least 43, at least 44, at least 45, at least 46, at least 47, at least 48, at least 49, at least 50, at least 51, or at least 52 polynucleotides that hybridize to each of at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least 10, at least 11, at least 12, at least 15, at least 20, at least 22, at least 24, at least 25, at least 26, at least 27, at least 28, at least 29, at least 30, at least 31, at least 32, at least 33, at least 34, at least 35, at least 36, at least 37, at least 38, at least 39, at least 40, at least 41, at least 42, at least 43, at least 44, at least 45, at least 46, at least 47, at least 48, at least 49, at least 50, at least 51, or at least 52 genes respectively listed in Table 1.
A polynucleotide of the array can include coding sequence or non-coding sequence (e.g., exons, introns, or 5' or 3' regulatory sequences), e.g., of a gene depicted in Table 1. The polynucleotide can include a sequence of the sense strand or the anti- sense strand of the coding sequence of a gene depicted in Table 1. The polynucleotide can also be single or double-stranded and of variable length. In some embodiments, the length of one strand of a polynucleotide that hybridizes to a gene (e.g., depicted in Table l) or any nucleic acid derived therefrom ((e.g., mRNA, cDNA, or fragments of mRNA or cDNA) can be six nucleotides, seven nucleotides, eight nucleotides, nine nucleotides, 10 nucleotides, 11 nucleotides, 12 nucleotides, 13 nucleotides, 14 nucleotides, 15 nucleotides, 20 nucleotides, 25 nucleotides, 30 nucleotides, 35 nucleotides, 40 nucleotides, 45 nucleotides, 50 nucleotides, 55 nucleotides, 60 nucleotides, 65 nucleotides, 70 nucleotides, 75 nucleotides, 80 nucleotides, 85 nucleotides, 90 nucleotides, 95 nucleotides, 100 nucleotides, 105 nucleotides, 110 nucleotides, 115 nucleotides, 120 nucleotides, 125 nucleotides, 130 nucleotides, 135 nucleotides, 136 nucleotides, 137 nucleotides, 138 nucleotides, 139 nucleotides, 140 nucleotides, 141 nucleotides, 142 nucleotides, 143 nucleotides, 144 nucleotides, 145 nucleotides, 146 nucleotides, 147 nucleotides, 148 nucleotides, 149 nucleotides, 150 nucleotides, 151 nucleotides, 152 nucleotides, 153 nucleotides, 154 nucleotides, 155 nucleotides, 156 nucleotides, 157 nucleotides, 158 nucleotides, 159 nucleotides, 160 nucleotides, 165 nucleotides, 170 nucleotides, 175 nucleotides, 180 nucleotides, 185 nucleotides, 190 nucleotides, 195 nucleotides, 200 nucleotides, 210 nucleotides, 220 nucleotides, 230 nucleotides, 240 nucleotides, or 250 nucleotides. In some
embodiments, the length of one strand of a polynucleotide that hybridizes to a gene (e.g., depicted in Table l) or any nucleic acid derived therefrom ((e.g., mRNA, cDNA, or fragments of mRNA or cDNA) can be about six nucleotides, about seven nucleotides, about eight nucleotides, about nine nucleotides, about 10 nucleotides, about 12 nucleotides, about 13 nucleotides, about 14 nucleotides, about 15 nucleotides, about 20 nucleotides, about 25 nucleotides, about 30 nucleotides, about 35 nucleotides, about 40 nucleotides, about 50 nucleotides, about 75 nucleotides, about 100 nucleotides, about 150, about 155, about 160, about 165, about 170, about 175, about 180, about 190, or about 200 or more nucleotides in length. In certain embodiments, the probe is between 25 and 35 nucleotides, between 35 and 45 nucleotides, between 65 and 75 nucleotides, between 25 and 200 nucleotides, between 50 and 175 nucleotides, between 75 and 165 nucleotides, between 100 and 200, nucleotides, between 125 and 250 nucleotides, or between 125 and 1000 nucleotides in length. A longer polynucleotide often allows for higher stringency hybridization and wash conditions. The polynucleotide can be DNA, RNA, modified DNA or RNA, or a hybrid, where the nucleic acid contains any combination of deoxyribo- and ribo-nucleotides, and any combination of uracil, adenine, thymine, cytosine and guanine, as well as other bases such as inosine, xanthine, and hypoxanthine.
The polynucleotide arrays can be attached to a solid support, e.g., a porous or non-porous material that is insoluble. The substrate can be associated with the support in variety of ways, e.g., covalently or non-covalently bound.
A support can be composed of a natural or synthetic material, an organic or inorganic material. The composition of the solid support on which the polynucleotide sequences are attached (either 5' or 3' terminal attachment) generally depend on the method of attachment (e.g., covalent attachment). Suitable solid supports include, but are not limited to, plastics, resins, polysaccharides, silica or silica-based materials, functionalized glass, modified silicon, carbon, metals, inorganic glasses, membranes, nylon, natural fibers such as silk, wool and cotton, or polymers. The material comprising the solid support can .have reactive groups such as carboxy, amino, or hydroxyl groups, which are used for attachment of the polynucleotides. Polymeric solid supports can include, e.g., polystyrene, polyethylene glycol tetraphthalate, polyvinyl acetate, polyvinyl chloride, polyvinyl pyrrolidone, polyacrylonitrile, polymethyl methacrylate, polytetrafluoroethylene, butyl rubber, styrenebutadiene rubber, natural rubber, polyethylene, polypropylene, (poly)tetrafluoroethylene, (poly)vinylidenefluoride, polycarbonate, or polymethylpentene (see, e.g., U.S. Patent No. 5,427,779, the disclosure of which is hereby incorporated by reference in its entirety). Alternatively, the polynucleotide sequences can be attached to the solid support without the use of such functional groups.
Each polynucleotide (of a plurality of polynucleotides) on an array can be immobilized at predetermined positions such that each polynucleotide can be identified by its position. Exemplary polynucleotide arrays for use in the methods and kits described herein are described in, e.g., U.S. Patent Nos. 6,197,599; 5,902,723; and 5,871,928; the disclosures of each of which are incorporated herein by reference in their entirety).
The arrays can contain multiple nucleic acids derived from a single gene. These multiple nucleic acids may be from one or more regions of the gene of interest. In some embodiments of any of the arrays described herein, the array of polynucleotides can have less than 100,000 (e.g., less than 90,000; less than 80,000; less than 70,000; less than 60,000; less than 50,000; less than 40,000; less than 30,000; less than 20,000; less than 15,000; less than 10,000; less than 5,000; less than 4,000." less than 3,000; less than 2,000; less than 1,500; less than 1,000; less than 750; less than 500, less than 200, less than 100, or less than 50) different polynucleotides.
The polynucleotide arraysscan also be conjugated to microscopic beads or solid support particles. Many suitable solid support particles are known in the art and illustratively include, e.g., particles, such as Luminex®-type encoded particles, magnetic particles, and glass particles.
Exemplary particles that can be used can have a variety of sizes and physical properties. Particles can be selected to have a variety of properties useful for particular experimental formats. For example, particles can be selected that remain suspended in a solution of desired viscosity or to readily precipitate in a solution of desired viscosity. Particles can be selected for ease of separation from sample constituents, for example, by including purification tags for separation with a suitable tag-binding material, paramagnetic properties for magnetic separation, and the like.
This application also provides kits. In some embodiments, the kits include that can be used to identify or detect any of the biomarkers of Table 1 or thei expression or expression levels. In some embodiments, the kits include any of the nucleic acid arrays described herein. The kits can, optionally, contain instructions for detecting and or measuring the level of one or more genes in a biological sample.
The kits can optionally include, e.g., a control biological sample or control labeled-amplicon set containing known amounts of one or more amplicons recognized by nucleic acid probes of the array. In some instances, the control can be an insert (e.g., a paper insert or electronic medium such as a CD, DVD, or floppy disk) containing expression level ranges of one or more genes predictive of a response to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
In some embodiments, the kits can include one or more reagents for processing a biological sample. For example, a kit can include reagents for isolating mRNA from a biological sample and/or reagents for converting the isolated mRNA to cDNA (e.g., reverse transcriptase, primers for reverse transcription or PCR amplification, or dNTPs). The kits can also, optionally, contain one or more reagents for detectably labeling an mRNA, an mRNA amplicon, genomic DNA or DNA amplicon, which reagents can include, e.g., an enzyme such as a Klenow fragment of DNA polymerase, T4 polynucleotide kinase, one or more detectablylabeled dNTPs, or detectablylabeled gamma phosphate ATP (e.g., 33P-ATP).
In some embodiments, the kits can include a software package for analyzing the results of, e.g., a microarray analysis or expression profile.
The kits can also include one or more antibodies for detecting the protein expression of any of the genes described herein. For example, a kit can include (or in some cases consist of) a plurality of antibodies capable of specifically binding to one or more proteins encoded by any of the genes depicted in Table 1 and optionally, instructions for detecting the one or more proteins and/or a detection antibody comprising a detectablylabeled. antibody that is capable of binding to at least one antibody of the plurality. In some embodiments, the kits can include antibodies that recognize one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, or 52 proteins encoded by genes depicted in Table 1.
The kits described herein can also, optionally, include instructions for administering a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), where the expression level of one or more genes detectable by the array predicts that a subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). The kits can contain instructions for administering a variety of non lenvatinib therapies where the expression level of one or more genes detectable by the array predicts that a subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
Biological Samples
Suitable biological samples for the methods described herein include any biological fluid, cell, tissue, or fraction thereof, which includes analyte biomolecules of interest such as nucleic acid (e.g., DNA or mRNA) or protein. A biological sample can be, for example, a specimen obtained from a subject (e.g., a mammal such as a human) or can be derived from such a subject. For example, a sample can be a tissue section obtained by biopsy, or cells that are placed in or adapted to tissue culture. A biological sample can also be a biological fluid such as urine, blood, plasma, serum, saliva, semen, sputum, cerebral spinal fluid, tears, or mucus, or such a sample absorbed onto a paper or polymer substrate. A biological sample can also include a skin sample, a tumor sample, circulating tumor cells, and circulating DNA. In specific embodiments, the biological sample is a tumor cell(s) or a cell(s) obtained from a region of the subject suspected of containing a tumor or a pre-cancerous lesion. A biological sample can be further fractionated, if desired, to a fraction containing particular cell types. For example, a blood sample can be fractionated into serum or into fractions containing particular types of blood cells such as red blood cells or white blood cells (leukocytes). If desired, a sample can be a combination of samples from a subject such as a combination of a tissue and fluid sample.
The biological samples can be obtained from a subject, e.g., a subject having, suspected of having, or at risk of developing, a cancer. Any suitable methods for obtaining the biological samples can be employed, although exemplary methods include, e.g., phlebotomy, swab (e.g., buccal swab), or fine needle aspirate biopsy procedure. Non-limiting examples of tissues susceptible to fine needle aspiration include lymph node, lung, thyroid, breast, skin, and liver. Samples can also be collected, e.g., by microdissection (e.g., laser capture microdissection (LCM) or laser microdissection (LMD)), bladder wash, smear (PAP smear), or ductal lavage.
Methods for obtaining and/or storing samples that preserve the activity or integrity of molecules (e.g., nucleic acids or proteins) in the sample are well known to those skilled in the art. For example, a biological sample can be further contacted with one or more additional agents such as appropriate buffers and/or inhibitors, including nuclease, protease and phosphatase inhibitors, which preserve or minimize changes in the molecules (e.g., nucleic acids or proteins) in the sample. Such inhibitors include, for example, chelators such as ethylenediamine tetraacetic acid (EDTA), ethylene glycol bis(P-aminoethyl ether) Ν,Ν,ΝΙ,ΝΙ-tetraacetic acid (EGTA), protease inhibitors such as phenylmethylsulfonyl fluoride (PMSF), aprotinin, leupeptin, antipain and the like, and phosphatase inhibitors such as phosphate, sodium fluoride, vanadate and the like. Appropriate buffers and conditions for isolating molecules are well known to those skilled in the art and can be varied depending, for example, on the type of molecule in the sample to be characterized (see, for example, Ausubel et al. Current Protocols in Molecular Biology (Supplement 47), John Wiley & Sons, New York (1999); Harlow and Lane, Antibodies: A Laboratory Manual (Cold Spring Harbor Laboratory Press (1988); Harlow and Lane, Using Antibodies: A Laboratory Manual, Cold Spring Harbor Press (1999); Tietz Textbook of Clinical Chemistry, 3rd ed. Burtis and Ashwood, eds. W.B. Saunders, Philadelphia, (1999)). A sample also can be processed to eliminate or minimize the presence of interfering substances. For example, a biological sample can be fractionated or purified to remove one or more materials that are not of interest. Methods of fractionating or purifying a biological sample include, but are not limited to, chromatographic methods such as liquid chromatography, ion-exchange
chromatography, size-exclusion chromatography, or affinity chromatography.
For use in the methods described herein, a sample can be in a variety of physical states. For example, a sample can be a liquid or solid, can be dissolved or suspended in a liquid, can be in an emulsion or gel, or can be absorbed onto a material.
Methods of Predicting Responsiveness to a Therapy Comprising Lenvatinib or a Pharmaceutically Acceptable Salt Thereof
This disclosure also provides methods of predicting whether a subject will respond, or have reduced or no response, to treatment with lenvatinib or a
pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). The methods involve assessing the expression level of one or more genes listed in Table 1 in a biological sample from a subject. If the expression level of certain genes in the biological sample is elevated or decreased (compared to a control), it is possible to determine whether the subject would benefit from treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
An elevated expression level, as compared to a control, of any one or more of the following genes: SLC31A1, PFKFB2, NPY6R, IGJ, NUP188, ERG, INSR, ZNF529, PIP5K1, TMEM2, TUBBP5, UBA6, SURF4, FAM122A, AMIGOl, ADAMTS9, RORA, ZNF542, PPARD, ATP11C, EML6, GNB5, ATF3, ZC3H11A, CCBL1, SHMT1, RAP2A, PGCP, SNRNP70, CLINTl, and CACNAII is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). Conversely, an expression level of these genes that is decreased or at a level that is about the same as (at least 85% but less than 100% of) a control is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
In contrast, an elevated expression level, as compared to a control, of any one or more of the following genes: TNKS, TARBP2, TTLL4, CHKA, PSPH, CPM, MDM1, HIPK2, DSCCl, STAG3L4, MSRB2, GDPD5, GJB2, ARRDC4, COPS7B, NEIL2, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDC1/PDXDC2, ANKRD13D, NAPEPLD, C70RF and IL22RA2 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), or will have a reduced responsiveness to a therapy comprising lenvatinib or a
pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) compared to a subject having lower/reduced expression levels of the one or more genes. Conversely, an expression level of these genes that is decreased or at a level that is about the same as (at least 85% but less than 100% of) a control is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
As noted above, the methods described herein can involve, assessing the expression level (e.g., mRNA or protein expression level) of one or more genes (e.g., one or more genes depicted in Table l), wherein the expression level of one or more of the genes predicts the response of a' subject. to treatment comprising a lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). "Assessing" can include, e.g., comparing the expression of one or more genes in a test biological sample with a known or a control expression level (e.g., in a reference biological sample) of the particular gene(s) of interest. For example, the expression level of one or more genes in a test biological sample can be compared to the corresponding expression levels in a subject who has responded or failed to respond to lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), or an average expression level of multiple (e.g., two, three, four, five, six, seven, eight, nine, 10, 15, 20, 25, 30, 35, or 40 or more) subjects, of the same species, who have responded or have failed to respond to lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). Assessing can also include determining if the expression level of one or more genes (e.g., one or more genes as depicted in Table l) falls within a range of values predetermined as predictive of responsiveness or non-responsiveness of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). In some embodiments, assessing can be, or include, determining if the expression of one or more genes (e.g., one or more of the genes depicted in Table l) falls above or below a predetermined cut-off value. A cut-off value is typically an expression level of a gene, or ratio of the expression level of a gene with the expression level of another gene, above or below which is considered predictive of responsiveness or non- responsiveness of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). Thus, in accordance with the methods (and compositions) described herein, a reference expression level of a gene (e.g., a gene depicted in Table 1) is identified as a cut-off value, above or below of which is predictive of responsiveness or non-responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). It is understood that a lenvatinib (e.g., lenvatinib mesylate) therapy response profile can be interpreted as a whole (the expression level of all genes in the profile), in parts (certain collections or groups of genes (e.g., 8 or 24 genes) within the profile), or on a gene-by-gene basis.
Some cut-off values are not absolute in that clinical correlations can still remain significant over a range of values on either side of the cutoff; however, it is possible to select an optimal cut-off value (e.g. varying H-scores) of expression levels of genes for a particular sample types. Cut-off values determined for use in the methods described herein can be compared with, e.g., published ranges of expression levels but can be individualized to the methodology used and patient population. It is understood that improvements in optimal cut-off values could be determined depending on the sophistication of statistical methods used and on the number and source of samples used to determine reference level values for the different genes and sample types. Therefore, established cut-off values can be adjusted up or down, on the basis of periodic re-evaluations or changes in methodology or population distribution.
The reference expression level of one or more genes can be determined by a variety of methods. The reference level can be determined by comparison of the expression level of a gene of interest in, e.g., populations of subjects (e.g., patients) that are responsive to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) or not responsive to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof. This can be accomplished, for example, by histogram analysis, in which an entire cohort of patients are graphically presented, wherein a first axis represents the expression level of a gene and a second axis represents the number of subjects in the cohort whose sample contain one or more expression levels at a given amount. Determination of the reference expression level of a gene can then be made based on an amount which best distinguishes these separate groups. The reference level can be a single number, equally applicable to every subject, or the reference level can vary, according to specific subpopulations of subjects. For example, older subjects can have a different reference level than younger subjects for the same metabolic disorder. In addition, a subject with more advanced disease (e.g., a more advanced form of a disease treatable by lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate)) can have a different reference value than one with a milder form of the disease.
After predicting that a subject will respond or will not respond to a treatment comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), a medical practitioner (e.g., a doctor) can select and administer the appropriate therapeutic modality for the subject (e.g., lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) or a hon-lenvatinib therapy, respectively). Selecting a therapy for a subject can be, e.g.: (i) writing a prescription for a medicament; (ii) giving (but not necessarily administering) a medicament to a subject (e.g., handing a sample of a prescription medication to a patient while the patient is at the physician's office); (iii) communication (verbal, written (other than a prescription), or electronic (email, post to a secure site)) to the patient of the suggested or recommended therapeutic modality (e.g., lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) or a non-lenvatinib therapy); or (iv) identifying a suitable therapeutic modality for;a subject and disseminating the information to other medical personnel, e.g., by way of patient record. The latter (iv) can be useful in a case where, e.g., more than one therapeutic agent are to be administered to a patient by different medical practitioners.
The methods described herein can also be used to generate a lenvatinib (e.g., lenvatinib mesylate) therapy response profile for a subject. The profile can include information that indicates whether one or more genes, such as one or more genes depicted in Table 1, are expressed (e.g., yes or no) and/or information that indicates the expression level of one or more genes (e.g., one or more genes depicted in Table 1). A lenvatinib therapy response profile can include the expression level of one or more additional genes and/or other proteomic markers, serum markers (e.g., lactate dehydrogenase dosage), or clinical markers. The response profiles described herein can contain information on the expression or expression level of at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least 10, at least 11, at least 12, at least 13, at least 14, at least 15, at least 16, at least 17, at least 18, at least 19, at least 20, at least 21, at least 22, at least 23, at least 24, or at least 25 genes listed in Table 1. The resultant information (lenvatinib therapy response profile) can be used for predicting the response of a subject (e.g., a human patient) to a treatment comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). In addition, the response profiles can be used in predicting the response of a subject to a variety of therapies and/or a variety of disease states since, e.g., the expression levels of one or more of the genes (e.g., one or more of the genes depicted in Table l) examined can be indicative of such responses or disorders, whether or not physiologic or behavioral symptoms of the disorder have become apparent.
Responsiveness (and, conversely, non-responsiveness) of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) can be classified in several ways and classification is dependent on the subject's disease (e.g., skin cancer, a liver cancer, a lung cancer, a brain tumor, a thyroid cancer, an ovarian cancer, a renal cancer, an endometrial cancer, or any other of the diseases treatable by therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate)), the severity of the disease, and the particular medicament the subject is administered. In the simplest sense,
responsiveness is any decrease in the disease state as compared to pre-treatment, and non-responsiveness is the lack of any change in the disease state as compared to pre- treatment. Responsiveness of a subject (e.g., a human) with a cancer can be classified based on one or more of a number of objective clinical indicia such as, but not limited to, tumor size, Clinical Benefit (CB), Progression Free Survival (PFS), Complete Response (CR), Overall Survival (OS), and Time-to-Progression (TTP).
"Clinical benefit" refers to having one of the following statuses— Complete Response (CR), Partial Response (PR); or Stable Disease (SD) with 6 months or more progression free survival (PFS). "Complete Response" means complete disappearance of all target lesions. "Partial Response" means at least 30% decrease in the sum of the longest diameter (LD) of target lesions, taking as reference the baseline summed LD. "Progressive Disease" (PD) means at least 20% increase in the sum of the LD of target lesions, taking as reference the smallest summed LD recorded since the treatment started, or the appearance of one or more new lesions. "Stable Disease" means neither sufficient shrinkage of the target lesions to qualify for PR nor sufficient increase to qualify for progressive disease (PD), taking as reference the smallest summed LD since the treatment started. "Progression Free Survival" (PFS) refers to the period from start date of treatment to the last date before entering PD status.
"Tumor shrinkage" (TS) means percent change of sum of diameters of target lesions, taking as reference the baseline sum diameters.
"Time to Progression" (TTP) is defined as the time from randomization until objective tumor progression. "Randomization" means randomization of a patient into a test group or a control group when therapy plan for a patient is determined.
"Overall Survival" (OS) ,is defined as the time from randomization until death from any cause.
It is understood that a lenvatinib (e.g., lenvatinib mesylate) response profile can be in electronic form (e.g., an electronic patient record stored on a computer or other electronic (computer-readable) media such as a DVD, CD, or floppy disk) or written form. The lenvatinib (e.g., lenvatinib mesylate) response profile can also include information for several (e.g., two, three, four, five, 10, 20, 30, 50, or 100 or more) subjects (e.g., human patients). Such multi-subject response profiles can be used, e.g., in analyses (e.g., statistical analyses) of particular characteristics of subject cohorts.
Methods of Treatment
The methods disclosed herein enable the assessment of a subject for responsiveness and non-responsiveness to lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). A subject who is likely to respond to lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) can be administered lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), whereas subjects who are unlikely to respond to lenvatinib or a
pharmaceutically acceptable salt thereof can be administered a non-lenvatinib therapy.
The methods of this disclosure also enable the classification of subjects into groups of subjects that are likely to benefit, and groups of subjects that are unlikely to benefit, from treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). The ability to select such subjects from a pool of subjects who are being considered for treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) is beneficial for effective treatment and reduction of adverse side effects of treatment.
Lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) shows potent anti-tumor effects in xenograft models of various tumors by inhibiting angiogenesis. The subjects who are considered for treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) include, but are not limited to, subjects having, suspected of having, or likely to develop a skin cancer (e.g., melanoma), a liver cancer (e.g., hepatocellular carcinoma), a lung cancer (e.g., a non-small lung cancer), a brain tumor (e.g., a glioma), a thyroid cancer, an ovarian cancer, a renal cancer (e.g., renal cell carcinoma), or an endometrial cancer.
In one embodiment, the subject to be treated with lenvatinib or a
pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) has, is suspected of having, or is likely to develop a skin cancer. Skin cancer is the uncontrolled growth of abnormal skin cells. If left unchecked, these cancer cells can spread from the skin into other tissues and organs. There are different types of skin cancer such as basal cell carcinoma (the most common skin cancer), squamous cell carcinoma, Kaposi's sarcoma, Merkel cell carcinoma, cutaneous lymphoma, and melanoma. Melanoma is a malignant tumor of melanocytes that is less common than other skin cancers, but is more dangerous and causes the majority of skin cancer-related deaths. In a specific embodiment, the subject to be treated with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) has, is suspected of having, or is likely to develop a melanoma.
If the subject is likely to respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (based on the determination of expression or expression levels of the biomarkers in Table 2), the subject can then be administered an effective amount of the lenvatinib compound (e.g., lenvatinib mesylate). An effective amount of the compound can suitably be determined by a health care practitioner taking into account, for example, the characteristics of the patient (age, sex, weight, etc.), the progression of the disease, and prior exposure to the drug. If the subject is unlikely or less likely to respond to a therapy comprising lenvatinib or a
pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) (based on the determination of expression or expression levels of the biomarkers in Table 3), the subject can then be administered a therapy that does not comprise lenvatinib. These therapies include, but are not limited to, dacarbazine, temozolomide, ipilimumab, interleukin-2, interferon, inhibitors of BRAF kinase, and "standard of care" treatment (i.e., prevailing standard of care as determined by the health care practitioner or as specified in the clinical study) such as investigational drugs and chemotherapy.
Subjects of all ages can be affected by disorders treatable by lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). Therefore, a biological sample used in a methods described herein can be obtained from a subject (e.g., a human) of any age, including a child, an adolescent, or an adult, such as an adult having, or suspected of having, a disease (e.g., melanoma) treatable by lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
The methods can also be applied to individuals at risk of developing a cancer treatable by lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). Such individuals include those who have (i) a family history of (a genetic predisposition for) such disorders or Gi) one or more risk factors for developing such disorders.
After classifying or selecting a subject based on whether the subject will respond or will not respond to lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), a medical practitioner (e.g., a doctor) can administer the appropriate therapeutic modality to the subject (e.g., a lenvatinib (e.g., lenvatinib mesylate) therapy or a non-lenvatinib therapy, respectively). Methods of administering lenvatinib and non-lenvatinib therapies are well known in the art.
It is understood that any therapy described herein (e.g., a therapy comprising a lenvatinib or a therapy that does not comprise a lenvatinib) can include one or more additional therapeutic agents. That is, any therapy described herein can be co¬ administered (administered in combination) with one or more additional therapeutic agents such as, but not limited to, dacarbazine (DTIC), temozolomide (TMZ), carboplatin, paclitaxel, ipilimuma¾ (Yervoy), everolimus, gemcitabine, interleukin-2, and interferon. Furthermore, any therapy described herein can include one or more agents for treating, for example, pain, nausea, and/or one or more side-effects of a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) or a non-lenvatinib agent.
Combination therapies (e.g., co-administration of a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) or a non-lenvatinib agent and one or more additional therapeutic agents) can be, e.g., simultaneous or successive. For example, lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) and one or more additional therapeutic agents can be administered at the same time or a lenvatinib compound (e.g., lenvatinib mesylate) can be administered first in time and the one or more additional therapeutic agents administered second in time. In some embodiments, the one or more additional therapeutic agents can be administered first in time and lenvatinib or a
pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) administered second in time.
In cases where the subject predicted to respond to a lenvatinib (e.g., lenvatinib mesylate) therapy has been previously administered one or more non lenvatinib therapies, the therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) can replace or augment a previously or currently administered therapy. For example, upon treating with the therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), administration of the one non lenvatinib therapies can cease or diminish, e.g., be administered at lower levels. Administration of the previous therapy can be maintained while the therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) is administered. In some embodiments, a previous therapy can be maintained until the level of the therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) reaches a level sufficient to provide a therapeutic effect.
In other embodiments, the subject can be monitored for a first pre-selected result, e.g., an improvement in one or more symptoms of a disease treatable by a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), e.g., melanoma or any other diseases treatable by therapy comprising a lenvatinib. In some embodiments, when the first pre-selected result is observed, treatment with the therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) can be decreased or halted. In some embodiments, the subject can then be monitored for a second pre-selected result after treatment with the therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate) is halted, e.g., a worsening (e.g., a worsening of a symptom) of a disease treatable by a lenvatinib (e.g., lenvatinib mesylate). When the second pre-selected result is observed, administration of the therapy comprising lenvatinib or a pharmaceutically' -acceptable salt thereof (e.g., lenvatinib mesylate) to the subject can be reinstated or increased, or administration of the first therapy can be reinstated, or the subject can be administered both a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), or an increased amount of a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), and the first therapeutic regimen.
The following are examples of the practice of the invention. They are not to be construed as limiting the scope of the invention in any way.
EXAMPLES
Example l: Gene Expression Profiling of Melanoma Tumor Biopsies to Identify a Response Signature to the Multi-RTK Inhibitor. E7080
Purpose ' Tumor response and prolonged disease stabilization (> 6 months) were observed in melanoma patients treated in phase I with E7080 (methanesulfonic acid salt of lenvatinib). This experiment was directed at identifying predictive genomic signatures for subjects who respond or fail to respond to treatment with E7080 using three criteria of response.
Materials and Methods- 27 patients with metastatic melanoma received E7080 10 mg twice daily continuously. Biopsy of accessible lesions was performed pre- treatment day 1 (Dl) and on day 22 (D22) post-treatment. Pretreatment samples of malignant melanoma from 27 donors were collected by surgical excision or core needle (20 gauge) and placed in a tissue tray containing a small amount of OCT medium. Tumor samples were subsequently completely covered with OCT medium, and gradually submerged in liquid nitrogen for cryopreservation. Samples were subsequently stored at -80°C until accessed for analysis. Representative samples from 26 selected donors were mounted and sectioned onto polyethylene naphthalate (PEN) membrane slides (Zeiss) to enable collection of desired cell types by laser
microdissection and pressure catapulting via the PALM Microbeam system. Prior to sectioning, all slides were rendered RNase-free by treatment with RNase ZAP and were irradiated with UV light to improve tissue adherence. Following sectioning, slides were maintained on dry ice and subsequently stored at -80°C until being individually retrieved for staining and laser capture microdissection (LCM) collection. An initial slide from each block was reviewed by a pathologist to confirm the presence of tumor and to estimate collection requirements. In addition, RNA was extracted from an unstained section from each block using the RNeasy Micro kit (Qiagen®) in order to demonstrate suitable quality RNA to pursue LCM.
For blocks with passing RNA quality metrics and those determined to have adequate viable tumor on which to focus collection, slides were stained with hematoxylin and eosin (H&E) and LCM of an estimated 5,000 neoplastic cells was performed with catapulting into' RLT buffer with BME. Collections were restricted to a 30 minute period following staining to maintain good quality RNA. Before and after images were taken to document the collection and were reviewed by a pathologist as a quality control measure.
Following RNA isolation, the quantity and purity of the RNA was determined by absorbance at 260 nm and 260/280 absorbance ratio respectively. Each of the total RNA preparations was individually assessed for RNA quality based on the 28S/18S ratio and RIN measured on an Bioanalyzer (Agilent) system using the RNA 6000 Nano LabChip Kit.
Amplified ss-cDNA was created using WT vation Pico RNA Amplification system V2 (Cat# 3300, NuGen Corp). The cDNA was purified using magnetic beads (Agencourt RNAClean, Beckman). The quantity and purity of the cDNA was determined by absorbance at 260nm and 260nm 280nm absorbance ratio respectively. The quality of the cDNA was evaluated by assessing size distribution using
Bioanalyzer RNA Nano chips (Agilent).
The cDNA was fragmented and biotin-labeled using FL-Ovation™ cDNA Biotin module (NuGEN, order no. 4200) and 4.0 to 4.8 μ loaded onto individual human U133 plus 2.0 GeneChips (Affymetrix) as the hybridization cocktail (200 μΐ). The
microarrays were hybridized at 45°C for 16· 24 hours and washed and stained on an FS450 fluidics station according to manufacturer recommendations (Affymetrix®, FS450_0004). The microarrays were scanned on a GeneChip Scanner 3000
(Affymetrix®). GeneChip analysis was performed using Microarray Analysis Suite version 5.0 to generate expression values. All of the genes represented on the
GeneChip were globally normalized and scaled to an average signal intensity of 100. In addition, residual slide material was used for two cases to evaluate the feasibility of collecting endothelial cells within tumor regions as identified by immunostaining for CD31. After LCM of endothelial cells into RLT buffer for gene expression profiling, tumor cells highlighted by a hematoxylin counterstain were captured into 30 mM Tris- HC1, pH 7.5, 150 mM NaCl, 0.1% Triton X- 100, 0.1% SDS buffer. Vascular collections were suspended after the two cases as it became apparent such processing would deplete the material and would likely prove inadequate for most donors. As such, the collection of up to an estimated 30,000 tumor cells into the above buffer was performed for all cases with available slides over a 1 hour period following standard H&E staining. These collections were submitted to NextGen Sciences for LC MS analyses.
Where available, complete sections of the blocks with passing array data have been H&E stained and RNA has been extracted with intent to generate gene expression data on the composite samples for comparison to the harvested tumor samples.
Results- From 26 patient samples, 22 pre treatment samples yielded quality melanoma mRNA samples for hybridization and analyses using data from ~24,000 RMA normalized probes. The genomic data was analyzed using Student's T-test based on: clinical benefit (CB); regression analysis for the continuous measure of tumor shrinkage (TS); and by Cox propd tional regression based on progression free survival (PFS).
"Clinical benefit" (CB) refers to having one of the following statuses - Complete Response (CR), Partial Response (PR); or Stable Disease (SD) with 6 months or more progression free survival (PFS). "Complete Response" means complete disappearance of all target lesions. "Partial Response" means at least 30% decrease in the sum of the longest diameter (LD) of target lesions, taking as reference the baseline summed LD. 'Trogressive Disease" (PD) meanfci at least 20% increase in the sum of the LD of target lesions, taking as reference the smallest summed LD recorded since the treatment started, or the appearance of one or more new lesions. "Stable Disease" means neither sufficient shrinkage of the target lesions to qualify for PR nor sufficient increase to qualify for progressive disease (PD), taking as reference the smallest summed LD since the treatment started.
"Progression Free Survival" (PFS) refers to the period from start date of treatment to the last date before entering PD status.
"Tumor shrinkage" (TS) means percent change of sum of diameters of target lesions, taking as reference the baseline sum diameters.
The above analysis identified genes encoding elements of the target receptor tyrosine kinase signaling pathways.
13 of the identified biomarkers were associated with improved clinical benefit, tumor shrinkage, and progression free survival. The criteria used to select genes as biomarkers in this category are as follows:
CB: (l) average expression level is 100 or more for either CB or non CB
CB: (2) t-test p-value is 0.05 or less
CB: (3) fold change is l.'5:.6r more '
TS: (l) average expression level of all samples is 50 or more
TS: (2) Pearson correlation test p-value is 0.05 or less
PFS: (l) cox proportional hazard model p-value is 0.05 or less
Table 4 provides a listing of genes that fall within this category.
Table 4
Figure imgf000061_0001
49 of the identified biomarkers were associated with improved tumor shrinkage and progression free survival. The criteria used to select genes as biomarkers in this category are as follows:
TS: (l) average expression level of all samples is 50 or more
TS: (2) Pearson correlation test p-value is 0.05 or less
PFS: (l) cox proportional hazard model p-value is 0.05 or less
Table 5
Figure imgf000063_0001
Figure imgf000064_0001
Conclusion- A small set of genes in melanoma cells may be used to predict clinical response in melanoma patients to E7080.
Example 2- Biomarker Discovery for E7080 from Phase I Melanoma Clinical Trial
This example describes a data and supercomputer driven analysis strategy for predicting gene expression measures that are critical for maximal tumor shrinkage (MTS) and progression free survival (PFS). The GNS Healthcare REFS™ (Reverse Engineering and Forward Simulation) is used to reconstruct an ensemble of 1000 networks that are predictive of MTS and PFS. REFS™ simulation analyses identified four candidate marker genes for MTS and six candidate marker genes for PFS.
Methods
General REFS™ methodology
Learning Probabilistic Models from Data■ A multivariate system with random variables X= (Xi, Xn) where each variable may take on values from a discrete (genetic markers) or continuous domain (gene expression and phenotypic data) may be characterized probabilistically by a joint multivariate probability distribution function P(Xi, ..., Xn; Θ). However, full specification of such joint probability distributions requires a large number of parameters Θ. Such a global joint probability distribution admits the following factorization into a product of local conditional probability distributions1
Ρ(Χ ...,Χη Θ) ^ Π^ ^^κ^) (1 ) where each variable X' is independent of its nondescendants given its &parents Yji,..., ¾K(local Markov condition) and 0/are parameters for Pi. The variables are simply a subset of the Xs, we use the ^notation to indicate they are inputs to the conditional probability. This approach yields a framework where each particular factorization and choice of parameters is a distinct probabilistic model Moi the structure of the process that created the observed data (Pearl, J., Models, reasoning and inference, (Cambridge University Press, Cambridge, New York, Melbourne, Madrid, Cape Town, Singapore, Sao Paulo, 2000)). Learning these models iJ from a data set D is simply determining which factorizations of PCXi, ..., Χη;Θ) are most likely given the observation of D, and given a factorization, what are the likely values for its parameters Θ = (Θι, ..., Θη).
Each factorization of P(Xi, AW into model M(as in Eq. l) is represented by a unique Directed Acyclic Graph (DAG) Cwith a vertex for each .A? and directed edges between vertices to represent the dependencies between variables embedded in the local conditional distributions, Pif-Xi/ Yji, YjKi). In addition to the graph G, l also specifies distributions for all 6>/the parameters of local conditional distributions Pi. Subgraphs of G, consisting of a vertex and a set of all its incoming edges, and associated local conditional distributions and parameters Θί, are referred to here as "network fragments". We interpret each of these network fragments Mito characterize both the functional variation of its output variable A/with respect to its parent input variables Yji, YjKi and the residual variation in Xi. For integrative genomics we consider several specific functional forms for network fragments and used linear regression. First, consider the case where all of the input variables Yji, YjKi are continuous, then we model the centroid of Xi y-
Χ, = θ0 + θβΥβ + ...+ θ^Κι (2)
and Xiby a normal distribution about that value:
Χ, ~ Ν(Χ„<ή) (3)
The parameters θο, 9ji, ..., 6jKj can be thought of as adjusted to best fit the data in the Maximum Likelihood Estimation (MLE) sense. The likelihood function gives the posterior distribution of the parameter values about the MLE point. Next, consider the case where one of the Fvariables is discrete. To model its influence its Unear term in Eq. 2 is dropped and the discrete value is used to switch the value of the remaining linear fitting parameters. That is to say, for each value of the discrete variable a differentset θο, 6ji, ...,6jKi of fitting parameters is introduced. Finally, if multiple Ys are discrete all of their linear terms are dropped from Eq. 2 and their joint discrete state is used as the switching value. In this study all of the output variables Aj'are continuous: discrete variables are only taken as inputs.
Parallel Ensemble Sampling · To determine which factorizations are likely given the data we use a Bayesian framework to compute the posterior probability of the model PCM/DJ from Bayes' Law 1 ^ P(D) '
where P(D) is the probability of D, P(M) is the prior probability of the model and
P(D I M)= J P(D I Μ(β))Ρ β I M)d® (5) is the integral of the data likelihood over the prior distribution of parameters Θ. We assume that data is complete. Assuming that parameters ©are independent, all models are equally likely, and P(D) is constant, we factor P(M ID) in Eq. 4 into the product of integrals over the parameters local to each network fragment Mi Eq. 4 now becomes
P(D I M) = Π J* P{D I ,(Θ,))/>(Θ,. | M,)d®i (6)
where P(®i I Mi) is the network specific prior for its parameters.
For this work we use Schwartz's Bayesian Information Criterion approximation to the above integral (asymptotically exact as the number of samples increases):
= -log J P(D I (Θ,))^(Θ, I Μ,)άΘ, * Sfl/C( ,) = SWi£( ,) + ^logN (7) where κ(Μΐ) is the number of fitting parameters in model Mi and . Vis the number of samples. We refer to S as a "score", but note the minus sign in the definition (to agree with the simulated annealing analogy described below) and so lower scores are more likely. SMLE is the negative logarithm of the MLE value of the likelihood function. The total network score is^
n
-\og(P(D \ M)) = Slol (M) =∑S(Mi) (8) a sum over the scores of each network fragment in the candidate graph model. In principal the repository of candidate network fragments can be constructed by exhaustive enumeration over variables and network fragment forms. We selected models that provided highest likelihood (Heckerman, D., A tutorial of learning with Bayesian networks, in Learning in graphical models (ed. Jordan, M.) 301 354 (MIT Press, Cambridge, 1999); Woolf, P.J. et al., Bayesian analysis of signaling networks governing embryonic stem cell fate decisions. Bioinformatics, 21, 741-53 (2005)), and considering at most 2 edges for a particular vertex. However, even with these constraints, the space of all possible graphs is still too large to be sampled by exhaustive enumeration.
Instead we use the Metropolis method (Markov Chain Monte Carlo) to generate samples from an equilibrium Boltzmann distribution of candidate structures (Ding, Y. & Lawrence, C.E. A statistical sampling algorithm for RNA secondary structure prediction. Nucleic Acids Res 31, 7280-301 (2003)) from P(M/D). Each step in a Metropolis Markov Chain corresponds to local transformations such as adding or deleting network fragments. To accelerate convergence we used simulating annealing were we applied the Metropolis method to a sequence of distributions
exp(—Slol(M)/Tj ) with decreasing 7] (annealing temperature). At each stage /the equilibrated samples from 7} initialize the Metropolis method at Tj+i. Convergence of the random walk is monitored along the way and the annealing schedule is dynamically modified to take more Monte Carlo steps when the barriers present a larger obstacle to diffusion through the space of networks. The method for doing this was to estimate rate of change with respect to Toi the mean total score SI0( ^ and also its variance (S,„,)— (S,0/) (the angle brackets denote Monte Carlo averages over networks at the current T.) From these values the change in temperature, T' - T = AT, is selected so that the distribution of Slol at V will have 80% overlap with the distribution at T. This process of maintaining overlap helps ensure that the sampling will be correct when T=l is reached. In addition, shorter runs were performed to confirm that results are consistent.with the longer runs.
In the normal usage of simulated annealing to find a global optimum, the control parameter yis allowed to go below l; as long as better solutions are still being found the temperature is allowed to decrease. In our approach we stop at T=l because the sampling there corresponds directly to the posterior distribution P(M ID) in Eq.4; going to lower values of T ould lead to over fitting the data.
Model Intervention Simulations - Stochastic simulation of a probabilistic model M allows predictions about the distribution of a variable Xito be made under different conditions. The conditions can be interventions with variables in the model and/or different values of inputs to the model. We used Gibbs sampling in which each variable Xiis sampled from its conditional Gaussian distribution, such as Eq. 2, 3, whose parameters take on most likely values given data D. For simulation of subjects not seen in the training data, only roots of the graph G had values. A simulation routine iteratively sweeps the network and generates samples of variables whose parents have already acquired a value in previous iterations until all variables have values. One full sweep produces one sample (one vector of values of all variables). Interventions such as a knockdown of gene transcript expression level variables are done by removal of the network fragment from M that outputs to the variable and the network is swept as described previously.
Modeling Strategy and Survival Analysis - Transcripts as well as pharmacokinetic measures are used to predict phenotypes (maximal tumor shrinkage and progression free survival) in this study. An ensemble of 1000 networks is used to capture the statistical sample of models consistent with the data. A survival regression analysis (R/survival package) is used to model progression free survival time (days).
Assessment and Processing of Gene Expression - Simpleaffy was used to assess the quality of microarray hybridization (Wilson, C.L. & Miller, C.J., Simpleaffy: a
BioConductor package for Affymetrix Quality Control and data analysis. Bioinformatics 21, 3683 5 (2005)) and the majority of samples lay within the tolerances suggested by Affymetrix for amplified RNA samples. The microarray data set was normalized using the PLIER (Probe Logarithm Intensity Error) algorithm developed and released by Affymetrix (Team, A.T. Affymetrix technical notes: Guide to Probe Logarithmic Intensity Error (PLIER) estimation. (Accessed 11 March 2011, Available-' http://www.affymetrix.com/support/technical technotes/pUer_technote.pdf)). This normalization technique has outperformed previously developed methods in the Affycomp II competition in detecting differential gene expression as well as quantitation.
Pharmacokinetics (PK) Analysis -' The period during which a patient takes E7080 is artificially divided into different Cycles for ease of evaluation and tracking. For the E7080 melanoma trial, each Cycle is 28 days (4 weeks) so Day 1-28 is cycle l; Day 29 is Day 1 of Cycle 2; and Day 57 is the Day 1 of Cycle 3. Blood samples were collected for PK analysis on Day 1 of the first cycle immediately prior to the first dose of E7080, and at 0.25, 0.5, 1, 1.5, 2, 2.5, 3, 4, 6 and 24 hours following the first dose of E7080 (single dose PK). Blood samples were also collected for PK analysis on Day 1 of cycle 2 immediately prior to the dose of E7080, and at 0.25, 0.5, 1, 1.5, 2, 2.5, 3, 4, 6 and 24 hours (multiple dose of PK). For Cycle 1 Day 1 (single dose PK) the following parameters were calculated and used in the analysis: Cmax and AUCO-6. Cmax is the maximum concentration of drug in the plasma. AUC is an abbreviation for Area Under Curve. AUCO-6 is the accumulated total drug from 0 hr to 6hr. For Cycle 2 Day 1 (multiple dose PK) following parameters were calculated and used-' Cmax and AUCO-6. Identification of Genes Connected to Maximal Tumor Shrinkage (MTS) from REFS™ Model: An ensemble model of 1000 networks was built for the prediction of MTS. 39 genes were identified as being linked to MTS in at least one of the 1000 network, or 0.1% cutoff of consensus model.
Results
Inferring a REFS predictive model of maximal tumor shrinkage and progression free survival— As described in Xing et al (Causal modeling using network ensemble simulations of genetic and gene expression data predicts genes involved in rheumatoid arthritis, PLoS Comput. Biol, 7, el001105 (2011)), the REFS™ predictive framework involves three phases. In the first phase, the data are processed so that probabilistic modeling methods can be applied to it (See Methods). In the second phase, we estimate an ensemble of network models based on data from the experiment. In the third phase we use forward simulation of networks in the ensemble to generate predictions of effects of modulating genes to phenotypic endpoints. The process is summarized in Figure 1. Summaries of data processing and the mathematical assessment of the quality of the model generated by the framework are provided in the Methods section.
Briefly, the model was built using all 54,675 gene expression values, pharmacokinetic and phenotypic measurements from melanoma patients in Phase I clinical trial. More than 7 x 109 (billion) network fragments are enumerated and 40,000 best network fragments are used by the parallel sampler to build an ensemble model of networks to predict maximal tumor shrinkage (MTS). A parametric survival regression (R survival package) model was constructed to capture how maximal tumor shrinkage together with genes to explain progression free survival (PFS). A snapshot of consensus structure of the network model is shown in Figure 2.
There are 39 genes identified as being connected to MTS (Table 6). These 39 genes are subject to pathway enrichment analysis with Ingenuity Pathway Analysis (Ingenuity® Systems, www.ingenuity.com). Ingenuity® literature network seeded with the genes from REFS™ model suggests that genes involved in cell growth, cell survival/death are enriched. Analysis of canonical pathway indicates that immune signaling (Toll-like receptor signaling) is among the enriched pathways.
Table 6^ List of 39 genes connected to maximal tumor shrinkage in REFS™ model.
203677_s_at TARBP2
221631_at CACNA1I
1566693_at NA
214103_s_at RAP2A
220706_at ADAMTS7
230609_at CLINT1
23557 l_at NA
1555630_a_at RAB34
202204_s_at AMFR
221417_x_at S1PR5
218735_s_at ZNF544
239624_at NA
211532_x_at NA
223356_s_at MTIF3
211587_x_at CHRNA3
54970_at ZMIZ2
208454_s_at PGCP
1560488_at LCNL1
226809_at LOC 100216479
229015_at NA
235198_at OSTM1
20350 l_at PGCP
240844_at NA
244708_at NA
203263_s_at ARHGEF9
1553739_at IRAK2 · Afrymetri ID Gene Symbol
215251_at NA
219274_at TSPAN12
222759_at SUV420H1
207716_at KRT38
217055_x_at NA
213235_at C16ori88
223060_at C14orfll9
222752_s_at TMEM206
20426 l_s_at PSEN2
1562267_s_at ZNF709
241745_at NA ·
222548_s_at MAP4K4
Model interventional strategy and identification of candidate marker genes for maximal tumor shrinkage and progression free survival - With REFS™ network model, one can simultaneously query all types of relationship models that exist. For example, genes that are significant regulators, or candidate marker genes, of phenotypes can be identified via in silico simulations of the REFS™ model. To identify candidate marker genes, systematic in silico simulations of 10-fold knockdown of all genes connected to phenotypes were completed to provide quantitative predictions of how the modulation of a particular gene expression measure would affect maximal tumor shrinkage or progression free survival.
Genes that were predicted to significantly modulate phenotypes are listed in Tables 7 and 8. They are ranked based on the likelihood that predicted changes could be validated in subsequent confirmatory clinical studies. Four genes were identified as candidate marker genes for maximal tumor shrinkage (Table 7) and six genes were identified as candidate marker genes for progression free survival (Table 8).
Table 7 - List of candidate marker genes for maximal tumor shrinkage.
1566693_at C70RF
203677_s_at TARBP2
214103_s_at RAP2A
221631_at CACNA1I nes for progression free survival.
Figure imgf000072_0001
237493_at IL22RA2
1566693_at C70RF
203677_s_at TARBP2
214103_s_at RAP2A
221631_at CACNA1I
Simulation analysis predicts four genes as candidate marker genes for maximal tumor shrinkage - With REFS™ simulation, four genes are identified as candidate marker genes for maximal tumor shrinkage. The four genes are TARBP2, RAP2A, CACNA1I, and a hypothetical gene from chromosome 7 (C70RF). The effects of how candidate marker genes associate with maximal tumor shrinkage are predicted via network simulation and shown in Figure 3. For example, lower level of TARBP2 (red distribution) is associated with more tumor shrinkage (Figure 3B) and on the contrary lower level of RAP2A is associated with less tumor shrinkage (Figure 3C).
f TARBP2, or TAR (ΗΓν- 1) RNA binding protein2, is a protein related to DICERl and has been recently identified to be required for processing of miRNAs to regulate tumorigenesis (Melo, S.A. et al. A TARBP2 mutation in human cancer impairs microRNA processing and DICERl function. Nat Genet 41, 365-70 (2009)). MAP kinase signaling pathway plays important roles in cell growth, differentiation, and survival to be involved in cancer growth. We identified RAP2A, a member of RAS oncogene family, as a candidate marker for maximal tumor shrinkage. Its role in human prostate cancer has been reported (Bigler, D., Gioeli, D., Conaway, M.R., Weber, M.J. & Theodorescu, D. Rap2 regulates androgen sensitivity in human prostate cancer cells. Prostate, 67, 1590-99 (2007)).
Simulation analysis predicts 6 genes as candidate marker genes for progression free survival - Since maximal tumor shrinkage is predictive of progression free survival, it is not surprising that four candidate marker genes of maximum tumor shrinkage (MTS) are also candidate marker genes of progression free survival. In addition, SHMT1 and IL22RA2 are identified as candidate marker genes of progression free survival (PFS). The REFS™ model predicts that lower level of IL22RA2 is associated with longer progression free survival time (Figure 4B) while lower level of SHMT1 is associated with shorter progression free survival time (Figure 4A). IL22RA2 is a soluble cytokine receptor, which binds to and inhibits IL-22 activity. IL-22 is a cytokine that has complex pro inflammatory, anti inflammatory, and auto immune effects (Aujla, S.J. & Kolls, J.K. IL-22: a critical mediator in mucosal host defense. J. Mol. Med., 87, 451-4 (2009)), suggesting the importance of immune system in progression free survival time. SHMTl is serine hydroxymethyltransferase 1 and its S P has been reported to be associated with cancer (Komlosi, V. et al. SHMTl 1420 and MTHFR 677 variants are associated with rectal but not colon cancer. BMC Cancer, 10:525).
Virtual PK simulation analysis and progression free survival - Pharmacokinetic measures Cmax (peak serum concentration of E7080), AUCO-6 (area under the plasma E7080 concentration time curve from 0 to 6 hour), AUCO-24 (area under the plasma E7080 concentration time curve from 0 to 24 hour) are being considered for building the REFS™ model. With an ensemble of models, we can consider all three PK measures as long as no more than one at a time due to correlative nature of the PK measures. In Virtual PK simulation, the values of PK variables such as Cmax, AUCO-6 and AUCO-24 can be set to desired value conditioning on gene expression measures of a specific patient. This allows us to simulate the clinical phenotypic response for an individual patient giving a set of PK values. The maximal tolerable dosing or maximal PK values are set for each individual patient and the clinical phenotypic responses are predicted for the group of patients. A higher response rate of E7080 treatment was predicted if maximal E7080 tolerable dosing is applied to patients. If 84 day of progression free survival time is used as cutoff, REFS™ predicts the number of good responder would increase from 13 to 17.
Discussion
In this study, we have built a REFS™ model predictive of E7080 responsiveness. The data used to construct the model are gene expression profiles before E7080 treatment and pharmacokinetic measures of E7080 from day 1 of cycle 1. All 54,675 genes are used to build the REFS™ model and in silico simulation analyses were done to identify candidate marker genes. Four genes were predicted as candidate marker genes for maximal tumor shrinkage and six genes were predicted as candidate marker genes for progression free survival.
From the list of candidate marker genes, traditional signaling pathway components such as RAP2A in MAPK pathway were identified as a candidate marker gene for both maximal tumor shrinkage and progression free survival. Genes involved in miRNA regulation, such as TARBP2, are also identified as candidate marker genes of maximal tumor shrinkage and progression free survival. In addition, genes such as CACNA1I and C70RF which are considered as "novel" in melanoma disease are also identified as candidate marker genes for maximal tumor shrinkage and/or progression free survival. Identification of IL22RA2 as a candidate marker gene suggests that immune status also plays a role in progression free survival.
The inclusion of pharmacokinetic measures in the REFS™ model allows the ability to address questions such as benefits of optimizing E7080 dosing or maximal tolerable E7080 dosing on the patient cohort. Virtual PK simulation analysis suggests that better response rate of E7080 can be achieved if every patient can achieve maximal E7080 concentration in the serum.
Example 3: Predictive Biomarker Development and Evaluation
Archived, fixed tumor tissue from cancer patients (e.g., patients with skin cancer, liver cancer, lung cancer, brain tumor, thyroid cancer, ovarian cancer, renal cancer and/or endometrial cancer) are collected for the assessment of biomarkers that can serve as signatures for responsiveness or non-responsiveness to therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate). Gene-expression profiling (GEP), proteomic, immunohistochemical (IHC), and/or other analyses are performed. All analyses are performed to correlate clinical outcomes related to treatment with lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate).
Biological samples (e.g., serum or plasma, blood mRNA, free circulating tumor DNA/miRNA) are also collected for biomarker analysis at baseline, Cycle 1/Day 15, Day 1 of all subsequent cycles, and at the off-treatment assessment in the clinical study.
Biomarker discovery' and 'evaluation is performed to identify blood, genetic, or tumor biomarkers which may be useful to predict subject response to lenvatinib or a pharmaceutically acceptable salt thereof (e.g., lenvatinib mesylate), as determined by the evaluation of clinical endpoints, such as CR (complete response) or PR (partial response), PFS (progression free survivaD, OS (overall survival), DCR (disease control rate) (CR or PR or SD (stable disease) for 7 weeks) , CBR (clinical benefit rate) (CR or PR or durable SD; SD lasting for 23 weeks), and the durable SD (SD lasting > 23 weeks) rate.
Example 4- Gene Expression as Predictive and Response Biomarkers of E7080
Purpose- Tumor response and progression free survival were observed in melanoma patients treated in phase II with E7080. This experiment was directed at validating predictive genomic signatures for subjects who respond or fail to respond to treatment with E7080.
Materials and Methods'- Archival tumor tissue was collected (if available) from enrolled subjects in the Phase 2 study of lenvatinib (E7080) in previously treated subjects with unresectable stage III or stage IV melanoma, Cohort 1 (subjects not harboring the V600E BRAF mutation and disease progression following up to two prior systemic anticancer regimen treatments). Gene expression analysis was conducted for the assessment of biomarkers which may be important in the development and progression of melanoma and can be correlated with clinical outcomes related to treatment with lenvatinib.
Lysates were prepared from macro-dissected FFPE slides (macro-dissection performed at Gentris). Briefly, 1ml of Xylene was added and vortexed for 10 sec, followed by centrifugation for 4 min at maximum speed (all centrifuge steps were carried out at room temp with benchtop microcentrifuge). Supernatant was removed by pipetting, leaving 200 μΐ of supernatant behind (without disturbing the pellet). 1ml of 100% ethanol was added and vortexed. This was followed by a spin down at maximum speed for 2min. The ethanol wash step was repeated. Maximum supernatant was then removed without disturbing the pellet. The pellet was allowed to dry at room temperature for 30 min with the tube open and then re-suspended in 45 μΐ 10 mM MES pH 6.5, 0.5% SDS, and 5 μΐ Proteinase K (20 mg/ml) and vortexed. The resulting solution was incubated at 55 degrees for 15 min, tapped gently to mix, and then incubated at 80 degrees for 15min. This was followed by centrifugation at maximum speed for 30 sec, and the supernatant was retrieved and 5 μΐ was used as template for each nCounter reaction and processed according to standard protocol. The final data was normalized for lane to lane variation using the positive spike in controls which are part of the probe set and then content normalized to Actin-B (the least variant endogenous gene) and checked for Quality Control. Any raw count <50 was considered background, and-50 wa's set as lower limit of detection.
For correlative analysis between response (Clinical benefit rate) and gene expression, the Mann-Whitney test was applied. For survival analysis with gene expression, the Cox proportional hazard model and Logrank test were utilized. Best cutoff value for dichotomization was identified using lowess-smoothed minimum p- value approach. Statistical analyses were done by R (version 2.13.1, www.R- project.org).
Results and discussion- Among 32 available samples, 8 samples were found to have Clinical benefit and 24 samples were not found to have Clinical Benefit. Higher expression level of any of RAP2A, SNRNPP70, and CLINT1 was significantly associated with Clinical benefit (Table 9). Table 9- Association of gene expression with clinical benefit rate.
CBR
Gene N(nega:posil| P value** ^ med.diff**
SNS P70 24:8 0.009 6843
CLINTl 24:8 0.039 194
RAP2A 24:8 0.043 738
* CBR (clinical benefit rate): PD plus SD vs. SD more than 6 months plus PR and CR
** Mann-Whitney U test; different expression level between CBR positive and negative group
*** median difference of expression levels.
Cox proportional hazard model identified higher gene expression levels of
baseline SNRNP70, CLINTl, PGCP and SHMT1 were significantly associated with longer progression free survival. Also the lower gene expression level of baseline CPM was significantly associated with longer progression free survival (Table 10).
Table 10 - Association of gene expression with progression free survival
Host oitafl mode.
a
PGCP 32 0.034 0.048 0.044 0.655 0.43-1 (-O.0O026)'(GE?.PGCP) < .583 7 25 0.230 0.073-0.72
SNRNP70 32 0.009 0.019 0.0 IS 0.569 0.35-0.91 (-8 -05)*(GEP.SNRNP70) < -0.638 16 16 0.341 0.14-0.83
SHMT1 32 0.02S 0.051 0.344 0.611 0.37-1 (-aO0O693)*(GEP.SHMTl) < 28 0.147 0.019-1.1
CPM 32 0.002 0.001 0.000 2.614 13-4.7 .00139)*(GEP.CPM) < .55 16 16 0.535 0.23-1.3
CLINTl 32 0.046 0.058 0.QS8 0.616 0.37-1 ( 0,PP145)*(GEP.CLINT1) < -1,27 6 26 0.SS1 0.19 1.6
*Expression of genes was determined to be associated with progression free survival if all of the p values were smaller than 0.1.
Conclusion- Baseline gene expression levels of SNRNP70, CLINTl, and RAP2A are associated with clinical benefit for E7080 treatment. High baseline SNRNP70,
CLINTl, PGCP, and SHMT1, and low baseline CPM are associated with longer
progression free survival with E7080 treatment.
This data differs from Example 1 in the finding that elevated expression of
PGCP is associated with responsiveness to E7080. In this Example, the lysate that was used was directly prepared^from FFPE slides and analyzed for expression of
genes without manipulation. Based on a consideration of the data, it is concluded that elevated PGCP levels are associated with responsiveness (and not non-responsiveness) to E7080 therapy. • ther Embodiments
While the invention has been described in conjunction with the detailed description thereof, the foregoing description is intended to illustrate and not limit the scope of the invention, which is defined by the scope of the appended claims. Other aspects, advantages, and modifications are within the scope of the following claims.

Claims

What we claim is:
1. A method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, the method comprising:
providing a biological sample obtained from a subject; and
measuring the expression level of one or more genes in the biological sample, wherein the one or more genes comprise at least one gene selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R, IGJ, NUP188, ERG, MDM1, HIPK2, INSR, ZNF529, DSCC1, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, ADAMTS9, SSPN, ZC3H6, VPS 37 A, OSBPL10, PDXDCl, PDXDC2, RORA, ANKRD13D, ZNF542, PPARD, NAPEPLD, ATPllC, EML6, GNB5, ATF3, ZC3H 11A, CCBLl, SHMT1, C70RF, IL22RA2, RAP2A, and CACNA1I, wherein an elevated expression level, as compared to a control, of one or more of SLC31A1, PFKFB2, NPY6R, IGJ, NUP188, ERG, INSR, ZNF529, PIP5K1, TMEM2, TUBBP5, UBA6, SURF4, FAM122A, AMIGOl, ADAMTS9, RORA, ZNF542, PPARD, ATPllC, EML6, GNB5, ATF3, ZC3H11A, CCBLl, SHMT1, RAP2A, or CACNA1I is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof,
and wherein an elevated expression level, as compared to a control, of one or more of TNKS, TARBP2, TTLL4, CHKA, PSPH, PGCP, MDMl, HIPK2, DSCC1, STAG3L4, MSRB2, GDPD5, GJB2, ARRDC4, COPS7B, NEIL2, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDCl, PDXDC2, ANKRD13D, NAPEPLD, C70RF or IL22RA2 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the one or more genes.
2. The method of claim 1, wherein the subject has, or is at risk of developing, a cancer.
3. The method of claim 2, wherein the cancer is selected from the group consisting of a skin cancer, a liver cancer, a lung cancer, a brain tumor, a thyroid cancer, an ovarian cancer, a renal cancer and an endometrial cancer.
4. The method of claim 2, wherein the cancer is a melanoma.
5. The method of any one of claims 1 to 4, wherein the subject is a human.
6. The method of any one of claims 1 to 5, wherein the biological sample is selected from the group consisting of a blood sample, circulating tumor cells, circulating DNA, a plasma sample, a serum sample, an urine sample, a skin sample and a tumor sample.
7. The method of any one of claims 1 to 6, further comprising communicating the test results to the subject's health care provider.
8. The method of any one of claims 1 to 7, further comprising modifying the subject's medical record to indicate that the subject is likely to respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, if the expression level of one or more of SLC31A1, PFKFB2, NPY6R, IGJ, NUP188, ERG, INSR, ZNF529, PIP5K1, TMEM2, TUBBP5, UBA6, SURF4, FAM122A, AMIGOl, ADAMTS9, RORA, ZNF542, PPARD, ATP11C, EML6, GNB5, ATF3, ZC3H11A, CCBL1, SHMT1, RAP2A, and CACNAlI is elevated, as compared to a control.
9. The method of any one of claims 1 to 7, further comprising modifying the subject's medical record to indicate that the subject is not likely to respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, if the expression level of one or more of TNKS, TARBP2, TTLL4, CHKA, PSPH, PGCP, MDM1, HIPK2, DSCC1, STAG3L4, MSRB2, GDPD5, GJB2, ARRDC4, COPS7B, NEIL2, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDCl, PDXDC2, ANKRD13D, NAPEPLD, C70RF and IL22RA2 is elevated, as compared to a control.
10. The method of claim 8 or 9, wherein the record is created on a computer readable medium.
11. The method of any one of claims 1 to 7, further comprising prescribing a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof for the subject if the expression level of one or more genes in the biological sample is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
12. The method of any one of claims 1 to 7, further comprising administering to the subject a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
13. The method of any one of claims 1 to 7, comprising:
determining that the expression level of one or more of SLC31A1, PFKFB2, NPY6R, IGJ, NUP188, ERG, INSR, ZNF529, PIP5K1, TMEM2, TUBBP5, UBA6, SURF4, FAM122A, AMIGOl, ADAMTS9, RORA, ZNF542, PPARD, ATP11C, EML6, GNB5, ATF3, ZC3H11A, CCBL1, SHMTl, RAP2A, and CACNA1I is elevated, as compared to a control; and
selecting a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof for the subject.
14. The method of any one of claims 1 to 7, comprising:
determining that the expression level of one or more of TNKS, TARBP2, TTLL4, CHKA, PSPH, PGCP, MDM1, HIPK2, DSCC1, STAG3L4, MSRB2, GDPD5, GJB2, ARRDC4, COPS7B, NEIL2, SSPN, ZC3H6, VPS 37 A, OSBPLIO, PDXDCl, PDXDC2, ANKRD13D, NAPEPLD, C70RF, and IL22RA2 is elevated, as compared to a control; and
selecting a therapy comprising an agent that is not lenvatinib for the subject.
15. The method of any one of claims 1 to 7, wherein the RNA level of the one or more genes is measured.
16. The method of any one of claims 1 to 7, wherein the protein level of the one or more genes is measured.
17. The method of any one of claims 1 to 7, further comprising administering to the subject a therapy that does not comprise lenvatinib if the expression level of one or more genes in the biological sample is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
18. The method of any one of claims 1 to 7, wherein the method comprises measuring the expression level of at least five genes selected from the group consisting of TNKS, TTLL4, PGCP, ERG, GJB2, INSR, FAM122A, SSPN, VPS37A, PDXDCl, PDXDC2, ZNF542, ATPllC, and ZC3H11A.
19. The method of any one of claims 1 to 7, wherein the method comprises measuring the expression level of at least five genes selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R, IGJ, NUP188, ERG, MDM1, HIPK2, INSR, ZNF529, DSCC1, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, ADAMTS9, SSPN, ZC3H6, VPS 37 A, OSBPL10, PDXDC1, PDXDC2, RORA, ANKRD13D, ZNF542, PPARD, NAPEPLD, ATPllC, EML6, GNB5, ATF3, ZC3H11A, and CCBL1.
20. The method of any one of claims 1 to 7, wherein the method comprises measuring the expression level of the following genes: SHMT1, C70RF, IL22RA2, TARBP2, RAP2A, and CACNA1I.
21. A method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, the method comprising- providing a biological sample obtained from a subject; and
measuring the expression level of SHMT1 in the biological sample,
wherein an elevated expression level, as compared to a control, of SHMTl, is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
22. A method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, the method comprising:
providing a biological sample obtained from a subject; and
measuring the expression level of C70RF in the biological sample,
wherein an elevated expression level, as compared to a control, of C70RF, is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of C70RF.
23. A method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, the method comprising:
providing a biological sample obtained from a subject; and
measuring the expression level of IL22RA2 in the biological sample, wherein an elevated expression level, as compared to a control, of IL22RA2, is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of IL22RA2.
24. A method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, the method comprising:
providing a biological sample obtained from a subject; and
measuring the expression level of TARBP2 in the biological sample,
wherein an elevated expression level, as compared to a control, of TARBP2 is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of TARBP2.
25. A method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, the method comprising:
providing a biological sample obtained from a subject; and
measuring the expression level of RAP2A in the biological sample,
wherein an elevated expression level, as compared to a control, of RAP2A, is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
26. A method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, the method comprising:
providing a biological sample obtained from a subject; and
measuring the expression level of CACNA1I in the biological sample, wherein an elevated expression level, as compared to a control, of CACNA1I, is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
27. The method of any one of claims 1 to 7, wherein the method comprises measuring the expression level of at least eight genes selected from the group consisting of TNKS, TTLL4, PGCP, ERG, GJB2, INSR, FAM122A, SSPN, VPS37A, PDXDC1, PDXDC2, ZNF542, ATP11C, and ZC3H11A.
28. The method of any one of claims 1 to 7, wherein the method comprises measuring the expression level of at least eight genes selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R, IGJ, NUP188, ERG, MDMl, HIPK2, INSR, ZNF529, DSCC1, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, ADAMTS9, SSPN, ZC3H6, VPS 37 A, OSBPL10, PDXDCl, PDXDC2, RORA, ANKRD13D, ZNF542, PPARD, NAPEPLD, ATPllC, EML6, GNB5, ATF3, ZC3H11A, and CCBL1.
29. A method of selecting a subject having, or at risk of developing, a cancer that would benefit from treatment comprising lenvatinib or a pharmaceutically acceptable salt thereof, comprising:
(a) determining the expression level in a biological sample obtained from a subject of at least one gene selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R, IGJ, NUP188, ERG, MDMl, HIPK2, INSR, ZNF529, DSCC1, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, ADAMTS9, SSPN, ZC3H6, VPS 37 A, OSBPL10, PDXDCl, PDXDC2, RORA, ANKRD13D, ZNF542, PPARD, NAPEPLD, ATPllC, EML6, GNB5, ATF3, ZC3H11A, CCBL1, SHMT1, C70RF, IL22RA2, RAP2A, and CACNAH;
(b) comparing the expression level of the at least one gene selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R, IGJ, NUP188, ERG, MDMl, HIPK2, INSR, ZNF529, DSCCl, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, ADAMTS9, SSPN, ZC3H6, VPS 37 A, OSBPL10, PDXDCl, PDXDC2, RORA, ANKRD13D, ZNF542, PPARD, NAPEPLD, ATPllC, EML6, GNB5, ATF3, ZC3H11A, CCBLl, SHMT1, C70RF, IL22RA2, RAP2A, and CACNAH in the biological sample from the subject to that in a control,
wherein an elevated expression level of one or more of SLC31A1, PFKFB2, NPY6R, IGJ, NUP188, ERG, INSR, ZNF529, PIP5K1, TMEM2, TUBBP5, UBA6, SURF4, FAM122A, AMIGOl, ADAMTS9, RORA, ZNF542, PPARD, ATPllC, EML6, GNB5, ATF3, ZC3H11A, CCBLl, SHMT1, RAP2A, and CACNAH compared to the control is indicative that the subject would benefit from treatment comprising lenvatinib or a pharmaceutically acceptable salt thereof,
and wherein an elevated expression level of one or more of TNKS, TARBP2, TTLL4, CHKA, PSPH, PGCP, MDMl, HIPK2, DSCCl, STAG3L4, MSRB2, GDPD5, GJB2, ARRDC4, COPS7B, NEIL2, SSPN, ZC3H6, VPS37A, OSBPL10, PDXDCl, PDXDC2, ANKRD13D, NAPEPLD, C70RF and IL22RA2 compared to the control is indicative that the subject would not benefit from treatment comprising lenvatinib or a pharmaceutically acceptable salt thereof; and
(c) selecting the subject who would benefit from treatment for treatment comprising lenvatinib or a pharmaceutically acceptable salt thereof.
30. The method of claim 29, wherein the RNA level of the one or more genes is measured.
31. The method of claim 29, wherein the protein level of the one or more genes is measured.
32. The method of any one of claims 29 to 31, wherein the method comprises measuring the expression level of at least five genes selected from the group consisting of TNKS, TTLL4, PGCP, ERG, GJB2, INSR, FAM122A, SSPN, VPS37A, PDXDCl, PDXDC2, ZNF542, ATPllC, and ZC3H11A.
33. The method of any one of claims 29 to 31, wherein the method comprises measuring the expression level of at least five genes selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R, IGJ, NUP188, ERG, MDM1, HIPK2, INSR, ZNF529, DSCC1, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, ADAMTS9, SSPN, ZC3H6, VPS 37 A, OSBPL10, PDXDCl, PDXDC2, RORA, ANKRD13D, ZNF542, PPARD, NAPEPLD, ATPllC, EML6, GNB5, ATF3, ZC3H11A, and CCBLl.
34. The method of any one of claims 29 to 31, wherein the method comprises measuring the expression level of the following genes: SHMT1, C70RF, IL22RA2, TARBP2, RAP2A, and CACNA1I.
35. The method of any one of claims 29 to 31, wherein the method comprises measuring the expression level of SHMTl.
36. The method of any one of claims 29 to 31, wherein the method comprises measuring the expression level of C70RF.
37. The method of any one of claims 29 to 31, wherein the method comprises measuring the expression level of IL22RA2.
38. The method of any one of claims 29 to 31, wherein the method comprises measuring the expression level of TARBP2.
39. The method of any one of claims 29 to 31, wherein the method comprises measuring the expression level of RAP2A.
40. The method of any one of claims 29 to 31, wherein the method comprises measuring the expression level of CACNAlI.
41. The method of any one of claims 29 to 31, wherein the method comprises measuring the expression level of at least eight genes selected from the group consisting of TNKS, TTLL4, PGCP, ERG, GJB2, INSR, FAM122A, SSPN, VPS37A, PDXDCl, PDXDC2, ZNF542, ATPllC, and ZC3H11A.
42. The method of any one of claims 29 to 31, wherein the method comprises measuring the expression level of at least eight genes selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R, IGJ, NUP188, ERG, MDM1, HIPK2, INSR, ZNF529, DSCCl, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, ADAMTS9, SSPN, ZC3H6, VPS 37 A, OSBPL10, PDXDCl, PDXDC2, RORA, ANKRD13D, ZNF542, PPARD, NAPEPLD, ATPllC, EML6, GNB5, ATF3, ZC3H11A, and CCBLl.
43. A method of treating a cancer, the method comprising administering to a subject in need thereof an effective amount of a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, wherein the subject has been identified as having an elevated expression level, as compared to a control, of one or more of SLC31A1, PFKFB2, NPY6R, IGJ, NUP188, ERG, INSR, ZNF529, PIP5K1, TMEM2, TUBBP5, UBA6, SURF4, FAM122A, AMIGOl, ADAMTS9, RORA, ZNF542, PPARD, ATPllC, EML6, GNB5, ATF3, ZC3H11A, CCBLl, SHMTl, RAP2A, and CACNAlI.
44. The method of claim 43, wherein the subject is a human.
45. The method of claim 43 or 44, wherein the cancer is selected from the group consisting of a skin cancer, a liver cancer, a lung cancer, a brain tumor, a thyroid cancer, an ovarian cancer, a renal cancer and an endometrial cancer.
46. The method of claim 43 or 44, wherein the cancer is a melanoma.
47. The method of any one of claims 43 to 46, wherein the RNA level of the one or more genes is measured.
48. The method of any one of claims 43 to 46, wherein the protein level of the one or more genes is measured.
49. The method of any one of claims 43 to 46, wherein the subject has been identified as having an elevated expression level, as compared to a control, of SHMTl.
50. The method of any one of claims 43 to 46, wherein the subject has been identified as having an elevated expression level, as compared to a control, of RAP2A.
51. The method of any one of claims 43 to 46, wherein the subject has been identified as having an elevated expression level, as compared to a control, of CACNA1I.
52. A composition comprising at least five polynucleotides that selectively hybridize to each of at least five genes selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R, IGJ, NUP188, ERG, MDM1, HIPK2, INSR, ZNF529, DSCC1, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, ADAMTS9, SSPN, ZC3H6, VPS37A, OSBPLIO, PDXDCl, PDXDC2, RORA, ANKRD13D, ZNF542, PPARD, NAPEPLD, ATPllC, EML6, GNB5, ATF3, ZC3H11A, CCBL1, SHMTl, C70RF, IL22RA2, RAP2A, and CACNAlI.
53. The composition of claim 52, wherein the at least five genes are selected from the group consisting of TNKS, TTLL4, PGCP, ERG, GJB2, INSR, FAM122A, SSPN, VPS37A, PDXDCl, PDXDC2, ZNF542, ATPllC, and ZC3H11A.
54. The composition of claim 52, wherein the at least five genes are selected from the group consisting of SHMT1, C70RF, IL22RA2, TARBP2, RAP2A, and CACNA1I.
55. The composition of any one of claims 52 to 54, wherein the at least five polynucleotides are bound to a solid support.
56. A composition comprising at least three polynucleotides that selectively hybridize to each of at least three genes selected from the group consisting of SHMT1, C70RF, IL22RA2, TARBP2, RAP2A, and CACNA1I.
57. A kit comprising'- an array comprising a plurality of polynucleotides bound to a solid support, wherein the plurality comprises at least five polynucleotides that selectively hybridize to each of at least five genes selected from the group consisting of TNKS, TARBP2, TTLL4, SLC31A1, CHKA, PSPH, PGCP, PFKFB2, NPY6R, IGJ, NUP188, ERG, MDMl, HIPK2, INSR, ZNF529, DSCC1, PIP5K1, TMEM2, STAG3L4, MSRB2, TUBBP5, GDPD5, UBA6, SURF4, GJB2, ARRDC4, COPS7B, FAM122A, NEIL2, AMIGOl, ADAMTS9, SSPN, ZC3H6, VPS 37 A, OSBPL10, PDXDC1, PDXDC2, RORA, ANKRD13D, ZNF542, PPARD, NAPEPLD, ATPllC, EML6, GNB5, ATF3, ZC3H11A, CCBLl, SHMT1, C70RF, IL22RA2, RAP2A, and CACNAH; and
instructions for detecting the presence or amount of one of more of the polynucleotides in a sample.
58. The kit of claim 57, further comprising one or more reagents for isolating nucleic acid from a sample.
59. The kit of claim 57, further comprising a means for amplifying a nucleic acid.
60. A kit comprising:
an array comprising a plurality of polynucleotides bound to a solid support, wherein the plurality comprises at least three polynucleotides that selectively hybridize to each of at least three genes selected from the group consisting of SHMT1, C70RF, IL22RA2, RAP2A, TARBP2, and CACNAH; and
instructions for detecting the presence or amount of one of more of the polynucleotides in a sample.
61. A method of predicting the response of a subject to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, the method comprising:
providing a biological sample obtained from a subject; and
measuring the expression level of one or more genes in the biological sample, wherein the one or more genes comprise at least one gene selected from the group consisting of SNRNP70, CLINTl, PGCP, and CPM,
wherein an elevated expression level, as compared to a control, of one or more of SNRNP70, CLINTl, and PGCP is predictive that the subject will respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof,
and wherein an elevated expression level, as compared to a control, of CPM is predictive that the subject will not respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, or will have a reduced responsiveness to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof compared to a subject having lower expression levels of the one or more genes.
62. The method of claim 61, wherein the subject has, or is at risk of developing, a cancer.
63. The method of claim 62, wherein the cancer is selected from the group consisting of a skin cancer, a liver cancer, a lung cancer, a brain tumor, a thyroid cancer, an ovarian cancer, a renal cancer and an endometrial cancer.
64. The method of claim 62, wherein the cancer is a melanoma.
65. The method of any one of claims 61 to 64, wherein the subject is a human.
66. The method of any one of claims 61 to 65, wherein the biological sample is selected from the group consisting of a blood sample, circulating tumor cells, circulating DNA, a plasma sample, a serum sample, an urine sample, a skin sample and a tumor sample.
67. The method of any one of claims 61 to 66, further comprising
communicating the test results to the subject's health care provider.
68. The method of any one of claims 61 to 67, further comprising modifying the subject's medical record to indicate that the subject is likely to respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, if the expression level of one or more of SNRNP70, CLINT1, and PGCP is elevated, as compared to a control.
69. The method of any one of claims 61 to 67, further comprising modifying the subject's medical record to indicate that the subject is not likely to respond to a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, if the expression level of CPM is elevated, as compared to a control.
70. The method of any one of claims 61 to 67, comprising:
determining that the expression level of one or more of SNRNP70, CLINT1, and PGCP is elevated, as compared to a control; and
selecting a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof for the subject.
71. The method of any one of claims 61 to 67, comprising:
determining that the expression level of CPM is elevated, as compared to a control: and
selecting a therapy comprising an agent that is not lenvatinib for the subject.
72. The method of any one of claims 61 to 67, further comprising administering to the subject a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof.
73. A method of treating a cancer, the method comprising administering to a subject in need thereof an effective amount of a therapy comprising lenvatinib or a pharmaceutically acceptable salt thereof, wherein the subject has been identified as having an elevated expression level, as compared to a control, of one or more of SNRNP70, CLINT1, and PGCP.
74. The method of claim 73, wherein the subject is a human.
75. The method of claim 73 or 74, wherein the cancer is selected from the group consisting of a skin cancer, a liver cancer, a lung cancer, a brain tumor, a thyroid cancer, an ovarian cancer, a renal cancer and an endometrial cancer.
76. The method of claim 73 or 74, wherein the cancer is a melanoma.
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Cited By (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2014185540A1 (en) * 2013-05-14 2014-11-20 Eisai R&D Management Co., Ltd. Biomarkers for predicting and assessing responsiveness of endometrial cancer subjects to lenvatinib compounds
WO2015067710A3 (en) * 2013-11-06 2015-06-25 Universite De Rennes 1 Tyrp1, a natural mirna sponge, and its use in managing human melanoma aggressiveness
US9549922B2 (en) 2013-06-26 2017-01-24 Eisai R&D Management Co., Ltd. Use of eribulin and lenvatinib as combination therapy for treatment of cancer
WO2017027672A1 (en) * 2015-08-12 2017-02-16 Celgene Corporation Methods for treating solid tumors and the use of biomarkers as a predictor of clinical sensitivity to immunomodulatory therapies
CN106729756A (en) * 2017-02-28 2017-05-31 北京泱深生物信息技术有限公司 Application of the biomarker as target in adenocarcinoma of lung diagnosis and treatment
US9945862B2 (en) 2011-06-03 2018-04-17 Eisai R&D Management Co., Ltd. Biomarkers for predicting and assessing responsiveness of thyroid and kidney cancer subjects to lenvatinib compounds
WO2018143874A1 (en) * 2017-01-31 2018-08-09 Younis Shady Methods for identifying new therapeutic agents
US10259791B2 (en) 2014-08-28 2019-04-16 Eisai R&D Management Co., Ltd. High-purity quinoline derivative and method for manufacturing same
US11090386B2 (en) 2015-02-25 2021-08-17 Eisai R&D Management Co., Ltd. Method for suppressing bitterness of quinoline derivative
WO2021211857A1 (en) * 2020-04-15 2021-10-21 Alkermes Pharma Ireland Limited Immunostimulatory agents in combination with angiogenesis inhibitors
CN113862360A (en) * 2021-10-22 2021-12-31 中日友好医院(中日友好临床医学研究所) Methods for diagnosing, preventing and treating lung cancer
US11369623B2 (en) 2015-06-16 2022-06-28 Prism Pharma Co., Ltd. Anticancer combination of a CBP/catenin inhibitor and an immune checkpoint inhibitor
US11547705B2 (en) 2015-03-04 2023-01-10 Merck Sharp & Dohme Llc Combination of a PD-1 antagonist and a VEGF-R/FGFR/RET tyrosine kinase inhibitor for treating cancer

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2008046911A2 (en) * 2006-10-20 2008-04-24 Exiqon A/S Novel human micrornas associated with cancer
US20090227533A1 (en) * 2007-06-08 2009-09-10 Bader Andreas G miR-34 Regulated Genes and Pathways as Targets for Therapeutic Intervention
US20100076691A1 (en) * 2006-11-03 2010-03-25 Baylor Research Institute Diagnosis of Metastatic Melanoma and Monitoring Indicators of Immunosuppression Through Blood Leukocyte Microarray Analysis
US20100137149A1 (en) * 2006-12-27 2010-06-03 Snu R&Db Foundation Data processing, analysis method of gene expression data to identify endogenous reference genes
US20110071042A1 (en) * 2009-05-14 2011-03-24 Prometheus Laboratories Inc. Biomarkers for determining sensitivity of breast cancer cells to her2-targeted therapy

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2008046911A2 (en) * 2006-10-20 2008-04-24 Exiqon A/S Novel human micrornas associated with cancer
US20100076691A1 (en) * 2006-11-03 2010-03-25 Baylor Research Institute Diagnosis of Metastatic Melanoma and Monitoring Indicators of Immunosuppression Through Blood Leukocyte Microarray Analysis
US20100137149A1 (en) * 2006-12-27 2010-06-03 Snu R&Db Foundation Data processing, analysis method of gene expression data to identify endogenous reference genes
US20090227533A1 (en) * 2007-06-08 2009-09-10 Bader Andreas G miR-34 Regulated Genes and Pathways as Targets for Therapeutic Intervention
US20110071042A1 (en) * 2009-05-14 2011-03-24 Prometheus Laboratories Inc. Biomarkers for determining sensitivity of breast cancer cells to her2-targeted therapy

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
GLEN.: "Pre-clinical investigation and clinical development of E7080, a multi-targeted tyrosine kinase inhbitor: implications for melanoma", 11 August 2010 (2010-08-11), Retrieved from the Internet <URL:http://theses.gla.ac.uk/2048> [retrieved on 20120722] *
YAMADA ET AL.: "Phase I Dose-Escalation Study and Biomarker Analysis of E7080 in Patients with Advanced Solid Tumors", CLINICAL CANCER RESEARCH, vol. 17, no. 8, 15 April 2011 (2011-04-15), pages 2528 - 2537 *

Cited By (27)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11598776B2 (en) 2011-06-03 2023-03-07 Eisai R&D Management Co., Ltd. Biomarkers for predicting and assessing responsiveness of thyroid and kidney cancer subjects to lenvatinib compounds
US9945862B2 (en) 2011-06-03 2018-04-17 Eisai R&D Management Co., Ltd. Biomarkers for predicting and assessing responsiveness of thyroid and kidney cancer subjects to lenvatinib compounds
JP2016522879A (en) * 2013-05-14 2016-08-04 エーザイ・アール・アンド・ディー・マネジメント株式会社 Biomarkers for predicting and assessing responsiveness of endometrial cancer subjects to lenvatinib compounds
US10517861B2 (en) 2013-05-14 2019-12-31 Eisai R&D Management Co., Ltd. Biomarkers for predicting and assessing responsiveness of endometrial cancer subjects to lenvatinib compounds
KR102204279B1 (en) * 2013-05-14 2021-01-15 에자이 알앤드디 매니지먼트 가부시키가이샤 Biomarkers for predicting and assessing responsiveness of endometrial cancer subjects to lenvatinib compounds
KR20160009551A (en) * 2013-05-14 2016-01-26 에자이 알앤드디 매니지먼트 가부시키가이샤 Biomarkers for predicting and assessing responsiveness of endometrial cancer subjects to lenvatinib compounds
WO2014185540A1 (en) * 2013-05-14 2014-11-20 Eisai R&D Management Co., Ltd. Biomarkers for predicting and assessing responsiveness of endometrial cancer subjects to lenvatinib compounds
CN105264380A (en) * 2013-05-14 2016-01-20 卫材R&D管理有限公司 Biomarkers for predicting and assessing responsiveness of endometrial cancer subjects to lenvatinib compounds
RU2658601C2 (en) * 2013-05-14 2018-06-21 Эйсай Ар Энд Ди Менеджмент Ко., Лтд. Biomarkers for predicting and assessing responsiveness of endometrial cancer subjects to lenvatinib compounds
US9549922B2 (en) 2013-06-26 2017-01-24 Eisai R&D Management Co., Ltd. Use of eribulin and lenvatinib as combination therapy for treatment of cancer
WO2015067710A3 (en) * 2013-11-06 2015-06-25 Universite De Rennes 1 Tyrp1, a natural mirna sponge, and its use in managing human melanoma aggressiveness
US10287633B2 (en) 2013-11-06 2019-05-14 Universite De Rennes 1 TYRP1, a natural miRNA sponge, and its use in managing human melanoma aggressiveness
US10259791B2 (en) 2014-08-28 2019-04-16 Eisai R&D Management Co., Ltd. High-purity quinoline derivative and method for manufacturing same
US10407393B2 (en) 2014-08-28 2019-09-10 Eisai R&D Management Co., Ltd. High-purity quinoline derivative and method for manufacturing same
US10822307B2 (en) 2014-08-28 2020-11-03 Eisai R&D Management Co., Ltd. High-purity quinoline derivative and method for manufacturing same
US11186547B2 (en) 2014-08-28 2021-11-30 Eisai R&D Management Co., Ltd. High-purity quinoline derivative and method for manufacturing same
US11090386B2 (en) 2015-02-25 2021-08-17 Eisai R&D Management Co., Ltd. Method for suppressing bitterness of quinoline derivative
US11547705B2 (en) 2015-03-04 2023-01-10 Merck Sharp & Dohme Llc Combination of a PD-1 antagonist and a VEGF-R/FGFR/RET tyrosine kinase inhibitor for treating cancer
US11369623B2 (en) 2015-06-16 2022-06-28 Prism Pharma Co., Ltd. Anticancer combination of a CBP/catenin inhibitor and an immune checkpoint inhibitor
WO2017027672A1 (en) * 2015-08-12 2017-02-16 Celgene Corporation Methods for treating solid tumors and the use of biomarkers as a predictor of clinical sensitivity to immunomodulatory therapies
EP3334844A4 (en) * 2015-08-12 2019-11-06 Celgene Corporation Methods for treating solid tumors and the use of biomarkers as a predictor of clinical sensitivity to immunomodulatory therapies
WO2018143874A1 (en) * 2017-01-31 2018-08-09 Younis Shady Methods for identifying new therapeutic agents
CN106729756B (en) * 2017-02-28 2021-05-25 青岛泱深生物医药有限公司 Application of biomarker as target in diagnosis and treatment of lung adenocarcinoma
CN106729756A (en) * 2017-02-28 2017-05-31 北京泱深生物信息技术有限公司 Application of the biomarker as target in adenocarcinoma of lung diagnosis and treatment
WO2021211857A1 (en) * 2020-04-15 2021-10-21 Alkermes Pharma Ireland Limited Immunostimulatory agents in combination with angiogenesis inhibitors
US11834483B2 (en) 2020-04-15 2023-12-05 Alkermes Pharma Ireland Limited Immunostimulatory agents in combination with angiogenesis inhibitors
CN113862360A (en) * 2021-10-22 2021-12-31 中日友好医院(中日友好临床医学研究所) Methods for diagnosing, preventing and treating lung cancer

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