Colorectal cancer consensus molecular subtype classifier codesets and methods of use thereof

A method of treating a patient having colorectal cancer, the method comprising:

• (i) classifying a cancer status of a subject having colorectal cancer by:
• (a) obtaining a tumor sample from the subject;
• (b) measuring expression levels of a plurality of genes in the tumor sample, wherein the plurality of genes comprises at least 20 genes selected from the group consisting of ACSL5, ADGRG6, AGR2, ANKRD27, ANP32B, APOL1, ARHGAP10, ARHGAP32, ARID3A, ASF1B, ASPH, ASRGL1, ATP10B, ATP9A, BCL2L15, BCL6, BST2, C20orf196, C3orf14, CA8, CAB39L, CACNAID, CCDC109B, CCNO, CDC42EP2, CDC42EP5, CDCA2, CDCA7, CDHR1, CEBPA, CENPE, CEP192, CKAP2, CPNE1, CREB3L1, CRYM, CSGALNACT2, CYTH3, DACT1, DAPK2, DEPDC1, DIDO1, DOCK5, DPM1, EIF6, ENO2, EPB41L4B, ERRFI1, ESRP1, FABP5, FAM105A, FAM122B, FAM3D, FAM84A, FARP1, FBXO34, FITM2, FOXA2, FRZB, FUT8, GALNT5, GALNT8, GFPT1, GGH, GNG4, GPCPD1, GPR143, GPR153, GRM8, GTF2A2, GUCY2C, GYG2, HEPH, HES2, HLA-E, HLX, HOXD11, HSPA4L, HSPA6, HUNK, IFIT3, ILDR1, IMMP2L, JADE3, KCNK1, KCTD1, KIF2C, KLK1, LDLRAD3, LEFTY1, LM04, LNX21, LRRC16A, MAGED1, MAP2K6, MAPRE1, MLLT3, MLPH, MPP1, MRAP2, MT2A, MYRIP, NCAPH, NDFIP2, NEDD9, NOL4L, NR112, NUCB2, OSTM1, PAK6, PALB2, PALLD, PBX1, PCMTD2, PCP4, PDP1, PDZD2, PDZKIIP1, PIGR, PIGU, PITX2, PLCB1, PLCH1, PNP, POLD3, POP1, PPPIR14C, PPP1R14D, PPP1R3D, PPP3CA, PRAP1, PRC1, PRDX5, PRLR, PRR15, RAPIGAP, RARRES3, RBMS1, RETNLB, RNF183, RNF43, SAMD5, SEMASA, SERPINB1, SESN1, SHROOM4, SLC25A37, SLC30A2, SLC4A11, SLC9A2, SLCO1B3, SLCO2B1, SOCS6, SPIRE2, SRPK1, ST6GALNAC1, STAT2, TC2N, TFAP2A, TMEM61, TMEM64, TNFRSF11A, TNNC2, TNS4, TOMM34, TRIM7, TRNP1, TSPAN6, UGT8, UPF3A, USP14, UTP15, WFDC2, XBP1, ZCCHC24, ZDHHC23, ZG16B, ZNF415, ZSCAN18, and ZWINT;
• (c) generating an expression profile based on a comparison between the expression level of the plurality of genes in the sample from the subject and a corresponding expression level obtained from a reference sample derived from a different subject having a known cancer status;
• and
• (d) categorizing the cancer status of the subject based on the expression profile;
• and
• (ii) administering an anti-cancer therapy to the subject based on the cancer status.