WO2014089055A1 - Prévision de réponse au tivozanib - Google Patents

Prévision de réponse au tivozanib Download PDF

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Publication number
WO2014089055A1
WO2014089055A1 PCT/US2013/072841 US2013072841W WO2014089055A1 WO 2014089055 A1 WO2014089055 A1 WO 2014089055A1 US 2013072841 W US2013072841 W US 2013072841W WO 2014089055 A1 WO2014089055 A1 WO 2014089055A1
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hypoxia
tumor
gene
signature
tivozanib
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PCT/US2013/072841
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English (en)
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Bin Feng
Richard NICOLETTI
Murray Robinson
Andrew Louis Strahs
Maria Isabel CHU
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Aveo Pharmaceuticals, Inc.
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Publication of WO2014089055A1 publication Critical patent/WO2014089055A1/fr

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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 field of the invention is molecular biology, genetics, oncology, bioinformatics and clinical diagnostics.
  • biomarker is defined as "a characteristic that is objectively measured and evaluated as an indicator of normal biologic or pathogenic processes or pharmacological response to a therapeutic intervention.”
  • the challenge is discovering cancer biomarkers. Although there have been
  • types - such as chronic myeloid leukemia, gastrointestinal stromal tumor,
  • the problem mainly lies in the inability to select patients with
  • a prognostic biomarker is used to classify a cancer, e.g., a solid tumor, according to aggressiveness, i.e., rate of growth and/or metastasis, and refractiveness to treatment. This is sometimes called distinguishing "good outcome” tumors from “poor outcome” tumors.
  • a predictive biomarker is used to assess the probability that a particular patient will benefit from treatment with a particular drug.
  • HER2 HER2 or NEU
  • trastuzumab HERCEPTI ®
  • PD biomarkers are an indication of the effect(s) of a drug on a patient while the patient is taking the drug. Accordingly, PD biomarkers often are used to guide dosage level and dosing frequency, during the early stages of clinical development of a new drug. For a discussion of cancer biomarkers, see, e.g., Sawyers, 2008, Nature 452:548-552.
  • Tivozanib (also known as AV-951) is a potent and selective small-molecule inhibitor of VEGF receptors 1, 2 and 3. Tivozanib exhibits picomolar inhibitory activity against all three receptors, and it exhibits antitumor activity in preclinical models (Nakamura et al, 2006, Cancer Res. 66:9134-9142). In a global, randomized Phase 3 superiority clinical trial evaluating the efficacy and safety of tivozanib compared to sorafenib in 517 patients with advanced renal cell carcinoma ("TIVO-1"), tivozanib yielded positive results (Motzer et al, 2012 ASCO Annual Meeting, Abstract No. 4501).
  • TIVO-1 advanced renal cell carcinoma
  • the invention is based on the identification of a set of genes that: (a) are related to the hypoxia response in mammalian cells; (b) display coherence in their expression level in humans; and (c) whose expression levels collectively indicate whether a human tumor is likely to be responsive (sensitive) or non-responsive (resistant) to treatment with the anti-cancer drug known as tivozanib. Accordingly, the invention provides a method for predicting quantitatively whether a human tumor will be responsive or non-responsive to treatment with tivozanib.
  • the method includes the following steps: (a) measuring, in a tissue sample from a human tumor, the relative expression level of at least six genes in a hypoxia signature, wherein the hypoxia signature consists of the following nine genes (denoted by the Human Gene Organisation (HUGO) gene symbol): ADM, CA9, EGLN3, NDRG1, SLC2A1, VEGFA, EPAS1, ANGPT2 and PGF; and
  • El, E2, ... En are the expression levels of the nine genes in the hypoxia signature, or a six-, seven- or eight-gene subset thereof.
  • An exemplary six-gene subset of the nine-gene hypoxia signature above consists of the following genes: ADM, CA9, EGLN3, NDRG1, SLC2A1, and VEGFA.
  • hypoxia signature expression level above a defined threshold indicates that the tumor is likely to be responsive to tivozanib
  • a hypoxia signature expression level below a defined threshold indicates that the tumor is likely to be non-responsive to tivozanib.
  • the term "hypoxia signature expression level" takes into account the expression levels of all nine genes in the hypoxia signature, or a six-, seven- or eight-gene subset thereof.
  • the hypoxia signature score may be directly correlated or inversely correlated with the hypoxia signature expression level, depending on the gene expression assay method and the units of measurement used. For example, when qRT-PCR results are expressed in terms of Or values, there is an inverse relationship between CT value and gene expression level. In other words, a lower CT value corresponds to a higher gene expression level.
  • the method includes normalizing the relative expression level of each gene in the hypoxia signature using an internal gene expression standard for each sample.
  • An exemplary internal gene expression standard is the mean expression of the following genes: MUS81, ZNF384, I O80D, RPLP 1 and CFL1.
  • the method includes performing a threshold determination analysis, thereby generating a defined threshold.
  • the threshold determination analysis can include a receiver operator characteristic curve analysis.
  • the relative gene expression level for each gene in the hypoxia signature can be obtained by measuring the messenger RNA (mRNA) level for that gene.
  • Suitable methods for measuring mRNA levels in tumor tissue samples include DNA microarray analysis, quantitative reverse transcriptase polymerase chain reaction (qRT-PCR), e.g., TAQMAN ® assays, quantitative nuclease protection assays, and nuclear "barcode” assays, e.g., the NanoString® nCounterTM assay.
  • qRT-PCR quantitative reverse transcriptase polymerase chain reaction
  • TAQMAN ® assays quantitative nuclease protection assays
  • nuclear "barcode” assays e.g., the NanoString® nCounterTM assay.
  • the invention provides a probe set (e.g., a PCR primer set) that comprises probes (e.g., PCR primer pairs) for measuring expression of each gene in the hypoxia signature gene set.
  • the probe set can be incorporated into a diagnostic test kit.
  • the invention provides a method of treating a cancer patient.
  • the method comprises: (a) determining whether the patient is likely to be responsive to tivozanib by: (1) measuring, in a tissue sample from a tumor in the patient, the relative expression level of at least six genes in a hypoxia signature consisting of the following genes: ADM, CA9,
  • hypoxia. signature. score
  • El, E2, ... En are the expression levels of the nine genes in the hypoxia signature, or a six-, seven- or eight-gene subset thereof; and wherein a hypoxia signature expression level above a defined threshold indicates that the tumor is likely to be responsive to tivozanib, and a hypoxia signature expression level below the defined threshold indicates that the tumor is likely to be resistant to tivozanib; and (b) administering to the patient a therapeutically effective amount of tivozanib if step (a) yields a result indicating that the tumor is likely to be responsive to tivozanib.
  • Exemplary human tumors and cancers whose responsiveness to treatment and/or that can be treated using the approaches disclosed herein may include kidney cancer (e.g., kidney renal clear cell carcinoma, kidney renal papillary cell carcinoma, kidney chromophobe), breast cancer (e.g., breast invasive carcinoma), bladder cancer (e.g., bladder urothelial carcinoma), colorectal cancer (e.g., colon adenocarcinoma), rectal cancer (e.g., rectum adenocarcinoma), cervical cancer (e.g., cervical squamous cell carcinoma and endocervical adenocarcinoma), ovarian cancer (e.g., ovarian serous cystadenocarcinoma), uterine cancer (e.g., uterine corpus endometrial carcinoma), brain cancer (e.g., glioblastoma multiforme, brain lower grade glioma), head and neck cancer (e.g., head and neck squam
  • FIG. 1 is a Kaplan-Meier plot comparing data from the hypoxia-low population and the hypoxia-high population from the tivozanib arm of the ⁇ -l clinical trial.
  • PFS progression-free survival
  • FIG. 2 is a Kaplan-Meier plot comparing data from the hypoxia-low population and the hypoxia-high population from the sorafenib arm of the TIVO-1 clinical trial.
  • FIG. 3 is a waterfall plot showing hypoxia signature scores across 4,706 tumor samples of 20 different cancer types.
  • the horizontal axis represents tumor samples of 20 different cancer types organized by cancer type. Cancer types are abbreviated using the abbreviations provided in Table 8.
  • the vertical axis represents hypoxia signature score for each sample. Hypoxia signature scores were normalized to the median across all samples for each cancer type. Hypoxia signature scores are presented from low to high with signatures scores above and below the median.
  • BRCA breast cancer
  • gray bars represent triple-negative breast cancer (TNBC) samples and white bars represent non-TNBC samples.
  • the expression levels of the genes of the hypoxia signature can be used collectively as a multigene predictive biomarker for classifying human tumors according to their likelihood of responding to treatment with the anti-tumor drug tivozanib, a VEGF tyrosine kinase inhibitor (TKI).
  • TKI VEGF tyrosine kinase inhibitor
  • Such classification of tumors is useful for identifying human patients who are suitable candidates for treatment with tivozanib in a clinical setting.
  • the method described herein is surprisingly specific for tivozanib. This is demonstrated by the fact that hypoxia signature scores do not show statistically significant correlation with clinical response to the anti-tumor drug sorafenib, another VEGF TKI. Definitions
  • AV-951 and “tivozanib” mean N- ⁇ 2-chloro-4-[(6,7-dimethoxy-4- quinolyl)oxy]-phenyl ⁇ -N'-(5-methyl-3-isoxazolyl)urea, which has the following chemical structure, including salts and polymorphs thereof:
  • optimum threshold hypoxia signature score means the threshold hypoxia signature score at which the classifier gives the most desirable balance between the cost of false negative calls and false positive calls.
  • El, E2, ... En are the expression levels of the nine genes in the hypoxia signature, or a six-, seven- or eight-gene subset thereof.
  • probe means a molecule that can be used for measuring the expression of a particular gene.
  • exemplary probes include PCR primers; gene-specific DNA oligonucleotide probes, such as microarray probes affixed to a microarray substrate;
  • ROC receiver operating characteristic
  • threshold determination analysis means analysis of a dataset representing a given tumor type, e.g. , human renal cell carcinoma, breast tumor, or colorectal tumor, to determine a threshold hypoxia signature score, e.g., an optimum threshold hypoxia signature score, for that particular tumor type.
  • the dataset representing a given tumor type includes (a) actual response data (response or non-response), and (b) a hypoxia signature score for each tumor from a group of tumor- bearing mice or humans.
  • TNBC triple-negative breast cancer
  • ER estrogen receptor
  • PR progesterone receptor
  • Her2/neu Her2/neu
  • hypoxia signature consists of, or consists essentially of, expression levels of the nine human genes listed in Table 1 below:
  • tissue samples A tissue sample from a tumor in a human patient can be used as a source of RNA, so that a hypoxia signature gene expression level can be determined.
  • tumors are carcinomas, sarcomas, gliomas and lymphomas.
  • specific cancers on which the disclosed methods can be used include renal cell carcinoma, colorectal cancer, rectal cancer, breast cancer, cervical cancer, uterine cancer, ovarian cancer, bladder cancer, brain cancer, liver cancer, lung cancer, pancreatic cancer, skin cancer and thyroid cancer.
  • the tissue sample can be obtained by using conventional tumor biopsy instruments and procedures. Endoscopic biopsy, excisional biopsy, incisional biopsy, fine needle biopsy, punch biopsy, shave biopsy and skin biopsy are examples of recognized medical procedures that can be used by the skilled person to obtain tumor samples for practicing the methods described herein.
  • the tumor tissue sample should be large enough to provide sufficient RNA for measuring individual gene expression levels.
  • the tissue sample from a tumor is in the form of circulating tumor cells (CTCs) in a blood sample.
  • CTCs circulating tumor cells
  • the tumor tissue sample can be in any form that allows quantitative analysis of gene expression or transcript abundance.
  • RNA is isolated from the tissue sample prior to quantitative analysis. Some methods of RNA analysis, however do not require RNA extraction, e.g., the qNPATM technology commercially available from High Throughput Genomics, Inc. (Tucson, AZ). Accordingly, the tissue sample can be fresh, preserved through suitable cryogenic techniques, or preserved through non-cryogenic techniques.
  • Tissue samples used in the disclosed methods can be clinical biopsy specimens, which often are fixed in formalin and then embedded in paraffin. Samples in this form are commonly known as formalin-fixed, paraffin-embedded (FFPE) tissue. Techniques of tissue preparation and tissue preservation suitable for use in the present invention are well-known to those skilled in the art.
  • Macrodissection or microdissection methods can be used to obtain a tissue sample from a tumor.
  • LMPC Laser Microdissection and Pressure Catapulting
  • the PALM ® Micro Beam microscope P.A.L.M. Microlaser Technologies AG, Bernried, Germany
  • SL-Microtest UV laser microdissection system Molecular Machines & Industries, Glattbrugg, Switzerland
  • Primary tumor cell cultures can be prepared from the sample in order to produce a pure tumor cell population.
  • the human tumor tissue sample is a tumor cell preparation derived from a blood sample containing circulating tumor cells.
  • Methods for obtaining such cells are known in the art. See, e.g., Danila et ah, 2001 , Clin. Cancer. Res. 13:7053-7058; Paterlini-Brechot et al, 2007, Cancer Lett. 253 : 180-204.
  • RNA isolation DNA microarray analysis and qRT-PCR generally involve RNA isolation from a tissue sample. Methods for rapid and efficient extraction of eukaryotic mRNA, i.e., poly(A) RNA, from tissue samples are well-established and known to persons skilled in the art. See, e.g., Ausubel et ah, 1997, Current Protocols of Molecular Biology, John Wiley & Sons.
  • the tissue sample can be fresh, frozen or fixed paraffin-embedded (FFPE) clinical study tumor specimens.
  • FFPE paraffin-embedded
  • FFPE samples of tumor material are more readily available, and FFPE samples are suitable sources of RNA for use in the methods disclosed herein.
  • FFPE samples are suitable sources of RNA for use in the methods disclosed herein.
  • FFPE samples are suitable sources of RNA for gene expression profiling by RT-PCR.
  • RNA isolation products and complete kits include Qiagen (Valencia, CA), Invitrogen (Carlsbad, CA), Ambion (Austin, TX) and Exiqon (Woburn, MA).
  • RNA isolation begins with tissue and cell disruption. During tissue and cell disruption, it is desirable to minimize RNA degradation by RNases.
  • One approach to limiting RNase activity during the RNA isolation process is to ensure that a denaturant is in contact with cellular contents as soon as the cells are disrupted.
  • Another common practice is to include one or more proteases in the RNA isolation process.
  • fresh tissue samples are immersed in an RNA stabilization solution, at room temperature, as soon as they are collected. The stabilization solution rapidly permeates the cells, stabilizing the RNA for storage at 4°C, for subsequent isolation.
  • RNAlater ® is available commercially as RNAlater ® (Ambion, Austin, TX).
  • RNA is isolated from disrupted tumor material by cesium chloride density gradient centrifugation.
  • mRNA makes up approximately 1% to 5% of total cellular RNA.
  • Immobilized oligo(dT), e.g., oligo(dT) cellulose is commonly used to separate mRNA from ribosomal RNA and transfer RNA. If stored after isolation, RNA must be stored under RNase-free conditions. Methods for stable storage of isolated RNA are known in the art. Various commercial products for stable storage of RNA are available.
  • a DNA microarray is a collection of specific DNA segments or probes affixed to a solid surface or substrate such as glass, plastic or silicon, with each specific DNA segment occupying a known location in the array.
  • Hybridization with a sample of labeled RNA usually under stringent hybridization conditions, allows detection and quantitation of RNA molecules corresponding to each probe in the array.
  • the microarray is scanned by confocal laser microscopy or other suitable detection method.
  • Modern commercial DNA microarrays often known as DNA chips, typically contain tens of thousands of probes, and thus can measure expression of tens of thousands of genes simultaneously. Such microarrays can be used in practicing the disclosed methods.
  • a two-color microarray reader can be used.
  • samples are labeled with a first fluorophore that emits at a first wavelength
  • an RNA or cDNA standard is labeled with a second fluorophore that emits at a different wavelength.
  • Cy3 (570 nm) and Cy5 (670 nm) often are employed together in two-color microarray systems.
  • DNA microarray technology is well-developed, commercially available, and widely employed.
  • microarray technology to measure expression levels of genes in the hypoxia signature without undue experimentation.
  • DNA microarray chips, reagents (such as those for RNA or cDNA preparation, RNA or cDNA labeling, hybridization and washing solutions), instruments (such as microarray readers) and protocols are well-known in the art and available from various commercial sources.
  • Commercial vendors of microarray systems include Agilent Technologies (Santa Clara, CA) and Affymetrix (Santa Clara, CA), but other microarray systems can be used.
  • Quantitative RT-PCR The level of mRNA representing individual genes in the hypoxia signature can be measured using conventional quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) technology. Advantages of qRT-PCR include sensitivity, flexibility, quantitative accuracy, and ability to discriminate between closely related mRNAs. Guidance concerning the processing of tissue samples for quantitative PCR is available from various sources, including manufacturers and vendors of commercial products for qRT-PCR (e.g., Qiagen (Valencia, CA) and Ambion (Austin, TX)). Instrument systems for automated performance of qRT-PCR are commercially available and used routinely in many laboratories. An example of a well-known commercial system is the Applied Biosystems 7900HT Fast Real-Time PCR System (Applied Biosystems, Foster City, CA).
  • the first step in gene expression profiling by RT- PCR is the reverse transcription of the mRNA template into cDNA, which is then exponentially amplified in a PCR reaction.
  • Two commonly used reverse transcriptases are avilo
  • AMV-RT myeloblastosis virus reverse transcriptase
  • MMLV-RT Moloney murine leukemia virus reverse transcriptase
  • the reverse transcription reaction typically is primed with specific primers, random hexamers, or oligo(dT) primers. Suitable primers are commercially available, e.g., GeneAmp ® RNA PCR kit (Perkin Elmer, Waltham, MA).
  • the resulting cDNA product can be used as a template in the subsequent polymerase chain reaction.
  • the PCR step is carried out using a thermostable DNA-dependent DNA
  • the polymerase most commonly used in PCR systems is a Thermus aquaticus (Taq) polymerase.
  • the selectivity of PCR results from the use of primers that are
  • primers specific to each gene in the hypoxia signature are based on the cDNA sequence of the genes.
  • Commercial technologies such as SYBR ® green or TaqMan ® (Applied Biosystems, Foster City, CA) can be used in accordance with the vendor's instructions.
  • Messenger RNA levels can be normalized for differences in loading among samples by comparing the levels of housekeeping genes such as beta-actin or GAPDH.
  • the level of mRNA expression can be expressed relative to any single control sample such as mRNA from normal, non-tumor tissue or cells. Alternatively, it can be expressed relative to mRNA from a pool of tumor samples, or tumor cell lines, or from a commercially available set of control mRNA.
  • Suitable primer sets for PCR analysis of expression levels of genes in the hypoxia signature can be designed and synthesized by one of skill in the art, without undue
  • PCR primer sets for practicing the disclosed methods can be purchased from commercial sources, e.g., Applied Biosystems, based on the sequences of genes in the hypoxia signature.
  • PCR primers preferably are about 17 to 25 nucleotides in length.
  • Primers can be designed to have a particular melting temperature (Tm), using conventional algorithms for Tm estimation.
  • Software for primer design and Tm estimation are available commercially, e.g., Primer ExpressTM (Applied Biosystems), and also are available on the internet, e.g., Primer3 (Massachusetts Institute of Technology).
  • Quantitative Nuclease Protection Assay An example of a suitable method for determining expression levels of genes in the hypoxia signature without an RNA extraction step is the quantitative nuclease protection assay (qNPATM), which is commercially available from High Throughput Genomics, Inc. (aka “HTG”; Arlington, AZ).
  • qNPATM quantitative nuclease protection assay
  • samples are treated in a 96-well plate with a proprietary Lysis Buffer (HTG), which releases total RNA into solution.
  • Lysis Buffer HCG
  • Gene-specific DNA oligonucleotides i.e., specific for each gene in the hypoxia signature, are added directly to the Lysis Buffer solution, and they hybridize to the RNA present in the Lysis Buffer solution.
  • the DNA oligonucleotides are added in excess, to ensure that all RNA molecules complementary to the DNA oligonucleotides are hybridized.
  • S I nuclease is added to the mixture.
  • the SI nuclease digests the non-hybridized portion of the target RNA, all of the non-target RNA, and excess DNA oligonucleotides. Then the SI nuclease enzyme is inactivated.
  • the RNA-DNA heteroduplexes are treated to remove the RNA portion of the duplex, leaving only the previously protected oligonucleotide probes.
  • the surviving DNA oligonucleotides are a stoichiometrically representative library of the original RNA sample.
  • the qNPA oligonucleotide library can be quantified using the ArrayPlate Detection System (HTG).
  • HOG ArrayPlate Detection System
  • NanoString® nCounter Analysis Another example of a technology suitable for determining expression levels of genes in the hypoxia signature is a commercially available assay system based on probes with molecular "barcodes" is the NanoString® nCounterTM Analysis system (NanoString Technologies, Seattle, WA). This system is designed to detect and count hundreds of unique transcripts in a single reaction. Each color-coded barcode is attached to a single target-specific probe corresponding to a gene of interest, e.g., a gene in the hypoxia signature.
  • probes When mixed together with controls, probes form a multiplexed "CodeSet."
  • the NanoString technology employs two approximately 50-base probes per mRNA, that hybridize in solution.
  • a “reporter probe” carries the signal, and a “capture probe” allows the complex to be immobilized for data collection. After hybridization, the excess probes are removed, and the probe/target complexes are aligned and immobilized in nCounter cartridges, which are placed in a digital analyzer.
  • the nCounter analysis system is an integrated system comprising an automated sample prep station, a digital analyzer, the CodeSet (molecular barcodes), and all of the reagents and consumables needed to perform the analysis. [0044] QuantiGene® Plex Assay.
  • RNA targets are a commercially available assay system known as the QuantiGene® Plex Assay (Panomics, Fremont, CA).
  • QuantiGene® Plex Assay Panomics, Fremont, CA
  • This technology combines branched DNA signal amplification with xMAP (multi-analyte profiling) beads, to enable simultaneous quantification of multiple RNA targets directly from fresh, frozen or FFPE tissue samples, or purified RNA preparations.
  • xMAP multi-analyte profiling
  • Hypoxia signature expression levels preferably are interpreted with respect to a threshold hypoxia signature gene expression level. Hypoxia signature expression levels higher than the threshold hypoxia signature expression level will be interpreted as indicating a tumor likely to be responsive (sensitive) to tivozanib treatment. Hypoxia signature gene expression levels lower than the threshold hypoxia signature expression level will be interpreted as indicating a tumor likely to be non-responsive (resistant) to tivozanib treatment. [0047] When discussing or interpreting hypoxia signature data, the skilled person will be aware that a gene expression "score" and gene expression level may be directly related, or inversely related, depending on the gene expression assay method and units of measurement employed.
  • tumor type takes into account (a) species (mouse or human); and (b) organ or tissue of origin.
  • tumor type further takes into account tumor categorization based on gene expression characteristics, e.g., HER2 -positive breast tumors, or non-small cell lung tumors expressing a particular EGFR mutation.
  • threshold determination analysis includes receiver operator characteristic (ROC) curve analysis.
  • ROC curve analysis is an established statistical technique, the application of which is within ordinary skill in the art. For a discussion of ROC curve analysis, see generally Zweig et at, 1993, "Receiver operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine," Clin. Chem. 39:561-577; and Pepe, 2003, The statistical evaluation of medical tests for classification and prediction, Oxford Press, New York.
  • Hypoxia signature scores and the optimum threshold hypoxia signature score may vary from tumor type to tumor type.
  • a threshold determination analysis preferably is performed on one or more datasets representing any given tumor type to be tested using the present invention.
  • the dataset used for threshold determination analysis includes: (a) actual response data (response or non-response), and (b) a hypoxia signature score for each tumor sample from a group of human tumors or mouse tumors. Once a hypoxia signature score threshold is determined with respect to a given tumor type, that threshold can be applied to interpret hypoxia signature scores from tumors of that tumor type.
  • the ROC curve analysis is performed essentially as follows. A sample with a hypoxia signature expression level above threshold is classified as a responder, and a sample with a hypoxia signature expression level below the threshold is classified as a non-responder. Whether the hypoxia signature score is higher or lower will depend on the type of assay and the units of measure employed. For every hypoxia signature expression level from a tested set of samples, "responders" and “non-responders” (hypothetical calls) are classified using that hypoxia signature score as the threshold. This process enables calculation of TPR (y vector) and FPR (x vector) for each potential threshold, through comparison of hypothetical calls against the actual response data for the data set.
  • ROC curve is constructed by making a dot plot, using the TPR vector, and FPR vector. If the ROC curve is above the diagonal from (0, 0) point to (1.0, 0.5) point, it shows that the hypoxia signature test result is a better test than random. [0053] The ROC curve can be used to identify the best operating point. The best operating point is the one that yields the best balance between the cost of false positives weighed against the cost of false negatives. These costs need not be equal.
  • the average expected cost of classification at point x,y in the ROC space is denoted by the expression
  • False positives and false negatives can be weighted differently by assigning different values for alpha and beta. For example, if it is decided to include more patients in the responder group at the cost of treating more patients who are non-responders, one can put more weight on alpha. In this case, it is assumed that the cost of false positive and false negative is the same (alpha equals beta). Therefore, the average expected cost of classification at point x,y in the ROC space is:
  • the smallest C can be calculated after using all pairs of false positive and false negative (x, y).
  • the optimum hypoxia signature score threshold is calculated as the hypoxia signature score of the (x, y) at C
  • a hypoxia signature score provides an approximate, but useful, indication of how likely a tumor is to be responsive or non-responsive.
  • the higher the hypoxia signature expression the more likely a tumor is to be responsive to tivozanib, and the lower the hypoxia signature expression, the more likely a tumor is to be resistant to tivozanib.
  • the invention includes a probe set for measuring expression of the nine genes of the hypoxia signature, i.e., the genes in Table 1 (above), or a six-, seven- or eight-gene subset thereof, in a tissue sample from a tumor.
  • the probe set is not a whole genome probe set.
  • the probe set is optimized for measuring expression of the nine genes of the hypoxia signature.
  • the probe set contains probes for measuring expression of fewer than 1,000 genes.
  • the probe set contains probes for measuring fewer than 500 genes.
  • the probe set contains probes for measuring expression of fewer than 100 genes.
  • the probe set contains probes for measuring expression of fewer than 50 genes.
  • the probe set includes probes for measuring expression of one or more genes used as internal standards.
  • genes to be used as internal standards can be affected by the type of tissue sample to be tested.
  • a suitable set of internal standards for renal cell carcinoma samples is MUS81, ZNF384, INO80D, RPLP1 and CFL1 (Gene ID Nos. 80198, 171017, 54891, 6176 and 1072, respectively).
  • Another exemplary set of internal standards for renal cell carcinoma samples is ARF 1, ATP5E, I O80D, RPLP1 and CFL1 (Gene ID Nos. 375, 514, 54891, 6176 and 1072, respectively).
  • a suitable set of internal standards for breast tumor samples is CFLl, EEFIG, PPIA, RPL3 and RPS27A (Gene ID Nos. 1072, 1937, 5478, 6122 and 6233, respectively).
  • a suitable set of internal standards for colorectal tumor samples is CIAOl, HNRNPL, ELAVL1, CHTOP, and RAB7A (Gene ID Nos, 9391, 3191, 1994, 26097 and 7879, respectively).
  • CIAOl HNRNPL
  • ELAVL1 ELAVL1
  • CHTOP CHTOP
  • RAB7A Gene ID Nos, 9391, 3191, 1994, 26097 and 7879, respectively.
  • the probe set is part of a diagnostic test kit that contains other components such as buffers, reagents and detailed instructions for using the probe set, e.g., in the methods described herein.
  • a diagnostic test kit can enhance the convenience and reproducibility in the performance of the methods described herein.
  • the probe set can be incorporated into a single microarray chip, a single qRT-PCR card, a single nCounter AnalysisTM CodeSet (NanoString®
  • a basic diagnostic test kit includes PCR primers for all the members of a hypoxia signature used in the methods described herein.
  • the kit includes PCR primers for genes to be used as internal standards.
  • a kit for testing renal cell carcinoma samples could include primers for MUS81, ZNF384, INO80D, RPLPl and CFLl, as internal standards.
  • a more elaborate test kit contains not only PCR primers, but also buffers, reagents and detailed instructions for measuring the expression levels of the members of a hypoxia signature, using PCR technology.
  • the kit includes a test protocol and all the
  • the invention includes a method of treating a cancer patient, comprising:
  • hypoxia signature consisting of the following genes: ADM, CA9, EGLN3, NDRG1, SLC2A1, VEGFA, EPAS 1, ANGPT2 and PGF (or a six-, seven- or eight-gene subset thereof); and
  • hypoxia.signature.score — * £/
  • El, E2, ... En are the expression levels of the nine genes in the hypoxia signature (or six-, seven- or eight-gene subset thereof), and wherein a hypoxia signature expression level above a defined threshold indicates that the tumor is likely to be responsive to tivozanib, and a hypoxia signature expression level below the defined threshold indicates that the tumor is likely to be resistant to tivozanib; and
  • the invention provides a method of treating a tumor in a patient, the method comprising administering to the patient a therapeutically effective amount of tivozanib, wherein the tumor has been identified as being responsive to tivozanib using the response prediction methods described herein.
  • the prediction method involves determining whether the tumor in the patient is likely to be responsive to tivozanib by:
  • hypoxia signature consisting of the following genes: ADM, CA9, EGLN3, NDRG1, SLC2A1, VEGFA, EPAS1, ANGPT2 and PGF (or a six-, seven- or eight- gene subset thereof); and
  • hypoxia.signature.score — * £/
  • El, E2, ... En are the expression levels of the nine genes in the hypoxia signature (or six-, seven- or eight-gene subset thereof), and wherein a hypoxia signature expression level above a defined threshold indicates that the tumor is likely to be responsive to tivozanib, and a hypoxia signature expression level below the defined threshold indicates that the tumor is likely to be resistant to tivozanib.
  • Information on tivozanib dosage level, dosing schedule, and potential side effects is known in the art. See, e.g., Nosov et al, 2012, J. Clin. Oncology 30: 1678-1685.
  • ccRCC Cluster 1 subtype Three previously unrecognized tumor classes or molecular subtypes were identified using hierarchical clustering of microarray data. These three molecular subtypes (ccRCC Cluster 1 subtype, ccRCC Cluster 2 subtype, and ccRCC Cluster 3 subtype) were found in different microarray datasets representing ccRCC tumor samples, using Gene Set Enrichment Analysis, with 51 non-overlapping sets of coherent genes, which represent a comprehensive set of molecular phenotypes. As shown below in Examples 3-4, one of these three molecular subtypes (ccRCC Cluster 3 subtype) was associated with: (a) low hypoxia signature expression level, and (b) resistance to treatment with tivozanib.
  • Example 2 Hypoxia Signature
  • hypoxia signature A nine-gene signature, designated herein as the hypoxia signature, was identified on the basis of several criteria, including association with HIF transcription, association with hypoxia, dynamic range in expression assays, and coherence.
  • coherence means that expression levels of the members of the gene set display a statistically significant tendency to increase or decrease in concert, within a given type of tissue, e.g., tumor tissue.
  • coherent genes share a common involvement in one or more biological functions.
  • the biological function is mammalian cellular response to hypoxia.
  • the hypoxia signature genes are the following nine human genes: ADM, CA9, EGLN3, NDRGl, SLC2A1, VEGFA, EPAS1, ANGPT2 and PGF.
  • a 22-sample pilot study was performed using microarray and RT-PCR analysis of FFPE samples from human RCC patients.
  • One purpose of the pilot study was to generate reference (normalization) data for each of the nine genes in the hypoxia signature.
  • the mean and standard deviation obtained in the pilot study for each of the nine hypoxia signature genes are in Table 2 below.
  • Another purpose of the pilot study was to determine a hypoxia signature classification cutoff (threshold) score for identifying ccRCC Cluster 3 subtype tissue.
  • the cutoff score was found to be a ⁇ value of 1.28.
  • a hypoxia signature expression level below this value was found to be associated with ccRCC Cluster 3 subtype tumors.
  • the data in the pilot study were used in subsequent analysis of samples from the TIVO-1 trial.
  • TIVO- 1 was a global, randomized Phase 3 superiority clinical trial evaluating the efficacy and safety of investigational drug tivozanib compared to sorafenib in 517 patients with advanced RCC (Motzer et al, 2012 ASCO Annual Meeting, Abstract No. 4501). All patients in TIVO- 1 had clear cell RCC, had undergone a prior nephrectomy, and had not been treated previously with either a VEGF or mTOR therapy. TIVO-1 demonstrated a significant improvement in progression-free survival (PFS) in patients receiving tivozanib vs. sorafenib.
  • PFS progression-free survival
  • a tertiary objective in the TIVO-1 trial was to study biomarkers in blood and archived tumor samples, and their correlations with drug response in patients treated with tivozanib or sorafenib.
  • FFPE samples from 105 patients were analyzed by RT-PCR.
  • 80 samples passed quality control examination.
  • eleven were excluded because they yielded non-detectable activity in assays for at least one of five housekeeping genes used as internal controls.
  • 33 were from the tivozanib treatment arm of the trial, and 36 were from the sorafenib arm.
  • a ACT for each gene in the hypoxia signature was calculated by subtracting the mean of the five pre-specified housekeeping genes (MUS81, ZNF384, I O80D, RPLP1 and CFLl) from the CT for each gene in each sample.
  • the ACT for each gene is a normalized value that represents the difference in that gene's expression level with respect to a mean housekeeping gene expression level, which is used as an internal expression standard for each sample.
  • the Entrez Gene ID numbers for the pre-specified housekeeping genes are shown in Table 3A below.
  • the hypoxia signature score for each sample was calculated by: (a) subtracting the mean of the same gene in the pilot study, (b) dividing by the standard deviation of the same gene in the pilot study, and (c) calculating the average expression, i.e., average ⁇ , of the nine hypoxia signature genes in each sample.
  • the purpose of steps (a) and (b) in this calculation was to give equal weight to each of the nine genes in the hypoxia signature. It was subsequently determined that the normalization provided by steps (a) and (b) is not necessary, but is optional.
  • the biomarker statistical analysis plan included two different statistical treatments of the gene expression data from the nine-gene hypoxia signature test, i.e., a dichotomous variable treatment, and continuous variable treatment.
  • a dichotomous variable treatment the classification cut-off (threshold) applied to the hypoxia signature results had been previously determined to be 1.28 CT, in the pilot study (Example 3 above).
  • the hypoxia- positive subset was defined as the samples with a hypoxia signature score of 1.28 CT or lower, and the hypoxia-negative subset was defined as the samples with a hypoxia signature score higher than 1.28 CT.
  • the effectiveness of tivozanib in the hypoxia-positive and hypoxia- negative populations was estimated using Cox proportional hazard models.
  • sorafenib in the hypoxia-positive and hypoxia-negative populations also was estimated using Cox proportional hazard models.
  • association between tivozanib treatment (PFS) or sorafenib treatment (PFS) and hypoxia signature score was calculated as a continuous variable, using Cox proportional hazards models.
  • the results of these analyses were consistent with those in which hypoxia signature score was dichotomized. They demonstrated the association between hypoxia signature score and tivozanib treatment (PFS), and indicate that this association is stronger than the association between hypoxia signature score and sorafenib treatment (PFS).
  • any eight-gene subset randomly chosen from the nine hypoxia genes, any seven-gene subset randomly chosen from the nine hypoxia genes, and any six-gene subset randomly chosen from the nine hypoxia genes yields an individual mean expression score that is statistically significantly correlated with tivozanib efficacy (PFS).
  • the present invention includes embodiments based on any of the nine possible eight-gene subsets of the nine-gene hypoxia signature, all nine of which are listed below in Table 5.
  • Table 5
  • the present invention includes embodiments based on any of the 36 possible seven- gene subsets of the nine-gene hypoxia signature, all 36 of which are listed below in Table 6.
  • the present invention includes embodiments based on any of the 84 possible six- gene subsets of the nine-gene hypoxia signature, all 84 of which are listed below in Table 7.
  • RNA-seq data were normalized as described herein.
  • a normalized count of TCGA RNA-seq level 3 data was downloaded for the twenty cancer types listed in Table 8. Data were transformed as log2(normalized count + 1).
  • the median-center for each gene across 4,706 samples corresponding to the twenty cancer types was determined by subtracting the median value for all 4,706 samples for each gene.
  • a hypoxia signature score using the mean the nine hypoxia genes for each of the 4,706 samples was calculated, then each sample was ordered by cancer type first and followed by hypoxia signature score from low to high (FIG. 3). Cut-off points may be identified based on biomarker clinical trial data as described in Examples 7 and 8. Table 8 shows the distribution of tumors above the median hypoxia signature score in the different cancer types.
  • hypoxia signature score above the cut-off (i.e., the median). It is expected that cancer types highly enriched for hypoxia signature scores above the median will have a higher response rate to tivozanib treatment. Prostate adenocarcinoma was the only cancer type where no samples were observed above the cut-off. In this analysis, the cancer type most enriched for hypoxia signature scores above the median is clear cell renal cell carcinoma (kirc) at 94.7% and, therefore, ccRCC is predicted to be responsive to tivozanib treatment. As shown in FIG. 3, for the breast cancer samples, a high hypoxia signature score was also enriched in TNBC samples.
  • Example 7 Predicting Response to Tivozanib in Breast Tumors and Triple-Negative Breast Cancer (TNBC) Subtypes
  • TNBC triple-negative breast cancer
  • the first hypoxia gene signature for testing includes all nine hypoxia genes disclosed herein, i.e., ADM, ANGPT2, CA9, EGLN3, EPAS1, NDRG1, PGF, SLC2A1, and VEGFA.
  • the second hypoxia gene signature for testing includes six of the nine hypoxia genes, i.e., ANGPT2, CA9, EGLN3, NDRG1, SLC2A1, and VEGFA.
  • ROC receiver operating characteristic
  • Responders and “non-responders” to treatment are determined by median PFS.
  • the ROC curve analysis is performed essentially as follows. Any sample with a hypoxia signature score less than threshold is identified as a non-responder. Any sample with a hypoxia signature score greater than or equal to threshold is identified as a responder. For every hypoxia signature score from a tested set of samples, "responders” and “non-responders” (hypothetical calls) are classified using that hypoxia signature score as the threshold. This process enables calculation of TPR (y vector) and FPR (x vector) for each potential threshold, through comparison of hypothetical calls against the actual response data for the data set.
  • a ROC curve is constructed by making a dot plot, using the TPR vector, and FPR vector. If the ROC curve is above diagonal from (0, 0) point, this shows that the hypoxia signature score test result is a better test than random.
  • the optimal operating point that is the point on the ROC curve where the biomarker test has the largest true positive rate while committing the smallest number of false positives, is chosen as the hypoxia signature score threshold.
  • the hypoxia gene signature for predicting response to tivozanib in patients suffering from colorectal cancer includes at least six of the nine genes (e.g., any six-, seven-, eight-, or nine-gene hypoxia gene signature) selected from ADM, CA9, EGLN3, NDRG1, SLC2A1, VEGFA, EPAS1, ANGPT2 and PGF.
  • An optimal cut-off for a hypoxia gene signature predicting response to tivozanib for patients with colorectal cancer may be based on any six-gene, seven-gene, or eight-gene subset thereof by performing the following steps.
  • hypoxia signature score is associated with tivozanib treatment (PFS) (the treatment arm), but is not associated with control treatment (PFS), then the hypoxia gene signature (6-gene or 9-gene) is established as a predictive biomarker for tivozanib in colorectal cancer. An optimal cut-off is then identified for the hypoxia signature score to establish biomarker positive and negative subgroups using a ROC curve as described below.
  • the cut-off is then applied to the biomarker positive and negative subgroups to confirm that the high hypoxia signature score subgroup is associated with response to tivozanib in patients suffering from colorectal cancer.
  • a ROC curve is an exemplary way to determine an optimal cut off for the nine gene hypoxia signature (or any 6-gene, 7-gene or 8-gene subset thereof) to establish tivozanib responder and non-responder subgroups as described above in Example 7.
  • Example 9 Predicting Human Response
  • tumor samples archival FFPE blocks, fresh samples or frozen samples
  • human patients indirectly through a hospital or clinical laboratory
  • Fresh or frozen tumor samples are placed in 10% neutral-buffered formalin for 5-10 hours before being alcohol dehydrated and embedded in paraffin, according to standard histology procedures.
  • RNA is extracted from 10 ⁇ FFPE sections. Paraffin is removed by xylene extraction followed by ethanol washing. RNA is isolated using a commercial RNA preparation kit.
  • RNA is quantitated using a suitable commercial kit, e.g., the RiboGreen ® fluorescence method (Molecular Probes, Eugene, OR). RNA size is analyzed by conventional methods. [0094] Reverse transcription is carried out using the SuperscriptTM First-Strand Synthesis Kit for qRT-PCR (Invitrogen). Total RNA and pooled gene-specific primers are present at 10- 50 ng/ ⁇ and 100 nM (each) respectively.
  • qRT-PCR primers are designed using a suitable commercial software, e.g., Primer Express ® software (Applied Biosystems, Foster City, CA).
  • the oligonucleotide primers are synthesized using a commercial synthesizer instrument and appropriate reagents, as recommended by the instrument manufacturer or vendor. Probes are labeled using a suitable commercial labeling kit.
  • PCR reactions are performed in 384-well plates, using an Applied Biosystems 7900HT instrument according to the manufacturer's instructions. Expression of each gene in the hypoxia signature is measured in duplicate 5 ⁇ reactions, using cDNA synthesized from 1 ng of total RNA per reaction well. Final primer and probe concentrations are 0.9 ⁇ (each primer) and 0.2 ⁇ , respectively. PCR cycling is carried out according to a standard operating procedure. To verify that the qRT-PCR signal is due to RNA rather than contaminating DNA, for each gene tested, a no RT control is run in parallel. The threshold cycle for a given amplification curve during qRT-PCR occurs at the point the fluorescent signal from probe cleavage grows beyond a specified fluorescence threshold setting. Test samples with greater initial template exceed the threshold value at earlier amplification cycles.
  • the hypoxia signature score for each tumor sample is calculated from the gene expression levels, according to the algorithm set forth above.
  • the actual response data associated with the tumor samples tested are obtained from the hospital or clinical laboratory supplying the tumor samples.
  • Clinical response is typically is defined in terms of tumor shrinkage, e.g., 30% shrinkage, as determined by suitable imaging technique, e.g., CT scan.
  • human clinical response is defined in terms of time, e.g., progression free survival time.
  • the optimal threshold hypoxia signature score for the given tumor type is calculated, as described above. Subsequently, this optimal threshold hypoxia signature score is used to predict whether newly -tested human tumors of the same tumor type will be responsive or non- responsive to treatment with tivozanib.

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Abstract

L'invention concerne un procédé diagnostique permettant de prévoir quantitativement si une tumeur humaine va répondre ou non à un traitement au tivozanib. Le test repose sur des mesures des niveaux d'expression d'au moins six gènes dans une signature d'hypoxie à neuf gènes.
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WO2016115149A1 (fr) * 2015-01-12 2016-07-21 Aveo Pharmaceuticals, Inc. Neuropiline-1 utilisée en tant que biomarqueur sérique
WO2016164593A1 (fr) * 2015-04-07 2016-10-13 President And Fellows Of Harvard College Compositions et méthodes de modulation de l'hydroxylation d'acc2 par phd3
CN105200132A (zh) * 2015-09-23 2015-12-30 中国人民解放军第二军医大学 裸鼹鼠vegfa基因特异性检测引物及检测试剂盒
CN111630183A (zh) * 2017-09-05 2020-09-04 新加坡科技研究局 透明细胞肾细胞癌生物标志物
EP3679161A4 (fr) * 2017-09-05 2021-06-02 Agency for Science, Technology and Research Biomarqueurs du carcinome à cellules rénales à cellules claires
CN113684261A (zh) * 2021-09-02 2021-11-23 济南艾迪康医学检验中心有限公司 利用荧光定量pcr检测znf384基因重排的引物和探针及试剂盒
CN113684261B (zh) * 2021-09-02 2024-04-30 济南艾迪康医学检验中心有限公司 利用荧光定量pcr检测znf384基因重排的引物和探针及试剂盒

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