CA2631236A1 - Methods and devices for identifying biomarkers of treatment response and use thereof to predict treatment efficacy - Google Patents

Abstract

The present invention features methods and devices for predicting the sensitivity of a patient to a compound or medical treatment. The invention also features methods for identifying gene biornarkers whose expression correlates to treatment sensitivity or resistance within a patient population or subpopulation.

Description

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METHODS AND DEVICES FOR IDENTIFYING BIOMARKERS OF TREATMENT
RESPONSE AND USE THEREOF TO PREDICT TREATMENT EFFICACY

FIELD OF THE INVENTION
The invention features methods and devices for identifying biomarkers of patient sensitivity to medical treatments, e.g., sensitivity to chemotherapeutic agents, and predicting treatment efficacy using the biomarkers.

BACKGROUND OF THE INVENTION
DNA microarrays have been used to measure gene expression in tumor samples from patients and to facilitate diagnosis. Gene expression can reveal the presence of cancer in a patient, its type, stage, and origin, and whether genetic mutations are involved. Gene expression may even have a role in predicting the efficacy of chemotherapy. Over recent decades, the National Cancer Institute (NCI) has tested compounds, including chemotherapy agents, for their effect in, limiting the growth of 60 human cancer cell lines. The NCI has also measured gene expression in those 60 cancer cell lines using DNA microarrays. Various studies have explored the relationship between gene expression and compound effect using the NCI
datasets.
During chemotherapy for cancers critical time is often lost due to a trial and error approach to fmding an effective therapy. In addition, cancer cells often develop resistance to a previously effective therapy. In such situations, patient outcome would be greatly improved by early detection of such resistance.
There remains a need for proven methods and devices that predict the sensitivity or resistance of cancer patients to a medical treatment.

SUMMARY OF THE INVENTION
The invention features methods and devices for predicting the sensitivity or resistance of a patient, e.g., a cancer patient, to a treatment, e.g., treatment with a compound, such as a chemotherapeutic agent, or radiation. In particular, the methods and devices can be used to predict the sensitivity or resistance of a cancer patient to any medical treatment, including, e.g., treatment with a compound, drug, or radiation. The devices and methods of the invention have been used to accurately predict treatment efficacy in cancer patients (e.g., patients with lung, lymphoma, and brain cancer) and can be used to predict treatment efficacy in patients diagnosed with any cancer.
Devices employing specific chemosensitivity/ chemoresistance biomarkers for the conunon chemotherapy drugs Vincristine, Cisplatin, Azaguanine, Etoposide, Adriamycin, Aclarubicin, Mitoxantrone, Mitomycin, Paclitaxel, Gemcitabine, Taxotere, Dexamethasone, Ara-C, Methylprednisolone, Methotrexate, Bleomycin, Methyl-(SAG, Carboplatin, 5-FU
(5-Fluorouracil), rituximab, radiation, histone deacetylase (HDAC) inhibitors, and 5-Aza-2'-deoxycytidine (Decitabine) are also provided. The methods and devices can be used to predict the sensitivity or resistance of a subject (e.g., a cancer patient) diagnosed with a disease condition, e.g., cancer (e.g., cancers of the breast, prostate, lung and bronchus, colon and rectum, urinary bladder, skin, kidney, pancreas, oral cavity and pharynx, ovary, tlzyroid, parathyroid, stomach, brain, esophagus, liver and intrahepatic bile duct, cervix larynx, heart, testis, small and large intestine, anus, anal canal and anoreotum, vulva, gallbladder, pleura, bones and joints, hypopharynx, eye and orbit, nose, nasal cavity and middle ear, nasopharynx, ureter, peritoneum, omentum and mesentery, or gastrointestines, as well as any form of cancer including, e.g., chronic myeloid leukemia, acute lymphocytic leukemia, non-Hodgkin lymphoma, melanoma, carcinoma, basal cell carcinoma, malignant mesothelioma, neuroblastoma, multiple myeloma, leukexnia, retinoblastoma, acute myeloid leukemia, chronic lymphocytic leukemia, Hodgkin lymphoma, carcinoid tumors, acute tumor, or soft tissue sarcoma) to a treatment, e.g., treatment with a compound or drug, e.g., a chemotherapeutic agent, or radiation.
In the first aspect, the invention features a method of predicting sensitivity of a cancer patient to a treatment for cancer by determining the expression level of at least one gene in a cell (e.g., a cancer cell) of the patient, in which the gene is selected from the group consisting of ACTB, ACTN4, ADA, ADAM9, ADAMTS 1, ADD 1, AF 1 Q, AIF1, AKAP 1, AKAP13, AKR1C1, AKT1, ALDH2, ALDOC, ALG5, ALMS1, ALOXI5B, AMIGO2, AMPD2, AMPD3,

2 ANAPC5, ANP32A, ANP32B, A.NXA1, AP1G2, APOBEC3B, APRT, ARHHE, ARHGAP15, ARHGAP25, ARHGDIB, ARHGEF6, ARL7, ASAHI, ASPH, ATF3, ATIC, ATP2A2, ATP2A3, ATP5D, ATP5G2, ATP6V1B2, BC008967, BCATI, BCHE, BCLIIB, BDNF, BHLHB2, BIN2, BLMH, BMI1, BNIP3, BRDT, BRRN 1, BTN3A3, Cl lozf2, C14orfl 39, C15ort25, Cl8orflO, Clorf24, CIorP29, Clorf38, CIQR1, C22orf18, C6orf32, CACNAIG, CACNB3, CALMI, CALML4, CALU, CAP350, CASP2, CASP6, CASP7, CAST, CBLB, CCNA2, CCNBIIPI, CCND3, CCR7, CCR9, CD1A, CD1C, CD1D, CD1E, CD2, CD28, CD3D, CD3E, CD3G, CD3Z, CD44, CD47, CD59, CD6, CD63, CD8A, CD8B1, CD99, CDCIO, CDC14B, CDH1 1, CDH2, CDKL5, CDKN2A, CDW52, CECR1, CENPB, CENTBI, CENTG2, CEP1, CGO18, CHRNA3, CHS1, CIAPINI, CKAP4, CKIP-1, CNP, COL4A1, COL5A2, COL6A1, COROIC, CRABPI, CRK, CRY1, CSDA, CTBP1, CTSC, CTSL, CUGBP2, CUTC, CXCL1, CXCR4, CXorf9, CYFIP2, CYLD, CYR61, DATF1, DAZAPI, DBN1, DBT, DCTNI, DDXl8, DDXS, DGKA, DIAPH1, DKCI, DKFZP434J154, DKFZP564C186, DKFZP564G2022, DKFZp564J157, DKFZP564K0822, DNAJCIO, DNAJC7, DNAPTP6, DOCK10; DOCK2, DPAGTI, DPEP2, DPYSL3, DSIPI, DUSP1, DXS9879E, EEFIB2, EFNB2, EHD2, EIF5A, ELK3, ENO2, EPAS1, EPB41L4B, ERCC2, ERG, ERP70, EVER1, EVI2A, EVL, EXTI, EZH2, F2R, FABP5, FAD104, FAM46A, FAU, FCGR2A, FCGR2C, FERIL3, FHL1, FHOD1, FKBPIA, FKBP9, FLJ10350, FLJ10539, FLJ10774, FLJ12270, FLJ13373, FLJ20859, FLJ21159, FLJ22457, FLJ35036, FLJ46603, FLNC, FLOT1, FMNLl, FNBPI, FOLHI, FOXF2, FSCN1, FTL, FYB, FYN, GOS2, G6PD, GALIG, GALNT6, GATA2, GATA3, GFPT1, GIMAP5, GIT2, GJAI, GLRB, GLTSCR2, GLUL, GMDS, GNAQ, GNB2, GNB5, GOT2, GPR65, GPRASPI, GPSM3, GRP58, GSTM2, GTF3A, GTSEI, GZMA, GZMB, H1F0, H1FX, H2AFX, H3F3A, HA-i, HEXB, HIC, HISTIH4C, HK1, HLA-A, HLA-B, HLA-DRA, HMGAl, HMGN2, ITMMR, HNRPAl, HNRPD, HNRPM, HOXA9, HRMTILI, HSA9761, HSPA5, HSU79274, HTATSFI, ICAM1, ICAM2, IER3, IFI16, IFI44, IFITM2, IFITM3, IFRG28, IGFBP2, IGSF4, IL13RA2, IL21R, IL2RG, IL4R, IL6, IL6R, IL6ST, IL8, IMPDH2, INPP5D, INSIGI, IQGAPl, IQGAP2, IRS2, ITGA5, ITM2A, JARIID2, JUNB, K-ALPHA-1, KHDRBS1, KIA.A0355, KIAA0802, KIA.A0877, KIAA0922, KIAA1078,

3 WO 2007/072225 _ PCT/IB2006/004048 K.IAA1128, KIAA1393, KIFCI, LAIR1, LAMB1, LAMB3, LAT, LBR, LCK, LCP1, LCP2, LEF1, LEPREI, LGALS1, LGALS9, LHFPL2, LNK, LOC54103, LOC55831, LOC81558, LOC94105, LONP, LOX, LOXL2, LPHN2, LPXN, LRMP, LRP12, LRRC5, LRRN3, LST1, LTB, LUM, LY9, LY96, MAGEB2, MAL, MAP1B, MAPILC3B, MAP4K1, MAPKI, MARCKS, MAZ, MCAM, MCL1, MCM5, MCM7, MDH2, MDNI, MEF2C, MFNG, MGC17330, MGC21654, MGC2744, MGC4083, MGC8721, MGC8902, MGLL, MLPH, MPHOSPH6, MPPI, MPZL1, MRP63, MRPS2, MT1E, MT1K, MUF1, MVP, MYB, MYL9, MYO I B, NAP I L 1, NAP I L2, NARF, NASP, NCOR2, NDN, NDUFABI, NDUFS6, NFKBIA, NIIID2, NIPA2, NME4, NME7, NNMT, NOL5A, NOL8, NOMO2, NOTCH1, NPC1, NQO1, NR1D2, NUDC, NUP210, NLTP88, NVL, NXFI, OBFC1, OCRL, OGT, OXA.IL, P2RX5, P4HA1, PACAP, PAF53, PAFAHIB3, PALM2-AKAP2, PAX6, PCBP2, PCCB, PFDN5, PFNI, PFN2, PGAMl, PHEMX, PHLDAI, PIM2, PITPNCI, PLAC8, PLAGL1, PLAUR, PLCB1, PLEK2, PLEKHCI, PLOD2, PLSCR1, PNAS-4, PNMA2, POLR2F, PPAP2B, PRF1, PRG1, PRIM1, PRKCH, PRKCQ, PRKD2, PRNP, PRP19, PRPF8, PRSS23, PSCDBP, PSMB9, PSMC3, PSME2, PTGER4, PTGES2, PTOV1, PTP4A3, PTPN7, PTPNS1, PTRF, PURA., PWP1, PYGL, QKI, RAB3GAP, RAB7L1, RAB9P40, RAC2, RAFTLIN, RAG2, R.AP1B, RASGRP2, RBPMS, RCN1, RFC3, RFC5, RGC32, RGS3, RHOH, RIMS3, RIOK3, RIl'K2, RIS1, RNASE6, RNF144, RPL10, RPLIOA, RPL12, RPL13A, RPL17, RPL18, RPL36A, RPLPO, RPLP2, RPS15, RPS19, RPS2, RPS4X, RPS4Y1, RRAS, RRAS2, RRBP1, RRM2, RUNX1, RLTNX3, S100A4, SART3, SATB1, SCAP1, SCARBI, SCN3A, SEC31L2, SEC61G, SELL, SELPLG, SEMA4G, SEPTIO, SEPT6, SERPINA1, SERPINBl, SERPINB6, SFRS5, SFRS6, SFRS7, SH2D1A, SH3GL3, SH3TC1, SHDI, SHMT2, SIATl, SKB1, SKP2, SLA, SLC1A4, SLC20A1, SLC25A15, SLC25A5, SLC39A14, SLC39A6, SLC43A3, SLC4A2, SLC7A11, SLC7A6, SMAD3, SMOX, SNRPA, SNRPB, SOD2, SOX4, SP140, SPANXC, SPI1, SRF, SRM, SSA2, SSBP2, SSRP1, SSSCAI, STAG3, STATI, STAT4, STAT5A, STC1, STC2, STOML2, T3JAM, TACC1, TACC3, TAF5, TAL1, TAP1, TARP, TBCA, TCF12, TCF4, TFDP2, TFPI, TIMMI7A, TIl1o1P1, TJP1, TK2, TM4SF1, TM4SF2, TM4SF8, TM6SF1, TMEM2, TMEM22, TMSBIO, TMSNB, TNFAIP3, TNFAIP8, TNFRSF10B, TNFRSFIA,

4

5 PCT/IB2006/004048 TNFRSF7, TN.IIC, TNPO1, TOB1, TOMIv12O, TOX, TPK1, TPM2, TRA@, TRAl, TRAM2, TRB@, TRD@, TRIM, TRIM14, TRIlVI22, TRIM28, TRIP13, TRPV2, TUBGCP3, TUSC3, TXN, TXNDCS, UBASH3A, UBE2A, UBE2L6, UBE2S, UCHL1, UCK2, UCP2, UFD1L, UGDH, ULK2, UMPS, UNG, USP34, USP4, VASP, VAV1, VLDLR, VWF, WASPIl', WBSCR20A, WBSCR20C, WHSC1, WNT5A, ZAP70, ZFP36LI, ZNF32, ZNF335, ZNF593, ZNFNIA1, and ZYX; in which change in the level of expression of the gene indicates the patient is sensitive or resistant to the treatment. In an embodiment, the method includes determining the expression of two of the listed genes, more preferably three, four, five, six, seven, eight, nine, or ten of the listed genes, and most preferably twenty, thirty, forty, fifty, sixty, seventy, eighty, ninety, or one hundred or more of the listed genes. In another embodiment, the change in the level of gene expression (e.g., an increase or decrease) is determined relative to the level of gene expression in a cell or tissue known to be sensitive to the treatment, such that a siunilar level of gene expression exhibited by a cell or tissue of the patient indicates the patient is sensitive to the treatment. In another embodiment, the change in the level of gene expression (e.g., an increase or decrease) is determined relative to the level of gene expression in a cell or tissue known to be resistant to the treatment, such that a similar level of gene expression exhibited by a cell or tissue of the patient indicates the patient is resistant to the treatment.
Izi another embodiment, the at least one gene=is selected from the group consisting of RPS4X, S100A4, NDUFS6, C14orfl 39, SLC25A5, RPL10, RPL12, EIF5A, RPL36A, BLMH, CTBP1, TBCA, MDH2, and DXS9879E, such-that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Vincristine.
Alternatively, the method.further inclildes measuring the expression level of at least one gene selected from the group consisting of UBB, B2M, MAN1A1, and SUI1, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Vincristine.
In another embodiment, the at least one gene is selected from the group consisting of C1QR1, SLA, PTPN7, ZNFNIAI, CENTB1, IFI16, ARHGEF6, SEC31L2, CD3Z, GZMB,' CD3D, MAP4K1, GPR65, PRF1, ARHGAPI5, TM6SF1, and TCF4, such that an increase in the' expression level of one or more of these genes indicates that the patient is sensitive to treatment with Cisplatin. Alternatively, the method further includes measuring the expression level of at least one gene selected from the group consisting ofHCLSl, CD53, PTPRCAP, and PTPRC, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Cisplatin.
In another embodiment, the at least one gene is selected from the group consisting of SRM, SCARBI, SIATl, CUGBP2, ICAM1, WASPIP, ITM2A, PALM2-AKAP2, PTPNS1, MPPl, LNK, FCGR2A, RUNX3, EVI2A, BTN3A3, LCP2, BCHE, LY96, LCP1, IFI16, MCAM, MEF2C, SLC1A4, FYN, Clorf38, CHS1, FCGR2C, TNIK, AMPD2, SEPT6, RAFTLIN, SLC43A3, RAC2, LPXN, CKIP-1, FLJ10539, FLJ35036, DOCK10, TRPV2, IFRG28, LEF1, and ADAMTS 1, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Azaguanine.
Alternatively, the method further includes measuring the expression level of at least one gene selected from the group consisting of MSN, SPARC, VIM, GAS7, ANPEP, EMP3, BTN3A2, FNI, and CAPN3, wherein an increase in expression of said gene indicates that said patient is sensitive to said treatment and wherein said treatment is treatment with Azaguanine_ In another embodiment, the at least one gene is selected from the group consisting of CD99, INSIGI, PRGI, MUFI, SLA, SSBP2, GNB5, MFNG, PSMB9, EVI2A, PTPN7, PTGER4, CXorf9, ZNFNIAI, CENTBI, NAPILI, HLA-DRA, IFI16, ARHGEF6, PSCDBP, SELPLG, LAT, SEC31L2, CD3Z, SH2DIA, GZMB, SCN3A, RAFTLIN, DOCK2, CD3D, RAC2, ZAP70, GPR65, PRF1, AR.HGAP15, NOTCH1, and UBASH3A, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Etoposide. Alternatively, the method further includes measuring the expression level of at least one gene selected from the group consisting of LAPTM5, HCLS
1, CD53, GMFG, PTPRCAP, PTPRC, CORO 1 A, and ITK, such that an increase in the expression level of one or more of these genes indicates that-the patient is sensitive to treatment with Etoposide.
In another embodiment, the at least one gene is selected from the group consisting of CD99, ALDOC, SLA, SSBP2, IL2RG, CXorf9, RHOH, ZNFNIAI, CENTBI, CD1C, MAP4K1,

6 CD3G, CCR9, CXCR4, ARHGEF6, SELPLG, LAT, SEC31L2, CD3Z, SH2D1A, CD1A, LAlR.l, TRB@, CD3D, WBSCR20C, ZAP70, IFI44, GPR65, AIF1, ARHGAPI5, NARF, and PACAP, such that an increase in the expression level of one or inore of these genes indicates that the patient is sensitive to treatment with Adriamyci.n. Alternatively, the method further includes measuring the expression level of at least one gene selected from the group consisting of LAPTM5, HCLSI, CD53, GMFG, PTPRCAP, TCF7, CD1B, PTPRC, CORO1A, HEMI, and ITK, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Adriamycin.
In another embodiment, the at least one gene is selected from the group consisting of RPL12, RPLP2, MYB, ZNFNIAI, SCAP1, STAT4, SP140, AMPD3, TNFAIP8, DDX18, TAFS, RPS2, DOCK2, GPR65, HOXA9, FLJ12270, and HNRPD, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Aclarubicin. Alternatively, the method further includes measuring the expression level of at least one gene selected from the group consisting of RPL32, FBL, and PTPRC, such that an inbrease in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Aclarubicin_ In another embodiment, the at least one gene is selected from the group consisting of PGAMI, DPYSL3, INSIGI, GJAI, BNIP3, PRG1, G6PD, PLOD2, LOXL2, SSBP2, Clorf29, TOX, STCl, TNFRSFIA, NCOR2, NAPILl, LOC94105, ARHGEF6, GATA3, TFPI, LAT, CD3Z, AFIQ, MAP1B, TR1M22, CD3D, BCAT1, IFI44, CUTC, NAPIL2, NME7, FLJ21159, and COL5A2, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Mitoxanthrone.
Alternatively, the method further includes measuring the expression level of at least one gene selected from the group consisting of BASPl, COL6A2, PTPRC, PRKCA, CCL2, and RAB3 1, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Mitoxantrone.
In another embodiment, the at least one gene is selected from the group consisting of STC1, GPR65, DOCK10, COL5A2, FAM46A, and LOC54103, such that an increase in the

7 expression level of one or more of these genes indicates that the patient is sensitive to treatment with Mitomycin.
In another embodiment, the at least one gene is selected from the group consisting of RPL10, RPS4X, NUDC, DKC1, DKFZP564C186, PRP19, RAB9P40, HSA9761, GMDS, CEP1, IL13RA2, MAGEB2, HMGN2, ALMS1, GPR65, FLJ10774, NOL8, DAZAPl, SLC25A15, PAF53, DXS9879E, PITPNCI, SPANXC, and KIAA1393, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treabment with Paclitaxel. Alternatively, the method further includes measuring the expression level of RALY, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Paclitaxel.
In another embodiment, the at least one gene is selected from the group consisting of PFN1, PGAMI, K-ALPHA-1, CSDA, UCHL1, PWP1, PALM2-AKAP2, TNFRSFIA, ATP5G2, AF 1 Q, NME4, and FHOD 1, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Gemcitabine.
In another embodiment, the at least one gene is selected from the group consisting of ANP32B, GTF3A, RRM2, TRIM14, SKP2, TRIP13, RFC3, CASP7, TXN, MCM5, PTGES2, OBFC1, EPB41L4B, and CALML4, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Taxotere.
In another embodiment, the at least one gene is selected from the group consisting of IFITM2, UBE2L6, USP4, ITM2A, IL2RG, GPRASP1, PTPN7, CXorf9, RHOH, GIT2, ZNI~~N1A1, CEPl, TNFRSF7, MAP4Ki, CCR7, CD3G, ATP2A3, UCP2, GATA3, CDKN2A, TARP, LAIR1, SH.2DIA, SEPT6, HA-1, ERCC2, CD3D, LSTI, AIF1, ADA, DATFl, ARHGAP 15, PLAC8, CECR1, LOCS 1558, and EHD2, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Dexamethasone. Alternatively, the method further includes measuring the expression level of at least one gene selected from the group consisting ofLAPTZVT5, ITGB2, ANPEP, CD53, CD37, ADORA2A, GNA15, PTPRC, COROIA, HEMl, FLII, and CREB3L1, such that an increase in the expression level of one or inore of these genes indicates that the patient is sensitive to

8 treatment with Deacainethasone.
In another embodiment, the at least one gene is selected from the group consisting of ITM2A, RHOH, PRIM1, CENTBI, NAP1L1, ATP5G2, GATA3, PRKCQ, SH2DIA, SEPT6, NME4, CD3D, CDlE, ADA, and FHOD 1, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Ara-C. Alternatively, the method fiurther includes measuring the expression level of at least one gene selected from the group consisting of GNA15, PTPRC, and RPL13, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Ara-C.
In another embodiment, the at least -one gene is selected from the group consisting of CD99, ARHGDIB, VWF, ITM2A, LGALS9, INPP5D, SATBl, TFDP2, SLA, IL2RG, MFNG, SELL, CDW52, LRMP, ICAM2, RIMS3, PTPN7, ARHGAP25, LCK, CXorf9, RHOH, GIT2, ZhTFNIA1, CENTBI, LCP2, SPI1, GZMA, CEP1, CD8A, SCAP1, CD2, CDIC, TNFRSF7, VAV1, MAP4K1, CCR7, C6orf32, ALOX15B, BRDT, CD3G, LTB, ATP2A3, NVL, RASGRP2, LCP1, CXCR4, PRKD2, GATA3, TRA@, K.IAA0922, TARP, SEC31L2, PRKCQ, SH2DIA, CHRNA3, CD1A, LST1, LAIRl, CACNAIG, TRB@, SEPT6, HA-1, DOCK2, CD3D, TRD@, T3JAM, FNBP1, CD6, AIF1, FOLH1, CDlE, LY9, ADA, CDKL5, TRIM, EVL, DATFl, RGC32, PRKCH, ARHGAP15, NOTCHl, BIN2, SEMA4G, DPEP2, CECRI, BCL1IB, STAG3, GALNT6, UBASH3A, PHEMX, FLJ13373, LEFl, IL21R, MGC17330, AKAP13, ZNF335, and GIMAP5, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive.to treatment with Methylprednisolone.
Alternatively, the method further includes measuring the expression level of at least one gene selected from the group consisting of SRRM1, LAPTM5, ITGB2; CD53, CD37, GMFG, PTPRCAP, GNAI5, BLM, PTPRC, COROIA, PRKCB1, HEMl, and UGT2B17, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Methylprednisolone.
I.n another embodiment, the at least one gene is selected from the group consisting of PRPF8, RPL18, GOT2, RPL13A, RPS15, RPLP2, CSDA, KHDRBS1, SNRPA, IMPDH2, RPS19, NUP88, ATP5D, PCBP2, ZNF593, HSU79274, PRIM1, PFDN5, OXA1L, H3F3A,

9 ATIC, CIAPINl, RPS2, PCCB, SHMT2, RPLPO, HNRPAI, STOML2, SKB1, GLTSCR2, CCNBIIPI, MRPS2, FLJ20859, and FLJ12270, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with'Methotrexate.
Alternatively, the method further includes measuring the expression level of at least one gene selected from the group consisting of RNPS 1, RPL32, EEF 1 G, PTMA, RPL 13, FBL, RBMX, and RPS9, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Methotrexate.
In another embodiment, the at least one gene is selected from the group consisting of PFN1, HKI, MCLI, ZYX, RAP1B, GNB2, EPAS1, PGAM1, CKAP4, DUSP1, MYL9, K-ALPHA-1, LGALSI, CSDA, IFITM2, ITGA5, DPYSL3, JUNB, NFKBIA, LAMBI, FHL1, INSIG1, TIlMP1, GJA1, PSME2, PRGl, EXT1, DKFZP434JI54, MVP, VASP, ARL7, NNMT, TAP1, PLOD2, ATF3, PALM2-AKAP2, IL8, LOXL2, IL4R, DGKA, STC2, SEC61G, RGS3, F2R, TPM2, PSMB9, LOX, STCI, PTGER4, IL6, SMAD3, WNT5A, BDNF, TNFRSFIA, FLNC, DKFZP564K0822, FLOT1, PTRF, HLA-B, MGC4083, TNFRSF10B, PLAGLI, PNMA2, TFPI, LAT, GZMB, CYR61, PLAUR, FSCNI, ERP70, AFIQ, HIC, COL6AI, IFITM3, MAP1B, FLJ46603, RAFTLIN, RRAS, FTL, KIAA0877, MT1E, CDC10, DOCK2, TRIM22, RISI, BCATI, PRF1, DBN1, MTIK, TMSB10, FLJ10350, Clorf24, NME7, TMEM22, TPK1, COL5A2, ELK3, CYLD, ADAMTSI, EFID2, and ACTB, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Bleomycin. Alternatively, the method further includes measuring the expression level of at least one gene selected from the group consisting of MSN, ACTR2, AKRIBI, VIIv1, ITGA3, OPTN, M6PRBP1, COL1A1, BASP1, ANPEP, TGFB1, NFIL3, NK4, CSPG2, PLAU, COL6A2, UBC, FGFRI, BAX, COL4A2, and .RAB31, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Bleomycin.
In another embodiment, the at least one gene is selected from the group consisting of SSRPI, NUDC, CTSC, APIG2, PSME2, LBR, EFNB2, SERPINAI, SSSCA1, EZH2, MYB, PRLM1, H2AFX, HMGA1, H1VIlVIR., TK2, WHSC1, DIAPHI, LAMB3, DPAGTI, UCK2, SERPTNBI, MDNI, BRRN1, GOS2, RAC2, MGC21654, GTSE1, TACC3, PLEK2, PLAC8, HNRPD, and PNAS-4, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Methyl-GAG.
Alternatively, the method furth.er includes measuring the expression level of PTMA, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Methyl-GAG.
In another embodiment, the at least one gene is selected from the group consisting of ITGA5, TNFAII'3, WNT5A, FOXF2, LOC94105, IFI16, LRRN3, DOCK10, LEPREI, COL5A2, and ADAMTS 1, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Carboplatin.
Alternatively, the method further includes measuring the expression level of at least one gene selected.from the group consisting of MSN, VIM, CSPG2, and FGFRl, such that an increase in.the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Carboplatin.
In another embodiment, the at least one gene is selected from the group consisting of RPL18, RPL10A, ANAPC5, EEF1B2, RPL13A, RPS15, AKAP1, NDUFABI, APRT, ZNF593, MRP63, IL6R, SART3, UCK2, RPL17, RPS2, PCCB, TOMM20, SHMT2, RPLPO, GTF3A, STOML2, DKFZp564J157, MRPS2, ALG5, and CALML4, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with 5-Fluorouracil (5-FU). Alternatively, the method fiu-ther includes measuring the expression level of at least one gene selected from the group consisting of RNPS 1, RPL13, RPS6, and RPL3, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with 5-Fluorouracil (5-FU).
In another embodiment, the at least one gene is selected from the group consisting of KIFC1, VLDLR, RUNX1, PAFAH1B3, H1FX, RNF144, TMSNB, CRY1, MAZ, SLA, SRF, UMPS, CD3Z, PRKCQ, HNRPM, ZA.P70, ADD1, RFC5, TM4SF2, PFN2, BMII, TUSGCP3, ATP6V1B2, CD1D, ADA, CD99, CD2, CNP, ERG, CD3E, CD1A, PSMC3, RPS4Y1, AKTl, TAL1, UBE2A, TCF12, UBE2S, CCND3, PAX6, RAG2, GSTM2, SATB1, NASP, IGFBP2, CDH2, CRABP1, DBN1, AKRICI, CACNB3, CASP2, CASP2, LCP2, CASP6, MYB, SFRS6, GLRB, NDN, GNAQ, TUSC3, GNAQ, JARID2, OCRL, FHL1, EZH2, SMOX, SLC4A2, UFD1L, ZNF32, HTATSFI, SHD1, PTOV I, NXF1, FYB, TRIlV128, BC008967, TRB@, H1F0, CD3D, CD3G, CENPB, ALDH2, A.NXA1, H2AFX, CDIE, DDX5, CCNA2, ENO2, SNRPB, GATA3, RRM2, GLUL, SOX4, MAL, UNG, ARHGDIB, RUNXI, MPHOSPH6, DCTN1, SH3GL3, PLEKHCI, CD47, POLR2F, RHOH, and ADD1, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Rituximab. A.lternatively, the method fiu-ther includes measuring the expression level of at least one gene selected from the group consisting of ITK, RALY, PSMC5, MYL6, CD 1 B, STMN1, GNA15, MDK, CAPG, ACTNI, CTNNAI, FARSLA, E2F4, CPSF1, SEPW1, TFRC, ABL1, TCF7, FGFR1, NUCB2, SMA3, FAT, VIM, and ATP2A3, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with Rituximab.
In another embodiment, the at least one gene is selected from the group consisting of .
TRAI, ACTN4, CALMI, CD63, FKBPIA, CALU, IQGAPI, MGC8721, STATI, TACCI, TM4SF8, CD59, CKAP4, DUSP1, RCN1, MGC8902, LGALSI, BHLHB2, RRBP1; PR1VP, IER3, MARCKS, LUM, FERIL3, SLC20A1, HEXB, EXTI, TJP1, CTSL, SLC39A6, RIOK3, CRK, NNMT, TRAM2, ADAM9, DNAJC7, PLSCRI, PRSS23, PLOD2, NPC1, TOBI, GFPT1, IL8, PYGL, LOXL2, KIAA0355, UGDH, PURA, ULK2, CENTG2, NID2, CAP350, CXCL1, BTN3A3, IL6, WNT5A, FOXF2, LPHN2, CDHI1, P4HA1, GRP58, DSIPI, MAPILC3B, GALIG, IGSF4, IRS2, ATP2A2, OGT, TNFRSF10B, K.IAA1128, TM4SF1, RBPMS, RIPK2, CBLB, NR1D2, SLC7AI 1, MPZL1, SSA2, NQOl, ASPH, ASAH1, MGLL, SERPINB6, HSPA5, ZFP36L1, COL4A1, CD44, SLC39A14, NIPA2, FKBP9, II,6ST, DKFZP564G2022, PPAP2B, MAP1B, MAPKl, MYO-IB, CAST, RRAS2, QKI, LHFPL2, 38970, ARHE, .KIAA1078, FTL, KIAA0877, PLCB1, KIAA.0802, RAB3GAP, SERPINBI, TIMM17A, SOD2, HLA-A, NOMO2, LOC55831, PHLDA1, TMEM2, MLPH, FAD104, LRRC5, RAB7L1, FLJ35036, DOCK10, LRP12, TXNDC5, CDC14B, HRMTILI, CORO1C, DNAJCIO, TNPOI, LONP, AMIGO2, DNAPTP6, and ADAMTS1, such that an increase in the expression level of one or moire of these genes indicates that the patient'is sensitive to treatment with radiation therapy. Alternatively, the method further includes measuring the expression level of at least one gene selected from the group consisting of WARS, CD8I, CTSB, PKM2, PPP2CB, CNN3, ANXA2, JAKI, E1F4G3, COL1A1, DYRK2, NFIL3,'ACTN1, CAPN2, BTN3A2, IGFBP3, FN1, COL4A2, and KPNB1, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treafirnent with radiation therapy.
In another embodiment, the at least one gene is selected from the group consisting of FAU, NOL5A, ANP32A, ARHGDIB, LBR, FABP5, ITM2A, SFRS5, IQGAP2, SLC7A6, SLA, IL2RG, MFNG, GPSM3, PIM2, EVER1, LRMP, ICAM2, RIMS3, FMNLl, MYB, PTPN7, LCK, CXorf9, RHOH, ZNFNIAI, CENTBI, LCP2, DBT, CEPI, IL6R, VAV1, MAP4KI, CD28, PTP4A3, CD3G, LTB, USP34, NVL, CD8B 1, SFRS6, LCP1, CXCR4, PSCDBP, SELPLG, CD3Z, PRKCQ, CDIA, GATA2, P2RX5, LAIRl, ClorP38, SH2D1A, TRB@, SEPT6, HA-1, DOCK2, WBSCR20C, CD3D, RNASE6, SFRS7, VVBSCR20A, NUP210, CD6, HNRPAl, AIF1, CYFIP2, GLTSCR2, C1Iorf2, ARHGAP15, BIN2, SH3TC1, STAG3, TM6SF1, C15orf25, FLJ22457, PACAP, and MGC2744, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with histone deacetylase (HDAC) inhibitor.
In another embodiment, the at least one gene is selected from the group consisting of CD99, SNRPA, CUGBP2, STAT5A, SLA, IL2RG, GTSE1, MYB, PTPN7, CXorf9, RHOH, ZNFNIAI, CENTBI, LCP2, HLSTIH4C, CCR7, APOBEC3B, MCM7, LCPI, SELPLG, CD3Z, PRKCQ, GZMB, SCN3A, LAIR1, SH2D1A, SEPT6, CGO18, CD3D, C18orfl0, PRFI, AIF1, MCM5, LPXN, C22orfl8, ARHGAP15, and LEF1, such that an increase in the expression level of one or more of these genes indicates that the patient is sensitive to treatment with 5-Aza-2'-deoxycytidine (Decitabine).
A second aspect of the invention features a method for determining the development of resistance by a patient (i.e,. a cell, such as a cancer cell, in the patient) to a treatment that the patient was previously sensitive to. The method includes determining the level of expression of one or more of the genes set forth in the first aspect of the invention, such that an increase in the expression level of a gene(s) which is decreased in a cell or tissue known to be sensitive to the treatment indicates that the patient is resistant to or has a propensity to become resistant to the treatment. Alterna.tively, an decrease in the expression level of a gene(s) which is increased in a cell or tissue known to be sensitive to the treatment indicates that the patient is resistant to or has a propensity to become resistant to the treatment.
A third aspect of the invention features a kit that includes a single-stranded nucleic acid (e.g., deoxyribonucleic acid or ribonucleic acid) that is complementary to or identical to at least 5 consecutive nucleotides (more preferably at least 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, or more consecutive nucleotides;
the nucleic acid can also be 5-20, 25, 5-50, 50-100, or over 100 consecutive nucleotides long) of at least one of the genes set forth in the first aspect of the invention, such that the single stranded nucleic acid is sufficient for the detection of expression of the gene(s) by allowing specific hybridization between the single stranded nucleic acid and a nucleic acid encoded by the gene, or a complement thereof. The kit further includes instructions for applying nucleic acids collected from a sample from a cancer patient (e.g., from a cell of the patient), determining the level of expression of the gene(s) hybridized to the single stranded nucleic acid, and predicting the patient's sensitivity to a treatment for cancer when use of the kit establishes that the expression level of the gene(s) is changes (i.e., increased or decreased relative to a control sample (i.e., tissue or cell) known to be sensitive or resitant to the treatment, as is discussed above in connection with the first aspect of the invention). In an embodiment, the instructions further indicate that an alteration in the expression level of the gene(s) relative to the expression of the gene(s) in a control sample (e.g., a cell or tissue known to be sensitive or resistant to the treatment) indicates a change in sensitivity of the patient to the treatment (i.e., a decrease in the level of expression of a gene known to be expressed in cells sensitive to the treatment indicates that the patient is becoming resistant to the treatment or is likely to become resistant to the treatment, and vice versa).
In an embodiment, the kit can be utilized to determine a patient's resistance or sensitivity to Vincristine, Cisplatin, Adriamycin, Etoposide, Azaguanine, Aclarubicin, Mitoxantrone, Paclitaxel, Mitomycin, Gemcitabine, Taxotere, Dexamethasone, Methylprednisolone, Ara-C, Methotrexate, Bleomycin, Methyl-GAG, Rituximab, histone deacetylase (HDAC) inhibitors, and 5-Aza-2'-deoxycytidine (Decitabine) by determining the expression level of one or more of the genes set forth in the first aspect of the invention and known to be increased in a patient sensitive to treatment with these agents (i.e., a patient is determined to be sensitive, or likely to be sensitive, to the indicated treatment if the level of expression of one or more of the gene(s) increases relative to the level of expression of the gene(s) in a control sample (i.e., a cell or tissue) in which increased expression of the gene(s) indicates sensitivity to the treatment, and vice versa).
In an embodiment, the nucleic acids are characterized by their ability to specifically identify nucleic acids complementary to the genes in a sample collected from a cancer patient.
A fourth aspect of the invention features a method of identifying biomarkers indicative of sensitivity of a cancer patient to a treatment for cancer by obtaining pluralities of measurements of the expression level of a gene (e.g., by detection of the expression of a gene using a single gene probe or by using multiple gene probes directed to a single gene) in different cell types and measurements of the growth of those cell types in the presence of a treatment for cancer relative to the growth of the cell types in the absence of the treatment for cancer;
correlating each plurality of ineasurements of the expression level of the gene in cells with the growth of the cells to obtain a correlation coefficient; selecting the median correlation coefficient calculated for the gene; and identifying the gene as a biomarker for use in determining the sensitivity of a cancer patient to said treatment for cancer if said =median correlation coefficient exceeds 0.3 (preferably the gene is identified as a biomarker for a patient's sensitivity to a treatment if the correlation coefficient exceeds 0.4, 0.5, 0.6, 0.7, 0.8. 0.9, 0.95, or 0.99 or more). In an embodiment, the method is performed in the presence of a second treatment.
A fifth aspect of the invention features a method of predicting sensitivity of a patient (e.g., a cancer patient) to a treatment for cancer by obtaining a measurement of a biomarker gene expression from a sample (e.g., a cell or tissue) from the patient; applying a model predictive of sensitivity to a treatment for cancer to the measurement, in which the model is developed using an algorithm selected from the group consisting of linear sums, nearest neighbor, nearest centroid, linear discriminant analysis, support vector machines, and neural networks; and predicting whether or not the patient will be responsive to the treatment for cancer. In an embodiment, the measurement is obtained by assaying gene expression of the biomarker in a cell known to be sensitive or resistant to the twreatment. In another embodiment, the model combines the outcomes of linear sums, linear discriminant analysis, support vector machines, neural networks, k-nearest neighbors, and nearest centroids, or the model is cross-validated using a random sample of multiple measurements. In another embodiment, treatment, e.g., a compound, has previously failed to show efficacy in a patient. In several embodiments, the linear sum is compared to a sum of a reference population with known sensitivity; the sum of a reference population is the median of the sums derived from the population members' biomarker gene expression. In another embodiment, the model is derived from the components of a data set obtained by independent component analysis or is derived from the components of a data set obtained by principal component analysis.
A sixth aspect of the invention features a kit, apparatus, and software used to implement the method of the fifth aspect of the invention.
In several embodiments of all aspects of the invention, the expression level of the gene(s) is determined by detecting the level of mRNA transcribed from the gene(s), by detecting the level of a protein product of the gene(s), or by detecting the level of the biological activity of a protein product of the gene(s). In further embodiments of all aspects of the invention, an increase or decrease in the expression level of the gene(s), relative to the expression level of the gene(s) in a cell or tissue sensitive to the treatment, indicates increased sensitivity of the cancer patient to the ,treatment. Alternatively, an increase or decrease in the expression level of the gene(s), relative to the expressiorri level of the gene(s) in a cell or tissue resistant to the treatment, indicates increased resistance of the cancer patient to the treatment. In another embodiment of all aspects of the invention, the cell is a cancer cell. In another embodiment of all aspects of the invention, the expression level of the gene(s) is measured using a quantitative reverse transcription-polymerase chain reaction (qRT-PCR). In an embodiment of all aspects of the invention, the level of expression of two of the listed genes is performed, more preferably the level of expression of three, four, five, six, seven, eight, nine, or ten of the listed genes is performed, and most preferably twenty, thirt.y, forty, fifty, sbcty, seventy, eighty, ninety, or one hundred or more of the listed genes is performed. In another embodiment of all aspects of the invention, the expression level of the gene(s) is determined using the kit of the third aspect of the invention.
In another embodiment of all aspects of the invention, the treatment is a compound, such as a chemotherapteutic agent selected from the group consisting of Vincristine, Cisplatin, Adriamycin, Etoposide, Azaguanine, Aclarubicin, Mitoxantrone, Paclitaxel, Mitomycin, Gemeitabine, Taxotere, Dexamethasone, Methylprednisolone, Ara-C, Methotrexate, Bleomycin, Methyl-GAG, Rituximab, histone deacetylase (HDAC) inhibitors, and 5-Aza-2'-deoxycytidine (Decitabine). In another embodiment of all aspects of the invention, the compound has previously failed to show effect in a subject (e.g., a subject selected from a subpopulation predicted to be sensitive to the treatment, a subject selected from a subpopulation predicted to die without treatment, a subject selected from a subpopulation predicted to have disease symptoms without treatment, a subject selected from a subpopulation predicted to be cured without treatment.
In another embodiment of all aspects of the invention, the treatment is, e.g., administration of a compound, a protein, an antibody, an oligonucleotide, a chemotherapeutic agent, or radiation to a patient. In an emobodiment of all aspects of the invention, the treatment is, e.g., a chemotherapeutic agent, such as, e.g., Vincristine, Cisplatin, Azaguanine, Etoposide, Adriamycin, Aclarubicin, Mitoxantrone, Mitomycin, Paclitaxel, Gemcitabine, Taxotere, Dexamethasone, Ara-C, Methylprednisolone, Methotrexate, Bleomycin, Methyl-GAG, Carboplatin, 5-FU (5-Fluorouracil), MABTHERATM (Rituximab), histone deacetylase (HDAC) inhibitors, 5-Aza-2'-deoxycytidine (Decitabine), alpha emitters such as astatine-211, bismuth-212, bismuth-213, lead-212, radium-223, actinium-225, and thorium-227, beta emitters such as tritium, strontium-90, cesium-137, carbon-11, nitrogen-13, oxygen-15, fluorine-18, iron-52, cobalt-55, cobalt-60, copper-61, copper-62, copper-64, zinc-62, zinc-63, arsenic-70, arsenic-71,.
arsenic-74, bromine-76, bromine-79, rubidium-82, yttrium-86, zirconium-89, indium-i 10, iodine-120, iodine-124, iodine-129, iodine-131, iodine-125, xenon-122, technetium-94m, technetium-94, technetium-99in, and technetium.-99, gamma ern.itters such as cobalt-60, cesium-137, and technetium-99m, Alemtuzumab, Daclizumab, Rituximab (MABTHERATm), Trastuzumab (HERCEPTINTM), Gemtuzurnab, Ibritumomab, Edrecolomab, Tositumomab, CeaVac, Epratuzum.ab, Mitumomab, Bevacizumab, Cetuximab, Edrecolomab, Lintuzumab, MDX-210, IGN-101, MDX-010, MAb, AME, ABX-EGF, EMD 72- 000, Apolizumab, Labetuzu.mab, ior-tl, MDX-220, MR.A, H-il scFv, Oregovomab, huJ591 MAb, BZL, Visilizumab, TriGem, TriAb, R3,1VIT-201, G-250, unconjugated, ACA-125, Onyva.x-105, CDP-860, BrevaRex MAb, AR54, IMC-1C11, GlioMAb-H, ING-1, Anti-LCG MAbs, MT-103, KSB-303, Therex, KW-2871, Anti-HMI.24, Anti-PTHrP, 2C4 antibody, SGN-30, TRAIL-RI
MAb, CAT, Prostate cancer antibody, H22xKi-4, ABX-MA1, Imuteran, Monopharm-C, Acivicin., Aclarubicin, Acodazole Hydrochloride, Acronine, Adozelesin, Adriamycin, Aldesleukin, Altretamine, Ambomycin, A. metantrone Acetate, Aminoglutethimide, Amsacrine, Anastrozole, Anthramycin, Asparaginase, Asperlin, Azacitidine, Azetepa, Azotomycin, Batimastat, Benzodepa, Bicalutamide, Bisantrene Hydrochloride, Bisnafide Dimesylate, Bizelesin, Bleomycin Sulfate, Brequinar Sodium, Bropirimine, Busulfan, Cactinomycin, Calusterone, Camptothecin, Caracemide, Carbetimer, Carboplatin, Carmustine, Carubicin Hydrochloride, Carzelesin, Cedefingol, Chlarambucil, Cirolemycin, Cisplatin, Cladribine, Combretestatin A-4, Crisnatol Mesylate, Cyclophosphamide, Cytarabine, Dacarbazine, DACA (N- [2-(Dimethyl-amino) ethyl] acridine-4-carboxamide), Dactinomycin, Daunorubicin Hydrochloride, Daunomycin, Decitabine, Dexormaplatin, Dezaguanine, Dezaguanine Mesylate, Diaziquone, Docetaxel, Dolasatins, Doxorubicin, Doxorubicin Hydrochloride, Droloxifene, Droloxifene Citrate, Dromostanolone Prapioriate, Duazomycin, Edatrexate, Eflornithine Hydrochloride, Ellipticine, Elsamitrucin, Enloplatin, Enpromate, Epipropidine, Epirubicin Hydrochloride, Erbulozole, Esorubicin Hydrochloride, Estramustine, Estramustine Phosphate Sodium, Etanidazole, Ethiodized Oil 113 1, Etoposide, Etoposide Phosphate, Etoprine, Fadrozole Hydrochloride, Fazarabine, Fenretinide, Floxuridine, Fludarabine Phosphate, Fluorouracil, 5-FdLTMP, Flurocitabine, Fosquidone, Fostriecin Sodium, Gemcitabine, Gemcitabine Hydrochloride, Gold Au 198, Homocamptothecin, Hydroxyurea, Idaru.bicin Hydrochloride, Ifosfamide, Iim.ofosine, Interferon Alfa-2a, Interferon Alfa-2b, Interferon Alfa-nl, Interferon Alfa-n3, Interferon Beta-I a, Interferon Gamma-I b, Iproplatin, Irinotecan Hydrochloride, Lanreotide Acetate, Letrozole, Leuprolide Acetate, Liarozole Hydrochloride, Lometrexol Sodium, Lomustine, Losoxantrone Hydrochloride, Masoprocol, Maytansine, Mechiorethamine Hydrochloride, Megestrol Acetate, Melengestrol Acetate, Melphalan, Menogaril, Mercaptopurine, Methotrexate, Methotrexate Sodium, Metoprine, Meturedepa, Mitindomide, Mitocarcin, Mitocromin, Mitogillin, Mitomalcin, Mitomycin, Mitosper, Mitotane, Mitoxantrone Hydrochloride, Mycophenolic Acid, Nocodazole, Nogalamycin,Ormaplatin, Oxisuran, Paclitaxel, Pegaspargase, Peliomycin, Pentamustine, PeploycinSulfate, Perfosfam.ide, Pipobroman, Piposulfan, Piroxantrone Hydrochloride, Plicamycin, Plomestane, Porfimer Sodium, Porfiromycin, Prednirn.ustine, Procarbazine Hydrochloride, Puromycin, Puromycin Hydrochloride, Pyrazofurin, Rhizoxin, Rhizoxin D, Riboprine, Rogletimide, Safingol, Safingol Hydrochloride, Semustine, Simtrazene, Sparfosate Sodium, Sparsomycin, Spirogermanium Hydrochloride, Spiromustine, Spiroplatin, Streptonigrin, Streptozocin, Strontium Chloride Sr 89, Sulofenur, Talisomycin, Taxane, Taxoid, Tecogalan Sodium, Tegafur, Teloxantrone Hydrochloride, Temoporfin, Teniposide, Teroxirone, Testolactone, Thiamiprine, Thioguanine, Thiotepa, Thymitaq, Tiazofurin, Tirapazarnine, Tomudex, TOP53, Topotecan Hydrochloride, Toreznifene Citrate, Trestolone Acetate, Triciribine Phosphate, Trimetrexate, Trimetrexate Glucuronate, Triptorelin, Tubulozole Hydrochloride, Uracil Mustard, Uredepa, Vapreotide, Verteporfin., Vinblastine, Vinblastine Sulfate, Vincristine, Vincristine Sulfate, Vindesine, Vindesine Sulfate, Vinepidine Sulfate, Vinglycinate Sulfate, Vinleurosine Sulfate, Vinorelbine.
Tartrate, Vinrosidine Sulfate, Vinzolidine Sulfate, Vorozole, Zeniplatin, Zinostatin, Zorubicin Hydrochloride, 2-Chlorodeoxyadenosine, 2' Deoxyformycin, 9-aminocamptothecin, raltitrexed, N-propargyl-5,8-dideazafolic acid, 2chloro-2'-arabino-fluoro-2'-deoxyadenosine, 2-chloro-2'-deoxyadenosine, anisomycin, trichostatin A, hPRL-G129R, CEP-75 1, linomide, sulfur mustard, nitrogen mustard (mechlor ethamine), cyclophosphamide, melphalan, chlorambucil, ifosfamide, busulfan, N-rnethyl-Nnitrosourea (MNU), N, N'-Bis (2-chloroethyl)-N-nitrosourea (BCNU), N-(2-chloroethyl)-N' cyclohexyl-N-nitrosourea (CCNU), N- (2-chloroethyl)-N'-(trans-4-~ . . . . . ., . . . . . .

methylcyclohexyl-N-nitrosourea (MeCCNiJ), N- (2-chloroethyl)-N'- (diethyl) ethylphosphonate-N-nitrosourea (fotemustine), streptozotocin, diacarbazine (DTIC), mitozolomide, temozolomide, thiotepa, mitomycin C, - AZQ, adozelesin, Cisplatin, Carboplatin, Ormaplatin, Oxaliplatin,C 1-973, DWA 2114R, JM216, JM335, Bis (platinum), tomudex, azacitidine, cytarabine, gemcitabine, 6-Mercaptopurine, 6-Thioguanine, Hypoxanthine, teniposide 9-amino camptothecin, Topotecan, CPT-l 1, Doxorubicin, Daunomycin, Epirubicin, darubicin, mitoxantrone, losoxantrone, Dactinomycin (Actinomycin D), amsacrine, pyrazoloacridine, all-trans retinol, 14-hydroxy-retro-retinol, all-trans retinoic acid, N- (4-Hydroxyphenyl) retinamide, 13-cis retinoic acid, 3-Methyl T7.'NEB, 9-cis retinoic acid, fludarabine (2-F-a.ra-AMP), 2-chlorodeoxyadenosine (2-Cda), 20-pi-1,25 dihydroxyvitamin D3, 5-ethynyluracil, abiraterone, aclarubicin, acylfulvene, adecypenol, adozelesin, aldesleukin, ALL-TK
antagonists, altretamine, ambamustine, amidox, amifostine, aminolevulinic acid, amrubicin, amsacrine, anagrelide, anastrozole, andrographolide, angiogenesis inhibitors, antagonist D, antagonist G, antarelix, anti-dorsalizing morphogenetic protein-1, antiandrogen, prostatic carcinoma, antiestrogen, antineoplaston, antisense oligonucleotides, aphidicolin glycinate, apoptosis gene modulators, apoptosis regulators, apurinic acid, ara-CDP-DL-PTBA, argininedeaminase, asulacrine, atamestane, atrimustine, axinastatin 1, axinastatin 2, axinasta.tin 3, azasetron, azatoxin, azatyrosine, baccatin III derivatives, balanol, batimastat, BCR/ABL
antagonists, benzochlorins, benzoylstaurosporine, beta lactam derivatives, beta-alethine, betaclamycin B, betulinic acid, bFGF inhibitor, bicalutamide, bisantrene, bisaziridinylspermine, bisnafide, bistratene A, bizelesin, breflate, bleomycin A2, bleomycin B2, bropirimine, budotitane, buthionine sulfoximine, calcipotriol, calphostin C, camptothecin derivatives (e.g., 10-hydroxy-camptothecin), canarypox IL-2, capecitabine, carboxamide-arnino-triazole, carboxyamidotriazole, CaRest M3, CARN 700, cartilage derived inhibitor, carzelesin, casein kinase inhibitors (ICOS), castanospermine, cecropin B, cetrorelix, chlorins, chloroquinoxaline sulfonamide, cicaprost, cis-porphyrin, cladribine, clomifene analogues, clotrimazole, collismycin A, collismycin B, combretastatin A4, combretastatin analogue, conagenin, crambescidin 816 , crisnatol, cryptophycin 8, cryptophycin A derivatives, curacin A, cyclopentanthraquinones, cycloplatam, cypemycin, cytarabine ocfosfate, cytolytic factor, cytostatin, dacliximab, decitabine, dehydrodidemnin B, 2'deoxycoform.ycin (DCF), deslorelin, dexifosfamide, dexrazoxane, dexverapanail, diaziquone, didemnin B, didox, diethylnorspermine, dihydro-5-azacytidine, dihydrotaxol, 9-, dioxamycin, diphenyl spiromustine, discodermolide, docosanol, dolasetron, doxifluridine, droloxifene, dronabinol, duocarrnycin SA, ebselen, ecomustine, edelfosine, edrecolomab, eflornithine, elemene, emitefur, epirubicin, epothilones (A, R =
H, B, R= Me), epithilones, epristeride, estramustine analogue, estrogen agonists, estrogen antagonists, etanidazole, etoposide, etoposide 4'-phosphate (etopofos), exemestane, fadrozole, fazarabine, fenretinide, filgrastim., finasteride, flavopiridol, flezelastine, fluasterone, fludarabine, fluorodaunorunicin hydrochloride, forfenimex, formestane, fostriecin, fotemustine, gadolinium texaphyrin, gallium nitrate, galocitabine, ganirelix, gelatinase inhibitors, gemcitabine, glutathione inbibitors, hepsulfam, heregulin, hexamethylene bisacetamide, homoharringtonine (HHT), hypericin, ibandronic acid, idarubicin, idoxifene, idramantone, ilmofosine, ilomastat, imidazoacridones, imiquimod, immunostimulant peptides, insulin-like growth factor-1 receptor inhibitor, interferon agonists, interferons, interleukins, iobenguane, iododoxorubicin, ipomeanol, 4-, irinotecan, iroplact, irsogladine, isobengazole, isohomohalicondrin B, itasetron, jasplakinolide, kahalalide F, lamellarin-N triacetate, lanreotide, leinamycin, lenograstim, lentinan sulfate, leptolstatin, letrozole, leukemia inhibiting factor, leukocyte alpha interferon, leuprolide +
estrogen + progesterone, leuprorelin, levamisole, liarozole, linear polyamine analogue, lipophilic disaccharide peptide, lipophilic platinum compounds, lissoclinamide 7, lobaplatin, lombricine, lometrexol, lonidamine, losoxantrone, lovastatin, loxoribine, lurtotecan, lutetium texaphyrin, lysofylline, lytic peptides, maytansine, mannostatin A, mari.mastat, masoprocol, maspin, matrilysin inhibitors, matrix metalloproteinase inhibitors, menogaril, merbarone, meterelin, methioninase, metocloprarnide, MIF' inhibitor, ifepristone, miltefosine, miru.nostim, mismatched double stranded RNA, mithracin, mitoguazone, mitolactol, mitomycin analogues, mitonafide, mitotoxin fibroblast growth factor-saporin, mitoxaxntrone, mofarotene, molgramostim, monoclonal antibody, human chorionic gonadotrophin, monophosphoryl lipid A+
myobacterium cell wall sk, znopidaznol, multiple drug resistance gene inhibitor, multiple tumor suppressor 1-based therapy, mustard anticancer agent, mycaperoxide B, mycobacterial cell wall.extxact, myriaporone, N-acetyldinaline, N-substituted benzarnides, nafarelin, nagrestip, naloxone +
pentazocine, napavin, naphterpin, nartograstixn, ii.edaplatin, nemorubicin, neridronic acid, neutral endopeptidase, nilutamide, nisamycin, nitric oxide modulators, nitroxide antioxidant, nitrullyn, 06-benzylguanine, octreotide, okicenone, oligonucleotides, onapristone, ondansetron, ondansetron, oracin, oral cytokine inducer, ormaplatin, osaterone, oxaliplatin, oxaunomycin, paclitaxel analogues, paclitaxel derivatives, palauamine, palmitoylrhizoxin, pamidronic acid, panaxytriol, panomifene, parabactin, pazelliptine, pegaspargase, peldesine, pentosan polysulfate sodium, pentostatin, pentrozole, perflubron, perfosfamide, perillyl alcohol, phenazinomycin, phenylacetate, phosphatase inhibitors, picibanil, pilocarpine hydrochloride, pirarubicin, piritrexim, placetin A, placetin B, plasminogen activator inhibitor, platinum complex, platinum compounds, platinum-t.riamine complex, podophyllotoxin, porf.uner sodium, porfiromycin, propyl bis-acridone, prostaglandin J2, proteasome inhibitors, protein A-based immune modulator, protein kinase C inhibitor, protein kinase C inhibitors, microalgal, protein tyrosine phosphatase inhibitors, purine nucleoside phosphorylase inhibitors, purpurins, pyrazoloacridine, pyridoxylated hemoglobin polyoxyethylene conjugate, raf antagonists, raltitrexed, ramosetron, ras famesyl protein transferase inhibitors, ras inhibitors, ras-GAP inhibitor, retelliptine demethylated, rhenium Re 186 etidronate, rhizoxin, ribozymes, RII retinamide, rogletimide, rohitukine, romurtide, roquiflirr-ex, rubiginone B 1, ruboxyl, safingol, saintopin, SarCNU, .
sarcophytol A, sargramostim, Sdi I mimetics, semustine, senescence derived inhibitor 1, sense oligonucleotides, signal transduction inhibitors, signal transduction modulators, single chain antigen binding protein, sizofiran, sobuzoxane, sodium borocaptate, sodium phenylacetate, solverol, somatomedin binding protein, sonermin, sparfosic acid, spicarnycin D, -spiromustine, splenopentin, spongistatin 1, squalamine, stem cell inhibitor, stem-cell division inhibitors, stipiamide, stromelysin inhibitors, sulfinosine, superactive vasoactive intestinal peptide antagonist, suradista, suramin., swainsonine, synthetic glycosaminoglycans, tallimustine, tamoxifen methiodide, tauromustine, tazarotene. , tecogalan sodium, tegafur, tellurapyrylium, _telomerase inhibitors, temoporfin, temozolomide, teniposide, tetrachlorodecaoxide, tetrazomine, thaliblastine, thalidomide, tbiocoraline, thrombopoietin, thrombopoietin mimetic, thymalfasin, thymopoietin receptor agonist, thymotrinan, thyroid stimulating hormone, tin ethyl etiopurpurin, tirapazamine, titanocene dicbioride, topotecan, topsentin, toremifene, totipotent stem cell factor, translation inhibitors, tretinoin, triacetyluridine, triciribine, trimetrexate, triptorelin, tropisetron, turosteride, tyrosine kinase inhibitors, tyrphostins, UBC inhibitors, ubenimex, urogenital sinus-derived growth inhibitory factor, urokinase receptor antagonists, vapreotide, variolin B, vector system, erythrocyte gene therapy, velaresol, veramine, verdins, verteporfin, vinorelbine, vinxaltine, vitaxin, vorozole, zanoterone, zeniplatin, zilascorb, or zinostatin stimalamer. In another embodiment of all aspects of the invention, a second treatment is utilized to determine gene expression in a sample from the patient.
In another embodiment of all aspects of the invention, the gene is selected from the group consisting of ABL1, ACTB, ACTN1, ACTN4, ACTR2, ADA, ADAM9, ADAMTS1, ADD1, ADORA2A, AF1Q, AIF1, AKAP1, AKAP13, AKR1B1, AKR1C1, AKT1, ALDH2, ALDH3A1, ALDOC, ALG5, ALMS 1, ALOX15B, AMIGO2, AMPD2, AMPD3, ANAPC5, ANP32A, ANP32B, ANPEP, ANXAI, ANXA2, AP1 G2, APOBEC3B, APRT, ARHE, ARHGAPI5, ARHGAP25, ARHGDIB, ARHGEF6, ARL7, ASAH1, ASPH, ATF3, ATIC, ATOX1, ATP1B3, ATP2A2, ATP2A3, ATP5D, ATP5G2, ATP6V1B2, B2M, BASP1, BAX, BC008967, BCAT1, BCHE, BCL11B, BDNF, BHLHB2, BIN2, BLM, BLMH, BLVRA, BMI1, BNIP3, BRDT, BRRN1, BTN3A2, BTN3A3, Cllorf2,, C14orfl39, C15orf25, Cl8orf10, Clorf24, Clorf29, Clorf38, C1QR1, C22orf18, C5orfI3, C6orf32, CACNAIG, CACNB3, CALDI, CALM1, CALML4, CALU, CAP350, CAPG, CAPN2, CAPN3, CASP2, CASP6, CASP7, CAST, CBFB, CBLB, CBRI, CBX3, CCL2, CCL21, CCNA2, CCNB1]P1, CCND3, CCR7, CCR9, CCT5, CD151, CD1A, CD1B, CD1C, CD1D, CD1E, CD2, CD28, CD37, CD3D, CD3E, CD3G, CD3Z, CD44, CD47, CD53, CD59, CD6, CD63, CD81, CDBA, CD8B1, CD99, CDC10, CDC14B, CDH11, CDH2, CDKL5, CDKN2A, CDW52, CECRI, CENPB, CENTBI, CENTG2, CEPI, CGO18, CHRNA3, CHS1, CIAPTNI, CKAP4, CK7P-1, CNN3, CNP, COL1A1, COL4A1;
COL4A2, COL5A2, COL6A1, COL6A2, COPA, COPEB, CORO1A, COROIC, COX7B, CPSF1, CRABP1, CREB3L1, CRIP2, CRK, CRY1, CSDA, CSPG2, CSRP1, CST3, CTBPI, ; = . , .. . . - . . .= . .

CTGF, CTNNAI, CTSB, CTSC, CTSD, CTSL, CUGBP2, CUTC, CX:CL1, CXCR4, CXorf9, CYFZP2, CYLD, CYR61, DATF1, DAZAPI, DBNl, DBT, DCTN1, DDOST, DDX18, DDX5, DGKA; DIAPHI, DIPA, DKC1, DKFZP434J154, DKFZP564CI86, DKFZP564G2022, DKFZp564J157, DKFZP564K0822, DNAJC10, DNAPTP6, DOCK10, DOCK2, DPAGTI, DPEP2, DPYSL3, DSIPI, DUSP1, DUSP3, DXS9879E, DYRK2, E2F4, ECE1, ECMl, EEF1A1, EEFIB2, EEF1G, EFNB2, EHD2, EIF2S2, EIF3S2, EIF4B, EIF4G3, EIF5A, ELA2B, ELK3, EMP3, EN02, EPASI, EPB41L4B, ERCC2, ERG, ERP70, EVERI, EVI2A, EVL, EXTI, EZH2, F2R, FABP5, FAD104, FAM46A, FARSLA, FAT, FAU, FBL, FCGR2A, FCGR2C, FER1L3, FGFR1, FHL1, FHOD1, FKBPIA, FKBP9, FLII, FLJ10350, FLJ10539, FLJ10774, FLJ12270, FLJ13373, FLJ20859, FLJ21159, FLJ22457, FLJ35036, FLJ46603, FLNC, FLOT1, FMNL1, FNI, FNBP1, FOLHl, FOXF2, FSCN1, FSTL1, FTHl, FTL, FYB, FYN, GOS2, G6PD, GALIG, GALNT6, GAPD, GAS7, GATA2, GATA3, GFPTI, GIMAP5, GIT2, GJAI, GLRB, GLTSCR2, GLUL, GMDS, GMFG, GNA15, GNAI2, GNAQ, GNB2, GNB5, GOT2, GPNMB, GPR65, GPRASPI, GPSM3, GRP58, GSTM2, GTF3A, GTSE1, GYPC, GZMA, GZMB, H1F0, H1FX, H2AFX, H3F3A, HA-I, HCLSI, HEMI, HEXB, HIC, HISTIH4C, HKl, HLA-A, HLA-B, BLA-DRA, HMGAl, HMGB2, HMGN2, HMMR, HNRPAl, HNRPD, HNRPM, HOXA9, HPRTI, HRMTILI, HSA9761, HSPA5, HSU79274, HTATSF1, HU6800, ICAM1, ICAM2, IER3, IFI16, IFI44, IFITM2, IFITM3, IFRG28, IGFBP2, IGFBP3, IGSF4, IL13RA2, IL21R, IL2RG, IL4R,1L6, IL6R, IL6ST, IL8, IMPDH2, INPP5D, INSIGI, IQGAPl, IQGAP2, IRS2, ITGA3, ITGA5, ITGB2, ITK, ITM2A, JAKI, JARID2, JUNB, K-ALPHA-i, KHDRBS 1, KTAA0220, KTA.A0355, KLAA0802, KIAA0877, KIA.A0922, KIAA1078, KIAA1128, KIAA1393, KIFC1, KPNB1, LAIRI, LAMB1, LAMB3, LAMRl, LAPTM5, LAT, LBR, LCK, LCP1, LCP2, LDHB, LEF1, LEPREI, LGALSI, LGALS9, LHFPL2, LMNB1, LNK, LOC54103, LOC55831, LOC81558, LOC94105, LONP, LOX,-LOXL2, LPHN2, LPXN, LRMP, LRP12, LRRC5, LRRN3, LSTI, LTB, LUM, LY9, LY96, M6PRBP1, MAD2LIBP, MAGEB2, MAL, MAN1A1, MAP1B, MAPILC3B, MAP4KI, MAPK1, MAPREI, MARCKS, MAZ, MCAM, MCL1, MCM5, MCM7, MDH2, MDK, MDN1, MEF2C, MFNG, MGC17330, MGC21654, MGC2744, MGC4083, MGC8721, MGC8902, MGLL, MIA, MICA, MLPH, MME, MMP2, MPHOSPH6; MPP1, MPZL1, MRP63, MRPL12, MRPS2, MSN, MT1E, MTIK, MUFI, MVP, MYB, MYC, MYL6, MYL9, MYOIB, NAPILI, NAP1L2, NARF, NARS, NASP, NBL1, NCL, NCOR2, NDN, NDUFAB1, NDUFS6, NFIL3, NFKBIA, NID2, NIPA2, NK4, NME4, NME7, NNMT, NOL5A, NOL8, NOMO2, NOTCH1, NPC1, NQOI, NRID2, NUCB2, NUDC, NCTP210, NUP88, NVL, NXF1, OBFC1, OCRL, OGT, OK/SW-c1.56, OPTN, OXA1L, P2RX5, P4HA1, PACAP, PAF53, PAFAHIB3, PALM2-AKAP2, PAX6, PBEF1, PCBP2, PCCB, PEA15, PFDN5, PFN1, PFN2, PGAMI, PGK1, PHEIVIX, PHLDA1, PIM2, PITPNC1, PKM2, PLAC8, PLAGLl, PLAU, PLAUR, PLCB1, PLEK2, PLEKHCI, PLOD2, PLSCRI, PNAS-4, PNMA2, POLR2F, PON2, PPAP2B, PPIA, PPIF, PPP1R11, PPP2CB, PRF1, PRG1, PRIM1, PRKCA, PRKCB1, PRKCH, PRKCQ, PRKD2, PRNP, PRP19, PRPF8, PRPS1, PRSS11, PRSS23, PSCDBP, PSMB9, PSMC3, PSMC5, PSME2, PTGER4, PTGES2, PTMA, PTOV1, PTP4A3, PTPN7, PTPNSI, PTPRC, PTPRCAP, PTRF, PTS, PURA, PWP1, PYGL,.QKI, R.AB31, RAB3GAP, RAB7, RAB7L1, RAB9P40, RAC2, RAFTLIN, RAG2, RALY, RAP1B, RASGRP2, RBMX, RBPMS, RCNI, REA, RFC3, RFC5, RGC32, RGS3, RHOC, RHOH, RIMS3, RIOK3, RIPK2, RIS1, RNASE6, RNF144, RNPS1, RPL10, RPL10A, RPLI1, RPL12, RPL13, RPL13A, RPL17, RPL18, RPL18A, RPL24, RPL3, RPL32, RPL36A, RPL39, RPL7, RPL9, RPLPO, RPLP2, RPS10, RPS I l, RPS15, RPS15A, RPS19, RPS2, RPS23, RPS24, RPS25, RPS27, RPS28, RPS4X, RPS4Yl, RPS6, RPS7, RPS9, RRAS, RRAS2, RRBP1, RRM2, RLTNXI, RUNX3, S100A13, S100A4, SART3, SATB1, SCAP1, SCARBI, SCARB2, SCN3A, SCTR, SEC31L2, SEC61G, SELL, SELPLG, SEMA4G, SEPT6, SEPT10, SEPWl, SERPINAI, SERPINBI, SERPINB6, SFRS3, SFRS5, SFRS6, SFRS7, SH2DIA, SH3GL3, SH3TC1, SHD1, SHFMI, SHMT2, SIAT1, SKBI, SKP2, SLA, SLC1A4, SLC20A1, SLC25A15, SLC25A5, SLC39A14, SLC39A6, SLC43A3, SLC4A2, SLC7A11, SLC7A6, SMA3, SMAD3, SMARCD3, SMOX, SMS, SND1, SNRPA, SNRPB, SNRPB2, SNRPE, SNRPF, SOD2, SOX4, SP140, SPANXC, SPARC, SPIl, SRF, SRM,-SRRM1, SSA2, SSBP2, SSRP1, SSSCAI, STAG3, STAT1, STAT4, STAT5A, STCI, STC2, STMN1, STOML2, SUIl, T3JAM, TACC1, TACC3, TAF5, TAGLN, TALl, TAP1, TARP, TBCA, TCF12, TCF4, TCF7, TFDP2, TFPI, TFRC, TGFB 1, TIlNIlv117A, TIMP l, ~" ."

TJP1, TK2, TM4SF1, TM4SF2, TM4SF8, TM6SF1, TMEM2, TMEM22, TMSBIO, TMSNB, TNFAlP3, TNFAIP8, TNFRSFIOB, TNFRSFIA, TNFRSF7, TNIK, TNPO1, TOB1, TOMM20, TOP2A, TOX, TPK1, TPM2, TRA@, TRA1, TRAM2, TRB@, TRD@, TRIM, TRIlvI14, TRIM22, TRIM28, TRIP13, TRPV2, TUBA3, TUBGCP3, TUFM, TUSC3, TXN, TXNDC5, UBASH3A, UBB, UBC, UBE2A, UBE2L6, UBE2S, UCHL1, UCK2, UCP2, UFD1L, UGCG, UGDH, UGT2B17, ULK2, UMPS, UNG, UROD, USP34, USP4, USP7, VASP, VAV1, VIM, VLDLR, VWF, WARS, WASPIP, WBSCR20A, WBSCR20C, WHSCI, WNT5A, XPOl, ZAP128, ZAP70, ZFP36LI, ZNF32, ZNF335, ZNF593, ZNFNIAI, or ZYX.
The nucleic acid sequence of each of the listed genes is publicly available through the Genbank database. The gene sequences are also included as part of the HG-U133A
GeneChip from Affymetrix, Inc.
"Resistant" or "resistance" as used herein means that a cell, a tumor, a person, or a living organism is able to withstand treatment, e.g., with a compound, such as a chemotherapeutic agent or radiation treatment, in that the treatment inhibits the growth of a cell, e.g., a cancer cell, in vitro or in a tumor, person, or living organism by less than 10%, 20 so,.30%, 40%, 50%, 60%, or 70% relative to the growth of a cell not exposed to the treatment. Resistance to treatment may be determined by a cell-based assay that measures the growth of treated cells as a function of the cells' absorbance of an incident light beam as used to perform the NCI60 assays described herein. In this example, greater absorbance indicates greater cell growth, and thus, resistance to the treatment. A smaller reduction in growth indicates more resistance to a treatment. By "chemoresistant" or "chemoresistance" is meant resistance to a compound.
"Sensitive" or "sensitivity" as used herein means that a cell, a tumor, a person, or a living organism is responsive to treatment, e.g., with a compound, such as a chemotherapeutic agent or radiation treatment, in that the treatment inhibits the growth of a cell, e.g., a cancer cell, in vitro or in a tumor, person, or living organism by 70%, 80%, 90%, 95%, 99% or 100%.
Sensitivity to treatment may be determined by a cell-based assay that measures the growth of treated cells as a function of the cells' absorbance of an incident light beam as used to perform the NCI60 assays described herein. In this example, lesser absorbance indicates lesser cell growth, and thus, sensitivity to the treatment. A greater reduction in growth indicates more sensitivity to the treatment. By " chemosensitive" or "chemosensitivity" is meant sensitivity to a compound.
"Complement" of a nucleic acid sequence or a"complementary" nucleic acid sequence as used herein refers to an oligonucleotide which is in "antiparallel association" when it is aligned with the nucleic acid sequence such that the 5' end of one sequence is paired with the 3' end of the other. Nucleotides and other bases may have complements and may be present in complementary nucleic acids. Bases not commonly found in natural nucleic acids that may be included in the nucleic acids of the present invention include, for example, inosine and 7-deazaguanine. "Complementarity" may not be perfect; stable duplexes of complementary nucleic acids may contain mismatched base pairs or urunatched bases. Those skilled in the art of nucleic acid technology can determine duplex stability empi.rically considering a number of variables including, for example, the length of the oligonucleotide, percent concentration of cytosine and guanine bases in the oligonucleotide, ionic strength, and incidence of mismatched base pairs.
When complementary nucleic acid sequences form a stable duplex, they are said to be "hybridized" or to "hybridize" to each other or it is said that "hybridization" has occurred.
Nucleic acids are referred to as being "complementary" if they contain nucleotides or nucleotide homologues that can form hydrogen bonds according to Watson-Crick base-pairing rules (e.g., G
with C, A with T or A with U) or other hydrogen bonding motifs such as for example diaminopurine with T, 5-methyl C with G, 2-thiothymidine with A, inosine with C, pseudoisocytosine with G, etc. Anti-sense RNA may be complementary to .other oligonucleotides, e.g., mRNA.
"Biomarker" as used herein indicates a gene whose expression indicates sensitivity or resistance to a treatment.
"Compound" as used herein means a chemical or biological substance, e.g., a drug, a protein, an antibody, or an oligonucleotide, which may be used to treat a disease or which has biological activity in vivo or in vitro. Preferred compounds may or may not be approved by the U.S. Food and Drug Administration (FDA). Preferred compounds include, e.g., chemotherapy agents that may inhibit cancer growth. Preferred chemotherapy agents include, e.g., Vincristine, WO 2007/072225 _ PCT/IB2006/004048 Cisplatin, *Azaguanine, Etoposide, Adriamycin, Aclarubicin, Mitoxantrone, Mitomycin, Paclitaxel, Gemcitabine, Taxotere, Dexamethasone, Ara-C, Methylprednisolone, Methotrexate, Bleomycin, Methyl-GAG, Carboplatin, 5-FU (5-Fluorouracil), MABTHERATm (Ritu.ximab), radiation, histone deacetylase (HDAC) inhibitors, and 5-Aza-2'-deoxycytidine (Decitabine).
Exemplary radioactive chemotherapeutic agents include compounds containing alpha emitters such as astatine-21 1, bismuth-212, bismuth-213, lead-212, radium-223, actinium-225, and thorium-227, beta emitters such as tritium, strontium-90, cesium-137, carbon-11, nitrogen-13, oxygen-15, fluorine-18, iron-52, cobalt-55, cobalt-60, copper-61, copper-62, copper-64, zinc-62, zinc-63, arsenic-70, arsenic-71, arsenic-74, bromine-76, bromine-79, rubidium-82, yttrium-86, zirconium-89, =indiunn-110, iodine- 120, iodine- 124, iodine- 129, iodine-131, iodine-125, xenon-122, technetium-94m, technetium-94, technetium-99m, and technetium-99, or gamma emitters such as cobalt-60, cesium-137, and technetium-99m. Exemplary chemotherapeutic agents also include antibodies such as Alemtuzumab, Daclizumab, Rituximab (MABTHERATm), Trastuzumab (IERCEPTINTm), Gemtuzumab, Ibritumomab, Edrecolomab, Tosituxnomab;
CeaVac, Epratuzumab, Mitumomab, Bevacizumab, Cetuximab, Edrecolomab, Lintuzumab, MDX-210, IGN-IOl, MDX-010, MAb, AME, ABX-EGF, EMD 72 000, Apolizumab, Labetuzumab, ior-t 1, MDX-220, MRA, H-1 i scFv, Oregovomab, huJ591 MAb, BZL, Visilizumab, TriGem, TriAb, R3, MT-201, G-250, unconjugated, ACA-125, Onyvax-105, CDP-860, BrevaRex MAb, AR54, IMC-1C11, GlioMAb-H, ING-1, Anti-LCG MAbs, MT-103, KSB-303, Therex, KW-2871, Anti-HMI.24, Anti-PTHrP, 2C4 antibody, SGN-30, TRAIL-RI
MAb, CAT, Prostate cancer antibody, H22xKi-4, ABX-MAl, Imuteran, and Monopharm-C.
Exemplary chemotherapeutic agents also include Acivicin; Aclarubicin;
Acodazole Hydrochloride; Acronine; Adozelesin; Adriamycin; Aldesleukin; Altretamine;
Alnbomycin; A.
metantrone Acetate; Aminoglutethimide; Amsacrine; Anastrozole; Anthramycin;
Asparaginase;
Asperlin; Azacitidine; Azetepa; Azotomycin; Batimastat; Benzodepa;
Bicalutamide; Bisantrene Hydrochloride; Bisnafide Dimesylate; Bizelesin; Bleomycin Sulfate; Brequinar Sodium;
Bropirimine; Busulfatk; Cactinomycin; Calusterone; Camptothecin; Caracemide;
Carbetimer;
Carboplatin; Carm.ustine; Carubicin Hydrochloride; Carzelesin; Cedefingol;
Chlorambucil;

Cirolemycin; Cisplatin; Cladribine; Combretestatin A-4; Crisnatol Mesylate;
Cyclophosphamide;
Cytarabine; Dacarbazine; DACA (N- [2- (Dimethyl-amino) ethyl] acrid.ine-4-carboxamide);
Dactinomycin; Daunorubicin. Hydrochloride; Daunomycin;. Decitabine;
Dexorrnaplatin;
Dezaguanine; Dezaguanine Mesylate; Diaziquone; Docetaxel; Dolasatins;
Doxorubicin;
Doxorubicin Hydrochloride; Droloxifene; Droloxifene Citrate; Dromostanolone Propionate;
Duazomycin; Edatrexate; Eflornithine .Hydrochloride; Ellipticine;
Elsamitrucin; Enloplatin;
Enpromate; Epipropidine; Epirubicin Hydrochloride; Erbulozole; Esorubicin Hydrochloride;
Estramustine; Estramustine Phosphate Sodium; Etanidazole; Ethiodized Oil 113 1; Etoposide;
Etoposide Phosphate; Etoprine; Fadrozole Hydrochloride; Fazarabine;
Fenretinide; Floxuridine;
Fludarabine Phosphate; Fluorouracil; 5-FdUMP; Flurocitabine; Fosquidone;
Fostriecin Sodium;
Gemcitabine; Gemcitabine Hydrochloride; Gold Au 198; Homocanmptothecin;
Hydroxyurea;
Idarubicin Hydrochloride; Ifosfamide; Ilmofosine; Interferon Alfa-2a;
Interferon Alfa-2b;
Interferon Alfa-nl; Interferon Alfa-n3; Interferon Beta-I a; Interferon Gamma-I b; Iproplatin;
Irinotecan Hydrochloride; Lanreotide Acetate; Letrozole; Leuprolide Acetate;
Liarozole Hydrochloride; Lometrexol Sodium; Lomustine; Losoxantrone Hydxochloride;
Masoprocol;
Maytansine; Mechlorethamine Hydrochloride; Megestrol Acetate; Melengestrol Acetate;
Melphalan; Menogaril; Mercaptopurine; Methotrexate; Methotrexate Sodium;
Metoprine;
Meturedepa; Mitindomide; Mitocarcin; Mitocromin; Mitogillin; Mitomalcin;
Mitomycin;
Mitosper; Mitotane; Mitoxantrone Hydrochloride; Mycophenolic Acid; Nocodazole;
Nogalamycin;Ormaplatin; Oxisuran; Paclitaxel; Pegaspargase; Peliomycin;
Pentamustine;
PeploycinSulfate; Perfosfamide; Pipobroman; Piposulfan; Piroxantrone Hydrochloride;
Plicamycin; Plomestane; Porfimer Sodium; Porfiromycin; Prednimustine;
Procarbazine Hydrochloride; Puromycin; Puromycin Hydrochloride; Pyrazofurin; Rhizoxin;
Rhizoxin D;
Riboprine; Rogletiunide; Safingol; Safingol Hydrochloride; Semustine;
Simtrazene; Sparfosate Sodium; Sparsomycin; Spirogermanium Hydrochloride; Spiromustine; Spiroplatin;
Streptonigrin; Streptozocin; Strontium Chloride Sr 89; Sulofenur; Talisomycin;
Taxane; Taxoid;
Tecogalan Sodium; Tegafur; Teloxantrone Hydrochloride; Temoporfin; Teniposide;
Teroxirone;
Testolactone; Thiainiprine; Thioguanine; Thiotepa; Thymitaq; Tiazofurin;
Tirapazamine;

Tomudex; TOPS3; Topotecan Hydrochloride; Toremifene Citrate; Trestolone Acetate;
Triciribine Phosphate; Trimetrexate; Trimetrexate Glucuronate; Triptorelin;
Tubulozole Hydrochloride; Uracil Mustard; Uredepa; Vapreotide; Verteporfin; Vinblastine;
Vinblastine Sulfate; Vincristine; Vincristine Sulfate; Vindesine; Vindesine Sulfate;
Vinepidine Sulfate;
Vinglycinate Sulfate; Vinleurosine Sulfate; Vinorelbine Tartrate; Vinrosidine Sulfate;
Vinzolidine Sulfate; Vorozole; Zeniplatin; Zinostatin; Zorubicin Hydrochloride; 2-Chlorodeoxyadenosine; 2' Deoxyformycin; 9-aminocamptothecin; raltitrexed; N-propargyl-5,8-dideazafolic acid; 2chloro-2'-arabino-fluoro-2'-deoxyadenosine; 2-chloro-2'-deoxyadenosine;
anisomycin; trichostatin A; hPRL-G129R; CEP-75 1; linomide; sulfur mustard;
nitrogen mustard (mechlor ethamine); cyclophosphamide; melphalan; chlorambucil; ifosfamide;
busulfan; N-methyl Nnitrosourea (1VDVU); N, N'-Bis (2-chloroethyl)-N-nitrosourea (BCNU); N-(2-chloroethyl)-N' cyclohexyl N-nitrosourea (CCNU); N- (2-chloroethyl)-N'- (trans-methylcyclohexyl-N-nitrosourea (MeCCNU); N- (2-chloroethyl)-N'- (diethyl) ethylphosphonate-N-nztrosourea (fotemustine); streptozotocin; diacarbazine (DTIC);
mitozolomide; temozolomide;
thiotepa; rnitomycin C; AZQ; adozelesin; Cisplatin; Carboplatin; Ormaplatin;
Oxaliplatin;Cl-973; DWA 2114R; JM216; JM335; Bis (platinum); tomudex; azacitidine;
cytarabine;
gemcitabine; 6-Mercaptopurine; 6-Thioguanine; Hypoxanthine; teniposide 9-amino camptothecin; Topotecan; CPT-11; Doxorubicin; Daunomycin; Epirubicin;
darubicin;
mitoxantrone; losoxantrone; Dactinomycin (Actinomycin D); amsacrine;
pyrazoloacridine; all-trans retinol; 14-hydroxy-retro-retinol; all-trans retinoic acid; N- (4-Hydroxyphenyl) retinamide;
13-cis retinoic acid; 3-Methyl TTNEB; 9-cis retinoic acid; fludarabine (2-F-ara-AMP); or 2-chlorodeoxyadenosine (2-Cda).
Other chemotherapeutic agents include, but are not limited to, 20-pi-1,25 dihydroxyvitarnin D3; 5-ethynyluracil; abiraterone; aclarubicin; acylfulvene;
adecypenol;
adozelesin; aldesleukin; ALL-TK antagonists; altretamine; ambamustine; amidox;
amifostine;
aminolevulinic acid; amrubicin; amsacrine; anagrelide; anastrozole;
andrographolide;
angiogenesis inhibitors; antagonist D; antagonist G; antarelix; anti-dorsalizing morphogenetic protein-l; antiandrogen, prostatic carcinoma; antiestrogen; antineoplaston;
antisense oligonucleotides; aphidicolin glycinate; apoptosis gene modulators; apoptosis regulators;
apurinic acid; ara-CDP-DL-PTBA; argininedeaminase; asulacrine; atamestane;
atrimustine;
axinastatin 1; axinastatin 2; axinastatin 3; azasetron; azatoxin; azatyrosine;
baccatin IlT
derivatives; balanol; batimastat; BCR/ABL antagonists; benzochlorins;
benzoylstaurosporine;
beta lactam derivatives; beta-alethine; betaclam.ycin B; betulinic acid; bFGF
inliibitor;
bicalutamide; bisantrene; bisaziridinylspermine; bisnafide; bistratene A;
bizelesin; breflate;
bleomycin A2; bleomycin B2; bropirimine; budotitane; buthionine sulfoximine;
calcipotriol;
calphostin C; camptothecin derivatives (e.g., 10-hydroxy-camptoth.ecin);
canarypox IL-2;
capecitabine; carboxaznide-amino"triazole; carboxyanzidotriazole; CaRest M3;
CARN 700;
cartilage derived inhibitor; carzelesin; casein kinase inhibitors (ICOS);
castanospermine;
cecropin B; cetrorelix; chiorin.s; chloroquinoxaline sulfonamide; cicaprost;
cis-porphyrin;
cladribine; clomifene analogues; clotrimazole; collismycin A ; collismycin B;
combretastatin A4;
combretastatin analogue; conagenin; crambescidin 816 ; crisnatol; cryptophycin 8; cryptophycin-A derivatives; curacin A; cyclopentanthraquinones; cycloplatarn; cypemycin;
cytarabine ocfosfate; cytolytic factor; cytostatin; dacliximab; decitabine;
dehydrodidemnin B;
2'deoxycoformycin (DCF); deslorelin; dexifosfamide; dexrazoxane; dexverapamil;
diaziquone;
didemnin B; didox; diethylnorspermine; dihydro-5-azacytidine; dihydrotaxol, 9-; dioxamycin;
diphenyl spiromustine; discodermolide; docosanol; dolasetron; doxifluridine;
droloxifene;
dronabinol; duocarmycin SA; ebselen; ecomustine; edelfosine; edrecolomab;
eflornithine;
elemene; emitefur; epirubicin; epothilones (A,. R= H; B, R = Me); epithilones;
epristeride;
estramustine analogue; estrogen agonists; estrogen antagonists; etanidazole;
etoposide; etoposide 4'-phosphate (etopofos); exemestane; fadrozole; fazarabine; fenretinide;
filgrastim; fmasteride;
flavopiridol; flezelastine; fluasterone; fludarabine; fluorodaunorunicin hydrochloride;
forfenimex; formestane; fostriecin; fotemustine; gadolinium texaphyrin;
gallium nitrate;
galocitabine; ganirelix; gelatinase inhibitors; gemcitabine; glutathiorie inhibitors; hepsulfam;
heregulin; hexamethylene bisacetamide; homoharringtonine (HHT); hypericin;
ibandronic acid;
idarubicin; idoxifene; idramantone; ilmofosine; ilomastat; irnidazoacridones;
imiquimod;
ixnmunostimulant peptides; insulin-like growth factor-1 receptor inhibitor;
interferon agonists;

interferons; interleukins; iobenguane; iododoxorubicin; iporrieanol, 4- ;
irinotecan; iroplact;
irsogladine; isobengazole; isohomohalicondrin B; itasetron; jasplakinolide;
kahalalide F;
lamellarin-N triacetate; lanreotide; leinamycin; lenograstim; lentinan sulfate; leptolstatin;
=
letrozole; leukemia inhibiting factor; leukocyte alpha interferon; leuprolide.
+ estrogen +
progesterone; leuprorelin; levamisole; liarozole; linear polyamin.e analogue;
lipophilic disaccharide peptide; lipophilic platinum compounds; lissoclinamide 7;
lobaplatin; lombricine;
lometrexol; lonidamine; losoxantrone; lovastatin; loxoribine; lurtotecan;
lutetium texaphyrin;
lysofylline; lytic peptides; maytansine; mannostatin A; marimastat;
masoprocol; maspin;
matrilysin inhibitors; matrix metalloproteinase inhibitors; menogaril;
rnerbarone; meterelin;
methioninase; metoclopramide; MIF inhibitor; ifepristone; miltefosin.e;
mirimostim; mismatched double stranded RNA; mithracin; mitoguazone; mitolactol; mitomycin analogues;
mitonafide;
mitotoxin fibroblast growth factor-saporin; mitoxantrone; mofarotene;
motgramostim;
monoclonal antibody, human chorionic gonadotrophin; monophosphoryl lipid A +
myobacterium cell wall sk; mopidamol; multiple drug resistance gene inhibitor; multiple tumor suppressor 1-based therapy; mustard anticancer agent; mycaperoxide B; mycobacterial cell wall extract;
myriaporone; N-acetyldinaline; N-substituted benzamides; nafarelin; nagrestip;
naloxone +
pentazocine; napavin; naphterpin; nartograstim; nedaplatin; nemorubicin;
neridronic acid; neutral endopeptidase; nilutamide; nisamycin; nitric oxide modulators; nitroxide antioxidant; nitrullyn;
06-benzylgu.anine; octreotide; okicenone; oligonucleotides; onapristone;
ondansetron;
ondansetron; oracin; oral cytokine inducer; ormaplatin; osaterone;
oxaliplatin; oxaunomycin;
paclitaxel analogues; paclitaxel derivatives; palauamine; palmitoylrhizoxin;
pamidronic acid;
panaxytriol; paiaomifene; parabactin; pazelliptine; pegaspargase; peldesine;
pentosan polysulfate sodium; pentostatin; pentrozole; perflubron; perfosfamide; perillyl alcohol;
phenazinomycin;
phenylacetate; phosphatase inhibitors; picibanil; pilocarpine hydrochloride;
pirarubicin;
piritrexim; placetin A; placetin B; plasminogen activator inhibitor; platinum complex; platinum compounds; platinum-triamine complex; podophyllotoxin; porfimer sodium;
porfiromycin;
propyl bis-acridone; prostaglandin J2; proteasome inhibitors; protein A-based immune modulator; protein kinase C inhibitor; protein kinase C inhibitors, rnicroalgal; protein tyrosine phosphatase inhibitors; purine nucleoside phosphorylase inhibitors; purpurins;
pyrazoloacridine;
pyridoxylated hemoglobin polyoxyethylene conjugate; raf antagonists;
raltitrexed; ramosetron;
ras farnesyl protein transferase inhibitors; ras inhibitors; ras-GAP
inhibitor; retelliptine demethylated; rhenium Re 186 etidronate; rhizoxin; ribozymes; RII retinamide;
rogletimi.de;
rohitukine; romurtide; roquinimex; rubiginone B 1; ruboxyl; safingol;
saintopin; SarCNYJ;
sarcophytol A; sargramostim; Sdi 1 mimetics; semustine; senescence derived inhibitor 1; sense oligonucleotides; signal transduction inhibitors; signal transduction modulators; single chain antigen binding protein; sizofiran; sobuzoxane; sodium borocaptate; sodium phenylacetate;
solverol; somatomedin binding protein; sonermin; sparfosic acid; spicamycin D;
spiromustine;
splenopentin; spongistatin 1; squalamine; stem cell inhibitor; stem-cell division inhibitors;
stipiarnide; stromelysin inhibitors; sulfmosine; superactive vasoactive intestinal peptide antagonist; suradista; suramin; swainsonine; synthetic glycosaminoglycans;
tallimustine;
tamoxifen methiodide; tauromustine; tazarotene; tecogalan sodium; tegafur;
tellurapyrylium;
telomerase inhibitors; temoporfin; temozolomide; teniposide;
tetrachlorodecaoxide; tetrazomine;
thaliblastine; thalidomide; thiocoraline; thrombopoietin; thrombopoietin mimetic; thymalfasin;
thymopoietin receptor agonist; thymotrinan; thyroid stimulating hormone; tin ethyl etiopurpurin;
tirapazamine; titanocene dichloride; topotecan; topsentin; toremifene;
totipotent stem cell factor;
translation inhibitors; tretinoin; triacetyluridine; triciribine;
trimetrexate; triptorelin; tropisetron;
turosteride; tyrosine kinase inhibitors; tyrphostins; UBC inhibitors;
ubenimex; urogenital sinus-derived growth inhibitory factor; urokinase receptor antagonists; vapreotide;
variolin B; vector system, erythrocyte gene therapy; velaresol; veramine; verdins; verteporfin;
vinorelbine;
vinxaltine; vitaxin; vorozole; zanoterone; zeniplatin; zilascorb; and zinostatin stimalamer.
To "inhibit growth" as used herein means causing a reduction -in cell growth in 'vivo or in vitro by, e.g., 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90 10, 95%, or 99% or more, as evident by a reduction in the size or number of cells exposed to a treatment (e.g., exposure to a compound), relative to the size or number of cells in the absence of the treatment. Growth inhibition may be the result of a treatment that induces apoptosis in a cell, induces necrosis in a cell, slows cell cycle progression, disrupts cellular metabolism, induces cell lysis, or induces some dther mechanism that reduces the size or number of cells.
"Marker gene" or "biomarker gene" as used herein means a gene in a cell the expression of which correlates to sensitivity or resistance of the cell (and thus the patient from which the cell was obtained) to a treatment (e.g., exposure to a compound).
"Microarray" as used herein means a device employed by any method that quantifies one or more subject oligonucleotides, e.g., DNA or RNA, or analogues thereof, at a time. One exemplary class of microarrays consists of DNA probes attached to a glass or quartz surface. For example, many microarrays, including those made by Af=fymetrix, use several probes for determining the expression of a single gene. The DNA microarray may contain oligonucleotide probes that may be, e.g., full-length cDNAs complementary to an RNA or cDNA
fragments that hybndize to part of an RNA. Exemplary RNAs include mRNA, miRNA, and miRNA
precursors. Exemplary microarrays also include a "nucleic acid microarray"
having a substrate-bound plurality. of nucleic acids, hybridization to each of the plurality of bound nucleic acids being separately detectable. The substrate may be solid or porous, planar or non-planar, unitary or distributed. Exemplary nucleic acid microarrays include all of the devices so called in Schena (ed.), DNA Microarrays: A Practical Approach (Practical Approach Series), Oxford University Press (1999); Nature Genet. 21 (1)(suppl.): 1-60 (1999); Schena (ed.), Microarray Biochip: Tools.
and Technology, Eaton Publishing Company/BioTechniques Books Division (2000).
Additionally, exemplary nucleic acid microarrays include substrate-bound plurality of nucleic acids in which the plurality of nucleic acids are disposed on a plurality of beads, rather than on a unitary planar substrate, as is described, inter alia, in Brenner et al., Proc. Natl. Acad. Sci. USA
97(4):1665-1670 (2000). Examples of nucleic acid microarrays may be found in U.S. Pat. Nos.
6,391,623, 6,383,754, 6,383,749, 6,380,377, 6,379,897, 6,376,191, 6,372,431, 6,351,712 6,344,316, 6,316,193, 6,312,906, 6,309,828, 6,309,824, 6,306,643, 6,300,063, 6,287,850, 6,284,497, 6,284,465, 6,280,954, 6,262,216, 6,251,601, 6,245,518, 6,263,287, 6,251,601, 6,238,866, 6,228,575, 6,214,587, 6,203,989, 6,171,797, 6,103,474, 6,083,726, 6,054,274, 6,040,138, 6,083,726, 6,004,755, 6,001,309, 5,958,342, 5,952,180, 5,936,731, 5,843,655, 5,814,454, 5,837,196, 5,436,327, 5,412,087, 5,405,783, the disclosures of which are incorporated E . == =

herein by reference in their entireties.
Exemplary microarrays may also include "peptide microarrays" or "protein microarrays"
having a substrate-bound plurality of polypeptides, the binding of a oligonucleotide, a peptide, or a protein to each of the pluxality of bound polypeptides being separately detectable. Alternatively, the peptide microarray, may have a plurality of binders, including but not limited to monoclonal antibodies, polyclonal antibodies, phage display binders, yeast 2 hybrid binders, aptamers, which can specifically detect the binding of specific oligonucleotides, peptides, or proteins. Examples of peptide arrays may be found in. WO 02/31463, WO 02/25288, WO 01/94946, WO
01/88162, WO 01/68671, WO 01/57259, WO 00/61806, WO 00/54046, WO 00/47774, WO 99/40434, WO
99/39210, WO 97/42507 and U.S. Pat. Nos. 6,268,210, 5,766,960, 5,143,854, the disclosures of which are incorporated herein by reference in their entireties.
"Gene expression" as used herein means the amount of a gene product in a cell, tissue, organism, or subject, e.g., amounts of DNA, RNA, or proteins, amounts of modifications of DNA, RNA, or protein, such as splicing, phosphorylation, acetylation, or methylation, or amounts of activity of DNA, RNA, or proteins associated with a given gene.
'NCI60" as used herein means a panel of 60 cancer cell lines from lung, colon, breast, ovarian, leukemia, renal, melanoma, prostate and brain cancers including the following cancer cell lines: NSCLC NCIH23, NSCLC NCIH522, NSCLC A549ATCC, NSCLC EKVX, NSCLC NCIH226, NSCLC NCIH332M, NSCLC H460, NSCLC HOP62, NSCLC HOP92, COLON HT29, COLON HCC-2998, COLON HCT116, COLON_SW620, COLON COL0205, COLON HCT15, COLON KM12, BREAST MCF7, BREAST MCF7ADRr, BREAST MDAMB231, BREAST HS578T, BREAST MDAMB435, BREAST MDN, BREAST BT549, BREAST T47D, OVAR OVCAR3, OVAR-OVCAR4, OVAR OVCAR5, OVAR OVCAR8, OVAR IGROVI, OVAR SKOV3, LEUK CCRFCEM, LEUK K562, LEUK MOLT4, LEUK. HL60,.LEUK RPMI8266, LEUK SR, RENAL_U031, RENAL SN12C, RENAL A498, RENAL CAKIl, RENAL R)CF393, RENA.L 7860, RENAL ACHN, RENAL TKIO, MELAN LOXIMVI, MELAN MALME3M, MELAN SKMEL2, MELAN SKMEL5, MELAN SKMEL28, MELAN_M14, ~ . . .

MELAN UACC62, MELAN UACC257, PROSTATE PC3, PROSTATE DUI45, CNS_SNB19, CNS_SNB75, CNS U251, CNS_SF268, CNS_SF295, and CNS_SF539.
"Treatment" or "medical treatment'.' means administering to a.subject or living organism or exposing to a cell or tumor a compound (e.g., a drug, a protein, an antibody, an , oligonucleotide, a chemotherapeutic agent, and a radioactive agent) or some other form of medical intervention used to treat or prevent cancer or the symptoms of cancer (e.g., cryotherapy and radiation therapy). Radiation therapy includes the administration to a patient of radiation generated from sources such as particle accelerators and related medical devices that emit X-radiation, gamma radiation, or electron (Beta radiation) beams. A treatment may fiirther include surgery, e.g., to remove a tumor from a subject or living organism.
Other features and advantages of the invention will be apparent from the following Detailed Description, the drawings, and the claims.

BRIEF DESCRIPTION OF THE DRAWINGS
Figure 1 depicts an illustration of the method of identifying biomarkers and predicting patient sensitivity to a medical treatment. The method has an in vitro component where the growth inhibition of a compound or medical treatment is measured on cell lines (6 of the 60 cell lines tested are shown). The gene expression is measured on the same cell lines without compound treatment. Those genes that have a correlation above a certain cutoff (e.g., a preffered cutoff of 0.3, in which a correlation coefficient equal to or greater than the cutoff of 0.3 is deemed statistcally significant by, e.g., cross-validation) to the growth inhibition are termed marker genes and the expressipn of those genes in vivo, e.g., may predict the sensitivity or resistance of a patient's cancer to a compound or other medical treatment. The in vivo component is applied to a patient to determine whether or not the treatment will be effective in treating disease in the patient. Here, the gene expression in cells of a sample of the suspected disease tissue (e.g., a tumor) in the patient is measured before or after treatment.
The activity of the marker genes in the sample is compared to a reference population of patients known to be sensitive or resistant to the treatment. The expression of marker genes in the cells of the patient , . . . . . ' known to be expressed in. the cells of reference patients sensitive to the treatment indicates that the patient to be treated is sensitive to the treatment and vice versa. Based on this comparison the patient is predicted to be sensitive or resistant to treatment with the compound.
Figure 2 depicts the treatrnent sensitivity predictions for a 5-year-old American boy with a brain tumor. The subject had surgery to. remove the tumor and, based on the analysis of gene expression in cells from a sample of the tumor, the subject was predicted to be chemosensitive to ten chemotherapy drugs. The subject received Vincristine and Cisplatin and survived.
Figure 3 depicts the treatment sensitivity predictions for a 7-month-ol.d American girl with a brain tumor. The subject had surgery to remove the tumor, and based on the analysis of gene expression in cells from a sample of the tumor, the subject was predicted to be chemoresistant to twelve chemotheraphy drugs. The subject received Vincristine and Cisplatin, but passed away 9 months later.
Figure 4 depicts the survival rate of 60 brain cancer patients divided into a group predicted to be chemosensitive to Cisplatin and a group predicted to be chemor.esistant to Cisplatin. All patients received Cisplatin after surgery.
Figure 5 depicts the survival rate of 56 lymphoma patients divided into a group predicted to be chemosensitive to Vincristine and Adriamycin and a group predicted to be chemoresistant.
All patients received Vincristine and Adriamycin.
Figure 6 depicts the survial rate of 19 lung cancer patients divided into a group predicted to be chemosensitive to Cisplatin and a group predicted to be chemoresistant.
All patients received Cisplatin.
Figure 7 depicts the survival rate of'14 diffuse large-B-cell lymphoma (DLBCL) patients divided into a group predicted to be chemosensitive to the drug combination R-CHOP and a group predicted to be chemoresistant. All patients were treated with R-CHOP.
Figure 8 depicts the predictions of sensitivity or resistance to treatment of a patient diagnosed with DLBCL. Various drug combinations and radiation therapy are considered. The=
drug combinations (indicated by abbreviations) are those commonly used to treat DLBCL.
Figure 9 depicts the survival rate of 60 brain cancer patients divided into a group predicted to be sensitive to radiation treatment and a group predicted to be resistant. All patients were treated with radiation.
Figure 10 depicts the survival rate of 60 brain cancer patients divided into a group predicted to be sensitive to radiation treatment and a group predicted to be resistant. All patients were treated with radiation. Gene biomarkers used in predicting radiation sensitivity or resistance were obtained using the correlation of the median gene expression measurement to cancer cell growth as opposed to the median of the correlations as employed in Figure 9.

DETATLED DESCRIPTION
The invention features methods for identifying biomarkers of treatment sensitivity, e.g., chemosensitivity to compounds, or resistance, devices that include the biomarkers, kits that include the devices, and methods for predicting treatment efficacy in a patient (e.g., a patient diagnosed with cancer). The kits of the invention include microarrays having oligonucleotide probes that are biomarkers of sensitivity or resistance to treatment (e.g., treatment with a chemotherapeutic agent) that hybridize to nucleic acids derived from or obtained from a subject and instructions for using the device to predict the sensitivity or resistance of the subject to the treatment. The invention also features methods of using the microarrays to determine whether a subject, e.g., a cancer patient, will be sensitive or resistant to treatment with, e.g., a chemotherapy agent. Also featured are methods of identifyi.ng gene biomarkers of sensitivity or resistance to a medical treatment based on the correlation of gene biomarker expression to treatment efficacy, e.g., the growth inhibition of cancer cells. Gene biomarkers that identify subjects as sensitive or resistant to a treatment may also be identified within patient populations already thought to be sensitive or resistant to that treatment. Thus, the methods, devices, and kits of the 'invention can be used to -identify patient -subpopulations that are responsive to a treatment thought to be ineffective for treating disease (e.g., cancer) in the general population.
More generally, cancer patient sensitivity to a compound or other medical treatment may be predicted using biomarker gene expression regardless of prior knowledge about patient responsiveness to treatment. The method according to the present invention can be implemented using software that is run on an , . == = . - . . . . . =
~ - - =

apparatus for measuring gene expression in connection with a microarray. The microarray (e.g. a DNA microarray), included in a kit for processing a tumor sample from a subject, and the apparatus for reading the microarray and turning the result into a chemosensitivity pr'ofile for the subject may be used to implement the methods of the invention.

Microarrays Containing Oligonucleotide Probes The microarrays of the invention include one or more oligonucleotide pr.obes that have nucleotide sequences that are identical to or complementary to, e.g., at least 5, 8, 12, 20, 30, 40, 60, 80, 100, 150, or 200 consecutive nucleotides (or nucleotide analogues) of the biomarker genes listed below. The oligonucleotide probes may be, e.g., 5-20, 25, 5-50, 50-100, or over 100 nucleotides long. The oligonucleotide probes may be deoxyribonucleic acids (DNA) or ribonucleic acids (RNA). Consecutive nucleotides within the oligonucleotide probes (e.g., 5-20, 25, 5-50, 50-100, or over 100 consecutive nucleotides), which are used as gene biomarkers of ...
chemosensitivity, may also appear as consecutive nucleotides in one or more of the genes described herein beginning at or near, e.g., the first, tenth, twentieth, thirtieth, fortieth, fiftieth, sixtieth, seventieth, eightieth, ninetieth, hundredth, hundred-fiftieth, two-hundredth, five-hundredth, or one-thousandth nucleotide of the genes listed in Tables 1-21 or below. Column List 2006 of Tables 1-21 indicates the preferred gene biomarkers for the compound lists.
Column List Preferred of Tables 1-21 indicates the most preferred gene biomarkers. Column List 2005 of Tables 1-21 indicates additio.nal biomarkers employed in Examples 1-8. Column Correlation of Tables 1-21 indicates the correlation coefficient of the biomarker gene expression to cancer cell growth inhibition. The following combinations of gene biomarkers have been used to detect a subject's sensitivity to the indicated treatment:

a) One or more of the gene sequences SFRS3, CCT5, RPL39, SLC25A5, UBE2S, EEFIAI, RPLP2, RPL24, RPS23, RPL39, RPL18, NCL, RPL9, RPL10A, RPS10, EIF3S2, SHFM1, RPS28, REA,-RPL36A, GAPD, HNRPA1, RPS11, HN.RPA1, LDHB, RPL3, RPL11, MRPL12, RPL1 SA, COX7B, and RPS7, preferably gene sequences UBB, RPS4X, S 100A4, NDUFS6, B2M, C14orf139, MAN1A1, SLC25A5, RPL10, RPL12, EIF5A, RPL36A, SUII, BLMH, CTBP1, TBCA, MDH2, and DXS9879E, and most preferably gene sequences RPS4X, S100A4, NDUFS6, C14orfl39, SLC25A5, RPL10, RPL12, EIF5A, RPL36A, BLMH, CTBP1, TBCA, ~MH2, and DXS9879E, whose expression indicates chemosensitivity to Vincristine.

b) One or more of the gene sequences B2M, ARHGDIB, FTL, NCL, MSN, SNRPF, XPO1, LDHB, SNRPF, GAPD, PTPN7, ARHGDIB, RPS27, IFI16, C5orfl3, and HCLS 1, preferably gene sequences CIQR1, HCLS1, CD53, SLA, PTPN7, PTPRCAP, ZNFNIAI, CENTBI, PTPRC, IFI16, ARHGEF6, SEC31L2, CD3Z, G.ZMB, CD3D, MAP4K1, GPR65; PRF1, ARHGAP15, TM6SF1, and TCF4, and most preferably gene sequences C1QR1, SLA, PTPN7, ZNFNIAI, CENTBI, IFI16, ARHGEF6, SEC31L2, CD3Z, GZMB, CD3D, MAP4K1, GPR65, PRF1, ARHGAP15, TM6SF1, and TCF4, whose*expression indicates chemosensitivity to Cisplatin.

c) One or more of the gene sequences PRPS1, DDOST, B2M, SPARC, LGALS1, CBFB, SNRPB2, MCAM, MCAM, EIF2S2, HPRT1, SRM, FKBPIA, GYPC, UROD, MSN, HNRPAI, SND1, COPA, MAPREI, EIF3S2, ATP1B3, EMP3, ECM1, ATOXl, NARS, PGKI, OK/SW-cl.56, FN1, EEF1A1, GNAI2, PRPSI, RPL7, PSMB9, GPNMB, PPP1R11, MIA, RAB7, VIM, and SMS, preferably gene sequences MSN, SPARC, VIM, SRM, SCARBI, SIATl, CUGBP2, GAS7, ICAMl, WASPIP, ITM2A, PALM2-AKAP2, ANPEP, PTPNSI, MPP1, LNK, FCGR2A, EMP3, RUNX3, EVI2A, BTN3A3, LCP2, BCHE, LY96, LCPI, IFI16, MCAM, MEF2C, SLC1A4, BTN3A2, FYN, FN1, Clorf38, CHSI, CAPN3, FCGR2C, TNIK, AMPD2, SEPT6, R.AFTLIN, SLC43A3, RAC2, LPXN, CKIP-1, FLJ10539, FLJ35036, DOCK10, TRPV2, IFRG28, LEF1, and ADAMTSI, and most preferably gene sequences SRM, SCARBI, SIAT1, CUGBP2, ICAM1, WASPIP, ITM2A, PALM2-AKAP2, PTPNS1, MPP1, LNK, FCGR2A, RUNX3, EVI2A, BTN3A3, LCP2, BCHE, LY96, LCP1, IFI16, MCAM, MEF2C, SLC1A4, FYN, Clorf38, CHSl, FCGR2C, TNIK, AMPD2, SEPT6, RAFTLIN, SLC43A3, RAC2, LPXN, CKIP-1, FLJ10539, FLJ35036, DOCK10, TRPV2, IFRG28, LEFI, and ADAMTS1, whose ~=

expression indicates chemosensitivity to Azaguanine.

d) One or more of the gene sequences B2M, MYC, CD99, RPS24, PPIF, PBEF1, and ANP32B, preferably gene sequences CD99, INSIGI, LAPTM5, PRG1, MUF1, HCLS1, CD53, SLA, SSBP2, GNB5, MFNG, GMFG, PSMB9, EVI2A, PTPN7, PTGER4, CXorf9, PTPRCAP, ZZNFN1Al, CENTBI, PTPRC, NAP1L1, HLA-DRA, IFI16, COROIA, ARHGEF6, PSCDBP, SELPLG, LAT, SEC31L2, CD3Z, SH2D1A, GZMB, SCN3A, ITK, RAFTLIN, DOCK2, CD3D, RAC2, ZAP70, GPR65, PRFI, ARHGAP15, NOTCHI, and UBASH3A, and most preferably gene sequences CD99, INSIG1, PRG1, MUF1, SLA, SSBP2, GNB5, MFNG, PSMB9, EVI2A, PTPN7, PTGER4, CXorf9, ZNFNIAI, CENTBI, NAP1L1, HLA-DRA, IFI16, ARHGEF6, PSCDBP, SELPLG, LAT, SEC31L2, CD3Z, SH2D1A, GZMB, SCN3A, RAFTLIN, DOCK2, CD3D, RAC2, ZAP70, GPR65, PRF1, ARHGAPI5, NOTCH1, and UBASH3A, whose expression indicates chemosensitivity to Etoposide.

e) One or more of the gene sequences KIAA0220, B2M, TOP2A, CD99, SNRPE, RPS27, HNRPAI, CBX3, ANP32B, HNRPA1, DDX5, PPIA, SNRPF, and USP7, preferably gene sequences CD99, LAPTM5, ALDOC, HCLS1, CD53, SLA, SSBP2, iL2RG, GMFG, CXorf9, RHOH, PTPRCAP, ZNFNIAI, CENTB1, TCF7, CD1C, MAP4K1, CD1B, CD3G, PTPRC, CCR9, CORO 1 A, CXCR4, ARHGEF6, HEM1, SELPLG, LAT, SEC31L2, CD3Z, SH2D 1 A, CDIA, LAIRI, ITK, TRB@, CD3D, WBSCR20C, ZAP70, IFI44, GPR65, AIF1, ARHGAP15, NARF, and PACAP, and most preferably gene sequences CD99, ALDOC, SLA, SSBP2, IL2RG, CXorf9, RHOH, ZNFI*T1A1, CENTBI, CD1C, MA1?4K1, CD3G, CCR9, CXCR4, ARHGEF6, SELPLG, LAT, SEC31L2, CD3Z, SH2DIA, CD1A, LAIRl, TRB@, CD3D, WBSCR20C, ZAP70, IFI44, GPR65, AIF1, ARHGAP15, NARF, and PACAP, whose expression indicates chemosensitivity to Adriamycin.

f) One or more of the gene sequences RPLP2, LAMRI,.RPS25, EIF5A, TUFM, HNRPAI, RPS9, MYB, LAMR1, ANP32B, IINRPAI, HNRPAI, EIF4B, HMGB2, RPS15A, and RPS7, preferably gene sequences RPL12, RPL32, RPLP2, MYB, r TN1A1, SCAP1, STAT4, SP140, AMPD3, TNFAIP8, DDXl8, TAF5, FBL, RPS2, PTPRC, DOCK2, GPR65, HOXA9, FL112270, and HNRPD, and most preferably gene sequences RPL12, RPLP2, MYB, ZNFNlAI, SCAPI, STAT4, SP140, AMPD3, TNFAIP8, DDX18, TAFS, RPS2, DOCK2, GPR65, HOXA9, FLJ 12270, and HNRPD, whose expression indicates chemosensitivity to Aclarubicin.

g) One or more of the gene sequences ARHGEF6, B2M, TOP2A, TOP2A, ELA2B, PTMA, LMNB1, TNFRSFIA, NAP1L1, B2M, IIlVRPAI, RPL9, C5orfl3, NCOR2, ANP32B, OK/SW-c1.56, TUBA3, HMGN2, PRPSI, DDX5, PRG1, PPIA, G6PD, PSMB9, SNRPF, and.MAP1B, preferably gene sequences PGAM1, DPYSL3,INSIGl, GJA1, BNIP3, PRG1, G6PD, BASP1, PLOD2, LOXL2, SSBP2, Clorf29, TOX, STC1, TNFRSFIA, NCOR2, NAP1L1, LOC94105, COL6A2, ARHGEF6, GATA3, TFPI, LAT, CD 3 Z, AF 1 Q, Iv1 AP 1 B, PTPRC, PRKCA;
TRIM22, CD3D, BCAT1, IFI44, CCL2, RAB31, CUTC, NAP1L2, NME7, FLJ21159, and COL5A2, and most preferably gene sequences PGAM1, DPYSL3, INSIG1, GJA1, BNIP3, PRG1, G6PD, PLOD2, LOXL2, SSBP2, Clorf29, TOX., STC1, TNFRSFIA, NCOR2, NAP1L1, LOC94105, ARHGEF6, GATA3, TFPI, LAT, CD3Z, AF 1 Q, MAP 1 B,. TRIM22, CD3D, B CAT 1, IFI44, CUTC, NAP 1 L2, NME7, FLJ21159, and COL5A2, whose expression indicates chemosensitivity to Mitoxantrone.

h) One or more of the gene sequences GAPD, GAPD, GAPD, TOP2A, SUI1, TOP2A, FTL, HNRPC, TNFRSF1A, SHC1, CCT7, P4HB, CTSL, DDX5, G6PD, and SNRPF, preferably gene sequences STC1, GPR65, II?OCK10, COL5A2, FAM46A, and LOC54103, and most preferably gene sequences STC1, GPR65, DOCK10, COL5A2, FAM46A, and LOC54103, whose expression indicates chemosensitivity to Mitomycin..

i) One or more of the gene sequences RPS23, SFRS3, KIAA0114, RPL39, SFRS3, LOC51035, RPS6, EXOSC2, RPL35, IFRD2, SMN2, EEF1Al, RPS3, RPS18, and RPS7, preferably gene sequences RPL10, RPS4X, NUDC, RALY, DKC1, DKFZP564C186, PRP19, RAB9P40, HSA9761, GMDS, CEP1, IL13R.A2, MAGEB2, HMGN2, ALMS1, GPR65, FLJ10774,.NOL8, DAZAPI, SLC25A15, PAF53, DXS9879E, PITPNCI, SPANXC, and KIA.A1393, and most preferably RPL10, RPS4X, NUDC, DKC1, DKFZP564C186, PRP19, RAB9P40, HSA9761, GMDS, CEP1, IL13RA2, MAGEB2, HMGN2, ALMSI, GPR65, FLJ10774, NOL8, DAZAPI, SLC25A15, PAF53, DXS9879E, PITPNCI, SPANXC, and KTAA1393, whose expression indicates chemosensitivity to Paclitaxel.

j) One or more of the gene sequences CSDA, LAMR1, and TUBA3, preferably gene sequences PFNl, PGAM1, K-ALPHA-1, CSDA, UCHL1, PWP1, PALM2-AKAP2, TNFRSFIA, ATP5G2, AF1Q, NME4, and FHOD1, and most preferably gene sequences PFN1, PGAM1, K-ALPHA-1, CSDA, UCHLI, PWP1, PALM2-AKAP2, TNFRSFlA, ATP5G2, AF 1 Q, NME4, FHOD 1, whose expression indicates chemosensitivity to Gemcitabine.

k) One or more of the gene sequences RPS23, SFRS3, KIAA0114, SFRS3, RPS6, DDX39, and RPS7, preferably gene sequences ANP32B, GTF3A, RRM2, TRIM14, SKP2, TRIP13,.
RFC3, CASP7, TXN, MCM5, PTGES2, OBFC1, EPB41L4B, and CALML4, and most preferably gene sequences ANP32B, GTF3A, RRM2, TRIM14, SKP2, TRIP13, RFC3, CASP7, TXN, MCM5, PTGES2, OBFC1, EPB41L4B, and CALML4, whose expression indicates chemosensitivity to Taxotere.

1) One or more of the gene sequences IL2RG, H1FX, RDBP, ZAP70, CXCR4, TM4SF2, ARHGDIB, CDA, CD3E, STMNI, GNA15, AXL, CCND3, SATBI, EIF5A, LCK, NKX2-5, LAPTM5, IQGAP2, FLII, EIF3S5, TRB, CD3D,'HOXB2, GATA3, HMGB2, PSMB9, ATP5G2, COROIA, ARHGDIB, DRAPI, PTPRCAP, RHOH, and ATP2A3, preferably gene sequences IFITM2, UBE2L6, LAPTM5, USP4, ITM2A, ITGB2, ANPEP, CD53, IL2RG, CD37, GPRASPI, PTPN7, CXorf9, RHOH, GIT2, ADORA2A, ZNFNIAI, GNA15, CEP1, TNFRSF7, MAP4K1, CCR7, CD3G, PTPRC, ATP2A3, UCP2, COROIA, GATA3, CDKN2A, HEM1;
TARP, LAIRl, SH2DIA, FLII, SEPT6, HA=1, CREB3L1, ERCC2, CD3D, LST1, AIF1, ADA, DATFI, ARHGAP15, PLAC8, CECR1, LOC81558, and EHD2, and most preferably gene sequences IFITM2, UBE2L6, USP4, ITM2A, IL2RG, GPRASPl, PTPN7, CXorf9, RHOH, GIT2, ZNFNIA1, CEPl, TNFRSF7, MAP4K1, CCR7, CD3G, ATP2A3, UCP2, GATA3, CDKN2A, TARP, LAIRl, SH2D1A, SEPT6, HA-1, ERCC2, CD3D, LSTI, AIFI, ADA, DATF1, ARHGAP15, PLAC8, CECR1, L'OC81558,.and EHD2, whose expression indicates chemosensitivity to Dexamethasone.

m) One or more of the gene sequences TM4SF2, ARHGDIB, ADA, H2AFZ, NAPiLl, CCND3, FABP5, LAMRI, REA, MCM5, SNRPF, and USP7, preferably gene sequences ITM2A, RHOH, PRIM1, CENTBl, GNA15, NAP1L1, ATP5G2, GATA3, PRKCQ, SH2DlA, SEPT6, PTPRC, NME4, RPL13, CD3D, CD1E, ADA, and FHOD1, and most preferably gene sequences ITM2A, RHOH, PRIMI, CENTBI,NAPILI, ATP5G2, GATA3, PRKCQ, SH2DIA, SEPT6, NME4, CD3D, CD1E, ADA, and FHOD1, whose expression indicates chemosensitivity to Ara-C.

n) One or more of the gene sequences LGALS9, CD7, IL2RG, PTPN7, ARHGEF6, CENTB 1, SEPT6, SLA, LCP1, IFITM1, ZAP70, CXCR4, TM4SF2, ZNF91, ARHGDIB, TFDP2, ADA, CD99, CD3E, CD1C, STMNl, CD53, CD7, GNA15, CCND3, MAZ, SATB1, ZNF22, AES, AIF1, MYB; LCK, C5orfl3, NKX2-5, ZNFNIAI, STAT5A, CHI3L2, LAPTM5, MAP4K1, DDXl 1, GPSM3, TRB, CD3D, CD3G, PRKCBI., CD1E, HCLS1, GATA3, TCF7, RHOG, CDW52, HMGB2, DGKA, ITGB2, PSMB9, IDH2, AES, MCM5, NUCB2, COROIA, ARHGDIB, PTPRCAP, CD47, RHOH, LGALS9, and ATP2A3, preferably gene sequences CD99, SRRM1, ARHGDIB, LAPTM5, VWF, ITM2A, ITGB2, LGALS9, INPP5D, SATBI, CD53, TFDP2, SLA, IL2RG, MFNG, CD37, GMFG, SELL, CDW52, LRMP, ICAM2, RIMS3, PTPN7, ARHGAP25, LCK, CXorf9, RHOH, PTPRCAP, GIT2, ZNFNIAI, CENTBI, LCP2, SPII, GNA15, GZMA, CEP1, BLM, CD8A, SCAPI, CD2, CDIC, TNFRSF7, VAVI, MAP4K1, CCR7, C6orf32, ALOXI5B, BRDT, CD3G, PTPRC, LTB, ATP2A3, NVL, RASGRP2, LCP1, COROIA, CXCR4, PRKD2, GATA3, TRA@, PRKCBI, HEMI, KIAA0922, TARP, SEC3IL2, PRKCQ, SH2DlA, CHRNA3, CD1A, LSTl, LAIRI, CACNAIG, TRB@, SEPT6, HA-1, DOCK2, CD3D, TRD@, T3JAM, FNBPI, CD6, AIFI, FOLH1, CDIE, LY9, UGT2B17, ADA, CDKL5, TRIM, EVL, DATFI, RGC32, PRKCH, ARHGAP15, NOTCHI, BIN2, SEMA4G, DPEP2, CECR1, BCL11B, STAG3, GALNT6, UBASH3A, PHEMX, FLJ13373, LEF1, IL21R, MGC17330, AKAP13, ZNF335, and GIMAP5, and most preferably gene sequences CD99, ARHGDIB, VWF, ITM2A, LGALS9, I1VPP5D, SATB1, TFDP2, SLA,IL2RG, MFNG, SELL, CDW52, LRMP, ICAM2, RIMS3, PTPN7, ARHGAP25, LCK, CXorf9, RHOH, GIT2, ZNFNIAl, CENTBI, LCP2, SPI1, GZMA, CEP1, CD8A, SCAP1, CD2, CD1C, TNFRSF7, VAV1, MAP4Kl, CCR7, C6orf32, ALOX15B, BRDT, CD3G, LTB, ATP2A3, NVL, RASGRP2, LCP1, CXCR4, PRKD2, GATA3, TRA@, K.IAA0922, TARP, SEC31L2, PRKCQ, SH2D1A, CHRNA3, CDlA, LSTl, LAIRI, CACNAIG, TRB@, SEPT6, HA-1, DOCK2, CD3D, TRD@, T3JAM; FNBPl, CD6, AIF1, FOLH1, CD1E, LY9, ADA, CDKL5, TR1M, EVL, DATFI, RGC32, PRKCH, ARHGAP15, NOTCHl, BIN2, SEMA4G, DPEP2, CECRI, BCL1 lB, STAG3, GALNT6, UBASH3A, PHEMX, FLJ13373, LEF1, IL21R, MGC17330, AKAP13, ZNF335, and GIM'AP5, whose expression indicates chemosensitivity to Methylprednisolone.

o) One or more of the gene sequences RPLP2, RPL4, HMGA1, RPL27, M'DH2, LAMRI,.
PTMA, ATPSB, NPMI, NCL, RPS25, RPL9, TRAP1, RPL21, LAMRI, REA, HNR.PAI, LDHB, RPS2, NME1, PAICS, EEF1B2, RPS15A, RPL19, RPL6,-ATP5G2, SNRPF, SNRPG, and RPS7, preferably gene sequences PRPF8, RPL18, RNPS1, RPL32, EEFIG, GOT2, RPL13A, PTMA, RPS15, RPLP2, CSDA, KHDRBS 1, SIVRPA, IMPDH2, RPS19, NUP88, ATP5D, PCBP2, ZNF593, HSU79274, PRIMl, PFDN5, OXA1L, H3F3A, ATIC, RPL13, CIAPIN1, FBL, RPS2, PCCB, RBMX, SHMT2, RPLPO, HNRPAI,-STOML2, RPS9, SKB1, GLTSCR2, CCNBlIP1, MRPS2, FLJ20859, and FLJ12270, and most preferably gene sequences PRPF8, RPL18, GOT2, RPL13A, RPS15, RPLP2, CSDA, KHDRBSI, SNRPA, IMPDH2, RPS19, NTJP88, ATP5D, PCBP2, ZNF593, HSU79274, PRIM1, PFDN5, OXA.IL, H3F3A, ATIC, CIAPIlVI, RPS2, PCCB, SHMT2, RPLPO, HNRPAI, STOML2, SKB1, GLTSCR2, CCNBIIP1, MRPS2, FLJ20859, and FLJ12270, whose expression indicates chemosensiti,vity to Methotrexate.

p) One or more of the gene sequences ACTB, COL5A1, MT1E, CSDA, COL4A2, MMP2, COL1A1, TNFRSFIA, CFHL1, TGFBI, FSCN1, NNMT, PLAUR, CSPG2, NFIL3, C5orf13, NCOR2, TUBB4, MYLK, TUBA3, PLAU, COL4A2, COL6A2, COL6A3, IFITM2, PSMB9, CSDA, and COLlAl, preferably gene sequences MSN, PFN1, l;iKl, ACTR2, MCL1, ZYX, RAP1B, GNB2, EPASl, PGAM1, CKAP4, DUSP1, MYL9, K-ALPHA-1, LGALSI, CSDA, AKR1B1, IFITM2, ITGA5, VIM, DPYSL3, JUNB, ITGA3; NFKBIA, LAMB1, FHL1,INSIGI, TIMP l, GJA 1, PSME2, PRG l, EXT 1, DKFZP434J 154, OPTN, M6PRBP 1, MVP, VASP, ARL7, NNMT, TAP1, COL1A1, BASP1, PLOD2, ATF3, PALM2-AKAP2, IL8, ANPEP, LOXL2, TGFB 1, IL4R, DGKA, STC2, SEC61 G, NFIL3, RGS3, NK4, F2R, TPM2, PSMB9, LOX, STCl, CSPG2, PTGER4, IL6, SMAD3, PLAU, WNT5A, BDNF, TNFRSFIA, FLNC, DKFZP564K0822, FLOTI, PTRF, HLA-B, COL6A2, MGC4083, TNFRSF10B, PLAGLl, PNMA2, TFPI, LAT, GZMB, CYR61, PLAUR, FSCN1, ERP70, AF1Q, UBC, FGFRI, HIC, BAX, COL4A2, COL6A1, IFITM3, MAP1B, FLJ46603, RAFTLIN, RRAS, FTL, KIAA0877, MTIE, CDC10, DOCK2, TRI1VI22, RIS1, BCAT1, PRF1, DBN1, MT1K, TMSB10, RAB31, FLJ10350, Clorf24, NME7, TMEM22, TPKI, COL5A2, ELK3, CYLD, ADAMTS1, EHD2, and ACTB, and most preferably gene sequences PFN 1, FIK1, MCL 1, ZYX, RAP 1 B, GNB2, EPAS1, PGAM1, CKAP4, DUSP1, MYL9, K-ALPHA-1, LGALS1, CSDA, IFITM2, ITGA5, DPYSL3, JUNB, NFKBIA, LAMB1, FHL1, INSIGl, TIlVIP1, GJA1, PSME2, PRG1, EXT1, DKFZP434J154, MVP, VASP, ARL7, NNMT, TAP1, PLOD2, ATF3, PALM2-AKAP2, IL8, LOXL2, IL4R, DGKA,.STC2, SEC61G, RGS3; F2R, TPM2, PSMB9, LOX, STCl, PTGER4, IL6, SMAD3, WNT5A, BDNF, TNFRSFIA, FLNC, DKFZP564K0822, FLOTI, PTRF, HLA-B, MGC4083, TNFRSFIOB, PLAGLI, PNMA2, TFPI, LAT, GZMB, CYR61, PLAUR, FSCN1, ERP70, AFIQ, HIC, COL6A1, IFITM3, MAP1B, FLJ46603, RAFTLIN, RRAS, FTL, KIAA0877, MT1E, CDC10, DOCK2, TRIM22, RIS1, BCAT1, PRF1, DBNl, MT1K, TMSBIO, FLJ10350, Clorf24, NME7, TMEM22, TPK1, COL5A2, ELK3, CYLD, ADAMTS1, EHD2, and ACTB, whose expression indicates chemosensitivity to Bleomycin_ q) One or more of the gene sequences NOS2A, MUCl, TFF3, GP1BB, IGLL1, BATF, MYB, PTPRS, NEFL, AIP, CEL, DGKA, RUNX1, ACTRIA, and CLCNKA, preferably gene sequences PTMA, SSRP1, NUDC, CTSC; AP1G2, PSME2, LBR, EFNB2, SERPINAI, SSSCA1, EZH2, MYB, PRLMl, H2AFX, HMGAI, HMM1.2, TK2, WHSC1, DIAPHl, LAMB3, DPAGTI, UCK2, SERPINBI, MDN1, BRRNI, GOS2, RAC2, MGC21654, GTSE1, TACC3, PLEK2, PLAC8, HNRPD, and PNAS-4, and most preferably gene sequences SSRP1, NUDC, CTSC, AP1G2, PSME2, LBR, EFNB2, SERPINAI, SSSCAI, EZH2, MYB, PRIMl, H2AFX, HMGA1, HMMR, TK2, WHSC1, DIAPHI, LAMB3, DPAGTI, UCK2, SERFlNB1, MDNl, BRRN1, G0S2, RAC2, MGC21654, GTSEl, TACC3, PLEK2, PLAC8, HNRPD, and PNAS-4, whose expression indicates chemosensitivity to Methyl-GAG.

r) One or more of the gene sequences MSN, ITGA5, VIM, TNFAIP3, CSPG2, WNT5A, FOXF2, LOC94105, TFI16, LRRN3, FGFR1, DOCK10, LEPREI, COL5A2, and ADAMTSI, and most preferably gene sequences ITGA5, TNFAIP3, WNT5A, FOXF2, LOC94105, IFI16, LRRN3, DOCK10, LEPREl, COL5A2, and ADAMTSI, whose expression indicates chemosensitivity to carboplatin.

s) One or more of the gene sequences RPL18, RPLIOA, RNPSl, ANAPC5, EEF1B2, RPL13A, RPS 15, AKAP1, NDUFAB 1, APRT, ZNF593, MRP63, IL6R, RPL13, SART3, RPS6, UCK2, RPL3, RPL17, RPS2, PCCB, TOMM20, SHMT2, RPLPO, GTF3A, S'I'OML2, DKFZp564Jr157, MRPS2, ALG5, and CALML4, and most preferably gene sequences RPL18, RPL10A, ANAPC5, EEFIB2, RPL13A, RPS15, AKAPl, NDUFABI, APRT, ZNF593, MRP63, IL6R, SART3, UCK2, RPL17, RPS2, PCCB, TOIv1IV120, SHMT2, R.PLPO, GTF3A, STOML2, DKFZp5643157, MRPS2, ALG5, and CALML4, whose expression indicates chemosensitivity to 5-FU(5-Fluorouracil).

t) One or more of the gene sequences ITK, KIFCI, VLDLR, RUNX1, PAFAHIB3; H1FX, RNF144, TMSNB, CRY1, MAZ, SLA, SRF, tTMPS, CD3Z, PRKCQ, H1ViZPM, ZAP70, ADD1, RFC5, TM4SF2, PFN2, BMI1, TUBGCP3, ATP6VIB2, RALY, PSMC5, CDID, ADA, CD99, CD2, CNP, ERG, MYL6, CD3E, CDIA, CD1B, STMN1, PSMC3, RPS4Y1, AKT1, TALI, GNA15, UBE2A, TCF12, UBE2S, CCND3, PAX6, MDK, CAPG, RAG2, ACTNl, GSTM2, SATBI, NASP, IGFBP2, CDH2, CRABP1, DBN1, CTNNAI, AKR1C1, CACNB3, FARSLA, CASP2, CASP2, E2F4, LCP2, CASP6, MYB, SFRS6, GLRB, NDN, CPSF1, GNAQ, TLTSC3, GNAQ, JARID2, OCRL, FHLI, EZH2, SMOX, SLC4A2, UFDIL, SEPWI, ZNF32, HTATSFI, SFLDI, PTOV1, NXFI, FYB, TRIM28, BC008967, TRB@, TFRC, HIFO, CD3D, CD3G, CENPB, ALDH2, ANXA1, H2AFX, CD1E, DDX5, ABLl, CCNA2, ENO2, SNRPB, GATA3, RRM2, GLUL, TCF7, FGFR1, SOX4, MAL, NUCB2, SMA3, FAT, UNG, ARHGDIB, RUNXI, MPHOSPH6, DCTN1, SH3GL3, VIM, PLEKHC1, CD47, POLR2F, RHOH, ADD1, and ATP2A3, preferably gene sequences ITK, KIFC1, VLDLR, RUNX1, PAFAHIB3, HIFX,.
RNF144, TMSNB, CRY1, MAZ, SLA, SRF, UMPS, CD3Z, PRKCQ, HNRPM, ZAP70, ADD1, RFC5, TM4SF2, PFN2, BMI1, TUBGCP3, ATP6V1B2, RALY, PSMC5, CD1D, ADA, CD99, CD2, CNP,.ERG, MYL6, CD3E, CD1A, CD1B, STMNI, PSMC3, RPS4Y1, AKT1, TAL1, GNA15, UBE2A, TCF12, UBE2S, CCND3, PAX6, MDK, CAPG, RAG2, ACTN1, GSTM2, SATB 1, NASP, IGFBP2, CDH2, CRABP1, DBN1, CTNNAI, AKR1C1, CACNB3, FARSLA, CASP2, CASP2, E2F4, LCP2, CASP6, MYB, SFRS6, GLRB, NDN, CPSF1, GNAQ, TUSC3, GNAQ, JARID2, OCRL, FHL1, EZH2, SMOX, SLC4A2, UFD1L, SEPW1, ZNF32, HTATSF1, SHD1, PTOVI, NXFI, FYB, TRIM28, BC008967, TRB@, TFRC, HIFO, CD3D, CD3G, CENPB, ALDH2, ANXA1, H2AFX, CD1E, DDX5, ABLl, CCNA2, ENO2, SNRPB, GATA3,-R.RM2, GLUL, TCF7, FGFRI, SOX4, MAL, NUCB2, SMA3, FAT, UNG, ARHGDIB, RUNX1, MPHOSPH6, DCTN1, SH3GL3, VIM, PLEKHC1, CD47, POLR2F, RHOH, A.DD1, and ATP2A3, and most preferably gene sequences KIFCI, VLDLR, RUNX1, PAFAHIB3, HIFX, RNF144, TMSNB, CRYl, MAZ, SLA, SRF, UMPS, CD3Z, PRKCQ, HNRPM, ZA.P70, ADD1, RFC5, TM4SF2, PFN2, BMI1, TUBGCP3, ATP6V1B2, CDID, ADA, CD99, CD2, CNP, ERG, CD3E, CDIA, PSMC3, RPS4Y1, AKTl, TAL1, UBE2A, TCF12, UBE2S, CCND3, PAX6, RAG2, GSTM2, SATB1, NASP, IGFBP2, CDH2, CRABP1, DBN1, AKR1C1, CACNB3, CASP2, CASP2, LCP2, CASP6, MYB, SFRS6, GLRB, NDN, GNAQ, TUSC3, GNAQ, JARID2, OCRL, FHL1, EZH2, SMOX, SLC4A2, UFD1L, ZNF32, HTATSFI, SHD1, PTOV1, NXF1, FYB, TRIM28, BC008967, TRB@, H1F0, CD3D, CD3G, CENPB, ALDH2, ANXAI, H2AFX, CD1E, DDX5, CCNA2, ENO2, SNRPB, GATA3, RRM2, GLUL, SOX4, MAL, UNG, ARHGDIB, RUNXl, MPHOSPH6, DCTN1, SH3GL3, PLEKHC1, CD47, POLR2F, RHOH, and ADD1, whose expression indicates chemosensitivity to MABTHERAm (Rituximab).

u) One or more of the gene sequences CCL21, ANXA2, SCARB2, MAD2LIBP, CAST, PTS, NBL1, ANXA2, CD151, TRAM2, HLA-A, CRIP2, UGCG, PRSS11, MME, CBR1, LGALS1, DUSP3, PFN2, MICA, FTH1, RHOC, ZAP128, PON2, COL5A2, CST3, MCAM, IGFBP3, MMP2, GALIG, CTSD, ALDH3AI, CSRPI, S100A4, CALD1, CTGF, CAPG, HLA-A, ACTN1, TAGLN, FSTLl, SCTR, BLVRA, COPEB, DIPA, SMARCD3, FN1, CTSL, CD63, DUSP1, CKAP4, MVP, PEA15, S100A13, and ECE1, preferably gene sequences TRA1, ACTN4, WARS, CALM1, CD63, CD81, FKBPIA, CALU, IQGAPI, CTSB, MGC8721, STAT1, TACC1, TM4SF8, CD59, CKAP4, DUSPl, RCN1, MGC8902, LGALSI, BHLHB2, RRBP1, PKM2, PRNP, PPP2CB, CNN3, ANXA2, IER3, JAK1, MARCKS, LUM, FER1L3, SLC20A1, EIF4G3, HEXB, EXT1, TJPI, CTSL, SLC39A6, RIOK3, CRK, NNMT, COL1A1, TRAM2, ADAM9, DNAJC7, PLSCRI, PRSS23, PLOD2, NPC1, TOB I, GFPT1, IL8, DYRK2, PYGL, LOXL2, KIAA0355, UGDH, NFIL3, PUR.A, ULK2, CENTG2, NID2, CAP350, CXCL1, BTN3A3, IL6, WNT5A, FOXF2, LPHN2, CDH11, P4HA1, GRP58,=ACTNl, CAPN2, DSIPI, MAPILC3B, GALIG, IGSF4; IRS2, ATP2A2, OGT, TNFRSFIOB, KIAA1128, T1VF4SF1, RBPMS, RIPK2, CBLB, NR1D2, BTN3A2, -SLC7A1 l, MPZL1, IGFBP3, SSA2, FN1, NQO1, ASPH, ASAH1, MGLL, SERPINB6, HSPA5, ZFP36L1, COL4A2, COL4A1, CD44, SLC39A14, NIPA2, FKBP9, IL6ST, DKFZP564G2022, PPAP2B, MAPIB,IVIAPKI, MYO1B, CAST, RRAS2, QKI, LHFPL2, 38970, ARBE, KIAA1078, FTL, KIAA0877, PLCB1, KIA.A0802, KPNB1, RAB3GAP, SERPINB1, TIMMI7A, SOD2, HLA-A, NOMO2, LOC55831, PHLDAI, TMEM2, MLPH, FAD104; LR.RC5, R.AB7L1, FLJ35036, DOCK10, LRP12, TXNDC5, CDC14B, HRMTIL1, CORO1C, DNAJCIO, TNPO1, LONP, AMIGO2, DNAPTP6, and ADAMTS 1, and most preferably gene sequences TRAI, ACTN4, CALM1, CD63, FKBPIA, CALU, IQGAPI, MGC8721, STAT1, TACC1, TM4SF8, CD59, CKAP4, DUSP1, RCN1, MGC8902, LGALSI, BHLHB2, RRBP1, PRNP, IER3, MARCKS, LUM, FER1L3, SLC20A1, HEXB, EXT1, TJPI, CTSL, SLC39A6, RIOK3, CRK, NNMT, TRAM2, ADAM9, DNAJC7, PLSCR1, PRSS23, PLOD2, NPC1,,TOB1, GFPT1, IL8, PYGL, LOXL2, KIAA0355, UGDH, PURA, ULK2, CENTG2, NID2, CAP350, CXCL1, BTN3A3, IL6, WNT5A, FOXF2, LPHN2, CDH1 1, P4HA1, GRP58, DSIPI, MAPILC3B, GALIG, IGSF4, IltS2, ATP2A2, OGT, TNFRSFIOB, KIAA.1128., TM4SF1, RBPMS, RIPK2, CBLB, NR1D2, SLC7A11, MPZLI, SSA2, NQOI, ASPH, ASAH1, MGLL, SERPINB6, HSPA5, ZFP36L1, COL4A1, CD44, SLC39AI4, NIPA2, FKBP9, IL6ST, DKFZP564G2022, PPAP2B, MAP1B, MAPKI, MYO1B, CAST, RRAS2, QKI, LHFPL2, 38970, ARHE, KIAA1078, FTL, KIA.A0877, PLCB1, KIAA0802, RAB3GAP, SERPINBl, TII~MMA, SOD2, HLA-A, NOMO2, LOC55831, PHLDA1, TMEM2, MLPH, FAD104, LRRC5, RAB7L1, FLJ35036, DOCK10, LRP12, TXNDC5, CDC14B, HRMTILI, CORO1C, DNAJCIO, TNPO1, LONP, AMIGO2, DNAPTP6, and ADAMTS 1, whose expression indicates sensitivity to radiation therapy.

v) One or more of the gene sequences FAU, NOL5A, ANP32A, ARHGDIB, LBR, FABP5, ITM2A, SFRS5, IQGAP2, SLC7A6, SLA, IL2RG, MFNG, GPSM3, PIM2, EVER1, LRMP, ICAM2, RLN1S3, FMNL1, MYB, PTPN7, LCK, CXorf9, RHOH, ZNFNlAl, CENTBI, LCP2, DBT, CEP1, IL6R, VAV1, MAP4K1, CD28, PTP4A3, CD3G, LTB, USP34, NVL, CD8B1, SFRS6, LCP1, CXCR4, PSCDBP, SELPLG, CD3Z, PRKCQ, CDlA, GATA2, P2RX5, LAIR1, Clorf38, SH2D1A, TRB@, SEPT6, HA-1, DOCK2, WBSCR20C, CD3D, RNASE6, SFRS7, WBS CR20A, NUP210, CD6, HNRPA 1, AIF 1, CYFIP2, GLTSCR2, C l 1 orf2, ARHGAP15, BIN2, SH3TC1, STAG3, TM6SF1, C15orf25, FLJ22457, PACAP, and MGC2744, whose expression iindicates sensitivity to an HDAC inhibitor.

w) One or more of the gene sequences CD99, SNRPA, CUGBP2, STAT5A, SLA, IL2RG, GTSE1, MYB, PTPN7, CXorf9, RHOH, ZNFNIAI, CENTBI, LCP2, HISTIH4C, CCR7, APOBEC3B, MCM7, LCP1, SELPLG, CD3Z, PRKCQ, GZMB, SCN3A, LAIR1, SH2D1A, SEPT6, CG018, CD3D, C18orf10, PRF1, AIF1, MCM5, LPXN, C22orfl 8, ARHGAP15, and LEF1, whose expression indicates sensitivity to 5-Aza-2'-deoxycytidine (Decitabirie).

Probes that may be employed on microarrays of the invention include oligonucleotide probes having sequences complementary to any of the biomarker gene sequences described above. Additionally, probes employed on microarrays of the invention may also include proteins, peptides, or antibodies that selectively bind any of the oligonucleotide probe sequences or their complementary sequences. Exemplary probes are listed in Tables 22-44, wherein for each treatment listed, the gene' biomarkers indicative of treatment sensitivity, the correlation of biomarker gene expression to growth inhibition, and the sequence of an exemplary probe (Tables 22-44) to detect the biomarker genes' (Tables 1-21) expression are shown.

Identification of Biomarker Genes The gene expression measurements of the NCI60 cancer cell lines were obtained from the National Cancer Institute and the Massachusetts Institute of Technology (MIT).
Each dataset was normalized so that sample expression measured by different chips could be compared. The preferred method of normalization is the logit transformation, which is performed for each gene y on each chip:
logit(y) = log [(y-background) / (saturation .- y)], where background is calculated as the minimum intensity measured on the chip minus 0.1 oo of the signal intensity range: min-0.001 *(max-min), and saturation is calculated as the maximum intensity measured on the chip plus 0.1 % of the signal intensity range:
max+0.001 *(max-min).
The resulting logit transformed data is then z-transformed to mean zero and standard deviation 1.
Next, gene expression is correlated to cancer cell growth inhibition. Growth inhibition data (GI50) of the NCI60 cell lines in the presence of any one of thousands of tested compounds was obtained from the NCI. The correlation between the logit-transformed.expression level of each gene in each cell line and the logarithm of G150 (the concentration of a given compound that results in a 50% inh.ibition of growth) can be calculated, e.g., using the Pearson correlation coefficient or the Spearman Rank-Order correlation coefficient. Instead of using G150s, any other measure of patient sensitivity to a given compound may be correlated to the patient's gene expression. Since a plurality of measurements may be available for a single gene, the most accurate determination of correlation coefficient was found to be the median of the correlation coefficients calculated for all probes measuring expression of the same gene.
The median correlation coefficient of gene expression measured on a probe to growth inhibition or patient sensitivity is calculated for all genes, and genes that have a median correlation above 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 0.95, or 0.99 are retained as biomarker genes.
Preferably, the correlation coefficient of biomarker genes will exceed 0.3.
This is repeated for all the compounds to be tested. The result is a list of marker genes that correlates to sensitivity for each compound tested.

Predicting Patient Sensitivity or Resistance to Medical Treatment For a given compound, the biomarker genes whose expression has been shown to correlate to chemosensitivity can be used to classify a patient, e.g., a cancer patient, as=sensitive to a medical treatment, e.g., administration of a chemotherapeutic agent or radiation. Using a tumor sample or a blood sample (e.g., in case of leukemia or lymphoma) from a patient, expression of the biomarker genes in the cells of the patient in the presence of the treatment agent is determined (using, for example; an RNA extraction kit, a DNA microarray and a DNA
microarray scanner)_ The gene expression measurements are then logit transformed as described above. The sum of the expression measurements of the marker genes is then compared to the median of the sums derived from a training set population of patients having the same tumor. If the sum of gene expression in the patient is closest to the median of the sums of expression in the surviving members of the training set, the patient is predicted to be sensitive to the compound or other medical treatinent. If the sum of expression in the patient is closest to the median of the sums of expression in the non-surviving members of the trai.ning set, the patient is predicted to be resistant to the compound.
Machine learning techniques such as Neural Networks, Support Vector Machines, K
Nearest Neighbor, and Nearest Centroids may also be employed to develop models that discriminate patients sensitive to treatment from those resistant to treatment using biomarker gene expression as model variables which assign each patient a classification as resistant or =
sensitive. Machine learning techniques used to classify patients using various measurements are described in U.S. Patent No. 5,822,715; U.S. Patent Application Publication Nos. 2003/0073083, 2005/0227266, 2005/0208512, 2005/0123945, 2003/0129629, and 2002/0006613; and in Vapnik V N. Statistical Learning Theory, John Wiley & Sons, New York, 1998; Hastie et al., 2001, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Springer, N.Y.;
Agresti, 1996, An Introduction to Categorical Data Analysis, John Wiley &
Sons, New York; V.
Tresp et al., "Neural Network Modeling of Physiological Processes", in Hanson S. J. et al. (Eds.), Computational Learning Theory and Natural Learning Systems 2, MIT Press, 1994, each of which are hereby incorporated by reference in their entirety.
A more compact microarray may be designed using only the oligonucleotide probes having measurements yielding the median correlation coefficients with cancer cell growth inhibition. Thus, in this embodiment, only one probe needs to be used to measure expression of each gene.

Identifying a Subpopulation of Patients Sensitive to a Treatment for Cancer The invention may also be used to identify a subpopulation of patients, e.g., cancer patients, that are sensitive to a compound or other medical treatment previously thought to be ineffective for the treatment of cancer. To this end, biomarker genes, whose expression correlates to sensitivity to a compound or other treatment, may be identified so that patients sensitive to a compound or other treatment may be identified. To identify such gene biomarkers, gene expression within cell lines may be correlated to the growth of those cell Lines in the presence of the same compound or other treatment. Preferably, genes whose expression correlates to cell growth with a correlation coefficient exceeding 0.3 may be considered possible biomarkers.
Alternatively, genes may be identified as biomarkers according to their ability to discriminate patients known to be sensitive to a treatment from those known to be resistant. The significance of the differences in gene expression between the sensitive and resistant patients may be measured using, e.g., t-tests. . Alternatively, naive Bayesian classifiers may be used to identify gene biomarkers that discriminate sensitive and resistant patient subpopulations given the gene expressions of the sensitive and resistant subpopulations within a treated patient population. The patient subpopulations considered may be further divided into patients predicted to survive without treatment, patients predicted to die without treatment, and patients predicted to have symptoms without treatment. The above methodology may be similarly applied to any of these fin-ther defined patient subpopulations to identify gene biomarkers able to predict a subject's sensitivity to compounds or other treatments for the treatment of cancer.
Patients with elevated expression of biomarker genes correlated to sensitivity to a compound or other medical treatment would be predicted to be sensitive to that compound or other medical treatment.
The invention is particularly useful for recovering compounds or other treatments that failed in clinical trials by identifying sensitive patient subpopulations using the gene expression methodology disclosed herein to identify gene biomarkers that can be used to predict clinical outcome.

Kit, Apparatus, and Software for Clinical Use This invention may also be used to predict patients who are resistant or sensitive to a particular treatment by using a kit that includes a kit for RNA extraction from tumors (e.g., Trizol from Invitrogen Inc), a kit for RNA amplification (e.g., MessageAmp from Ambion Inc), a.
microarray for measuring gene expression (e.g., HG-tt133A GeneChip from Affymetrix Inc), a microarray hybridization station and scanner (e.g., GeneChip System 3000Dx from Affyrnetrix Inc), and software for analyzing the expression of marker genes as described in herein (e.g., implemented in R from R-Project or S-Plus from Insightful Corp.).

Methodology of the In Trtro Cancer Growth Inhibition Screen The human tumor cell lines of the cancer screening panel are grown in RPMI

medium containing 5% fetal bovine serum and 2 mM L-glutamine. Cells are inoculated into 96 well microtiter plates in 100 L at plating densities ranging from 5,000 to 40,000 cells/well depending on the doubling time of individual cell lines. After cell inoculation, the niicrotiter plates are incubated at 37 C, 5% C02, 95% air and 100% relative humidity for 24 hours prior to addition of experimental compounds.
After 24 hours, two plates of each cell line are fixed in situ with TCA, to represent a measurement of the cell population for each cell line at the time of compound addition (Tz).
Experimental compounds are solubilized in dimethyl sulfoxide at 400-fold the desired final maximum test concentration and stored frozen prior to use. At the time of compound addition, an aliquot of frozen concentrate is thawed and diluted to twice the desired final maximum test concentration with complete medium containing 50 g/znl Gentamicin. Additional four, 10-fold or 1/2 log serial dilutions are made to provide a total of five compound concentrations plus control. Aliquots of 100 l of these different compound dilutions are added to the appropriate naicrotiter wells already containing 100 1 of medium, resulting in the requixed fmal compound concentrations.
Following compound addition, the plates are incubated for an additional 48 h at 37 C, 5%
C02, 95% air, and 100% relative humidity. For adherent cells, the assay is terminated by the addition of cold TCA. Cells are fixed in situ by the gentle addition of 50 l of cold 50% (w/v) TCA (final concentration, 10% TCA) and incubated for 60 minutes at 4 C. The supernatant is discarded, and the plates are washed five times with tap water and air-dried.
Sulforhodamine B
(SRB) solution (100 l) at 0.4% (w/v) in 1% acetic acid is added to each well, and plates are incubated for 10 minutes at room temperature. After staining, unbound dye is removed by washing five times with 1% acetic acid and the plates are air-dried. Bound stain is subsequently solubilized with 10 mM trizma base, and the absorbance is read on an automated plate reader at a wavelength of 515 nrn.. For suspension cells, the methodology is the same except that the. assay is terminated by fixing settled cells at the bottom of the wells by gently adding 50 l of 80% TCA
(final concentration, 16 % TCA). Using the seven absorbance measurements [time zero, (Tz), control growth, (C), and test growth in the presence= of compound at the five concentration levels (Ti)], the percentage growth is calculated at each of the compound concentrations levels.
Percentage growth inhibition is calculated as:
[(Ti-Tz)/(C-Tz)] x 100 for concentrations for which Ti>/=Tz [(Ti-Tz)/Tz] x 100 for concentrations for which Ti<Tz Three dose response parameters are calculated for each experimental agent.
Growth inhibition of 50% (G150) is calculated from [(Ti-Tz)/(C-Tz)] x 100 = 50, which is the compound concentration resulting in a 50% reduction in the net protein increase (as measured by SRB
staining) in control cells during the compound incubation. The compound concentration resulting in total growth inhibition (TGI) is calculated from Ti = Tz. The LC50 (concentration of compound resulting in a 50% reduction in the measured protein at the end of the compound treatment as compared to that at the beginning) indicating a net loss of cells following treatment is calculated from [(Ti-Tz)/Tz] x 100 =-50. Values are calculated for each of these three parameters if the level of activity is reached; -however, if the effect is not reached or is exceeded, the value for that parameter is expressed as greater or less than the maximum or minimum concentration tested.

RNA Extraction and Gene Expression Measurement Cell/tissue. samples are snap frozen in liquid nitrogen until processing. RNA
is-extracted using e.g. Trizol Reagent from Invitrogen following manufacturers instructions. RNA is amplified using e.g. MessageAmp kit from Ambion following manufacturers instructions.
.Amplified RNA is quantified using e.g. HG-U133A GeneChip from Affymetrix Inc and compatible apparatus e.g. GCS3000I?x from Affymetrix, using manufacturers instructions.

The resulting gene expression measurements are further processed as described in this document. 'The procedures described can be implemented using R software available from R-Project and supplemented with packages available from Bioconductor.
For many drugs 10-30 biomarkers are sufficient to give an adequate response, thus, =given the relatively small number of biomarkers required, procedures, such as quantitative reverse transcriptase polymerase chain reaction (qRT-PCR), may be performed to measure, with greater precision, the amount of biomarker genes expressed in a sample. This will provide an alternative to or a complement to microarrays so that a single companion test, perhaps more quantitative than microarrays alone, employing biomarkers of the invention can be used to predict sensitivity to a new drug. qRT-PCR may be performed alone or in combination with a microarray described herein. Procedures for performing qRT-PCR are described in, e.g., U.S. Patent No. 7,101,663 and U.S. Patent Application Nos. 2006/0177837 and 2006/0088856. The methods of the invention are readily applicable to newly discovered drugs as well as drugs described herein.
The following examples are provided so that those of ordinary skill in the art can see how to use the methods and kits of the invention. The examples are not intended to limit the scope of what the inventor regards as their invention.

EXAMPLES
Example 1: Identification of gene biomarkers for chemosensitivity to common chemotherapy drugs.
DNA chip measurements of the 60 cancer cell lines of the NCI60 data set were downloaded from the Broad Institute and logit normalized. C'rrowth inhibition data of thoiisands of compounds against the same cell lines were downloaded from the National Cancer Institute.
Compounds where the difference concentration to achieve 50% in growth inhibition (G150) was less than 1 log were deemed uninformative and rejected. Each gene's expression in each cell line was correlated to its growth (-Iog(GI50)) in those cell lines in the presence of a given compound.
The median Pearson correlation coefficient was used when multiple expression measurements were available for a given gene, and genes having a median correlation coefficient greater than 0.3 were identified as biomarkers for a given compound.

Example 2: Prediction of treatment sensitivity for brain cancer patients.
DNA chip measwrements of gene expression in tumors from 60 brain cancer patients were downloaded from the Broad Institute. All data files were logit normalized. For each of the common chemotherapy drugs Cisplatin, Vincristine, Adriamycine, Etoposide, Aclarubicine, Mitoxantrone and Azaguani.n.e, the gene expression for the marker genes was summed. The sum was normalized by dividing by the standard deviation of all patients and compared to the median of the sums of patients who survived and the median of the sums of patients who died:
NorznalizedSum(compound) =
sum(marker genes for compound)/sd(sums of all patients) Sensitivity(compound) =
[NormalizedSum(compound)-mediarz(NormalizedSumdeadpatients(compound))]z [NormalizedSum(compound) - median(NormalizedSumsurvivingpatients(compound))]2 Figures 2 and 3 show the resulting treatment sensitivity predictions for two of the 60 patients. All patients received Cisplatin and the prediction of survival amongst the 60 patients based on their Cisplatin chemosensitivity yielded the Kaplan=Meier survival curve shown in Figure 4. The expression of the 16 Cisplatin biornarker genes was first reduced to 5 components (dimensions) using Independent Component 'Analysis (fastICA). Five different classification methods were trained on the five components from the 60 patients: K Nearest Neighbor with K=1, K Nearest Neighbor with K=3, Nearest Centroid, Support Vector Machine, and Neural Network. Chemosensitivity or sensitivity to radiation treatment was predicted by combining the classifications of the five methods wherein each classification method was assigned a single vote:
unanimous chemosensitive/treatment sensitive prediction resulted in a prediction of chemosensitive/treatment sensitive. All other predictions resulted in a prediction of chemoresistant/treatinent resistant. The performance of the combined classifier was validated using leave-one-out cross validation and the survival of the two predicted groups shown in Figure 4. The survival rate of the patients predicted to be chemosensitive was higher than the patients predicted to be chemoresistant.

Example 3: Prediction of chemosensitivity for lymphoma (DLBCL) patients.
DNA chip measurements of gene expression in the tumors from 56 DLBCL (diffuse large B-cell lymphoma) patients were downloaded from the Broad Institute. All data files were logit normalized. All patients received Vincristine and Adriamycine and the prediction of survival =
amongst the 56 patients based on their Vincristine and Adriamycine chemosensitivity yielded the Kaplan-Meier survival curve shown in Figure 5. The expression of the 33 Vincristine genes and 16 Adriamycine genes was first reduced to 3 components (dimensions) using Independent Component Analysis (fastICA). Five different classification methods were trained on the independent components from the 56 patients: K Nearest Neighbor with K=1, K
Nearest Neighbor with K=3, Nearest Centroid, Support Vector Machine, and Neural Network.
Chemosensitivity was predicted by combining the classifications of the five methods wherein each classification method was assigned a single vote: unanimous chemosensitive prediction resulted in a prediction of chemosensitive. AlI other predictions resulted in a prediction of chemoresistant. The performance of the combined classifier was validated using leave-one-out cross validation and the survival of the two predicted groups is shown in Figure 5. The survival rate of the patients predicted to be chemosensitive was higher than the patients predicted to be chemoresistant.

Example 4: Prediction of chemosensitivity for lung cancer patients.
DNA chip measurements of gene expression in the tumors from 86 lung cancer (adenocarcinoma) patients was downloaded from the University of Michigan, Ann Arbor. Of the 86 patients, 19 had Stage III of the disease and received adjuvant chemotherapy. Raw data was logit normalized. Instead of the combined classifier described for the brain cancer and lymphoma examples above, the sum of biomarker gene expression was calculated for each patient and used to discriminate chemosensitive and chemoresistant patients. For each patient, the gene expression of the 16 marker genes for Cisplatin sensitivity (all Stage III patients received Cisplatin after surgery) was summed. If the sum was closer to the median of the sums of the surviving patients, the patient was predicted to be sensitive to Cisplatin. If the sum was closest to the median of the sums of the non-surviving patients, the patient was predicted to be resistant to Cisplatin. The survival rates of the two predicted groups are shown in Figure 6. The survival rate of the patients predicted to be chemosensitive was higher than the patients predicted to be chemoresistant.
Egample5: Prediction of Rituximab sensitivity for lymphoma (DLBCL) patients.
The method is not limited to cytotoxic chemicals. It is also applicable to predicting the efficacy of protein therapeutics, such as monoclonal antibodies, approved for treating cancer. For example, the monoclonal antibody MABTHERAm (Rituximab, RITUXANT~") was examined.
Data for cytotoxicity of Rituximab in cell lines in vitro were obtained from published reports (Ghetie et al., Blood, 97(5):1392-1398, 2001). This cytotoxicity in each cell line was correlated to the expression of genes in these cell lines (downloaded from the NCBI Gene Expression Omnibus database using accession numbers GSE2350, GSE1880, GDS181). The identified marker genes were used to predict the sensitivity of DLBCL to Rituximab in a small set of 14 patients treated with Rituximab and CHOP (R-CHOP) (downloaded from NCBI Gene Expression Omnibus under accession number GSE4475). Conversion between different chip types was performed using matching tables available through Affymetrix.
The. survival of patients predicted to be sensitive to be R-CHOP is compared to the survival of patients predicted to be resistant to R-CHOP in Figure 7. The survival rate of the patients predicted to be chemosensitive was higher than the patients predicted to be chemoresistant.
To predict the sensitivity toward combination therapies, such as those used to treat Diffuse Large B-cell Lymphoma (DLBCL), patient sensitivity to a particular combination therapy is predicted by combining the marker genes for the individual compounds used in the combination. An example of this is shown in Figure 8, where the predicted sensitivities of one patient towards a number of combination therapies used against DLBCL
(identified by their acronyms) are shown: R-CHOP contains Rituximab (MABTHERATM), Vincristine, Doxorubicin (Adriaznycin), Cyclophosphamide, and Prednisolone; R-ICE contains Rituximab, Ifosfamide, Carboplatin, and Etoposide; R-MIME contains Rituximab, Mitoguazone, Ifosfamide, Methotrexate; and Etoposide; CHOEP contains Cyclophosphamide, Doxorubicin, Etoposide, Vincristine and Prednisone; DHAP contains Dexamethasone, Cytarabine (Ara C), and Cisplatin;
ESHAP contains Etoposide,.Methylprednisolone (Solumedrol), Cytarabine (Ara-C) and Cisplatin; and HOAP-Bleo contains Doxorubicin, Vincristine, Ara C, Prednisone, and Bleomycin.

Example 6: Prediction of radiosensitivity for brain tumor (medulloblastoma) patients.
The method of identifying biomarkers can also be applied to other forms of treatment such as radiation therapy. For example, sensitivity to radiation therapy was predicted for brain tumor patients. Radiation therapy in the form of craniospinal irradiation yielding 2,400-3,600 centiGray (cGy) with a tumor dose of 5,300-7,200 cGy was administered to the brain tumor patients using a medical device that emits beams of radiation. Sensitivity of the 60 cancer cell lines used in the NCI60 dataset to radiation treatment was obtained from published reports. This sensitivity was correlated to the expression of genes in the cell lines as described above to identify marker genes. DNA .microarray measurements of gene expression in brain tumors obtained from patients subsequently treated with radiation therapy were obtained from the Broad Institute. The identified gene biomarkers were used to classify the patients as sensitive or resistant to radiation therapy: The survival of the patients in the two predicted categories is shown in Figure 9. The survival rate of the patients predicted to be sensitive to radiation therapy was higher than the patients predicted to be resistant to radiation therapy.

Example 7: Drug rescue.
Every member of a population may not be equally responsive to a particular treatment.

For example, new compounds often fail in late clinical frials because of lack of efficacy in the population tested. While such compounds may not be effective in the overall population, there may be subpopulations sensitive to those.failed compounds due to various reasons, including inherent differences in gene expression. The method as described herein.can be used to rescue failed compounds by identifying a patient subpopulation sensitive to a compound using their gene expression as an indicator. Subsequent=clinical trials restricted to a sensitive patient subpopulation may demonstrate efficacy of a previously failed compound within that particular patient. subpopulation, advancing the compound towards approval for use in that subpopulation.
To this end, in vitro measurements of the inhibitory effects of a compound on various cancer cell samples from the responsive patient subpopulation collected as.described above or measures of clinical response of a treated patient are compared to the gene expression of cells from those patients. The growth of the cancer cell samples can be correlated to gene expression measurements as described above. This will identify marker genes that can be used to predict patient sensitivity to the failed compound. Preferably, biomarker genes will be identified within the patient.population previously shown to be sensitive to the failed compound. Once biomarkers are identified, the expression of biomarker genes in patients can be measured according to the procedure detailed above. The patients are predicted to be responsive or non-responsive to compound treat.ment according to their gene biomarker expression. Clinical effect must then be demonstrated in the group of patients that are predicted to be sensitive to the failed compound.
The method may be further refined if patients responsive to the compound treatment are further subdivided into those predicted to survive without the compound and.those predicted to die or suffer a relapse without the compound. Clinical efficacy in the subpopulation that is predicted to die or suffer relapse can be further demonstrated. Briefly, the gene expression at the time of diagnosis of patients who later die from their disease is compared to gene expression at the time of diagnosis of patients who are still alive after 5 years. Genes differentially expressed between the two groups are identified as prospective biomarkers and a model is built using those gene biomarkers to predict treatment efficacy.
Examples of compounds that have failed in clinical trials include Iressa (Gefi.nitib, AstraZeneca) in refractory, advanced non-small-cell lung cancer (NSCLC), Avastin (Bevacizumab, Genentech) in first-line treatment for advanced pancreatic cancer, Avastin (Bevacizumab, Genentech) in relapsed metastatic breast cancer patients, and Tarceva (Erlotinib, Genentech) in metastatic non-small cell lung cancer (NSCLC)_ The method of the invention may be applied to these compounds, among others, so that sensitive patient subpopulations responsive to those compounds may be identified.

Example 8: Median of the correlations versus correlation of the median.
The median of the= correlations of the individual probe measurements to cancer cell growth as employed by the invention was compared to the correlation of the median probe measurements: this will determine at which step of the method a-median calculation should be performed. In the former, several correlations are calculated for each gene since multiple probes measure a given gene's expression, but only the median of the correlation coefficients is finally retained to identify biomarkers. In the latter, only one correlation is calculated for each gene because only the median gene expression measurement is considered for each gene. Figure 10 shows the results of using the correlation of the median expression measurements to identify biomarker genes of radiation sensitivity predicting the survival of 60 brain cancer patients. The difference in survival between the group predicted to be radiation sensitive and the group predicted to be radiation resistant in Figure 10 is much smaller than the difference depicted in Figure 9 which employed a median correlation coefficient suggesting that the invention's median of the correlations employed in Figure 9 outperforms the correlation of the median depicted in Figure 10.
If we look at individual marker genes like OMD, the median of the correlation to measured radiosensitivity'o'f cell lines in vitro is 0.32. =The correlation of the median, however, is 0.3.9. Adjusting the cutoff from 0.3 to 0.4 to compensate for the difference does not improve on Figure 10, however. . , We have also compared median correlation to.weighted voting as proposed by Staunton et al., PNAS 98(19):10787-10792, (2001). Weighted voting produced a poor result similar to that of Figure 10, with a P-value of 0.11.

Other Embodiments All publications and patent applications mentioned in th.is.specification are herein zncorporated by reference to the same extent as if each independent publication or patent application was specifically and individually indicated to be incorporated by reference.
While the invention has been described in connection with specific embodiments thereof, it will be. understood that it is capable of further modifications and this application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure that come within known or customary practice within the art to which the invention pertains and may be applied to the essential features hereinbefore set forth.

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[SSr] t75P'1 T~~le 6. i~slntrt6l.c3n bd bmasivers 3,13~_2Ap~ zist 2005 Liat tYiGZ L st_PrcfeFr Carsx~Ldk3.oa [1rp 3zPL12 Rr+s,12 0.3 [2r] RPL32 RPL32 0.37 13, ] RPLPZ R8L82 ItPI.t:'.2 0.37 ( a r E hYB MSC9 ?i1B 0. 31 [5,1 L31F19IA.1 stTE].a1 0-34 16,1 R''CAFi SCAP1. 0.33 ['7r] $',CdT4 $2 AT4 0.31 18,1 si'140 sP140 0.4 [3r SMl'Sa3 AxFo3 t1.3 [10,1 +FqgAIPO ThYI*R:fF'8 0.4 (,11, ) 'pAS1D DDX38' 0.31 (12 , ) TAT5 TA~-5 0.3 [13r] 8'AL 1''ffi. 0.41 [140] RPS2 R862 0.34 (15,] -Pa4 PTriRC 0.37 [ 2 6,) DOCSC2 DOCR2 0.32 [17,] Gex65 0PR65 0.35 (18 r] HOS99 907GT49 0.33 (19,) t'r 732270 gTJ;2~70 4.31 (204 IMRFD amr~D 0.c [23, J r.AMAl (22,] RP62S
['13, ) E'ixFSA
(2q,] xorea [25, ) HlIt"Al [26,) RPSB
[27,1 ARMa (28s) 8.3:1+48 129,1 S[eGBa 0 0, ) sa61Sn [31.t xFSfi TGb16 7. MzitoraatroaA btomxricers Lisx 2006 L.ist 2iJ05 Liat Prxcr Liat -Prelerr Casge3.atian (I.} 2422YN3 PGAesi 0,.32 E2,) Di'Y6L3 [ki+YSt,3 0,39 (3.I 1~s~GX SHS2G1 0.32 [4r} ~7h1 0m1 0.31 CSe1 ~Pl 9PTP3 0.31 C6a) ~1 FRiil P.RGI 0.39 [7,) GePD c~Pn G6PP 0.34 [ 8 r) 13I4&Pl HASPl 0.31 [9p] r1.oU2 r2,CD2 0_34 (10,] LUY'L2 L6KL2 0.31 [f.le} 6S6iY2 858P2 0,.36 112,,) CLorf29 Cicr#24 0.35 413r ) 'j'OX '16X 10.35 [14r) STCl ~oTCS fl.39 [i5r] TnYR8lflh Tl1kb~SF#21 'CNP'FiSP'F8 0.14 [ 16r 1 7iCOR2 tlCpFi.2 QpCQR2 0.3 [L7.) fl7k41L1 ND.FILI RAPLL2 0.32 [f$A] .LQC$410S 7.OC94105e 0._34 B19a] CpL6X2 CaZ6~2 0.3 120a] ARHGEP6 h8tftsrFG'6 E4R13Ci$F5 0.34 [21,] GAT3L3 GAlTA3 3 iF _ 35 IZ2, ) TE71 T71 9.31 123,1 T.EkM bnT 0.31.
124,t CB3S QD38 9.37 [25#1 AFl.Q ,+lE'1Q 0.33 (26. y W1D HAI+ls FMF1H 9.34 (27a ) kTERC PTAEBC . fi..31 12811 99C4 . . FRKCA. 0.35 129,1 7CRIK22 TtiIiC22 0.3 [30,] CD3D Ctt3D 0.31 [32,1 acAai srS.;ri 0.32 [32,1 IH'I44 3F144 0.33 (33.1 CCL2 cCr.P 0.37 [346) RA$31 R'A931 0.31 [35,) Curc CuTC 0.33 (36,) NAt'~1L2 RFiPF= 0.33 [37,) t=7 RME7 0.35 (38,) 1"L321159 PL721150 0.33 (39. ) CQl.5112 Ca2.5A2 0.39 [ 4f-r ) Mis (41,1 oli/sW-.o l. S6 020) TOP2A
f43,) 9LA2s (44r) PY44'1 [45r1 71MD1 (46f) AH7RBAl ['t7r 1 RL''L9 148,1 . C5+Dcz$13 [4Qr1 w37,8 [50r] TM3 ($1-) HtlGq2 (52.) PaFS1 (53.1 oDBS
1540 9'P3:A
(55e1 PS21B9 156.1 6L4'RP!
Tab].e 8. bitoMyciftbi=ar)m--rs Lf.*t :406 FxG768oo .Gi't 1'rlor L3 G+, PrGfdrt Coxs clEeti.on [1r1 STC.1 STC3 0.34 [3r) 0'PFt6S - CM65 Q.3Z
[3r1 DOCeaic? Z74c1t14} 0.35 [4rl COLshx CGF+Sfi2 Q.33 [5r) FP,e646A PAT986A 0.36 ,*6rl 2.0C54.103 L4C54103 0.39 Ta4.Ee 9_ PacZitazal (Taxol) tr.f=arkera List 2006 Hi1fiRDD List 1+=ior l,iat Prsfarr Carrelatiflm [1,1 "id itPt,~10 0.31 [2,] tiP54X RP5;4x 0_31 [3rI OCDC ri7uDC 0.3 14, ) PALp ttFiL~ 4.31 [5.] ARmn GRCZ 0.3 [6,] DSE'5P544CI 6 MZP564QI80 0.32 [7,] P&iT1B PRP19 0.3k [ 9 r] RPiB4P 60 It7199P4Q 0.33 [9,] H8919761 H0A9761 0_37' [10r] akm$ G[+Jt78 0.3 [11.] CEP; CSPi 0.3 [12.1 IL13P12 IL1,31t]52 0.34 [18.1 kAC=2 mGsH2 0.41 [ 14r1 P3=2 HLNCN2 D.35 (15,1 A:"1 AL4i51 0.3 (16,.) 6PRB5 CiPR65 0,31 [17,.) P!LJ'10774 1r2.J10774 0.31 (18, J HULB 3TitLB 0 .31 [14ri AA3"AP2 nA W. 2 0,32 (Z4,1 S:LCZSAl"s SW,2SA,15 013;
121.r] I+AF'53 21tF53 0.3f 122,1 3s"879e J)k59075S 0.31 i23ej PITPKCI PIIP'SC1 0.33 [24,) 8PAP1XC Si l.NXC 0.3 125,1 NYAA1393 ISIAA3393 0.33 Tabl+n 10. GemcitA4it~c JGemaar~ bs~kma~>~A
x+.t.a'k_,2Oa8 A06800 Ltat P.rio.s Lifit PreierX tarrc1.nti.=
Cxrl 8PR1 p87q1 G.77 C2.7 PGAK1 PGAN1 0.35 E3r1 x+-,pLPiiA-1 1[.. AY&'aA.-1 Q.34 E'4rl {%8 A C91}Pi 0}31 Cs.l ucaLl. vCHLl 0õ36 Ese7 PW1 pwei 0.31 -( 7 d) i~ALKZ-AGri7eB PALM2AUP2 4.31 ( 8 r y'1't7~'1i5rT.A '1'&U'RaP 1a 0.31 E9.1 ATP502 Afi4st92 0_36 [IOrj AP'iit AL"iQ 8.31 [ELeI VW4 DLMFF4 fl.31 [M,1 mnanl rucrv.i flw32 Tahle 23.. TapepCqre (dooptaxel) bjomgLrkers I+i.~t 2D06 I~fat 2aa5 Lixt Priar L3at prc~farr Cprrr~l~t30it (L.j Aa~a32a ARP~321a 0.45 C3.7 CfIF:iJF. 6',Ck"u 0.31 13.7 RRM2 wxM? 0.31 1411 THIM14 4~.Rg714 0.31 [5.l SStP2 S"2 0.33 t6,] 'lREi'13 ;PAXP13 0 . 36 (7f] =3 t+3'C3 0.45 (8. ) CA81+7 C)L&P7 0.32 ( 9,0lT= TXN 0.36 (10. ) }=5 klCtl5 0.34 (ll,k PTG6&Z' PTCE$2 0.39 (12. ) oBrG1 08FCI 0.37 {I3. j B'891L4B 8PQ41L48 0.32 114.1 c3:Lt3[,4 CAS,MiA d: 31 TaD3e a2. I3rxamttattsPns biomar'lcrars L1.W~2QQ8 k7Ct4V00 3.i tprl~rr xFlSt ftmlc= veaxr*xa,t~=.
I 3 r 1 IPTTM2 IE'ETYl2 0.38 tZ.l MMZLb oHE2L8 0.32 T3,1 LAPTt]S LApTt=]S= i.a~'kg E1.366 14,1 CbSPA 'tr5k-4 0_33 ES-1 TTM2A YrKaA 0.38 E3:] 7T108: 33YS62 0.42 (7,) AWPZP A14lCP 0.31 E 6s 1 C'053 C 53 0.34 E901 xL2RQ ST3F3G 3.i,2Rt'i 0.36 [ia,] cQ37 C037 0.34 E 11t ] GPR3tSp1 GPR74SP1 0.36 E=l2, 7 PTM PlRx? 0131 E13,] cxnrf4 cxorf5 0.36 (14 Ir] B,HS)H AHDB RHOE! 0.313 j1St] ~1i~2 GS72 0.31 (16,1 AT7+OP8.2A At14Lt42A 0.31 (27r ) Siii+2VlA1 ZNPN1A1 0.35 (19,1 GNA 15 GNM5= G2JA1S 0.33 (19t1 CLE1 = C8P1 0.32 421011 TCP?tS73' . T~IPRSP 7 0.46 I 21 ,F mp4K1. rv~4s1 O.3 122,1 cczt.T =7 0.3:x {23 ,1 CD3G C.'C3tf 0.35 124,1 kT1+itC FTl'AC 0.41 t25,) AVFT.2l3,3 ATZ'214i3 r'iP3P2A3 0.4 (2dr1 UCP.". VCF2 . 0.3 E270 1CQxi,O1.A CesaoM CoimlA V.39 72.

(2$r 1 CA'~-"U GATA9 C71"1A3 0.37 (29,1 CMttt2A t"DRgzA 0.32 j3{)a'J TIEMl 9=I 0.3 131, ) TJ1IiP TA[iP 0.3 E32a I L1iZR1 1+A=1 0.34 (33, I 59:201A =6NSOlah 0.34 f34, ) Ft,'EX 2Z1S rwI 0.33 135, I GZPT6 sIIIE'T4 0.34 136, SAw1 H3k-~ 0.34 137M1 G=3Ial CSFB3i.1 0F31 [36,~ L~RCC2 8RCC2 0.55 ( 3'a r 2 C~3 ~- CP391 ~D3p 0.32 (d0rF l+s'S'1 7:sTL 0.3$
ASPI Y.EBL 0.35 142,1 ADa ASSa D.,43 143,1 DATFY VATPi 0.41 [44, J ARECliP15 ARgCA3+f5 0.3 145,1 PS,apB ptaCB 0.31 [46.) Cnck1 CSCR1 -0.31 [47,1 i,ac83S58 S,OC81558 0,33 [99.) Lrgb2 $HD2 0.37 T.abla 13. Ara-C (C}-taarAbi" 11yC7r4oh1OrfdCe) 3ti07Abtskttj;
List_2006 EV+6800 Ust Px#.rsr Umt k*re:4crr Cors+al+at3o+n [ l r] STl92ai I LM2A 9.32 (2.I RO4H It'SOA 0_33 [ 3 r) F'VX67]= H=M3 0.3 VE, j CIIl4T8'y. CEST81 0.31 [$.7 Gra15 Ga7711S pM
[6r3 W&PIL3= 1vik'1L.1 V.AF1L1 9_31 E7rl ATP562 AY'P507 0.31 18,3 G?i'iA3 CA'1'2k3 0 _33 E~r3 P '~'4 PRKCQ 0.32 [ 1[#, 592h1A &S2D1A 0.3 5]i1AT6 SBPT6 8.42 E12,~ FTPiiC i'TPStC 0.,33 L13,1 tiP134 MP, ,4 0.33 C24 I zti+i:.13 RpL13 0.3 ~ 15, I CEW C03D 9.31 [ LG r 7 Grin . CA11S
L 27' r] Al?A 15DA 20A 0.34 LISrJ ~~DY 86oDt 0.31 Tab2e 14. iteth5aipredaisolonm 6iamarksra 336t_2D06 Huf:340 S,iat Frior List Preferr Carralatian [ 1 s j CD95 CL?99 C#3D9 0.31 ( 2. j SFtRtS2 SRRHI 0.31 ( 3: ~ AStHWCIB A'&9GLI8 ,itRHC+ATB 6.31 [4, I LA1'Tl75 LAPE'6S5 LA,FWK5 0. 37 [5rI v4m '4'RfF 6,45 [9, J ,LTM21L 3T7I2A 0.35 [7.1 XTcE'2 I'tZ32 LTGB2 0.43 [ B~ ] LGALS.g Y,Gni,S9 'GGF1t,S3 6.43 L9,1 197Z'SD SGlAP'50 0_34 tYD, ] SAZS1 5AtJ41 Mca=l 0_32 (11.) C1?53 C053 CD53 0.33 (12,1 TP'DF2 'FFD82 TFG182 ID. 4 (130) SLk 8LA sloa 0.31 [].4 ,] 3L2RG SL23L6 7S,2RG0.3 ! r.G M~NG 0.3 (16r1 CD37 CD37 0.37 [17,) GaE'G= GdEG 0.4 f184e ) en= 0.35 [ 19, ] COFPSa. CaWSz CDF~z 0. 33 (20p) I-vE LBeeP 0.32 12,P) Ycpm I47sM2 0.38 [2201 =153 Ras53 0.36 P30 ?TFGT7 Y'~.'Pl17 PTP~77 0.39 Ia4-J +AYtHG74P25 P M=25 0.37 {25r] 1= ?GClt SCi< 0.1 f26r1 CRarf9 CXor19 0.3 lZ7r1 1n05 RSU.H RHC4H 0.51 (28t) p7.'lqbQAB 1"T;'RCl+ P P9~'itG1P 0.5 f24r1 ~1;7='2 GiT2 0.33 [}0~] ESIF LA7. ZHpAiAI YmlAl 0 .$$
[31r [ CEflT81 CESTBI CB1Q.1!$1 0.3S
L32r1 LC22 Td_P2 0.34 [33,] 8P21 8?S1 0.3 [34, ] G17A13 CNA15 G1q7415 0.39 [35r] OtHL 657lh 0.31 06.) C.t:3"] CLPl 0.37 [37r y $LX aLbS 0.33 f30r1 CDO& CD031 0.38 f39,l 9C.AP1 6CAY1 0.32 (40,1 CDZ C92 0.46 [41,j CD4C eDF.C CDLC 0.37 (42,1 2'NFRSF7 TWrRfiP7 0.31 f 43r 1vxv3 VA9l 0.41 14.4 r] lyA i"+GbCl F7A~"llC1 KAP9KL 0i*36 [45r] CC.R2 CCR.! 0.17 [46,1 C6crf32 C6as232 0_3$
f6Tr1 P.1,07158 Ai11X158 4~43 140r1 HND3' SEtQT 10.33 f49r3 CD3C CD34 C63G 0.S2 [50,. ) p1'P1iC ~TFeC 0.37 fsi'] ram ZTH 0.32 ISS,P) A7i*2A:7 1+1'3'FYA3 ATF2A3 0.3 15.3,3 xvi. tWvi, 0.31 t54, ) RP,&q"Z R~+6c1P2 0:35 [5.5d ) LC~.*I LC3.1. 1,C. 1 0.34 [58r ) t"OVRQ3A CfORO2A CQROIA 0.41 157y] c7xm C1iC&d CXCR+1 0.3 f38r1 PRI-z 8RwA2 0_33 [59r1 GA4'A3 GAi"A3 GATD3 0_39 [6aeI sRR0 TBAY 0.4 161, ] PRKC81 PR1=1 PB.I(C83 0.33 192,1 Rmm.1 M.Nl 0.32 =
[63,] kTAr10922 KIAA0922 0.34 f 6a, ] TA" h'ARP 0.49 E65,1 5603112 88C31312 0.32 t661) F8XCQ P1fi1CCQ 0.37 C67,.) SAZQIA 6H2D1A 0.33 [ 6 9 f 1 O}iRH3}3 CBRiTA9 0. 5 (89F 1 CD34 CD1A O.+FA
f10r) L'ST1 L$.G.i 0.36 [ 71 r) LRI$1 I,A2R.1 0.47 t72,1 CACN7i1G CaCNAl+3 0. ti3 [73r] TRBB TRB@ 1RaQ 0.31 P40 68P76 fUT6 5151"76 4,.33 ('F5 f4 HA-1 &A-1 0.62 f76rj ROCEC2 DOeh3 0.32 [71,1 CD3D CD30 CYt3D 0.41 [78,] TeD@ Mb@ 01-30 [79.I T3JA15 T3aBts 0.37 [ ar] 8NBP1 Y77HPf G,37 tes,Y cas cn6 0.4 i82.1 AIY1 A371 AIF1 0.31 [B3.] 7=E31 I'oLH3 10.45 (04,} C1711", CD18 C'Y-1S 0.50 [d5,] US9 L5t9 0.39 (86r] AGl3B1# 4GaPZ8X7 0.47 [37,j ALL& hDA 11AlA 0.39 E38r] cmms RDRLS 0.44 [89r l TA734 T]tl7d D.38 [9412 BsnG 89L 0.39 E91,1 DlLTP1 PATFl 0.31 [92,] RGC32 AM32 0.53 (33, ] rRXCx PaxCH 0.3 [4d,] xxsaAP15 atABGa.F15 0.3+1 [4~,] mOTCHL nt?ilGg3 0.36 E9fi,) 8xN$ 83392 0.31 =[ g7 r') tlEMA44 817JA9G 0. 35 C9$,1 "SP2 FE?2 0.33 [g9rl C8CR1 CLCR1 0.34 [k00,3 8CLL1B SCL31B 0_33 110I,1 STAG3 STAZ3 0.41 [Yd2r] GI#LN'P6 {'aALNT6 0.32 [~d3rl U'aASOP, ti0A8S31- 0.3 [ tOd r J PtiSta$ - PREM7: 9.38 [ f03 r] P'LJ'13373_ FW13373 0.34 [106,1 TrBLrE 3,E~1 4.49 jL07,1 Yf.21$ TI.7-1R 0.42 1108,1 EiGCi7330 MGc17330 0.33 =109iJ ASSFiB13 11tCAP13 0.53 [ 1tD, 3uP'335 9tW335 0.3 lLfl, ] (iTKKP5 i4TS7AgS 0.34 Ta3r1C 15. :6etturtr~x4tt kri,nasax3f4rs Lf.pt~2006 4Tf6809 F.~--ftf.cx Lx.ot Prefe= Car=?atioa [ i+ JPRPi'6 PmL'B D. 34 (2.r 1 R..mL18 tr2mI3 D.34 [ 3 r l IC"sl R6PS.1 0.36 [a.l RPt32 HPL32 0.39 [ 5, ] smeic EMe~dG 0.34 I 6 r laDT2 OU*E2 0.31 ( 7, l RS'L13A 9lPI.i3A 0.31 [ 8. L'M P1klA C'Y?EA 0.41 (9k] RPS15 R:'51.5 0.39 [7-d#l RF?i82 RPL?Y RPIaP2 0.32 [11r] CSQA. CSPA 0.39 E.12,1 3: DAesE x~xssl 0.32 [13,; Smtsa sm"A 0.3L
(14,1 YnMPD1i.2 ilP1182 3MPtltY2 0.39 (1S{ ] RP814 . RPfi19 0.47 NUP88 Ei0mB8 O.Sb (I.7,7 AT.'P.5G hTTSP 0.3.3 (L84PCY3pZ 1'LBF2 0.32 E L4 r Eb1F593 Tu193r:r93 0.=0 ;20,1 BSII79274 13Sk17927-0 0.32 t2f,] PRIrIf FR2ML 0.3 [22f] PrmS PI DI;5 0.33 [23f] aT.A1L ug4.LZ 4. 37 124,1 83g3A S3'33 0.d2 25r] ATIC ATSC 0.31 126,] E1PT.13 R-IM13 0.36 (27,] CIAPZHI C~SW1 0.34 j28r] M 1'BG = 0433 (29s) RPS2 11H82 RPS2' 0.32 30r1 PCC6 ECCB 0.36 [310] 3 t3?!~f RBkS 0.33 [32,] sRrr2 smm e.34 [ 38, } lli.'I.po it?I.Pfl 0.35 134r] 8H'RPal B!4&BAL 88[tl'.hl. 0.35 [30,} 8R'D2lTr2 STn1T+ Q.j2 [36rj SPS9 ttp99 0.36 [37,j &7032 6[tB2 0.33 [38r3 GLTSC82 GIt'FSCR2 0.37 139,j ccu1SL*1 CtlmafxPf 0.3 [4.0, E 1utP62 MR8542 0.33 (41,] t'w20059 91õ720659 0.34 (47,3 l9J12270 9'L,712270 0.3 TnbZe 16. 51~p,ain bSonwaxkars Liat 2006 aU6S00 Liet_Pria.a Ltst Prafcrorl Corsolatican [ I i} MSl7 ~ySLI 0.3 [20] ggNl P~771 0.45 [3r7 NK1 A~l 0.33 [ 1. ] ~TR2 AtiTR2 0.31 [S,E McL1 is= 0.31 (6,1 ,Tlx EfPX 0.32 [ 7r 1 R&PIO Ft3CB3B 0.34 (B~~ Gla82 6LPB2 0.32 [9:( 81'AS! ZPA61 0.31 t 10r 1 PCiwl PGAYfl 0.42 [ L 1 rI CKA7'4 CF31F4 0.31 [L2,] DOS'PL pWP; 0.4 [L3,E =9 DiK149 0.4 i 1 S. t 3-AU1'8A-l ii-ALB"-l 0.37 (15r ) LGALS1 2.CzPS:E-1 0.38 116,1 CS37A CSDA CSDA 0.3 [17,1 74RR181 AK[t.fs1 0.32 [ 18 F E 3'FITlf2 28TZT52 3F2T242 0. 36 C19.E xTOAg xTGAS 0.0 (20.1 vtN VIM 0.39 [21,1 UiPYSL3 L~pYsL3 0 _44[
t22,1 Jt3p1B JUtaO 0.32 [23r) x=3 IT=3 0.38 [29,1 tiijSeZA ?dFRBIA 0.32 [25,] A7+MFll a,Pml 0.37 [3G, l. 81iL3 "I,1 0.31 [+7.7r] Ll~STG~ 327SIG1 0.a74 [2'9,] Tu'f?I 3'Y3S81 0.48 [29,] G;CA.1 G.TA1 0.54 [30,] PSx92 eoma 0_34 [31.,] P$Gi i &Gl 0..46 13ir ] L'Y'IT E'~Y'1 0.15 133, 1 W3P434M-4 R3F22434.7354 0.31 [3tr ] QP'i41' OPTif 0.11 [35r ] lL6p'xsP1 tfSPaEP1 0.57 [36,) MVP MtvP 0.34 [37.1 t/ASP VA6P 0.31 L 3 8 r]ARL7 eRL.7 O. 39 C39,r] WW3' NNDIT NEIHIT 0.34 [440] THPI TAl"1 0.3 (41,1 CDL3#tl G=A1 QQL1A3 0.33 [da,l B&Sgl BjAS*'1 0_35 [43,) PLOD2 gLpsy? 0.37 (44,) ATY3 ATF9 0.42 [43..1 P~iLm2-AJ,AP2 VALM2-,RF1kP3 0.33 [46a) ZLO ILB 0.38 [47a] 11I48L"P A2ikEP 0.35 C46=1 L+YXL2 3,t-= 0.32 [49r j '1+3T"BI al'WF1 9 .31 [$04-1 xir44 Ip.kR 0.a1 [51.1 Do= DG[sA 0.32 [52,j STC2 e7c2= 0.31 [53+j sEC61G BLC634 0.41 [54,1 RP'IL3 NPIL3 r,ffiIL3 0.47 [55,r ] RGS3 YtG63 0.37 [56,1 If14d mx6 0.34 [57,1 'P'28 P2R 0.34 t5e=] TPMZ TFM2 0.3s {59r] $rsM89 PStlE+3 8&M89 0.34 T60rI LOX zax 0.37 (61t) STC2 S'80i 0.35 [620 CSPO2 CSYR2 CSm 0.3s 163.) BlG=4 PTGSK4 0.31 (64,1 ZL6 TL6 0.34 16501 SWO3 atiSq3 0.38 16,611 Pj:;]LD PLi4u PZF1Lf 0.35 [67,1 WlqT5A WMTgpk 0 . "
[68,j BwTF 9DllE 0_34 TNFetsF33 ~37~FiSP l~i "Pitu2'lA 0.46 (70f] fySi61C P2tIC 0.34 171,1 DICPZP564fi0922 OFCP'Lp5641C0H22 0.34 [72.] ri'OT1 E7AT1 0.39 [73.) P2RF R=P 0.39 [7'4+] HtA'E lELle-8 0.36 [75ry COL6AT 4QT,6A2 CoZ6A.3 ~.32 (76. j tCGC4083 45C4003 4,3.2 [77. a -TIQEASPI.OB THFR6F14B 0.34 17901 PL14GL1 PLAtaI.1 0.31 [79,1 PMh2 PHAA2 0_38 [80r] Tk'PI TFPI 0.3$
(B1t] LAT LAT 0.46 (82,1 Ozm GLLKB 0.51 [83,) CYR6f CYR61 0.37 (84,1 Pf,ES9R #Y.AUR. PLAUii 0.35 (SS,j P6c[41 F9C373 ffSQ7x 0.32 t85,) 9RP70 ER270 0.32 [E7..1 APIQ -lF?{t 0.3 [88, ) U8C u8C 0.37 t$9,j PGl'Itl. PGFR1 0.33 t90,) 13Zc 83C 0.33 191,1 Hax EAX 0.35 [92,j CoI,4A2 COL4A2 CG2e4A2 9.32 t93,1 t:0F,6A2 40L6A1 0.32 [94,1 IHTTit3 IPI7f'M3 0. 3 195,1 2Sr1P18 W)H 0.34 ( 9'6M446603 PT,346603 0.37 [ 47 ~ ) FAAPTLI.IQ RA3+TI.xW 0.34 [ee. a ~s s~ne ~u.ai [99~.I ft% PTS, 0.3 1100,] icttAafi874 RSA}iOSi7 0.31 [ 3Ql ,] k22E 2~T18 trtTt3t 0.31 [102+] CDOTiC CE7GFlY 11,51 [ f n 3'] Dcx= caOCnc2 4.38 [itl+k,] TR.IlK22 xB2ld22 [1050] SZ9k Bisi 0.37 [ 10s. 1 8CATI . 9CA01 0.42 (167,1 pli1"E FRP I 0.34 1108,) nsatl DbHl 0.34 [109rI biTllC MTT7C 0.3 ExSD,I W1pDAaA TQdS8l0 0.42 t2110=1 M31 RA831 0.45 1112'j "10350 PL.S~0~5~ V=rd [I13,.] a1os12d c14rf2a 0,34 [111r] HN8 NlSE.7 0.46 [ I LS,. ] 's}E7122 Tet82827 0.3 111611 7CP8i TIsAl t1. 37 [117,] Cfl~SA2 cOLS}]Z fi,31 t YY3, ] EtsK~ sI,X3 U. 38 [f19,.] C'YY,iI CST.v 0,4 (12011 AuAMT81 nannam 1 0.31 (E21A 'IRFECa2 22W 0.4E
1122,1 RC'1D tsCM ACTa 0.33 Talxie 1?. 1Mex.W.-c," tnethy7.,,glYwcax la~(a~pfclia+~7x~rnaar~l diA~Trocl~io~id LÃst *sQQB lEG6SIF0 I.ict Pri+pr LL,Gt Fx'~kexz P?Y~~'ilitiGA
~
ti,l -tZ~ ] SSREI S5FiP1 U.37' t~ e] H67 C 2i[FITC 0.35 14:rl c2sc CTsC 0.35 j 5,] AP LG2 141*1G2 0,33 16t) PSM82 F62m2 0.3 17rI Laa zb-B 0.38 [ 8, E kYEi82 Ct"p02 0.31 [ 4 e I 62RPSNit~ SEitlPINk1 0.34 [1Qr] EGS'CJtl e90CA.1 0.32 [33.Y Z882 X:;ES2 0.36 (120 KF.B KYB 2d.YH 0.33 (3.3.rl T'RIi#x PR=Ml 0.39 Ã14,1 s2i13'X H2AF?x 0.33 (is,] EMaa samai 0.35 [L~ r ] Hl~."5tC #5A4[39 (1133 [.17,.] TYC2 TK2 0.42 [1$.] FJE~SCl 4tHSCL 0,35 119,1 &TA'P[i1 bi"Si2 fl .33A
120,] LUM3 LteMFt3 0.31 j2l,rj Df+AGTi DPA6E1 0.42 122,j t7C[C3 'VC2S2 0.21 jZ30:] SERPINBF &ERFMl 0.31 124,] HDlGy 2iClNL 0.a5 j25a] 8RRT1L SaR111 0.33 {26r] 6(3S2 0982 0.43 [27,1 1t8C2 StAC2 0..35 [28,] L[OC21534 MOC21658 0,36 129,1 4"%-SLi GTRV1 0.35 [3U0Z T.SCC3 TACC3 0.31 [3I~j ~2 PLEK2 0.32 [3Z+1 pIJW8 PLrACS 0.31 [33, l @TiItPD }IN&PD 0.35 E34+] RtzAS-4 ~ Bgs.9-4 0..3 Tab1e 18. CarEmp=1=atiR biomarkers Y.,i:st 2066 13]r6800 I.3.at Fr3cr LS.st Prafw.rr Cvrxtilstarut ( ir 3 usa a0&'lq 4.33 12,j Y=}S ITca5 0.43 0+ lvxti VZtd 0.34 (4t) TUPAXTi!3 TaPAZP3 014 isO CS8G8 CSPG2 0.35 , 160 NUTSA ApT57l 0.34 I?il roxpz POX'c'T 0.36 {$,] LOc9d10S 1,Oc44105 0.32 {9r] EFI16 IF11b 0.3$
j 10, ] L+IiP.Zi3 LiRaZR3 0.33 [ 11 r] p4WA1 FK]P~fil 0.37 [12,) DoCnlo 13OCK10 0.4 113f1 LZM1 T.8M1 0.32 [14.) COL5A2 COLSA2 0.3 [ 15 ,l F1D.Pii4i81 71pAKTS L 0.34.
VaYaleo 39. 5-F[9 ;5-~lOxrzOVr~CL&~ lsiGmarYe~s I.ist 2006 ~6~00 ListPriar Liat Frele_r eorzaiaticn [1,] 12P7+i$ 8PL16 b.35 ['2r] F.PLf~A RPI.10l6 0.36 E3r1 R19g$L R&PB1 0.3 E4r ] AW~POS JIMApCB 0.3 ES.I 3sF1a2 ffi1SY'382 0.4 f 6. ]RPL13A PtP=F,19A 0.30 E7=l Rps1s PtQ''SIS 0.34 Eg.3 AX"i AKRPI 0.37 (9.1 rrcareAal 3iDUnn81 0.3 110,1 APRT A93LT 0.32 { 1I, ] LW583 ztEF593 0.37 [ L2, ] De6tpfi3 D7RF63 0.31 [L3,1 TL6it YL5$ 0.31 [ 14 e] IIiP7a'13 RFL13 0,37 [ L'" #] SaAT3 SA'&R3 0>.3S
[16r1 R' Sb P.F56 0.49 [lxrl U= OCRZ 0.3$
[lA"l RP1.3 Xt'PL3 0.32 [19fl 8PL27 i2?1r17 0.34 [20,) 7iPS2 RPs2 0 132 {'21, l Pt'es Pr-ICa 0.31 122,1 TOMEd2II = "lfh[20 0.39 {23, 3 SHkiTZ SffiST2 0.36 iZ4,1 RFLPO Aftp0 0.3 E25r1 GTF3~1 ClY3A = 0.5 [26,1 zzmqw STOML2 0.4 E37r] D33Sp96.13151 GF:1.'Ep564J157 0.36 E28 r ] MR?52 24RFR2 0.34 .129.1 AW5 ALG5 0.37 130t) CAIT;ML4 oat;tw4 0.3 'ltbla 20. Ritwcimats (@laatb.eCat) bi*ma5kera L.La r20D6 Y.isl~.Prlcrr List Fxsferr C0rra1ab3an t 1. E iY93 sTx 0.36 1201 1SIFC1 7.IFC1 0.36 1311 v3;= YD337r.R 0.39 [4.E RIMI RG&xi 0:32 (5, 1 PA~ItS1S3 PA81LH1B3 0.32 [60I Birx H1L7C 0.43 [?-1 MAtY14&4 RN~144 0.36 180 mu TltJM8 0.47 [9rj CIKY3 C8Y1 0.37 [l0i ~ MAZ 7tA8 0.33 ( t 1 r~ BSaA SLA 0.35 [12pj 6FC8 eaF 0.37 (13,1 LtNAG UEms 0.41 [14,1 CC3E Cg38 0_33 (3.5p) P3CRCo VRlCCQ 0.31 11611 NUM Q1YRP7l 0.45 f17.7 YlYY70 EIti+70 0.38 lISp) AAD1 AiyCYl 0.31 139F1 RFCS RPCS 0.35 Rzo,I TU4Sa2 rH4aF2 0.33 [Z1rj v'F92 mz 0,3 122.1 mill wqxx 0.31 [23lJ TOBGGP3 TUSGCP3 0.33 (26, ] J127151t1A2 ATPM 92 fl..d2 [29. ] RAL; ftAtY 0.31 [26,1 PSHOS PSHCS 0.36 [27,} CD11D CD1Q 0.32 [30,I PA" ADA 9.34 [29,} CD99 CD99 0.33 [3Qp } CdZ Cn2 0.43 [.31,1 CaB 0.49 [3ZrI E1ti} 0.47 [33. ) I6X7.{ PiYLS 0.41 [3#PE GR3Z CC38 0.36 135p] CD1A C2Y3.A 0.48 [36,3 CO1A CLfl$ 0_47 137,1 ST.HU1 $'Tlo31 0.32 [ 3$. ! PS.LiC:3 29t[G7 0_ 39 [39,] RPG41a A etY1 0.36 [40,1 Al:T1 AKTi 0.38 (41.3 '=1 s+-AL1 0.37 142.3 O1M1615 aNA15 0.37 (.43.3 4T=2A, t38G2A 4.35 (44,1 . TCF12 iCP12 0.35 [45.] i7EFS3S 09E7S 0.52 1446,1 et.'$03 CC61D3 Yt .3$
($7s I FF4R6 PA}C6 0.35 I 4'.9, ] KQK kTDR Q ..3 {~'9 e} CAPC CEAIIG 0.35 {$Q, ) APidB RTSG2 0.39 151,j AC:Tl43 at'TiTi 0.37 (52,} GS3't!z G32lt2 0.47 [53.7 SItT31 SATk1 0.36 (54,1 flA3P lTA.RI:T 0.3 Mr] 36FBP2 $%W2 0.46 [56õ] C062 Cp82 0.49 (57+ 1 CFMBPI CHASPI 0.36 [58, ) PHR#1 DH97]. 0.49 [59 r 1 CTMJ41 C'PalbtAi 0.53 L60,) 2ui81C1 aaAtic1 0.32 [6lr ) CACIm3 CACd1s3 0,37 (62, ) PARSLh ,FqRSLA 0135 (b3r) CABF2 CASP2 D.42 ['6dr) CASP2 dASP2 D.31 [85r) 82F4 8284 0.36 [66,) LCPZ LCY2 0.35 [67,) CFSSPB CASPfi 0.32 [6$r1 HI"B lSYB 0.3 [89, I spk86 SPit9t6 0.44 ( 70 r) t3Lti3 cC,7LB 0.34 (72* 1 HbM iZDM 0 _39 172r1 CRSP1 CP6Fl 0.33 ( 73, ) OiUA{} liinp D.46 (741) lQSC3 TF7SC3 0.41 [75zt 1 GNM] GHAQ 0.54 [76,1 JARiA2 a7caxn2 0.44 f77,1 4CRL QGRi+ 0.5 (70,1 rE.LX PHI,1 0.36 t7Brl =112 SZH2 0.4 t80r1 Sxox 5ltCX 0.35 183,j SLc6A- 9LC8e12 0_35 tB2r) UM1L rJP31LL 0_3 [b3,) 9EeM'1 SL"Yi41 0.31 194r) $YlY'32 SNP32 0.35 [BS,) gTAtaPi 82ATSF1 8.35 186,1 6ilG2 SAaI 0,43 (07.) PTO'71 MG3 6.4M
) 88 r ) .O:X!"1 t7XF1 4.46 (8B,? !'YB PYB 0.II7 [~Orl TR33c28 Ts;t129 0.30 (91,j 9C00=B967 HC008967 0.4 (92r} 'OM TR88 4.3 C93,) TFRC TFgC 0.31 (94r) pl?''0 87.s~0= D.36 (95,} Cn31) Co30 0.32 ;94,2 Cn3G CC3G D.4 197,] CsxPH CLwC1V9 0.36 Iqgr1 At= AL6N2 0.33 t99 .1 ANXA1 +AlOXAL 0.35 )100,) 62AEX 62hP7t 0.51 [101,) CDSE Cn2S 0.33 (102,) D085 peXS 0.39 E.103. ) lC3Ll JkALh 0.3 [ l0 4r jCCM ccna2 013 [145r] H002 LHo2 0.35 [146r] s2ii- 5HRP8 0.38 [ 10 7 r j GhTA3 CA3"A3 0.38 [108,1 RiiM2 14R?SZ 0 .4$
[.t09, ] GLl1], GL7JL 0.4 [LLO,,j 'CCP7 24CH"7 0.39 ( I I I s 1 po3'kI 'E'GE'Rl 0.33 (I12r) SQX4 90X4 0.3 t F 13. ) lt,A=ic lSFLL 0.3 (t1471 IMC94 RUCB2 0.38 (),).5rj SKd~# SMA'3 ' 043 [116r1 PhT EtAR* 0.57 [ 1'17 r 1 UNG "G 0 .31 (11~,] 1-RMGDZB AsHCbTH 0.36 (119,] RM121 Ru67c1 0.38 (1201) 1sE*BO9FE6 NV80S806 0.5 [1Z2,] RC2Nl OCTu1 0.34 [122,] S83GL3 8H3M3 0.3A
[ ].23, ] vlZf vIN 0,41 ( S.2 d, j IR,ElG8C1 JtL87CF7C1 D.3 (L23,,] Cn47 CD47 0132 (126,1 AO'La81' Aao[)t2P 0 .37 1127,1 RHOH AFitn 0.43 (].28a] AISCx ADDl 0.46 1139, 1 ATF2713 :7LTP2A3 _ D.39 Tab1e 21. Radiat,ian sensitivit,g biamarksre 14et-2005 80&800 I,iat_Priar Li.et 1>sefssr Co[lE'Ia#i4a4 [ 1 ,] T+&1 S7AI 0 . ] 6 E2,1 ACEL44 ,ACSDT+1 0,36 [3r] ~ WAR6 0.39 14,7 CAmi CALk1 0.32 [5,) C1363 CD63 Cn63 0.32 (6,1 CD81 CD&1 0.43 [ 7'] nCB1+l)L FlCetP1A 0.38 [ 8 r) C= C3tI,Si 4.47 { 9f} SQp,AP1 F{]GAka 1, 0.37 110,1 C?5B CTSB 0.33 (ll,f FfCeC@72l MOC872.1 0a35 ( l2, ] aF'TAt1 STAT1 0_ 3Y
(13,3 T+ACCl 7-qcci 0.41 [ lA .] 5l645F'8 re4slr6 0.33 615,1 CD59 CD59 0.31 E Lfl, ] CMAPA CKmPd CSBP+# 0.43 [17,1 Gt7SP1 otr3P2 DUSUl 0.38 [is,] BCH,1 RCq1 0131 [19,] MGC89Q2 1M7C8902 0.35 [2Q,] LGSLS't IGs3L62 LGAAL41 0.33 (31.] BHLEfi'02 B9S.U82 0.3 (22,, j ki93 L 8L18B3 0.31 423. ] 8y= PIClf2 0.33 (24.1 PRMk pAtrF 0.42 Ã 2 5 e] pBP:kC$ FFP2CB 0.31 [26,] Ctna'3 Csa3 0.36 [27,1 ANSA2 A2iY+12 A68k2 0.32 [28,] 2ER3 2Mt3 0.34 [2s, ] J,SKl T3iiRI 0_33 [~~,} NgRCKB MARCKS 0.43 C31, ] Z,vn LIXM 0.48 [32rj P'E5i1T.3 F$&TL3 0.47 E33,] SI.t20A1 sE.C30Al 0.41 E 3d. f j LIP84',3 E Ik'Q.G3 0.36 (35,] FiCXB HHSH 0.46 (S6.] ERT1 S=T1 0.47 937,1 T3LP L 1IV 1 ib. 32 [36,] CT87. CTSL GTSL 0.38 [39,] SL39Pi6 SLC39}Y6 0.36 [ab,] R103;3 kSCtKj 0.38 [ a 1, j CRPC CRBC 4. S7 j42, 1 AN347' lfp1MT 0.37 E43,1 CDI,lA1 ROLlAk 0.35 E 4 4 o]'SStA.'k2 S1tAD52 TRAtai 0.35 [ 4,5 , ] Ap,1,.w9 2snA[i9 0.52 E46,1 02iAJC7 V?SA;7C.7 003$

[87r] PI,6CR1 l~i 0.35 188,1 PRBS33 PAG8823 D.3 [49rL pL06Z RLDD2 0.36 L50+] WK1 NPC3 0.34 L51rl TOill S"Ml 0.37 L52fi GFPTI GPFTY 0.37 LSS,] Iz+s as 0.36 [54,1 [tYRlC2 DY~iK2 0.3 LOSr7 FYGL TYG7, 0.46 L56r] LCAISL2 'Yr{t%LZ 0.49 (57r1 3~8A0355 yCS"0355 4.35 ("r] v-s94' vobB 0.49 159,1 IMSL3 4i13L3 9.53 [d0r 1 PO&a. 8t1SCA 4.32 161,1 OLZ2 V=Z 0.37 (62,1 CZN'FQ2 CSNT02 0.35 [63,1 NLLt2 NSD2 0142 LOr 1 Z'11F35D ClkP3SA 0.3.1 [65,I QCeLI exaLi 0.36 Lb6r ) a'L9d3a3 Bxta3a3 9.35 (47r ) ~*6 27.5 fl.32 I6Br 1 WMA ~7CSir 0_3 169 r I FQRE'2 Ff18F2 0.44 i7pr ] UYMO LFH92 D_34 [7+1a 1 OR912 G"Will. 0.133 [72r 1 P48A3 ETCHAl D..33 L 73 r) QL 58 GRFSB D..+Sb [ 7A r] A=1 AO'1'811 tl.CY9ff 0.41 ('7gr) CAM CAM 0.5+4 L76,j DSiPI DaIP! 0.44 [77,1 MAP2LC3B ?t#P3LC3& 0.3 [76>l 4ALS0 QALIC ~"a?SIG 0.36 (74f) ZGBT4 IGS7'4 0.4 [ B4 r j 2852 I7S2 D e 35 [ 5I r ) F.TP231,3 FiTP'2A2 0.35 [Bz,) OGT tycr 0.3 [ 63r ] TRP3tSF1Q 7'tErRB'!"10u 0.31 [54r1 xTA7iE#~i$ xSAA1126 at35 [ SSr ] TM&SFI Tt745F1 0.33 [$6a] ~Ets R9PMS 0.43 107,1 P.ZLSx2 IttLM 0.42 [$Sr] C=s C8LB 0.45 189:I 3CR3lt2 WRlD2 0.47 j90,1 0,'L293A2 &T~3AZ 0.38 (9Zr] S'LC7A13 SLC7A21 0t4 02r ] HPSLi !~+$Ei 0.3 193, 1 I17MP3 LGi'BF3 TG$p$3 4. 3L
144 r 1 &GA2 SW 0.36 f9501 Pn FN3 FNl D. 32 [96r; iaqoa n'ool 0.4 [97o) 3-SPH A9PH 0. 36 [95r1 AsAn1 ASA&1 0.33 [D9r) 41GDI, N1GTS, 0.35 [ld4 ] sE$PIHH6 = SERPI7R96, 0.61 (1Qfr~ i15fAS ElSPfiS 0.33 js02r7 SY"p36LI zrPg6r1 0135 q i43, 1C.t1L 4A2 cD,aA2 0.3 ( L04, ] ML4-41 Ct7L4n1 0,.3 [Mr ] PA44 C7144 4.3S
(fD6,] SLC39A34 SLC31M),4 0.38 (1D7r] HiPAZ $LPsA2 0.35 (109,] H8BP9 t"fiHP9 0.48 (199,7 1L65T ILbBT 0.4 (110r1 DIi"L856401022 06FZS+56442022 0.39 [111,} PPAP28 PPAL'2H 0.33 [ l I2 r} pG4?18 0AP12 0.3 [ 713, 7 KXPK1 Pl881CL 9.3 [ 11 ~ r] 1LZ018 PlzoLb 9.3$
[11Sr] CABT CASb CA'aT 0.31 [116,] 8R&32 Iti?J482 0.52 (117r] QPSi QICS 0,31 [11Sr ] LEML7 LLII"PI.2 0..36 11I2rI HEPT10 :IEPT2C 0.30 [120r) ABHP ARSE O.S
(121,1 912AA1070 8X&ui1fl78 0.34 E122,1 rTL FsL 0.38 1123:3 KSAA0877 a3A1i0877 0.41 (124r1 1'LCB1 FLCS1 0.3 [125, 7 lCTA716802 KS2;&.0802 0.32 [ 13fi. ) E1ro81 ItPNAl 0.37 E127,1 RA830AP kPd330" 0.43 [128r1 SE"IHB3 BSliF3MB1 0.40 (1291] '1kLdMI7A T3MM17A 6_3$
[130,] SoD1 S0 8 0.35 [ 13 x r 1 HLA-A i'13.A.-A 'BLA+A +6.32 [z32r 3 gpna2 l9QMCi2 9.43 [33dr ] 3'+ACSS831 iAitSS431 0.32 [ 134 r 1.FBApA1 S11L.D81 9.32 [335r ) sMX2 ?MEdf2 0.47 [136r] #lLpB 1SLPH 0..35 [137,1 rHqi04 Fm104 0.34 [ 130, ) I.I{itC5 F,RRCS 0.42 [139,1 RAB7L1 Rttia7L1 0.41 1140, ) Fwr35038 ET,73B0349 0.36 [141,1 DGClClfF DOG1S].0 0.41 [142,.) LRP1Z i.EtB12 0.36 [ 14:Br l T71NRc5 TXLiEtCS 0.4 [144,) CmC146 CpC14B 0.39 [145,) SR'1dTLL1 6iSM2'lt,l 0.38 [145r3 CCTBOIC COfi41c 0.38 [ ta7, ] DauS 7C1i7 OF13k5C10 0.31 [ 148, ] 2L1iiPO1 Tt3FOt1 0.33 [149*] LONP T.GiP ' 0.32 (150,] SNt602 Stgcu2 0.3$
[1g1; ] Dttl'LP1T6 DNAPTPG 0..31 [132, ) AplikTS1 AnaSkTS1 0.37 [153r ] c'CL$1 [154,) SChRE2 [ 155. j NA02318a [156,2 PTS
(157,J 'uaLL
t15e'7 CP1S2 (15 9 r ) Cst=82 7160,] U6cG
[161, l L1tS511 [i62r ] HlIS
[163,1 CB1iz1 [164,) QjESP3 (165,) E'Eff2 [165.) HiCe [1.67,) eTa1 [168r l R!!QC

1=6Er1 Mly128 [17pr] EGIt}'Z
( Y~ 1 r } C[TL=5lL2 i i72 r } CS9.'3 [273'} F-CM
=E7tr} = MKP2 jl75r] CTSD
(176,1 $L=DBS"
1177,1 CS&Pl 1178.1 SaonA4 1174ri Czrs.ni t I ao r x CTGF
[I&3,} CR,pG
[Y6Z; iA=p [iB3.j a3TL1 SGPR
~395r } BLYP'A
[iBBr} COPEH
[I57rI DIP7~
tx9Ar 1 s74ARtcn3 [ 13~ r 74~P~+
[190.} E~7.15 [ 191 r } S1df0A13 [asz.i ~

Table 22. Vincristine biomarkers.
Gene Correlation Probe Sequence [1,] SLC25A5 0.32 TCCTGTACTTGTCCTCAGCTTGGGC
[2,] RPL10 0.38 GCCCCACTGGACAACACTGATTCCT
[3,] RPL12 0.31 TGCCTGCTCCTGTACTTGTCCTCAG
[4,) RPS4X 0.39 AAATGTTTCCTTGTGCCTGCTCCTG
[5,) EIF5A 0.31 TCCTGTACTTGTCCTCAGCTTGGGC
[6,] BLMH 0.32 AAGCCTATACGTTTCTGTGGAGTAA
[7,] TBCA 0.3 ACTTGTCCTCAGCTTGGGCTTCTTC
[8,] MDH2 0.34 TCCTGTACTTGTCCTCAGCTTGGGC
[9,] S100A4 0.32 TGGACCCCACTGGCTGAGAATCTGG
[10,] C14orf139 0.3 TTGGACATCTCTAGTGTAGCTGCCA
Table 23. Cisplatin biomarkers.
Gene Correlation Probe Sequence [1,] C1QR1 0.3 CACCCAGCTGGTCCTGTGGATGGGA
[2,] SLA 0.37 TGCCTGCTCCTGTACTTGTCCTCAG
[3,] PTPN7 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC
[4,] ZNFNIAI 0.33 CACCCAGCTGGTCCTGTGGATGGGA
[5,] CENTBI 0.37 TTGGACATCTCTAGTGTAGCTGCCA
[6,] IFI16 0.31 TCCTCCATCACCTGAAACACTGGAC
[7,] ARHGEF6 0.35 TGCCTGCTCCTGTACTTGTCCTCAG
[8,] SEC31L2 0.32 AAGCCTATACGTTTCTGTGGAGTAA
[9,] CD3Z 0.32 TTGGACATCTCTAGTGTAGCTGCCA
[10,] GZMB 0.3 TCCTCCATCACCTGAAACACTGGAC
[11,] CD3D 0.34 TCCTCCATCACCTGAAACACTGGAC
[12,] MAP4K1 0.32 CACCCAGCTGGTCCTGTGGATGGGA
[13,] GPR65 0.39 CACCCAGCTGGTCCTGTGGATGGGA
[14,] PRFl 0.31 TCCTTGTGCCTGCTCCTGTACTTGT
[15,] ARHGAP15 0.35 CACCCAGCTGGTCCTGTGGATGGGA
[16,] TM6SF1 0.41 TGCCTGCTCCTGTACTTGTCCTCAG
[17,] TCF4 0.4 AAATGTTTCCTTGTGCCTGCTCCTG
Table 24. Etoposide biomarkers.
Gene Correlation Probe Sequence [1,] CD99 0.3 AAGCCTATACGTTTCTGTGGAGTAA
[2,] INSIG1 0.35 TCCTTGTGCCTGCTCCTGTACTTGT
[3,] PRG1 0.34 GCCCCACTGGACAACACTGATTCCT
[4,] MUF1 0.35 AAGCCTATACGTTTCTGTGGAGTAA
[5,] SLA 0.37 CACCCAGCTGGTCCTGTGGATGGGA
[6,] SSBP2 0.37 TGGACCCCACTGGCTGAGAATCTGG
[7,] GNB5 0.35 TCCTTGTGCCTGCTCCTGTACTTGT
[8,) MFNG 0.33 GCCCCACTGGACAACACTGATTCCT
[9,] PSMB9 0.31 -AAGCCTATACGTTTCTGTGGAGTAA
[10,] EVI2A 0.41 TCCTCCATCACCTGAAACACTGGAC
[11,] PTPN7 0.3 AAGCCTATACGTTTCTGTGGAGTAA
[12,] PTGER4 0.3 TGCCTGCTCCTGTACTTGTCCTCAG
[13,] CXorf9 0.3 GCCCCACTGGACAACACTGATTCCT
[14,] ZNFNlAl 0.35 ACTTGTCCTCAGCTTGGGCTTCTTC
[15,] CENTB1 0.3 TGGACCCCACTGGCTGAGAATCTGG
[16,] NAPILI 0.31 TCCTCCATCACCTGAAACACTGGAC
[17,] HLA-DRA 0.34 TGCCTGCTCCTGTACTTGTCCTCAG
[18,] IFI16 0.38 CACCCAGCTGGTCCTGTGGATGGGA
[19,] ARHGEF6 0.33 TGGACCCCACTGGCTGAGAATCTGG
[20,) PSCDBP 0.4 AAGCCTATACGTTTCTGTGGAGTAA
[21,) SELPLG 0.35 TTGGACATCTCTAGTGTAGCTGCCA
[22,) SEC31L2 0.42 AAATGTTTCCTTGTGCCTGCTCCTG

[23,] CD3Z - 0.36 TGCCTGCTCCTGTACTTGTCCTCAG
[24,] SH2D1A 0.33 CACCCAGCTGGTCCTGTGGATGGGA
[25,] GZMB 0.34 TGGACCCCACTGGCTGAGAATCTGG
(26,) SCN3A 0.3 GCCCCACTGGACAACACTGATTCCT
[27,] RAFTLIN 0.39 TCCTCCATCACCTGAAACACTGGAC
[28,] DOCK2 0.33 TGCCTGCTCCTGTACTTGTCCTCAG
[29,] CD3D 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC
[30,] ZAP70 0.35 TCCTCCATCACCTGAAACACTGGAC
[31,] GPR65 0.35 TGGACCCCACTGGCTGAGAATCTGG
[32,] PRF1 0.32 TGGACCCCACTGGCTGAGAATCTGG
[33,] ARHGAP15 0.32 ACTTGTCCTCAGCTTGGGCTTCTTC
[34,] NOTCHI 0.31 TGCCTGCTCCTGTACTTGTCCTCAG
[35,] UBASH3A 0.32 ACTTGTCCTCAGCTTGGGCTTCTTC
Table 25. Azaguanine biomarkers.
Gene Correlation Probe Sequence [i,] SRM 0.32 TGCCTGCTCCTGTACTTGTCCTCAG
[2,] SCARBI 0.4 TTGGACATCTCTAGTGTAGCTGCCA
[3,] SIAT1 0.31 AAATGTTTCCTTGTGCCTGCTCCTG
[4,] CUGBP2 0.37 TGGACCCCACTGGCTGAGAATCTGG
[5,] WASPIP 0.44 TCCTGTACTTGTCCTCAGCTTGGGC
[6,] ITM2A 0=.31 AAGCCTATACGTTTCTGTGGAGTAA
[7,] PALM2-AKAP2 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC
[8,] LNK 0.43 TTGGACATCTCTAGTGTAGCTGCCA
[9,] FCGR2A 0.3 TGCCTGCTCCTGTACTTGTCCTCAG
[10,] RUN?C3 0.43 TCCTGTACTTGTCCTCAGCTTGGGC
[11,] EVI2A 0.4 AAATGTTTCCTTGTGCCTGCTCCTG
[12,] BTN3A3 0.4 ACTTGTCCTCAGCTTGGGCTTCTTC
[13,] LCP2 0.34 TCCTTGTGCCTGCTCCTGTACTTGT
[14,] BCHE 0.35 TCCTCCATCACCTGAAACACTGGAC
[15,] LY96 0.47 TGCCTGCTCCTGTACTTGTCCTCAG
[16,] LCP1 0.42 ACTTGTCCTCAGCTTGGGCTTCTTC
[17,] IFI16 0.33 CACCCAGCTGGTCCTGTGGATGGGA
[18,] MCAM 0.37 TTGGACATCTCTAGTGTAGCTGCCA
[19,] MEF2C 0.41 CACCCAGCTGGTCCTGTGGATGGGA
[20,] FYN 0.31 TCCTGTACTTGTCCTCAGCTTGGGC
[21,] Clorf38 0.37 AAGCCTATACGTTTCTGTGGAGTAA
[22,] FCGR2C 0.34 TGCCTGCTCCTGTACTTGTCCTCAG
[23,] TNIK 0.35 AAGCCTATACGTTTCTGTGGAGTAA
[24,] AMPD2 0.3 TCCTGTACTTGTCCTCAGCTTGGGC
[25,] SEPT6 0.41 AAATGTTTCCTTGTGCCTGCTCCTG
[26,] RAFTLIN 0.39 TCCTTGTGCCTGCTCCTGTACTTGT
[27,] SLC43A3 0.52 CACCCAGCTGGTCCTGTGGATGGGA
[28,] LPXN 0.54 AAGCCTATACGTTTCTGTGGAGTAA
[29,] CKIP-1 0.33 TCCTGTACTTGTCCTCAGCTTGGGC
[30,] FLJ10539 0.33 TCCTTGTGCCTGCTCCTGTACTTGT
[31,] FLJ35036 0.36 AAGCCTATACGTTTCTGTGGAGTAA
[32,] DOCK10 0.3 GCCCCACTGGACAACACTGATTCCT
[33,] TRPV2 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC
[34,] IFRG28 0.3 TCCTTGTGCCTGCTCCTGTACTTGT
[35,] LEF1 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC
[36,] ADAMTS1 0.36 TGGACCCCACTGGCTGAG:9ATCTGG
Table 26. Carboplatin biomarkers.
Gene Correlation Probe Sequence [1,] ITGAS 0.43 AAATGTTTCCTTGTGCCTGCTCCTG
[2,] TNFAIP3 0.4 TGCCTGCTCCTGTACTTGTCCTCAG

[3,1 WNT5A 0.34 TCCTCCATCACCTGAAACACTGGAC
[4,] FOXF2 0.36 TGCCTGCTCCTGTACTTGTCCTCAG
[5,] LOC94105 0.32 AAATGTTTCCTTGTGCCTGCTCCTG
[6,] IFI16 0.38 TCCTCCATCACCTGAAACACTGGAC
[7,] LRRN3 0.33 TTGGACATCTCTAGTGTAGCTGCCA
[8,] DOCK10 0.4 TCCTGTACTTGTCCTCAGCTTGGGC
[9,] LEPREI 0.32 GCCCCACTGGACAACACTGATTCCT
[10,] ADAMTS1 0.34 TGGACCCCACTGGCTGAGAATCTGG
Table 27. Adriamycin biomarkers.
Gene Correlation Probe Sequence [1,] CD99 0.41 AAGCCTATACGTTTCTGTGGAGTAA
[2,] ALDOC 0.31 TCCTTGTGCCTGCTCCTGTACTTGT
[3,] SLA 0.35 TGCCTGCTCCTGTACTTGTCCTCAG
[4,] SSBP2 0.34 TCCTCCATCACCTGAAACACTGGAC
[5,] IL2RG 0.38 TCCTTGTGCCTGCTCCTGTACTTGT
[6,] CXorf9 0.32 TGGACCCCACTGGCTGAGAATCTGG
[7,] RHOH 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC
[8,] ZNFNlAI 0.43 TTGGACATCTCTAGTGTAGCTGCCA
[9,] CENTBI 0.36 AAGCCTATACGTTTCTGTGGAGTAA
[10,] MAP4K1 0.35 TCCTCCATCACCTGAAACACTGGAC
[11,] CD3G 0.31 AAATGTTTCCTTGTGCCTGCTCCTG
[12,] CCR9 0.34 CACCCAGCTGGTCCTGTGGATGGGA
[13,] CXCR4 0.3 TCCTTGTGCCTGCTCCTGTACTTGT
[14,] ARHGEF6 0.31 TCCTCCATCACCTGAAACACTGGAC
[15,1 SELPLG 0.31 TGGACCCCACTGGCTGAGAATCTGG
[16,] SEC31L2 0.33 TGCCTGCTCCTGTACTTGTCCTCAG
[a.7r1 CD3Z 0.37 ACTTGTCCTCAGCTTGGGCTTCTTC
[18,] SH2D1A 0.37 TTGGACATCTCTAGTGTAGCTGCCA
[19,] CD1A 0.4 AAGCCTATACGTTTCTGTGGAGTAA
[20,] LAIR1 0.39 AAGCCTATACGTTTCTGTGGAGTAA
[21,] TRB@ 0.34 TCCTCCATCACCTGAAACACTGGAC
[22,] CD3D 0.33 TCCTTGTGCCTGCTCCTGTACTTGT
[23,] WBSCR20C 0.34 ACTTGTCCTCAGCTTGGGCTTCTTC
[24,] ZAP70 0.33 TCCTGTACTTGTCCTCAGCTTGGGC
[25,] IFI44 0.32 TGCCTGCTCCTGTACTTGTCCTCAG
[26,] GPR65 0.31 AAGCCTATACGTTTCTGTGGAGTAA
[27,] AIF1 0.3 CACCCAGCTGGTCCTGTGGATGGGA
[28,] ARHGAP15 0.37 TCCTGTACTTGTCCTCAGCTTGGGC
[29,] NARF 0.3 TCCTCCATCACCTGAAACACTGGAC
[30,] PACAP 0.32 CACCCAGCTGGTCCTGTGGATGGGA
Table 28. Aclarubicin biomarkers.
Gene Correla.tion Probe Sequence [2s] RPL12 0.3 AAATGTTTCCTTGTGCCTGCTCCTG
[2,] RPLP2 0.37 TTGGACATCTCTAGTGTAGCTGCCA
[3,] MYB 0.31 TCCTTGTGCCTGCTCCTGTACTTGT
[4,] ZNFNIAI 0.34 AAATGTTTCCTTGTGCCTGCTCCTG
[5,] SCAPI 0.33 TGCCTGCTCCTGTACTTGTCCTCAG
[6,] STAT4 0.31 AAATGTTTCCTTGTGCCTGCTCCTG
[7,] SP140 0.4 AAGCCTATACGTTTCTGTGGAGTAA
[8,] AMPD3 0.3 _ TGCCTGCTCCTGTACTTGTCCTCAG
[9,] TNFAIP8 0.4 AAGCCTATACGTTTCTGTGGAGTAA
[10,].DDX18 0.31 TCCTTGTGCCTGCTCCTGTACTTGT
[11,] TAF5 0.3 TCCTTGTGCCTGCTCCTGTACTTGT
[12,] RPS2 0.34 CACCCAGCTGGTCCTGTGGATGGGA
[13,] DOCK2 0.32 AAGCCTATACGTTTCTGTGGAGTAA

[14,] GPR65 0.35 AAGCCTATACGTTTCTGTGGAGTAA
[15,] HOXA9 0.33 TCCTTGTGCCTGCTCCTGTACTTGT
[16,] FLJ12270 0.31 AAATGTTTCCTTGTGCCTGCTCCTG
[17,] HNRPD 0.4 ACTTGTCCTCAGCTTGGGCTTCTTC
Table 29. Mitoxantrone biomarkers.
Gene Correlation Probe Sequence [1,] PGAM1 0.32 TGCCTGCTCCTGTACTTGTCCTCAG
[2,] DPYSL3 0.36 AAATGTTTCCTTGTGCCTGCTCCTG
[3,] INSIGI 0.32 TCCTTGTGCCTGCTCCTGTACTTGT
[4,] GJA1 0.31 TTGGACATCTCTAGTGTAGCTGCCA
[5,] BNIP3 0.31 TTGGACATCTCTAGTGTAGCTGCCA
[6,] PRG1 0.39 GCCCCACTGGACAACACTGATTCCT
[7,] G6PD 0.34 TGCCTGCTCCTGTACTTGTCCTCAG
[8,] PLOD2 0.34 GCCCCACTGGACAACACTGATTCCT
[9,] LOXL2 0.31 TCCTTGTGCCTGCTCCTGTACTTGT
[10,] SSBP2 0.36 TCCTCCATCACCTGAAACACTGGAC
[11,] Clorf29 0.35 TCCTTGTGCCTGCTCCTGTACTTGT
[12,] TOX 0.35= TCCTTGTGCCTGCTCCTGTACTTGT
[13,] STC1 0.39 TCCTGTACTTGTCCTCAGCTTGGGC
[14,] TNFRSFIA 0.34 AAATGTTTCCTTGTGCCTGCTCCTG
[15,] NCOR2 0.3 TCCTCCATCACCTGAAACACTGGAC
[16,] NAP1L1 0.32 TCCTTGTGCCTGCTCCTGTACTTGT
[17,] LOC94105 0.34 AAGCCTATACGTTTCTGTGGAGTAA
[18,] ARHGEF6 0.34 TCCTCCATCACCTGAAACACTGGAC
[19,] GATA3 0.35 TCCTTGTGCCTGCTCCTGTACTTGT
[20,] TFPI 0.31 TCCTGTACTTGTCCTCAGCTTGGGC
[21,] CD3Z 0.37 AAGCCTATACGTTTCTGTGGAGTAA
[22,] AF1Q 0.33 GCCCCACTGGACAACACTGATTCCT
[23,] MAP1B 0.34 TGCCTGCTCCTGTACTTGTCCTCAG
[24,] CD3D 0.31 TCCTTGTGCCTGCTCCTGTACTTGT
[25,] BCAT1 0.32 TCCTGTACTTGTCCTCAGCTTGGGC
[26,] IFI44 0.33 TGGACCCCACTGGCTGAGAATCTGG
[27,] CUTC 0_33 AAATGTTTCCTTGTGCCTGCTCCTG
[28,] NAP1L2 0_33 AAGCCTATACGTTTCTGTGGAGTAA
[29,] NME7 0.35 AAATGTTTCCTTGTGCCTGCTCCTG
[30,] FLJ21159 0.33 TCCTGTACTTGTCCTCAGCTTGGGC
Table 30. Mitomycin biomarkers.
Gene Correlation Probe Sequence [1,] STC1 0.34 TGCCTGCTCCTGTACTTGTCCTCAG
[2,] GPR65 0.32 GCCCCACTGGACAACACTGATTCCT
[3,] DOCK10 0.35 ACTTGTCCTCAGCTTGGGCTTCTTC
[4,] FAM46A 0.36 TCCTTGTGCCTGCTCCTGTACTTGT
[5,] LOC54103 0.39 ACTTGTCCTCAGCTTGGGCTTCTTC
Table 31. Paclitaxel (Taxol) biomarkers.
Gene Correlation Probe Sequence [1,] RPL10 0.31 TCCTCCATCACCTGAAACACTGGAC
[2,] RPS4X 0.31 TCCTCCATCACCTGAAACACTGGAC
[3,] DKC1 0.3 TCCTTGTGCCTGCTCCTGTACTTGT
[4,] DKFZP564C186 0.32 ACTTGTCCTCAGCTTGGGCTTCTTC
[5,] PRP19 0.31 TGCCTGCTCCTGTACTTGTCCTCAG
[6,] RAB9P40 0.33 GCCCCACTGGACAACACTGATTCCT
[7,] HSA9761 0.37 AAATGTTTCCTTGTGCCTGCTCCTG
[8,] GMDS 0.3 AAATGTTTCCTTGTGCCTGCTCCTG

[9,] CEP1 0.3 AAATGTTTCCTTGTGCCTGCTCCTG
[10,] IL13RA2 0.34 AAATGTTTCCTTGTGCCTGCTCCTG
[11,] MAGEB2 0.41 ACTTGTCCTCAGCTTGGGCTTCTTC
[12,] HMGN2 0.35 CACCCAGCTGGTCCTGTGGATGGGA
[13,3 ALMS1 0.3 TCCTCCATCACCTGAAACACTGGAC
[14,] GPR65 0.31 TGCCTGCTCCTGTACTTGTCCTCAG
[15,] FLJ10774 0.31 TGGACCCCACTGGCTGAGAATCTGG
[16,] NOLB 0.31 TGCCTGCTCCTGTACTTGTCCTCAG
[17,] DAZAP1 0.32 TGCCTGCTCCTGTACTTGTCCTCAG
[18,] SLC25A15 0.31 TTGGACATCTCTAGTGTAGCTGCCA
[19,] PAF53 0.36 TCCTCCATCACCTGAAACACTGGAC
[20,] PITPNCI 0.33 TCCTCCATCACCTGAAACACTGGAC
[21,] SPANXC 0.3 TGGACCCCACTGGCTGAGAATCTGG
[22,] KIAA1393 0.33 CACCCAGCTGGTCCTGTGGATGGGA
Table 32. Gemcitabine (Gemzar) biomarkers.
Gene Correlation Probe Sequence [1,] UBE2L6 0.38 CACCCAGCTGGTCCTGTGGATGGGA
[2,] TAP1 0.33 CACCCAGCTGGTCCTGTGGATGGGA
[3,] F2R 0.3 TCCTGTACTTGTCCTCAGCTTGGGC
[4,] PSMB9 0.31 TGCCTGCTCCTGTACTTGTCCTCAG
[5,] IL7R 0.31 AAGCCTATACGTTTCTGTGGAGTAA
[6,] TNFAIPB 0.33 AAGCCTATACGTTTCTGTGGAGTAA
[7,] HLA-C 0.33 TGGACCCCACTGGCTGAGAATCTGG
[8,] IFI44 0.31 TGGACCCCACTGGCTGAGAATCTGG
Table 33. Taxotere (docetaxel) biomarkers.
Gene Correlation Probe Sequence [1,] ANP32B 0.45 GCCCCACTGGACAAGACTGATTCCT
[2,] GTF3A 0.31 TTGGACATCTCTAGTGTAGCTGCCA
[3,] TRIM14 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC
[4,] SKP2 0.33 GCCCCACTGGACAACACTGATTCCT
[5,] TRIP13 0.36 TCCTGTACTTGTCCTCAGCTTGGGC
[6,] RFC3 0.45 GCCCCACTGGACAACACTGATTCCT
[7,] CASP7 0.32 TGCCTGCTCCTGTACTTGTCCTCAG
[8,] TXN 0.36 AAGCCTATACGTTTCTGTGGAGTAA
[9,] MCM5 0.34 AAATGTTTCCTTGTGCCTGCTCCTG
[10,] PTGES2 0.39 AAATGTTTCCTTGTGCCTGCTCCTG
[11,] OBFC1 0.37 TGGACCCCACTGGCTGAGAATCTGG
[12,] EPB41L4B 0.32 GCCCCACTGGACAACACTGATTCCT
[13,] CALML4 0.31 TCCTCCATCACCTGAAACACTGGAC
Table 34. Dexamethasone biomarkers.
Gene Correlation Probe Sequence [1,] IFITM2 0.38 ATATATGGACCTAGCTTGAGGCAAT
[2,] UBE2LG 0.32 AAGCCTATACGTTTCTGTGGAGTAA
[3,] ITM2A 0.38 CACCCAGCTGGTCCTGTGGATGGGA
[4,] IL2RG 0.36 TCCTCCATCACCTGAAACACTGGAC
[5,] GPRASPI 0.36 TCCTGTACTTGTCCTCAGCTTGGGC
[6,1 PTPN7 0.31 TCCTTGTGCCTGCTCCTGTACTTGT
[7,] CXorf9 0.36 GCCCCACTGGACAACACTGATTCCT
[8,] RHOH 0.33 TGCCTGCTCCTGTACTTGTCCTCAG
[9,] GIT2 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC
[10,] ZNFNIAI 0.35 TCCTTGTGCCTGCTCCTGTACTTGT
[11,] CEP1 0.31 CACCCAGCTGGTCCTGTGGATGGGA
[12,] MAP4K1 0.3 AAGCCTATACGTTTCTGTGGAGTAA
[13,] CCR7 0.33 AAATGTTTCCTTGTGCCTGCTCCTG

[14,] CD3G 0.35 CACCCAGCTGGTCCTGTGGATGGGA
[15,] UCP2 0.3 AAGCCTATACGTTTCTGTGGAGTAA
[16,] GATA3 0.37 TGGACCCCACTGGCTGAGAATCTGG
[17,] CDKN2A 0.32 TCCTGTACTTGTCCTCAGCTTGGGC
[18,] TARP 0.3 GCCCCACTGGACAACACTGATTCCT
[19,] LAIR1 0.34 TTGGACATCTCTAGTGTAGCTGCCA
[20,] SH2D}.A 0.34 TCCTTGTGCCTGCTCCTGTACTTGT
[21,] SEPT6 0.34 TGCCTGCTCCTGTACTTGTCCTCAG
[22,] HA-1 0.34 TCCTTGTGCCTGCTCCTGTACTTGT
[23,] CD3D 0.32 TCCTCCATCACCTGAAACACTGGAC
[24,] LST1 0.39 CACCCAGCTGGTCCTGTGGATGGGA
[25,] AIF1 0.35 AAGCCTATACGTTTCTGTGGAGTAA
[26,] ADA 0.33 TGCCTGCTCCTGTACTTGTCCTCAG
[27,] DATF1 0.41 CACCCAGCTGGTCCTGTGGATGGGA
[28,] ARHGAP15 0.3 TCCTGTACTTGTCCTCAGCTTGGGC
[29,] PLACB 0.31 CACCCAGCTGGTCCTGTGGATGGGA
[30,] CECR1 0.31 GCCCCACTGGACAACACTGATTCCT
[31,] LOC81558 0.33 TGGACCCCACTGGCTGAGAATCTGG
[32,] EHD2 0.37 ACTTGTCCTCAGCTTGGGCTTCTTC
Table 35. Ara-C (Cytarabine hydrochloride) biomarkers.
Gene Correlation Probe Sequence [1,] ITM2A 0.32 TGGACCCCACTGGCTGAGAATCTGG
[2,] RHOH 0.31 AAATGTTTCCTTGTGCCTGCTCCTG
[3,] PRIM1 0.3 TCCTCCATCACCTGAAACACTGGAC
[4,] CENTBI 0.31 TCCTTGTGCCTGCTCCTGTACTTGT
[5,] NAP1L1 0.31 GCCCCACTGGACAACACTGATTCCT
[6,] ATP5G2 0.31 TCCTCCATCACCTGAAACACTGGAC
[7,] GATA3 0.33 AAATGTTTCCTTGTGCCTGCTCCTG
[8,] PRKCQ 0.32 AAGCCTATACGTTTCTGTGGAGTAA
[9,] SH2D1A 0.3 GCCCCACTGGACAACACTGATTCCT
[10,] SEPT6 0.42 ACTTGTCCTCAGCTTGGGCTTCTTC
[11,] NME4 0.33 ACTTGTCCTCAGCTTGGGCTTCTTC
[12,] CD3D 0.31 AAGCCTATACGTTTCTGTGGAGTAA
[13,] CD1E 0.32 TGGACCCCACTGGCTGAGAATCTGG
[14,] ADA 0.34 GCCCCACTGGACAACACTGATTCCT
[15,] FHOD1 0.31 CACCCAGCTGGTCCTGTGGATGGGA
Table 36. Methylprednisolone biomarkers.
Gene Correlation Probe Sequence [1,] CD99 0.31 GCCCCACTGGACAACACTGATTCCT
[2,] ARHGDIB 0.31 TGCCTGCTCCTGTACTTGTCCTCAG
[3,] ITM2A 0.35 GCCCCACTGGACAACACTGATTCCT
[4,] LGALS9 0.43 TCCTCCATCACCTGAAACACTGGAC
[5,] INPPSD 0.34 TGGACCCCACTGGCTGAGAATCTGG
[6,] SATBl 0.32 TCCTTGTGCCTGCTCCTGTACTTGT
[7,] TFDP2 0.4 AAATGTTTCCTTGTGCCTGCTCCTG
[8,] SLA 0.31 TGGACCCCACTGGCTGAGAATCTGG
[9,] IL2RG 0.3 TGCCTGCTCCTGTACTTGTCCTCAG
[10,] MFNG 0.3 TGCCTGCTCCTGTACTTGTCCTCAG
[11,] SELL 0.33 AAATGTTTCCTTGTGCCTGCTCCTG
[12,] CDW52 0.33 TCCTCCATCACCTGAAACACTGGAC
[13,] LRMP 0.32 TCCTGTACTTGTCCTCAGCTTGGGC
[14,] ICAM2 0.38 CACCCAGCTGGTCCTGTGGATGGGA
[15,] RIMS3 0.36 TGCCTGCTCCTGTACTTGTCCTCAG
[16,] PTPN7 0.39 TGGACCCCACTGGCTGAGAATCTGG
[17,] ARHGAP25 0.37 TCCTGTACTTGTCCTCAGCTTGGGC

[18,] LCK 0.3 TCCTCCATCACCTGAAACACTGGAC
[19,] CXorf9 0.3 TTGGACATCTCTAGTGTAGCTGCCA
[20,] RHOH 0.51 AAGCCTATACGTTTCTGTGGAGTAA
[21,] GIT2 0.33 ACTTGTCCTCAGCTTGGGCTTCTTC
[22,] ZNFNIAI 0.53 TCCTTGTGCCTGCTCCTGTACTTGT
[23,] CENTBI 0.36 TCCTCCATCACCTGAAACACTGGAC
[24,] LCP2 0.34 TCCTGTACTTGTCCTCAGCTTGGGC
[25,] S2I1 0.3 TCCTGTACTTGTCCTCAGCTTGGGC
[26,] GZMA 0.31 AAGCCTATACGTTTCTGTGGAGTAA
[27,] CEP1 0.37 AAGCCTATACGTTTCTGTGGAGTAA
[28,] CD8A 0.38 TGGACCCCACTGGCTGAGAATCTGG
[29,] SCAP1 0.32 TCCTCCATCACCTGAAACACTGGAC
[30,1 CD2 0.48 GCCCCACTGGACAACACTGATTCCT
[31,] VAV1 0.41 ACTTGTCCTCAGCTTGGGCTTCTTC
[32,] MAP4K1 0.36 TCCTGTACTTGTCCTCAGCTTGGGC
[33,] CCR7 0.37 ACTTGTCCTCAGCTTGGGCTTCTTC
[34,] C6orf32 0.38 TCCTTGTGCCTGCTCCTGTACTTGT
[35,] ALOX15B 0.43 TGCCTGCTCCTGTACTTGTCCTCAG
[36,] BRDT 0.33 AAGCCTATACGTTTCTGTGGAGTAA
[37,] CD3G 0.51 AAGCCTATACGTTTCTGTGGAGTAA
[38,] LTB 0.32 ACTTGTCCTCAGCTTGGGCTTCTTC
[39,] NVL 0.31 TTGGACATCTCTAGTGTAGCTGCCA
[40,].RASGRP2 0.35 TGCCTGCTCCTGTACTTGTCCTCAG
[41,] LCP1 0.34 AAATGTTTCCTTGTGCCTGCTCCTG
[42,] CXCR4 0.3 AAGCCTATACGTTTCTGTGGAGTAA
[43,] PRKD2 0.33 CACCCAGCTGGTCCTGTGGATGGGA
[44,] GATA3 0.39 TCCTGTACTTGTCCTCAGCTTGGGC
[45,] KIAA0922 0.36 GCCCCACTGGACAACACTGATTCCT
[46,] TARP 0.49 TCCTCCATCACCTGAAACACTGGAC
[47,] SEC31L2 0.32 ACTTGTCCTCAGCTTGGGCTTCTTC
[48,] PRKCQ 0.37 TTGGACATCTCTAGTGTAGCTGCCA
[49,] SH2D1A 0.33 AAGCCTATACGTTTCTGTGGAGTAA
[50,] CHRNA3 0.5 AAGCCTATACGTTTCTGTGGAGTAA
[51,] CD1A 0.44 AAGCCTATACGTTTCTGTGGAGTAA
[52,] LST1 0.36 CACCCAGCTGGTCCTGTGGATGGGA
[53,] LAIR1 0.47 CACCCAGCTGGTCCTGTGGATGGGA
[54,] CACNAIG 0.33 GCCCCACTGGACAACACTGATTCCT
[55,] TRB@ 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC
[56,] SEPT6 0.33 TCCTTGTGCCTGCTCCTGTACTTGT
[57,] HA-1 0.42 CACCCAGCTGGTCCTGTGGATGGGA
[58,] DOCK2 0.32 TCCTGTACTTGTCCTCAGCTTGGGC
[59,) CD3D 0.41 TCCTGTACTTGTCCTCAGCTTGGGC
[60,] TRD@ 0.38 TGCCTGCTCCTGTACTTGTCCTCAG
(61,] T3JAM 0.37 TGCCTGCTCCTGTACTTGTCCTCAG
[62,] FNBP1 0.37 TCCTGTACTTGTCCTCAGCTTGGGC
[63,] CD6 0.4 CACCCAGCTGGTCCTGTGGATGGGA
[64,] AIF1 0.31 TGCCTGCTCCTGTACTTGTCCTCAG
[65,] FOLH1 0.45 TCCTGTACTTGTCCTCAGCTTGGGC
[66,] CD1E 0.58 CACCCAGCTGGTCCTGTGGATGGGA
[67,] LY9 0.39 TCCTTGTGCCTGCTCCTGTACTTGT
[68,] ADA 0.39 AAATGTTTCCTTGTGCCTGCTCCTG
[69,] CDKL5 0.44 GCCCCACTGGACAACACTGATTCCT
[70,] TRIM 0.38 AAGCCTATACGTTTCTGTGGAGTAA
[71,] DATF1 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC
[72,] RGC32 0.51 TCCTTGTGCCTGCTCCTGTACTTGT
[73,] ARHGAP15 0.34 CACCCAGCTGGTCCTGTGGATGGGA
[74,] NOTCHI 0.36 TCCTTGTGCCTGCTCCTGTACTTGT

[75,] BIN2 0.31 AAATGTTTCCTTGTGCCTGCTCCTG
[76,] SEMA4G 0.35 AAGCCTATACGTTTCTGTGGAGTAA
[77,] DPEP2 0.33 CACCCAGCTGGTCCTGTGGATGGGA
[78,] CECR1 0.36 TCCTGTACTTGTCCTCAGCTTGGGC
[79,] BCL11B 0.33 TGCCTGCTCCTGTACTTGTCCTCAG
[80,] STAG3 0.41 TTGGACATCTCTAGTGTAGCTGCCA
[81,] GALNTG 0.32 TGCCTGCTCCTGTACTTGTCCTCAG
[82,] UBASH3A 0.3 AAATGTTTCCTTGTGCCTGCTCCTG
[83,] PHEMX 0.38 TCCTCCATCACCTGAAACACTGGAC
[84,] FLJ13373 0.34 TCCTTGTGCCTGCTCCTGTACTTGT
[85,] LEF1 0.49 TCCTCCATCACCTGAAACACTGGAC
[86,] IL21R 0.42 TTGGACATCTCTAGTGTAGCTGCCA
[87,] MGC17330 0.33 TCCTTGTGCCTGCTCCTGTACTTGT
[88,] AKAP13 0.53 TCCTTGTGCCTGCTCCTGTACTTGT
[89,] GIMAP5 0.34 AAATGTTTCCTTGTGCCTGCTCCTG
Table 37. Methotrexate biomarkers.
Gene Correlation Probe Sequence [1,] PRPF8 0.34 TCCTCCATCACCTGAAACACTGGAC
[2,] RPL18= 0.34 AAGCCTATACGTTTCTGTGGAGTAA
[3,] GOT2 0.31 CACCCAGCTGGTCCTGTGGATGGGA
[4,] RPL13A 0.31 TCCTGTACTTGTCCTCAGCTTGGGC
[5,] RPS15 0.39 CACCCAGCTGGTCCTGTGGATGGGA
[6,] RPLP2 0.32' GCCCCACTGGACAACACTGATTCCT
[7,] CSDA 0.39 GCCCCACTGGACAACACTGATTCCT
[8,] KHDRBS1 0.32 TCCTCCATCACCTGAAACACTGGAC
[9,] SNRPA 0.31 TCCTGTACTTGTCCTCAGCTTGGGC
[10,] IMPDH2 0.39 AAATGTTTCCTTGTGCCTGCTCCTG
[11,] RPS19 0.47 AAATGTTTCCTTGTGCCTGCTCCTG
[12,] NUP88 0.36 CACCCAGCTGGTCCTGTGGATGGGA
j13,] ATP5D 0.33 TGCCTGCTCCTGTACTTGTCCTCAG
[14,] PCBP2 0.32 AAATGTTTCCTTGTGCCTGCTCCTG
[15,] 2NF593 0.4 AAATGTTTCCTTGTGCCTGCTCCTG
[16,] HSU79274 0.32 TGGACCCCACTGGCTGAGAATCTGG
[17,] PRIM1 0.3 CACCCAGCTGGTCCTGTGGATGGGA
[18,] PFDNS 0.33 TCCTCCATCACCTGAAACACTGGAC
[19,] OXA.1L 0.37 CACCCAGCTGGTCCTGTGGATGGGA
[20,] ATIC 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC
[21,] CIAPIN1 0.34 ACTTGTCCTCAGCTTGGGCTTCTTC
[22,] RPS2 0.32 CACCCAGCTGGTCCTGTGGATGGGA
[23,] PCCB 0.36 GCCCCACTGGACAACACTGATTCCT
[24,] SHMT2 0.34 ACTTGTCCTCAGCTTGGGCTTCTTC
[25,] RPLPO 0.35 AAGCCTATACGTTTCTGTGGAGTAA
[26,] HNRPAI 0.35 TGGACCCCACTGGCTGAGAATCTGG
[27,] STOML2 0.32 TGCCTGCTCCTGTACTTGTCCTCAG
[28,] SKB1 0.33 ACTTGTCCTCAGCTTGGGCTTCTTC
[29,] GLTSCR2 0.37 AAGCCTATACGTTTCTGTGGAGTAA
[30,] CCNBIIP1 0.3 TCCTTGTGCCTGCTCCTGTACTTGT
[31,] MRPS2 0.33 TTGGACATCTCTAGTGTAGCTGCCA
[32,] FLJ20859 0.34 TGCCTGCTCCTGTACTTGTCCTCAG
[33,] FLJ12270 0.3 ACTTGTCCTCAGCTTGGGCTTCTTC
Table 38. Bleomycin biomarkers.
Gene Correlation Probe Sequence [1,] PFN1 0.45 GCCCCACTGGACAACACTGATTCCT
[2,] HK1 0.33 TTGGACATCTCTAGTGTAGCTGCCA
[3,] MCL1 0.31 TGGACCCCACTGGCTGAGAATCTGG

[4,] ZYX 0.32 TGGACCCCACTGGCTGAGAATCTGG
[5,] RAPlB 0.34 ACTTGTCCTCAGCTTGGGCTTCTTC
[6,] GNB2 0.32 CACCCAGCTGGTCCTGTGGATGGGA
[7,] EPAS1 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC
[8,] PGAM1 0.42 TGCCTGCTCCTGTACTTGTCCTCAG
[9,] CKAP4 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC
[10,] DUSP1 0.4 AAATGTTTCCTTGTGCCTGCTCCTG
[11,] MYL9 0.4 TTGGACATCTCTAGTGTAGCTGCCA
[12,] K-ALPHA-1 0.37 TTGGACATCTCTAGTGTAGCTGCCA
[13,] CSDA 0.3 TCCTTGTGCCTGCTCCTGTACTTGT
[14,] IFITM2 0.36 TTGGACATCTCTAGTGTAGCTGCCA
[15,] ITGA5 0.43 GCCCCACTGGACAACACTGATTCCT
[16,] DPYSL3 0.44 TGGACCCCACTGGCTGAGAATCTGG
[17,] JUNB 0.32 TCCTGTACTTGTCCTCAGCTTGGGC
[18,] NFKBIA 0.32 TCCTCCATCACCTGAAACACTGGAC
[19,] LAMB1 0.37 AAATGTTTCCTTGTGCCTGCTCCTG
[20,] FHL1 0.31 TGGACCCCACTGGCTGAGAATCTGG
[21,] INSIG1 0.31 TGGACCCCACTGGCTGAGAATCTGG
[22,] TIMP1 0.48 TGGACCCCACTGGCTGAGAATCTGG
[23,] GJA1 0.54 AAGCCTATACGTTTCTGTGGAGTAA
[24,] PRG1 0.46 TCCTTGTGCCTGCTCCTGTACTTGT
[25,] EXT1 0.35 TCCTTGTGCCTGCTCCTGTACTTGT
[26,] DKFZP434J154 0.31 GCCCCACTGGACAACACTGATTCCT
[27,] MVP 0.34 CACCCAGCTGGTCCTGTGGATGGGA
[28,] VASP 0.31 TCCTCCATCACCTGAAACACTGGAC
[29,] ARL7 0.39 TGGACCCCACTGGCTGAGAATCTGG
[30,] NNMT 0.34 TCCTGTACTTGTCCTCAGCTTGGGC
[31,] TAP1 0.3 TCCTGTACTTGTCCTCAGCTTGGGC
[32,] PLOD2 0.37 GCCCCACTGGACAACACTGATTCCT
[33,] ATF3 0.42 CACCCAGCTGGTCCTGTGGATGGGA
[34,] PALM2-AKAP2 0.33 TGGACCCCACTGGCTGAGAATCTGG
[35,] IL8 0.34 GCCCCACTGGACAACACTGATTCCT
[36,] LOXL2 0.32 GCCCCACTGGACAACACTGATTCCT
[37,] IL4R 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC
[38,] DGKA 0.32 GCCCCACTGGACAACACTGATTCCT
[39,] SEC61G 0.41 CACCCAGCTGGTCCTGTGGATGGGA
[40,] RGS3 0.37 TGGACCCCACTGGCTGAGAATCTGG
[41,] F2R 0.34 CACCCAGCTGGTCCTGTGGATGGGA
[42,] TPM2 0.35 CACCCAGCTGGTCCTGTGGATGGGA
[43,] PSMB9 0.34 CACCCAGCTGGTCCTGTGGATGGGA
[44,] LOX 0.37 TCCTGTACTTGTCCTCAGCTTGGGC
[45,] STC1 0.35 TCCTCCATCACCTGAAACACTGGAC
[46,] PTGER4 0.31 CACCCAGCTGGTCCTGTGGATGGGA
[47,] SMAD3 0.38 TTGGACATCTCTAGTGTAGCTGCCA
[48,] WNT5A 0.44 TGGACCCCACTGGCTGAGAATCTGG
[49,] BDNF 0.34 'I'CCTCCATCACCTGAAACACTGGAC
[50,] TNFRSFIA 0.46 TCCTCCATCACCTGAAACACTGGAC
[51,] FLNC 0.34 ACTTGTCCTCAGCTTGGGCTTCTTC
[52,] DKFZP564K0822 0.34 TTGGACATCTCTAGTGTAGCTGCCA
[53,] FLOT1 0.38 TTGGACATCTCTAGTGTAGCTGCCA
[54,] PTRF 0.39 TGGACCCCACTGGCTGAGAATCTGG
[55,] HLA-B 0.36 TTGGACATCTCTAGTGTAGCTGCCA
[56,] MGC4083 0.32 GCCCCACTGGACAACACTGATTCCT
[57,] TNFRSF10B 0.34 TGCCTGCTCCTGTACTTGTCCTCAG
[58,] PLAGL1 0.31 TGCCTGCTCCTGTACTTGTCCTCAG
[59,] PNMA2 0.38 GCCCCACTGGACAACACTGATTCCT
[60,] TFPI 0.38 TCCTGTACTTGTCCTCAGCTTGGGC

[61,] GZMB 0.51 TCCTCCATCACCTGAAACACTGGAC
[62,] PLAUR 0.35 AAGCCTATACGTTTCTGTGGAGTAA
[63,] FSCN1 0.32 ACTTGTCCTCAGCTTGGGCTTCTTC
[64,] ERP70 0.32 ACTTGTCCTCAGCTTGGGCTTCTTC
[65,] AFIQ 0.3 TTGGACATCTCTAGTGTAGCTGCCA
[66,] HIC 0.33 TGCCTGCTCCTGTACTTGTCCTCAG
[67,] COL6A1 0.32 AAGCCTATACGTTTCTGTGGAGTAA
[68,] IFITM3 0.3 GCCCCACTGGACAACACTGATTCCT
[69,] MAP1B 0.38 CACCCAGCTGGTCCTGTGGATGGGA
[70,] FLJ46603 0.37 TCCTCCATCACCTGAAACACTGGAC
[71,] RAFTLIN 0.34 TGGACCCCACTGGCTGAGAATCTGG
[72,] RRAS 0.31 TCCTGTACTTGTCCTCAGCTTGGGC
[73,] FTL 0.3 CACCCAGCTGGTCCTGTGGATGGGA
[74,] KIAA0877 0.31 CACCCAGCTGGTCCTGTGGATGGGA
[75,] MT1E 0.31 TCCTTGTGCCTGCTCCTGTACTTGT
[76,] CDC10 0.51 AAATGTTTCCTTGTGCCTGCTCCTG
[77,] DOCK2 0.32 AAGCCTATACGTTTCTGTGGAGTAA
[78,] RIS1 0.37 ACTTGTCCTCAGCTTGGGCTTCTTC
[79,] BCAT=1 0.42 TTGGACATCTCTAGTGTAGCTGCCA
[80,] PRF1 0.34 TCCTCCATCACCTGAAACACTGGAC
[81,] DBNI 0.36 GCCCCACTGGACAACACTGATTCCT
[82,] MT1K 0.3 TGCCTGCTCCTGTACTTGTCCTCAG
[83,] TMSB10 0.42 GCCCCACTGGACAACACTGATTCCT
[84,] FLJ10350 0.4 AAATGTTTCCTTGTGCCTGCTCCTG
[85,] Clorf24 0.34 TGCCTGCTCCTGTACTTGTCCTCAG
[86,] NME7 0.46 TCCTGTACTTGTCCTCAGCTTGGGC
[87,] TMEM22 0.3 TGCCTGCTCCTGTACTTGTCCTCAG
[88,] TPK1 0.37 TCCTCCATCACCTGAAACACTGGAC
[89,] ELK3 0.38 TGCCTGCTCCTGTACTTGTCCTCAG
[90,] CYLD 0.4 TCCTTGTGCCTGCTCCTGTACTTGT
[91,] ADAMTS1 0.31 AAGCCTATACGTTTCTGTGGAGTAA
[92,] EHD2 0.41 TCCTCCATCACCTGAAACACTGGAC
[93,] ACTB 0.33 TCCTTGTGCCTGCTCCTGTACTTGT

Table 39. Methyl-GAG (methyl glyoxal bis amidinohydrazone dihydrochloride) biomarkers.
Gene Correlation Probe Sequence [1,] SSRP1 0.37 TGCCTGCTCCTGTACTTGTCCTCAG
[2,] CTSC 0.35 CACCCAGCTGGTCCTGTGGATGGGA
[3,] LBR 0.38 ACTTGTCCTCAGCTTGGGCTTCTTC
[4,]. EFNB2 0.31 AAATGTTTCCTTGTGCCTGCTCCTG
[5,] SERPINAI 0.34 TCCTTGTGCCTGCTCCTGTACTTGT
[6,] SSSCAI 0.32 TCCTGTACTTGTCCTCAGCTTGGGC
[7,] EZH2 0.36 TTGGACATCTCTAGTGTAGCTGCCA
[8,] MYB 0.33 GCCCCACTGGACAACACTGATTCCT
[9,] PRIM1 0.39 TCCTCCATCACCTGAAACACTGGAC
[10,] H2AFX 0_33 TCCTTGTGCCTGCTCCTGTACTTGT
[11,] HMGA1 0.35 TTGGACATCTCTAGTGTAGCTGCCA
[12,] HMMR 0.33 TCCTTGTGCCTGCTCCTGTACTTGT
[13,] TK2 0.42 CACCCAGCTGGTCCTGTGGATGGGA
[14,] WHSC1 0.35 AAATGTTTCCTTGTGCCTGCTCCTG
[15,] DIAPH1 0.34 GCCCCACTGGACAACACTGATTCCT
[16,] LAMB3 0.31 GCCCCACTGGACAACACTGATTCCT
[17,] DPAGT1 0.42 TGCCTGCTCCTGTACTTGTCCTCAG
[18,] UCK2 0.31 GCCCCACTGGACAACACTGATTCCT
[19,] SERPINB1 0.31 TCCTTGTGCCTGCTCCTGTACTTGT
[20,] MDN1 0.35 TGCCTGCTCCTGTACTTGTCCTCAG

[21,] GOS2 0.43 CACCCAGCTGGTCCTGTGGATGGGA
[22,] MGC21654 0.36 TGGACCCCACTGGCTGAGAATCTGG
[23,] GTSE1 0.35 ACTTGTCCTCAGCTTGGGCTTCTTC
[24,] TACC3 0.31 TCCTCCATCACCTGAAACACTGGAC
[25,] PLAC8 0.31 CACCCAGCTGGTCCTGTGGATGGGA
[26,] HNRPD 0.35 TTGGACATCTCTAGTGTAGCTGCCA
[27,]'PNAS-4 0.3 TTGGACATCTCTAGTGTAGCTGCCA
Table 40. HDAC inhibitors biomarkers.
Gene Correlation Probe Sequence [1,] FAU 0.33 TTGGACATCTCTAGTGTAGCTGCCA
[2,] NOL5A 0.33 TGGACCCCACTGGCTGAGAATCTGG
[3,] AN232A 0.32 CACCCAGCTGGTCCTGTGGATGGGA
[4,] ARHGDIB 0.3 ACTTGTCCTCAGCTTGGGCTTCTTC
[5,] LBR 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC
[6,] FABP5 0.33 TCCTCCATCACCTGAAACACTGGAC
[7,] ITM2A 0.32 TTGGACATCTCTAGTGTAGCTGCCA
[8,] SFRS5 0.34 TCCTCCATCACCTGAAACACTGGAC
[9,] IQGAP2 0.4 CACCCAGCTGGTCCTGTGGATGGGA
[10,] SLC7A6 0.35 AAGCCTATACGTTTCTGTGGAGTAA
[11,] SLA 0.31 TGCCTGCTCCTGTACTTGTCCTCAG
[12,] IL2RG 0.31 TCCTCCATCACCTGAAACACTGGAC
[13,] MFNG 0.39 TCCTGTACTTGTCCTCAGCTTGGGC
[14,] GPSM3 0.32 TTGGACATCTCTAGTGTAGCTGCCA
[15,] PIM2 0.3 TTGGACATCTCTAGTGTAGCTGCCA
[16,] EVER1 0.35 GCCCCACTGGACAACACTGATTCCT
[17,] LRMP 0.35 TGCCTGCTCCTGTACTTGTCCTCAG
[18,] ICAM2 0.44 TCCTGTACTTGTCCTCAGCTTGGGC
[19,] RIMS3 0.43 TGGACCCCACTGGCTGAGAATCTGG
[20,] FMNL1 0.35 TTGGACATCTCTAGTGTAGCTGCCA
[21,] MYB 0.37 TGCCTGCTCCTGTACTTGTCCTCAG
[22,] PTPN7 0.36 TCCTTGTGCCTGCTCCTGTACTTGT
[23,] LCK 0.48 CACCCAGCTGGTCCTGTGGATGGGA
[24,] CXorf9 0.3 ACTTGTCCTCAGCTTGGGCTTCTTC
[25,] RHOH 0.31 TCCTTGTGCCTGCTCCTGTACTTGT
[26,] ZNFNIAI 0.33 AAATGTTTCCTTGTGCCTGCTCCTG
[27,] CENTB1 0.45 CACCCAGCTGGTCCTGTGGATGGGA
[28,] LCP2 0.31 TGCCTGCTCCTGTACTTGTCCTCAG
[29,] DBT 0.32 TCCTGTACTTGTCCTCAGCTTGGGC
[30,] CEP1 0.31 TTGGACATCTCTAGTGTAGCTGCCA
[31,] IL6R 0.31 TGGACCCCACTGGCTGAGAATCTGG
[32,] VAV1 0.32 TCCTTGTGCCTGCTCCTGTACTTGT..
[33,1 MAP4K1 0.3 AAGCCTATACGTTTCTGTGGAGTAA
[34,] CD28 0.36 TCCTTGTGCCTGCTCCTGTACTTGT
[35,] PTP4A3 0.3 TTGGACATCTCTAGTGTAGCTGCCA
[36,] CD3G 0.33 CACCCAGCTGGTCCTGTGGATGGGA
[37,] LTB 0.4 TCCTGTACTTGTCCTCAGCTTGGGC
[38,] USP34 0.44 GCCCCACTGGACAACACTGATTCCT
[39,] NVL 0.41 TCCTTGTGCCTGCTCCTGTACTTGT
[40,1 CD8B1 0.33 ACTTGTCCTCAGCTTGGGCTTCTTC
[41,] SFRS6 0.31 GCCCCACTGGACAACACTGATTCCT
[42,] LCP1 0.34 TCCTGTACTTGTCCTCAGCTTGGGC
[43,] CXCR4 0.36 TGCCTGCTCCTGTACTTGTCCTCAG
[44,] PSCDBP 0.33 TGGACCCCACTGGCTGAGAATCTGG
[45,] SELPLG 0.33 TTGGACATCTCTAGTGTAGCTGCCA
[46,] CD3Z 0.3 TCCTTGTGCCTGCTCCTGTACTTGT
[47,] PRKCQ 0.33 TTGGACATCTCTAGTGTAGCTGCCA

[48,] CDIA 0.34 GCCCCACTGGACAACACTGATTCCT
[49,] GATA2 0.31 TTGGACATCTCTAGTGTAGCTGCCA
[50,] P2RX5 ' 0.32 TGCCTGCTCCTGTACTTGTCCTCAG
[51,] LAIR1 0.35 TGGACCCCACTGGCTGAGAATCTGG
[52,] C1orf38 0.4 GCCCCACTGGACAACACTGATTCCT
[53,] SH2D1A 0.44 TCCTTGTGCCTGCTCCTGTACTTGT
[54,] TRB@ 0.33 CACCCAGCTGGTCCTGTGGATGGGA
[55,] SEPT6 0.34 GCCCCACTGGACAACACTGATTCCT
[56,] HA-1 0.32 AAGCCTATACGTTTCTGTGGAGTAA
[57,] DOCK2 0.3 TCCTTGTGCCTGCTCCTGTACTTGT
[58,] WBSCR20C 0.31 TGCCTGCTCCTGTACTTGTCCTCAG
[59,] CD3D 0.3 ACTTGTCCTCAGCTTGGGCTTCTTC
[60,] RNASE6 0.31 GCCCCACTGGACAACACTGATTCCT
[61,] SFRS7 0.32 AAATGTTTCCTTGTGCCTGCTCCTG
[62,] WBSCR20A 0.3 AAGCCTATACGTTTCTGTGGAGTAA
[63,] NUP210 0.31 TTGGACATCTCTAGTGTAGCTGCCA' [64,] CD6 0.34 TCCTTGTGCCTGCTCCTGTACTTGT
[65,] HNRPAI 0.3 GCCCCACTGGACAACACTGATTCCT
[66,] AIF1 0.34 AAGCCTATACGTTTCTGTGGAGTAA
[67,] CYFIP2 0.38 TGGACCCCACTGGCTGAGAATCTGG
[68,] GLTSCR2 0.38 TCCTTGTGCCTGCTCCTGTACTTGT
[69,] Cllorf2 0.31 AAGCCTATACGTTTCTGTGGAGTAA
[70,] ARHGAP15 0.33 TGGACCCCACTGGCTGAGAATCTGG
[71s] BIN2 0.35 TTGGACATCTCTAGTGTAGCTGCCA
[72,] SH3TC1 0.35 ACTTGTCCTCAGCTTGGGCTTCTTC
[73,] STAG3 0.32 AAATGTTTCCTTGTGCCTGCTCCTG
[74,] TM6SF1 0_34 ACTTGTCCTCAGCTTGGGCTTCTTC
[75,] C15orf25 0.33 TCCTCCATCACCTGAAACACTGGAC
[76,] FLJ22457 0.36 AAATGTTTCCTTGTGCCTGCTCCTG
[77,] PACAP 0.34 TGCCTGCTCCTGTACTTGTCCTCAG
[78,] MGC2744 0.31 GCCCCACTGGACAACACTGATTCCT
Table 41. 5-Fluorouracil biomarkers.
Gene Correlation Probe Sequence [1,] RPL18 0.38 AAATGTTTCCTTGTGCCTGCTCCTG
[2,] RPL10A 0.39 TGGACCCCACTGGCTGAGAATCTGG
[3,] ANAPC5 0.37 ACTTGTCCTCAGCTTGGGCTTCTTC
[4,] EEF1B2 0.3 TCCTGTACTTGTCCTCAGCTTGGGC
[5,] RPL13A 0.5 TGCCTGCTCCTGTACTTGTCCTCAG
[6,] RPS15 0.4 ACTTGTCCTCAGCTTGGGCTTCTTC
[7,] NDUFABl 0.38 GCCCCACTGGACAACACTGATTCCT
[8,] APRT 0.32 AAATGTTTCCTTGTGCCTGCTCCTG
[9,] ZNF593 0.34 TCCTCCATCACCTGAAACACTGGAC
[10,] MRP63 0.32 AAATGTTTCCTTGTGCCTGCTCCTG
[ll,l IL6R 0.41 TGGACCCCACTGGCTGAGAATCTGG
[12,] SART3 0.37 TCCTCCATCACCTGAAACACTGGAC
[13,] UCK2 0.32 GCCCCACTGGACAACACTGATTCCT
[14,] RPL17 0.31 AAGCCTATACGTTTCTGTGGAGTAA
[15,] RPS2 0.35 CACCCAGCTGGTCCTGTGGATGGGA
[16,] PCCB 0.38 TCCTTGTGCCTGCTCCTGTACTTGT
[17,] TOMM20 0.32 TGGACCCCACTGGCTGAGAATCTGG
118,] SHMT2 0.32 TTGGACATCTCTAGTGTAGCTGCCA
j19,1 RPLPO 0.31 TCCTTGTGCCTGCTCCTGTACTTGT
[20,] GTF3A 0.32 CACCCAGCTGGTCCTGTGGATGGGA
[21,] STOML2 0.33 TGGACCCCACTGGCTGAGAATCTGG
[22,] DKFZp564J157 0.4 AAATGTTTCCTTGTGCCTGCTCCTG
[23,] MRPS2 0.32 TCCTGTACTTGTCCTCAGCTTGGGC

[24,] ALG5 0.3 TTGGACATCTCTAGTGTAGCTGCCA
[25,] CALML4 0.33 CACCCAGCTGGTCCTGTGGATGGGA
Table 42. Radiation sensitivity biomarkers.
Gene Correlation Probe Sequence [1,] TRAl 0.36 TGGACCCCACTGGCTGAGAATCTGG
[2,] ACTN4 0.36 ACTTGTCCTCAGCTTGGGCTTCTTC
[3,] CALMl 0.32 TCCTCCATCACCTGAAACACTGGAC
[4,] CD63 0.32 TCCTGTACTTGTCCTCAGCTTGGGC
[5,] FKBP1A 0.38 TGGACCCCACTGGCTGAGAATCTGG
[6,] CALU 0.47 ACTTGTCCTCAGCTTGGGCTTCTTC
[7,] IQGAPl 0.37 TTGGACATCTCTAGTGTAGCTGCCA
[8,] MGC8721 0.35 AAATGTTTCCTTGTGCCTGCTCCTG
[9,] STAT1 0.37 TGGACCCCACTGGCTGAGAATCTGG
[10,] TACCl 0.41 ACTTGTCCTCAGCTTGGGCTTCTTC
[I1,] TM4SF8 0.33 AAGCCTATACGTTTCTGTGGAGTAA
[12,] CD59 0.31 TCCTCCATCACCTGAAACACTGGAC
[13,] CKAP4 0.45 TCCTTGTGCCTGCTCCTGTACTTGT
[14,] DUSP1 0.38 TCCTGTACTTGTCCTCAGCTTGGGC
[15,] RCN1 0.31 TGCCTGCTCCTGTACTTGTCCTCAG
[16,] MGC8902 0.35 TGCCTGCTCCTGTACTTGTCCTCAG
[17,] RRBP1 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC
[18,] PRNP 0.42 TTGGACATCTCTAGTGTAGCTGCCA
[19,] IER.3 - 0.34 GCCCCACTGGACAACACTGATTCCT
[20,] MARCKS 0.43 GCCCCACTGGACAACACTGATTCCT
[21,] FER1L3 0.47 TGCCTGCTCCTGTACTTGTCCTCAG
[22,] SLC20A1 . 0.41 ACTTGTCCTCAGCTTGGGCTTCTTC
[23,] HEXB 0.46 AAATGTTTCCTTGTGCCTGCTCCTG
[24,] EXTl 0.47 CACCCAGCTGGTCCTGTGGATGGGA
[25,] TJP1 0.32 AAATGTTTCCTTGTGCCTGCTCCTG
[26,] CTSL 0.38 TCCTGTACTTGTCCTCAGCTTGGGC
[27,] SLC39A6 0.36 TCCTGTACTTGTCCTCAGCTTGGGC
[28,] RIOK3 0.38 TCCTCCATCACCTGAAACACTGGAC
[29,] CRK 0.37 TGCCTGCTCCTGTACTTGTCCTCAG
[30,] NNMT 0.37 TGCCTGCTCCTGTACTTGTCCTCAG
[31,] TRAM2 0.35 TTGGACATCTCTAGTGTAGCTGCCA
[32,] ADAM9 0.52 TCCTGTACTTGTCCTCAGCTTGGGC
[33,] PLSCR1 0.35 TGGACCCCACTGGCTGAGAATCTGG
[34,] PRSS23 0.3 TGCCTGCTCCTGTACTTGTCCTCAG
[35,] PLOD2 0.36 TGCCTGCTCCTGTACTTGTCCTCAG
[36,] NPC1 0.39 TGCCTGCTCCTGTACTTGTCCTCAG
[37,] TO31 0.37 CACCCAGCTGGTCCTGTGGATGGGA
[38,] GFPT1 0.47 CACCCAGCTGGTCCTGTGGATGGGA
[39,] IL8 0.36 AAATGTTTCCTTGTGCCTGCTCCTG
[40,] PYGL 0.46 TCCTCCATCACCTGAAACACTGGAC
[41,] LOXL2 0.49 TTGGACATCTCTAGTGTAGCTGCCA
[42,] KZAA0355 0.36 TCCTTGTGCCTGCTCCTGTACTTGT
[43,] UGDH 0.49 TTGGACATCTCTAGTGTAGCTGCCA
[44,] PURA 0.32 TGCCTGCTCCTGTACTTGTCCTCAG
[45,] ULK2 0.37 AAGCCTATACGTTTCTGTGGAGTAA
[46,] CENTG2 0.35 GCCCCACTGGACAACACTGATTCCT
[47,] CAP350 0.31 GCCCCACTGGACAACACTGATTCCT
[48,] CXCL1 0.36 TCCTGTACTTGTCCTCAGCTTGGGC
[49,] BTN3A3 0.35 AAGCCTATACGTTTCTGTGGAGTAA
[50,] WNT5A 0.3 AAGCCTATACGTTTCTGTGGAGTAA
[51,] FOXF2 0.44 AAATGTTTCCTTGTGCCTGCTCCTG
[52,] LPHN2 0.34 GCCCCACTGGACAACACTGATTCCT

[53,] =CDH11 0.39 TGGACCCCACTGGCTGAGAATCTGG
[54,1 P4HA1 0.33 TCCTCCATCACCTGAAACACTGGAC
[55,] GRP58 0.44 CACCCAGCTGGTCCTGTGGATGGGA
[56,] DSIPI 0.44 TGGACCCCACTGGCTGAGAATCTGG
[57,] MAP1LC3B 0.5 AAGCCTATACGTTTCTGTGGAGTAA
[58,] GALIG 0.36 AAATGTTTCCTTGTGCCTGCTCCTG
[59,] IGSF4 0.4 TCCTCCATCACCTGAAACACTGGAC
[60,] IRS2 0.35 TGGACCCCACTGGCTGAGAATCTGG
[61,] ATP2A2 0.35 CACCCAGCTGGTCCTGTGGATGGGA
[62,] OGT 0.3 TCCTGTACTTGTCCTCAGCTTGGGC
[63,] TNFRSF10B 0.31 AAGCCTATACGTTTCTGTGGAGTAA
[64,] KIAA1128 0.35 CACCCAGCTGGTCCTGTGGATGGGA
[65,] TM4SF1 0.35 CACCCAGCTGGTCCTGTGGATGGGA
[66,] RIPK2 0.42 TGCCTGCTCCTGTACTTGTCCTCAG
[67,] NR1D2 0.47 TTGGACATCTCTAGTGTAGCTGCCA
[68,] SSA2 0.36 TTGGACATCTCTAGTGTAGCTGCCA
[69,] NQ01 0.4 AAGCCTATACGTTTCTGTGGAGTAA
[70,] ASPH 0.36 TGCCTGCTCCTGTACTTGTCCTCAG
[71,] ASAH1 0.33 ACTTGTCCTCAGCTTGGGCTTCTTC
[72,] MGLL 0.35 TGGACCCCACTGGCTGAGAATCTGG
[73,] SERPINB6 0.51 AAGCCTATACGTTTCTGTGGAGTAA
[74,] HSPA5 0.33 TCCTTGTGCCTGCTCCTGTACTTGT
[75,] ZFP36L1 0.39 TCCTTGTGCCTGCTCCTGTACTTGT
[76,] COL4A1 0.3 ACTTGTCCTCAGCTTGGGCTTCTTC
[77,] NIPA2 0.36 ACTTGTCCTCAGCTTGGGCTTCTTC
[78,] FKBP9 0.48 AAATGTTTCCTTGTGCCTGCTCCTG
[79,] IL6ST 0.4 GCCCCACTGGACAACACTGATTCCT
[80,] DKFZP564G2022 0.39 TTGGACATCTCTAGTGTAGCTGCCA
[81,] PPAP2B 0.33 TGGACCCCACTGGCTGAGAATCTGG
[82,] MAP1B 0.3 CACCCAGCTGGTCCTGTGGATGGGA
[83,] MAPK1 0.3 TGGACCCCACTGGCTGAGAATCTGG
[84,] MYO1B 0.38 ACTTGTCCTCAGCTTGGGCTTCTTC
[85,] CAST 0.31 TGCCTGCTCCTGTACTTGTCCTCAG
[86,'] RRAS2 0.52 AAATGTTTCCTTGTGCCTGCTCCTG
[87,] QKI 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC
[88,] LHFPL2 0.36 TCCTTGTGCCTGCTCCTGTACTTGT
[89,] SEPT10 0.38 GCCCCACTGGACAACACTGATTCCT
[90,] ARHE 0.5 AAGCCTATACGTTTCTGTGGAGTAA
[91,] KIAA1078 0.34 AAGCCTATACGTTTCTGTGGAGTAA
[92,] FTL 0.38 TCCTGTACTTGTCCTCAGCTTGGGC
[93,] KIAA0877 0.41 AAATGTTTCCTTGTGCCTGCTCCTG
[94,] PLCB1 0.3 AAGCCTATACGTTTCTGTGGAGTAA
[95,] KIAA0802 0.32 TGCCTGCTCCTGTACTTGTCCTCAG
[96,] RAB3GAP 0.43 TGCCTGCTCCTGTACTTGTCCTCAG
[97,] SERPINB1 0.46 TGCCTGCTCCTGTACTTGTCCTGAG
[98,] TIMM17A 0.38 AAATGTTTCCTTGTGCCTGCTCCTG
[99,] SOD2 0.35 TTGGACATCTCTAGTGTAGCTGCCA
[100,] HLA-A 0.33 TTGGACATCTCTAGTGTAGCTGCCA
[101,] I30M02 0.43 CACCCAGCTGGTCCTGTGGATGGGA
[102,] LOC55831 0.32 TCCTGTACTTGTCCTCAGCTTGGGC
[103,] PHLDAl 0.32 CACCCAGCTGGTCCTGTGGATGGGA
[104,] TMEM2 = 0.47 TGGACCCCACTGGCTGAGAATCTGG
[105,] MLPH 0.35 ACTTGTCCTCAGCTTGGGCTTCTTC
[106,] FAD104 0.34 ACTTGTCCTCAGCTTGGGCTTCTTC
[107,] LRRC5 0.42 CACCCAGCTGGTCCTGTGGATGGGA
[108,] RAB7L1 0.41 TTGGACATCTCTAGTGTAGCTGCCA
[109,] FLJ35036 0.36 TCCTGTACTTGTCCTCAGCTTGGGC

[110,] DOCK10 0.41 TCCTCCATCACCTGAAACACTGGAC
[111,] LRP12 0.36 AAGCCTATACGTTTCTGTGGAGTAA
[112,] TXNDC5 0.4 ACTTGTCCTCAGCTTGGGCTTCTTC
[113,] CDC14B 0.39 TGCCTGCTCCTGTACTTGTCCTCAG
[114,] HRMT1Ll 0.38 CACCCAGCTGGTCCTGTGGATGGGA
[115,] DNAJC10 0.31 TTGGACATCTCTAGTGTAGCTGCCA
[116,] TNPO1 0.33 GCCCCACTGGACAACACTGATTCCT
[117,] LONP. 0.32 AAATGTTTCCTTGTGCCTGCTCCTG
[118,] AMIG02 0.38 AAGCCTATACGTTTCTGTGGAGTAA
[119,] DNAPTP6 0.31 TGCCTGCTCCTGTACTTGTCCTCAG
[120,] ADAMTSI 0.37 TTGGACATCTCTAGTGTAGCTGCCA
Table 43. Mabthera (rituximab) biomarkers.
Gene Correlation Probe Sequence [1,] PSMB2 0.89 TCCTCCATCACCTGAAACACTGGAC
[2,] BAT1 0.88 AAGCCTATACGTTTCTGTGGAGTAA=
[3,] ASCC3L1 0.89 TCCTTGTGCCTGCTCCTGTACTTGT
[4,] SET 0.94 AAATGTTTCCTTGTGCCTGCTCCTG
[5,] YWHAZ 0.83 TCCTTGTGCCTGCTCCTGTACTTGT
[6,] GLUL 0.8 TGGACCCCACTGGCTGAGAATCTGG
[7,] LDHA 0.8 TCCTTGTGCCTGCTCCTGTACTTGT
[8,] HMGBl 0.84 AAATGTTTCCTTGTGCCTGCTCCTG
[9,] SFRS2 0.87 AAATGTTTCCTTGTGCCTGCTCCTG
[10,] DPYSL2 0.82 TCCTGTACTTGTCCTCAGCTTGGGC
[11,] MGC8721 0.82. CACCCAGCTGGTCCTGTGGATGGGA
[12,] NOLSA 0.86 TGCCTGCTCCTGTACTTGTCCTCAG
[13,] SFRS10 0.88 AAATGTTTCCTTGTGCCTGCTCCTG
[14,] SF3B1 0.82 TCCTGTACTTGTCCTCAGCTTGGGC
[15,] K-ALPHA-1 0.86 TGCCTGCTCCTGTACTTGTCCTCAG
[16,] TXNRD1 0.86 TGGACCCCACTGGCTGAGAATCTGG
[17,] ARHGDIB 0.83 CACCCAGCTGGTCCTGTGGATGGGA
[18,] ZFP36L2 0.92 TTGGACATCTCTAGTGTAGCTGCCA
[19,] DHX15 0.81 TGGACCCCACTGGCTGAGAATCTGG
[20,] SOX4 0.85 CACCCAGCTGGTCCTGTGGATGGGA
[21,] GRSF1 0.81 TGGACCCCACTGGCTGAGAATCTGG
[22,] MCM3 0.85 GCCCCACTGGACAACACTGATTCCT
[23,] IFITMl 0.82 TCCTCCATCACCTGAAACACTGGAC
[24,] RPA2 0.86 TCCTCCATCACCTGAAACACTGGAC
[25,] LBR 0.87 ACTTGTCCTCAGCTTGGGCTTCTTC
[26,] CKS1B 0.85 AAGCCTATACGTTTCTGTGGAGTAA
[27,] NASP 0.82 TGGACCCCACTGGCTGAGAATCTGG
[28,] HNRPDL 0.81 TCCTCCATCACCTGAAACACTGGAC
[29,] CUGBP2 0.81 TGCCTGCTCCTGTACTTGTCCTCAG
[30,] PTBP1 0.87 TCCTTGTGCCTGCTCCTGTACTTGT
[31,] ARL7 0.83 TTGGACATCTCTAGTGTAGCTGCCA
[32,] CTCF 0.83 ACTTGTCCTCAGCTTGGGCTTCTTC
[33,] HMGCR 0.86 TCCTTGTGCCTGCTCCTGTACTTGT
[34,] ITM2A 0.88 AAATGTTTCCTTGTGCCTGCTCCTG
[35,] SFRS3 0.93 TCCTTGTGCCTGCTCCTGTACTTGT
[36,] SRPK2 0.82 TCCTTGTGCCTGCTCCTGTACTTGT
[37,] JARID2 0.92 CACCCAGCTGGTCCTGTGGATGGGA
[38,] M96 0.84 TCCTGTACTTGTCCTCAGCTTGGGC
[39,] MAD2L1 0.87 TCCTCCATCACCTGAAACACTGGAC
[40,] SATB1 0.81 ACTTGTCCTCAGCTTGGGCTTCTTC
[41,] TMPO 0.9 ACTTGTCCTCAGCTTGGGCTTCTTC
[42,) SIVA 0.84 ACTTGTCCTCAGCTTGGGCTTCTTC

[43,] SEMA4D 0.9 TCCTCCATCACCTGAAACACTGGAC
[44,] TFDP2 0.87 TCCTTGTGCCTGCTCCTGTACTTGT
[45,] SKP2 0.86 AAGCCTATACGTTTCTGTGGAGTAA
[46,] SH3YL1 0.88 GCCCCACTGGACAACACTGATTCCT
[47,] RFC4 0.87 TCCTCCATCACCTGAAACACTGGAC
[48,] PCBP2 0.83 AAGCCTATACGTTTCTGTGGAGTAA
[49,] IL2RG 0.84 GCCCCACTGGACAACACTGATTCCT
[50,] CDC45L 0.89 TCCTGTACTTGTCCTCAGCTTGGGC
[51,] GTSE1 0.83 TTGGACATCTCTAGTGTAGCTGCCA
[52,] KIF11 0.85 AAGCCTATACGTTTCTGTGGAGTAA
[53,] FEN1 0.88 TTGGACATCTCTAGTGTAGCTGCCA
[54,] MYB 0.9 TGGACCCCACTGGCTGAGAATCTGG
[55,] LCK 0.87 TCCTCCATCACCTGAAACACTGGAC
[56,] CENPA 0.84 GCCCCACTGGACAACACTGATTCCT
[57,] CCNE2 0.84 GCCCCACTGGACAACACTGATTCCT
[58,] H2AFX 0.88 TTGGACATCTCTAGTGTAGCTGCCA
[59,] SNRPG 0.84 TCCTCCATCACCTGAAACACTGGAC
[60,] CD3G 0.94 TCCTTGTGCCTGCTCCTGTACTTGT
[61,] STK6 0.9 ACTTGTCCTCAGCTTGGGCTTCTTC
[62,] PTP4A2 0.81 TGCCTGCTCCTGTACTTGTCCTCAG
[63,] FDFT1 0.91 AAATGTTTCCTTGTGCCTGCTCCTG
[64,] HSPA8 0.84 AAATGTTTCCTTGTGCCTGCTCCTG
[65,] HNRPR 0.94 TCCTTGTGCCTGCTCCTGTACTTGT
[66,] MCM7 0.92 AAATGTTTCCTTGTGCCTGCTCCTG
[67,] SFRS6 0_85 TGGACCCCACTGGCTGAGAATCTGG
[68,] PAK2 0.8 CACCCAGCTGGTCCTGTGGATGGGA
[69,] LCP1 0.85 TCCTGTACTTGTCCTCAGCTTGGGC
[70,] STAT3 0.81 ACTTGTCCTCAGCTTGGGCTTCTTC
[71,] OK/SW-cl.56 0.8 TCCTTGTGCCTGCTCCTGTACTTGT
[72,] WHSC1 0.81 TGGACCCCACTGGCTGAGAATCTGG
[73,] DIAPHI 0.88 AAGCCTATACGTTTCTGTGGAGTAA
[74,] KIF2C 0.88 TCCTGTACTTGTCCTCAGCTTGGGC
[75,] HDGFRP3 0.89 CACCCAGCTGGTCCTGTGGATGGGA
[76,] PNMA2 0.93 TTGGACATCTCTAGTGTAGCTGCCA
[77,] GATA3 0.93 TCCTGTACTTGTCCTCAGCTTGGGC
[78,] BUB1 0.88 AAATGTTTCCTTGTGCCTGCTCCTG
[79,] TPX2 0.8 CACCCAGCTGGTCCTGTGGATGGGA
[80,] SH2D1A 0.86 TCCTTGTGCCTGCTCCTGTACTTGT
[81,] TNFAIP8 0.9 TCCTCCATCACCTGAAACACTGGAC
[82,] CSElL 0.83 AAATGTTTCCTTGTGCCTGCTCCTG
[83,] MCAM 0.8 TCCTGTACTTGTCCTCAGCTTGGGC
[84,] AF1Q 0.83 GCCCCACTGGACAACACTGATTCCT
[85,] CD47 0.86 CACCCAGCTGGTCCTGTGGATGGGA
[86,] SFRS1 0.85 AAGCCTATACGTTTCTGTGGAGTAA
[87,] FYB 0.92 TCCTGTACTTGTCCTCAGCTTGGGC
[88,] TRB@ 0.84 ACTTGTCCTCAGCTTGGGCTTCTTC
[89,] CXCR4 0.94 GCCCCACTGGACAACACTGATTCCT
[90,] H3F3B 0.84 TCCTCCATCACCTGAAACACTGGAC
[91,] MK167 0.83 ACTTGTCCTCAGCTTGGGCTTCTTC
[92,] MAC30 0.82 TCCTTGTGCCTGCTCCTGTACTTGT
[93,] ARIDSB 0.88 AAGCCTATACGTTTCTGTGGAGTAA
[94,] LOC339287 0.81 AAGCCTATACGTTTCTGTGGAGTAA
[95,] CD3D 0.82 TCCTTGTGCCTGCTCCTGTACTTGT
[96,] ZAP70 0.87 AAGCCTATACGTTTCTGTGGAGTAA
[97,] LAPTM4B 0.83 TCCTCCATCACCTGAAACACTGGAC
[98,] SFRS7 0.87 TCCTTGTGCCTGCTCCTGTACTTGT
[99,] HNRPA1 0.9 AAGCCTATACGTTTCTGTGGAGTAA

(100,] HSPCA - 0.88 AAGCCTATACGTTTCTGTGGAGTAA
[101,] AIF1 0.82 TCCTTGTGCCTGCTCCTGTACTTGT
[102,] GTF3A 0.87 AAGCCTATACGTTTCTGTGGAGTAA
[103,] MCM5 0.91 TTGGACATCTCTAGTGTAGCTGCCA
[104,] GTL3 0.85 AAGCCTATACGTTTCTGTGGAGTAA
[105,] ZNF22 0.89 TGCCTGCTCCTGTACTTGTCCTCAG
[106,] FLJ22794 0.83 GCCCCACTGGACAACACTGATTCCT
[107,] LZTFL1 0.89 ACTTGTCCTCAGCTTGGGCTTCTTC
[108,] e(y)2 0.87 TCCTCCATCACCTGAAACACTGGAC
[109,] FLJ20152 0.92 TCCTCCATCACCTGAAACACTGGAC
[110,] ClOorf3 0.86 ACTTGTCCTCAGCTTGGGCTTCTTC
[111,] NRN1 ' 0.86 AAATGTTTCCTTGTGCCTGCTCCTG
[112,] FLJ10858 0.81 GCCCCACTGGACAACACTGATTCCT
[113,] BCL11B 0.89 GCCCCACTGGACAACACTGATTCCT
[114,] ASPM 0.91 AAGCCTATACGTTTCTGTGGAGTAA
[115,] LEF1 0.9 TTGGACATCTCTAGTGTAGCTGCCA
[116,] L0C146909 0.83 ACTTGTCCTCAGCTTGGGCTTCTTC
Table 44. 5-Aza-2'-deoxycytidine(decitabine) biomarkers.
Gene Correlation Probe Sequence [1,] CD99 0.31 TTGGACATCTCTAGTGTAGCTGCCA
[2,] SNRPA 0.32 TCCTGTACTTGTCCTCAGCTTGGGC
[3,] CUGBP2 0.32 TCCTGTACTTGTCCTCAGCTTGGGC
[4,] STAT5A 0.32 GCCCCACTGGACAACACTGATTCCT
[5,] SLA 0.38 TTGGACATCTCTAGTGTAGCTGCCA
[6,] 'IL2RG 0.33 TGGACCCCACTGGCTGAGAATCTGG
[7,] GTSE1 0.32 ACTTGTCCTCAGCTTGGGCTTCTTC
[8,] MYB 0.36 TGGACCCCACTGGCTGAGAATCTGG
[9,] PTPN7 0.33 TCCTGTACTTGTCCTCAGCTTGGGC
[10,] CXorf9 0.42 TCCTGTACTTGTCCTCAGCTTGGGC
[11,] RHOH 0.38 AAATGTTTCCTTGTGCCTGCTCCTG
[12,] ZNFNIAI 0.33 AAGCCTATACGTTTCTGTGGAGTAA
[13,] CENTBI 0.35 CACCCAGCTGGTCCTGTGGATGGGA
[14,] LCP2 0.3 AAATGTTTCCTTGTGCCTGCTCCTG
[15,] HIST1H4C 0.33 TGGACCCCACTGGCTGAGAATCTGG
[16,] CCR7 0.37 TGCCTGCTCCTGTACTTGTCCTCAG
[17,] APOBEC3B 0.31 TCCTTGTGCCTGCTCCTGTACTTGT
[18,] MCM7 0.31 TGGACCCCACTGGCTGAGAATCTGG
[19,] LCP1 0.31 AAGCCTATACGTTTCTGTGGAGTAA
[20,] SELPLG 0.4 TGGACCCCACTGGCTGAGAATCTGG
[21,] CD3Z 0.35 TCCTGTACTTGTCCTCAGCTTGGGC
(22,) PRKCQ 0.39 TGCCTGCTCCTGTACTTGTCCTCAG.
[23,] GZMB 0.32 GCCCCACTGGACAACACTGATTCCT
[24,] SCN3A 0.4 AAGCCTATACGTTTCTGTGGAGTAA
[25,] LAIR1 0.35 TGCCTGCTCCTGTACTTGTCCTCAG
[26,] SH2D1A 0.35 GCCCCACTGGACAACACTGATTCCT
[27,] SEPT6 0.35 ACTTGTCCTCAGCTTGGGCTTCTTC
[28,] CG018 0.32 ACTTGTCCTCAGCTTGGGCTTCTTC
[29,] CD3D 0.31 TGGACCCCACTGGCTGAGAATCTGG
[30,] C18orf10 0.33 TCCTTGTGCCTGCTCCTGTACTTGT
[31,) PRF1 0.31 TCCTCCATCACCTGAAACACTGGAC
[32,] AIF1 0.31 TTGGACATCTCTAGTGTAGCTGCCA
[33,] MCM5 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC
[34,] LPXN 0.35 TCCTCCATCACCTGAAACACTGGAC
[35,] C22orf18 0.33 AAATGTTTCCTTGTGCCTGCTCCTG
[36,] ARHGAP15 0.31 AAATGTTTCCTTGTGCCTGCTCCTG
[37,] LEF1 0.43 GCCCCACTGGACAACACTGATTCCT

What is claimed is:

DEMANDE OU BREVET VOLUMINEUX

LA PRESENTE PARTIE DE CETTE DEMANDE OU CE BREVET COMPREND
PLUS D'UN TOME.

NOTE : Pour les tomes additionels, veuillez contacter le Bureau canadien des brevets JUMBO APPLICATIONS/PATENTS

THIS SECTION OF THE APPLICATION/PATENT CONTAINS MORE THAN ONE
VOLUME

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NOTE POUR LE TOME / VOLUME NOTE:

Claims (94)

1. A method of predicting sensitivity of a cancer patient to a treatment for cancer comprising determining a level of expression of at least one gene in a cell of said patient, said gene selected from the group consisting of ACTB, ACTN4, ADA, ADAM9, ADAMTS1, ADD1, AF1Q, AIF1, AKAP1, AKAP13, AKR1C1, AKT1, ALDH2, ALDOC, ALG5, ALMS1, ALOX15B, AMIGO2, AMPD2, AMPD3, ANAPC5, ANP32A, ANP32B, ANXA1, AP1G2, APOBEC3B, APRT, ARHE, ARHGAP15, ARHGAP25, ARHGDIB, ARHGEF6, ARL7, ASAH1, ASPH, ATF3, ATIC, ATP2A2, ATP2A3, ATP5D, ATP5G2, ATP6V1B2, BC008967, BCAT1, BCHE, BCL11B, BDNF, BHLHB2, BIN2, BLMH, BMI1, BNIP3, BRDT, BRRN1, BTN3A3, C11orf2, C14orf139, C15orf25, C18orf10, C1orf24, C1orf29, C1orf38, C1QR1, C22orf18, C6orf32, CACNA1G, CACNB3, CALM1, CALML4, CALU, CAP350, CASP2, CASP6, CASP7, CAST, CBLB, CCNA2, CCNB1IP1, CCND3, CCR7, CCR9, CD1A, CD1C, CD1D, CD1E, CD2, CD28, CD3D, CD3E, CD3G, CD3Z, CD44, CD47, CD59, CD6, CD63, CD8A, CD8B1, CD99, CDC10, CDC14B, CDH11, CDH2, CDKL5, CDKN2A, CDW52, CECR1, CENPB, CENTB1, CENTG2, CEP1, CG018, CHRNA3, CHS1, CIAPIN1, CKAP4, CKIP-1, CNP, COL4A1, COL5A2, COL6A1, CORO1C, CRABP1, CRK, CRY1, CSDA, CTBP1, CTSC, CTSL, CUGBP2, CUTC, CXCL1, CXCR4, CXorf9, CYFIP2, CYLD, CYR61, DATF1, DAZAP1, DBN1, DBT, DCTN1, DDX18, DDX5, DGKA, DIAPH1, DKC1, DKFZP434J154, DKFZP564C186, DKFZP564G2022, DKFZp564J157, DKFZP564K0822, DNAJC10, DNAJC7, DNAPTP6, DOCK10, DOCK2, DPAGT1, DPEP2, DPYSL3, DSIPI, DUSP1, DXS9879E, EEF1B2, EFNB2, EHD2, EIF5A, ELK3, ENO2, EPAS1, EPB41L4B, ERCC2, ERG, ERP70, EVER1, EVI2A, EVL, EXT1, EZH2, F2R, FABP5, FAD104, FAM46A, FAU, FCGR2A, FCGR2C, FER1L3, FHL1, FHOD1, FKBP1A, FKBP9, FLJ10350, FLJ10539, FLJ10774, FLJ12270, FLJ13373, FLJ20859, FLJ21159, FLJ22457, FLJ35036, FLJ46603, FLNC, FLOT1, FMNL1, FNBP1, FOLH1, FOXF2, FSCN1, FTL, FYB, FYN, G0S2, G6PD, GALIG, GALNT6, GATA2, GATA3, GFPT1, GIMAP5, GIT2, GJA1, GLRB, GLTSCR2, GLUL, GMDS, GNAQ, GNB2, GNB5, GOT2, GPR65, GPRASP1, GPSM3, GRP58, GSTM2, GTF3A, GTSE1, GZMA, GZMB, H1F0, H1FX, H2AFX, H3F3A, HA-1, HEXB, HIC, HIST1H4C, HK1, HLA-A, HLA-B, HLA-DRA, HMGA1, HMGN2, HMMR, HNRPA1, HNRPD, HNRPM, HOXA9, HRMT1L1, HSA9761, HSPA5, HSU79274, HTATSF1, ICAM1, ICAM2, IER3, IFI16, IFI44, IFITM2, IFITM3, IFRG28, IGFBP2, IGSF4, IL13RA2, IL21R, IL2RG, IL4R, IL6, IL6R, IL6ST, IL8, IMPDH2, INPP5D, INSIG1, IQGAP1, IQGAP2, IRS2, ITGA5, ITM2A, JARID2, JUNB, K-ALPHA-1, KHDRBS1, KIAA0355, KIAA0802, KIAA0877, KIAA0922, KIAA1078, KIAA1128, KIAA1393, KIFC1, LAIR1, LAMB1, LAMB3, LAT, LBR, LCK, LCP1, LCP2, LEF1, LEPRE1, LGALS1, LGALS9, LHFPL2, LNK, LOC54103, LOC55831, LOC81558, LOC94105, LONP, LOX, LOXL2, LPHN2, LPXN, LRMP, LRP12, LRRC5, LRRN3, LST1, LTB, LUM, LY9, LY96, MAGEB2, MAL, MAP1B, MAP1LC3B, MAP4K1, MAPK1, MARCKS, MAZ, MCAM, MCL1, MCM5, MCM7, MDH2, MDN1, MEF2C, MFNG, MGC17330, MGC21654, MGC2744, MGC4083, MGC8721, MGC8902, MGLL, MLPH, MPHOSPH6, MPP1, MPZL1, MRP63, MRPS2, MT1E, MT1K, MUF1, MVP, MYB, MYL9, MYO1B, NAP1L1, NAP1L2, NARF, NASP, NCOR2, NDN, NDUFAB1, NDUFS6, NFKBIA, NID2, NIPA2, NME4, NME7, NNMT, NOL5A, NOL8, NOMO2, NOTCH1, NPC1, NQO1, NR1D2, NUDC, NUP210, NUP88, NVL, NXF1, OBFC1, OCRL, OGT, OXA1L, P2RX5, P4HA1, PACAP, PAF53, PAFAH1B3, PALM2-AKAP2, PAX6, PCBP2, PCCB, PFDN5, PFN1, PFN2, PGAM1, PHEMX, PHLDA1, PIM2, PITPNC1, PLAC8, PLAGL1, PLAUR, PLCB1, PLEK2, PLEKHC1, PLOD2, PLSCR1, PNAS-4, PNMA2, POLR2F, PPAP2B, PRF1, PRG1, PRIM1, PRKCH, PRKCQ, PRKD2, PRNP, PRP19, PRPF8, PRSS23, PSCDBP, PSMB9, PSMC3, PSME2, PTGER4, PTGES2, PTOV1, PTP4A3, PTPN7, PTPNS1, PTRF, PURA, PWP1, PYGL, QKI, RAB3GAP, RAB7L1, RAB9P40, RAC2, RAFTLIN, RAG2, RAP1B, RASGRP2, RBPMS, RCN1-, RFC3, RFC5, RGC32, RGS3, RHOH, RIMS3, RIOK3, RIPK2, RIS1, RNASE6, RNF144, RPL10, RPL10A, RPL12, RPL13A, RPL17, RPL18, RPL36A, RPLP0, RPLP2, RPS15, RPS19, RPS2, RPS4X, RPS4Y1, RRAS, RRAS2, RRBP1, RRM2, RUNX1, RUNX3, S100A4, SART3, SATB1, SCAP1, SCARB1, SCN3A, SEC31L2, SEC61G, SELL, SELPLG, SEMA4G, SEPT10, SEPT6, SERPINA1, SERPINB1, SERPINB6, SFRS5, SFRS6, SFRS7, SH2D1A, SH3GL3, SH3TC1, SHD1, SHMT2, SIAT1, SKB1, SKP2, SLA, SLC1A4, SLC20A1, SLC25A15, SLC25A5, SLC39A14, SLC39A6, SLC43A3, SLC4A2, SLC7A11, SLC7A6, SMAD3, SMOX, SNRPA, SNRPB, SOD2, SOX4, SP140, SPANXC, SPI1, SRF, SRM, SSA2, SSBP2, SSRP1, SSSCA1, STAG3, STAT1, STAT4, STAT5A, STC1, STC2, STOML2, T3JAM, TACC1, TACC3, TAF5, TAL1, TAP1, TARP, TBCA, TCF12, TCF4, TFDP2, TFPI, TIMM17A, TIMP1, TJP1, TK2, TM4SF1, TM4SF2, TM4SF8, TM6SF1, TMEM2, TMEM22, TMSB10, TMSNB, TNFAIP3, TNFAIP8, TNFRSF10B, TNFRSF1A, TNFRSF7, TNIK, TNPO1, TOB1, TOMM20, TOX, TPK1, TPM2, TRA@, TRA1, TRAM2, TRB@, TRD@, TRIM, TRIM14, TRIM22, TRIM28, TRIP13, TRPV2, TUBGCP3, TUSC3, TXN, TXNDC5, UBASH3A, UBE2A, UBE2L6, UBE2S, UCHL1, UCK2, UCP2, UFD1L, UGDH, ULK2, UMPS, UNG, USP34, USP4, VASP, VAV1, VLDLR, VWF, WASPIP, WBSCR20A, WBSCR20C, WHSC1, WNT5A, ZAP70, ZFP36L1, ZNF32, ZNF335, ZN7593, ZNFN1A1, and ZYX; wherein a change in the level of expression of said gene indicates said patient is sensitive to, said treatment.

2. The method of claim 1, wherein said at least one gene is selected from the group consisting of RPS4X, S100A4, NDUFS6, C14orf139, SLC25A5, RPL10, RPL12, EIF5A, RPL36A, BLMH, CTBP1, TBCA, MDH2, and DXS9879E or wherein the method further comprises measuring a level of expression of at least one gene selected from the group consisting of UBB, B2M, MAN1A1, and SUI1, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to Vincristine.

3. The method of claim 1, wherein said at least one gene is selected from the group consisting of C1QR1, SLA, PTPN7, ZNFN1A1, CENTB1, IFI16, ARHGEF6, SEC31L2, CD3Z, GZMB, CD3D, MAP4K1, GPR65, PRF1, ARHGAP15, TM6SF1, and TCF4 or wherein the method further comprises measuring the level of expression of at least one gene selected from the group consisting of HCLS1, CD53, PTPRCAP, and PTPRC, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to Cisplatin.

4. The method of claim 1, wherein said at least one gene is selected from the group consisting of SRM, SCARB1, SIAT1, CUGBP2, ICAM1, WASPIP, ITM2A, PALM2-AKAP2, PTPNS1, MPP1, LNK, FCGR2A, RUNX3, EVI2A, BTN3A3, LCP2, BCHE, LY96, LCP1, IFI16, MCAM, MEF2C, SLC1A4, FYN, C1orf38, CHS1, FCGR2C, TNIK, AMPD2, SEPT6, RAFTLIN, SLC43A3, RAC2, LPXN, CKIP-1, FLJ10539, FLJ35036, DOCK10, TRPV2, IFRG28, LEF1, and ADAMTS1 or wherein the method further comprises measuring the level of expression of at least one gene selected from the group consisting of MSN, SPARC, VIM, GAS7, ANPEP, EMP3, BTN3A2, FN1, and CAPN3, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to Azaguanine.

5. The method of claim 1, wherein said at least one gene is selected from the group consisting of CD99, INSIG1, PRG1, MUF1, SLA, SSBP2, GNB5, MFNG, PSMB9, EVI2A, PTPN7, PTGER4, CXorf9, ZNFN1A1, CENTB1, NAP1L1, HLA-DRA, IFI16, ARHGEF6, PSCDBP, SELPLG, LAT, SEC31L2, CD3Z, SH2D1A, GZMB, SCN3A, RAFTLIN, DOCK2, CD3D, RAC2, ZAP70, GPR65, PRF1, ARHGAP15, NOTCH1, and UBASH3A or wherein the method further comprises measuring the level of expression of at least one gene selected from the group consisting of LAPTM5, HCLS1, CD53, GMFG, PTPRCAP, PTPRC, CORO1A, and ITK, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to Etoposide.

6. The method of claim 1, wherein said at least one gene is selected from the group consisting of CD99, ALDOC, SLA, SSBP2, IL2RG, CXorf9, RHOH, ZNFN1A1, CENTB1, CD1C, MAP4Kl, CD3G, CCR9, CXCR4, ARHGEF6, SELPLG, LAT, SEC31L2, CD3Z, SH2D1A, CD1A, LAIR1, TRB@, CD3D, WBSCR20C, ZAP70, IFI44, GPR65, AIF1, ARHGAP15, NARF, and PACAP or wherein the method further comprises measuring the level of expression of at least one gene selected from the group consisting of LAPTM5, HCLS1, CD53, GMFG, PTPRCAP, TCF7, CD1B, PTPRC, CORO1A, HEM1, and ITK, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to Adriamycin.

7. The method of claim 1, wherein said at least one gene is selected from the group consisting of RPL12, RPLP2, MYB, ZNFN1A1, SCAP1, STAT4, SP140, AMPD3, TNFAIP8, DDX18, TAF5, RPS2, DOCK2, GPR65, HOXA9, FLJ12270, and HNRPD or wherein the method further comprises measuring the level of expression of at least one gene selected from the group consisting of RPL32, FBL, and PTPRC, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to Aclarubicin.

8. The method of claim 1, wherein said at least one gene is selected from the group consisting of PGAM1, DPYSL3, INSIG1, GJA1, BNIP3, PRG1, G6PD, PLOD2, LOXL2, SSBP2, Clorf29, TOX, STC1, TNFRSF1A, NCOR2, NAP1L1, LOC94105, ARHGEF6, GATA3, TFPI, LAT, CD3Z, AF1Q, MAP1B, TRIM22, CD3D, BCAT1, IFI44, CUTC, NAP1L2, NME7, FLJ21159, and COL5A2 or wherein the method further comprises measuring the level of expression of at least one gene selected from the group consisting of BASP1, COL6A2, PTPRC, PRKCA, CCL2, and RAB31, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to Mitoxantrone.

9. The method of claim 1, wherein said at least one gene is selected from the group consisting of STC1, GPR65, DOCK10, COL5A2, FAM46A, and LOC54103, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to Mitomycin.

10. The method of claim 1, wherein said at least one gene is selected from the group consisting of RPL10, RPS4X, NUDC, DKC1, DKFZP564C186, PRP19, RAB9P40, HSA9761, GMDS, CEP1, IL13RA2, MAGEB2, HMGN2, ALMS1, GPR65, FLJ10774, NOL8, DAZAP1, SLC25A15, PAF53, DXS9879E, PITPNC1, SPANXC, and KIAA1393 or wherein the method further comprises measuring the level of expression of RALY, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to Paclitaxel.

11. The method of claim 1, wherein said at least one gene is selected from the group consisting of PFN1, PGAM1, K-ALPHA-1, CSDA, UCHL1, PWP1, PALM2-AKAP2, TNFRSF1A, ATP5G2, AF1Q, NME4, and FHOD1, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to Gemcitabine.

12. The method of claim 1, wherein said at least one gene is selected from the group consisting of ANP32B, GTF3A, RRM2, TRIM14, SKP2, TRIP13, RFC3, CASP7, TXN, MCM5, PTGES2, OBFC1, EPB41L4B, and CALML4, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to Taxotere.

13. The method of claim 1, wherein said at least one gene is selected from the group consisting of IFITM2, UBE2L6, USP4, ITM2A, IL2RG, GPRASP1, PTPN7, CXorf9, RHOH, GIT2, ZNFN1A1, CEP1, TNFRSF7, MAP4K1, CCR7, CD3G, ATP2A3, UCP2, GATA3, CDKN2A, TARP, LAIR1, SH2D1A, SEPT6, HA-1, ERCC2, CD3D, LST1, AIF1, ADA, DATF1, ARHGAP15, PLAC8, CECR1, LOC81558, and EHD2 or wherein the method further comprises measuring the level of expression of at least one gene selected from the group consisting of LAPTM5, ITGB2, ANPEP, CD53, CD37, ADORA2A, GNA15, PTPRC, CORO1A, HEM1, FLII, and CREB3L1, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to Dexamethasone.

14. The method of claim 1, wherein said at least one gene is selected from the group consisting of ITM2A, RHOH, PRIM1, CENTB1, NAP1L1, ATP5G2, GATA3, PRKCQ, SH2D1A, SEPT6, NME4, CD3D, CD1E, ADA, and FHOD1 or wherein the method further comprises measuring the level of expression of at least one gene selected from the group consisting of GNA15, PTPRC, and RPL13, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to Ara-C.

15. The method of claim 1, wherein said at least one gene is selected from the group consisting of CD99, ARHGDIB, VWF, ITM2A, LGALS9, INPP5D, SATB1, TFDP2, SLA, IL2RG, MFNG, SELL, CDW52, LRMP, ICAM2, RIMS3, PTPN7, ARHGAP25, LCK, CXorf9, RHOH, GIT2, ZNFN1A1, CENTB1, LCP2, SPI1, GZMA, CEP1, CD8A, SCAP1, CD2, CD1C, TNFRSF7, VAV1, MAP4K1, CCR7, C6orf32, ALOX15B, BRDT, CD3G, LTB, ATP2A3, NVL, RASGRP2, LCP1, CXCR4, PRKD2, GATA3, TRA@, KIAA0922, TARP, SEC31L2, PRKCQ, SH2D1A, CHRNA3, CD1A, LST1, LAIR1, CACNA1G, TRB@, SEPT6, HA-1, DOCK2, CD3D, TRD@, T3JAM, FNBP1, CD6, AIF1, FOLH1, CD1E, LY9, ADA, CDKL5, TRIM, EVL, DATF1, RGC32, PRKCH, ARHGAP15, NOTCH1, BIN2, SEMA4G, DPEP2, CECR1, BCL11B, STAG3, GALNT6, UBASH3A, PHEMX, FLJ13373, LEF1, IL21R, MGC17330, AKAP13, ZNF335, and GIMAP5 or wberein the method further comprises measuring the level of expression of at least one gene selected from the group consisting of SRRM1, LAPTM5;
ITGB2, CD53, CD37, GMFG, PTPRCAP, GNA15, BLM, PTPRC, CORO1A, PRKCB1, HEM1, and UGT2B17, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to Methylprednisolone.

16. The method of claim 1, wherein said at least one gene is selected from the group consisting of PRPF8, RPL18, GOT2, RPL13A, RPS15, RPLP2, CSDA, KHDRBS1, SNRPA, IMPDH2, RPS19, NUP88, ATP5D, PCBP2, ZNF593, HSU79274, PRIM1, PFDN5, OXA1L, H3F3A, ATIC, CIAPIN1, RPS2, PCCB, SHMT2, RPLP0, HNRPA1, STOML2, SKB1, GLTSCR2, CCNB1IP1, MRPS2, FLJ20859, and FLJ12270 or wherein the method further comprises measuring the level of expression of at least one gene selected from the group consisting of RNPS1, RPL32, EEF1G, PTMA, RPL13, FBL, RBMX, and RPS9, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to Methotrexate.

17. The method of claim 1, wherein said at least one gene is selected from the group consisting of PFN1, HK1, MCL1, ZYX, RAP1B, GNB2, EPAS1, PGAM1, CKAP4, DUSP1, MYL9, K-ALPHA-1, LGALS1, CSDA, IFITM2, ITGA5, DPYSL3, JUNB, NFKBIA, LAMB1, FHL1, INSIG1, TIMP1, GJA1, PSME2, PRG1, EXT1, DKFZP434J154, MVP, VASP, ARL7, NNMT, TAP1, PLOD2, ATF3, PALM2-AKAP2, IL8, LOXL2, IL4R, DGKA, STC2, SEC61G, RGS3, F2R, TPM2, PSMB9, LOX, STC1, PTGER4, IL6, SMAD3, WNT5A, BDNF, TNFRSF1A, FLNC, DKFZP564K0822, FLOT1, PTRF, HLA-B, MGC4083, TNFRSF10B, PLAGL1, PNMA2, TFPI, LAT, GZMB, CYR61, PLAUR, FSCN1, ERP70, AF1Q, HIC, COL6A1, IFITM3, MAP1B, FLJ46603, RAFTLIN, RRAS, FTL, KIAA0877, MT1E, CDC10, DOCK2, TRIM22, RIS1, BCAT1, PRF1, DBN1, MT1K, TMSB10, FLJ10350, Clorf24, NME7, TMEM22, TPK1, COL5A2, ELK3, CYLD, ADAMTS1, EHD2, and ACTB or wherein the method further comprises measuring the level of expression of at least one gene selected from the group consisting of MSN, ACTR2, AKR1B1, VIM, ITGA3, OPTN, M6PRBP1, COL1A1, BASP1, ANPEP, TGFB1, NFIL3, NK4, CSPG2, PLAU, COL6A2, UBC, FGFR1, BAX, COL4A2, and RAB31, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to Bleomycin.

18. The method of claim 1, wherein said at least one gene is selected from the group consisting of SSRP1, NUDC, CTSC, AP1 G2, PSME2, LBR, EFNB2, SERPINA1, SSSCA1, EZH2, MYB, PRIM1, H2AFX, HMGA1, HMMR, TK2, WHSC1, DIAPH1, LAMB3, DPAGT1, UCK2, SERPINB1, MDN1, BRRN1, G0S2, RAC2, MGC21654, GTSE1, TACC3, PLEK2, PLAC8, HNRPD, and PNAS-4 or wherein the method further comprises measuring the level of expression of PTMA, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to Methyl-GAG.

19. The method of claim 1, wherein said at least one gene is selected from the group consisting of ITGA5, TNFAIP3, WNT5A, FOXF2, LOC94105, IFI16, LRRN3, DOCK10, LEPRE1, COL5A2, and ADAMTS1 or wherein the method further comprises measuring the level of expression of at least one gene selected from the group consisting of MSN, VIM, CSPG2, and FGFR1, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to Carboplatin.

20. The method of claim 1, wherein said at least one gene is selected from the group consisting of RPL18, RPL10A, ANAPC5, EEF1B2, RPL13A, RPS15, AKAP1, NDUFAB1, APRT, ZNF593, MRP63, IL6R, SART3, UCK2, RPL17, RPS2, PCCB, TOMM20, SHMT2, RPLP0, GTF3A, STOML2, DKFZp564J157, MRPS2, ALG5, and CALML4 or wherein the method further comprises measuring the level of expression of at least one gene selected from the group consisting of RNPS1, RPL13, RPS6, and RPL3, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to 5-FU (5-Fluorouracil).

21. The method of claim 1, wherein said at least one gene is selected from the group consisting of KIFC1, VLDLR, RUNX1, PAFAH1B3, H1FX, RNF144, TMSNB, CRY1, MAZ, SLA, SRF, UMPS, CD3Z, PRKCQ, HNRPM, ZAP70, ADD1, RFC5, TM4SF2, PFN2, BMI1, TUBGCP3, ATP6V1B2, CD1D, ADA, CD99, CD2, CNP, ERG, CD3E, CD1A, PSMC3, RPS4Y1, AKT1, TAL1, UBE2A, TCF12, UBE2S, CCND3, PAX6, RAG2, GSTM2, SATB1, NASP, IGFBP2, CDH2, CRABP1, DBN1, AKR1C1, CACNB3, CASP2, CASP2, LCP2, CASP6, MYB, SFRS6, GLRB, NDN, GNAQ, TUSC3, GNAQ, JARID2, OCRL, FHL1, EZH2, SMOX, SLC4A2, UFD1L, ZNF32, HTATSF1, SHD1, PTOV1, NXF1, FYB, TRIM28, BC008967, TRB@, H1F0, CD3D, CD3G, CENPB, ALDH2, ANXA1, H2AFX, CD1E, DDX5, CCNA2, ENO2, SNRPB, GATA3, RRM2, GLUL, SOX4, MAL, UNG, ARHGDIB, RUNX1, MPHOSPH6, DCTN1, SH3GL3, PLEKHC1, CD47, POLR2F, RHOH, and ADD1 or wherein the method further comprises measuring the level of expression of at least one gene selected from the group consisting of ITK, RALY, PSMC5, MYL6, CD1B, STMN1, GNA15, MDK, CAPG, ACTN1, CTNNA1, FARSLA, E2F4, CPSF1, SEPW1, TFRC, ABL1, TCF7, FGFR1, NUCB2, SMA3, FAT, VIM, and ATP2A3, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to Rituximab.

22. The method of claim 1, wherein said at least one gene is selected from the group consisting of TRA1, ACTN4, CALM1, CD63, FKBP1A, CALU, IQGAP1, MGC8721, STAT1, TACC1, TM4SF8, CD59, CKAP4, DUSP1, RCN1, MGC8902, LGALS1, BHLHB2, RRBP1, PRNP, IER3, MARCKS, LUM, FER1L3, SLC20A1, HEXB, EXT1, TJP1, CTSL, SLC39A6, RIOK3, CRK, NNMT, TRAM2, ADAM9, DNAJC7, PLSCR1, PRSS23, PLOD2, NPC1, TOB1, GFPT1, IL8, PYGL, LOXL2, KIAA0355, UGDH, PURA, ULK2, CENTG2, NID2, CAP350, CXCL1, BTN3A3, IL6, WNT5A, FOXF2, LPHN2, CDH11, P4HA1, GRP58, DSIPI, MAP1LC3B, GALIG, IGSF4, IRS2, ATP2A2, OGT, TNFRSF10B, KIAA1128, TM4SF1, RBPMS, RIPK2, CBLB, NR1D2, SLC7A11, MPZL1, SSA2, NQO1, ASPH, ASAH1, MGLL, SERPINB6, HSPA5, ZFP36L1, COL4A1, CD44, SLC39A14, NIPA2, FKBP9, IL6ST, DKFZP564G2022, PPAP2B, MAP1B, MAPK1, MYO1B, CAST, RRAS2, QKI, LHFPL2, 38970, ARHE, KIAA1078, FTL, KIAA0877, PLCB1, KIAA0802, RAB3GAP, SERPINB1, TIMM17A, SOD2, HLA-A, NOMO2, LOC55831, PHLDA1, TMEM2, MLPH, FAD104;
LRRC5, RAB7L1, FLJ35036, DOCK10, LRP12, TXNDC5, CDC14B, HRMT1L1, CORO1C, DNAJC10, TNPO1, LONP, AMIGO2, DNAPTP6, and ADAMTS1 or wherein the method further comprises measuring the level of expression of at least one gene selected from the group consisting of WARS, CD81, CTSB, PKM2, PPP2CB, CNN3, ANXA2, JAK1, EIF4G3, COL1A1, DYRK2, NFIL3, ACTN1, CAPN2, BTN3A2, IGFBP3, FN1, COL4A2, and KPNB1, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to radiation therapy.

23. The method of claim 1, wherein said at least one gene is -selected from the group consisting of FAU, NOL5A, ANP32A, ARHGDIB, LBR, FABP5, ITM2A, SFRS5, IQGAP2, SLC7A6, SLA, IL2RG, MFNG, GPSM3, PIM2, EVER1, LRMP, ICAM2, RIMS3, FMNL1, MYB, PTPN7, LCK, CXorf9, RHOH, ZNFN1A1, CENTB1, LCP2, DBT, CEP1, IL6R, VAV1, MAP4K1, CD28, PTP4A3, CD3G, LTB, USP34, NVL, CD8B1, SFRS6, LCP1, CXCR4, PSCDBP, SELPLG, CD3Z, PRKCQ, CD1A, GATA2, P2RX5, LAIR1, Clorf38, SH2D1A, TRB@, SEPT6, HA-1, DOCK2, WBSCR20C, CD3D, RNASE6, SFRS7, WBSCR20A, NUP210, CD6, HNRPA1, AIF1, CYFIP2, GLTSCR2, C11orf2, ARHGAP15, BIN2, SH3TC1, STAG3, TM6SF1, C15orf25, FLJ22457, PACAP, and MGC2744, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to histone deacetylase (HDAC) inhibitor.

24. The method of claim 1, wherein said at least one gene is selected from the group consisting of CD99, SNRPA, CUGBP2, STAT5A, SLA, IL2RG, GTSE1, MYB, PTPN7, CXorf9, RHOH, ZNFN1A1, CENTB1, LCP2, HIST1H4C, CCR7, APOBEC3B, MCM7, LCP1, SELPLG, CD3Z, PRKCQ, GZMB, SCN3A, LAIR1, SH2D1A, SEPT6, CG018, CD3D, C18orf10, PRF1, AIF1, MCM5, LPXN, C22orf18, ARHGAP15, and LEF1, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to 5-Aza-2'-deoxycytidine (Decitabine).

25. The method of any of claims 1-24, wherein the level of expression of said gene is determined by detecting the level of mRNA transcribed from said gene.

26. The method of any of claims 1-24, wherein the level of expression of said gene is determined by detecting the level of a protein product of said gene.

27. The method of any of claims 1-24, wherein said the level of expression of said gene is determined by detecting the level of the biological activity of a protein product of said gene.

28. The method of any of claims 1, wherein an increase in the level of expression of said gene indicates increased sensitivity of said cancer patient to said treatment.

29. The method of any of claims 1-24, wherein said cell is a cancer cell.

30. The method of any of claims 1, wherein a decrease in the level of expression of said gene indicates increased sensitivity of said cancer patient to said treatment.

31. The method of claim 1, wherein the level of expression of said gene is measured using a quantitative reverse transcription-polymerase chain reaction (qRT-PCR).

32. A method for determining the development of resistance of a cell in a patient to a treatment to which a cell in said patient has previously been sensitive, said method comprising determining the level of expression of at least one gene of any one of claims 2-24 in said cell, wherein a decrease in the level of expression of said gene in said cell relative to the level of expression of said gene in a control cell sensitive to said treatment indicates resistance or a propensity to develop resistance to the treatment by said patient.

33. A method for determining the development of resistance of a cell in a patient to a treatment to which a cell in said patient has previously been sensitive, said method comprising determining the level of expression of at least one gene of any one of claims 2-24 in said cell, wherein an increase in the level of expression of said gene in said cell relative to the level of expression of said gene in a control cell sensitive to said treatment indicates resistance or a propensity to develop resistance to the treatment by said patient.

34. A kit comprising a single-stranded nucleic acid that is complementary to or identical to at least 5 consecutive nucleotides of at least one gene selected from the group consisting of ACTB, ACTN4, ADA, ADAM9, ADAMTS1, ADD1, AF1Q, AIF1, AKAP1, AKAP13, AKR1C1, AKT1, ALDH2, ALDOC, ALG5, ALMS1, ALOX15B, AMIGO2, AMPD2, AMPD3, ANAPC5, ANP32A, ANP32B, ANXA1, AP1G2, APOBEC3B, APRT, ARHE, ARHGAP15, ARHGAP25, ARHGDIB, ARHGEF6, ARL7, ASAH1, ASPH, ATF3, ATIC, ATP2A2, ATP2A3, ATP5D, ATP5G2, ATP6V1B2, BC008967, BCAT1, BCHE, BCL11B, BDNF, BHLHB2, BIN2, BLMH, BMI1, BNIP3, BRDT, BRRN1, BTN3A3, C11orf2, C14orf139, C15orf25, C18orf10, C1orf24, C1orf29, C1orf38, C1QR1, C22orf18, C6orf32, CACNA1G, CACNB3, CALM1, CALML4, CALU, CAP350, CASP2, CASP6, CASP7, CAST, CBLB, CCNA2, CCNB1IP1, CCND3, CCR7, CCR9, CD1A, CD1C, CD1D, CD1E, CD2, CD28, CD3D, CD3E, CD3G, CD3Z, CD44, CD47, CD59, CD6, CD63, CD8A, CD8B1, CD99, CDC10, CDC14B, CDH11, CDH2, CDKL5, CDKN2A, CDW52, CECR1, CENPB, CENTB1, CENTG2, CEP1, CG018, CHRNA3, CHS1, CIAPIN1, CKAP4, CKIP-1, CNP, COL4A1, COL5A2, COL6A1, CORO1C, CRABP1, CRK, CRY1, CSDA, CTBP1, CTSC, CTSL, CUGBP2, CUTC, CXCL1, CXCR4, CXorf9, CYFIP2, CYLD, CYR61, DATF1, DAZAP1, DBN1, DBT, DCTN1, DDX18, DDX5, DGKA, DIAPH1, DKC1, DKFZP434J154, DKFZP564C186, DKFZP564G2022, DKFZp564J157, DKFZP564K0822, DNAJC10, DNAJC7, DNAPTP6, DOCK10, DOCK2, DPAGT1, DPEP2, DPYSL3, DSIPI, DUSP1, DXS9879E, EEF1B2, EFNB2, EHD2, EIF5A, ELK3, ENO2, EPAS1, EPB41L4B, ERCC2, ERG, ERP70, EVER1, EVI2A, EVL, EXT1, EZH2, F2R, FABP5, FAD104, FAM46A, FAU, FCGR2A, FCGR2C, FER1L3, FHL1, FHOD1, FKBP1A, FKBP9, FLJ10350, FLJ10539, FLJ10774, FLJ12270, FLJ13373, FLJ20859, FLJ21159, FLJ22457, FLJ35036, FLJ46603, FLNC, FLOT1, FMNL1, FNBP1, FOLH1, FOXF2, FSCN1, FTL, FYB, FYN, G0S2, G6PD, GALIG, GALNT6, GATA2, GATA3, GFPT1, GIMAP5, GIT2, GJA1, GLRB, GLTSCR2, GLUL, GMDS, GNAQ, GNB2, GNB5, GOT2, GPR65, GPRASP1, GPSM3, GRP58, GSTM2, GTF3A, GTSE1, GZMA, GZMB, H1F0, H1FX, H2AFX, H3F3A, HA-1, HEXB, HIC, HISTIH4C, HK1, HLA-A, HLA-B, HLA-DRA, HMGA1, HMGN2, HMMR, HNRPA1, HNRPD, HNRPM, HOXA9, HRMT1L1, HSA9761, HSPA5, HSU79274, HTATSF1, ICAM1, ICAM2, IER3, IFI16, IFI44, IFITM2, IFITM3, IFRG28, IGFBP2, IGSF4, IL13RA2, IL21R, IL2RG, IL4R, IL6, IL6R, IL6ST, IL8, IMPDH2, INPP5D, INSIG1, IQGAP1, IQGAP2, IRS2, ITGA5, ITM2A, JARID2, JUNB, K-ALPHA-1, KHDRBS1, KIAA0355, KIAA0802, KIAA0877, KIAA0922, KIAA1078, KIAA1128, KIAA1393, KIFC1, LAIR1, LAMB1, LAMB3, LAT, LBR, LCK, LCP1, LCP2, LEF1, LEPRE1, LGALS1, LGALS9, LHFPL2, LNK, LOC54103, LOC55831, LOC81558, LOC94105, LONP, LOX, LOXL2, LPHN2, LPXN, LRMP, LRP12, LRRC5, LRRN3, LST1, LTB, LUM, LY9, LY96, MAGEB2, MAL, MAP1B, MAP1LC3B, MAP4K1, MAPK1, MARCKS, MAZ, MCAM, MCL1, MCM5, MCM7, MDH2, MDN1, MEF2C, MFNG,-MGC17330, MGC21654, MGC2744, MGC4083, MGC8721, MGC8902, MGLL, MLPH, MPHOSPH6, MPP1, MPZL1, MRP63, MRPS2, MT1E, MT1K, MUF1, MVP, MYB, MYL9, MYO1B, NAP1L1, NAP1L2, NARF, NASP, NCOR2, NDN, NDUFAB1, NDUFS6, NFKB1A, NID2, NIPA2, NME4, NME7, NNMT, NOL5A, NOL8, NOMO2, NOTCH1, NPC1, NQO1, NR1D2, NUDC, NUP210, NUP88, NVL, NXF1, OBFC1, OCRL, OGT, OXA1L, P2RX5, P4HA1, PACAP, PAF53, PAFAH1B3, PALM2-AKAP2, PAX6, PCBP2, PCCB, PFDN5, PFN1, PFN2, PGAM1, PHEMX, PHLDA1, PIM2, PITPNC1, PLAC8, PLAGL1, PLAUR, PLCB1, PLEK2, PLEKHC1, PLOD2, PLSCR1, PNAS-4, PNMA2, POLR2F, PPAP2B, PRF1, PRG1, PRIM1, PRKCH, PRKCQ, PRKD2, PRNP, PRP19, PRPF8, PRSS23, PSCDBP, PSMB9, PSMC3, PSME2, PTGER4, PTGES2, PTOV1, PTP4A3, PTPN7, PTPNS1, PTRF, PURA, PWP1, PYGL, QKI, RAB3GAP, RAB7L1, RAB9P40, RAC2, RAFTLIN, RAG2, RAP1B, RASGRP2, RBPMS, RCN1, RFC3, RFC5, RGC32, RGS3, RHOH, RIMS3, RIOK3, RIPK2, RIS1, RNASE6, RNF144, RPL10, RPLIOA, RPL12, RPL13A, RPL17, RPL18, RPL36A, RPLPO, RPLP2, RPS15, RPS19, RPS2, RPS4X, RPS4Y1, RRAS, RRAS2, RRBP1, RRM2, RUNX1, RUNX3, S100A4, SART3, SATB1, SCAP1, SCARB1, SCN3A, SEC31L2, SEC61G, SELL, SELPLG, SEMA4G, SEPT10, SEPT6, SERPINA1, SERPINB1, SERPINB6, SFRS5, SFRS6, SFRS7, SH2D1A, SH3GL3, SH3TC1, SHD1, SHMT2, SIAT1, SKB1, SKP2, SLA, SLC1A4, SLC20A1, SLC25A15, SLC25A5, SLC39A14, SLC39A6, SLC43A3, SLC4A2, SLC7A11, SLC7A6, SMAD3, SMOX, SNRPA, SNRPB, SOD2, SOX4, SP140, SPANXC, SPI1, SRF, SRM, SSA2, SSBP2, SSRP1, SSSCA1, STAG3, STAT1, STAT4, STAT5A, STC1, STC2, STOML2, T3JAM, TACC1, TACC3, TAF5, TAL1, TAP1, TARP, TBCA, TCF12, TCF4, TFDP2, TFP1, TIMM17A, TIMP1, TJP1, TK2, TM4SF1, TM4SF2, TM4SF8, TM6SFI, TMEM2, TMEM22, TMSB10, TMSNB, TNFAIP3, TNFAIP8, TNFRSF10B, TNFRSF1A, TNFRSF7, TNIK, TNPO1, TOB1, TOMM20, TOX, TPK1, TPM2, TRA@, TRA1, TRAM2, TRB@, TRD@, TRIM, TRIM14, TRIM22, TRIM28, TRIP13, TRPV2, TUBGCP3, TUSC3, TXN, TXNDC5, UBASH3A, UBE2A, UBE2L6, UBE2S, UCHL1, UCK2, UCP2, UFD1L, UGDH, ULK2, UMPS, UNG, USP34, USP4, VASP, VAV1, VLDLR, VWF, WASPIP, WBSCR20A, WBSCR20C, WHSC1, WNT5A, ZAP70, ZFP36L1, ZNF32, ZNF335, ZNF593, ZNFN1A1, and ZYX; wherein said single stranded nucleic acid is sufficient for the detection of the level of expression of said gene and allows specific hybridization between said single stranded nucleic acid and a nucleic acid encoded by said gene or a complement thereof, said kit further comprising instructions for applying nucleic acids collected from a sample from a cancer patient, instructions for determining the level of expression of said gene hybridized to said single stranded nucleic acid, and instructions for predicting said patient's sensitivity to a treatment for cancer.

35. The kit of claim 34, wherein said instructions further indicate that a change in said level of expression of said gene relative to the level of expression of said gene in a control cell sensitive to said treatment indicates a change in sensitivity of said patient to said treatment.

36. The kit of claim 34, wherein said gene is selected from the group consisting of RPS4X, S100A4, NDUFS6, C14orf139, SLC25A5, RPL10, RPL12, EIF5A, RPL36A, BLMH, CTBP1, TBCA, MDH2, and DXS9879E, or wherein said kit further comprises one or more single-stranded nucleic acids complementary to or identical to at least 5 consecutive nucleotides of a gene selected from the group consisting of UBB, B2M, MAN1A1, and SUI1, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to said treatment and wherein said treatment is treatment with Vincristine.

37. The kit of claim 34, wherein said gene is selected from the group consisting of C1QR1, SLA, PTPN7, ZNFN1A1, CENTB1, IFI16, ARHGEF6, SEC31L2, CD3Z, GZMB, CD3D, MAP4K1, GPR65, PRF1, ARHGAP15, TM6SF1, and TCF4, or wherein said kit further comprises one or more single-stranded nucleic acids complementary to or identical to at least 5 consecutive nucleotides of a gene selected from the group consisting of HCLS1, CD53, PTPRCAP, and PTPRC, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to said treatment and wherein said treatment is treatment with Cisplatin.

38. The kit of claim 34, wherein said gene is selected from the group consisting of SRM, SCARB1, SIAT1, CUGBP2, ICAM1, WASPIP, ITM2A, PALM2-AKAP2, PTPNS1, MPP1, LNK, FCGR2A, RUNX3, EVI2A, BTN3A3, LCP2, BCBE, LY96, LCP1, IFI16, MCAM, MEF2C, SLC1A4, FYN, Clorf38, CHS1, FCGR2C, TNIK, AMPD2, SEPT6, RAFTLIN, SLC43A3, RAC2, LPXN, CKIP-1, FLJ10539, FLJ35036, DOCK10, TRPV2, IFRG28, LEFI, and ADAMTS1, or wherein said kit further comprises one or more single-stranded nucleic acids complementary to or identical to at least 5 consecutive nucleotides of a gene selected from the group consisting of MSN, SPARC, VIM, GAS7, ANPEP, EMP3, BTN3A2, FN1, and CAPN3, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to said treatment and wherein said treatment is treatment with Azaguanine.

39. The kit of claim 34, wherein said gene is selected from the group consisting of CD99, INSIG1, PRG1, MUF1, SLA, SSBP2, GNB5, MFNG, PSMB9, EVI2A, PTPN7, PTGER4, CXorf9, ZNFN1A1, CENTB1, NAP1L1, HLA-DRA, IFI16, ARHGEF6, PSCDBP, SELPLG, LAT, SEC31L2, CD3Z, SH2D1A, GZMB, SCN3A, RAFTLIN, DOCK2, CD3D, RAC2, ZAP70, GPR65, PRF1, ARHGAP15, NOTCH1, and UBASH3A, or wherein said kit further comprises one or more single-stranded nucleic acids complementary to or identical to at least 5 consecutive nucleotides of a gene selected from the group consisting of LAPTM5, HCLS1, CD53, GMFG, PTPRCAP, PTPRC, CORO1A, and ITK, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to said treatment and wherein said treatment is treatment with Etoposide.

40. The kit of claim 34, wherein said gene is selected from the group consisting of CD99, ALDOC, SLA, SSBP2, IL2RG, CXorf9, RHOH, ZNFN1A1, CENTB1, CD1C, MAP4K1, CD3G, CCR9, CXCR4, ARHGEF6, SELPLG, LAT, SEC31L2, CD3Z, SH2D1A, CD1A, LAIR1, TRB@, CD3D, WBSCR20C, ZAP70, IFI44, GPR65, AIF1, ARHGAP15, NARF, and PACAP, or wherein said kit further comprises one or more single-stranded nucleic acids complementary to or identical to at least 5 consecutive nucleotides of a gene selected from the group consisting of LAPTM5, HCLS1, CD53, GMFG, PTPRCAP, TCF7, CD1B, PTPRC, CORO1A, HEM1, and ITK, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to said treatment and wherein said treatment is treatment with Adriamycin.

41. The kit of claim 34, wherein said gene is selected from the group consisting of RPL12, RPLP2,MYB, ZNFN1A1, SCAP1, STAT4, SP140, AMPD3,TNFAIP8, DDX18, TAF5, RPS2, DOCK2, GPR65, HOXA9, FLJ12270, and HNRPD, or wherein said kit further comprises one or more single-stranded nucleic acids complementary to or identical to at least 5 consecutive nucleotides of a gene selected from the group consisting of RPL32, FBL, and PTPRC, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to said treatment and wherein said treatment is treatment with Aclarubicin.

42. The kit of claim 34, wherein said gene is selected from the group consisting of PGAM1, DPYSL3, INSIG1, GJA1, BNIP3, PRG1, G6PD, PLOD2, LOXL2, SSBP2, Clorf29, TOX, STC1, TNFRSF1A, NCOR2, NAP1L1, LOC94105, ARHGEF6, GATA3, TFPI, LAT, CD3Z, AF1Q, MAP1B, TRIM22; CD3D, BCAT1, IFI44, CUTC, NAP1L2, NME7, FLJ21159, and COL5A2, or wherein said kit further comprises one or more single-stranded nucleic acids complementary to or identical to at least 5 consecutive nucleotides of a gene selected from the group consisting of BASP1, COL6A2, PTPRC, PRKCA, CCL2, and RAB31, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to said treatment and wherein said treatment is treatment with Mitoxantrone.

43. The kit of claim 34, wherein said gene is selected from the group consisting of STC1, GPR65, DOCK10, COL5A2, FAM46A, and LOC54103, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to said treatment and wherein said treatment is treatment with Mitomycin.

44. The kit of claim 34, wherein said gene is selected from the group consisting of RPL10, RPS4X, NUDC, DKC1, DKFZP564C186, PRP19, RAB9P40, HSA9761, GMDS, CEP1, IL13RA2, MAGEB2, HMGN2, ALMS1, GPR65, FLJ10774, NOL8, DAZAP1, SLC25A15, PAF53, DXS9879E, PITPNC1, SPANXC, and KIAA1393, or wherein said kit further comprises one or more single-stranded nucleic acids complementary to or identical to at least 5 consecutive nucleotides of RALY, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to said treatment. and wherein said treatment is treatment with Paclitaxel.

45. The kit of claim 34, wherein said gene is selected from the group consisting of PFN1, PGAM1, K-ALPHA-1, CSDA, UCHL1, PWP1, PALM2-AKAP2, TNFRSF1A, ATP5G2, AF1Q, NME4, and FHOD1, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to said treatment and wherein said treatment is treatment with Gemcitabine.

46. The kit of claim 34, wherein said gene is selected from the group consisting of ANP32B, GTF3A, RRM2, TRIM14, SKP2, TRIP13, RFC3, CASP7, TXN, MCM5, PTGES2, OBFC1, EPB41L4B, and CALML4, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to said treatment and wherein said treatment is treatment with Taxotere.

47. The kit of claim 34, wherein said gene is selected from the group consisting of IFITM2, UBE2L6, USP4, ITM2A, IL2RG, GPRASP1, PTPN7, CXorf9, RHOH, GIT2, ZNFN1A1, CEP1, TNFRSF7, MAP4K1, CCR7, CD3G, ATP2A3, UCP2, GATA3, CDKN2A, TARP, LAIR1, SH2D1A, SEPT6, HA-1, ERCC2, CD3D, LST1, AIF1, ADA, DATF1, ARHGAP15, PLAC8, CECR1, LOC81558, and EHD2, and COL5A2, or wherein said kit further comprises one or more single-stranded nucleic acids complementary to or identical to at least 5 consecutive nucleotides of a gene selected from the group consisting of LAPTM5, ITGB2, ANPEP, CD53, CD37, ADORA2A, GNA15, PTPRC, CORO1A, HEM1, FLII, and CREB3L1, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to said treatment and wherein said treatment is treatment with Dexamethasone.

48. The kit of claim 34, wherein said gene is selected from the group consisting of ITM2A, RHOH, PRIM1, CENTB1, NAP1L1, ATP5G2, GATA3, PRKCQ, SH2D1A, SEPT6, NME4, CD3D, CD1E, ADA, and FHOD1, or wherein said kit further comprises one or more single-stranded nucleic acids complementary to or identical to at least 5 consecutive nucleotides of a gene selected from the group consisting of GNA15, PTPRC, and RPL13, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to said treatment and wherein said treatment is treatment with Ara-C.

49. The kit of claim 34, wherein said gene is selected from the group, consisting of CD99, ARHGDIB, VWF, ITM2A, LGALS9, INPP5D, SATB1, TFDP2, SLA, IL2RG, MFNG, SELL, CDW52, LRMP, ICAM2, RIMS3, PTPN7, ARHGAP25, LCK, CXorf9, RHOH, GIT2, ZNFN1A1, CENTB1, LCP2, SPI1, GZMA, CEP1, CDSA, SCAP1, CD2, CD1C, TNFRSF7, VAV1, MAP4K1, CCR7, C6orf32, ALOX15B, BRDT, CD3G, LTB, ATP2A3, NVL, RASGRP2, LCP1, CXCR4, PRKD2, GATA3, TRA@, KIAA0922, TARP, SEC31L2, PRKCQ, SH2D1A, CHRNA3, CD1A, LSTI, LAIR1, CACNA1G, TRB@, SEPT6, HA-1, DOCK2, CD3D, TRD@, T3JAM, FNBP1, CD6, AIF1, FOLH1, CD1E, LY9, ADA, CDKL5, TRIM, EVL, DATF1, RGC32, PRKCH, ARHGAP15, NOTCH1, BIN2, SEMA4G, DPEP2, CECR1, BCL11B, STAG3, GALNT6, UBASH3A, PHEMX, FLJ13373, LEF1, IL21R, MGC17330, AKAP13, ZNF335, and GIMAP5, or wherein said kit further comprises one or more single-stranded nucleic acids complementary to or identical to at least 5 consecutive nucleotides of a gene selected from the group consisting of SRRM1, LAPTM5, ITGB2, CD53, CD37, GMFG, PTPRCAP, GNA15, BLM, PTPRC, CORO1A, PRKCB1, HEM1, and UGT2B17, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to said treatment and wherein said treatment is treatment with Methylprednisolone.

50. The kit of claim 34, wherein said gene is selected from the group consisting of PRPF8, RPL18, GOT2, RPL13A, RPS15, RPLP2, CSDA, KHDRBS1, SNRPA, IMPDH2, RPS19, NUP88, ATP5D, PCBP2, ZNF593, HSU79274, PRIM1, PFDN5, OXA1L, H3F3A, ATIC, CIAPIN1, RPS2, PCCB, SHMT2, RPLP0, HNRPA1, STOML2, SKB1, GLTSCR2, CCNB1IP1, MRPS2, FLJ20859, and FLJ12270, or wherein said kit further comprises one or more single-stranded nucleic acids complementary to or identical to at least 5 consecutive nucleotides of a gene selected from the group consisting of RNPS1, RPL32, EEF1G, PTMA, RPL13, FBL, RBMX, and RPS9, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to said treatment and wherein said treatment is treatment with Methotrexate.

51. The kit of claim 34, wherein said gene is selected from the group consisting of PFN1, HK1, MCL1, ZYX, RAP1B, GNB2, EPAS1, PGAM1, CKAP4, DUSP1, MYL9, K-ALPHA-1, LGALS1, CSDA, IFITM2, ITGA5, DPYSL3, JUNB, NFKBIA, LAMB1, FHL1, INSIG1, TIMP1, GJA1, PSME2, PRG1, EXT1, DKFZP434J154, MVP, VASP, ARL7, NNMT, TAP1, PLOD2, ATF3, PALM2-AKAP2, IL8, LOXL2, IL4R, DGKA, STC2, SEC61G, RGS3, F2R, TPM2, PSMB9, LOX, STC1, PTGER4, IL6, SMAD3, WNT5A, BDNF, TNFRSF1A, FLNC, DKFZP564K0822, FLOT1, PTRF, HLA-B, MGC4083, TNFRSF10B, PLAGL1, PNMA2, TFPI, LAT, GZMB, CYR61, PLAUR, FSCN1, ERP70, AF1Q, HIC, COL6A1, IFITM3, MAP1B, FLJ46603, RAFTLIN, RRAS, FTL, KIAA0877, MT1E, CDC10, DOCK2, TRIM22, RIS1, BCAT1, PRF1, DBN1, MT1K, TMSB10, FLJ10350, Clorf24, NME7, TMEM22, TPK1, COL5A2, ELK3, CYLD, ADAMTS1, EHD2, and ACTB, or wherein said kit further comprises one or more single-stranded nucleic acids complementary to or identical to at least 5 consecutive nucleotides of a gene selected from the group consisting of MSN, ACTR2, AKR1B1, VIM, ITGA3, OPTN, M6PRBP1, COL1A1, BASP1, ANPEP, TGFB1, NFIL3, NK4, CSPG2, PLAU, COL6A2, UBC, FGFR1, BAX, COL4A2, and RAB31, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to said treatment and wherein said treatment is treatment with Bleomycin.

52. The kit of claim 34, wherein said gene is selected from the group consisting of SSRP1, NUDC, CTSC, AP1G2, PSME2, LBR, EFNB2, SERPINA1, SSSCA1, EZH2, MYB, PRIM1, H2AFX, HMGA1, FMMR, TK2, WHSC1, DIAPH1, LAMB3, DPAGT1, UCK2, SERPINB1, MDN1, BRRN1, G0S2, RAC2, MGC21654, GTSE1, TACC3, PLEK2, PLAC8, HNRPD, and PNAS-4, or wherein said kit further comprises one or more single-stranded nucleic acids complementary to or identical to at least 5 consecutive nucleotides of PTMA, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to said treatment and wherein said treatment is treatment with Methyl-GAG.

53. The kit of claim 34, wherein said gene is selected from the group consisting of ITGA5, TNFAIP3, WNT5A, FOXF2, LOC94105, IFI16, LRRN3, DOCK10, LEPRE1, COL5A2, and ADAMTS 1, or wherein said kit further comprises one or more single-stranded nucleic acids complementary to or identical to at least 5 consecutive nucleotides of a gene selected from the group consisting of MSN, VIM, CSPG2, and FGFR1, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to said treatment and wherein said treatment is treatment with Carboplatin.

54. The kit of claim 34, wherein said gene is selected from the group consisting of RPL18, RPL10A, ANAPC5, EEF1B2, RPL13A, RPS15, AKAP1, NDUFAB1, APRT, ZNF593, MRP63, IL6R, SART3, UCK2, RPL17, RPS2, PCCB, TOMM20, SHMT2, RPLP0, GTF3A, STOML2, DKFZp564J157, MRPS2, ALG5, and CALML4, or wherein said kit further comprises one or more single-stranded nucleic acids complementary to or identical to at least 5 consecutive nucleotides of a gene selected from the group consisting of RNPS1, RPL13, RPS6, and RPL3, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to said treatment and wherein said treatment is treatment with 5-FU (5-Fluorouracil).

55. The kit of claim 34, wherein said gene is selected from the group consisting of KIFC1, VLDLR, RUNX1, PAFAH1B3, H1FX, RNF144, TMSNB, CRY1, MAZ, SLA, SRF, UMPS, CD3Z, PRKCQ, HNRPM, ZAP70, ADD1, RFC5, TM4SF2, PFN2, BMI1, TUBGCP3, ATP6V1B2, CD1D, ADA, CD99, CD2, CNP, ERG, CD3E, CD1A, PSMC3, RPS4Y1, AKT1, TAL1, UBE2A, TCF12, UBE2S, CCND3, PAX6, RAG2, GSTM2, SATB1, NASP, IGFBP2, CDH2, CRABP1, DBN1, AKR1C1, CACNB3, CASP2, CASP2, LCP2, CASP6, MYB, SFRS6, GLRB, NDN, GNAQ, TUSC3, GNAQ, JARID2, OCRL, FHL1, EZH2, SMOX, SLC4A2, UFD1L, ZNF32, HTATSF1, SHD1, PTOV1, NXF1, FYB, TRIM28, BC008967, TRB@, HIF0, CD3D, CD3G, CENPB, ALDH2, ANXA1, H2AFX, CD1E, DDX5; CCNA2, ENO2, SNRPB, GATA3, RRM2, GLUL, SOX4, MAL, UNG, ARHGDIB, RUNX1, MPHOSPH6, DCTN1, SH3GL3, PLEKHC1, CD47, POLR2F, RHOH, and ADD1, or wherein said kit further comprises one or more single-stranded nucleic acids complementary to or identical to at least 5 consecutive nucleotides of a gene selected from the group consisting of ITK, RALY, PSMC5, MYL6, CD1B, STMN1, GNA15, MDK, CAPG, ACTN1, CTNNA1, FARSLA, E2F4, CPSF1, SEPW1, TFRC, ABL1, TCF7, FGFR1, NUCB2, SMA3, FAT, VIM, and ATP2A3, wherein an increase in expres the level of expression sion of said gene indicates that said patient is sensitive to said treatment and wherein said treatment is treatment with Rituxixnab.

56. The kit of claim 34, wherein said gene is selected from the group consisting of TRA1, ACTN4, CALM1, CD63, FKBP1A, CALU, IQGAP1, MGC8721, STAT1, TACC1, TM4SF8, CD59, CKAP4, DUSP1, RCN1, MGC8902, LGALS1, BHLHB2, RRBP1, PRNP, IER3, MARCKS, LUM, FERIL3, SLC20A1, HEXB, EXT1, TJP1, CTSL, SLC39A6, RIOK3, CRK, NNMT, TRAM2, ADAM9, DNAJC7, PLSCR1, PRSS23, PLOD2, NPC1, TOB1, GFPT1,IL8, PYGL, LOXL2, KIAA0355, UGDH, PURA, ULK2, CENTG2, NID2, CAP350, CXCL1, BTN3A3, IL6, WNT5A, FOXF2, LPHN2, -CDH11, P4HA1, GRP58, DSIPI, MAP1LC3B, GALIG, IGSF4, IRS2, ATP2A2, OGT, TNFRSF10B, KIAA1128, TM4SF1, RBPMS, RIPK2, CBLB, NRID2, SLC7A11, MPZL1, SSA2, NQO1, ASPH, ASAH1, MGLL, SERPINB6, HSPA5, ZFP36L1, COL4A1, CD44, SLC39A14, NIPA2, FKBP9, IL6ST, DKFZP564G2022, PPAP2B, MAP1B, MAPK1, MYO1B, CAST, RRAS2, QKI, LHFPL2, 38970, ARHE, KIAA1078, FTL, KIAA0877, PLCB1, KIAA0802, RAB3GAP, SERPINB1, TIMM17A, SOD2, HLA-A, NOMO2, LOC55831, PHLDA1, TMEM2, MLPH, FAD104, LRRC5, RAB7L1, FLJ35036, DOCK10, LRP12, TXNDC5, CDC14B, HRMT1L1, CORO1C, DNAJC10, TNPO1, LONP, AMIGO2, DNAPTP6, and ADAMTS1, or wherein said kit further comprises one or more single-stranded nucleic acids complementary to or identical to at least 5 consecutive nucleotides of a gene selected from the group consisting of WARS, CD81, CTSB, PKM2, PPP2CB, CNN3, ANXA2, JAK1, EIF4G3, COL1A1, DYRK2, NFIL3, ACTN1, CAPN2, BTN3A2, IGFBP3, FN1, COL4A2, and KPNB1, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to said treatment and wherein said treatment is treatment with radiation therapy.

57. The kit of claim 34, wherein said gene is selected from the group consisting of FAU, NOL5A, ANP32A, ARHGDIB, LBR, FABP5, ITM2A, SFRS5, IQGAP2, SLC7A6, SLA, IL2RG, MFNG, GPSM3, PIM2, EVER1, LRMP, ICAM2, RIMS3, FMNL1, MYB, PTPN7, LCK, CXorf9, RHOH, ZNFN1A1, CENTB1, LCP2, DBT, CEP1, IL6R, VAV1, MAP4K1, CD28, PTP4A3, CD3G, LTB, USP34, NVL, CD8B1, SFRS6, LCP1, CXCR4, PSCDBP, SELPLG, CD3Z, PRKCQ, CD1A, GATA2, P2RX5, LAIR1, Clorf38, SH2D1A, TRB@, SEPT6, HA-1, DOCK2, WBSCR20C, CD3D, RNASE6, SFRS7, WBSCR20A, NUP210, CD6, HNRPA1, AIF1, CYFIP2, GLTSCR2, C11orf2, ARHGAP15, BIN2, SH3TC1, STAG3, TM6SF1, C15orf25, FLJ22457, PACAP, and MGC2744, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to said treatment and wherein said treatment is treatment with histone deacetylase (HDAC) inhibitor.

58. The kit of claim 34, wherein said gene is selected from the group consisting of CD99, SNRPA, CUGBP2, STAT5A, SLA, IL2RG, GTSE1, MYB, PTPN7, CXorf9, RHOH, ZNFN1A1, CENTB1, LCP2, HIST1H4C, CCR7, APOBEC3B, MCM7, LCP1, SELPLG, CD3Z, PRKCQ, GZMB, SCN3A, LAIR1, SH2D1A, SEPT6, CG018, CD3D, Cl8orf10, PRF1, AIF1, MCM5, LPXN, C22orf18, ARHGAP15, and LEF1, wherein an increase in the level of expression of said gene indicates that said patient is sensitive to said treatment and wherein said treatment is treatment with 5-Aza-2'-deoxycytidine (Deditabine).

59. The method of any one of claims 1-24, wherein said determining comprises detecting the level of expression of said gene by using a kit of any one of claims 34-58.

60. The kit of claim 34, wherein said treatment comprises administering a chemotherapeutic agent.

61. The kit of claim 34, wherein said single-stranded nucleic acid is characterized by the ability to specifically identify the presence or absence of a nucleic acid complementary to said gene in a sample collected from said cancer patient.

62. The kit of any one of claims 34-58, wherein said single-stranded nucleic acid is at least 15 nucleotides long.

63. The kit of claim 62, wherein said single-stranded nucleic acid is at least 25 nucleotides long.

64. The kit of any one of claims 34-58, wherein said single-stranded nucleic acid is a deoxyribonucleic acid (DNA).

65. A method of identifying biomarkers useful for the determination of sensitivity of a cancer patient to a treatment for cancer comprising:
a. obtaining pluralities of measurements of the level of expression of a gene in different cell types and measurements of the growth of those cell types in the presence of a treatment for cancer relative to the growth of said cell types in the absence of said treatment for cancer;
b. correlating each plurality of measurements of the level of expression of said gene in said cells with the growth of said cells to obtain a correlation coefficient;

c. selecting the median correlation coefficient calculated for said gene; and d. identifying said gene as a biomarker for use in determining the sensitivity of a cancer patient to said treatment for cancer if said median correlation coefficient exceeds 0.3.

66. The method of claim 65, wherein said correlation coefficient exceeds 0.4.

67. The method of claim 65, wherein said gene is selected from the group consisting of ACTB, ACTN4, ADA, ADAM9, ADAMTS1, ADD1, AF1Q, ALF1, AKAP1, AKAP13, AKR1C1, AKT1, ALDH2, ALDOC, ALG5, ALMS1, ALOX15B, AMIGO2, AMPD2, AMPD3, ANAPC5, ANP32A, ANP32B, ANXA1, AP1G2, APOBEC3B, APRT, ARHE, ARHGAP15, ARHGAP25, ARHGDIB, ARHGEF6, ARL7, ASAH1, ASPH, ATF3, ATIC, ATP2A2, ATP2A3, ATP5D, ATP5G2, ATP6V1B2, BC008967, BCAT1, BCHE, BCL11B, BDNF, BHLHB2, BIN2, BLMH, BMI1, BNIP3, BRDT, BRRN1, BTN3A3, C11orf2, C14orf139, C15orf25, C18orf10, Clorf24, Clorf29, Clorf38, C1QR1, C22orf18, C6orf32, CACNA1G, CACNB3, CALM1, CALML4, CALU, CAP350, CASP2, CASP6, CASP7, CAST, CBLB, CCNA2, CCNB11P1, CCND3, CCR7, CCR9, CD1A, CD1C, CD1D, CD1E, CD2, CD28, CD3D, CD3E, CD3G, CD3Z, CD44, CD47, CD59, CD6, CD63, CD8A, CD8B1, CD99, CDC10, CDC14B, CDH11, CDH2, CDKL5, CDKN2A, CDW52, CECR1, CENPB, CENTB1, CENTG2, CEP1, CG018, CHRNA3, CHS1, CIAPIN1, CKAP4, CKIP-1, CNP, COL4A1, COL5A2, COL6A1, CORO1C, CRABP1, CRK, CRY1, CSDA, CTBP1, CTSC, CTSL, CUGBP2, CUTC, CXCL1, CXCR4, CXorf9, CYFIP2, CYLD, CYR61, DATF1, DAZAP1, DBN1, DBT, DCTN1, DDX18, DDX5, DGKA, DIAPH1, DKC1, DKFZP434J154, DKFZP564C186, DKFZP564G2022, DKFZp564J157, DKFZP564K0822, DNAJC10, DNAJC7, DNAPTP6, DOCK10, DOCK2, DPAGT1, DPEP2, DPYSL3, DSIPI, DUSP1, DXS9879E, EEF1B2, EFNB2, EHD2, EIF5A, ELK3, ENO2, EPAS1, EPB41L4B, ERCC2, ERG, ERP70, EVER1, EVI2A, EVL, EXT1, EZH2, F2R, FABP5, FAD104, FAM46A, FAU, FCGR2A, FCGR2C, FER1L3, FHL1, FHOD1, FKBP1A, FKBP9, FLJ10350, FLJ10539, FLJ10774;
FLJ12270, FLJ13373, FLJ20859, FLJ21159, FLJ22457, FLJ35036, FLJ46603, FLNC, FLOT1, FMNL1, FNBP1, FOLH1, FOXF2, FSCN1, FTL, FYB, FYN, G0S2, G6PD, GALIG, GALNT6, GATA2, GATA3, GFPT1, GIMAP5, GIT2, GJA1, GLRB, GLTSCR2, GLUL, GMDS, GNAQ, GNB2, GNB5, GOT2, GPR65, GPRASP1, GPSM3, GRP58, GSTM2, GTF3A, GTSE1, GZMA, GZMB, HIF0, H1FX, H2AFX, H3F3A, HA-1, HEXB, HIC, HIST1H4C, HK1, HLA-A, HLA-B, HLA-DRA, HMGA1, HMGN2, HMMR, HNRPA1, HNRPD, HNRPM, HOXA9, HRMTIL1, HSA9761, HSPA5, HSU79274, HTATSF1, ICAM1, ICAM2, IER3, IFI16, IFI44, IFITM2, IFITM3, IFRG28, IGFBP2, IGSF4, IL13RA2, IL21R, IL2RG, IL4R, IL6, IL6R, IL6ST, IL8, IMPDH2, INPP5D, INSIG1, IQGAP1, IQGAP2, IRS2, ITGA5, ITM2A, JARID2, JUNB, K-ALPHA-1, KHDRBS1, KIAA0355, KIAA0802, KIAA0877, KIAA0922, KLAA1078, KIAA1128, KIAA1393, KIFC1, LAIR1, LAMB1, LAMB3, LAT, LBR, LCK, LCP1, LCP2, LEF1, LEPRE1, LGALS1, LGALS9, LHFPL2, LNK, LOC54103, LOC55831, LOC81558, LOC94105, LONP, LOX, LOXL2, LPHN2, LPXN, LRMP, LRP12, LRRC5, LRRN3, LST1, LTB, LUM, LY9, LY96, MAGEB2, MAL, MAP1B, MAP1LC3B, MAP4K1, MAPK1, MARCKS, MAZ, MCAM, MCL1, MCM5, MCM7, MDH2, MDN1, MEF2C, MFNG, MGC17330, MGC21654, MGC2744, MGC4083, MGC8721, MGC8902, MGLL, MLPH, MPHOSPH6, MPP1, MPZL1, MRP63, MRPS2, MT1E, MT1K, MUF1,MVP, MYB, MYL9, MYO1B, NAP1L1, NAP1L2, NARF, NASP, NCOR2, NDN, NDUFAB1, NDUFS6, NFKBIA, NID2, NIPA2, NME4, NME7, NNMT, NOLSA, NOL8, NOMO2, NOTCH1, NPC1, NQO1, NR1D2, NUDC, NUP210, NUP88, NVL, NXF1, OBFC1, OCRL, OGT, OXA1L, P2RX5, P4HA1, PACAP, PAF53; PAFAH1B3, PALM2-AKAP2, PAX6, PCBP2, PCCB, PFDN5, PFN1, PFN2, PGAM1, PHEMX, PHLDA1, PIM2, PITPNC1, PLAC8, PLAGL1, PLAUR, PLCB1, PLEK2, PLEKHCl, PLOD2, PLSCR1, PNAS-4, PNMA2, POLR2F, PPAP2B, PRF1, PRG1, PRIM1, PRKCH, PRKCQ, PRKD2, PRNP, PRP19, PRPF8, PRSS23, PSCDBP, PSMB9, PSMC3, PSME2, PTGER4, PTGES2, PTOV1, PTP4A3, PTPN7, PTPNS1, PTRF, PURA, PWP1, PYGL, QKI, RAB3GAP, RAB7L1, RAB9P40, RAC2, RAFTLIN, RAG2, RAP1B, RASGRP2, RBPMS, RCN1, RFC3, RFC5, RGC32, RGS3, RHOH, RIMS3, RIOK3, RIPK2, RIS1, RNASE6, RNF144, RPL10, RPL10A, RPL12, RPL13A, RPLI7, RPL18, RPL36A, RPLPO, RPLP2, RPS15, RPS19, RPS2, RPS4X, RPS4Y1, RRAS, RRAS2, RRBP1, RRM2, RUNX1, RUNX3, S100A4, SART3, SATB1, SCAP1, SCARB1, SCN3A, SEC31L2, SEC61G, SELL, SELPLG, SEMA4G, SEPT10, SEPT6, SERPINA1, SERPINB1, SERPINB6, SFRS5, SFRS6, SFRS7, SH2D1A, SH3GL3, SH3TC1, SHD1, SHMT2, SIAT1, SKB1, SKP2, SLA, SLC1A4, SLC20A1, SLC25A15, SLC25A5, SLC39A14, SLC39A6, SLC43A3, SLC4A2, SLC7A11, SLC7A6, SMAD3, SMOX, SNRPA, SNRPB, SOD2, SOX4, SP140, SPANXC, SPI1, SRF, SRM, SSA2, SSBP2, SSRP1, SSSCA1, STAG3, STAT1, STAT4, STAT5A, STC1, STC2, STOML2, T3JAM, TACC1, TACC3, TAF5, TAL1, TAP1, TARP, TBCA, TCF12, TCF4, TFDP2, TFPI, TIMM17A, TIMP1, TJP1, TK2, TM4SF1, TM4SF2, TM4SF8, TM6SF1, TMEM2, TMEM22, TMSB10, TMSNB, TNFAIP3, TNFAIP8, TNFRSF10B, TNFRSF1A, TNFRSF7, TNIK, TNPO1, TOB1, TOMM20, TOX, TPK1, TPM2, TRA@, TRA1, TRAM2, TRB@, TRD@, TRIM, TRIM14, TRIM22, TRIM28, TRIP13, TRPV2, TUBGCP3, TUSC3, TXN, TXNDC5, UBASH3A, UBE2A, UBE2L6, UBE2S, UCHL1, UCK2, UCP2, UFD1L, UGDH, ULK2, UMPS, UNG, USP34, USP4, VASP, VAV1, VLDLR, VWF, WASPIP, WBSCR20A, WBSCR20C, WHSC1, WNT5A, ZAP70, ZFP36L1, ZNF32, ZNF335, ZNF593, ZNFN1A1, and ZYX.

68. The method of claim 65, wherein the measurement of step a) includes measurements of growth in the presence of a second treatment.

69. The method of claim 65, wherein said treatment comprises administering a compound, a protein, an antibody, an oligonucleotide, a chemotherapeutic agent, or radiation to a patient.

70. The method of claim 69, wherein said compound is selected from the group consisting of Vincristine, Cisplatin, Adriamycin, Etoposide, Azaguanine, Aclarubicin, Mitoxantrone, Paclitaxel, Mitomycin, Gemcitabine, Taxotere, Dexamethasone, Methylprednisolone, Ara-C, Methotrexate, Bleomycin, Methyl-GAG, Rituximab, histone deacetylase (HDAC) inhibitors, and 5-Aza-2'-deoxycytidine (Decitabine).

71. The method of claim 69, wherein said compound has previously failed to show an effect in said cancer patient.

72. The method of claim 65, wherein said cancer patient is selected from a subpopulation predicted to be sensitive to said treatment.

73. The method of claim 65, wherein said cancer patient is selected from a subpopulation predicted to die without treatment.

74. The method of claim 65, wherein said cancer patient is selected from a subpopulation predicted to have disease symptoms without treatment.

75. The method of claim 65, wherein said cancer patient is selected from a subpopulation predicted to be cured without treatment.

76. The methods of claim 1 or 65, wherein said measurements of the level of expression are analyzed using a quantitative reverse transcription-polymerase chain reaction (qRT-PCR).

77. A method of predicting sensitivity of a cancer patient to a treatment for cancer, comprising:
a. obtaining a measurement of the level of expression of a biomarker gene in a sample from said cancer patient;
b. applying a model predictive of sensitivity to a treatment for cancer to said measurement, wherein said model is developed using an algorithm selected from the group consisting of linear sums, nearest neighbor, nearest centroid, linear discriminant analysis, support vector machines, and neural networks; and c. predicting whether or not said cancer patient will be responsive to said treatment for cancer.

78. The method of claim 77, wherein said gene is selected from the group consisting of ACTB, ACTN4, ADA, ADAM9, ADAMTS1, ADD1, AF-1Q, AIF1, AKPP1, AKAP13, AKR1C1, AKT1, ALDH2, ALDOC, ALG5, ALMS1, ALOX15B, AMIGO2, AMPD2, AMPD3, ANAPC5, ANP32A, ANP32B, ANXA1, AP1G2, APOBEC3B, APRT, ARHE, ARHFGAP15, ARHGAP25, ARHGDIB, ARHGEF6, ARL7, ASAH1, ASPH, ATF3, ATIC, ATP2A2, ATP2A3, ATP5D, ATP5G2, ATP6V1B2, BC008967, BCAT1, BCHE, BCL11B, BDNF, BHLHB2,BIN2, BLMH, BMI1, BNIP3, BRDT, BRRN1, BTN3A3, C11orf2, C1orf139, C15orf25, C18orf10, Clorf24, Clorf29, Clorf38, C1QR1, C22orf18, C6orf32, CACNA1G, CACNB3, CALM1, CALML4, CALU, CAP350, CASP2, CASP6, CASP7, CAST, CBLB, CCNA2, CCNBIIP1, CCND3, CCR7, CCR9, CD1A, CD1C, CD1D, CD1E, CD2, CD28, CD3D, CD3E, CD3G, CD3Z, CD44, CD47, CD59, CD6, CD63, CD8A, CD8B1, CD99, CDC10, CDC14B, CDH11, CDH2, CDKL5, CDKN2A, CDW52, CECR1, CENPB, CENTB1, CENTG2, CEP1, CG018, CHRNA3, CHS1, CIAPIN1, CKAP4, CKIP-1, CNP, COL4A1, COL5A2, COL6A1, CORO1C, CRABP1, CRK, CRY1, CSDA, CTBP1, CTSC, CTSL, CUGBP2, CUTC, CXCL1, CXCR4, CXorf9, CYFIP2, CYLD, CYR61, DATF1, DAZAP1, DBN-1, DBT, DCTN1, DDX18, DDXS, DGKA, DIAPH1, DKC1, DKFZP434J154, DKFZP564C186, DKFZP564G2022, DKFZp564J157, DKFZP564K0822, DNAJC10, DNAJC7, DNAPTP6, DOCK10, DOCK2, DPAGT1, DPEP2, DPYSL3, DSIPI, DUSP1, DXS9879E, EEF1B2, EFNB2, EHD2, EIF5A, ELK3, ENO2, EPAS1, EPB41L4B, ERCC2, ERG, ERP70, EVER1, EVI2A, EVL, EXT1, EZH2, F2R, FABP5, FAD104, FAM46A, FAU, FCGR2A, FCGR2C, FER1L3, FHL1, PHOD1, FKBP1A, FKBP9, FLJ10350, FLJ10539, FLJ10774, FLJ12270, FLJ13373, FLJ20859, FLJ21159, FLJ22457, FLJ35036, FLJ46603, FLNC, FLOT1, FMNL1, FNBPI, FOLH1, FOXF2, FSCN1, FTL, FYB, FYN, G0S2, G6PD, GALIG, GALNT6, GATA2, GATA3, GFPT1, GIMAP5, GIT2, GJAl, GLRB, GLTSCR2, GLUL, GMDS, GNAQ, GNB2, GN135, GOT2, GPR65, GPRASP1, GPSM3, GRP58, GSTM2, GTF3A, GTSE1, GZMA, GZMB, H1F0, H1FX, H2AFX, H3F3A, HA-1, HEXB, HIC, HIST1H4C, HK1, HLA-A, HLA-B, HLA-DRA, HMGA1, HMGN2, HMMR, HNRPA1, HNRPD, HNRPM, HOXA9, HRMT1L1, HSA9761, HSPA5, HSU79274, HTATSF1, ICAM1 ICAM2, TER3, IFI16, IFI44, IFITM2, IFITM3, IFRG28, IGFBP2, IGSF4, IL13RA2, IL21R, IL2RG, IL4R, IL6, IL6R, IL6ST, IL8, IMPDH2,INPP5D, INSIG1, IQGAP1, IQGAP2, IRS2, ITGA5, ITM2A, JARID2, JUNB, K-ALPHA-1, KHDRBS1, KIAA0355, KIAA0802, KIAA0877, KIAA0922, KIAA1078, KIAA1128, KIAA1393, KIFC1, LAIR1, LAMB1, LAMB3, LAT, LBR, LCK, LCP1, LCP2, LEF1, LEPRE1, LGALS1, LGALS9, LHFPL2, LNK, LOC54103, LOC55831, LOC81558, LOC94105, LONP, LOX, LOXL2, LPHN2, LPXN, LRMP, LRP12, LRRC5, LRRN3, LST1, LTB, LUM, LY9, LY96, MAGEB2, MAL, MAP1B, MAP1LC3B, MAP4K1, MAPK1, MARCKS, MAZ, MCAM, MCL1, MCM5, MCM7, MDH2, MDN1, MEF2C, MFNG, MGC17330, MGC21654, MGC2744, MGC4083, MGC8721, MGC8902, MGLL, MLPH, MPHOSPH6, MPP1, MPZL1, MRP63, MRPS2, MT1E, MT1K, MUF1, MVP, MYB, MYL9, MYO1B, NAP1L1, NAP1L2, NARF, NASP, NCOR2, NDN, NDUFAB1, NDUFS6, NFKBIA, NID2, NIPA2, NME4, NME7, NNMT, NOL5A, NOL8, NOMO2, NOTCH1, NPC1, NQO1, NR1D2, NUDC, NUP210, NUP88, NVL, NXTF1, OBFC1, OCRL, OGT, OXA1L, P2RX5, P4HA1, PACAP, PAF53, PAFAH1B3, PALM2-AKAP2, PAX6, PCBP2, PCCB, PFDN5, PFN1, PFN2, PGAM1, PHEMX, PHLDA1, PIM2, PITPNC1, PLAC8, PLAGL1, PLAUR, PLCB1, PLEK2, PLEKHC1, PLOD2, PLSCR1, PNAS-4, PNMA2, POLR2F, PPAP2B, PRF1, PRG1, PRIM1, PRKCH, PRKCQ, PRKD2, PRNP, PRP19, PRPF8, PRSS23, PSCDBP, PSMB9, PSMC3, PSME2, PTGER4, PTGES2, PTOV1, PTP4A3, PTPN7, PTPNS1, PTRF, PURA, PWP1, PYGL, QKI, RAB3GAP, RAB7L1, RAB9P40, RAC2, RAFTLIN, RAG2, RAP1B, RASGRP2, RBPMS, RCN1, RFC3, RFC5, RGC32, RGS3, RHOH, RIMS3, RIOK3, RIPK2, RIS1, RNASE6, RNF144, RPL10, RPL10A, RPL12, RPL13A, RPL17, RPL18, RPL36A, RPLP0, RPLP2, RPS15, RPS19, RPS2, RPS4X, RPS4Y1, RRAS, RRAS2, RRBP1, RRM2, RUNX1, RUNX3, S100A4, SART3, SATB1, SCAP1, SCARB1, SCN3A, SEC31L2, SEC61G, SELL, SELPLG, SEMA4G, SEPT10, SEPT6, SERPINA1, SERPINB1, SERPINB6, SFRS5, SFRS6, SFRS7, SH2D1A, SH3GL3, SH3TC1, SHD1, SHMT2, SIAT1; SKB1, SKP2, SLA, SLC1A4, SLC20A1, SLC25A15, SLC25A5, SLC39A14, SLC39A6, SLC43A3, SLC4A2, SLC7A11, SLC7A6, SMAD3, SMOX, SNRPA, SNRPB, SOD2, SOX4, SP140, SPANXC, SPI1, SRF, SRM, SSA2, SSBP2, SSRP1, SSSCA1, STAG3, STAT1, STAT4, STAT5A, STC1, STC2, STOML2, T3JAM, TACC1, TACC3, TAF5, TAL1, TAP1, TARP, TBCA, TCF12, TCF4, TFDP2, TFPI, TIMM17A, TIMP1, TJP1, TK2, TM4SF1, TM4SF2, TM4SF8, TM6SF1, TMEM2, TMEM22, TMSB10, TMSNB, TNFAIP3, TNFAIP8, TNFRSF10B, TNFRSF1A, TNFRSF7, TNIK, TNPO1, TOB1, TOMM20, TOX, TPK1, TPM2, TRA@, TRA1, TRAM2, TRB@, TRD@, TRIM, TRIM14, TRIM22, TRIM28, TRIP13, TRPV2, TUBGCP3, TUSC3, TXN, TXNDC5, UBASH3A, UBE2A, UBE2L6, UBE2S, UCHL1, UCK2, UCP2, UFD1L, UGDH, ULK2, UMPS, UNG, USP34, USP4, VASP, VAV1, VLDLR, VWF, WASPIP, WBSCR20A, WBSCR20C, WHSC1, WNT5A, ZAP70, ZFP36L1, ZNF32, ZNF335, ZNF593, ZNFN1A1, and ZYX.

79. The method of claim 77, wherein said model combines the outcomes of linear sums, linear discriminant analysis, support vector machines, neural networks, k-nearest neighbors, and nearest centroids.

80. The method of claim 77, wherein said model is cross-validated using a random sample of said measurements.

81. The method of claim 77, wherein a second treatment is present.

82. The method of claim 77, wherein said treatment comprises administering a compound, a protein, an antibody, an oligonucleotide, a chemotherapeutic agent, or radiation to a patient.

83. The method of claim 82, wherein said compound is selected from the group consisting of Vincristine, Cisplatin, Adriamycin, Etoposide, Azaguanine, Aclarubicin, Mitoxantrone, Paclitaxel, Mitomycin, Gemcitabine, Taxotere, Dexamethasone, Methylprednisolone, Ara-C, Methotrexate, Bleomycin, Methyl-GAG, Rituximab, histone deacetylase (HDAC) inhibitors, and 5-Aza-2'-deoxycytidine (Decitabine).

84. The method of claim 82, wherein said compound has previously failed to show effect on patients.

85. The method of claim 77, wherein said linear sum is compared to a sum of a reference population with known sensitivity.

86. The method of claim 85, wherein said sum of a reference population is the median of the sums derived from the population members' biomarker gene expression.

87. The method of claim 77, wherein said model is derived from the components of a data set obtained by independent component analysis.

88. The method of claim 77, wherein said model is derived from the components of a data set obtained by principal component analysis.

89. The method of claim 77, wherein said cancer patient is selected from a subpopulation predicted to be sensitive to said treatment.

90. The method of claim 77, wherein said cancer patient is selected from a subpopulation predicted to die without treatment.

91. The method of claim 77, wherein said cancer patient is selected from a subpopulation predicted to have disease symptoms without treatment.

92. The method of claim 77, wherein said cancer patient is selected from a subpopulation predicted to be cured without treatment.

93. The method of claim 77, wherein said measurements of the level of expression of said biomarker gene are analyzed using a quantitative reverse transcription-polymerase chain reaction (qRT-PCR).

94. A kit, apparatus, and software used to implement the method of claim 77.