WO2013120092A1 - Methods for predicting response to cancer therapy - Google Patents

Methods for predicting response to cancer therapy Download PDF

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Publication number
WO2013120092A1
WO2013120092A1 PCT/US2013/025614 US2013025614W WO2013120092A1 WO 2013120092 A1 WO2013120092 A1 WO 2013120092A1 US 2013025614 W US2013025614 W US 2013025614W WO 2013120092 A1 WO2013120092 A1 WO 2013120092A1
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cancer
expression
protein
bcg
melanoma
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PCT/US2013/025614
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French (fr)
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Delphine J. LEE
Seema PLAISIER
Myung-shin SIM
Don MORTON
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John Wayne Cancer Institute
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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B25/00—ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
    • G16B25/10—Gene or protein expression profiling; Expression-ratio estimation or normalisation
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
    • A61K35/00—Medicinal preparations containing materials or reaction products thereof with undetermined constitution
    • A61K35/66—Microorganisms or materials therefrom
    • A61K35/74—Bacteria
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61P—SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
    • A61P35/00—Antineoplastic agents
    • 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
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
    • G01N33/5008—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics
    • G01N33/5011—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics for testing antineoplastic activity
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
    • G01N33/5008—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics
    • G01N33/5044—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics involving specific cell types
    • G01N33/5047—Cells of the immune system
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
    • A61K39/00—Medicinal preparations containing antigens or antibodies
    • A61K2039/555—Medicinal preparations containing antigens or antibodies characterised by a specific combination antigen/adjuvant
    • A61K2039/55588—Adjuvants of undefined constitution
    • A61K2039/55594—Adjuvants of undefined constitution from bacteria
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
    • A61K39/00—Medicinal preparations containing antigens or antibodies
    • A61K2039/58—Medicinal preparations containing antigens or antibodies raising an immune response against a target which is not the antigen used for immunisation
    • A61K2039/585—Medicinal preparations containing antigens or antibodies raising an immune response against a target which is not the antigen used for immunisation wherein the target is 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
    • C12Q2600/112—Disease subtyping, staging or classification
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/52—Predicting or monitoring the response to treatment, e.g. for selection of therapy based on assay results in personalised medicine; Prognosis
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B25/00—ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B40/00—ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding

Definitions

  • the present invention relates generally to the fields of molecular biology and medicine. More particularly, it concerns methods for predicting response outcomes to cancer therapies.
  • Cutaneous melanoma is the most rapidly increasing neoplasm in the world today, increasing at a rate of 4%-5% a year in most countries.
  • the explanation for this rapidly rising incidence is not known, but may be related to the loss of the ozone layer from the earth which allows more ultraviolet light to reach the earth and cause skin cancer.
  • melanoma Located on the skin where it can be earlier observed and treated, melanoma would be expected to be a cancer with a favorable prognosis. But in fact, melanoma is the most malignant and aggressive human neoplasm; a primary melanoma as small as 5.0 mm in thickness will kill 50% of the patients within 5 years, whereas comparably sized breast, colon or other solid cancers would kill none. In fact, even thin melanomas measuring 1.0-1.5 mm in thickness have a 20% rate of metastasis to the regional lymph nodes (AJCC - Stage III).
  • metastases in regional lymph nodes spread to distant sites (AJCC Stage IV) and result in death of about 35%-65% of patients with nodal metastases within 5 years depending upon the size and number of involved lymph nodes.
  • Those patients who have metastases to a distant organ site and are treated with current systemic therapies survive a median of only 10- 12 months and less than 5% survive five years or more.
  • these patients have a small number of metastases that are surgically resected, then their five year survival potential may increase to 35%-40%.
  • Other than surgery there are few effective therapies for melanoma are few effective therapies for melanoma.
  • Those therapies that are used as an adjuvant following surgery to treat potential micrometastases of melanoma that remain after surgery are very toxic: such examples include high-dose interferon or IL-2, and more recently the biological Yervoy (ipilimumab) which is an anti CTLA-4 antibody recently approved by the FDA for Stage III and IV melanoma. All of these treatments are expensive; for example, Yervoy costs $ 120,000 for a 4-course treatment. Other than cost, the toxic side effects associated with these adjuvant treatments include hepatitis, ulcerative colitis, thyroiditis and psychological changes such as depression, and some treatment related deaths. Thus, if it could be predicted the whether 35-65% of Stage III patients would be long-term vs.
  • assays are provided that may be used to differentiate between subjects with melanoma who will remain free of disease for about 5-10 years and subjects with melanoma that will recur early within the first 2-3 years, e.g., with greater than about 99% accuracy.
  • Methods are provided in various aspects for predicting prognosis or response to therapy with Bacillus Calmette-Guerin (BCG) for subjects with a cancer, such as, e.g., melanoma, breast cancer, colon cancer, lung cancer, bowel cancer, pancreatic cancer, renal cancer, or other solid cancerous tumor.
  • BCG Bacillus Calmette-Guerin
  • An aspect of the present invention relates to an in vitro method for providing a prognosis or prediction of response to a treatment with Bacillus Calmette-Guerin (BCG) in a subject with a cancer, said method comprising: a) culturing in vitro a first and second biological sample from the patient comprising cells in the presence and absence of Bacillus Calmette-Guerin, respectively, for a sufficient time and under conditions to permit gene expression by the cells; b) assessing the expression of one, two, three, four, five or all biomarkers selected from the group of biomarkers consisting of 240534_at, LOC283038, AGR2, RRP7A, LI C00472, and RR 3P2 in the first and second cultured biological sample; and c) providing a prognosis or prediction for the subject based on the expression information, such that an increase in expression of LINC00472, RR 3P2, or 240534_at in the first biological sample as compared to the second biological sample indicates a poor survival
  • the first and second biological samples should contain cells of the same tissue type; for example, the first and second biological samples may be blood samples and may contain peripheral blood mononuclear cells.
  • the prognosis or prediction further comprises evaluating the presence or absence of ulceration of the cancer (e.g., an original or primary cancer) in the subject, wherein ulceration indicates a poor survival, a high risk of recurrence, or a poor response to said treatment with Bacillus Calmette-Guerin.
  • the sample may comprise a blood sample.
  • the sample may comprise peripheral blood mononuclear cells. Said contacting or culturing may occur in vitro.
  • Said contacting or culturing may comprise culturing peripheral blood mononuclear cells from the sample with BCG for from about 3 to about 9 hours, about 6 hours, at least 6 hours, at least 12 hours, or at least 24 hours.
  • Bacillus Calmette-Guerin may be administered to the subject.
  • Said contacting or culturing may occur in vivo.
  • the cancer may be a melanoma, breast cancer, colon cancer, lung cancer, bowel cancer, pancreatic cancer, or renal cancer.
  • the melanoma may be a stage II, stage III, or stage IV melanoma.
  • Said obtaining expression information may comprise obtaining or receiving said sample.
  • the sample may be paraffin- embedded and/or frozen.
  • said obtaining expression information comprises measuring expression of said one or more biomarkers.
  • said obtaining expression information may comprise RNA quantification, e.g., cDNA microarray, quantitative RT-PCR, in situ hybridization, Northern blotting or nuclease protection.
  • Said obtaining expression information may comprise protein quantification, e.g., protein quantification comprises immunohistochemistry, an ELISA, a radioimmunoassay (RIA), an immunoradiometric assay, a fluoroimmunoassay, a chemiluminescent assay, a bioluminescent assay, a gel electrophoresis, or a Western blot analysis.
  • Providing the prognosis or prediction may comprise generating a classifier based on the expression, wherein the classifier is defined as a weighted sum of expression levels of the biomarkers.
  • Providing the prognosis or prediction may comprise generating a weighted gene voting score.
  • the classifier is generated on a computer.
  • the classifier may be generated by a computer readable medium comprising machine executable instructions suitable for generating a classifier.
  • Providing the prognosis or prediction may comprise classifying a group of subjects based on the classifier associated with individual subjects in the group with a reference value.
  • the method may further comprise reporting said prognosis or prediction.
  • the method may further comprise prescribing or administering an adjuvant therapy to said subject based on said prediction.
  • a BCG therapy is prescribed or administered to the subject based on said prediction. In other embodiments, a BCG therapy is not prescribed or administered to the subject based on said prediction.
  • the cancer may be a stage II cancer or a stage III cancer, or a stage IV cancer. In some embodiments, the cancer is not a stage IV cancer.
  • Another aspect of the present invention relates to a composition comprising Bacillus
  • Calmette-Guerin for use in treating cancer in a patient from whom a biological sample comprising cells has been tested by culturing in the presence of BCG and determined to exhibit an increase in expression of AGR2, LOC283038, or RRP7A as compared to such a sample that was not cultured in the presence of BCG.
  • the cancer may be a melanoma.
  • Yet another aspect of the present invention relates to a method of treating a patient having a cancer, comprising selecting an individual whose peripheral blood mononuclear cells express an increased level of one, two, or all of AGR2, LOC283038, or RRP7A, relative to a reference expression level, as a result of culturing said cells with Bacillus Calmette- Guerin (BCG); and administering a BCG therapy to the subject.
  • Said selecting may comprise measuring expression of said at least one of AGR2, LOC283038, or RRP7A in said peripheral blood mononuclear cells in vitro.
  • the cancer may be a melanoma.
  • Some aspects of the present invention relate to a method for providing a prognosis or prediction of response to a treatment with Bacillus Calmette-Guerin (BCG) in a subject with a cancer, said method comprising: obtaining expression information of biomarkers in a biological sample of a subject by testing said sample; wherein the biological sample is contacted or cultured with Bacillus Calmette-Guerin prior to said testing; and wherein the biomarkers either: (a) comprise at least ten genes from the group consisting of Tables 2-4, or (b) comprise 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more of: 1555845_at, 1560271_at, 1562673_at, 216771_at, 224105_x_at, 236502_at, 240534_at, 244055_at, AGR2, ATG5, C18orf25, C22orf39, CIRBP-AS1, CYP4B 1, EPHA1, HNRNPD, LARS2, LI C00472, LOC10050
  • altered expression of one or more genes selected from the group consisting of the genes listed in Tables 2-4 having a positive FC(SS/LS)-value indicates a poor survival, a high risk of recurrence, or a poor response to said treatment with Bacillus Calmette-Guerin
  • altered expression of one or more genes selected from the group consisting of Tables 2-4 having a negative FC(SS/LS)- value indicates a favorable survival, a low risk of recurrence, or a favorable response to said treatment with Bacillus Calmette-Guerin.
  • Another aspect of the present invention relates to an array comprising a plurality of antigen-binding fragments that bind to expression products of biomarkers or a plurality of primers or probes that bind to transcripts of the biomarkers to assess expression levels, the biomarkers comprising either (a) 1, 2, 3, 4, 5 or all of AGR2, LOC283038, RRP7A, LI C00472, RR 3P2, and 240534_at, (b) 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more of: 1555845_at, 156027 l_at, 1562673_at, 216771_at, 224105_x_at, 236502_at, 240534_at, 244055_at, AGR2, ATG5, C18orf25, C22orf39, CIRBP-AS1, CYP4B1, EPHA1, HNRNPD, LARS2, LI C00472, LOC100509474 /// ZNF518A, LOC283038, MASP 1, METAP
  • kits comprising a plurality of antigen-binding fragments that bind to expression products of biomarkers or a plurality of primers or probes that bind to transcripts of the biomarkers to assess expression levels, the biomarkers comprising either (a) 1, 2, 3, 4, 5 or all of AGR2, LOC283038, RRP7A, LTNC00472, RRN3P2, and 240534_at, (b) 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more of: 1555845_at, 156027 l_at, 1562673_at, 216771_at, 224105_x_at, 236502_at, 240534_at, 244055_at, AGR2, ATG5, C18orf25, C22orf39, CIRBP-AS1, CYP4B1, EPHA1, HNRNPD, LARS2, LI C00472, LOC100509474 /// ZNF518A, LOC283038, MASP 1,
  • a biological sample comprising PBMC may be cultured in a media for a period of time of at least about 3, 4, 5, 6, 7, 8, 9, 10, 1 1, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24 or more hours prior to measuring the gene expression of the PBMC.
  • the PBMC may be cultured in the presence or absence of BCG.
  • expression of one or more of the genes listed in Tables 1-4, Tables 2-4, or 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more of: 1555845_at, 1560271_at, 1562673_at, 216771_at, 224105_x_at, 236502_at, 240534_at, 244055_at, AGR2, ATG5, C18orf25, C22orf39, CIRBP-AS1, CYP4B 1, EPHA1, HNRNPD, LARS2, LINC00472, LOC100509474 /// ZNF518A, LOC283038, MASP 1, METAP1, MTF2, OCLN, PDLIM7, PWWP2B, RRN3P2, RRP7A, SMC1A, SRGAP1, TSC22D1, UBXN8, WDR25, and/or WDR87, may be measured in PBMC from a subject after culture of the PBMC in a media that does not contain BCG and
  • PBMC expression may be evaluated as described herein, and it is anticipated that prediction of a good prognosis or poor prognosis response to BCG in cancer will correlate with increased or decreased protection, respectively, against tuberculosis or other bacteria after vaccination with BCG.
  • assays are provided for utilizing peripheral blood mononuclear cells (PBMC) from a melanoma patient (e.g., a Stage III melanoma patient) which upon culture with BCG will induce gene expression profiles.
  • PBMC peripheral blood mononuclear cells
  • RNA from PBMC exposed to or cultured in the presence of BCG may be detected, measured, or analyzed, e.g., via microarray analysis, RT-PCT, etc.
  • the expression profiles may be used to indentify an immune phenotype that can lead to prolonged survival in the melanoma or other cancer patients.
  • methods and assays disclosed herein may be used to identify genes and/or pathways that can modulate host defense against melanoma. These approaches may be used to target specific immunotherapies that enhance the activity of these naturally occurring anti-tumor immune responses.
  • the tissue sample may be collected from a subject with a cancer and, optionally, stored or shipped prior to testing.
  • the collection may comprise surgical resection.
  • the sample of tissue may be stored in RNALaterTM or flash frozen, such that RNA may be isolated at a later date.
  • RNA may be isolated from the tissue and used to generate labeled probes for a nucleic acid microarray analysis.
  • the RNA may also be used as a template for qRT-PCR in which the expression of a plurality of biomarkers is analyzed.
  • the expression data generated may be used to derive a score which may predict an individual's response to BCG immune stimulation or predict an individual's survival from cancer, e.g., using the- Rank Hypergeometric Overlap (RRHO) analysis method of Plaisier et al. (2010), or to obtain a sum based on each corresponding biomarker gene expression by weighted gene voting (Golub et al., 1999).
  • the score may be used to predict whether the subject will be a short- term or a long-term cancer survivor.
  • Biomarker genes that may be used in cancer prognosis or score generation may be one or more selected from (a) 1, 2, 3, 4, 5, or all of 240534_at, LOC283038, AGR2, RRP7A, LINC00472, or RRN3P2; (b) 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more of : 1555845_at, 1560271_at, 1562673_at, 216771_at, 224105_x_at, 236502_at, 240534_at, 244055_at, AGR2, ATG5, C18orf25, C22orf39, CIRBP-AS1, CYP4B1, EPHA1, HNRNPD, LARS2, LINC00472, LOC100509474 /// ZNF518A, LOC283038, MASP 1, METAP 1, MTF2, OCLN, PDLIM7, PWWP2B, RRN3P2, RRP7A, SMC1A, SRGAP1, TSC22
  • At least 10, 20, 30, 40, 50, 60, 70, 80, 90, 100 of more of the genes listed in Tables 2-4 may be detected or measured, e.g., to predict a response to a treatment with Bacillus Calmette-Guerin (BCG) in a subject.
  • BCG Bacillus Calmette-Guerin
  • biomarkers or genes may be measured by a variety of techniques that are well known in the art. Quantifying the levels of the messenger RNA (mRNA) of a biomarker may be used to measure the expression of the biomarker. Alternatively, quantifying the levels of the protein product of a biomarker may be used to measure the expression of the biomarker. Additional information regarding the methods discussed below may be found in Ausubel et al. (2003) or Sambrook et al. (1989). One skilled in the art will know which parameters may be manipulated to optimize detection of the mRNA or protein of interest.
  • mRNA messenger RNA
  • a nucleic acid microarray may be used to quantify the differential expression of a plurality of biomarkers.
  • Microarray analysis may be performed using commercially available equipment, following manufacturer's protocols, such as by using the Affymetrix GeneChip® technology (Santa Clara, CA) or the Microarray System from Incyte (Fremont, CA).
  • single-stranded nucleic acids e.g., cDNAs or oligonucleotides
  • the arrayed sequences are then hybridized with specific nucleic acid probes from the cells of interest.
  • Fluorescently labeled cDNA probes may be generated through incorporation of fluorescently labeled deoxynucleotides by reverse transcription of RNA extracted from the cells of interest.
  • the RNA may be amplified by in vitro transcription and labeled with a marker, such as biotin.
  • the labeled probes are then hybridized to the immobilized nucleic acids on the microchip under highly stringent conditions. After stringent washing to remove the non-specifically bound probes, the chip is scanned by confocal laser microscopy or by another detection method, such as a CCD camera.
  • the raw fluorescence intensity data in the hybridization files are generally preprocessed with the robust multichip average (RMA) algorithm to generate expression values.
  • RMA robust multichip average
  • Quantitative real-time PCR may also be used to measure the differential expression of a plurality of biomarkers.
  • the RNA template is generally reverse transcribed into cDNA, which is then amplified via a PCR reaction.
  • the amount of PCR product is followed cycle-by-cycle in real time, which allows for determination of the initial concentrations of mRNA.
  • the reaction may be performed in the presence of a fluorescent dye, such as SYBR Green, which binds to double- stranded DNA.
  • the reaction may also be performed with a fluorescent reporter probe that is specific for the DNA being amplified.
  • a non-limiting example of a fluorescent reporter probe is a TaqMan® probe (Applied Biosystems, Foster City, CA).
  • the fluorescent reporter probe fluoresces when the quencher is removed during the PCR extension cycle.
  • Multiplex qRT-PCR may be performed by using multiple gene-specific reporter probes, each of which contains a different fluorophore. Fluorescence values are recorded during each cycle and represent the amount of product amplified to that point in the amplification reaction. To minimize errors and reduce any sample-to-sample variation, qRT-PCR may be performed using a reference standard. The ideal reference standard is expressed at a constant level among different tissues, and is unaffected by the experimental treatment.
  • Suitable reference standards include, but are not limited to, mRNAs for the housekeeping genes glyceraldehyde-3-phosphate-dehydrogenase (GAPDH) and ⁇ -actin.
  • GPDH glyceraldehyde-3-phosphate-dehydrogenase
  • ⁇ -actin glyceraldehyde-3-phosphate-dehydrogenase
  • the level of mRNA in the original sample or the fold change in expression of each biomarker may be determined using calculations well known in the art.
  • Immunohistochemical staining may also be used to measure the differential expression of a plurality of biomarkers.
  • This method enables the localization of a protein in the cells of a tissue section by interaction of the protein with a specific antibody.
  • the tissue may be fixed in formaldehyde or another suitable fixative, embedded in wax or plastic, and cut into thin sections (from about 0.1 mm to several mm thick) using a microtome.
  • the tissue may be frozen and cut into thin sections using a cryostat.
  • the sections of tissue may be arrayed onto and affixed to a solid surface (i.e., a tissue microarray).
  • the sections of tissue are incubated with a primary antibody against the antigen of interest, followed by washes to remove the unbound antibodies.
  • the primary antibody may be coupled to a detection system, or the primary antibody may be detected with a secondary antibody that is coupled to a detection system.
  • the detection system may be a fluorophore or it may be an enzyme, such as horseradish peroxidase or alkaline phosphatase, which can convert a substrate into a colorimetric, fluorescent, or chemiluminescent product.
  • the stained tissue sections are generally scanned under a microscope. Because a sample of tissue from a subject with cancer may be heterogeneous, i.e., some cells may be normal and other cells may be cancerous, the percentage of positively stained cells in the tissue may be determined. This measurement, along with a quantification of the intensity of staining, may be used to generate an expression value for the biomarker.
  • An enzyme-linked immunosorbent assay may be used to measure the differential expression of a plurality of biomarkers.
  • an ELISA assay There are many variations of an ELISA assay. All are based on the immobilization of an antigen or antibody on a solid surface, generally a microtiter plate.
  • the original ELISA method comprises preparing a sample containing the biomarker proteins of interest, coating the wells of a microtiter plate with the sample, incubating each well with a primary antibody that recognizes a specific antigen, washing away the unbound antibody, and then detecting the antibody-antigen complexes.
  • the antibody-antibody complexes may be detected directly.
  • the primary antibodies are conjugated to a detection system, such as an enzyme that produces a detectable product.
  • the antibody-antibody complexes may be detected indirectly.
  • the primary antibody is detected by a secondary antibody that is conjugated to a detection system, as described above.
  • the microtiter plate is then scanned and the raw intensity data may be converted into expression values using means known in the art.
  • An antibody microarray may also be used to measure the differential expression of a plurality of biomarkers.
  • a plurality of antibodies is arrayed and covalently attached to the surface of the microarray or biochip.
  • a protein extract containing the biomarker proteins of interest is generally labeled with a fluorescent dye.
  • the labeled biomarker proteins are incubated with the antibody microarray. After washes to remove the unbound proteins, the microarray is scanned.
  • the raw fluorescent intensity data may be converted into expression values using means known in the art.
  • Luminex multiplexing microspheres may also be used to measure the differential expression of a plurality of biomarkers.
  • These microscopic polystyrene beads are internally color-coded with fluorescent dyes, such that each bead has a unique spectral signature (of which there are up to 100). Beads with the same signature are tagged with a specific oligonucleotide or specific antibody that will bind the target of interest (i.e., biomarker mRNA or protein, respectively).
  • the target is also tagged with a fluorescent reporter.
  • there are two sources of color one from the bead and the other from the reporter molecule on the target.
  • the beads are then incubated with the sample containing the targets, of which up to 100 may be detected in one well.
  • the small size/surface area of the beads and the three dimensional exposure of the beads to the targets allows for nearly solution-phase kinetics during the binding reaction.
  • the captured targets are detected by high-tech fluidics based upon flow cytometry in which lasers excite the internal dyes that identify each bead and also any reporter dye captured during the assay.
  • the data from the acquisition files may be converted into expression values using means known in the art.
  • In situ hybridization may also be used to measure the differential expression of a plurality of biomarkers.
  • This method permits the localization of mRNAs of interest in the cells of a tissue section.
  • the tissue may be frozen, or fixed and embedded, and then cut into thin sections, which are arrayed and affixed on a solid surface.
  • the tissue sections are incubated with a labeled antisense probe that will hybridize with an mRNA of interest.
  • the hybridization and washing steps are generally performed under highly stringent conditions.
  • the probe may be labeled with a fluorophore or a small tag (such as biotin or digoxigenin) that may be detected by another protein or antibody, such that the labeled hybrid may be detected and visualized under a microscope.
  • each antisense probe may be detected simultaneously, provided each antisense probe has a distinguishable label.
  • the hybridized tissue array is generally scanned under a microscope. Because a sample of tissue from a subject with cancer may be heterogeneous, i.e., some cells may be normal and other cells may be cancerous, the percentage of positively stained cells in the tissue may be determined. This measurement, along with a quantification of the intensity of staining, may be used to generate an expression value for each biomarker. The number of biomarkers whose expression is measured in a sample of cells from a subject with cancer may vary.
  • the risk score is based upon the differential expression of the biomarkers, a higher degree of accuracy should be attained when the expression of more biomarkers is measured; however, a large number of biomarkers in the gene signature would hamper the clinical usefulness.
  • the differential expression of a selected number of biomarkers may be measured.
  • obtaining a biological sample or “obtaining a blood sample” refer to receiving a biological or blood sample, e.g., either directly or indirectly.
  • the biological sample such as a blood sample or a sample containing peripheral blood mononuclear cells (PBMC)
  • PBMC peripheral blood mononuclear cells
  • the biological sample may be drawn or taken by a third party and then transferred, e.g., to a separate entity or location for analysis.
  • the sample may be obtained and tested in the same location using a point-of care test.
  • said obtaining refers to receiving the sample, e.g., from the patient, from a laboratory, from a doctor's office, from the mail, courier, or post office, etc.
  • the method may further comprise reporting the determination to the subject, a health care payer, an attending clinician, a pharmacist, a pharmacy benefits manager, or any person that the determination may be of interest.
  • Patient response can be assessed using any endpoint indicating a benefit to the patient, including, without limitation, (1) inhibition, to some extent, of disease progression, including slowing down and complete arrest; (2) reduction in the number of disease episodes and/or symptoms; (3) reduction in lesional size; (4) inhibition (i.e., reduction, slowing down or complete stopping) of disease cell infiltration into adjacent peripheral organs and/or tissues; (5) inhibition (i.e., reduction, slowing down or complete stopping) of disease spread; (6) relief, to some extent, of one or more symptoms associated with the disorder; (7) increase in the length of disease-free presentation following treatment; and/or (8) decreased mortality at a given point of time following treatment.
  • cancer prognosis refers to a prediction of how a patient will progress, and whether there is a chance of recovery.
  • Cancer prognosis generally refers to a forecast or prediction of the probable course or outcome of the cancer.
  • cancer prognosis includes the forecast or prediction of any one or more of the following: duration of survival of a patient susceptible to or diagnosed with a cancer, duration of recurrence-free survival, duration of progression-free survival of a patient susceptible to or diagnosed with a cancer, response rate in a group of patients susceptible to or diagnosed with a cancer, duration of response in a patient or a group of patients susceptible to or diagnosed with a cancer, and/or likelihood of metastasis in a patient susceptible to or diagnosed with a cancer.
  • Prognosis also includes prediction of favorable responses to cancer treatments, such as a conventional cancer therapy.
  • subject or “patient” is meant any single subject for which therapy is desired, including humans, cattle, dogs, guinea pigs, rabbits, chickens, and so on. Also intended to be included as a subject are any subjects involved in clinical research trials not showing any clinical sign of disease, or subjects involved in epidemiological studies, or subjects used as controls.
  • “increased expression” refers to an elevated or increased level of expression in a cancer sample relative to a suitable control (e.g., a non-cancerous tissue or cell sample, a reference standard), wherein the elevation or increase in the level of gene expression is statistically significant (p ⁇ 0.05). Whether an increase in the expression of a gene in a cancer sample relative to a control is statistically significant can be determined using an appropriate t-test (e.g., one-sample t-test, two-sample t-test, Welch's t-test) or other statistical test known to those of skill in the art.
  • Genes that are overexpressed in a cancer can be, for example, genes that are known, or have been previously determined, to be overexpressed in a cancer.
  • decreased expression refers to a reduced or decreased level of expression in a cancer sample relative to a suitable control (e.g., a non-cancerous tissue or cell sample, a reference standard), wherein the reduction or decrease in the level of gene expression is statistically significant (p ⁇ 0.05).
  • the reduced or decreased level of gene expression can be a complete absence of gene expression, or an expression level of zero.
  • Whether a decrease in the expression of a gene in a cancer sample relative to a control is statistically significant can be determined using an appropriate t-test (e.g., one-sample t-test, two-sample t-test, Welch's t-test) or other statistical test known to those of skill in the art.
  • Genes that are underexpressed in a cancer can be, for example, genes that are known, or have been previously determined, to be underexpressed in a cancer.
  • the marker level may be compared to the level of the marker from a control, wherein the control may comprise one or more tumor samples (e.g., colon cancer samples) taken from one or more patients determined as having a good prognosis ("good prognosis” control) or a poor prognosis (“poor prognosis” control), or both.
  • the control may comprise data obtained at the same time (e.g., in the same hybridization experiment) as the patient's individual data, or may be a stored value or set of values, e.g., stored on a computer, or on computer-readable media. If the latter is used, new patient data for the selected marker(s), obtained from initial or follow-up samples, can be compared to the stored data for the same marker(s) without the need for additional control experiments.
  • a good or bad prognosis may, for example, be assessed in terms of patient survival, likelihood of disease recurrence or disease metastasis (patient survival, disease recurrence and metastasis may for example be assessed in relation to a defined timepoint, e.g., at a given number of years after cancer surgery (e.g., surgery to remove one or more tumors) or after initial diagnosis.
  • a good or bad prognosis may be assessed in terms of overall survival or disease free survival.
  • “good prognosis” may refer to the likelihood that a patient afflicted with cancer will remain disease free (e.g., cancer free) or survive despite the presence of the cancer.
  • “Poor prognosis” may be used to mean the likelihood of a relapse or recurrence of the underlying cancer or tumor, metastasis, or death. Cancer patients classified as having a “good prognosis” may remain free of the underlying cancer or tumor or survive despite the presence of cancer or tumor. For example, cancerous cells and/or tumors from a cancer may continue to exist in a patient with a good prognosis, but the patient's immune system may slow or prevent the progression or growth of the cancer, thus allowing the patient to continue to survive.
  • the time frame for assessing prognosis and outcome is, for example, less than one year, one, two, three, four, five, six, seven, eight, nine, ten, fifteen, twenty, or more years.
  • the relevant time for assessing prognosis or disease-free survival time may begin at the time of the surgical removal of the tumor or suppression, mitigation, or inhibition of tumor growth.
  • a "good prognosis” refers to the likelihood that a cancer patient will survive for a period of at least five, such as for a period of at least ten years.
  • a "poor prognosis” refers to the likelihood that a cancer patient, such as a melanoma patient, will experience disease relapse, tumor recurrence, metastasis, or death within less than ten years, such as less than five years or less than 1.5 years.
  • Time frames for assessing prognosis and outcome provided herein are illustrative and are not intended to be limiting.
  • the term "high risk” means the patient is expected to have a distant relapse in a shorter period less than a predetermined value (for example, from a control), for example in less than 5 years, preferably in less than 3 years or less than 1.5 years.
  • low risk means the patient is expected to have a distant relapse in a longer period greater than a predetermined value, for example, after 5 years, preferably in more than ten years.
  • Time frames for assessing risks provided herein are illustrative and are not intended to be limiting.
  • antigen binding fragment herein is used in the broadest sense and specifically covers intact monoclonal antibodies, polyclonal antibodies, multispecific antibodies (e.g., bispecific antibodies) formed from at least two intact antibodies, and antibody fragments.
  • primer as used herein, is meant to encompass any nucleic acid that is capable of priming the synthesis of a nascent nucleic acid in a template-dependent process. Primers may be oligonucleotides from ten to twenty and/or thirty base pairs in length, but longer sequences can be employed. Primers may be provided in double-stranded and/or single-stranded form, although the single-stranded form is preferred. Embodiments discussed in the context of methods and/or compositions of the invention may be employed with respect to any other method or composition described herein. Thus, an embodiment pertaining to one method or composition may be applied to other methods and compositions of the invention as well.
  • encode or "encoding” with reference to a nucleic acid are used to make the invention readily understandable by the skilled artisan; however, these terms may be used interchangeably with “comprise” or “comprising,” respectively.
  • FIG. 1 Survival curve of patients studied. Eleven melanoma patients (matched by age, sex and tumor burden), six of whom survived less than 1.5 years (short term survivors- SS) and five of whom survived greater than ten years (long term survivors-LS) after BCG immunostimulation.
  • FIG. 2 Sum of votes from high weighted genes (weights > 1.1) from samples treated as labeled in the charts.
  • FIG. 3 RRHO Map. Rank pairs were used to find optimal overlapping gene sets.
  • FIGS. 4A-D Pathways analysis of overlapping T-lep/ LS and L-lep/SS genes (FIG. 4A and FIG. 4B).
  • LS melanoma and T-lep patients might be particularly relevant to improved host immunity
  • the inventors studied the 2003 genes identified by RRHO (in FIG. 3) which showed significant overlap in T-lep vs. L-lep and LS vs SS using knowledge-guided bioinformatic analysis, incorporating data on likely biologic functions, including gene ontology information and regulatory data (Ingenuity ® Systems, www.ingenuity.com). Shown are the top five functional groups and canonical pathways found.
  • IPA was used to study the 960 genes identified by RRHO which showed significant overlap in L-lep vs. T-lep and SS vs LS (FIG. 4C and FIG. 4D). Shown are the top five functional groups and canonical pathways found.
  • FIGS. 5A-C Sum of votes from all probesets with weight > 1.1 (FIG. 5 A), top 50 probesets (FIG. 5B) and top 100 (FIG. 5C) weighted probesets from PBMCs treated with media for six hours.
  • FIGS. 6A-C Sum of votes from all probesets with weight > 1.1 (FIG. 6A), top 50 probesets (FIG. 6B) and top 100 (FIG. 6C) weighted probesets from PBMCs treated with BCG for six hours.
  • FIGS. 7A-C Sum of votes from all probesets with weight > 1.1 (FIG. 7A), top 50 probesets (FIG. 7B) and top 100 (FIG. 7C) weighted probesets from PBMCs treated with media for 24 hours.
  • FIGS. 8A-C Sum of votes from all probesets with weight > 1.1 (FIG. 8A), top 50 probesets (FIG. 8B) and top 100 (FIG. 8C) weighted probesets from PBMCs treated with BCG for 24 hours.
  • FIG. 9 Spectrum of melanoma patients tested is shown.
  • FIG. 10 An example of a method of experiments is shown.
  • BCG Bacillus Calmette-Guerin
  • the inventors investigated peripheral blood responses of melanoma patients prior to BCG administration in known "short-term survivors” (SS) versus “long-term survivors” (LS) to gain insight into BCG-induced immune pathways that may be important for melanoma survival.
  • SS short-term survivors
  • LS long-term survivors
  • methods for providing a prognosis or prediction of response to a treatment with Bacillus Calmette-Guerin (BCG) in a subject with a cancer, said method comprising: a) obtaining expression information of one or more biomarkers in a biological sample from the subject by testing said sample; wherein the biological sample is contacted or cultured with Bacillus Calmette-Guerin in vitro prior to said testing; and wherein said biomarkers comprise 1, 2, 3, 4, 5, or all of 240534_at, LOC283038, AGR2, RRP7A, LI C00472, and/or RR 3P2; and b) providing a prognosis or prediction for the subject based on the expression information, wherein, as compared with a reference expression level, an increase in expression of LINC00472, RRN3P2, or 240534_at indicates a poor survival, a high risk of recurrence, or a poor response to said treatment with Bacillus Calmette-Guerin, and an increase
  • PBMCs peripheral blood mononuclear cells
  • probesets with high signal-to-noise ratios with weights above 1.1 (lists of probesets used are in Tables 1-4). Expression data, p values, and fold changes of LS vs SS were obtained. The top 50 and top 100 genes were identified from each media condition by examining the weight values.
  • Methods of the present invention may be used, in some embodiments, to identify patients who may benefit more from in vivo BCG immunostimulation for melanoma by in vitro testing prior to therapy.
  • a short probe list with only the highest weight/signal to noise ratio (SNR) genes can be used to attain high prediction accuracy in the 6 hr Med group (top 50 or top 100).
  • SNR weight/signal to noise ratio
  • Each melanoma outcome classifier may be tested using a replicate patient data set.
  • a 6 hr BCG classifier may be used to predict the samples in a second independent patient set.
  • the 24 hr BCG classifier may be used to predict the samples in a second independent patient set.
  • a combination of probes from each in vitro treatment and time point may also be used in predicting cancer prognosis or response to BGC treatment.
  • Biomarker genes that may be used in cancer prognosis or risk score generation may be: (a) 1, 2, 3, 4, 5, or all of 240534_at, LOC283038, AGR2, RRP7A, LTNC00472, or RRN3P2; (b) 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more of : 1555845_at, 1560271_at, 1562673_at, 216771_at, 224105_x_at, 236502_at, 240534_at, 244055_at, AGR2, ATG5, C18orf25, C22orf39, CIRBP-AS1, CYP4B 1, EPHA1, HNRNPD, LARS2, LTNC00472, LOC100509474 /// ZNF518A, LOC283038, MASP1, METAP 1, MTF2, OCLN, PDLIM7, PWWP2B, RRN3P2, RRP7A, SMC1A, SRGAP1, TSC22D1,
  • probe set refers to the Affymetrix probe set identification number, des is the description of the gene represented by the probeset, symbol is the gene symbol, entrez is the ID for the NCBI entrez search site, FC refers to the signed fold change of expression in short term survivors vs. long term survivors in which a positive number refers to the fold change higher in the short-term survivors and a negative number refers to the fold change higher in the long-term survivors, t-test pvalue calculates the student's t-test p value for the expression values of the two groups comprised of six short-term survivors vs. five long-term survivors, weight refers to the calculated value described in example 1 used to identify the probesets used to classify the individual subjects.
  • breakpoint family F16///NBPF24/ 40670///
  • breakpoint family 245///NBPF3// ///S4224/
  • member 2 SLC7A2 6542 2.920404 0.002217 5 retinoblastoma 1.56534
  • polypeptide J4 1.22868

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Abstract

Provided herein are improved methods and assays for predicting prognosis and/or response to therapies in cancer patients. In certain aspects, methods are provided for predicting prognosis or response to treatment with Bacillus Calmette-Guerin (BCG). In certain embodiments, the methods may involve obtaining peripheral blood mononuclear cells (PBMC) from a subject with melanoma and culturing the PBMC with BCG prior to analysis of gene expression in the PBMC.

Description

DESCRIPTION
METHODS FOR PREDICTING RESPONSE TO CANCER THERAPY
BACKGROUND OF THE INVENTION
This application claims the benefit of United States Provisional Patent Application No. 61/596,956, filed February 9, 2012, the entirety of which is incorporated herein by reference.
1. Field of the Invention
The present invention relates generally to the fields of molecular biology and medicine. More particularly, it concerns methods for predicting response outcomes to cancer therapies.
2. Description of Related Art
Cutaneous melanoma is the most rapidly increasing neoplasm in the world today, increasing at a rate of 4%-5% a year in most countries. The explanation for this rapidly rising incidence is not known, but may be related to the loss of the ozone layer from the earth which allows more ultraviolet light to reach the earth and cause skin cancer.
Located on the skin where it can be earlier observed and treated, melanoma would be expected to be a cancer with a favorable prognosis. But in fact, melanoma is the most malignant and aggressive human neoplasm; a primary melanoma as small as 5.0 mm in thickness will kill 50% of the patients within 5 years, whereas comparably sized breast, colon or other solid cancers would kill none. In fact, even thin melanomas measuring 1.0-1.5 mm in thickness have a 20% rate of metastasis to the regional lymph nodes (AJCC - Stage III). These metastases in regional lymph nodes spread to distant sites (AJCC Stage IV) and result in death of about 35%-65% of patients with nodal metastases within 5 years depending upon the size and number of involved lymph nodes. Those patients who have metastases to a distant organ site and are treated with current systemic therapies survive a median of only 10- 12 months and less than 5% survive five years or more. However, if these patients have a small number of metastases that are surgically resected, then their five year survival potential may increase to 35%-40%. Other than surgery there are few effective therapies for melanoma. Those therapies that are used as an adjuvant following surgery to treat potential micrometastases of melanoma that remain after surgery are very toxic: such examples include high-dose interferon or IL-2, and more recently the biological Yervoy (ipilimumab) which is an anti CTLA-4 antibody recently approved by the FDA for Stage III and IV melanoma. All of these treatments are expensive; for example, Yervoy costs $ 120,000 for a 4-course treatment. Other than cost, the toxic side effects associated with these adjuvant treatments include hepatitis, ulcerative colitis, thyroiditis and psychological changes such as depression, and some treatment related deaths. Thus, if it could be predicted the whether 35-65% of Stage III patients would be long-term vs. short-term survivors, it would greatly contribute to the subsequent management of their malignant melanoma. This information could aid in treatment decisions; to avoid adverse and toxic side effects in patients who show evidence for long-term survival as well as save the health care system the cost of treatment of those patients. This would allow physicians to concentrate therapeutic efforts on the patients who show evidence for short- term survival. Such patients will more readily accept more aggressive, toxic therapies as well as the cost of adjuvant treatment.
Thus, the ability to separate individual patients into those that will survive for longer periods versus those that will soon die of their disease would improve not only treatment of individual patients, but may also provide information to identify research subjects who would be more willing to undergo trials in the testing of new therapies of melanoma.
While the present histopathologic and blood assays do not differentiate between patients who will have long-term survival from those who will have short-term survival, they can identify with fair accuracy large groups of patients who will show 20%-30% overall differences in survival from other patient groups. No test currently can predict whether an individual patient is going to survive or shortly die of his disease. This, of course, creates great anxiety on the part of the patient and requires close and careful follow up by multiple physicians, requiring frequent follow up visits, multiple PET/CT scans at great expense to the health care costs and a patient's quality of life. These tests and follow up appointments would be justified in a patient whom is predicted to have a poor survival, but could be avoided in those patients who may be cured by surgery alone.
Currently there are no tests commercially available that can distinguish with 90% accuracy between short-term survival and long-term survival in melanoma patients. A number of blood tumor markers' assays have been proposed to identify patients that are more likely to recur versus those who will not recur, such as serum LDH levels, TA-90 Immune complex levels, circulating tumor cells, serum SlOO assays and melanoma inhibiting factor assays. All of these may show changes when patients are followed serially and rising levels of these markers may suggest a recurrence. However, these assays are not particularly sensitive when the patient initially presents for treatment and are not able to effectively predict whether a patient will recur early and die or survive long-term. Therefore, there is clearly a need for an improved assay for predicting early in a patient's course whether the patient will likely recur and die from the disease or remain free of disease, e.g., and therefore need no adjuvant treatment.
SUMMARY OF THE INVENTION
Provided herein are improved methods and assays for predicting prognosis in cancer patients. For example, in various aspects, assays are provided that may be used to differentiate between subjects with melanoma who will remain free of disease for about 5-10 years and subjects with melanoma that will recur early within the first 2-3 years, e.g., with greater than about 99% accuracy. Methods are provided in various aspects for predicting prognosis or response to therapy with Bacillus Calmette-Guerin (BCG) for subjects with a cancer, such as, e.g., melanoma, breast cancer, colon cancer, lung cancer, bowel cancer, pancreatic cancer, renal cancer, or other solid cancerous tumor. An aspect of the present invention relates to an in vitro method for providing a prognosis or prediction of response to a treatment with Bacillus Calmette-Guerin (BCG) in a subject with a cancer, said method comprising: a) culturing in vitro a first and second biological sample from the patient comprising cells in the presence and absence of Bacillus Calmette-Guerin, respectively, for a sufficient time and under conditions to permit gene expression by the cells; b) assessing the expression of one, two, three, four, five or all biomarkers selected from the group of biomarkers consisting of 240534_at, LOC283038, AGR2, RRP7A, LI C00472, and RR 3P2 in the first and second cultured biological sample; and c) providing a prognosis or prediction for the subject based on the expression information, such that an increase in expression of LINC00472, RR 3P2, or 240534_at in the first biological sample as compared to the second biological sample indicates a poor survival, a high risk of recurrence, or a poor response to said treatment with Bacillus Calmette-Guerin, and an increase in expression of AGR2, LOC283038, or RRP7A in the first biological sample as compared to the second biological sample indicates a favorable survival, a low risk of recurrence, or a favorable response to said treatment with Bacillus Calmette- Guerin. Generally, the first and second biological samples should contain cells of the same tissue type; for example, the first and second biological samples may be blood samples and may contain peripheral blood mononuclear cells. In some embodiments, the prognosis or prediction further comprises evaluating the presence or absence of ulceration of the cancer (e.g., an original or primary cancer) in the subject, wherein ulceration indicates a poor survival, a high risk of recurrence, or a poor response to said treatment with Bacillus Calmette-Guerin. The sample may comprise a blood sample. The sample may comprise peripheral blood mononuclear cells. Said contacting or culturing may occur in vitro. Said contacting or culturing may comprise culturing peripheral blood mononuclear cells from the sample with BCG for from about 3 to about 9 hours, about 6 hours, at least 6 hours, at least 12 hours, or at least 24 hours. Bacillus Calmette-Guerin may be administered to the subject. Said contacting or culturing may occur in vivo. The cancer may be a melanoma, breast cancer, colon cancer, lung cancer, bowel cancer, pancreatic cancer, or renal cancer. The melanoma may be a stage II, stage III, or stage IV melanoma. Said obtaining expression information may comprise obtaining or receiving said sample. The sample may be paraffin- embedded and/or frozen. In some embodiments, said obtaining expression information comprises measuring expression of said one or more biomarkers. In some embodiments, said obtaining expression information may comprise RNA quantification, e.g., cDNA microarray, quantitative RT-PCR, in situ hybridization, Northern blotting or nuclease protection. Said obtaining expression information may comprise protein quantification, e.g., protein quantification comprises immunohistochemistry, an ELISA, a radioimmunoassay (RIA), an immunoradiometric assay, a fluoroimmunoassay, a chemiluminescent assay, a bioluminescent assay, a gel electrophoresis, or a Western blot analysis. Providing the prognosis or prediction may comprise generating a classifier based on the expression, wherein the classifier is defined as a weighted sum of expression levels of the biomarkers. Providing the prognosis or prediction may comprise generating a weighted gene voting score. The classifier is generated on a computer. The classifier may be generated by a computer readable medium comprising machine executable instructions suitable for generating a classifier. Providing the prognosis or prediction may comprise classifying a group of subjects based on the classifier associated with individual subjects in the group with a reference value. The method may further comprise reporting said prognosis or prediction. The method may further comprise prescribing or administering an adjuvant therapy to said subject based on said prediction. In some embodiments, a BCG therapy is prescribed or administered to the subject based on said prediction. In other embodiments, a BCG therapy is not prescribed or administered to the subject based on said prediction. The cancer may be a stage II cancer or a stage III cancer, or a stage IV cancer. In some embodiments, the cancer is not a stage IV cancer. Another aspect of the present invention relates to a composition comprising Bacillus
Calmette-Guerin (BCG) for use in treating cancer in a patient from whom a biological sample comprising cells has been tested by culturing in the presence of BCG and determined to exhibit an increase in expression of AGR2, LOC283038, or RRP7A as compared to such a sample that was not cultured in the presence of BCG. The cancer may be a melanoma.
Yet another aspect of the present invention relates to a method of treating a patient having a cancer, comprising selecting an individual whose peripheral blood mononuclear cells express an increased level of one, two, or all of AGR2, LOC283038, or RRP7A, relative to a reference expression level, as a result of culturing said cells with Bacillus Calmette- Guerin (BCG); and administering a BCG therapy to the subject. Said selecting may comprise measuring expression of said at least one of AGR2, LOC283038, or RRP7A in said peripheral blood mononuclear cells in vitro. The cancer may be a melanoma. Some aspects of the present invention relate to a method for providing a prognosis or prediction of response to a treatment with Bacillus Calmette-Guerin (BCG) in a subject with a cancer, said method comprising: obtaining expression information of biomarkers in a biological sample of a subject by testing said sample; wherein the biological sample is contacted or cultured with Bacillus Calmette-Guerin prior to said testing; and wherein the biomarkers either: (a) comprise at least ten genes from the group consisting of Tables 2-4, or (b) comprise 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more of: 1555845_at, 1560271_at, 1562673_at, 216771_at, 224105_x_at, 236502_at, 240534_at, 244055_at, AGR2, ATG5, C18orf25, C22orf39, CIRBP-AS1, CYP4B 1, EPHA1, HNRNPD, LARS2, LI C00472, LOC100509474 /// ZNF518A, LOC283038, MASP1, METAP 1, MTF2, OCLN, PDLIM7, PWWP2B, RRN3P2, RRP7A, SMC1A, SRGAP1, TSC22D1, UBXN8, WDR25, and/or WDR87; and providing a prognosis or prediction for the subject based on the expression information. In some embodiments, as compared with a reference expression level, altered expression of one or more genes selected from the group consisting of the genes listed in Tables 2-4 having a positive FC(SS/LS)-value indicates a poor survival, a high risk of recurrence, or a poor response to said treatment with Bacillus Calmette-Guerin, and altered expression of one or more genes selected from the group consisting of Tables 2-4 having a negative FC(SS/LS)- value indicates a favorable survival, a low risk of recurrence, or a favorable response to said treatment with Bacillus Calmette-Guerin. In some embodiments, as compared with a reference expression level, increased expression of one or more of 1555845_at, 1560271_at, 1562673_at, 224105_x_at, 236502_at, 244055_at, C18orf25, C22orf39, LARS2, LOC100509474 /// ZNF518A, LOC283038, METAP1, MTF2, OCLN, SMC1A, UBXN8, and/or WDR25 a favorable survival, a low risk of recurrence, or a favorable response to said treatment with Bacillus Calmette-Guerin, and increased expression of one or more of 216771_at, 240534_at, CIRBP-AS1, CYP4B1, EPHA1, LI C00472, MASP 1, RRN3P2, SRGAP 1, WDR87 indicates a poor survival, a high risk of recurrence, or a poor response to said treatment with Bacillus Calmette-Guerin. Another aspect of the present invention relates to an array comprising a plurality of antigen-binding fragments that bind to expression products of biomarkers or a plurality of primers or probes that bind to transcripts of the biomarkers to assess expression levels, the biomarkers comprising either (a) 1, 2, 3, 4, 5 or all of AGR2, LOC283038, RRP7A, LI C00472, RR 3P2, and 240534_at, (b) 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more of: 1555845_at, 156027 l_at, 1562673_at, 216771_at, 224105_x_at, 236502_at, 240534_at, 244055_at, AGR2, ATG5, C18orf25, C22orf39, CIRBP-AS1, CYP4B1, EPHA1, HNRNPD, LARS2, LI C00472, LOC100509474 /// ZNF518A, LOC283038, MASP 1, METAP 1, MTF2, OCLN, PDLIM7, PWWP2B, RRN3P2, RRP7A, SMC1A, SRGAP1, TSC22D 1, UBXN8, WDR25, and/or WDR87, or (c) at least ten genes selected from the group consisting of Tables 2-4. The array may be a microchip or a cDNA microarray.
Yet another aspect of the present invention relates to a kit comprising a plurality of antigen-binding fragments that bind to expression products of biomarkers or a plurality of primers or probes that bind to transcripts of the biomarkers to assess expression levels, the biomarkers comprising either (a) 1, 2, 3, 4, 5 or all of AGR2, LOC283038, RRP7A, LTNC00472, RRN3P2, and 240534_at, (b) 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more of: 1555845_at, 156027 l_at, 1562673_at, 216771_at, 224105_x_at, 236502_at, 240534_at, 244055_at, AGR2, ATG5, C18orf25, C22orf39, CIRBP-AS1, CYP4B1, EPHA1, HNRNPD, LARS2, LI C00472, LOC100509474 /// ZNF518A, LOC283038, MASP 1, METAP 1, MTF2, OCLN, PDLIM7, PWWP2B, RRN3P2, RRP7A, SMC1A, SRGAP1, TSC22D 1, UBXN8, WDR25, and/or WDR87, or (c) at least ten genes selected from the group consisting of Tables 2-4, wherein said kit is housed in a container.
In some aspects, a biological sample comprising PBMC may be cultured in a media for a period of time of at least about 3, 4, 5, 6, 7, 8, 9, 10, 1 1, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24 or more hours prior to measuring the gene expression of the PBMC. The PBMC may be cultured in the presence or absence of BCG. In some embodiments, expression of one or more of the genes listed in Tables 1-4, Tables 2-4, or 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more of: 1555845_at, 1560271_at, 1562673_at, 216771_at, 224105_x_at, 236502_at, 240534_at, 244055_at, AGR2, ATG5, C18orf25, C22orf39, CIRBP-AS1, CYP4B 1, EPHA1, HNRNPD, LARS2, LINC00472, LOC100509474 /// ZNF518A, LOC283038, MASP 1, METAP1, MTF2, OCLN, PDLIM7, PWWP2B, RRN3P2, RRP7A, SMC1A, SRGAP1, TSC22D1, UBXN8, WDR25, and/or WDR87, may be measured in PBMC from a subject after culture of the PBMC in a media that does not contain BCG and used to predict response to a BCG therapy.
It is anticipated that assays and methods provided herein may be used for generally predicting the immune response to a therapy with BCG for subjects. For example, in some embodiments, PBMC expression may be evaluated as described herein, and it is anticipated that prediction of a good prognosis or poor prognosis response to BCG in cancer will correlate with increased or decreased protection, respectively, against tuberculosis or other bacteria after vaccination with BCG.
In various aspects, assays are provided for utilizing peripheral blood mononuclear cells (PBMC) from a melanoma patient (e.g., a Stage III melanoma patient) which upon culture with BCG will induce gene expression profiles. In particular embodiments, RNA from PBMC exposed to or cultured in the presence of BCG may be detected, measured, or analyzed, e.g., via microarray analysis, RT-PCT, etc. The expression profiles may be used to indentify an immune phenotype that can lead to prolonged survival in the melanoma or other cancer patients. In various aspects, methods and assays disclosed herein may be used to identify genes and/or pathways that can modulate host defense against melanoma. These approaches may be used to target specific immunotherapies that enhance the activity of these naturally occurring anti-tumor immune responses.
The tissue sample may be collected from a subject with a cancer and, optionally, stored or shipped prior to testing. The collection may comprise surgical resection. The sample of tissue may be stored in RNALater™ or flash frozen, such that RNA may be isolated at a later date. RNA may be isolated from the tissue and used to generate labeled probes for a nucleic acid microarray analysis. The RNA may also be used as a template for qRT-PCR in which the expression of a plurality of biomarkers is analyzed. The expression data generated may be used to derive a score which may predict an individual's response to BCG immune stimulation or predict an individual's survival from cancer, e.g., using the- Rank Hypergeometric Overlap (RRHO) analysis method of Plaisier et al. (2010), or to obtain a sum based on each corresponding biomarker gene expression by weighted gene voting (Golub et al., 1999). The score may be used to predict whether the subject will be a short- term or a long-term cancer survivor. Biomarker genes that may be used in cancer prognosis or score generation may be one or more selected from (a) 1, 2, 3, 4, 5, or all of 240534_at, LOC283038, AGR2, RRP7A, LINC00472, or RRN3P2; (b) 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more of : 1555845_at, 1560271_at, 1562673_at, 216771_at, 224105_x_at, 236502_at, 240534_at, 244055_at, AGR2, ATG5, C18orf25, C22orf39, CIRBP-AS1, CYP4B1, EPHA1, HNRNPD, LARS2, LINC00472, LOC100509474 /// ZNF518A, LOC283038, MASP 1, METAP 1, MTF2, OCLN, PDLIM7, PWWP2B, RRN3P2, RRP7A, SMC1A, SRGAP1, TSC22D1, UBXN8, WDR25, and/or WDR87, or (c) Tables 1-4 or Tables 2-4. In some embodiments, at least 10, 20, 30, 40, 50, 60, 70, 80, 90, 100 of more of the genes listed in Tables 2-4 may be detected or measured, e.g., to predict a response to a treatment with Bacillus Calmette-Guerin (BCG) in a subject.
The expression of biomarkers or genes may be measured by a variety of techniques that are well known in the art. Quantifying the levels of the messenger RNA (mRNA) of a biomarker may be used to measure the expression of the biomarker. Alternatively, quantifying the levels of the protein product of a biomarker may be used to measure the expression of the biomarker. Additional information regarding the methods discussed below may be found in Ausubel et al. (2003) or Sambrook et al. (1989). One skilled in the art will know which parameters may be manipulated to optimize detection of the mRNA or protein of interest.
A nucleic acid microarray may be used to quantify the differential expression of a plurality of biomarkers. Microarray analysis may be performed using commercially available equipment, following manufacturer's protocols, such as by using the Affymetrix GeneChip® technology (Santa Clara, CA) or the Microarray System from Incyte (Fremont, CA). For example, single-stranded nucleic acids (e.g., cDNAs or oligonucleotides) may be plated, or arrayed, on a microchip substrate. The arrayed sequences are then hybridized with specific nucleic acid probes from the cells of interest. Fluorescently labeled cDNA probes may be generated through incorporation of fluorescently labeled deoxynucleotides by reverse transcription of RNA extracted from the cells of interest. Alternatively, the RNA may be amplified by in vitro transcription and labeled with a marker, such as biotin. The labeled probes are then hybridized to the immobilized nucleic acids on the microchip under highly stringent conditions. After stringent washing to remove the non-specifically bound probes, the chip is scanned by confocal laser microscopy or by another detection method, such as a CCD camera. The raw fluorescence intensity data in the hybridization files are generally preprocessed with the robust multichip average (RMA) algorithm to generate expression values.
Quantitative real-time PCR (qRT-PCR) may also be used to measure the differential expression of a plurality of biomarkers. In qRT-PCR, the RNA template is generally reverse transcribed into cDNA, which is then amplified via a PCR reaction. The amount of PCR product is followed cycle-by-cycle in real time, which allows for determination of the initial concentrations of mRNA. To measure the amount of PCR product, the reaction may be performed in the presence of a fluorescent dye, such as SYBR Green, which binds to double- stranded DNA. The reaction may also be performed with a fluorescent reporter probe that is specific for the DNA being amplified.
A non-limiting example of a fluorescent reporter probe is a TaqMan® probe (Applied Biosystems, Foster City, CA). The fluorescent reporter probe fluoresces when the quencher is removed during the PCR extension cycle. Multiplex qRT-PCR may be performed by using multiple gene-specific reporter probes, each of which contains a different fluorophore. Fluorescence values are recorded during each cycle and represent the amount of product amplified to that point in the amplification reaction. To minimize errors and reduce any sample-to-sample variation, qRT-PCR may be performed using a reference standard. The ideal reference standard is expressed at a constant level among different tissues, and is unaffected by the experimental treatment. Suitable reference standards include, but are not limited to, mRNAs for the housekeeping genes glyceraldehyde-3-phosphate-dehydrogenase (GAPDH) and β-actin. The level of mRNA in the original sample or the fold change in expression of each biomarker may be determined using calculations well known in the art.
Immunohistochemical staining may also be used to measure the differential expression of a plurality of biomarkers. This method enables the localization of a protein in the cells of a tissue section by interaction of the protein with a specific antibody. For this, the tissue may be fixed in formaldehyde or another suitable fixative, embedded in wax or plastic, and cut into thin sections (from about 0.1 mm to several mm thick) using a microtome. Alternatively, the tissue may be frozen and cut into thin sections using a cryostat. The sections of tissue may be arrayed onto and affixed to a solid surface (i.e., a tissue microarray). The sections of tissue are incubated with a primary antibody against the antigen of interest, followed by washes to remove the unbound antibodies. The primary antibody may be coupled to a detection system, or the primary antibody may be detected with a secondary antibody that is coupled to a detection system. The detection system may be a fluorophore or it may be an enzyme, such as horseradish peroxidase or alkaline phosphatase, which can convert a substrate into a colorimetric, fluorescent, or chemiluminescent product. The stained tissue sections are generally scanned under a microscope. Because a sample of tissue from a subject with cancer may be heterogeneous, i.e., some cells may be normal and other cells may be cancerous, the percentage of positively stained cells in the tissue may be determined. This measurement, along with a quantification of the intensity of staining, may be used to generate an expression value for the biomarker.
An enzyme-linked immunosorbent assay, or ELISA, may be used to measure the differential expression of a plurality of biomarkers. There are many variations of an ELISA assay. All are based on the immobilization of an antigen or antibody on a solid surface, generally a microtiter plate. The original ELISA method comprises preparing a sample containing the biomarker proteins of interest, coating the wells of a microtiter plate with the sample, incubating each well with a primary antibody that recognizes a specific antigen, washing away the unbound antibody, and then detecting the antibody-antigen complexes. The antibody-antibody complexes may be detected directly. For this, the primary antibodies are conjugated to a detection system, such as an enzyme that produces a detectable product. The antibody-antibody complexes may be detected indirectly. For this, the primary antibody is detected by a secondary antibody that is conjugated to a detection system, as described above. The microtiter plate is then scanned and the raw intensity data may be converted into expression values using means known in the art.
An antibody microarray may also be used to measure the differential expression of a plurality of biomarkers. For this, a plurality of antibodies is arrayed and covalently attached to the surface of the microarray or biochip. A protein extract containing the biomarker proteins of interest is generally labeled with a fluorescent dye. The labeled biomarker proteins are incubated with the antibody microarray. After washes to remove the unbound proteins, the microarray is scanned. The raw fluorescent intensity data may be converted into expression values using means known in the art.
Luminex multiplexing microspheres may also be used to measure the differential expression of a plurality of biomarkers. These microscopic polystyrene beads are internally color-coded with fluorescent dyes, such that each bead has a unique spectral signature (of which there are up to 100). Beads with the same signature are tagged with a specific oligonucleotide or specific antibody that will bind the target of interest (i.e., biomarker mRNA or protein, respectively). The target, in turn, is also tagged with a fluorescent reporter. Hence, there are two sources of color, one from the bead and the other from the reporter molecule on the target. The beads are then incubated with the sample containing the targets, of which up to 100 may be detected in one well. The small size/surface area of the beads and the three dimensional exposure of the beads to the targets allows for nearly solution-phase kinetics during the binding reaction. The captured targets are detected by high-tech fluidics based upon flow cytometry in which lasers excite the internal dyes that identify each bead and also any reporter dye captured during the assay. The data from the acquisition files may be converted into expression values using means known in the art.
In situ hybridization may also be used to measure the differential expression of a plurality of biomarkers. This method permits the localization of mRNAs of interest in the cells of a tissue section. For this method, the tissue may be frozen, or fixed and embedded, and then cut into thin sections, which are arrayed and affixed on a solid surface. The tissue sections are incubated with a labeled antisense probe that will hybridize with an mRNA of interest. The hybridization and washing steps are generally performed under highly stringent conditions. The probe may be labeled with a fluorophore or a small tag (such as biotin or digoxigenin) that may be detected by another protein or antibody, such that the labeled hybrid may be detected and visualized under a microscope. Multiple mRNAs may be detected simultaneously, provided each antisense probe has a distinguishable label. The hybridized tissue array is generally scanned under a microscope. Because a sample of tissue from a subject with cancer may be heterogeneous, i.e., some cells may be normal and other cells may be cancerous, the percentage of positively stained cells in the tissue may be determined. This measurement, along with a quantification of the intensity of staining, may be used to generate an expression value for each biomarker. The number of biomarkers whose expression is measured in a sample of cells from a subject with cancer may vary. Since the risk score is based upon the differential expression of the biomarkers, a higher degree of accuracy should be attained when the expression of more biomarkers is measured; however, a large number of biomarkers in the gene signature would hamper the clinical usefulness. In a certain embodiment, the differential expression of a selected number of biomarkers may be measured.
As used herein, "obtaining a biological sample" or "obtaining a blood sample" refer to receiving a biological or blood sample, e.g., either directly or indirectly. For example, in some embodiments, the biological sample, such as a blood sample or a sample containing peripheral blood mononuclear cells (PBMC), is directly obtained from a subject at or near the laboratory or location where the biological sample will be analyzed. In other embodiments, the biological sample may be drawn or taken by a third party and then transferred, e.g., to a separate entity or location for analysis. In other embodiments, the sample may be obtained and tested in the same location using a point-of care test. In these embodiments, said obtaining refers to receiving the sample, e.g., from the patient, from a laboratory, from a doctor's office, from the mail, courier, or post office, etc. In some further aspects, the method may further comprise reporting the determination to the subject, a health care payer, an attending clinician, a pharmacist, a pharmacy benefits manager, or any person that the determination may be of interest. "Patient response" can be assessed using any endpoint indicating a benefit to the patient, including, without limitation, (1) inhibition, to some extent, of disease progression, including slowing down and complete arrest; (2) reduction in the number of disease episodes and/or symptoms; (3) reduction in lesional size; (4) inhibition (i.e., reduction, slowing down or complete stopping) of disease cell infiltration into adjacent peripheral organs and/or tissues; (5) inhibition (i.e., reduction, slowing down or complete stopping) of disease spread; (6) relief, to some extent, of one or more symptoms associated with the disorder; (7) increase in the length of disease-free presentation following treatment; and/or (8) decreased mortality at a given point of time following treatment.
"Prognosis" refers to a prediction of how a patient will progress, and whether there is a chance of recovery. "Cancer prognosis" generally refers to a forecast or prediction of the probable course or outcome of the cancer. As used herein, cancer prognosis includes the forecast or prediction of any one or more of the following: duration of survival of a patient susceptible to or diagnosed with a cancer, duration of recurrence-free survival, duration of progression-free survival of a patient susceptible to or diagnosed with a cancer, response rate in a group of patients susceptible to or diagnosed with a cancer, duration of response in a patient or a group of patients susceptible to or diagnosed with a cancer, and/or likelihood of metastasis in a patient susceptible to or diagnosed with a cancer. Prognosis also includes prediction of favorable responses to cancer treatments, such as a conventional cancer therapy.
By "subject" or "patient" is meant any single subject for which therapy is desired, including humans, cattle, dogs, guinea pigs, rabbits, chickens, and so on. Also intended to be included as a subject are any subjects involved in clinical research trials not showing any clinical sign of disease, or subjects involved in epidemiological studies, or subjects used as controls.
As used herein, "increased expression" refers to an elevated or increased level of expression in a cancer sample relative to a suitable control (e.g., a non-cancerous tissue or cell sample, a reference standard), wherein the elevation or increase in the level of gene expression is statistically significant (p < 0.05). Whether an increase in the expression of a gene in a cancer sample relative to a control is statistically significant can be determined using an appropriate t-test (e.g., one-sample t-test, two-sample t-test, Welch's t-test) or other statistical test known to those of skill in the art. Genes that are overexpressed in a cancer can be, for example, genes that are known, or have been previously determined, to be overexpressed in a cancer.
As used herein, "decreased expression" refers to a reduced or decreased level of expression in a cancer sample relative to a suitable control (e.g., a non-cancerous tissue or cell sample, a reference standard), wherein the reduction or decrease in the level of gene expression is statistically significant (p < 0.05). In some embodiments, the reduced or decreased level of gene expression can be a complete absence of gene expression, or an expression level of zero. Whether a decrease in the expression of a gene in a cancer sample relative to a control is statistically significant can be determined using an appropriate t-test (e.g., one-sample t-test, two-sample t-test, Welch's t-test) or other statistical test known to those of skill in the art. Genes that are underexpressed in a cancer can be, for example, genes that are known, or have been previously determined, to be underexpressed in a cancer. In a further embodiment, the marker level may be compared to the level of the marker from a control, wherein the control may comprise one or more tumor samples (e.g., colon cancer samples) taken from one or more patients determined as having a good prognosis ("good prognosis" control) or a poor prognosis ("poor prognosis" control), or both. The control may comprise data obtained at the same time (e.g., in the same hybridization experiment) as the patient's individual data, or may be a stored value or set of values, e.g., stored on a computer, or on computer-readable media. If the latter is used, new patient data for the selected marker(s), obtained from initial or follow-up samples, can be compared to the stored data for the same marker(s) without the need for additional control experiments.
A good or bad prognosis may, for example, be assessed in terms of patient survival, likelihood of disease recurrence or disease metastasis (patient survival, disease recurrence and metastasis may for example be assessed in relation to a defined timepoint, e.g., at a given number of years after cancer surgery (e.g., surgery to remove one or more tumors) or after initial diagnosis. In one embodiment, a good or bad prognosis may be assessed in terms of overall survival or disease free survival.
For example, "good prognosis" may refer to the likelihood that a patient afflicted with cancer will remain disease free (e.g., cancer free) or survive despite the presence of the cancer. "Poor prognosis" may be used to mean the likelihood of a relapse or recurrence of the underlying cancer or tumor, metastasis, or death. Cancer patients classified as having a "good prognosis" may remain free of the underlying cancer or tumor or survive despite the presence of cancer or tumor. For example, cancerous cells and/or tumors from a cancer may continue to exist in a patient with a good prognosis, but the patient's immune system may slow or prevent the progression or growth of the cancer, thus allowing the patient to continue to survive. In contrast, "bad prognosis" cancer patients experience disease relapse, tumor recurrence, metastasis, and death. In particular embodiments, the time frame for assessing prognosis and outcome is, for example, less than one year, one, two, three, four, five, six, seven, eight, nine, ten, fifteen, twenty, or more years. In certain aspects, the relevant time for assessing prognosis or disease-free survival time may begin at the time of the surgical removal of the tumor or suppression, mitigation, or inhibition of tumor growth. A "good prognosis" refers to the likelihood that a cancer patient will survive for a period of at least five, such as for a period of at least ten years. In further aspects of the invention, a "poor prognosis" refers to the likelihood that a cancer patient, such as a melanoma patient, will experience disease relapse, tumor recurrence, metastasis, or death within less than ten years, such as less than five years or less than 1.5 years. Time frames for assessing prognosis and outcome provided herein are illustrative and are not intended to be limiting. The term "high risk" means the patient is expected to have a distant relapse in a shorter period less than a predetermined value (for example, from a control), for example in less than 5 years, preferably in less than 3 years or less than 1.5 years. The term "low risk" means the patient is expected to have a distant relapse in a longer period greater than a predetermined value, for example, after 5 years, preferably in more than ten years. Time frames for assessing risks provided herein are illustrative and are not intended to be limiting.
The term "antigen binding fragment" herein is used in the broadest sense and specifically covers intact monoclonal antibodies, polyclonal antibodies, multispecific antibodies (e.g., bispecific antibodies) formed from at least two intact antibodies, and antibody fragments. The term "primer," as used herein, is meant to encompass any nucleic acid that is capable of priming the synthesis of a nascent nucleic acid in a template-dependent process. Primers may be oligonucleotides from ten to twenty and/or thirty base pairs in length, but longer sequences can be employed. Primers may be provided in double-stranded and/or single-stranded form, although the single-stranded form is preferred. Embodiments discussed in the context of methods and/or compositions of the invention may be employed with respect to any other method or composition described herein. Thus, an embodiment pertaining to one method or composition may be applied to other methods and compositions of the invention as well.
As used herein the terms "encode" or "encoding" with reference to a nucleic acid are used to make the invention readily understandable by the skilled artisan; however, these terms may be used interchangeably with "comprise" or "comprising," respectively.
As used herein the specification, "a" or "an" may mean one or more. As used herein in the claim(s), when used in conjunction with the word "comprising," the words "a" or "an" may mean one or more than one. The use of the term "or" in the claims is used to mean "and/or" unless explicitly indicated to refer to alternatives only or the alternatives are mutually exclusive, although the disclosure supports a definition that refers to only alternatives and "and/or." As used herein "another" may mean at least a second or more.
Throughout this application, the term "about" is used to indicate that a value includes the inherent variation of error for the device, the method being employed to determine the value, or the variation that exists among the study subjects.
Other objects, features and advantages of the present invention will become apparent from the following detailed description. It should be understood, however, that the detailed description and the specific examples, while indicating preferred embodiments of the invention, are given by way of illustration only, since various changes and modifications within the spirit and scope of the invention will become apparent to those skilled in the art from this detailed description.
BRIEF DESCRIPTION OF THE DRAWINGS
The following drawings form part of the present specification and are included to further demonstrate certain aspects of the present invention. The invention may be better understood by reference to one or more of these drawings in combination with the detailed description of specific embodiments presented herein.
FIG. 1 : Survival curve of patients studied. Eleven melanoma patients (matched by age, sex and tumor burden), six of whom survived less than 1.5 years (short term survivors- SS) and five of whom survived greater than ten years (long term survivors-LS) after BCG immunostimulation. FIG. 2: Sum of votes from high weighted genes (weights > 1.1) from samples treated as labeled in the charts.
FIG. 3: RRHO Map. Rank pairs were used to find optimal overlapping gene sets.
FIGS. 4A-D: Pathways analysis of overlapping T-lep/ LS and L-lep/SS genes (FIG. 4A and FIG. 4B). To detect which gene sets or biological pathways are overrepresented LS melanoma and T-lep patients might be particularly relevant to improved host immunity, the inventors studied the 2003 genes identified by RRHO (in FIG. 3) which showed significant overlap in T-lep vs. L-lep and LS vs SS using knowledge-guided bioinformatic analysis, incorporating data on likely biologic functions, including gene ontology information and regulatory data (Ingenuity® Systems, www.ingenuity.com). Shown are the top five functional groups and canonical pathways found. IPA was used to study the 960 genes identified by RRHO which showed significant overlap in L-lep vs. T-lep and SS vs LS (FIG. 4C and FIG. 4D). Shown are the top five functional groups and canonical pathways found.
FIGS. 5A-C: Sum of votes from all probesets with weight > 1.1 (FIG. 5 A), top 50 probesets (FIG. 5B) and top 100 (FIG. 5C) weighted probesets from PBMCs treated with media for six hours.
FIGS. 6A-C: Sum of votes from all probesets with weight > 1.1 (FIG. 6A), top 50 probesets (FIG. 6B) and top 100 (FIG. 6C) weighted probesets from PBMCs treated with BCG for six hours. FIGS. 7A-C: Sum of votes from all probesets with weight > 1.1 (FIG. 7A), top 50 probesets (FIG. 7B) and top 100 (FIG. 7C) weighted probesets from PBMCs treated with media for 24 hours.
FIGS. 8A-C: Sum of votes from all probesets with weight > 1.1 (FIG. 8A), top 50 probesets (FIG. 8B) and top 100 (FIG. 8C) weighted probesets from PBMCs treated with BCG for 24 hours.
FIG. 9: Spectrum of melanoma patients tested is shown.
FIG. 10: An example of a method of experiments is shown.
DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS
Bacillus Calmette-Guerin (BCG), obtained from a strain of the attenuated live bovine tuberculosis bacillus Mycobacterium bovis, is administered as a vaccine for tuberculosis and is also used as a potent adjuvant for the treatment of superficial bladder cancer. The clinical off-label use of BCG as a systemic immune adjuvant for over 30 years in melanoma patients with advanced resectable disease by surgical oncologists suggests it use may improve survival.
Here, the inventors investigated peripheral blood responses of melanoma patients prior to BCG administration in known "short-term survivors" (SS) versus "long-term survivors" (LS) to gain insight into BCG-induced immune pathways that may be important for melanoma survival.
In some embodiments, methods are provided for providing a prognosis or prediction of response to a treatment with Bacillus Calmette-Guerin (BCG) in a subject with a cancer, said method comprising: a) obtaining expression information of one or more biomarkers in a biological sample from the subject by testing said sample; wherein the biological sample is contacted or cultured with Bacillus Calmette-Guerin in vitro prior to said testing; and wherein said biomarkers comprise 1, 2, 3, 4, 5, or all of 240534_at, LOC283038, AGR2, RRP7A, LI C00472, and/or RR 3P2; and b) providing a prognosis or prediction for the subject based on the expression information, wherein, as compared with a reference expression level, an increase in expression of LINC00472, RRN3P2, or 240534_at indicates a poor survival, a high risk of recurrence, or a poor response to said treatment with Bacillus Calmette-Guerin, and an increase in expression of AGR2, LOC283038, or RRP7A indicates a favorable survival, a low risk of recurrence, or a favorable response to said treatment with Bacillus Calmette-Guerin. As shown in the below examples, 11 melanoma patients (matched by age, sex and tumor burden) were studied, six of whom survived less than 1.5 years (short term survivors- SS) and five of whom survived greater than ten years (long term survivors-LS) after BCG immunostimulation. Peripheral blood mononuclear cells (PBMCs) collected prior to BCG administration were stimulated in vitro with either BCG or media for six or 24 hours and analyzed by gene expression microarrays. To determine whether the gene expression differences between LS and SS in BCG responsiveness in vitro can provide theragnostic information in melanoma patients considering BCG immunostimulation, we selected probesets with high signal-to-noise ratios, with weights above 1.1 (lists of probesets used are in Tables 1-4). Expression data, p values, and fold changes of LS vs SS were obtained. The top 50 and top 100 genes were identified from each media condition by examining the weight values. Using weighted gene voting, probesets from gene expression profiles of cells stimulated with BCG at six (441 total) (Table 2) and 24 hours (152 total) (Table 4) predicted five LS and six SS with 100% accuracy, while cells cultured in media for 24 hours (231 total) (Table 3) predicted 10 of the 1 1 samples (91%) and cells in media for six hours predicted 8 of 11 (206 total) (Table 1). Methods of the present invention may be used, in some embodiments, to identify patients who may benefit more from in vivo BCG immunostimulation for melanoma by in vitro testing prior to therapy.
The inventors found that the 24 hr BCG samples allowed the construction of a robust, 100% accurate classifier for long or short prediction probe lists (all probesets with >1.1 weight, or top 50 or top 100). This is evidently the most robust sample group to attain high prediction accuracy classifiers for outcome in melanoma.
Long probe lists (weight > 1.1, N = 206 in 6 hr Med and N = 231 24 hr Med) are needed to cumulatively attain high prediction accuracy in the 6 hr BCG and 24 hr Med groups. A short probe list with only the highest weight/signal to noise ratio (SNR) genes can be used to attain high prediction accuracy in the 6 hr Med group (top 50 or top 100). Each melanoma outcome classifier may be tested using a replicate patient data set. In some embodiments, a 6 hr BCG classifier may be used to predict the samples in a second independent patient set. In other embodiments, the 24 hr BCG classifier may be used to predict the samples in a second independent patient set. A combination of probes from each in vitro treatment and time point may also be used in predicting cancer prognosis or response to BGC treatment.
Biomarker genes that may be used in cancer prognosis or risk score generation may be: (a) 1, 2, 3, 4, 5, or all of 240534_at, LOC283038, AGR2, RRP7A, LTNC00472, or RRN3P2; (b) 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more of : 1555845_at, 1560271_at, 1562673_at, 216771_at, 224105_x_at, 236502_at, 240534_at, 244055_at, AGR2, ATG5, C18orf25, C22orf39, CIRBP-AS1, CYP4B 1, EPHA1, HNRNPD, LARS2, LTNC00472, LOC100509474 /// ZNF518A, LOC283038, MASP1, METAP 1, MTF2, OCLN, PDLIM7, PWWP2B, RRN3P2, RRP7A, SMC1A, SRGAP1, TSC22D1, UBXN8, WDR25, and/or WDR87, or (c) one or more selected from Tables 1 -4, preferably Tables 2-4, below.
Tables 1-4 : probe set refers to the Affymetrix probe set identification number, des is the description of the gene represented by the probeset, symbol is the gene symbol, entrez is the ID for the NCBI entrez search site, FC refers to the signed fold change of expression in short term survivors vs. long term survivors in which a positive number refers to the fold change higher in the short-term survivors and a negative number refers to the fold change higher in the long-term survivors, t-test pvalue calculates the student's t-test p value for the expression values of the two groups comprised of six short-term survivors vs. five long-term survivors, weight refers to the calculated value described in example 1 used to identify the probesets used to classify the individual subjects.
Table 1. Probesets obtained from cells cultured in media for six hours. t-test pvalue probe set desc symbol entrez FC (SS/LS) (all samples) Weight
protease, serine,
1570274_at 55 PRSS55 203074 4.72883 0.00028 3.14976
236515_at 1.39413 0.00003 2.82269 mucin 6,
oligomeric
1565662_at mucus/gel-forming MUC6 4588 -1.28858 0.00073 2.39564 polycystic kidney
1563465_at disease 1 like 1 PKD1L1 168507 -2.46790 0.00094 2.26840
1561069_at -3.85687 0.00006 2.13257
202443_x_at notch 2 NOTCH2 4853 1.15321 0.00010 2.00561 potassium channel
tetramerisation
domain containing
226493_at 18 KCTD18 130535 -1.10513 0.00017 1.98926
237171_at -1.28000 0.00031 1.92061 twist homolog 2
229404_at (Drosophila) TWIST2 117581 -2.14330 0.00218 1.89063
RAP1 interacting
factor homolog
240098_at (yeast) RIF1 55183 1.45269 0.00084 1.82524
RAR-related
242385_at orphan receptor B RORB 6096 -2.05862 0.00034 1.79860
SWI/SN F related,
matrix associated,
actin dependent
regulator of
chromatin,
subfamily b,
228898_s_at member 1 SMARCB1 6598 -1.70319 0.00023 1.78443
1561239_at 2.44483 0.00023 1.77616
1562215_at 1.37395 0.00051 1.75049 non-protein coding
1568849_at RNA 165 NCRNA00165 727701 -1.87601 0.00050 1.71185 excision repair
cross- complementing
rodent repair
deficiency,
complementation
1554882_at group 8 ERCC8 1161 2.02451 0.00063 1.70700 stearoyl-CoA
224019_at desaturase 5 SCD5 79966 -3.37642 0.00453 1.68408
237644_at -4.95588 0.00542 1.67998 proteasome
(prosome,
macropain) 26S
subunit, non-
219485_s_at ATPase, 10 PSMD10 5716 -1.12068 0.00071 1.67193 239140_at -1.39340 0.00155 1.65761
47773_at F-box protein 42 FBX042 54455 -1.17659 0.00042 1.65181
Fer3-like
1553517_at (Drosophila) FERD3L 222894 -2.02932 0.00109 1.64856
236117_at 1.35197 0.00874 1.63034 adenosine
monophosphate
207992_s_at deaminase 3 AM PD3 272 1.73466 0.00059 1.62993
1570405_at 1.86255 0.00149 1.62460
Yipl interacting
factor homolog B
1554553_s_at (S. cerevisiae) YIF1B 90522 -1.35879 0.00155 1.60609
1555415_at 3.70754 0.00085 1.60372
240184_at -1.97413 0.00063 1.59323
238240_at 3.02105 0.00065 1.59044
231662_at arginase, liver ARG1 383 -2.27547 0.00221 1.58091
X-ray repair
complementing
defective repair in
Chinese hamster
210812_at cells 4 XRCC4 7518 1.48761 0.00073 1.57859
216146_at 2.72645 0.00066 1.56588 zinc finger protein
236267_at 346 ZNF346 23567 -1.19540 0.00591 1.56266
244087_at 1.53089 0.00416 1.54884
1569147_at 1.59710 0.00159 1.54471
1563081_at 1.76215 0.00178 1.53522
215504_x_at 1.55837 0.00085 1.51661
1562613_at -1.90403 0.00076 1.51592 hypothetical
233673_at LOC339524 LOC339524 339524 1.31038 0.00627 1.50388
237992_at -1.95060 0.00331 1.50380
1556182_x_a hypothetical
t protein LOC441869 LOC441869 441869 -1.85049 0.00103 1.47281 kringle containing
transmembrane
243029_at protein 1 KREMEN 1 83999 -1.79559 0.00104 1.46486
1555335_at integrin, alpha 9 ITGA9 3680 -4.42086 0.01540 1.45907 translocase of
inner
mitochondrial
membrane 22
219184_x_at homolog (yeast) TIMM22 29928 -1.17624 0.00099 1.44987 solute carrier
family 7 (cationic
amino acid
transporter, y+
220135_s_at system), member 9 SLC7A9 11136 -1.29039 0.00100 1.44117 cysteinyl-tRNA
1562436_at synthetase CARS 833 1.41701 0.01248 1.43535
212377_s_at notch 2 NOTCH2 4853 1.15701 0.00356 1.43125 low density
lipoprotein
receptor-related
1555353_at protein 1 LRP1 4035 -1.45686 0.00105 1.43059
1567612_at 1.53812 0.00212 1.41934
WW and C2
domain containing
213085_s_at 1 WWC1 23286 -1.18972 0.00436 1.41916
CD99 molecule-like
233825_s_at 2 CD99L2 83692 -1.45317 0.00141 1.40342 transforming,
acidic coiled-coil
containing protein
202289_s_at 2 TACC2 10579 -1.70922 0.00190 1.40130
241195_at -1.29793 0.00148 1.39516 ubiquitin specific
1554836_at peptidase 36 USP36 57602 -1.46443 0.00132 1.39461 fibroblast growth
231523_at factor 14 FGF14 2259 1.47170 0.01385 1.38601
237951_at -1.59212 0.00388 1.38352 cancer
susceptibility
1556630_at candidate 2 CASC2 255082 2.65579 0.00134 1.37840 mastermind-like
domain containing
205088_at 1 MAMLD1 10046 1.72281 0.00243 1.37578
ArfGAP with FG
206820_at repeats 2 AGFG2 3268 1.63078 0.00386 1.37420
236904_x_at tectorin alpha TECTA 7007 1.30218 0.00153 1.37255
KH homology
domain containing
l///sperm
autoantigenic KH DC1///SPA 80759///
205406_s_at protein 17 17 53340 1.14831 0.00244 1.37221
1566688_at -1.61839 0.01192 1.36163
WD repeat domain
224905_at 26 WDR26 80232 1.09443 0.02110 1.35964
5'-nucleotidase,
203939_at ecto (CD73) NT5E 4907 1.62231 0.00157 1.35136 v-yes-1 Yamaguchi
sarcoma viral
oncogene homolog
210917_at 1 YES1 7525 1.39640 0.00203 1.34953 tetratricopeptide
223924_at repeat domain 25 TTC25 83538 1.26789 0.00158 1.34871 family with
sequence similarity
225668_at 173, member B FAM 173B 134145 1.56259 0.00656 1.34007
Rhox homeobox
1552724_at family, member 1 RHOXF1 158800 1.23522 0.00427 1.33657
1560464_at -2.81865 0.00900 1.33456 Smad nuclear
interacting protein
219409_at 1 SN IP1 79753 1.09425 0.00369 1.33089
Cdk5 and Abl
226004_at enzyme substrate 2 CABLES2 81928 -1.15507 0.00224 1.33031 vasoactive
intestinal peptide
205946_at receptor 2 VIPR2 7434 4.42563 0.02221 1.33015 chromosome 21
open reading
1559028_at frame 15 C21orfl5 54094 3.55900 0.00610 1.32681 taste receptor,
1553556_at type 2, member 40 TAS2R40 259286 -1.71074 0.00186 1.32585 zinc finger protein
229532_at 502 ZNF502 91392 -1.51915 0.00588 1.32583
AH NAK
212992_at nucleoprotein 2 AH NAK2 113146 1.42042 0.00401 1.32088
220700_at -2.32883 0.01254 1.31913
TH l-like
22526 l_x_at (Drosophila) TH1L 51497 1.10252 0.00226 1.31693
1565897_at 1.64402 0.00183 1.31511 neuronal PAS
230412_at domain protein 3 N PAS3 64067 -2.20438 0.00984 1.31452
242299_at 1.97894 0.00385 1.31357 solute carrier
family 16, member
11
(monocarboxylic
acid transporter
241952_at 11) SLC16A11 162515 2.04828 0.00269 1.31228
ATPase, Na+/K+
transporting, beta
204311_at 2 polypeptide ATP1B2 482 -1.68742 0.00266 1.30824 zinc finger protein
42 homolog
243161_x_at (mouse) ZFP42 132625 1.48440 0.00308 1.30735
239371_at -1.83965 0.00508 1.30377 trypsin domain
231422_x_at containing 1 TYSND1 219743 1.65391 0.00199 1.30222 cyclic AM P- regulated
phosphoprotein,
1560018_at 21 kD ARPP21 10777 -3.09217 0.01328 1.30174
229907_at -1.17066 0.00203 1.30055 transmembrane
221951_at protein 80 TM EM80 283232 -1.32317 0.00212 1.29493 coatomer protein
complex, subunit
201359_at beta 1 COPB1 1315 -1.10713 0.01390 1.29291 sortilin-related
VPS10 domain
228720_at containing SORCS2 57537 -1.43918 0.00396 1.29220 receptor 2
236575_at 1.72262 0.00357 1 28940 chromodomain
helicase DNA
213965_s_at binding protein 5 CHD5 26038 -1.41266 0.00694 1 28764
DNA (cytosine-5-)- methyltransferase
220139_at 3-like DNMT3L 29947 2.13450 0.00215 1 28696
229786_at -1.23856 0.00257 1 28664
1563171_at -1.52720 0.00396 1 28368 microtubule
associated
monoxygenase,
calponin and LIM
domain containing
212472_at 2 MICAL2 9645 1.30562 0.00257 1 27655
220916_at -1.86086 0.00303 1 27506 synemin,
intermediate
212730_at filament protein SYNM 23336 1.76807 0.00318 1 27317
228335_at claudin 11 CLDN 11 5010 1.48033 0.00753 1 26358 receptor accessory
204364_s_at protein 1 REEP1 65055 1.78301 0.00243 1 26209
244318_at 1.50330 0.00830 1 25390 olfactory receptor,
family 1, subfamily
1567284_at J, member 4 OR1J4 26219 -1.40445 0.00532 1 25237 polypyrimidine
tract binding
22649 l_x_at protein 1 PTBP1 5725 -1.34696 0.00696 1 25157
236452_at 1.89284 0.00405 1 24846 family with
sequence similarity
1569139_s_at 53, member A FAM53A 152877 -1.39234 0.00298 1 24656 methionyl-tRNA
201475_x_at synthetase MARS 4141 1.10532 0.00256 1 24555
237961_at -1.47445 0.00736 1 24462
1001281
211111_at similar to HGC6.3 HGC6.3 24 -1.42627 0.00440 1 24444
236936_at 1.61122 0.00726 1 24058
236776_at -1.43639 0.00486 1 23652
221414_s_at defensin, beta 126 DEFB126 81623 -1.61306 0.00422 1 23542 acyl-CoA
synthetase
medium-chain
215432_at family member 1 ACSM1 116285 -2.16506 0.01484 1 23520
244222_at 2.93981 0.02337 1 22890
ATPase, Ca++
transporting, type
209935_at 2C, member 1 ATP2C1 27032 1.12696 0.00494 1 22694 Purkinje cell
241382_at protein 4 like 1 PCP4L1 654790 1.24472 0.01226 1 22261 leucine rich repeat
and sterile alpha
235449_at motif containing 1 LRSAM1 90678 -1.45291 0.01352 1 22237
216171_at 1.63818 0.00288 1 22209 chromosome 21
open reading
1566926_at frame 104 C21orfl04 54748 -4.50640 0.03991 1 21867
229372_at golgi transport 1A GOLT1A 127845 -2.40693 0.00987 1 21810 cyclin-dependent
kinase inhibitor 2A
(melanoma, pl6,
207039_at inhibits CDK4) CDKN2A 1029 1.69368 0.00297 1 21702 poly(A) binding
protein interacting
213754_s_at protein 1 PAIP1 10605 -1.11324 0.00360 1 21539
RNA binding
protein with
207836_s_at multiple splicing RBPMS 11030 -1.93174 0.00348 1 20599 calcium channel,
voltage- dependent, beta 1
206996_x_at subunit CACN B1 782 1.55675 0.00316 1 20568
155597 l_s_at F-box protein 28 FBX028 23219 1.23435 0.00773 1 20495 hypothetical
231942_at LOC643837 LOC643837 643837 1.35911 0.00502 1 20455
ATP-binding
cassette, subfamily C
1554918_a_a (CFTR/MRP),
t member 4 ABCC4 10257 1.31180 0.00358 1 20154
219181_at lipase, endothelial LIPG 9388 1.94947 0.00406 1 20143
237234_at cytohesin 2 CYTH2 9266 -1.10536 0.01037 1 20129
BEN domain
1558476_at containing 5 BEN D5 79656 -1.27986 0.00452 1 20067 islet amyloid
207062_at polypeptide IAPP 3375 1.83985 0.00321 1 20022 guanylate binding
223434_at protein 3 G BP3 2635 -1.49851 0.00330 1 19882
237146_at 2.43342 0.01009 1 19591
216764_at -1.81533 0.00374 1 19156 solute carrier
family 5
(sodium/glucose
cotransporter),
20777 l_at member 2 SLC5A2 6524 -2.54666 0.00509 1 18970
234550_at -1.39966 0.00393 1 18467
241804_at -1.12612 0.00375 1 18354 phosphodiesterase
2A, cGM P-
204134_at stimulated PDE2A 5138 1.67972 0.00636 1 18011 231262_at -1.61113 0.00366 1 17793
232877_at 1.28875 0.00706 1 17617
CUGBP, Elav-like
230497_at family member 5 CELF5 60680 -2.00475 0.00472 1 17614 chromosome 10
open reading
218390_s_at frame 84 C10orf84 63877 1.20429 0.00425 1 17024 dihydroxyacetone
kinase 2 homolog
218688_at (S. cerevisiae) DAK 26007 1.32721 0.00656 1 16963
234424_at -1.35253 0.00482 1 16744
240213_at -2.62614 0.03637 1 16655 transcription factor
236995_x_at EC TFEC 22797 -1.59447 0.00477 1 16422
1564729_at -1.89878 0.00612 1 16337 hypothetical
244151_at LOC285733 LOC285733 285733 1.51218 0.00418 1 16153
24446 l_at cytospin B CYTSB 92521 1.36779 0.00718 1 16061 purinergic receptor
P2X, ligand-gated
224069_x_at ion channel, 2 P2RX2 22953 -1.52671 0.00935 1 16010
1553840_a_a coiled-coil domain
t containing 149 CCDC149 91050 -1.75370 0.00673 1 15919
2'-5'- oligoadenylate
synthetase 3,
232666_at lOOkDa OAS3 4940 -1.76988 0.00450 1 15805
FERM domain
220819_at containing 1 FRMD1 79981 2.06307 0.02229 1 15727
1570087_at -1.12042 0.00542 1 15723
PDZ and LIM
203369_x_at domain 7 (enigma) PDLI M7 9260 2.53975 0.00782 1 15718
EP300 interacting
inhibitor of
211698_at differentiation 1 EID1 23741 -1.32344 0.00689 1 15662 lipoma H MG IC
fusion partner-like
228422_at 4 LHFPL4 375323 2.02745 0.01111 1 15597
210830_s_at paraoxonase 2 PON2 5445 -1.31328 0.00708 1 15569 collagen and
calcium binding
243805_at EGF domains 1 CCBE1 147372 -1.99625 0.00543 1 15558 tripartite motif-
204341_at containing 16 TRIM 16 10626 1.38093 0.01081 1 15246
221144_at -1.47733 0.00790 1 15017
SMAD family
member 5 opposite
220263_at strand SMAD50S 9597 -2.75571 0.00525 1 14512 methionyl-tRNA
213671_s_at synthetase MARS 4141 1.08911 0.00445 1 14507
214038_at chemokine (C-C CCL8 6355 -5.51473 0.03186 1 14491 motif) ligand 8
sema domain,
immunoglobulin
domain (Ig), short
basic domain,
secreted,
209730_ .at (semaphorin) 3F SEMA3F 6405 -1.25415 0.01068 1.14477 solute carrier
family 12
(potassium/chlorid
e transporters),
219874_ .at member 8 SLC12A8 84561 1.96616 0.00596 1.14405 glutamate
receptor,
ionotropic, N- methyl D-aspartate
229883_ .at 2D GRIN2D 2906 2.00884 0.00670 1.14221 family with
sequence similarity
230869_ .at 155, member A FAM 155A 728215 -1.80354 0.00447 1.14191 hypothetical
1562738_a_a protein LOC1001308 1001308
t LOC100130855 55 55 1.21080 0.00671 1.14154 inositol 1,4,5- trisphosphate 3-
232526_ .at kinase B ITPKB 3707 1.54071 0.01282 1.14130
GU LP, engulfment
adaptor PTB
domain containing
204237_ .at 1 G ULP1 51454 -2.47258 0.02905 1.14104
Sp2 transcription
211736_ .at factor SP2 6668 1.44320 0.00436 1.13920 solute carrier
family 38, member
242330_ .at 9 SLC38A9 153129 -1.55482 0.00875 1.13833
ADP-ribosylation
factor guanine
nucleotide- exchange factor
l(brefeldin A-
216266_ .s_at inhibited) ARFGEF1 10565 1.13235 0.00721 1.13124 phosphodiesterase
240088_ .at 5A, cGM P-specific PDE5A 8654 -1.27941 0.00830 1.13104 transferrin
receptor (p90,
237214_ .at CD71) TFRC 7037 1.45701 0.00713 1.13086 solute carrier
family 6 (amino
acid transporter),
219795_ .at member 14 SLC6A14 11254 1.32739 0.00704 1.13077
Ral GTPase
activating protein,
235524_ .at alpha subunit 1 RALGAPA1 253959 -1.54242 0.00730 1.13030 (catalytic) uncoupling protein
2 (mitochondrial,
208998_at proton carrier) UCP2 7351 -1.25921 0.00527 1.12621
233875_at -2.51411 0.01963 1.12396 retinitis
pigmentosa
207624_s_at GTPase regulator RPGR 6103 1.32065 0.00475 1.12251 zinc finger protein
64 homolog
219536_s_at (mouse) ZFP64 55734 -1.39309 0.01389 1.12159 hypothetical
LOC442497///solut
e carrier family 3
(activators of
dibasic and neutral
amino acid
transport), LOC442497// 442497//
200924_s_at member 2 /SLC3A2 /6520 1.22155 0.00553 1.12050
SLIT and NTRK-like
232636_at family, member 4 SLITRK4 139065 1.63475 0.00668 1.11682
239625_at 1.79184 0.00529 1.11595
1569172_a_a hypothetical
t LOC441005 LOC441005 441005 -1.30764 0.01074 1.11542
C-type lectin
domain family 2,
1556209_at member B CLEC2B 9976 -1.75794 0.00901 1.11513 nucleoporin
232598_at 210kDa-like NU P210L 91181 1.74042 0.01680 1.11449 zinc finger protein
216482_x_at 79 ZNF79 7633 1.44178 0.00666 1.11407 microf ibrillar- associated protein
210492_at 3-like MFAP3L 9848 -1.47002 0.00740 1.11354
1556263_s_at -2.03305 0.00732 1.11336
214480_at ets variant 3 ETV3 2117 2.71652 0.00919 1.11327 coiled-coil domain
206016_at containing 22 CCDC22 28952 1.08973 0.03729 1.11283
B melanoma
1555369_at antigen BAGE 574 2.29056 0.00562 1.11263 zinc finger CCCH- type containing
231899_at 12C ZC3H12C 85463 1.36795 0.00910 1.11148 regulator of
telomere
elongation helicase
213829_x_at 1 RTEL1 51750 -1.22308 0.00589 1.11081 growth hormone
2///growth
hormone
l///chorionic
somatomammotro
pin hormone-like
..///chorionic
somatomammotro
pin hormone
2///chorionic
somatomammotro 2689///2
pin hormone 1 GH2///GH1// 688///14
(placental /CSH L1///CS 44///144
208068_x_at lactogen) H2///CSH1 3///1442 -1.38150 0.00856 1.11061
TSC22 domain
215111_s_at family, member 1 TSC22D1 8848 1.64307 0.01092 1.10938
240133_x_at 1.28869 0.00517 1.10858
238223_at 1.39984 0.00859 1.10836 neutral
sphingomyelinase
(N-SMase)
activation
232148_at associated factor NSMAF 8439 1.24657 0.00757 1.10794 amyotrophic
lateral sclerosis 2
(juvenile)
chromosome
1556757_a_a region, candidate
t 11 ALS2CR11 151254 -1.62714 0.01042 1.10583
1561573_at -1.84998 0.00670 1.10434
CASK interacting
1552689_at protein 1 CASKIN 1 57524 -1.26756 0.00787 1.10372 nucleolar protein 7,
20288 l_x_at 27kDa NOL7 51406 1.31964 0.00604 1.10243 v-src sarcoma
(Schmidt-Ruppin A- 2) viral oncogene
221281_at homolog (avian) SRC 6714 1.47641 0.00564 1.10161
Table 2. Probesets obtained from cells cultured in BCG for six hours. t-test pvalue probe set desc symbol entrez FC (SS/LS) (all samples) Weight
56.2718
230111_at 16.67453 0.36902 4 similar to DnaJ
homolog subfamily B 10028692 37.5659
230953_at member 3 LOC100286922 2 1.334661 0.368435 4
19.0065
243123_at 1.255 0.352843 8 myeloid/lymphoid or 9.08814
211790_s_at mixed-lineage MLL2 8085 6.072978 0.363616 3 leukemia 2
3.05310
243002_at 1.875467 0.145121 8 cytochrome P450,
family 2, subfamily C, 2.73073
208126_s_at polypeptide 18 CYP2C18 1562 2.16154 9.54E-06 2 mannosidase, alpha, 2.39302
203668_at class 2C, member 1 MAN2C1 4123 -1.25461 7.77E-05 7 aarF domain 2.22040
221893_s_at containing kinase 2 ADCK2 90956 -1.1977 0.004217 9
2.12052
230477_at 1.616841 0.002083 8 leucine-rich, glioma 2.10658
206349_at inactivated 1 LGI1 9211 2.277778 0.00098 3 adenomatous 2.03204
215310_at polyposis coli APC 324 -1.33461 0.000112 7 dynein, axonemal, 1.97693
1567377_at heavy chain 1 DNAH1 25981 2.205109 0.019565 2 forkhead-associated
(FHA)
phosphopeptide 1.95581
1557771_at binding domain 1 FHAD1 114827 -1.94532 0.005179 2
1.95320
241737_x_at -1.80352 0.000341 3
1.94929
229593_at -1.24013 0.000141 3 general transcription
factor MIC,
polypeptide 3, 1.92866
1569058_at 102kDa GTF3C3 9330 -1.8138 0.000263 6 thyrotrophic 1.92008
210167_s_at embryonic factor TEF 7008 3.444826 0.121801 5 motor neuron and
pancreas homeobox 1.91586
214614_at 1 MNX1 3110 -2.30187 0.000485 4 chromosome X open
221121_at reading frame 48 CXorf48 54967 1.681961 0.00036 1.90792 zinc finger protein 1.89768
1558942_at 765 ZNF765 91661 -1.18237 0.004579 5 hypothetical
242305_at LOC645513 LOC645513 645513 -1.39227 0.003968 1.88525
1.87186
243649_at F-box protein 7 FBX07 25793 -1.34232 0.000275 7 forkhead box C2
(MFH-1,
mesenchyme 1.86863
239058_at forkhead 1) FOXC2 2303 -1.92486 0.000121 4
1.84398
221205_at 3.929315 0.258756 3
1.84066
240601_at -1.32475 0.000915 7
ArfGAP with FG 1.83591
20682 l_x_at repeats 2 AG FG2 3268 1.6855 0.006638 5
232439_at -1.65386 0.000185 1.82287 2
1.81776
243113_at -1.68195 0.000929 6
1.80167
234333_at KIAA2022 KIAA2022 340533 2.176055 0.000212 4
1.78835
215643_at 1.24313 0.000806 7 family with sequence
similarity 184, 1.78791
233802_at member B FAM 184B 27146 1.522901 0.001137 9
1.78104
239551_at -1.70584 0.000539 7
1.78053
23843 l_at -1.23656 0.001954 7
Rho GTPase 1.75691
217153_at activating protein 1 ARHGAP1 392 1.551011 0.000738 2
N EDD4 binding 1.74988
214753_at protein 2-like 2 N4BP2L2 10443 -1.23048 0.001022 6
237628_at -1.48825 0.000605 1.7482 nuclear receptor
subfamily 1, group 1, 1.74596
1570188_at member 3 N R1I3 9970 3.213365 0.000507 5 kelch-like 14 1.74380
1554942_a_at (Drosophila) KLH L14 57565 1.489026 0.003329 5 polymerase (DNA
203366_at directed), gamma POLG 5428 1.060533 0.004347 1.7307
1.71732
1559011_at FU 13773 FU 13773 246318 -1.59791 0.001469 9
1.71691
242362_at -1.20117 0.015895 4 neuroblastoma
breakpoint family,
member
10///neuroblastoma
breakpoint family,
member
16///neuroblastoma
breakpoint family,
member
24///neuroblastoma
breakpoint family,
member
8///hypothetical 10013240
LOC440670///neuro 6///7289
blastoma breakpoint 36///728
family, member 912///72
9///neuroblastoma NBPF10///N BP 8841///4
breakpoint family, F16///NBPF24/ 40670///
member //N BPF8///AE0 400818//
ll///KIAA1245///ne 1///N BPF9///N /200030/
uroblastoma BPF11///KIAA1 //149013
breakpoint family, 245///NBPF3// ///S4224/
member /N BPF1///N BP //55672// 1.71506
1562062_at 3///neuroblastoma F14 /25832 -1.10967 0.000652 5 breakpoint family,
member
..///neuroblastoma
breakpoint family,
member 14
1.71461
24378 l_at -2.29679 0.005724 3 nitric oxide synthase
1 (neuronal) adaptor
215153_at protein NOS1AP 9722 2.35 0.213242 1.71268
1.70804
1570347_at MAX-like protein X M LX 6945 1.275933 0.004928 8
1.69813
22426 l_at -1.34196 0.001787 4 chromosome 7 open 1.68612
210109_at reading frame 54 C7orf54 27099 -1.26553 0.000264 8 piccolo (presynaptic 1.68030
217096_at cytomatrix protein) PCLO 27445 1.951872 0.004437 6
23065 l_at -1.38041 0.001308 1.67924 contactin associated 1.67855
232388_at protein-like 4 CNTNAP4 85445 1.347488 0.000933 4 rhophilin, Rho
GTPase binding 1.67119
227196_at protein 2 RH PN2 85415 -1.59266 0.001158 6
1.65940
244778_x_at -1.35799 0.001197 3
1.65551
1562673_at -1.36591 0.000337 6 pleckstrin and Sec7 1.63546
203317_at domain containing 4 PSD4 23550 -1.32535 0.001104 7
238242_at 1.263637 0.007532 1.63338 calcyon neuron- specific vesicular 1.63185
219896_at protein CALY 50632 1.636609 0.000524 1
1.63156
244236_at -1.42066 0.001286 6
1.62905
241867_at -1.32592 0.000405 8 polymerase (RNA) II
(DNA directed) 1.62294
214144_at polypeptide D POLR2D 5433 -1.27863 0.00306 7 calcium channel,
voltage-dependent, 1.62209
207693_at beta 4 subunit CACN B4 785 1.47335 0.078504 8 steroid 5 alpha- 1.62151
218800_at reductase 3 SRD5A3 79644 -1.96843 0.004858 5 bromodomain 1.61517
239000_at containing 4 BRD4 23476 1.431894 0.000488 1 olfactory receptor,
family 1, subfamily A, 1.61356
221388_at member 1 OR1A1 8383 -2.13165 0.000943 9
1.61284
236370_at -1.37967 0.000581 8 1.61219
244643_at -1.76874 0.002247 3
1.60877
1568866_at -1.38499 0.005108 1
G l to S phase 1.60721
205541_s_at transition 2 GSPT2 23708 -1.30825 0.002054 4
GI NS complex
subunit 4 (Sld5 1.59730
235029_at homolog) G INS4 84296 -1.39593 0.022773 2 farnesyltransferase, 1.59181
1568865_at CAAX box, beta FNTB 2342 -1.5313 0.003305 8 solute carrier family
7 (amino acid
transporter, L-type), 1.57662
202752_x_at member 8 SLC7A8 23428 1.750838 0.001832 3 leucine rich repeat 1.57381
215173_at containing 50 LRRC50 123872 1.320419 0.003977 3 solute carrier family
7 (cationic amino
acid transporter, y+ 1.57210
230658_at system), member 2 SLC7A2 6542 2.920404 0.002217 5 retinoblastoma 1.56534
227635_at binding protein 6 RBBP6 5930 -1.3165 0.000739 4
NOBOX oogenesis 1.56243
234519_at homeobox NOBOX 135935 -2.00936 0.001256 2
1.56152
220785_at urotensin 2 UTS2 10911 2.071276 0.000557 6 zinc finger protein 1.55713
232247_at 502 ZNF502 91392 -1.6538 0.004641 6
LAG1 homolog,
235463_s_at ceramide synthase 6 LASS6 253782 -1.24712 0.009521 1.55677
1.54631
207424_at myogenic factor 5 MYF5 4617 3.381617 0.005094 2
1.54605
216664_at -3.16716 0.006541 4 solute carrier family
7 (cationic amino
acid transporter, y+ 1.54582
230597_at system), member 3 SLC7A3 84889 1.638726 0.000786 1
1.54018
1564407_a_at 1.572438 0.000868 9 leucine rich repeat 1001307 1.53737
238214_at containing 69 LRRC69 42 -1.46876 0.008114 1
1.53357
235786_at -1.18441 0.000643 8
1.53317
214643_x_at bridging integrator 1 BIN 1 274 1.238992 0.004092 3 cytochrome b5 1.53021
238280_at reductase-like CYB5RL 606495 3.241643 0.006317 4
1.51798
226392_at -1.18039 0.000653 9 zinc finger protein 1.51429
214761_at 423 ZNF423 23090 -1.6839 0.00069 4
219523_s_at odz, odd Oz/ten-m ODZ3 55714 3.775272 0.004949 1.51360 homolog 3 1
(Drosophila)
1.51091
242658_at -1.33813 0.001346 8 similar to
hCG2039164///hypo LOC728683///L 728683// 1.50818
217158_at thetical LOC442421 OC442421 /442421 4.040737 0.000616 8
OTU domain 1.50812
233933_s_at containing 5 OTUD5 55593 -1.12951 0.004759 7 zona pellucida 1.50798
20702 l_at binding protein ZPBP 11055 -1.37051 0.001764 5 zinc finger protein 1.50343
229328_at 540 ZNF540 163255 1.437183 0.00383 2 cyclic nucleotide
gated channel alpha 1.50298
206417_at 1 CNGA1 1259 1.637536 0.002156 3 protein tyrosine
phosphatase, 1.50106
200637_s_at receptor type, F PTPRF 5792 1.999961 0.001649 5
1.49884
240032_at 1.7664 0.00087 9
1.49626
241106_at -1.5559 0.001327 5 outer dense fiber of 1.49440
237420_at sperm tails 2-1 ike ODF2L 57489 -1.48701 0.00102 9
1.49115
239409_at -1.29709 0.006381 8 transcription
elongation factor A 1.48986
1566208_at (Sll), 1 TCEA1 6917 2.769474 0.001006 7 calpain 1, (mu/l) 1.48947
232012_at large subunit CAPN1 823 -1.11729 0.010462 4 angel homolog 2 1.48903
217630_at (Drosophila) ANGEL2 90806 -1.44806 0.009007 4 autism susceptibility 1.48743
243364_at candidate 2 AUTS2 26053 -1.40696 0.000666 7
241965_at -1.18529 0.000858 1.47904
1.47876
1560680_at -1.40022 0.002422 4
ATPase,
aminophospholipid
transporter, class 1, 1.46791
239457_at type 8B, member 3 ATP8B3 148229 1.849828 0.002412 4
1.46402
244512_at -1.73272 0.002924 5 matrix 1.45329
220783_at metallopeptidase 27 MMP27 64066 1.767559 0.001099 4
238382_x_at -1.65431 0.005369 1.45038 unkempt homolog 1.44368
229908_s_at (Drosophila)-like UN KL 64718 -1.09166 0.004685 6
1.43937
237874_at -2.02803 0.001181 4 chromosome 17 1.43766
238980_x_at open reading frame C17orf56 146705 -1.25777 0.004546 6 56
TAF15 RNA
polymerase II, TATA
box binding protein
(TBP)-associated 1.43372
227884_at factor, 68kDa TAF15 8148 -1.3817 0.003442 4 chromosome 12
open reading frame 1.43275
219022_at 43 C12orf43 64897 -1.15441 0.016397 6
1.43009
1569818_at -2.14744 0.016419 5
1.42839
24269 l_at -1.32023 0.013201 9 hypothetical protein
1556900_at LOC149773 LOC149773 149773 1.359246 0.003074 1.42456 hypothetical 10023320 1.42403
241947_at LOC100233209 LOC100233209 9 -1.37465 0.003607 8 developmental
pluripotency 1.42044
241550_at associated 5 DPPA5 340168 3.093511 0.024178 9 hypothetical protein 1.41999
1560744_at LOC283028 LOC283028 283028 -2.77011 0.0011 2
1.41511
23406 l_at 1.510658 0.002528 8 retinol
dehydrogenase 13 1.41265
227360_at (all-trans/9-cis) RDH 13 112724 1.27247 0.103586 8
1.40910
1559397_s_at proline rich 14 PRR14 78994 1.401074 0.001207 7
ATP-binding
cassette, sub-family
204719_at A (ABC1), member 8 ABCA8 10351 1.365137 0.002457 1.40549
1.40405
230590_at -1.23612 0.001798 6
1.39949
24329 l_at -1.34972 0.003922 3
1.39885
237818_at 2.05061 0.006164 4
1.39491
237611_at 1.326846 0.00186 2 solute carrier family 1.39403
238499_at 45, member 3 SLC45A3 85414 1.455486 0.004539 7
1.38597
216538_at -1.36406 0.004141 9 cullin-associated and
neddylation- 1.38468
207483_s_at dissociated 1 CAND1 55832 -1.07861 0.03302 9 signal peptide 1.38360
1566897_at peptidase 3 SPPL3 121665 -1.39737 0.00841 4 fucosyltransferase 6
(alpha (1,3) 1.38255
210399_x_at fucosyltransferase) FUT6 2528 1.203676 0.034151 8
CAP-GLY domain 1.37850
242287_at containing linker CLIPl 6249 -1.16782 0.0013 2 protein 1
zinc finger protein 1.37822
1562789_at 229 ZNF229 7772 1.547278 0.006871 5 zinc finger, MYN D- 1.37793
241793_at type containing 17 ZMYN D17 118490 -1.18541 0.00278 1 transcription factor 1.37652
235925_at 12 TCF12 6938 -1.3328 0.001467 7 tubulin tyrosine
ligase-like family, 1.37524
219882_at member 7 TTLL7 79739 1.636009 0.023119 2
Sep (0- phosphoserine)
tRNA:Sec
(selenocysteine)
1569634_at tRNA synthase SEPSECS 51091 1.659369 0.014485 1.37491 phosphatidylinositol 1.37323
1559479_at 4-kinase type 2 beta PI4K2B 55300 -1.41126 0.001358 5
1.37270
238302_at 1.855888 0.00203 8
1.37066
1554155_at microcephalin 1 MCPH 1 79648 -1.2039 0.034163 8 immunoglobulin
heavy variable 4-
31///immunoglobuli
n heavy variable
group///immunoglob
ulin heavy constant
mu///immunoglobuli
n heavy constant
gamma 3 (G3m
marker)///immunogl
obulin heavy
constant gamma 1
(Glm
marker)///immunogl
obulin heavy 28396///
constant IGHV4- 3509///3
delta///immunoglob 31///IGHV@// 507///35
ulin heavy constant /IGHM///IGHG 02///350
alpha 3///IG HG1///I 0///3495/
l///immunoglobulin G HD///IG HA1/ //3493/// 1.36871
234419_x_at heavy locus //IGH@ 3492 1.472449 0.091122 6 steroidogenic acute 1.36787
204548_at regulatory protein STAR 6770 1.486064 0.004337 3 transmembrane 1.36758
226589_at protein 192 TMEM192 201931 -1.18323 0.019329 1
1.36476
237213_at 1.196313 0.01426 3
DiGeorge syndrome
critical region gene
241748_x_at 14 DGCR14 8220 1.398284 0.001269 1.36439 eukaryotic
translation initiation 1.36369
1569408_at factor 2C, 4 EIF2C4 192670 -1.44678 0.001903 9 potassium channel
tetramerisation 1.35900
226245_at domain containing 1 KCTD1 284252 1.26459 0.002741 5
U BX domain protein 1.35670
238903_at 2B U BXN2B 137886 -1.18594 0.013434 3
DEAH (Asp-Glu-Ala- Asp/His) box
213420_at polypeptide 57 DHX57 90957 -1.30912 0.009354 1.35579
239948_at nucleoporin 153kDa NU P153 9972 -1.38566 0.00998 1.35525 sperm acrosome 1.35357
220982_s_at associated 1 SPACA1 81833 -1.72823 0.003026 4 peptidyl prolyl
isomerase A
(cyclophilin A)-like
4C///peptidylprolyl
isomerase A
(cyclophilin A)-like
4B///peptidylprolyl
isomerase A
(cyclophilin A)-like 653598//
4G///peptidylprolyl /653505/
isomerase A PPIAL4C///PPI //644591
(cyclophilin A)-like AL4B///PPIAL4 ///16402 1.35159
217136_at 4A G///PPIAL4A 2 -1.49907 0.001662 9
1.34889
239308_at 1.34206 0.021455 9
SEC14-like 3 (S. 1.34672
241221_at cerevisiae) SEC14L3 266629 1.791831 0.012465 5
1.34209
241391_at -1.34926 0.001907 1
1.33939
217164_at -1.45222 0.001319 1
1.33934
242337_at -1.13401 0.001454 4
1.33916
242910_x_at -1.46591 0.010197 9
1.33848
240829_at -1.70481 0.014828 3
I NS-IGF2
readthrough
transcript///insulin- like growth factor 2 INS- 723961// 1.33185
202409_at (somatomedin A) IGF2///IGF2 /3481 1.706509 0.006601 1 capping protein
(actin filament)
muscle Z-line, alpha 1.33121
1569450_at 2 CAPZA2 830 -1.32326 0.005123 7 serine/arginine 1.33006
237828_at repetitive matrix 4 SRRM4 84530 3.104426 0.004298 1 nuclear factor
(erythroid-derived 1.32855
1567014_s_at 2)-like 2 NFE2L2 4780 -1.19473 0.022715 5 discs, large homolog 1.32477
230229_at 1 (Drosophila) DLG1 1739 -1.24005 0.002779 4 defensin, beta
103B///defensin, DEFB103B///D 414325//
224239_at beta 103A EFB103A /55894 1.35669 0.005283 1.3243
CDK5 regulatory
subunit associated 1.32251
237418_at protein 2 CDK5RAP2 55755 -1.42631 0.001678 5
1.32131
244853_at -1.38368 0.003466 4 destrin (actin
depolymerizing 1.31926
230933_at factor) DSTN 11034 1.218269 0.003671 1
1.30870
1557805_at -1.17663 0.001512 4 coiled-coil domain 1.30830
1563090_at containing 33 CCDC33 80125 1.335658 0.005682 9
1.30757
236168_at -1.27405 0.010582 1
1.30735
239434_at -1.41489 0.001838 8
1.30653
233832_at -1.20322 0.095804 3
1.30498
238260_at 1.287431 0.004131 5
1.30497
1565697_at -2.0872 0.004084 6
242901_at 1.317407 0.01697 1.30462 collagen, type VI II, 1.30349
52651_at alpha 2 COL8A2 1296 -1.27528 0.0067 4 cytochrome P450,
family 17, subfamily 1.30254
1562573_at A, polypeptide 1 CYP17A1 1586 -2.30623 0.008413 9 prenyl (decaprenyl)
diphosphate 1.30170
219307_at synthase, subunit 2 PDSS2 57107 -1.33057 0.008222 7
FERM, RhoGEF
(ARHGEF) and
pleckstrin domain
protein 1
(chondrocyte- 1.30073
227996_at derived) FARP1 10160 -1.44724 0.012578 4
1.30053
240109_at -1.4435 0.004396 6
CTAGE family, 1.29782
204055_s_at member 5 CTAGE 5 4253 -1.32139 0.001514 8
CCR4-NOT
transcription 1.29600
20086 l_at complex, subunit 1 CNOT1 23019 -1.12372 0.002926 8 sprouty-related,
EVH1 domain
212466_at containing 2 SPRED2 200734 1.371168 0.008451 1.29231 primary ciliary 1.29221
237152_at dyskinesia protein 1 PCDP1 200373 1.87254 0.033579 6
M-phase 1.29140
240942_at phosphoprotein 8 MPHOSPH8 54737 -1.40189 0.006081 2 l-acylglycerol-3- phosphate 0- acyltransferase 6
(lysophosphatidic
acid acyltransferase, 1.29109
236743_at zeta) AGPAT6 137964 1.554833 0.004018 7 family with sequence
similarity 165, 1.29102
1554430_at member B FAM 165B 54065 -1.26461 0.003812 5 synapse defective 1,
Rho GTPase,
homolog 1 (C.
216272_x_at elegans) SYDE1 85360 1.167436 0.013171 1.28967 transmembrane BAX
inhibitor motif 1.28864
219206_x_at containing 4 TMBIM4 51643 -1.06172 0.012975 9
RCD1 required for
cell differentiation 1 1.28635
213903_s_at homolog (S. pombe) RQCD1 9125 -1.3079 0.003914 1 guanine nucleotide
binding protein (G
protein), alpha
activating activity 1.28618
204763_s_at polypeptide 0 G NAOl 2775 1.339524 0.007663 2 leucine-rich repeats
and immunoglobulin- 1.28116
242164_s_at like domains 2 LRIG2 9860 1.374015 0.001625 7
1556222_at septin 7-like SEPT7L 285961 -1.09091 0.013716 1.27678 pregnancy specific
beta-l-glycoprotein 1.27632
239910_at 6 PSG6 5675 2.276468 0.008097 3
1.27529
240276_at 1.581116 0.002294 5
AH NAK
1558378_a_at nucleoprotein 2 AH NAK2 113146 2.38388 0.018136 1.27412 zinc finger protein 1.27330
229532_at 502 ZNF502 91392 -1.58751 0.00569 9 tyrosine 3- monooxygenase/tryp
tophan 5- monooxygenase
activation protein,
epsilon polypeptide 1.27242
240979_at pseudogene LOC284100 284100 1.446502 0.003526 8 hypothetical protein 1002873 1.27195
1570566_at LOC100287312 LOC100287312 12 -1.30787 0.003446 1 triggering receptor
expressed on
myeloid cells-like 2 1.26996
1567624_at pseudogene 1 TREML2P1 221438 2.765653 0.009531 6
1.26909
1565705_x_at -1.39303 0.003485 5
1.26847
208434_at -2.89704 0.001953 1 1.26843
1566843_at period 4 pseudogene PER4 168741 -2.47369 0.011892 8 choline/ethanolamin
e
phosphotransferase 1.26827
1561884_at 1 CEPT1 10390 -1.28504 0.00465 5 peroxisomal
228225_at biogenesis factor 2 PEX2 5828 -1.16091 0.005325 1.26529
Sadl and UNC84
234504_at domain containing 5 SU N5 140732 2.578577 0.018087 1.26488 nescient helix loop 1.26461
215228_at helix 2 N H LH2 4808 1.385055 0.006229 3
1.26356
1560263_at -3.05726 0.037787 9
1.26169
1566768_at -1.8135 0.008244 5
TIA1 cytotoxic
granule-associated
RNA binding protein1.25910
217500_at like 1 TIAL1 7073 -2.47261 0.011816 9 hypothetical protein 1.25844
234016_at LOC90499 LOC90499 90499 2.007879 0.002598 7
1.25784
234649_at -1.44433 0.00837 5
1.25781
1566001_at -1.42091 0.005572 7
1.25764
1560347_at -2.10698 0.01088 7 zinc finger protein 1.25686
203604_at 516 ZNF516 9658 -1.47149 0.002546 3
1.25675
233440_at -1.38415 0.005802 2 caspase recruitment
domain family, 1.25389
1555309_a_at member 14 CARD14 79092 1.799933 0.002117 2
1.25360
216052_x_at artemin ARTN 9048 1.242474 0.0099 1
1.25339
1561592_at -3.54561 0.013278 5
GrpE-like 2,
mitochondrial (E. 1.25328
238427_at coli) GRPEL2 134266 1.185824 0.005695 4
10013042 1.25250
236059_at IGYY565 LOC100130428 8 -1.1649 0.004401 2
236443_at -1.46992 0.025228 1.25231
1.25202
241891_at -1.30596 0.001978 6 chorionic
somatomammotropi
n hormone 1 1.25145
208357_x_at (placental lactogen) CSH1 1442 -4.70779 0.030769 1 solute carrier organic
anion transporter 1.24968
211557_x_at family, member 2B1 SLC02B1 11309 1.517841 0.012234 9 testis-specific
transcript, Y-linked
8B (non-protein
coding)///testis- specific transcript, Y- 10010111
linked 8 (non-protein TTTY8B///TTTY 8///8467 1.24886
224142_s_at coding) 8 3 -2.39007 0.0065 5
1.24810
240503_at -1.59824 0.002302 3
1.24791
233515_at -1.32106 0.003471 1
1.24553
242374_at -1.19509 0.006361 1
1.24461
232030_at KIAA1632 KIAA1632 57724 -1.28442 0.002568 8 eukaryotic
translation initiation 1.24366
236700_at factor 3, subunit C EIF3C 8663 -1.32247 0.012925 5
1.24202
243235_at 2.255506 0.012564 2 similar to
hCG1815675///RAD9
homolog A (S. LOC100130987 10013098 1.23928
1562022_s_at pombe) ///RAD9A 7///5883 1.130282 0.025976 1
H ERV-H LTR- 1.23891
234673_at associating 2 H H LA2 11148 1.755232 0.007554 7
1.23836
1566115_at -1.6751 0.009542 2
G protein-coupled
1553316_at receptor 82 G PR82 27197 -1.81941 0.006631 1.23729
1.23727
205758_at CD8a molecule CD8A 925 1.295288 0.027224 9 ankyrin repeat and
KH domain 1.23616
229457_at containing 1 AN KH D1 54882 -1.16879 0.004519 5
1.23600
241429_at -1.25189 0.003661 3 chromosome 19
open reading frame 1.23437
226379_s_at 25 C19orf25 148223 1.149714 0.006316 8
1.23116
240630_at 1.229182 0.002069 9 polymerase (RNA) II
(DNA directed)
polypeptide J4, 1.22868
240014_at pseudogene POLR2J4 84820 -1.8722 0.013843 1 pyridoxal-dependent
decarboxylase
domain containing
2///pyridoxal- dependent
decarboxylase PDXDC2///PDX 283970// 1.22837
232288_at domain containing 1 DC1 /23042 -1.29693 0.003029 4
1556061_at ribonuclease P/MRP RPP30 10556 -1.26182 0.014891 1.22832 30kDa subunit 8
1.22817
239735_at -1.3791 0.0042 6
U PF3 regulator of
nonsense transcripts 1.22761
206958_s_at homolog A (yeast) UPF3A 65110 -1.14649 0.015753 8
1.22686
1561408_at 1.770413 0.004712 5
1.22667
230415_at -1.62347 0.003057 5 coatomer protein
complex, subunit 1.22254
1559862_at alpha CO PA 1314 -1.67824 0.004186 3
DBF4 homolog B (S. 1.22073
20666 l_at cerevisiae) DBF4B 80174 -3.43003 0.008932 8
1.22037
244207_at 1.403219 0.002728 1 unc-5 homolog C (C. 1.22030
240958_at elegans) UNC5C 8633 1.669237 0.00354 1 ribosomal protein 1.22014
216566_at L14 RPL14 9045 1.783249 0.002446 2 zinc finger protein 1.21944
20429 l_at 518A ZNF518A 9849 -1.18391 0.016808 7 phospholipase A2, 1.21771
206311_s_at group I B (pancreas) PLA2G 1B 5319 1.600514 0.00207 5
1.21671
240248_at -1.30644 0.007253 1 gamma-aminobutyric
acid (GABA) A 1.21623
229724_at receptor, beta 3 GABRB3 2562 2.131848 0.002002 3 similar to anaphase
promoting complex 10013389 1.21570
230037_at subunit 1 LOC100133898 8 1.460238 0.00281 6 aminolevulinate, 1.21472
216568_x_at delta-, synthase 2 ALAS2 212 -1.77035 0.007232 7
1.21416
240370_at -1.59037 0.006988 4
PDS5, regulator of
cohesion
maintenance,
homolog B (S. 1.21368
215888_at cerevisiae) PDS5B 23047 -1.21394 0.002396 5
COP9 constitutive
photomorphogenic
homolog subunit 8 1.21280
214260_at (Arabidopsis) COPS8 10920 -1.14083 0.0032 5 oculocerebrorenal
208316_s_at syndrome of Lowe OCRL 4952 1.356575 0.003378 1.21242 hypothetical 1.21223
237116_at LOC646903 LOC646903 646903 1.453966 0.020077 9 dual specificity 1.21070
224832_at phosphatase 16 DUSP16 80824 1.367793 0.004012 1 solute carrier family 1.21063
232551_at 26, member 6 SLC26A6 65010 -1.25206 0.005906 6 1.20981
232852_at 1.309219 0.006872 7 hypothetical 10013270 1.20925
1569898_a_at LOC100132707 LOC100132707 7 -1.18097 0.005452 9
ABO blood group
(transferase A, alpha
1-3-N- acetylgalactosaminyl
transferase;
transferase B, alpha
1-3- galactosyltransferase
216929_x_at ) ABO 28 1.22743 0.005889 1.20915 hairy and enhancer 1.20845
216674_at of split 2 (Drosophila) HES2 54626 -2.10438 0.014387 4 hypothetical 1.20843
1562223_at LOC642426 LOC642426 642426 2.007501 0.008085 1 hypothetical protein 10028850 1.20770
236092_at LOC100288507 LOC100288507 7 -1.18722 0.103122 5
1.20430
233113_at -2.46915 0.003863 2
1.20405
241630_at -1.21865 0.009866 2 mitogen-activated
protein kinase- activated protein 1.20403
215050_x_at kinase 2 MAPKAPK2 9261 2.204511 0.006103 4
1.20325
241497_at -1.504 0.005229 5
1.20221
243450_at -1.31101 0.009845 3 chibby homolog 3 1.20072
241712_at (Drosophila) CBY3 646019 -1.22228 0.003334 6
1.19973
230809_at -3.13865 0.016255 7
Ca++-dependent
233950_at secretion activator CAD PS 8618 1.769634 0.005742 1.19865
1.19751
1566979_at 1.444414 0.002384 3 calcium binding and 1.19747
238560_at coiled-coil domain 2 CALCOC02 10241 -1.28566 0.002239 8
1.19741
231332_at -1.26876 0.00474 3 family with sequence
similarity 83, 1.19542
238741_at member A FAM83A 84985 2.578323 0.011406 8 flavin containing
monooxygenase 2 1.19442
211726_s_at (non-functional) FM02 2327 1.563743 0.004062 4
U DP-N-acetyl-alpha-
Π- galactosamine:polyp
eptide N- 1.19418
236536_at acetylgalactosaminyl GALNT13 114805 1.802469 0.003342 4 transferase 13
(GalNAc-T13)
acetyl-CoA 1.19416
214358_at carboxylase alpha ACACA 31 -1.21445 0.067674 7
G protein-coupled
receptor 37
(endothelin receptor
214586_at type B-like) G PR37 2861 2.433164 0.008704 1.19339
1.19253
243034_at -1.64557 0.038523 8
1562800_at 2.320423 0.004567 1.1907 interferon gamma 1.19019
242903_at receptor 1 I FNGR1 3459 -1.33916 0.014688 9
1.19006
244843_x_at 1.491583 0.015517 5
1.18810
241338_at 1.419004 0.007807 8 establishment of
cohesion 1 homolog 1.18704
235588_at 2 (S. cerevisiae) ESC02 157570 -1.47918 0.006544 5 family with sequence
similarity 57,
22778 l_x_at member B FAM57B 83723 1.951628 0.006679 1.18538 chromosome 6 open 1.18532
220904_at reading frame 208 C6orf208 80069 1.46154 0.009195 6 choline/ethanolamin
e
phosphotransferase 1.18526
219375_at 1 CEPT1 10390 -1.10959 0.03646 4 ubiquitin specific 1.18421
1563497_at peptidase 25 USP25 29761 -1.33498 0.013634 4
RAN binding protein 1.18283
210120_s_at 3 RAN BP3 8498 -1.16488 0.008163 8
DKFZP564C152 1.18068
1557398_at protein DKFZP564C152 26120 -3.16879 0.028626 2 myelin expression 1.18028
22277 l_s_at factor 2 MYEF2 50804 -1.31658 0.002932 6 hydroxysteroid (17- beta) dehydrogenase 1.17964
1559518_at 12 HSD17B12 51144 -1.41017 0.030567 8 ribosomal protein 1.17944
217107_at S4X pseudogene 9 RPS4XP9 442257 1.780774 0.00845 4
1.17882
1565265_at 2.838828 0.018145 2
1.17841
240804_at 1.356341 0.003875 4
1.17828
216148_at -1.35991 0.01799 8
1.17799
24203 l_at -1.55547 0.003938 1
NODAL modulator
3///NODAL NOM03///NO 408050//
modulator M02///NOMO /283820/
242922_at 2///NODAL 1 //23420 -1.2273 0.011282 1.17778 modulator 1
matrix 1 17751
224207_x_at metallopeptidase 28 MMP28 79148 1.220973 0.022061 1 zinc finger protein 1 17750
1555801_s_at 385B ZNF385B 151126 2.169949 0.01536 7
1 17717
235660_at -1.26058 0.004005 1
1 17616
1570105_at -1.37139 0.005781 4
1 17464
220784_s_at urotensin 2 UTS2 10911 1.571361 0.010999 1
1 17429
1561305_at 1.932974 0.004195 8
1 17428
241088_at 2.025458 0.003816 9 mitochondrial fission 1 17421
22309 l_x_at factor M FF 56947 -1.20285 0.004498 6 protein kinase,
interferon-inducible
double stranded RNA
dependent activator
pseudogene
l///protein kinase,
interferon-inducible
double stranded RNA PRKRAP1///PR 731716// 1 17312
237107_at dependent activator KRA /8575 -1.29242 0.013456 4
1 16934
229024_at -1.78314 0.003669 4 family with sequence
similarity 174, 1 16927
226752_at member A FAM 174A 345757 -1.26912 0.003698 8 zinc finger protein 1 16914
222884_at 346 ZNF346 23567 -1.18751 0.011779 6 zinc finger protein 1 16882
237453_at 529 ZNF529 57711 -1.5369 0.004881 8
1 16713
1561166_a_at -1.52098 0.008649 5
1 16666
218318_s_at nemo-like kinase NLK 51701 -1.25198 0.010114 7
1 16548
222097_at -1.54168 0.038275 3
1 16524
240171_at -1.60726 0.002654 6
1 16517
1569578_at -1.23811 0.00269 7
Rho-type GTPase- activating protein 1 16512
205414_s_at RICH2 RICH2 9912 2.669813 0.005896 4 ras homolog gene 1 16487
226417_at family, member B RHOB 388 4.810413 0.220243 9
1 16428
237199_at -1.22645 0.004946 6 hypothetical protein 1 16420
1563637_at LOC729652 LOC729652 729652 -1.60804 0.00381 6 1.16418
243527_at -1.25053 0.016075 9 hypothetical 1.16397
1562703_at LOC157381 LOC157381 157381 1.413936 0.020872 7
1.16259
239033_at -1.23845 0.13776 6
1.16197
1556595_at 1.46024 0.006692 1
1.16195
1570630_at 1.951291 0.036934 9
1.16175
211219_s_at LIM homeobox 2 LHX2 9355 2.916667 0.010657 2
1.16157
240624_x_at 1.497581 0.00854 7 chromosome 11
open reading frame 1.15947
239789_at 49 Cllorf49 79096 1.183866 0.030949 8
G protein-coupled 1.15892
223582_at receptor 98 G PR98 84059 1.660903 0.005336 4
1.15781
244540_at -2.53759 0.004947 4
1.15753
242990_at -1.22815 0.005193 8 family with sequence 1.15650
1552323_s_at similarity 122C FAM 122C 159091 -1.42492 0.007668 4
Src homology 2
domain containing 1.15532
204657_s_at adaptor protein B SH B 6461 1.438232 0.062875 3
1.15450
207669_at keratin 83 KRT83 3889 -3.53873 0.039564 1
U DP
glucuronosyltransfer
ase 1 family,
polypeptide
A6///UDP
glucuronosyltransfer
ase 1 family,
polypeptide
A7///UDP
glucuronosyltransfer
ase 1 family,
polypeptide
A8///UDP 54578///
glucuronosyltransfer UGT1A6///UG 54577///
ase 1 family, T1A7///UGT1A 54576/// 1.15229
221304_at polypeptide A10 8///UGT1A10 54575 1.815952 0.00609 6
ATPase,
aminophospholipid
transporter, class 1, 1.15186
226302_at type 8B, member 1 ATP8B1 5205 -1.38656 0.003782 6
N-acyl
phosphatidylethanol
amine phospholipase 1.15099
242229_at D NAPEPLD 222236 -1.25718 0.003547 8 238822_at 1.244452 0.003143 8 patatin-like
phospholipase 1 15021
236135_at domain containing 7 PNPLA7 375775 -3.18668 0.012172 8
1 14906
213289_at apolipoprotein O-like APOOL 139322 -1.30636 0.01006 6
1 14863
1561228_at 1.707715 0.003894 4 cyclin-dependent
kinase llA///cyclin- dependent kinase CDK11A///CDK 728642// 1 14821
207428_x_at 11B 11B /984 -1.16503 0.003369 8 hypothetical protein 10013281 1 14775
1565748_at LOC100132815 LOC100132815 5 -1.43481 0.023401 3 mitogen-activated
protein kinase kinase 1 14773
216206_x_at 7 MAP2K7 5609 1.347055 0.018939 9
1 14773
240659_x_at -1.29907 0.007366 6
LIM domain
containing preferred
translocation partner
243874_at in lipoma LPP 4026 -1.48347 0.004034 1 14715
1 14583
244878_at -1.33987 0.003928 8
233692_at -1.27249 0.003613 1 14562
SH3-domain GRB2- 1 14554
1567027_at like 1 pseudogene 2 SH3GL1P2 6459 1.755712 0.026969 6 l-acylglycerol-3- phosphate 0- 1 14540
223182_s_at acyltransferase 3 AGPAT3 56894 -1.17559 0.025724 7
1 14486
216158_at -1.34003 0.05504 7
1 14293
232265_at ataxin 7-like 1 ATXN7L1 222255 1.703193 0.003049 7
1 14285
219592_at microcephalin 1 MCPH 1 79648 -1.42003 0.017534 3 secreted frizzled- 1 14119
223122_s_at related protein 2 SFRP2 6423 -1.47075 0.018443 8
DENN/MADD
domain containing 1 14046
226849_at 1A DENN D1A 57706 -1.32017 0.006839 3
1 13966
206962_x_at 2.560024 0.004843 9 chromosome 1 open 1 13836
229113_s_at reading frame 86 Clorf86 199990 -1.09141 0.019724 7 lymphocyte-specific 1 13686
203523_at protein 1 LSP1 4046 -1.32375 0.004835 2 sex comb on midleg- 1 13671
1555356_a_at like 4 (Drosophila) SCM L4 256380 -1.53071 0.005441 5 transcription factor 1 13636
215611_at 12 TCF12 6938 -1.25901 0.011934 7
214815_at tripartite motif- TRIM33 51592 -1.19747 0.014135 1 13552 containing 33 5
A kinase (PRKA) 1 13529
205359_at anchor protein 6 AKAP6 9472 1.321286 0.004492 3
1 13514
229434_at -1.17295 0.006214 9 hypothetical protein 1 13457
243225_at LOC283481 LOC283481 283481 -1.51588 0.003569 8 histidine triad
nucleotide binding 1 13445
226537_at protein 3 HINT3 135114 -1.18038 0.107127 5
1 13383
242563_at -1.65859 0.020677 4 gap junction protein, 1 13378
234116_at delta 4, 40.1kDa GJ D4 219770 -1.45509 0.003487 1
ORAI calcium
release-activated 1 13367
230347_at calcium modulator 2 ORAI2 80228 -1.30263 0.030068 8 transmembrane 1 13291
239593_at protein 213 TMEM213 155006 1.436847 0.010051 5 translocase of outer
mitochondrial
membrane 70
homolog A (S.
201512_s_at cerevisiae) TOMM70A 9868 -1.12723 0.009322 1 13282 ectonucleotide
pyrophosphatase/ph 1 13231
219912_s_at osphodiesterase 3 ENPP3 5169 1.420576 0.051104 4 transmembrane 1 13199
221951_at protein 80 TM EM80 283232 -1.31851 0.00352 2
1 13152
233097_x_at -1.30952 0.007009 2
10012864 1 13128
243523_at LMN E6487 LOC100128644 4 1.475552 0.143026 9
1 13128
217278_x_at 5.351368 0.021795 5
1 13094
239661_at -1.4505 0.007786 2 nardilysin (N-arginine 1 13041
229422_at dibasic convertase) N RD1 4898 -1.26433 0.005354 8
BRCA1 interacting
protein C-terminal 1 12945
221703_at helicase 1 BRI P1 83990 1.902363 0.003889 3
1 12873
213605_s_at -1.38229 0.005541 1 ataxin 2-binding
221217_s_at protein 1 A2BP1 54715 1.894762 0.003422 1 12756
1 12631
1560208_at 2.008445 0.003899 8
1 12492
244553_at -1.49295 0.005423 6
1 12458
236628_at 1.71023 0.005002 3
WD repeat domain 1 12410
221981_s_at 59 WDR59 79726 -1.85388 0.005018 8 1 12380
243730_at 1.580583 0.010253 5
1 12272
239621_at -1.44892 0.00378 9
1 12190
242407_at -1.29655 0.015102 1
1 11993
244868_at -1.21919 0.009826 1 zinc finger protein
1552375_at 333 ZNF333 84449 -1.28971 0.033694 1 11926
1 11875
240759_at -1.15962 0.005208 9
1 11825
215648_at -1.38213 0.008543 5
1562296_at 1.830859 0.008368 1.1177
1 11745
238869_at -1.23843 0.006357 9
BTB (POZ) domain
207722_s_at containing 2 BTBD2 55643 1.35564 0.009486 1 11635
240666_at -1.37516 0.004012 1 11529
1 11431
207080_s_at peptide YY PYY 5697 1.565988 0.07198 8
1 11413
242375_x_at 1.194398 0.023644 9 chromosome 1 open 1 11289
24077 l_at reading frame 101 ClorflOl 257044 -1.57381 0.006533 6
1 11266
234175_at 1.505724 0.005603 1 t-complex- associated-testis-
232258_at expressed 3 TCTE3 6991 -1.47479 0.021819 1 11099
1 11079
243558_at -1.36512 0.005401 6
5'-nucleotidase, 1 11032
224529_s_at cytosolic IA NT5C1A 84618 -1.6 0.021687 6
210419_at BARX homeobox 2 BARX 2 8538 1.501661 0.004328 1 10796
1 10775
238761_at -1.40498 0.010899 2
1 10759
232261_at 1.769699 0.012417 4
1 10752
224398_at -1.75634 0.004864 7
1 10737
235112_at -1.16445 0.110024 9 zinc finger and SCAN
domain containing 1 10732
239157_at 12 pseudogene 1 ZSCAN12P1 221584 1.987099 0.003715 3
1 10678
215525_at -1.49901 0.00412 2 peptidylprolyl
isomerase 1 10674
214986_x_at (cyclophilin)-like 2 PPI L2 23759 -1.4094 0.004819 9
236763_at -1.25319 0.005496 1 10669 2
GRB2-related 1.10628
1560524_at adaptor protein-like GRAPL 400581 1.366567 0.003877 5
1.10615
235328_at plexin CI PLXNC1 10154 -1.24527 0.034284 7
1.10613
207848_at arginine vasopressin AVP 551 1.808552 0.041831 4
1.10587
1560940_at 1.448891 0.062805 1
1.10569
237006_at -1.27759 0.004293 1
1.10506
1557452_at 1.618989 0.006763 5
1.10456
1567045_at -1.33659 0.003744 7
1.10292
211712_s_at annexin A9 ANXA9 8416 1.870555 0.010403 2 chromosome 6 open 1.10257
220324_at reading frame 155 C6orfl55 79940 3.078274 0.004736 7
V-set and
transmembrane
domain containing 1.10210
236308_at 2A VSTM2A 222008 1.524408 0.008282 9 hypothetical 10019093 1.10194
227710_s_at LOC100190939 LOC100190939 9 -1.22185 0.00935 8 cytochrome P450,
family 19, subfamily 1.10193
239460_at A, polypeptide 1 CYP19A1 1588 1.86817 0.005102 8 general transcription
factor MIC,
polypeptide 3, 1.10172
1555439_at 102kDa GTF3C3 9330 -1.40274 0.010229 3
FAST kinase domains 1.10141
219002_at 1 FASTKD1 79675 -1.11218 0.009521 8 dual specificity
phosphatase
15///chromosome
20 open reading DUSP15///C20 128853// 1.10076
230402_at frame 57 orf57 /83747 1.860654 0.005066 1
1.10016
238119_at -1.19719 0.009184 5 chromosome 4 open 1.10010
237642_at reading frame 42 C4orf42 92070 1.529668 0.026277 7 Table 3. Probesets obtained from cells cultured in media for 24 hours.
FC t-test pvalue probe set desc symbol entrez (SS/LS) (all samples) Weight
1555973_at -1.32 0.0008 2.65
1561699_a_at 3.14 0.0001 2.14
1560929_at 3.73 0.0002 2.04
237364_at -1.88 0.0004 1.96 transducin-like
enhancer of split 6
(E(spl) homolog,
1553812_at Drosophila) TLE6 79816 5.21 0.0008 1.95 solute carrier family
236436_at 25, member 45 SLC25A45 283130 -1.23 0.0001 1.93
1565706_at -1.42 0.0007 1.80
234911_at 2.01 0.0007 1.78 hypothetical protein
1557717_at LOC338862 LOC338862 338862 1.50 0.0003 1.76 estrogen-related
1556156_at receptor beta ESRRB 2103 4.64 0.0013 1.74 hypothetical 100129
244489_at LOC100129268 LOC100129268 268 -1.98 0.0003 1.73 leucine-rich repeats
and
immunoglobul in-like
205953_at domains 2 LRIG2 9860 -1.15 0.0012 1.72 solute carrier family
17 (sodium
phosphate), member
1560885_x_at 1 SLC17A1 6568 -2.25 0.0003 1.70
240927_at -1.71 0.0011 1.68 transmembrane
229736_at protein 86B TMEM86B 255043 -1.74 0.0004 1.66
243998_at keratin 222 KRT222 125113 1.58 0.0053 1.61 zinc finger protein
232247_at 502 ZN F502 91392 -1.66 0.0078 1.60 adipocyte-specific
228082_at adhesion molecule ASAM 79827 2.61 0.0014 1.59 pregnancy specific
beta-l-glycoprotein
208134_x_at 2 PSG2 5670 -2.07 0.0013 1.57
SFT2 domain
232487_at containing 1 SFT2D1 113402 -1.62 0.0007 1.57 cholinergic receptor,
221355_at nicotinic, gamma CH RNG 1146 1.44 0.0018 1.56
1561756_at 2.46 0.0010 1.55 minichromosome
maintenance
complex component
223570_at 10 MCM10 55388 1.77 0.0006 1.55 chromosome 20
1554818_s_at open reading frame C20orfl2 55184 1.96 0.0026 1.53 12
ADP-ribosylation
factor GTPase
211975_at activating protein 2 ARFGAP2 84364 -1.08 0.0016 1.53
202272_s_at F-box protein 28 FBX028 23219 1.26 0.0010 1.49 patatin-like
phospholipase
228383_at domain containing 7 PN PLA7 375775 1.45 0.0018 1.49 kelch-like 36
219453_at (Drosophila) KLHL36 79786 -1.27 0.0008 1.49 hypothetical protein
LOC90925///immun
oglobulin heavy
constant gamma 1 LOC90925///IG 90925///
215721_at (Glm marker) HG1 3500 2.69 0.0010 1.47 discs, large homolog
229703_at 1 (Drosophila) DLG1 1739 1.36 0.0011 1.46 phospholipase C, eta
214745_at 1 PLCH 1 23007 1.52 0.0012 1.46
1562358_at 2.07 0.0035 1.46
217582_at 1.53 0.0015 1.46
236030_at REST corepressor 2 RCOR2 283248 1.57 0.0010 1.45
238236_at 1.48 0.0012 1.45
238386_x_at 1.77 0.0010 1.44
227273_at -1.36 0.0022 1.44 eukaryotic
translation initiation
235296_at factor 5A2 EIF5A2 56648 -1.24 0.0033 1.43
213240_s_at keratin 4 KRT4 3851 3.53 0.0049 1.43
230585_at 1.53 0.0012 1.42
240763_at -2.12 0.0027 1.42
243649_at F-box protein 7 FBX07 25793 -1.44 0.0012 1.42 solute carrier family
229925_at 6, member 17 SLC6A17 388662 1.31 0.0057 1.41
241166_at 2.64 0.0024 1.41 phosphodiesterase
1C, calmodulin-
216869_at dependent 70kDa PDE1C 5137 1.73 0.0012 1.40
DEAH (Asp-Glu-Ala- His) box polypeptide
1559039_at 36 DHX36 170506 -1.37 0.0016 1.40
204101_at myotubularin 1 MTM 1 4534 -1.42 0.0162 1.40
223362_s_at septin 3 40789 55964 1.51 0.0025 1.39
N EDD4 binding
229718_at protein 2-like 1 N4BP2L1 90634 -1.29 0.0014 1.39 chromosome 3 open
1569128_at reading frame 38 C3orf38 285237 -1.37 0.0091 1.39 protein phosphatase
1, regulatory
1566301_at (inhibitor) subunit 11 PPP1R11 6992 1.44 0.0014 1.39
226926_at dermokine DMKN 93099 1.36 0.0013 1.39 hypothetical protein
236652_at LOC149703 LOC149703 149703 1.69 0.0017 1.38
234223_at -2.41 0.0021 1.38 uridine-cytidine
223141_at kinase 1 UCK1 83549 -1.21 0.0015 1.38 cystic fibrosis
transmembrane
conductance
regulator (ATP- binding cassette sub¬
217026_at family C, member 7) CFTR 1080 -1.84 0.0014 1.38
1566204_at 1.65 0.0017 1.37 taste receptor, type
221395_at 2, member 13 TAS2R13 50838 1.38 0.0027 1.37 kielin/chordin-like
242855_at protein KCP 375616 -2.15 0.0015 1.37
156403 l_a_at RELT-like 2 RELL2 285613 -1.17 0.0058 1.37
1566518_at -1.46 0.0092 1.37
243659_at -1.47 0.0016 1.36 mediator complex
20696 l_s_at subunit 20 MED20 9477 2.12 0.0024 1.36
239117_at -1.42 0.0016 1.36 hexosaminidase
(glycosyl hydrolase
family 20, catalytic
238591_at domain) containing H EXDC 284004 -1.25 0.0026 1.36
1560115_a_at KIAA1217 KIAA1217 56243 -3.33 0.0278 1.36 prostaglandin E
receptor 1 (subtype
231201_at EP1), 42kDa PTGER1 5731 -2.17 0.0018 1.36
237726_at 1.41 0.0021 1.36
237723_at -2.01 0.0037 1.35 alpha-methylacyl-
209424_s_at CoA racemase AMACR 23600 -1.22 0.0032 1.35 hypothetical protein
1565729_at LOC284630 LOC284630 284630 1.47 0.0021 1.35
243635_at 1.66 0.0099 1.35 family with
sequence similarity
244644_at 9, member C FAM9C 171484 1.81 0.0018 1.35
A kinase (PRKA)
anchor protein
207870_at (yotiao) 9 AKAP9 10142 1.76 0.0049 1.34 polymerase (DNA
directed), epsilon 2
205909_at (p59 subunit) POLE2 5427 -1.26 0.0178 1.33 microtubule- associated protein
215391_at 1A MAP1A 4130 3.21 0.0053 1.33
HtrA serine
228580_at peptidase 3 HTRA3 94031 1.32 0.0018 1.32
1562080_at 1.87 0.0087 1.32 224398_at 1.91 0.0032 1.32 gap junction protein,
221407_at delta 2, 36kDa GJ D2 57369 1.22 0.0125 1.32 chromosome 3 open
226815_at reading frame 31 C3orf31 132001 1.29 0.0019 1.32
SLIT-ROBO Rho
GTPase activating
232869_at protein 3 SRGAP3 9901 -2.57 0.0019 1.32 signal-induced
proliferation-
236096_at associated 1 like 3 SIPA1L3 23094 1.53 0.0048 1.31
240693_at 1.34 0.0021 1.31
242089_at 1.28 0.0062 1.31 family with
sequence similarity
244435_at 196, member A FAM196A 642938 1.68 0.0056 1.30
1557878_at -1.62 0.0057 1.30
234023_s_at centromere protein J CEN PJ 55835 -1.69 0.0091 1.30
211437_at 2.47 0.0042 1.30 wingless-type MMTV
integration site
206737_at family, member 11 WNT11 7481 2.15 0.0243 1.30 sushi, von
Willebrand factor
type A, EG F and
pentraxin domain
1566722_a_at containing 1 SVEP1 79987 2.03 0.0019 1.30
1561962_at 2.07 0.0022 1.30
243989_at 1.58 0.0022 1.29 deoxynucleotidyltran
1566362_at sferase, terminal DNTT 1791 2.71 0.0098 1.29 coiled-coil domain
220077_at containing 134 CCDC134 79879 1.27 0.0157 1.29 myosin light chain
224823_at kinase MYLK 4638 1.40 0.0021 1.29
1558858_at 2.26 0.0035 1.29 keratin 18
217000_at pseudogene 50 KRT18P50 442236 2.02 0.0022 1.29
237912_at -1.97 0.0143 1.28 neuroblastoma
202926_at amplified sequence N BAS 51594 -1.10 0.0089 1.28 autophagy/beclin-1
52731_at regulator 1 AMBRA1 55626 -1.29 0.0025 1.28
1554394_at N EL-like 1 (chicken) N ELL1 4745 1.79 0.0024 1.27 kinesin family
222144_at member 17 KI F17 57576 -2.47 0.0198 1.27 tubulin
polymerization- promoting protein
231140_at family member 2 TPPP2 122664 -1.69 0.0123 1.27
207660_at dystrophin DMD 1756 1.46 0.0027 1.27
241704_x_at zinc finger protein ZN F320 162967 -1.21 0.0028 1.27 320
carbonic anhydrase
220234_at VIII CA8 767 -1.52 0.0054 1.27 hypothetical
1561685_a_at LOC441178 LOC441178 441178 3.67 0.0089 1.27
234154_at 2.08 0.0037 1.27 hypothetical
LOC100126583///im
munoglobulin heavy
variable 3/OR16-13
(non- functional)///immun
oglobulin heavy
constant alpha 2
(A2m
marker)///immunogl 1001265
obulin heavy LOC100126583 83///283
constant alpha ///IGHV30R16- 03///349
-.///immunoglobulin 13///IGHA2///I 4///3493
217022_s_at heavy locus GHA1///IGH@ ///3492 -2.31 0.0025 1.26
1557316_at -1.19 0.0039 1.26
1569673_at 1.80 0.0024 1.26 non-metastatic cells
5, protein expressed
in (nucleoside-
206197_at diphosphate kinase) N ME5 8382 1.37 0.0099 1.26
1560877_a_at 1.35 0.0029 1.26 peptidylprolyl
isomerase
242154_x_at (cyclophilin)-like 5 PPI L5 122769 1.18 0.0040 1.26
241228_at 1.64 0.0105 1.25 eosinophil granule
ontogeny transcript 1001267
222314_x_at (non-protein coding) EGOT 91 1.55 0.0032 1.25 tetratricopeptide
230747_s_at repeat domain 39C TTC39C 125488 -1.29 0.0035 1.25
244512_at -1.52 0.0060 1.24
205573_s_at sorting nexin 7 SNX7 51375 2.02 0.0040 1.24 chromosome 2 open
1556464_a_at reading frame 72 C2orf72 257407 1.34 0.0032 1.24
1554550_at KIAA1430 KIAA1430 57587 2.18 0.0029 1.23
231305_at 1.28 0.0041 1.23 proline rich 729250//
20E///proline rich /729246/
20D///proline rich PRR20E///PRR //729240
20C///proline rich 20D///PRR20C ///72923
20B///proline rich ///PRR20B///P 3///1221
1562722_at 20A RR20A 83 1.62 0.0129 1.23 replication factor C
(activator 1) 1,
209085_x_at 145kDa RFC1 5981 -1.20 0.0077 1.23
207182_at gamma- GABRA6 2559 1.56 0.0029 1.22 aminobutyric acid
(GABA) A receptor,
alpha 6
243326_at 2.04 0.0036 1.22 chromosome 18
open reading frame
233577_at 57 C18orf57 54523 1.81 0.0079 1.22
SSU72 RNA
polymerase II CTD
phosphatase
homolog (S.
226229_s_at cerevisiae) SSU72 29101 -1.25 0.0202 1.22 hypothetical protein 1002880
1556468_at LOC100288099 LOC100288099 99 2.60 0.0056 1.22 zinc finger protein
1569039_s_at 677 ZN F677 342926 -1.35 0.0094 1.22
SH2 domain
219749_at containing 4A SH2D4A 63898 1.57 0.0049 1.22 microtubule- associated protein
203929_s_at tau MAPT 4137 1.56 0.0031 1.22
220826_at 2.21 0.0031 1.21 serine/arginine-rich
22947 l_s_at splicing factor 8 SRSF8 10929 2.19 0.0030 1.21
CH K2 checkpoint
210416_s_at homolog (S. pombe) CH EK2 11200 1.13 0.0112 1.21 meteorin, glial cell
differentiation
228419_at regulator METRN 79006 1.27 0.0053 1.21 peptidase inhibitor
207938_at 15 PI 15 51050 1.48 0.0143 1.21
239360_at 2.32 0.0064 1.20 chromosome 7 open
221573_at reading frame 25 C7orf25 79020 -1.30 0.0123 1.20
240049_at 1.98 0.0040 1.20
1557495_at -1.81 0.0070 1.20 ataxia telangiectasia
1570352_at mutated ATM 472 -1.38 0.0216 1.20 dentin matrix acidic
208175_s_at phosphoprotein 1 DMP1 1758 1.57 0.0074 1.20 phosphodiesterase
6D, cGMP-specific,
231065_at rod, delta PDE6D 5147 -1.33 0.0085 1.19 trimethyllysine
222744_s_at hydroxylase, epsilon TMLH E 55217 -1.28 0.0042 1.19
235608_at -1.21 0.0035 1.19
240367_at 1.18 0.0093 1.19 chromosome 8 open
reading frame
44///serum/glucocor
ticoid regulated
kinase family, C8orf44///SGK 56260///
243264_s_at member 3 3 23678 -1.37 0.0034 1.19 DDB1 and CUL4
230679_at associated factor 10 DCAF10 79269 -1.36 0.0042 1.19 chromosome 2 open
224180_x_at reading frame 86 C2orf86 51057 -1.18 0.0045 1.18
237440_at 1.70 0.0050 1.18 myeloma
overexpressed (in a
subset of t(ll;14)
positive multiple
227343_at myelomas) MYEOV 26579 1.34 0.0035 1.18 tet oncogene family
1554641_a_at member 3 TET3 200424 1.23 0.0096 1.18 immunoglobulin
lambda-like
215946_x_at polypeptide 3 IGLL3 91353 -1.80 0.0048 1.18
LIM domain
containing preferred
translocation
243874_at partner in lipoma LPP 4026 -1.37 0.0036 1.18
FK506 binding
20339 l_at protein 2, 13kDa FKBP2 2286 1.15 0.0037 1.18 hypothetical
1557604_at LOC401312 LOC401312 401312 3.97 0.0170 1.18
227362_at SLC2A4 regulator SLC2A4RG 56731 1.73 0.0084 1.17
215944_at 1.88 0.0061 1.17 protein kinase C,
230437_s_at beta PRKCB 5579 1.34 0.0109 1.17 chromosome 2 open
231133_at reading frame 39 C2orf39 92749 3.17 0.0090 1.17
238393_at -3.05 0.0322 1.17
236558_at -1.41 0.0151 1.17 hypothetical protein
1558859_at LOC222159 LOC222159 222159 -1.46 0.0045 1.17
239744_at -1.70 0.0043 1.16
AFFX-TrpnX-
3_at -1.42 0.0039 1.16
1557339_at 2.84 0.0095 1.16 chromosome 18
open reading frame
232348_at 8 C18orf8 29919 1.36 0.0040 1.16 calcium channel,
voltage-dependent,
234756_at gamma subunit 8 CACNG8 59283 1.58 0.0047 1.16
234494_x_at -3.25 0.0167 1.16
232239_at hCG2024094 LOC643529 643529 1.19 0.0069 1.16 zinc finger protein
1554922_at 678 ZN F678 339500 -2.01 0.0189 1.15
U PF3 regulator of
nonsense transcripts
206958_s_at homolog A (yeast) U PF3A 65110 -1.16 0.0042 1.15
AT-hook
1558565_at transcription factor AKNA 80709 1.90 0.0084 1.15 Werner helicase
218015_s_at interacting protein 1 WRNI P1 56897 2.05 0.0042 1.15 methyl-CpG binding
220195_at domain protein 5 MBD5 55777 -1.36 0.0102 1.15 vacuolar protein
sorting 26 homolog
243316_x_at A (S. pombe) VPS26A 9559 -1.25 0.0057 1.15 retinoic acid
receptor responder
(tazarotene induced)
20639 l_at 1 RARRES1 5918 1.29 0.0047 1.15
215998_at -2.01 0.0042 1.15
243553_x_at -1.46 0.0055 1.15
229380_at 1.47 0.0100 1.15
211498_s_at N K3 homeobox 1 N KX3-1 4824 2.16 0.0259 1.14
1561611_at 1.25 0.0059 1.14
224287_at 1.65 0.0043 1.14 sodium channel,
nonvoltage-gated 1,
241436_at gamma SCNN 1G 6340 2.40 0.0125 1.14
GI NS complex
subunit 4 (Sld5
240778_at homolog) GINS4 84296 -1.31 0.0049 1.14
SH3 domain
1558647_at containing 19 SH3D19 152503 1.25 0.0134 1.14
235268_at -1.40 0.0062 1.14
157003 l_at 1.97 0.0140 1.14 fibronectin type III
domain containing
1569490_at 3B FN DC3B 64778 1.48 0.0048 1.13
216150_at 1.60 0.0052 1.13 chromosome 17
open reading frame
228136_s_at 70 C17orf70 80233 1.65 0.0053 1.13 dynein, axonemal,
215341_at heavy chain 6 DNAH6 1768 1.39 0.0045 1.13 nuclear transcription
factor, X-box binding
202585_s_at 1 N FX1 4799 -1.20 0.0061 1.13
1566182_at 1.42 0.0046 1.13 inducible T-cell co-
213450_s_at stimulator ligand ICOSLG 23308 -1.28 0.0188 1.13
231502_at -1.32 0.0222 1.13
240616_at 1.51 0.0116 1.13 spindlin family,
228654_at member 4 SPI N4 139886 -1.22 0.0047 1.13 solute carrier family
13 (sodium- dependent
dicarboxylate
transporter),
230687 at member 3 SLC13A3 64849 -2.47 0.0074 1.13 235965_at -1.60 0.0228 1.12 emopamil binding
protein (sterol
202735_at isomerase) EBP 10682 1.26 0.0059 1.12
214063_s_at transferrin TF 7018 -1.94 0.0084 1.12
SRY (sex determining
224178_s_at region Y)-box 6 SOX6 55553 -1.40 0.0102 1.12
DEAH (Asp-Glu-Ala- His) box polypeptide
218579_s_at 35 DHX35 60625 -1.27 0.0062 1.12
232379_at SKI-like oncogene SKI L 6498 1.52 0.0080 1.12
X-prolyl
aminopeptidase
(aminopeptidase P)
224188_s_at 3, putative XPNPEP3 63929 -1.13 0.0065 1.12
C-type lectin domain
1556209_at family 2, member B CLEC2B 9976 -1.80 0.0049 1.12
240985_at 1.70 0.0060 1.12 multiple C2 domains,
229005_at transmembrane 2 MCTP2 55784 -1.98 0.0065 1.12
LEM domain
224980_at containing 2 LEMD2 221496 -1.26 0.0074 1.12
234200_at -1.81 0.0052 1.12 pygopus homolog 2
225370_at (Drosophila) PYG02 90780 -1.27 0.0100 1.11 actin binding LIM
protein family,
228132_at member 2 ABLI M2 84448 1.80 0.0124 1.11
209218_at squalene epoxidase SQLE 6713 1.37 0.0056 1.11 limb region 1
homolog (mouse)-
220036_s_at like LM BR1L 55716 -1.21 0.0050 1.11 cancer susceptibility
1564372_s_at candidate 2 CASC2 255082 1.64 0.0051 1.11
241293_x_at 1.53 0.0066 1.11 zinc finger protein 41
227898_s_at homolog (mouse) ZFP41 286128 -1.29 0.0099 1.11 zinc finger, SWI M-
231915_at type containing 4 ZSWIM4 65249 2.71 0.0244 1.11 methyltransferase
219698_s_at like 4 METTL4 64863 -1.24 0.0051 1.11
1559020_a_at -1.30 0.0068 1.11
Niemann-Pick
217584_at disease, type CI N PC1 4864 -1.39 0.0062 1.11
PHD finger protein
231967_at 20-like 1 PH F20L1 51105 -1.25 0.0064 1.11
202674_s_at LIM domain 7 LM07 4008 -1.34 0.0113 1.11
F-box and leucine-
220080_at rich repeat protein 8 FBXL8 55336 -1.59 0.0083 1.11 microtubule-actin
241896_at crosslinking factor 1 MACF1 23499 1.26 0.0052 1.10
233069_at protein phosphatase PPP4R1L 55370 -1.92 0.0055 1.10 4, regulatory subunit
1-like
240949_x_at 1.61 0.0061 1.10
226513_at -1.19 0.0053 1.10
Table 4. Probesets obtained from cells cultured in BCG for 24 hours. t-test pvalue Wei probe set desc symbol entrez FC (SS/LS) (all samples) ght
1561389_at -1.68 0.000002 3.39
SFT2 domain
229023_at containing 3 SFT2D3 84826 -3.12 0.000705 2.42
1555603_at B melanoma antigen BAGE 574 -3.69 0.000032 2.31 dentin matrix acidic
208175_s_at phosphoprotein 1 DMP1 1758 -3.60 0.000286 2.26
NADH
dehydrogenase
(ubiquinone) 1 beta
218201_at subcomplex, 2, 8kDa N DU FB2 4708 -1.19 0.000594 2.00
232982_at synergin, gamma SYN RG 11276 -1.57 0.000439 2.00 tubulin folding
229767_at cofactor D TBCD 6904 2.38 0.000396 1.99 odz, odd Oz/ten-m
homolog 3
227050_at (Drosophila) ODZ3 55714 2.66 0.000131 1.95
234569_at 1.48 0.001334 1.79 junctional adhesion
231720_s_at molecule 3 JAM3 83700 -1.37 0.000454 1.75
233405_at -1.59 0.001144 1.72
1568375_at defensin, beta 124 DEFB124 245937 -2.08 0.000456 1.69 chromosome 15
open reading frame
240876_x_at 43 C15orf43 145645 -1.64 0.002711 1.66
236375_at -1.23 0.001730 1.65
1556670_at 1.22 0.001282 1.63
236919_at -1.36 0.004954 1.62
1561893_at -1.24 0.004046 1.57 family with sequence
similarity 20,
202915_s_at member B FAM20B 9917 -1.15 0.009636 1.56
EF-hand domain (C- terminal) containing
220523_at 2 EFHC2 80258 1.90 0.007115 1.55
223941_at F-box protein 24 FBX024 26261 1.77 0.002501 1.53
240675_at 2.88 0.003977 1.52 hypothetical 100132
1559514_at LOC100132077 LOC100132077 077 1.73 0.001216 1.51 dihydrofolate
202534_x_at reductase DHFR 1719 -1.22 0.006115 1.49
SLIT-ROBO Rho
GTPase activating
215550_at protein 3 SRGAP3 9901 -1.34 0.001580 1.48
20753 l_at crystallin, gamma C CRYGC 1420 1.33 0.000929 1.47
229815_at 1.77 0.001140 1.47 aldehyde
215798_at dehydrogenase 1 ALDH1L1 10840 -1.31 0.006102 1.46 family, member LI
244458_at -1.27 0.001109 1.45 kelch domain
1553437_at containing 7A KLH DC7A 127707 -2.06 0.001393 1.42 vacuolar protein
sorting 24 homolog
217837_s_at (S. cerevisiae) VPS24 51652 1.17 0.001158 1.42 myeloid-associated
differentiation
242378_at marker-like 2 MYADML2 255275 1.38 0.002445 1.42 potassium voltage- gated channel, Isk- related family,
222923_s_at member 3 KCNE3 10008 1.44 0.005748 1.41 complement
component (3b/4b)
receptor 1 (Knops
208488_s_at blood group) CR1 1378 1.33 0.004178 1.41
223000_s_at Fll receptor FUR 50848 1.16 0.010080 1.38
1556806_at -1.82 0.005631 1.37 suppressor of
213337_s_at cytokine signaling 1 SOCS1 8651 -1.48 0.003096 1.37 eukaryotic
translation initiation
236605_at factor 3, subunit K EI F3K 27335 -1.29 0.001671 1.37
242124_at 3.99 0.001433 1.37
G protein-coupled
206190_at receptor 17 GPR17 2840 1.97 0.001534 1.36
234890_at -1.77 0.004719 1.35
236616_at -1.30 0.001659 1.35 aldo-keto reductase
family 1, member C3
(3-alpha
hydroxysteroid
dehydrogenase, type
209160_at ID AKR1C3 8644 -1.50 0.006027 1.34 deleted in
lymphocytic
leukemia 2 (non¬
1569600_at protein coding) DLEU2 8847 -2.58 0.002540 1.34
ADP-ribosylation
factor-like 6
interacting protein 1
pseudogene///ARP3
actin-related protein
3 homolog (yeast) 100288
pseudogene 702///
l///ribosomal 100288
protein L4 580///
pseudogene 1///T LOC100288702/ 650808
cell receptor alpha //ACTR3P1///R ///695
locus///sal-like 2 PL4P1///TRA@/ S///62
234867_at (Drosophila) //SALL2 97 1.39 0.002277 1.33 244358_at 1.37 0.004076 1.33 mex-3 homolog C (C.
1556873_at elegans) M EX3C 51320 -1.67 0.002959 1.33 chromosome 21
open reading frame
1552605_s_at 74 C21orf74 54143 1.92 0.008349 1.31
233152_x_at -1.76 0.008682 1.31
1569577_x_at -1.59 0.014371 1.31
233501_at 1.74 0.006398 1.31 gonadotropin- releasing hormone
1553067_a_at (type 2) receptor 2 GN RH R2 114814 -1.39 0.024193 1.30
1569698_s_at -1.54 0.011372 1.30
1554887_at -2.24 0.002030 1.30 hypothetical protein
236523_at LOC285556 LOC285556 285556 4.03 0.017883 1.30
1569305_a_at 1.74 0.001976 1.30 cold shock domain
213319_s_at protein A CSDA 8531 2.18 0.004773 1.29
THAP domain
220360_at containing 9 THAP9 79725 -1.65 0.002348 1.29 zinc finger, C3H 1-
244499_at type containing ZFC3H 1 196441 1.16 0.002702 1.29
1563224_at -1.45 0.006213 1.29
239167_at -1.23 0.002102 1.29
239867_at 1.53 0.005152 1.28 ribosomal protein S6
kinase, 70kDa,
204171_at polypeptide 1 RPS6KB1 6198 -1.15 0.002338 1.28 zinc finger homeobox
233752_s_at 3 ZFHX3 463 2.41 0.009505 1.28 topoisomerase (DNA)
208900_s_at 1 TOPI 7150 -1.35 0.002180 1.28
233473_x_at -1.30 0.002222 1.28 chromosome 20
open reading frame
228236_at 54 C20orf54 113278 2.41 0.005267 1.26
237825_x_at -1.70 0.007913 1.26 protein phosphatase
1, regulatory
(inhibitor) subunit
1555444_a_at 12B PPP1R12B 4660 -1.89 0.022398 1.26
5'-3' exoribonuclease
1570394_at 1 XRN 1 54464 -1.43 0.005130 1.26
239830_at -1.22 0.004673 1.25 protein phosphatase,
Mg2+/Mn2+
229484_at dependent, 1J PPM1J 333926 1.36 0.002636 1.25 solute carrier family
6 (neurotransmitter
transporter,
217621_at noradrenalin), SLC6A2 6530 -2.40 0.016885 1.25 member 2
236041_at -1.31 0.002907 1.24 splA/ryanodine
receptor domain and
SOCS box containing
223580_at 2 SPSB2 84727 1.39 0.018572 1.24
1560189_at -1.23 0.004232 1.23
242676_at 1.16 0.004519 1.23 ubiquitin protein
ligase E3 component
226921_at n-recognin 1 U BR1 197131 -1.10 0.003463 1.23 nuclear factor of
activated T-cells,
cytoplasmic,
calcineurin-
208196_x_at dependent 1 N FATC1 4772 1.62 0.002906 1.23 similar to
peptidylprolyl
isomerase A///similar
to TRIMCyp///similar
to 643997
TRI MCyp///hypotheti ///440
cal 063///
LOC402644///similar 439953
to peptidylprolyl ///402
isomerase A///similar 644///
to TRIMCyp///similar LOC643997///L 391532
to TRIM5/cyclophilin OC440063///LO ///342
A fusion C439953///LOC 541///
protein///similar to 402644///LOC3 256374
TRIMCyp///peptidylp 91532///LOC34 ///202
rolyl isomerase A 2541///LOC256 227///
pseudogene///peptid 374///LOC2022 128192
yl prolyl isomerase A 27///LOC12819 ///547
217346_at (cyclophilin A) 2///PPIA 8 -1.15 0.006064 1.22 zinc finger protein
232247_at 502 ZN F502 91392 -1.43 0.002888 1.22 ribosomal protein
S26 pseudogene
57///odz, odd 100271
Oz/ten-m homolog RPS26P57///OD 401///
234885_at l(Drosophila) Zl 10178 2.40 0.004420 1.22 hypothetical protein
239879_at LOC284998 LOC284998 284998 2.05 0.030351 1.22
1558592_at -1.53 0.003091 1.22
235811_at -1.60 0.004775 1.22
RAB14, member RAS
211503_s_at oncogene family RAB14 51552 -1.18 0.004539 1.22 myosin, light chain 9,
201058_s_at regulatory MYL9 10398 1.58 0.005445 1.22 gap junction protein,
20549 l_s_at beta 3, 31kDa GJ B3 2707 1.61 0.016618 1.21
215336_at A kinase (PRKA) AKAP11 11215 -1.20 0.005337 1.21 anchor protein 11
sarcoglycan, alpha
(50kDa dystrophin- associated
210632_s_at glycoprotein) SGCA 6442 2.25 0.006095 1.21
240787_at -1.71 0.004199 1.21 harakiri, BCL2
interacting protein
(contains only BH3
206863_x_at domain) H RK 8739 -1.79 0.005944 1.20 chromosome 11
open reading frame
1557180_at 87 Cllorf87 399947 -2.02 0.011556 1.20 glutaredoxin-like
protein YDR286C
230404_at homolog FU 44606 401207 -1.30 0.003346 1.20 hypothetical
1558459_s_at LOC401320 LOC401320 401320 -1.18 0.003397 1.19 hepatoma-derived
growth factor-related
223252_at protein 2 H DGFRP2 84717 -1.16 0.015457 1.19
241540_at -2.20 0.005638 1.19 chromosome 5 open
238635_at reading frame 28 C5orf28 64417 -1.26 0.004316 1.19
242203_at -2.18 0.010548 1.19
1559220_at -1.25 0.003789 1.19 pyridoxal-dependent
decarboxylase
1558430_at domain containing 1 PDXDC1 23042 -1.46 0.005603 1.19 zinc finger protein
228294_s_at 775 ZN F775 285971 3.20 0.014239 1.18 gamma-aminobutyric
acid (GABA) A
207182_at receptor, alpha 6 GABRA6 2559 -1.74 0.004338 1.18 oncostatin M
205729_at receptor OSMR 9180 -3.81 0.017794 1.18
CUB and Sushi
240228_at multiple domains 3 CSMD3 114788 -2.51 0.009372 1.18
235767_x_at -1.13 0.006539 1.18 cystathionine-beta-
212816_s_at synthase CBS 875 1.65 0.006717 1.17 ankyrin repeat
229307_at domain 28 AN KRD28 23243 1.29 0.006056 1.17
FSH D region gene 1
1558107_at pseudogene LOC283788 283788 2.13 0.006552 1.17 promyelocytic
211589_at leukemia PML 5371 -2.56 0.034519 1.17
242869_at 1.33 0.024575 1.17 cadherin-related
219796_s_at family member 5 CDHR5 53841 -2.47 0.028648 1.17 actin binding LIM
protein family,
228132_at member 2 ABLIM2 84448 1.32 0.004192 1.17 241884_at -1.36 0.004856 1.17
240146_at -1.36 0.006587 1.17 zinc finger protein 91
22463 l_at homolog (mouse) ZFP91 80829 -1.16 0.006651 1.16
RIMS binding protein
238817_at 2 RI MBP2 23504 1.76 0.004196 1.16 hypothetical 400931
LOC400931///hypoth LOC400931///L ///150
1557342_a_at etical LOC150381 OC150381 381 -6.37 0.055932 1.16
201965_s_at senataxin SETX 23064 -1.19 0.005597 1.16 hypothetical protein
236769_at LOC158402 LOC158402 158402 -1.64 0.007878 1.16 chromosome 16
open reading frame
231076_at 82 C16orf82 162083 2.25 0.007837 1.16 hypothetical
237899_at LOC729994 LOC729994 729994 1.69 0.012315 1.16 methyltransferase
232102_at like 6 METTL6 131965 1.70 0.007773 1.16 signal recognition
208095_s_at particle 72kDa SRP72 6731 -1.16 0.004393 1.15 chromosome 9 open
220505_at reading frame 53 C9orf53 51198 -3.49 0.019461 1.15 abhydrolase domain
237974_at containing 12B ABHD12B 145447 -1.71 0.006071 1.15 serpin peptidase
inhibitor, clade A
(alpha-1
antiproteinase,
antitrypsin), member
206325_at 6 SERPINA6 866 -2.88 0.049101 1.14 chromosome 3 open
226815_at reading frame 31 C3orf31 132001 1.24 0.006804 1.14
237438_at -1.26 0.004494 1.14 lin-9 homolog (C.
1552771_a_at elegans) LIN9 286826 2.76 0.006277 1.14 keratin associated
220976_s_at protein 1-1 KRTAPl-1 81851 1.90 0.011890 1.14 chromosome 14
open reading frame
1562299_at 25 C14orf25 319089 1.27 0.006095 1.13
215614_at 1.70 0.005541 1.13
H ECT domain
218632_at containing 3 H ECTD3 79654 1.13 0.004917 1.13 ceroid-lipofuscinosis,
214252_s_at neuronal 5 CLN5 1203 1.38 0.015069 1.13 sema domain,
transmembrane
domain (TM), and
cytoplasmic domain,
215028_at (semaphorin) 6A SEMA6A 57556 -2.26 0.005273 1.13 myosin binding
206304_at protein H MYBPH 4608 3.30 0.004649 1.13 203533_s_at cullin 5 CU L5 8065 -1.10 0.010839 1.13
240273_at 3.77 0.011347 1.13
1559302_at KIAA1467 KIAA1467 57613 -1.62 0.012276 1.12 achaete-scute
complex homolog 1
209987_s_at (Drosophila) ASCL1 429 -1.46 0.005149 1.12 hypothetical 100128
228629_s_at LOC100128025 LOC100128025 025 2.61 0.032369 1.12
TRAF-interacting
protein with
forkhead-associated
domain, family
236673_at member B TI FAB 497189 -1.25 0.009781 1.12 metal response
element binding
203346_s_at transcription factor 2 MTF2 22823 -1.12 0.015926 1.11
244088_at 1.29 0.033660 1.11
244809_at 2.33 0.013816 1.11
LYR motif containing
227797_x_at 2 LYRM2 57226 -1.27 0.005177 1.11
155848 l_s_at -1.85 0.005292 1.11
BCL2-associated
202984_s_at athanogene 5 BAG5 9529 -1.15 0.006077 1.11 ubiquitin protein
214980_at ligase E3A U BE3A 7337 -1.40 0.005449 1.10 cadherin 4, type 1, R-
239485_at cadherin (retinal) CDH4 1002 1.40 0.008232 1.10 chromosome 11
open reading frame
242515_x_at 17 Cllorfl7 56672 1.40 0.010679 1.10
SU MOl/sentrin
202318_s_at specific peptidase 6 SEN P6 26054 -1.13 0.008043 1.10
I. EXAMPLES
The following examples are included to demonstrate preferred embodiments of the invention. It should be appreciated by those of skill in the art that the techniques disclosed in the examples which follow represent techniques discovered by the inventor to function well in the practice of the invention, and thus can be considered to constitute preferred modes for its practice. However, those of skill in the art should, in light of the present disclosure, appreciate that many changes can be made in the specific embodiments which are disclosed and still obtain a like or similar result without departing from the spirit and scope of the invention. EXAMPLE 1
Weighted Gene Voting allows accurate prediction of survival groups
To gain insight into BCG-induced immune pathways that may be important for melanoma survival, the in vitro responses of PBMC from melanoma patients who received BCG immunostimulation were measured and compared these to profiles of an established mycobacterial skin infection. The inventors studied 1 1 melanoma patients (matched by age, sex and tumor burden), six of whom survived less than 1.5 years (short term survivors-SS) and five of whom survived greater than ten years (long term survivors-LS) after BCG immunostimulation. PBMCs collected prior to BCG administration were stimulated in vitro with either BCG or media for six or 24 hours and analyzed by gene expression microarrays. To determine whether the gene expression differences between LS and SS in BCG responsiveness in vitro can provide theragnostic information in melanoma patients considering BCG immunostimulation, the inventors selected probesets with high signal-to- noise ratios. Using weighted gene voting, these probesets predicted five LS and six SS with 100% accuracy. These preliminary data suggest that in vivo BCG responsiveness might be predictable by in vitro testing prior to therapy.
Methods; All probes were assigned a weight, (meanLs - meanss) / (stdevLs + stdevss). To pick probes that had differential mean expression between the LS and SS groups, the inventors selected probes with weight greater than 1.1 to vote. This gave a signature several hundred in length (6 hr media, 206; 6 hr BCG, 441; 24 hr media, 231 ; 24 hr BCG, 152). Each selected high weight probe was given a vote, (sample - (meanLS + meanSs)/2). The sum of the votes for all selected genes was used to make prediction of which class the sample belonged to, positive sum indicating a prediction for the LS class and negative sum for SS class.
Weight » mean LS - mean SS
stddev LS + stddev SS
Vote 58 x - mean LS * mean SS
2
Score - Ivofes^^
Score + LS (tong survivor}
Score - " SS {short survivor)
Results; High prediction accuracy was attained for the 6 hr BCG (100%), 24 hr media (91%), and 24 hr BCG (100%) groups.
For each probe, the inventors calculated a weight that describes how well the expression values in the two patient survival groups separated; the inventors selected genes with weight greater than 1.1 giving probe lists -100-400 in length. Voting for each gene reflects the distance from the midline between expression values in the LS and SS classes; the sum of votes for all selected genes was used to make predictions. Using these gene lists, high prediction accuracy was observed in the 6 hr BCG treated cells, 24 hr media treated cells, and the 24 hr BCG treated cells, but not in the 6 hr media treated cells.
EXAMPLE 2
Conserved gene expression changes between outcome groups in metastatic melanoma and leprosy
Methods; To put the PBMC survival profile in context, the inventors compared it to the subtypes of leprosy as they have known differences in anti-mycobacterial immune responses and have distinct clinical outcomes. Rank-Rank Hypergeometric Overlap (RRHO) analysis compares gene expression profiles from two independent microarray experiments and generates a gene list that has statistically significant overlap between the two expression profiles. The inventors observed that the gene expression profile of melanoma LS PBMCs has significant overlap with favorable outcome tuberculoid leprosy patients (n= 960, min hypergeometric p-value = 10"23'5, 24 hour BCG-treated cells) and the profile of melanoma SS PBMCs has significant overlap with unfavorable outcome lepromatous leprosy (n= 2003, min hypergeometric p-value = 10"16'9, 24 hour BCG-treated cells). The inventors performed Rank- Rank Hypergeometric Overlap (RRHO) analysis to compare gene expression profiles from treated melanoma PBMCs and from leprosy tissues (Dataset obtained from Montoya et al. 2009). The inventors represented two full expression profiles as ranked lists, ranked on the log t-test p-value between expression in the two groups signed positive for higher expression in SS/L-lep and negative for higher expression in LS/T-lep. The RRHO algorithm traverses both ranked lists incrementally, at each step calculating the significance (hypergeometric p- value) of the number of genes above the current rank in both ranked lists. This matrix of hypergeometric p-values is logio-transformed and converted to a heatmap. High positive values on the map indicate that the gene lists up to the ranks indicated on the axes are significantly overenriched for overlapping genes, while high negative indicate significant underenrichment for overlapping genes. The point at which the highest positive value or lowest negative value is reached defines the bounds above which the most significant overlapping gene set lies. Light grey lines are drawn on the map where the direction of the change in average expression switches from positive to negative; these lines define regions containing the most significant overlapping gene sets with conserved direction in both ranked gene lists (both gene expression profiles being compared).
Results; Having observed evidence of significant differential gene expression between melanoma patients with different prognostic outcomes, the inventors compared these profiles to those in established mycobacterial infection in which the clinical spectrum presents along a continuum of two poles: Lepromatous leprosy (L-lep) patients show progressive infection, with high bacterial loads in disseminated skin lesions while tuberculoid leprosy (T-lep) patients maintain a self-limited infection, with few bacteria in few skin lesions.
The inventors used Rank-Rank Hypergeometric Overlap (RRHO) analysis to compare gene expression profiles of patient survival groups in melanoma (short survivors SS vs long survivors LS) and between subtypes of leprosy (lepromatous leprosy L-lep vs tuberculoid leprosy T-lep). The inventors located the areas of highly significant overlap in two regions of the map corresponding to overlapping genes in (1) melanoma short survivors and lepromatous leprosy (unfavorable outcome, lower left region of the map, max = 23) and (2) melanoma long survivors and tuberculoid leprosy (favorable outcome, upper right region, max = 17). Results are shown in FIG. 3. Table 5. Overlapping Genes
Figure imgf000075_0001
The table shows the number of overlapping genes that contribute to these significant p-values, 960 and 2003, respectively. Genes in these lists will be tested in subsequent datasets to determine whether they have predictive value in the ability to respond to BCG immune stimulation in vivo and/or cancer survival.
EXAMPLE 3
Pathways analysis of overlapping T-lep/ LS and L-lep/SS genes
Methods; The functional groups and canonical pathways analyses were generated through the use of Ingenuity Pathways Analysis (IPA, Ingenuity® Systems, www.ingenuity.com). Probe sets identified by RRHO above which were comparatively increased in expression in T-lep vs. L-lep and LS vs SS melanoma patients were included in the analysis. Fischer's exact test was used to calculate a p-value determining the probability that each biological function is due to chance alone.
Results; The inventors used rank-rank hypergeometric overlap (RRHO) analysis to compare gene expression profiles of patient survival groups in melanoma (short-term survivors SS vs long-term survivors LS) and between subtypes of leprosy (lepromatous leprosy, L-lep vs tuberculoid leprosy, T-lep) (FIG. 3). The inventors represented each full expression profile as ranked lists, ranked on the log t-test p-value between expression in the two groups signed positive for higher expression in SS/L-lep and negative for higher expression in LS/T-lep. The RRHO algorithm traverses both ranked lists incrementally at each step calculating the significance (hypergeometric p-value) of the number of genes above the current rank in both ranked lists. This matrix of hypergeometric p-values is log10- transformed and converted to a heatmap. The inventors located the areas of most highly significant overlap in two regions of the map corresponding to overlapping genes in (1) melanoma short survivors and lepromatous leprosy (lower left region of the map, max = 23) and (2) melanoma long survivors and tuberculoid leprosy (upper right region, max = 17). The table shows the number of overlapping genes that contribute to these significant p-values, 960 and 2003, respectively.
To detect which gene sets or biological pathways are overrepresented LS melanoma and T-lep patients might be particularly relevant to improved host immunity, the inventors studied the genes identified by RRHO which showed significant overlap in T-lep vs. L-lep and LS vs SS using pathways analysis (Ingenuity® Systems, www.ingenuity.com). Shown are the top five functional groups and canonical pathways found (FIG. 4A and FIG. 4B). One of the top canonical pathways with an enrichment for genes in the canonical oncostatin M (p < 0.0009) and IL-6 signaling (p < 0.005) pathways (FIG. 4B) indicates these immunologic pathways may be relevant for further study in either prediction of survival or physiologically relevant pathways containing targets for therapeutic manipulation. Similarly the inventors studied the genes identified by RRHO which showed significant overlap in L-lep vs. T-lep and SS vs LS. Shown are the top five functional groups and canonical pathways found (FIG. 4C and FIG. 4D). A top functional pathway revealed enrichment for genes in the lysosomal pathway composed of 24 genes (p < 10-13, FIG. 4C). These findings suggest that it may be possible to identify patients who would benefit more from in vivo BCG immunostimulation for melanoma and to use an anti-mycobacterial cutaneous immune expression profile to filter favorable and unfavorable systemic immune signatures. The inventors anticipate using the anti-mycobacterial cutaneous immune expression profile to identify relevant predictive or physiologic genes and pathways in cancer survival. Taken together, these findings support the use of these methods to identify patients who may benefit more from in vivo BCG immunostimulation for melanoma (FIG. 2). An anti-mycobacterial cutaneous immune expression profile may be evaluated to identify favorable and unfavorable systemic immune signatures (FIG. 3 and 4).
EXAMPLE 4
Methods; The inventors investigated peripheral blood gene expression responses of melanoma patients prior to BCG administration in known "short-term survivors" (SS) versus "long-term survivors" (LS) to gain insight into BCG-induced immune pathways that may be important for melanoma survival.
For the first two experiments, 24 melanoma patients matched by age, sex and tumor burden were studied. Of the 24 patients, 13 survived less than 1.5 years (short-term survivors) and 1 1 survived greater than ten years (long-term survivors) after BCG immunostimulation. PBMCs collected prior to BCG administration were stimulated in vitro with either BCG or medium for six or 24 hours and analyzed by gene expression microarrays.
For the next experiment, PBMCs from 13 different melanoma patients (six LS vs. seven SS) who did not receive BCG therapy at any point during their disease were studied. These PBMCs were stimulated in vitro with either BCG or medium for six or 24 hours and analyzed by gene expression microarrays.
A spectrum of the melanoma patients tested is shown in FIG. 9. The general approach for the methods used in this example are shown in FIG. 10.
The SS and LS patients' expression patterns were compared and a list of gene probesets that were differentially expressed across the three experiments was identified. The genes were as follows: 1555845_at : no gene symbol, 1560271_at: no gene symbol, 1562673_at: no gene symbol, 216771_at: no gene symbol, 224105_x_at: no gene symbol, 236502_at: no gene symbol, 240534_at: no gene symbol, 244055_at: no gene symbol, AGR2, ATG5, C18orf25, C22orf39, CIRBP-AS1, CYP4B 1, EPHA1, HNR PD, LARS2, LTNC00472, LOCI 00509474 /// ZNF518A, LOC283038, MASP 1, METAP 1, MTF2, OCLN, PDLIM7, PWWP2B, RRN3P2, RRP7A, SMC1A, SRGAP1, TSC22D1, UBXN8, WDR25, and WDR87. Shown below are the probeset ID, the corresponding description and gene symbol and entrez ID if available.
Table 6. Select Probesets
Figure imgf000077_0001
1562673_at
226406_at chromosome 18 open reading frame 25 C18orf25 147339
1553974_at chromosome 22 open reading frame 39 C22orf39 128977
216771_at
1552868_at CIRBP antisense RNA 1 (non-protein CIRBP-AS1 148046 coding)
224105_x_at
236502_at
210096_at cytochrome P450, family 4, subfamily B, CYP4B1 1580 polypeptide 1
241482_at EPH receptor A1 EPHA1 2041
240534_at
229129_at heterogeneous nuclear ribonucleoprotein D HNRNPD 3184
(AU-rich element RNA binding protein 1 ,
37kDa)
244055_at
34764_at leucyl-tRNA synthetase 2, mitochondrial LARS2 23395
220324_at long intergenic non-protein coding RNA 472 LINC00472 79940
1557591_at uncharacterized LOC283038 LOC283038 283038
232224_at mannan-binding lectin serine peptidase 1 MASP1 5648
(C4/C2 activating component of Ra-reactive
factor)
212673_at methionyl aminopeptidase 1 METAP1 23173
203347_s_at metal response element binding MTF2 22823 transcription factor 2
1555468_at neuropilin 2 NRP2 8828
231022_at occludin OCLN 10050665
8
214122_at PDZ and LIM domain 7 (enigma) PDLIM7 9260
238046_x_at PWWP domain containing 2B PWWP2B 170394
243124_at RNA polymerase I transcription factor RRN3P2 653390 homolog (S. cerevisiae) pseudogene 2
33307_at ribosomal RNA processing 7 homolog A (S. RRP7A 27341 cerevisiae)
201589_at structural maintenance of chromosomes 1A SMC1A 8243
1569269_s_at SLIT-ROBO Rho GTPase activating protein SRGAP1 57522
1
239123_at TSC22 domain family, member 1 TSC22D1 8848
215983_s_at UBX domain protein 8 UBXN8 7993
219609_at WD repeat domain 25 WDR25 79446
224135_at WD repeat domain 87 WDR87 83889
204291_at uncharacterized LOC100509474 /// zinc LOC1005094 10050947
finger protein 518A 74 /// 4 /// 9849
ZNF518A
Table 7 below shows each probeset name (or its corresponding gene name if available) and the probability that it alone can predict LS or SS outcome (P value from univariable analysis), or the probability that it alone with ulceration can predict (P value from multivariable analysis : Single gene model + ulceration), or the probability that it in combination with other can predict with better accuracy (P value from multivariable analysis multiple gene model + ulceration). The probesets with the ability to predict with better accuracy are indicated in the seventh column by the presence of a P value.
Table 7. Data for Individual Probes for Predicting Outcome
Figure imgf000080_0001
Figure imgf000081_0001
The association of gene expression and clinical variables to overall survival of melanoma patients was examined by doing univariable and multivariable survival analysis using a Cox Proportional Hazard regression model. All 36 patients were used in the survival analysis with 24 events (deaths). Statistical significance was defined as a p- value <0.05. All the analyses were done using SAS 9.2 (Cary, NC).
Results: Univariable and multivariable survival analyses were done for prognostic variables such as breslow thickness, ulceration, # positive lymphnodes, age at diagnosis, primary melanoma body site and gender. Ulceration was the only clinical variable that was significantly associated with overall survival. Multivariable survival analyses were done incorporating significant clinical variable (ulceration) and a gene expression variable entered one at a time. This process revealed whether single gene / probeset still showed significant association to the survival time even when the ulceration was present in the model.
Along with ulceration, the high expression of genes / probesets such as 1555845_at, 1560271_at,1562673_at, 224105_x_at, 236502_at, 244055_at, AGR2, C18orf25, C22orf39, LARS2, LOC100509474 /// ZNF518A, LOC283038, METAP1, MTF2, , OCLN, SMC1A, UBXN8, WDR25 were significantly associated with better survival and the following genes were significantly associated with worse survival: 216771_at, 240534_at, CIRBP-AS1, CYP4B1, EPHA1, LINC00472, MASP1, RRN3P2, SRGAP1, WDR87.
Multivariable survival analysis was done incorporating ulceration and all the genomic variables listed above. The best parsimonious final model was obtained after applying the stepwise selection method (forward selection and backward elimination combined). This survival model with multiple genes had superior model fit to any other single gene survival models and this was determined by smallest AKAIKE information criteria.
Along with ulceration, the genes / probes represented in the Table below showed significant association to overall survival, with prediction ability superior to the individual probes + ulceration. High expression of AGR2, LOC283038, RRP7A and low expression of LINC00472, R N3P2 and 240534_at were significantly associated with better survival.
Table 6. Genes with significant association to overall survival.
Figure imgf000083_0001
* * *
All of the compositions and methods disclosed and claimed herein can be made and executed without undue experimentation in light of the present disclosure. While the compositions and methods of this invention have been described in terms of preferred embodiments, it will be apparent to those of skill in the art that variations may be applied to the compositions and methods and in the steps or in the sequence of steps of the method described herein without departing from the concept, spirit and scope of the invention. More specifically, it will be apparent that certain agents which are both chemically and physiologically related may be substituted for the agents described herein while the same or similar results would be achieved. All such similar substitutes and modifications apparent to those skilled in the art are deemed to be within the spirit, scope and concept of the invention as defined by the appended claims. REFERENCES
The following references, to the extent that they provide exemplary procedural or other details supplementary to those set forth herein, are specifically incorporated herein by reference.
Ausubel et al., In: Current Protocols in Molecular Biology, John Wiley & Sons, NY, 631-636, 2003.
Golub et al., Molecular classification of cancer: class discovery and class prediction by gene expression monitoring, Science, 286(5439):531-537, 1999. PubMed PMID: 10521349.
Montoya et al., Divergence of macrophage phagocytic and antimicrobial programs in leprosy, Cell Host Microbe, 6(4):343-353, 2009. PubMed PMID: 19837374.
Plaisier et al., Rank-rank hypergeometric overlap: identification of statistically significant overlap between gene-expression signatures, Nucleic Acids Res., 38(17):el69, 2010. PubMed PMID: 20660011.
Sambrook et al., In: Molecular cloning: a laboratory manual, 2nd Ed., Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY, 1989.

Claims

CLAIMS WHAT IS CLAIMED IS:
1. An in vitro method for providing a prognosis or prediction of response to a treatment with Bacillus Calmette-Guerin (BCG) in a subject with a cancer, said method comprising: a) culturing in vitro a first and second biological sample from the patient comprising cells in the presence and absence of Bacillus Calmette-Guerin, respectively, for a sufficient time and under conditions to permit gene expression by the cells; b) assessing the expression of one or more biomarkers selected from the group of biomarkers consisting of 240534_at, LOC283038, AGR2, RRP7A, LINC00472, and R N3P2 in the first and second cultured biological sample; c) providing a prognosis or prediction for the subject based on the expression information, such that an increase in expression of LINC00472, R N3P2, or 240534_at in the first biological sample as compared to the second biological sample indicates a poor survival, a high risk of recurrence, or a poor response to said treatment with Bacillus Calmette-Guerin, and an increase in expression of AGR2, LOC283038, or RRP7A in the first biological sample as compared to the second biological sample indicates a favorable survival, a low risk of recurrence, or a favorable response to said treatment with Bacillus Calmette-Guerin.
2. The method of claim 1, wherein said biomarkers comprise at least two of 240534_at, LOC283038, AGR2, RRP7A, LINC00472, or RRN3P2.
3. The method of claim 1, wherein said biomarkers comprise at least three of 240534_at, LOC283038, AGR2, RRP7A, LINC00472, or RRN3P2.
4. The method of claim 1, wherein said biomarkers comprise 240534_at, LOC283038, AGR2, RRP7A, LINC00472, and RRN3P2.
5. The method of claim 1, wherein the sample comprises a blood sample.
6. The method of claim 1, wherein the sample comprises peripheral blood mononuclear cells.
7. The method of claim 6, wherein said contacting or culturing comprises culturing peripheral blood mononuclear cells from the sample with BCG for from about 3 to about 9 hours.
8. The method of claim 7, wherein said contacting or culturing comprises culturing peripheral blood mononuclear cells from the sample with BCG for about 6 hours.
9. The method of claim 1, wherein the prognosis or prediction further comprises evaluating the presence or absence of ulceration of the cancer, wherein ulceration indicates a poor survival, a high risk of recurrence, or a poor response to said treatment with Bacillus Calmette-Guerin.
10. The method of claim 1, further comprising administering Bacillus Calmette-Guerin to the subject.
11. The method of claim 1 , wherein the cancer is a melanoma, breast cancer, colon cancer, lung cancer, bowel cancer, pancreatic cancer, or renal cancer.
12. The method of claim 11, wherein the cancer is a melanoma.
13. The method of claim 12, wherein the melanoma is a stage II, stage III, or stage IV melanoma.
14. The method of claim 13, wherein the melanoma is a stage III melanoma.
15. The method of claim 1, wherein said obtaining expression information comprises obtaining or receiving said sample.
16. The method of claim 15, wherein said sample is paraffin-embedded.
17. The method of claim 15, wherein said sample is frozen.
18. The method of claim 1, wherein said obtaining expression information comprises measuring expression of said one or more biomarkers.
19. The method of claim 18, wherein said obtaining expression information comprises RNA quantification.
20. The method of claim 19, wherein the RNA quantification comprises cDNA microarray, quantitative RT-PCR, in situ hybridization, Northern blotting or nuclease protection.
21. The method of claim 1, wherein said obtaining expression information comprises protein quantification.
22. The method of claim 21, wherein said protein quantification comprises immunohistochemistry, an ELISA, a radioimmunoassay (RIA), an immunoradiometric assay, a fluoroimmunoassay, a chemiluminescent assay, a bioluminescent assay, a gel electrophoresis, or a Western blot analysis.
23. The method of claim 1, wherein providing the prognosis or prediction comprises generating a classifier based on the expression, wherein the classifier is defined as a weighted sum of expression levels of the biomarkers.
24. The method of claim 1, wherein providing the prognosis or prediction comprises generating a weighted gene voting score.
25. The method of claim 23, wherein the classifier is generated on a computer.
26. The method of claim 23, wherein the classifier is generated by a computer readable medium comprising machine executable instructions suitable for generating a classifier.
27. The method of claim 23, wherein providing the prognosis or prediction comprises classifying a group of subjects based on the classifier associated with individual subjects in the group with a reference value.
28. The method of claim 1 , further comprising reporting said prognosis or prediction.
29. The method of claim 1, further comprising prescribing or administering an adjuvant therapy to said subject based on said prediction.
30. The method of claim 1, wherein a BCG therapy is prescribed or administered to the subject based on said prediction.
31. The method of claim 1, wherein a BCG therapy is not prescribed or administered to the subject based on said prediction.
32. The method of claim 1, wherein the cancer is a stage II cancer.
33. The method of claim 1, wherein the cancer is a stage III cancer.
34. The method of claim 1, wherein the cancer is a stage IV cancer.
35. A composition comprising Bacillus Calmette-Guerin (BCG) for use in treating cancer in a patient from whom a biological sample comprising cells has been tested by culturing in the presence of BCG and determined to exhibit an increase in expression of AGR2, LOC283038, or RRP7A as compared to such a sample that was not cultured in the presence of BCG.
36. The composition of claim 35, wherein the cancer is a melanoma.
37. A method of treating a patient having a cancer, comprising selecting an individual whose peripheral blood mononuclear cells express an increased level of at least one of AGR2, LOC283038, or RRP7A, relative to a reference expression level, as a result of culturing said cells with Bacillus Calmette-Guerin (BCG); and administering a BCG therapy to the subject.
38. The method of claim 37, wherein said selecting comprises measuring expression of said at least one of AGR2, LOC283038, or RRP7A in said peripheral blood mononuclear cells in vitro.
39. The method of claim 37, wherein the cancer is a melanoma.
40. An array comprising a plurality of antigen-binding fragments that bind to expression products of biomarkers or a plurality of primers or probes that bind to transcripts of the biomarkers to assess expression levels, the biomarkers comprising AGR2, LOC283038, RRP7A, LINC00472, RRN3P2, and 240534_at.
41. The array of claim 40, wherein the array is a microchip.
42. The array of claim 40, wherein the array is a cDNA microarray.
43. A kit comprising a plurality of antigen-binding fragments that bind to expression products of biomarkers or a plurality of primers or probes that bind to transcripts of the biomarkers to assess expression levels, the biomarkers comprising at least one of AGR2, LOC283038, RRP7A, LINC00472, RRN3P2, and 240534_at, wherein said kit is housed in a container.
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