Colorectal Cancers

Overview

About 75% of patients with colorectal (CRC) have sporadic (not inherited) disease. The majority involve somatic mutations which result in chromosomal instability (CIN), whilst around a quarter have patterns of gene hypermethylation known as an CpG island methylator phenotype (CIMP), including many with microsatellite instability (MSI). There are a wide variety of genes that are involved in CRC, with tumors having an average of 9 mutated genes.

25% of patients have a family history of CRC. These include a sub-set of patients with defined genetic syndromes (see Predisposing Syndromes, below). The most frequent of these is Lynch Syndrome (also called Hereditary Non-Polyposis Colorectal Cancer) which accounts for approximately 5-8% of all colorectal cancers, and usually associated with germline mutations in mismatch repair genes including: MSH2, MSH6, MLH1, PMS1 and PMS2. There are a range of other syndromes, including Familial Adenomatous Polyposis (FAP), which is an autosomal dominant disorder causing extensive adenomatous polyps in the colon and early onset colorectal cancer. FAP accounts for about 1% of all colorectal cancers. The disorder is characterised by APC gene mutation. FAP is also assciated with elevated risk of extracolonic tumours.

See also: Colorectal (Bowel) Cancer - clinical resources (28)

Literature Analysis

Mouse over the terms for more detail; many indicate links which you can click for dedicated pages about the topic.

Tag cloud generated 29 August, 2019 using data from PubMed, MeSH and CancerIndex

Mutated Genes and Abnormal Protein Expression (543)

How to use this data tableClicking on the Gene or Topic will take you to a separate more detailed page. Sort this list by clicking on a column heading e.g. 'Gene' or 'Topic'.

GeneLocationAliasesNotesTopicPapers
APC 5q22.2 GS, DP2, DP3, BTPS2, DP2.5, PPP1R46 -APC and Colorectal Cancer
2495
KRAS 12p12.1 NS, NS3, CFC2, RALD, KRAS1, KRAS2, RASK2, KI-RAS, C-K-RAS, K-RAS2A, K-RAS2B, K-RAS4A, K-RAS4B, c-Ki-ras2 -KRAS and Colorectal Cancer
2138
BRAF 7q34 NS7, B-raf, BRAF1, RAFB1, B-RAF1 -BRAF and Colorectal Cancer
1606
MSH2 2p21 FCC1, COCA1, HNPCC, LCFS2, HNPCC1 -MSH2 and Colorectal Cancer
1442
CTNNB1 3p22.1 CTNNB, MRD19, armadillo -CTNNB1 and Colorectal Cancer
1209
MLH1 3p22.2 FCC2, COCA2, HNPCC, hMLH1, HNPCC2 Germline
-MLH1 and Lynch Syndrome
1208
EGFR 7p11.2 ERBB, HER1, mENA, ERBB1, PIG61, NISBD2 -EGFR and Colorectal Cancer
1032
PTGS2 1q31.1 COX2, COX-2, PHS-2, PGG/HS, PGHS-2, hCox-2, GRIPGHS -PTGS2 (COX2) and Colorectal Cancer
-COX2 Inhibitors for Colorectal Cancer
-COX2 Polymorphisms and Colorectal Cancer
437
TP53 17p13.1 P53, BCC7, LFS1, TRP53 -TP53 and Colorectal Cancer
640
MSH6 2p16 GTBP, HSAP, p160, GTMBP, HNPCC5 -MSH6 and Colorectal Cancer
499
PIK3CA 3q26.32 MCM, CWS5, MCAP, PI3K, CLOVE, MCMTC, PI3K-alpha, p110-alpha -PIK3CA and Colorectal Cancer
404
NRAS 1p13.2 NS6, CMNS, NCMS, ALPS4, N-ras, NRAS1 -NRAS and Colorectal Cancer
392
CDKN2A 9p21.3 ARF, MLM, P14, P16, P19, CMM2, INK4, MTS1, TP16, CDK4I, CDKN2, INK4A, MTS-1, P14ARF, P19ARF, P16INK4, P16INK4A, P16-INK4A -CDKN2A and Colorectal Cancer
377
CEACAM5 19q13.2 CEA, CD66e -CEACAM5 and Colorectal Cancer
375
DCC 18q21.2 CRC18, CRCR1, MRMV1, IGDCC1, NTN1R1 -DCC and Colorectal Cancer
285
MTHFR 1p36.22 -MTHFR mutations and polymorphisms and Colorectal Cancer
278
MUTYH 1p34.1 MYH -MUTYH and Colorectal Cancer
276
CDKN1A 6p21.2 P21, CIP1, SDI1, WAF1, CAP20, CDKN1, MDA-6, p21CIP1 Prognostic
-CDKN1A Expression in Colorectal Cancer
265
SMAD4 18q21.2 JIP, DPC4, MADH4, MYHRS -SMAD4 and Colorectal Cancer
219
MGMT 10q26.3 -MGMT and Colorectal Cancer
215
SRC 20q11.23 ASV, SRC1, THC6, c-SRC, p60-Src -SRC and Colorectal Cancer
175
MYC 8q24.21 MRTL, MYCC, c-Myc, bHLHe39 -MYC and Colorectal Cancer
170
TCF4 18q21.2 E2-2, ITF2, PTHS, SEF2, FECD3, ITF-2, SEF-2, TCF-4, SEF2-1, SEF2-1A, SEF2-1B, SEF2-1D, bHLHb19 -TCF4 and Colorectal Cancer
166
VEGFA 6p21.1 VPF, VEGF, MVCD1 -VEGFA and Colorectal Cancer
162
GSTM1 1p13.3 MU, H-B, GST1, GTH4, GTM1, MU-1, GSTM1-1, GSTM1a-1a, GSTM1b-1b -GSTM1 and Colorectal Cancer
159
PCNA 20p12.3 ATLD2 -PCNA and Colorectal Cancer
156
BRCA1 17q21.31 IRIS, PSCP, BRCAI, BRCC1, FANCS, PNCA4, RNF53, BROVCA1, PPP1R53 -BRCA1 germliine mutation and increased risk of Colorectal Cancer?
153
TGFBR2 3p24.1 AAT3, FAA3, LDS2, MFS2, RIIC, LDS1B, LDS2B, TAAD2, TGFR-2, TGFbeta-RII -TGFBR2 and Colorectal Cancer
148
BAX 19q13.33 BCL2L4 -BAX and Colonic Neoplasms
139
NODAL 10q22.1 HTX5 -NODAL and Colorectal Cancer
131
CDX2 13q12.2 CDX3, CDX-3, CDX2/AS -CDX2 and Colorectal Cancer
125
UGT1A1 2q37 GNT1, UGT1, UDPGT, UGT1A, HUG-BR1, BILIQTL1, UDPGT 1-1 -UGT1A1 and Colorectal Cancer
117
STAT3 17q21.2 APRF, HIES, ADMIO, ADMIO1 -STAT3 and Colorectal Cancer
115
IGF2 11p15.5 GRDF, IGF-II, PP9974, C11orf43 -IGF2 and Colorectal Cancer
112
MMP2 16q12.2 CLG4, MONA, CLG4A, MMP-2, TBE-1, MMP-II -MMP2 and Colorectal Cancer
112
TCF7L2 10q25.2-q25.3 TCF4, TCF-4 -TCF7L2 and Colorectal Cancer
108
S100A4 1q21.3 42A, 18A2, CAPL, FSP1, MTS1, P9KA, PEL98 -S100A4 and Colorectal Cancer
-S100A4 and Colorectal Cancer
83
XRCC1 19q13.31 RCC -XRCC1 and Colorectal Cancer
104
NAT2 8p22 AAC2, PNAT, NAT-2 -NAT2 and Colorectal Cancer
102
MIR21 17q23.1 MIRN21, miR-21, miRNA21, hsa-mir-21 -MicroRNA miR-21 and Colorectal Cancer
102
CDH1 16q22.1 UVO, CDHE, ECAD, LCAM, Arc-1, CD324 -CDH1 and Colorectal Cancer
100
GSTT1 22q11.23 -GSTT1 and Colorectal Cancer
100
RUNX3 1p36.11 AML2, CBFA3, PEBP2aC -RUNX3 and Colorectal Cancer
99
MSH3 5q14.1 DUP, FAP4, MRP1 -MSH3 and Colorectal Cancer
98
MET 7q31.2 HGFR, AUTS9, RCCP2, c-Met, DFNB97 -C-MET and Colorectal Cancer
95
MCC 5q22.2 MCC1 -MCC and Colorectal Cancer
94
MUC1 1q22 EMA, MCD, PEM, PUM, KL-6, MAM6, MCKD, PEMT, CD227, H23AG, MCKD1, MUC-1, ADMCKD, ADMCKD1, CA 15-3, MUC-1/X, MUC1/ZD, MUC-1/SEC Prognostic
-MUC1 and Colorectal Cancer
93
MUC2 11p15.5 MLP, SMUC, MUC-2 -MUC2 and Colorectal Cancer
88
CDKN1B 12p13.1 KIP1, MEN4, CDKN4, MEN1B, P27KIP1 Prognostic
-CDKN1B and Colorectal Cancer
75
CHEK2 22q12.1 CDS1, CHK2, LFS2, RAD53, hCds1, HuCds1, PP1425 -CHEK2 and Colorectal Cancer
74
SMAD2 18q21.1 JV18, MADH2, MADR2, JV18-1, hMAD-2, hSMAD2 -SMAD2 and Colorectal Cancer
72
DPYD 1p21.3 DHP, DPD, DHPDHASE -DPYD and Colorectal Cancer
71
TGFBR1 9q22.33 AAT5, ALK5, ESS1, LDS1, MSSE, SKR4, ALK-5, LDS1A, LDS2A, TGFR-1, ACVRLK4, tbetaR-I -TGFBR1 and Colorectal Cancer
68
DNMT3B 20q11.21 ICF, ICF1, M.HsaIIIB -DNMT3B and Colorectal Cancer
63
DNMT1 19p13.2 AIM, DNMT, MCMT, CXXC9, HSN1E, ADCADN, m.HsaI -DNMT1 and Colorectal Cancer
60
PMS1 2q31.1 MLH2, PMSL1, hPMS1, HNPCC3 -PMS1 and Colorectal Cancer
60
ERCC2 19q13.32 EM9, TTD, XPD, TTD1, COFS2, TFIIH -ERCC2 and Colorectal Cancer
57
ABCC1 16p13.11 MRP, ABCC, GS-X, MRP1, ABC29 -ABCC1 (MRP1) and Colorectal Cancer
57
FOXP3 Xp11.23 JM2, AIID, IPEX, PIDX, XPID, DIETER -FOXP3 and Colorectal Cancer
57
TGFA 2p13 TFGA -TGFA and Colonic Neoplasms
56
IGFBP3 7p12.3 IBP3, BP-53 -IGFBP3 and Colorectal Cancer
55
FOS 14q24.3 p55, AP-1, C-FOS -FOS and Colonic Neoplasms
55
CACNA1G 17q21.33 NBR13, SCA42, Cav3.1, Ca(V)T.1 -CACNA1G and Colorectal Cancer
54
AXIN2 17q24.1 AXIL, ODCRCS -AXIN2 and Colorectal Cancer
53
SOCS1 16p13.13 JAB, CIS1, SSI1, TIP3, CISH1, SSI-1, SOCS-1 -SOCS1 and Colorectal Cancer
53
TYMS 18p11.32 TS, TMS, HST422 -TYMS and Colorectal Cancer
52
NEUROG1 5q31.1 AKA, ngn1, Math4C, bHLHa6, NEUROD3 -NEUROG1 and Colorectal Cancer
51
SMAD7 18q21.1 CRCS3, MADH7, MADH8 -SMAD7 and Colorectal Cancer
47
BMPR1A 10q23.2 ALK3, SKR5, CD292, ACVRLK3, 10q23del -BMPR1A and Colorectal Cancer
47
EPCAM 2p21 ESA, KSA, M4S1, MK-1, DIAR5, EGP-2, EGP40, KS1/4, MIC18, TROP1, EGP314, HNPCC8, TACSTD1 -EPCAM and Colorectal Cancer
46
SFRP1 8p11.21 FRP, FRP1, FrzA, FRP-1, SARP2 -SFRP1 and Colorectal Cancer
46
MMP7 11q22.2 MMP-7, MPSL1, PUMP-1 -MMP7 and Colorectal Cancer
45
NAT1 8p22 AAC1, MNAT, NATI, NAT-1 -NAT1 and Colorectal Cancer
45
RAC1 7p22.1 MIG5, Rac-1, TC-25, p21-Rac1 -RAC1 and Colorectal Cancer
44
FBXW7 4q31.3 AGO, CDC4, FBW6, FBW7, hAgo, FBX30, FBXW6, SEL10, hCdc4, FBXO30, SEL-10 -FBXW7 and Colorectal Cancer
43
LGR5 12q22-q23 FEX, HG38, GPR49, GPR67, GRP49 -LGR5 and Colorectal Cancer
43
SFRP2 4q31.3 FRP-2, SARP1, SDF-5 -SFRP2 and Colorectal Cancer
43
OGG1 3p25.3 HMMH, MUTM, OGH1, HOGG1 -OGG1 and Colorectal Cancer
42
TGFB1 19q13.2 CED, LAP, DPD1, TGFB, TGFbeta -TGFB1 and Colorectal Cancer
42
XRCC3 14q32.33 CMM6 -XRCC3 and Colorectal Cancer
41
GAPDH 12p13.31 G3PD, GAPD, HEL-S-162eP -GAPDH and Colorectal Cancer
40
FLT1 13q12.3 FLT, FLT-1, VEGFR1, VEGFR-1 -FLT1 and Colorectal Cancer
40
KRT20 17q21.2 K20, CD20, CK20, CK-20, KRT21 -KRT20 and Colorectal Cancer
40
CRABP1 15q25.1 RBP5, CRABP, CRABPI, CRABP-I -CRABP1 and Colorectal Cancer
38
ESR1 6q25.1-q25.2 ER, ESR, Era, ESRA, ESTRR, NR3A1 -ESR1 and Colorectal Cancer
38
NQO1 16q22.1 DTD, QR1, DHQU, DIA4, NMOR1, NMORI -NQO1 and Colorectal Cancer
38
PPARD 6p21.31 FAAR, NUC1, NUCI, NR1C2, NUCII, PPARB -PPAR delta and Colorectal Cancer
37
LOX 5q23.1 AAT10 -LOX and Colorectal Cancer
37
THBS1 15q14 TSP, THBS, TSP1, TSP-1, THBS-1 -THBS1 and Colorectal Cancer
35
TWIST1 7p21.1 CRS, CSO, SCS, ACS3, CRS1, BPES2, BPES3, TWIST, bHLHa38 -TWIST1 and Colorectal Cancer
35
EPHB2 1p36.12 DRT, EK5, ERK, CAPB, Hek5, PCBC, EPHT3, Tyro5, BDPLT22 -EPHB2 and Colorectal Cancer
35
MUC5AC 11p15.5 TBM, leB, MUC5, mucin -MUC5AC and Colorectal Cancer
34
XIAP Xq25 API3, ILP1, MIHA, XLP2, BIRC4, IAP-3, hIAP3, hIAP-3 -XIAP and Colonic Neoplasms
34
CYP1A2 15q24.1 CP12, P3-450, P450(PA) -CYP1A2 and Colorectal Cancer
34
PTGS1 9q33.2 COX1, COX3, PHS1, PCOX1, PES-1, PGHS1, PTGHS, PGG/HS, PGHS-1 -PTGS1 and Colorectal Cancer
34
CHFR 12q24.33 RNF116, RNF196 -CHFR and Colorectal Cancer
33
WNT3A 1q42.13 -WNT3A and Colorectal Cancer
32
POLE 12q24.3 FILS, POLE1, CRCS12 -POLE and Colorectal Cancer
32
EPHX1 1q42.12 MEH, EPHX, EPOX, HYL1 -EPHX1 and Colorectal Cancer
31
MLH3 14q24.3 HNPCC7 -MLH3 and Colorectal Cancer
31
TLR4 9q33.1 TOLL, CD284, TLR-4, ARMD10 -TLR4 and Colorectal Cancer
31
SEPT9 17q25.3 MSF, MSF1, NAPB, SINT1, PNUTL4, SeptD1, AF17q25 -SEPT9 and Colorectal Cancer
30
ALDH2 12q24.12 ALDM, ALDHI, ALDH-E2 -ALDH2 and Colorectal Cancer
30
MIR126 9q34.3 MIRN126, mir-126, miRNA126 -MicroRNA mir-126 and Colorectal Cancer
29
TIAM1 21q22.11 TIAM-1 -TIAM1 and Colorectal Cancer
29
CDC42 1p36.12 TKS, G25K, CDC42Hs -CDC42 and Colorectal Cancer
29
SOX10 22q13.1 DOM, WS4, PCWH, WS2E, WS4C -SOX10 and Colorectal Cancer
29
EXO1 1q43 HEX1, hExoI -EXO1 and Colorectal Cancer
29
BMP4 14q22.2 ZYME, BMP2B, OFC11, BMP2B1, MCOPS6 -BMP4 and Colorectal Cancer
29
CRP 1q23.2 PTX1 -CRP and Colorectal Cancer
28
AREG 4q13.3 AR, SDGF, AREGB, CRDGF -AREG and Colorectal Cancer
28
NOS2 17q11.2 NOS, INOS, NOS2A, HEP-NOS -NOS2 and Colorectal Cancer
28
TIMP3 22q12.3 SFD, K222, K222TA2, HSMRK222 -TIMP3 and Colorectal Cancer
27
IGF1 12q23.2 IGFI, IGF-I, IGF1A -IGF1 and Colorectal Cancer
27
PTP4A3 8q24.3 PRL3, PRL-3, PRL-R -PTP4A3 and Colorectal Cancer
27
CYP2C9 10q23.33 CPC9, CYP2C, CYP2C10, CYPIIC9, P450IIC9 -CYP2C9 and Colorectal Cancer
26
ATF3 1q32.3 -ATF3 and Colorectal Cancer
26
WIF1 12q14.3 WIF-1 -WIF1 and Colorectal Cancer
26
CDX1 5q32 -CDX1 and Colorectal Cancer
26
HIC1 17p13.3 hic-1, ZBTB29, ZNF901 -HIC1 and Colorectal Cancer
26
RAD50 5q31.1 NBSLD, RAD502, hRad50 -RAD50 and Colorectal Cancer
25
IL17C 16q24.2 CX2, IL-17C -IL17C and Colorectal Cancer
25
CLOCK 4q12 KAT13D, bHLHe8 -CLOCK and Colorectal Cancer
25
ZEB1 10p11.22 BZP, TCF8, AREB6, FECD6, NIL2A, PPCD3, ZFHEP, ZFHX1A, DELTAEF1 -ZEB1 and Colonic Neoplasms
23
SOX9 17q24.3 CMD1, SRA1, CMPD1, SRXX2, SRXY10 -SOX9 and Colorectal Cancer
23
BMP2 20p12.3 BDA2, BMP2A, SSFSC -BMP2 and Colorectal Cancer
23
IRS1 2q36 HIRS-1 -IRS1 and Colorectal Cancer
23
CLDN1 3q28-q29 CLD1, SEMP1, ILVASC -CLDN1 and Colorectal Cancer
23
MRE11 11q21 ATLD, HNGS1, MRE11A, MRE11B -MRE11A and Colorectal Cancer
23
MACC1 7p21.1 7A5, SH3BP4L -MACC1 and Colorectal Cancer
23
PPARG 3p25.2 GLM1, CIMT1, NR1C3, PPARG1, PPARG2, PPARgamma -PPARG and Colorectal Cancer
23
CCK 3p22.1 -CCK and Colonic Neoplasms
22
NOD2 16q12.1 CD, ACUG, BLAU, IBD1, YAOS, BLAUS, NLRC2, NOD2B, CARD15, CLR16.3, PSORAS1 -NOD2 and Colorectal Cancer
22
POLD1 19q13.33 CDC2, MDPL, POLD, CRCS10 -POLD1 and Colorectal Cancer
22
CHEK1 11q24.2 CHK1 -CHEK1 and Colorectal Cancer
22
SMO 7q32.1 Gx, CRJS, SMOH, FZD11 -SMO and Colorectal Cancer
22
MTRR 5p15.31 MSR, cblE -MTRR and Colorectal Cancer
22
LEF1 4q25 LEF-1, TCF10, TCF7L3, TCF1ALPHA -LEF1 and Colonic Neoplasms
21
ABCC2 10q24.2 DJS, MRP2, cMRP, ABC30, CMOAT -ABCC2 and Colorectal Cancer
20
EREG 4q13.3 ER, Ep, EPR -EREG and Colorectal Cancer
20
GREM1 15q13.3 DRM, HMPS, MPSH, PIG2, CRAC1, CRCS4, DAND2, HMPS1, IHG-2, DUP15q, C15DUPq, GREMLIN, CKTSF1B1 -GREM1 and Colorectal Cancer
20
E2F4 16q22.1 E2F-4 -E2F4 and Colorectal Cancer
20
HMGB1 13q12.3 HMG1, HMG3, HMG-1, SBP-1 -HMGB1 and Colorectal Cancer
19
IRS2 13q34 IRS-2 -IRS2 and Colorectal Cancer
19
AXIN1 16p13.3 AXIN, PPP1R49 -AXIN1 and Colorectal Cancer
19
NFKB1 4q24 p50, KBF1, p105, EBP-1, CVID12, NF-kB1, NFKB-p50, NFkappaB, NF-kappaB, NFKB-p105, NF-kappa-B -NFKB1 and Colorectal Cancer
19
FCGR3A 1q23.3 CD16, FCG3, CD16A, FCGR3, IGFR3, IMD20, FCR-10, FCRIII, FCGRIII, FCRIIIA -FCGR3A and Colorectal Cancer
19
MAP2K1 15q22.31 CFC3, MEK1, MKK1, MAPKK1, PRKMK1 -MAP2K1 and Colorectal Cancer
19
CXCL1 4q13.3 FSP, GRO1, GROa, MGSA, NAP-3, SCYB1, MGSA-a -CXCL1 and Colonic Neoplasms
19
HLTF 3q25.1-q26.1 ZBU1, HLTF1, RNF80, HIP116, SNF2L3, HIP116A, SMARCA3 -HLTF and Colorectal Cancer
19
SNAI1 20q13.13 SNA, SNAH, SNAIL, SLUGH2, SNAIL1, dJ710H13.1 -SNAI1 and Colonic Neoplasms
18
WRN 8p12 RECQ3, RECQL2, RECQL3 -WRN and Colorectal Cancer
18
BNIP3 10q26.3 NIP3 -BNIP3 and Colorectal Cancer
18
MIRLET7B 22q13.31 LET7B, let-7b, MIRNLET7B, hsa-let-7b -MicroRNA let-7b and Colorectal Cancer
18
BUB1 2q14 BUB1A, BUB1L, hBUB1 -BUB1 and Colorectal Cancer
18
HFE 6p22.2 HH, HFE1, HLA-H, MVCD7, TFQTL2 -HFE and Colorectal Cancer
18
KLF4 9q31.2 EZF, GKLF -KLF4 and Colonic Neoplasms
18
NFKBIA 14q13.2 IKBA, MAD-3, NFKBI -NFKBIA and Colorectal Cancer
18
LGALS1 22q13.1 GBP, GAL1 -LGALS1 and Colorectal Cancer
17
MBD4 3q21.3 MED1 -MBD4 and Colorectal Cancer
17
CDH13 16q23.3 CDHH, P105 -CDH13 and Colorectal Cancer
17
ALOX15 17p13.2 12-LOX, 15LOX-1, 15-LOX-1 -ALOX15 and Colorectal Cancer
17
ARHGEF1 19q13.2 LSC, GEF1, LBCL2, SUB1.5, P115-RHOGEF -ARHGEF1 and Colorectal Cancer
17
FASN 17q25.3 FAS, OA-519, SDR27X1 -FASN and Colorectal Cancer
17
TMEFF2 2q32.3 TR, HPP1, TPEF, TR-2, TENB2, CT120.2 -TMEFF2 and Colorectal Cancer
16
IGFBP7 4q12 AGM, PSF, TAF, FSTL2, IBP-7, MAC25, IGFBP-7, RAMSVPS, IGFBP-7v, IGFBPRP1 -IGFBP7 and Colorectal Cancer
16
CHIA 1p13.2 CHIT2, AMCASE, TSA1902 -CHIA and Colorectal Cancer
16
BAG1 9p13.3 HAP, BAG-1, RAP46 Overexpression
Prognostic
-BAG1 overexpression in Colorectal Cancer
16
ADIPOQ 3q27 ACDC, ADPN, APM1, APM-1, GBP28, ACRP30, ADIPQTL1 -ADIPOQ and Colorectal Cancer
16
GDF15 19p13.11 PDF, MIC1, PLAB, MIC-1, NAG-1, PTGFB, GDF-15 -GDF15 and Colorectal Cancer
16
CASR 3q13 CAR, FHH, FIH, HHC, EIG8, HHC1, NSHPT, PCAR1, GPRC2A, HYPOC1 -CASR and Colorectal Cancer
16
ESR2 14q23.2-q23.3 Erb, ESRB, ESTRB, NR3A2, ER-BETA, ESR-BETA -ESR2 and Colorectal Cancer
15
PHIP 6q14.1 ndrp, BRWD2, WDR11, DCAF14 -PHIP and Colonic Neoplasms
15
APOE 19q13.32 AD2, LPG, APO-E, ApoE4, LDLCQ5 -APOE and Colorectal Cancer
15
CCNA2 4q27 CCN1, CCNA -CCNA2 and Colorectal Cancer
15
GSTA1 6p12.2 GST2, GTH1, GSTA1-1, GST-epsilon -GSTA1 and Colorectal Cancer
15
CXCL2 4q13.3 GRO2, GROb, MIP2, MIP2A, SCYB2, MGSA-b, MIP-2a, CINC-2a -CXCL2 and Colorectal Cancer
15
PAK1 11q13.5-q14.1 PAKalpha -PAK1 and Colorectal Cancer
15
REG4 1p12 GISP, RELP, REG-IV -REG4 and Colorectal Cancer
14
ALCAM 3q13.1 MEMD, CD166 -ALCAM and Colorectal Cancer
14
DKK1 10q21.1 SK, DKK-1 -DKK1 and Colonic Neoplasms
14
VIP 6q25.2 PHM27 -VIP and Colorectal Cancer
14
TCF3 19p13.3 E2A, E47, AGM8, ITF1, VDIR, TCF-3, bHLHb21 -TCF3 and Colorectal Cancer
14
PLAUR 19q13.31 CD87, UPAR, URKR, U-PAR -PLAUR and Colonic Neoplasms
14
ADH1B 4q23 ADH2, HEL-S-117 -ADH1B and Colorectal Cancer
14
MED1 17q12 PBP, CRSP1, RB18A, TRIP2, PPARBP, CRSP200, DRIP205, DRIP230, PPARGBP, TRAP220 -MED1 and Colorectal Cancer
14
IL4 5q31.1 BSF1, IL-4, BCGF1, BSF-1, BCGF-1 -IL4 and Colorectal Cancer
14
WNT2 7q31.2 IRP, INT1L1 -WNT2 and Colorectal Cancer
13
VIM 10p13 HEL113, CTRCT30 -VIM and Colorectal Cancer
13
TOP1 20q12 TOPI -TOP1 and Colonic Neoplasms
13
YES1 18p11.32 Yes, c-yes, HsT441, P61-YES -Proto-Oncogene Proteins c-yes and Colonic Neoplasms
13
TAP1 6p21.32 APT1, PSF1, ABC17, ABCB2, PSF-1, RING4, TAP1N, D6S114E, TAP1*0102N -TAP1 and Colorectal Cancer
13
TACSTD2 1p32.1 EGP1, GP50, M1S1, EGP-1, TROP2, GA7331, GA733-1 -TACSTD2 and Colorectal Cancer
13
ADIPOR1 1q32.1 CGI45, PAQR1, ACDCR1, CGI-45, TESBP1A -ADIPOR1 and Colorectal Cancer
13
FCGR2A 1q23.3 CD32, FCG2, FcGR, CD32A, CDw32, FCGR2, IGFR2, FCGR2A1 -FCGR2A and Colorectal Cancer
13
CYP24A1 20q13.2 CP24, HCAI, CYP24, HCINF1, P450-CC24 -CYP24A1 and Colonic Neoplasms
13
KLF5 13q22.1 CKLF, IKLF, BTEB2 -KLF5 and Colorectal Cancer
13
PLA2G4A 1q31.1 GURDP, cPLA2, PLA2G4, cPLA2-alpha -PLA2G4A and Colorectal Cancer
12
KISS1 1q32.1 HH13, KiSS-1 -KISS1 and Colorectal Cancer
12
INSR 19p13.2 HHF5, CD220 -INSR and Colorectal Cancer
12
XRCC2 7q36.1 FANCU -XRCC2 and Colorectal Cancer
12
APAF1 12q23.1 CED4, APAF-1 -APAF1 and Colorectal Cancer
12
RASSF2 20p13 CENP-34, RASFADIN -RASSF2 and Colorectal Cancer
12
PRINS 10p12.1 NCRNA00074 -PRINS and Colorectal Cancer
12
PLA2G2A 1p36.13 MOM1, PLA2, PLA2B, PLA2L, PLA2S, PLAS1, sPLA2 -PLA2G2A and Colorectal Cancer
12
BCL9 1q21.2 LGS -BCL9 and Colorectal Cancer
12
TNFRSF10A 8p21.3 DR4, APO2, CD261, TRAILR1, TRAILR-1 -TNFRSF10A and Colorectal Cancer
12
STAR 8p11.23 STARD1 -STAR and Colorectal Cancer
12
FPGS 9q34.11 -FPGS and Colorectal Cancer
12
TLR2 4q31.3 TIL4, CD282 -TLR2 and Colorectal Cancer
12
B2M 15q21.1 IMD43 -B2M and Colorectal Cancer
12
AIM2 1q23.1-q23.2 PYHIN4 -AIM2 and Colorectal Cancer
11
SLCO1B1 12p12.1 LST1, HBLRR, LST-1, OATP2, OATPC, OATP-C, OATP1B1, SLC21A6 -SLCO1B1 and Colorectal Cancer
11
LIF 22q12.2 CDF, DIA, HILDA, MLPLI -LIF and Colorectal Cancer
11
CTNNA1 5q31.2 MDPT2, CAP102 -CTNNA1 and Colonic Neoplasms
11
PTPRJ 11p11.2 DEP1, SCC1, CD148, HPTPeta, R-PTP-ETA -PTPRJ and Colorectal Cancer
11
BLM 15q26.1 BS, RECQ2, RECQL2, RECQL3 -BLM and Colorectal Cancer
11
ZNF217 20q13.2 ZABC1 -ZNF217 and Colorectal Cancer
11
PTPN13 4q21.3 PNP1, FAP-1, PTP1E, PTPL1, PTPLE, PTP-BL, hPTP1E, PTP-BAS -PTPN13 and Colorectal Cancer
11
LAMC2 1q25.3 B2T, CSF, EBR2, BM600, EBR2A, LAMB2T, LAMNB2 -LAMC2 and Colorectal Cancer
11
ALOX5 10q11.21 5-LO, 5LPG, LOG5, 5-LOX -ALOX5 and Colorectal Cancer
10
WNT5A 3p14.3 hWNT5A -WNT5A and Colonic Neoplasms
10
YY1AP1 1q22 GRNG, HCCA1, HCCA2, YY1AP -YY1AP1 and Colorectal Cancer
10
XAF1 17p13.1 BIRC4BP, XIAPAF1, HSXIAPAF1 -XAF1 and Colonic Neoplasms
10
CEACAM1 19q13.2 BGP, BGP1, BGPI -CEACAM1 and Colorectal Cancer
10
SFRP4 7p14.1 PYL, FRP-4, FRPHE, sFRP-4 -SFRP4 and Colorectal Cancer
10
DUSP4 8p12 TYP, HVH2, MKP2, MKP-2 -DUSP4 and Colorectal Cancer
10
IL23R 1p31.3 -IL23R and Colorectal Cancer
10
TAP2 6p21.32 APT2, PSF2, ABC18, ABCB3, PSF-2, RING11, D6S217E -TAP2 and Colorectal Cancer
10
VCAN 5q14.2-q14.3 WGN, ERVR, GHAP, PG-M, WGN1, CSPG2 -VCAN and Colorectal Cancer
10
PTPRQ 12q21.2 DFNB84, DFNB84A, PTPGMC1, R-PTP-Q -PTPRQ and Colorectal Cancer
10
XIST Xq13.2 SXI1, swd66, DXS1089, DXS399E, LINC00001, NCRNA00001 -XIST and Colorectal Cancer
10
FOSL1 11q13.1 FRA, FRA1, fra-1 -FOSL1 and Colon Cancer
10
PRDM2 1p36.21 RIZ, KMT8, RIZ1, RIZ2, KMT8A, MTB-ZF, HUMHOXY1 -PRDM2 and Colorectal Cancer
10
ROCK1 18q11.1 ROCK-I, P160ROCK -ROCK1 and Colorectal Cancer
9
POLB 8p11.21 -POLB and Colorectal Cancer
9
MYOD1 11p15.1 PUM, MYF3, MYOD, bHLHc1 -MYOD1 and Colorectal Cancer
9
ITGB3 17q21.32 GT, CD61, GP3A, BDPLT2, GPIIIa, BDPLT16 -ITGB3 and Colorectal Cancer
9
PTPRC 1q31.3-q32.1 LCA, LY5, B220, CD45, L-CA, T200, CD45R, GP180 -PTPRC and Colorectal Cancer
9
TAGLN 11q23.3 SM22, SMCC, TAGLN1, WS3-10 -TAGLN and Colorectal Cancer
9
GZMB 14q12 C11, HLP, CCPI, CGL1, CSPB, SECT, CGL-1, CSP-B, CTLA1, CTSGL1 -GZMB and Colorectal Cancer
9
LMNA 1q22 FPL, IDC, LFP, CDDC, EMD2, FPLD, HGPS, LDP1, LMN1, LMNC, MADA, PRO1, CDCD1, CMD1A, FPLD2, LMNL1, CMT2B1, LGMD1B -LMNA and Colorectal Cancer
9
EPHB4 7q22.1 HTK, MYK1, HFASD, TYRO11 -EPHB4 and Colorectal Cancer
9
AKAP12 6q25.1 SSeCKS, AKAP250 -AKAP12 and Colorectal Cancer
9
ERCC5 13q33.1 XPG, UVDR, XPGC, COFS3, ERCM2, ERCC5-201 -ERCC5 and Colorectal Cancer
9
PER3 1p36.23 GIG13, FASPS3 -PER3 and Colorectal Cancer
9
AGR2 7p21.1 AG2, AG-2, HPC8, GOB-4, HAG-2, XAG-2, PDIA17, HEL-S-116 -AGR2 and Colorectal Cancer
9
FEN1 11q12.2 MF1, RAD2, FEN-1 -FEN1 and Colorectal Cancer
9
UCHL1 4p13 NDGOA, PARK5, PGP95, SPG79, PGP9.5, Uch-L1, HEL-117, PGP 9.5, HEL-S-53 -UCHL1 and Colorectal Cancer
9
SLIT2 4p15.31 SLIL3, Slit-2 -SLIT2 and Colorectal Cancer
9
TFPI2 7q21.3 PP5, REF1, TFPI-2 -TFPI2 and Colorectal Cancer
9
IL17A 6p12.2 IL17, CTLA8, IL-17, CTLA-8, IL-17A -IL17A and Colorectal Cancer
9
REG1A 2p12 P19, PSP, PTP, REG, ICRF, PSPS, PSPS1 -REG1A and Colorectal Cancer
9
CYP2A6 19q13.2 CPA6, CYP2A, CYP2A3, P450PB, CYPIIA6, P450C2A -CYP2A6 and Colorectal Cancer
9
PSMD10 Xq22.3 p28, p28(GANK), dJ889N15.2 -PSMD10 and Colorectal Cancer
9
UBE2C 20q13.12 UBCH10, dJ447F3.2 -UBE2C and Colorectal Cancer
9
PER1 17p13.1 PER, hPER, RIGUI -PER1 and Colorectal Cancer
8
NDRG2 14q11.2 SYLD -NDRG2 and Colorectal Cancer
8
TOP2A 17q21.2 TOP2, TP2A -TOP2A Expression in Colorectal Cancer
8
PER2 2q37.3 FASPS, FASPS1 -PER2 and Colorectal Cancer
8
PTGER4 5p13.1 EP4, EP4R -PTGER4 and Colorectal Cancer
8
TCF7 5q31.1 TCF-1 -TCF7 and Colorectal Cancer
8
CSK 15q24.1 -CSK and Colonic Neoplasms
8
EPHB3 3q27.1 EK2, ETK2, HEK2, TYRO6 -EPHB3 and Colorectal Cancer
8
SFRP5 10q24.2 SARP3 -SFRP5 and Colonic Neoplasms
8
KRT7 12q13.13 K7, CK7, SCL, K2C7 -KRT7 and Colorectal Cancer
8
PTGER2 14q22.1 EP2 -PTGER2 and Colorectal Cancer
8
MTSS1 8q24.13 MIM, MIMA, MIMB -MTSS1 and Colorectal Cancer
8
BACH1 21q21.3 BACH-1, BTBD24 -BACH1 and Colorectal Cancer
8
NOX1 Xq22.1 MOX1, NOH1, NOH-1, GP91-2 -NOX1 and Colonic Neoplasms
8
CSE1L 20q13.13 CAS, CSE1, XPO2 -CSE1L and Colorectal Cancer
8
ERCC6 10q11.23 CSB, CKN2, COFS, ARMD5, COFS1, POF11, RAD26, UVSS1 -ERCC6 and Colorectal Cancer
8
FSCN1 7p22.1 HSN, SNL, p55, FAN1 -FSCN1 and Colorectal Cancer
8
NDRG1 8q24.22 GC4, RTP, DRG1, NDR1, NMSL, TDD5, CAP43, CMT4D, DRG-1, HMSNL, RIT42, TARG1, PROXY1 -NDRG1 and Colorectal Cancer
8
OLFM4 13q14.3 GC1, OLM4, OlfD, GW112, hGC-1, hOLfD, UNQ362, bA209J19.1 -OLFM4 and Colorectal Cancer
8
SALL4 20q13.2 DRRS, HSAL4, ZNF797 -SALL4 and Colorectal Cancer
8
CCL20 2q36.3 CKb4, LARC, ST38, MIP3A, Exodus, MIP-3a, SCYA20, MIP-3-alpha -CCL20 and Colorectal Cancer
8
FZD7 2q33 FzE3 -FZD7 and Colorectal Cancer
8
CXCR2 2q35 CD182, IL8R2, IL8RA, IL8RB, CMKAR2, CDw128b -CXCR2 and Colonic Neoplasms
8
S100P 4p16.1 MIG9 -S100P and Colonic Neoplasms
8
CFTR 7q31.2 CF, MRP7, ABC35, ABCC7, CFTR/MRP, TNR-CFTR, dJ760C5.1 -CFTR and Colonic Neoplasms
8
GLI3 7p14.1 PHS, ACLS, GCPS, PAPA, PAPB, PAP-A, PAPA1, PPDIV, GLI3FL, GLI3-190 -GLI3 and Colorectal Cancer
8
HPGD 4q34.1 PGDH, PGDH1, PHOAR1, 15-PGDH, SDR36C1 -HPGD and Colorectal Cancer
8
RRM2 2p25-p24 R2, RR2, RR2M -RRM2 and Colorectal Cancer
7
SLC5A8 12q23.1-q23.2 AIT, SMCT, SMCT1 -SLC5A8 and Colonic Neoplasms
7
NR4A2 2q22-q23 NOT, RNR1, HZF-3, NURR1, TINUR -NR4A2 and Colorectal Cancer
7
PLCE1 10q23.33 PLCE, PPLC, NPHS3 -PLCE1 and Colorectal Cancer
7
NR4A1 12q13 HMR, N10, TR3, NP10, GFRP1, NAK-1, NGFIB, NUR77 -NR4A1 and Colonic Neoplasms
7
MIR1290 1p36.13 MIRN1290, hsa-mir-1290 -MIRN1290 microRNA, human and Colorectal Cancer
7
STAT6 12q13.3 STAT6B, STAT6C, D12S1644, IL-4-STAT -STAT6 and Colonic Neoplasms
7
HDAC3 5q31.3 HD3, RPD3, RPD3-2 -HDAC3 and Colonic Neoplasms
7
ADH1C 4q23 ADH3 -ADH1C and Colorectal Cancer
7
ATG5 6q21 ASP, APG5, APG5L, hAPG5, APG5-LIKE -ATG5 and Colorectal Cancer
7
SMAD5 5q31.1 DWFC, JV5-1, MADH5 -SMAD5 and Colorectal Cancer
7
OSCAR 19q13.42 PIGR3, PIgR-3 -OSCAR and Colorectal Cancer
7
ATOH1 4q22.2 ATH1, HATH1, MATH-1, bHLHa14 -ATOH1 and Colonic Neoplasms
7
PTPRT 20q12-q13.11 RPTPrho -PTPRT and Colorectal Cancer
7
GATA4 8p23.1 TOF, ASD2, VSD1, TACHD -GATA4 and Colorectal Cancer
7
ACTB 7p22.1 BRWS1, PS1TP5BP1 -ACTB and Colorectal Cancer
7
HNF4A 20q13.12 TCF, HNF4, MODY, FRTS4, MODY1, NR2A1, TCF14, HNF4a7, HNF4a8, HNF4a9, NR2A21, HNF4alpha -HNF4A and Colonic Neoplasms
7
PEBP1 12q24.23 PBP, HCNP, PEBP, RKIP, HCNPpp, PEBP-1, HEL-210, HEL-S-34 -PEBP1 and Colorectal Cancer
7
RALA 7p14.1 RAL -RALA and Colorectal Cancer
7
TNFRSF10B 8p21.3 DR5, CD262, KILLER, TRICK2, TRICKB, ZTNFR9, TRAILR2, TRICK2A, TRICK2B, TRAIL-R2, KILLER/DR5 -TNFRSF10B and Colonic Neoplasms
7
HIPK2 7q34 PRO0593 -HIPK2 and Colorectal Cancer
7
CDH3 16q22.1 CDHP, HJMD, PCAD -CDH3 and Colorectal Cancer
7
SLCO1B3 12p12.2 LST3, HBLRR, LST-2, OATP8, OATP-8, OATP1B3, SLC21A8, LST-3TM13 -SLCO1B3 and Colorectal Cancer
7
CEACAM6 19q13.2 NCA, CEAL, CD66c -CEACAM6 and Colorectal Cancer
7
CD1A 1q23.1 R4, T6, CD1, FCB6, HTA1 -CD1A and Colorectal Cancer
7
MTHFD1 14q23.3 MTHFC, MTHFD -MTHFD1 and Colorectal Cancer
7
BCL2L2 14q11.2 BCLW, BCL-W, PPP1R51, BCL2-L-2 -BCL2L2 and Colorectal Cancer
7
TNFSF13 17p13.1 APRIL, CD256, TALL2, ZTNF2, TALL-2, TNLG7B, TRDL-1, UNQ383/PRO715 -TNFSF13 and Colorectal Cancer
7
RFC1 4p14 A1, RFC, PO-GA, RECC1, MHCBFB, RFC140 -RFC1 and Colorectal Cancer
7
PPARGC1A 4p15.2 LEM6, PGC1, PGC1A, PGC-1v, PPARGC1, PGC-1alpha, PGC-1(alpha) -PPARGC1A and Colorectal Cancer
7
APCS 1q23.2 SAP, PTX2, HEL-S-92n -APCS and Colorectal Cancer
7
ADAMTS1 21q21.3 C3-C5, METH1 -ADAMTS1 and Colorectal Cancer
6
FLT4 5q35.3 PCL, FLT-4, FLT41, LMPH1A, VEGFR3, VEGFR-3 -FLT4 and Colorectal Cancer
6
TJP1 15q13.1 ZO-1 -TJP1 and Colorectal Cancer
6
MAPK14 6p21.31 RK, p38, CSBP, EXIP, Mxi2, CSBP1, CSBP2, CSPB1, PRKM14, PRKM15, SAPK2A, p38ALPHA -MAPK14 and Colonic Neoplasms
6
CYP27B1 12q14.1 VDR, CP2B, CYP1, PDDR, VDD1, VDDR, VDDRI, CYP27B, P450c1, CYP1alpha -CYP27B1 and Colonic Neoplasms
6
ARNTL 11p15.3 TIC, JAP3, MOP3, BMAL1, PASD3, BMAL1c, bHLHe5 -ARNTL and Colorectal Cancer
6
LTA 6p21.33 LT, TNFB, TNFSF1, TNLG1E -LTA and Colorectal Cancer
6
GATA5 20q13.33 CHTD5, GATAS, bB379O24.1 -GATA5 and Colorectal Cancer
6
ELAVL1 19p13.2 HUR, Hua, MelG, ELAV1 -ELAVL1 and Colonic Neoplasms
6
SACS 13q12.12 SPAX6, ARSACS, DNAJC29, PPP1R138 -SACS and Colorectal Cancer
6
MUC3A 7q22.1 MUC3, MUC-3A -MUC3A and Colorectal Cancer
6
PCDH10 4q28.3 PCDH19, OL-PCDH -PCDH10 and Colorectal Cancer
6
FRZB 2q32.1 FRE, OS1, FZRB, hFIZ, FRITZ, FRP-3, FRZB1, SFRP3, SRFP3, FRZB-1, FRZB-PEN -FRZB and Colorectal Cancer
6
MIRLET7I 12q14.1 LET7I, let-7i, MIRNLET7I, hsa-let-7i -MicroRNA let-7i and Colorectal Cancer
6
RALBP1 18p11.22 RIP1, RLIP1, RLIP76 -RALBP1 and Colorectal Cancer
6
MMP12 11q22.2 ME, HME, MME, MMP-12 -MMP12 and Colorectal Cancer
6
POLK 5q13.3 DINP, POLQ, DINB1 -POLK and Colorectal Cancer
6
MSI1 12q24 -MSI1 and Colorectal Cancer
6
ODC1 2p25 ODC -ODC1 and Colorectal Cancer
6
GPX2 14q23.3 GPRP, GPx-2, GI-GPx, GPRP-2, GPx-GI, GSHPx-2, GSHPX-GI -GPX2 and Colorectal Cancer
6
ANGPTL4 19p13.2 NL2, ARP4, FIAF, HARP, PGAR, HFARP, TGQTL, UNQ171, pp1158 -ANGPTL4 and Colorectal Cancer
6
CD276 15q24.1 B7H3, B7-H3, B7RP-2, 4Ig-B7-H3 -CD276 and Colorectal Cancer
6
DMPK 19q13.32 DM, DM1, DMK, MDPK, DM1PK, MT-PK -DMPK and Colorectal Cancer
6
TDGF1 3p21.31 CR, CRGF, CRIPTO -TDGF1 and Colonic Neoplasms
6
LARS 5q32 LRS, LEUS, LFIS, ILFS1, LARS1, LEURS, PIG44, RNTLS, HSPC192, hr025Cl -LARS and Colorectal Cancer
5
SLC4A3 2q36 AE3, SLC2C -SLC4A3 and Colonic Neoplasms
5
ADIPOR2 12p13.31 PAQR2, ACDCR2 -ADIPOR2 and Colorectal Cancer
5
HLA-E 6p21.3 MHC, QA1, EA1.2, EA2.1, HLA-6.2 -HLA-E and Colorectal Cancer
5
EPHA7 6q16.1 EHK3, EK11, EHK-3, HEK11 -EPHA7 and Colorectal Cancer
5
CEACAM7 19q13.2 CGM2 -CEACAM7 and Colorectal Cancer
5
SPHK1 17q25.1 SPHK -SPHK1 and Colonic Neoplasms
5
LGALS4 19q13.2 GAL4, L36LBP -LGALS4 and Colorectal Cancer
5
KLK6 19q13.41 hK6, Bssp, Klk7, SP59, PRSS9, PRSS18 -KLK6 and Colonic Neoplasms
5
SATB1 3p23 -SATB1 and Colorectal Cancer
5
NR5A2 1q32.1 B1F, CPF, FTF, B1F2, LRH1, LRH-1, FTZ-F1, hB1F-2, FTZ-F1beta -NR5A2 and Colonic Neoplasms
5
SMYD3 1q44 KMT3E, ZMYND1, ZNFN3A1, bA74P14.1 -SMYD3 and Colorectal Cancer
5
CD55 1q32.2 CR, TC, DAF, CROM, CHAPLE -CD55 and Colorectal Cancer
5
AKR1B10 7q33 HIS, HSI, ARL1, ARL-1, ALDRLn, AKR1B11, AKR1B12 -AKR1B10 and Colorectal Cancer
5
CCL21 9p13.3 ECL, SLC, CKb9, TCA4, 6Ckine, SCYA21 -CCL21 and Colorectal Cancer
5
ACTA2 10q23.31 AAT6, ACTSA, MYMY5 -ACTA2 and Colonic Neoplasms
5
ST14 11q24.3 HAI, MTSP1, SNC19, ARCI11, MT-SP1, PRSS14, TADG15, TMPRSS14 -ST14 and Colorectal Cancer
5
EIF3E 8q23.1 INT6, EIF3S6, EIF3-P48, eIF3-p46 -EIF3E and Colonic Neoplasms
5
CD58 1p13.1 ag3, LFA3, LFA-3 -CD58 and Colonic Neoplasms
5
MT1G 16q13 MT1, MT1K -MT1G and Colorectal Cancer
5
CRY1 12q23.3 PHLL1 -CRY1 and Colorectal Cancer
5
DLL4 15q15.1 AOS6, hdelta2 -DLL4 and Colorectal Cancer
5
CASP5 11q22.3 ICH-3, ICEREL-III, ICE(rel)III -CASP5 and Colorectal Cancer
5
UHRF1 19p13.3 Np95, hNP95, ICBP90, RNF106, TDRD22, hUHRF1, huNp95 -UHRF1 and Colorectal Cancer
5
LOXL2 8p21.3 LOR, LOR2, WS9-14 -LOXL2 and Colorectal Cancer
5
TNFRSF6B 20q13.33 M68, TR6, DCR3, M68E, DJ583P15.1.1 Amplification
-TNFRSF6B Amplification and Overexpression in Colon Cancer
5
IL16 15q25.1 LCF, NIL16, PRIL16, prIL-16 -IL16 and Colorectal Cancer
5
CLDN7 17p13.1 CLDN-7, CEPTRL2, CPETRL2, Hs.84359, claudin-1 -CLDN7 and Colorectal Cancer
5
RALGDS 9q34.13-q34.2 RGF, RGDS, RalGEF -RALGDS and Colorectal Cancer
5
PGK1 Xq21.1 PGKA, MIG10, HEL-S-68p -PGK1 and Colorectal Cancer
5
HHIP 4q31.21 HIP -HHIP and Colorectal Cancer
4
LEPR 1p31.3 OBR, OB-R, CD295, LEP-R, LEPRD -LEPR and Colorectal Cancer
4
CASP8AP2 6q15 CED-4, FLASH, RIP25 -CASP8AP2 and Colorectal Cancer
4
CRY2 11p11.2 HCRY2, PHLL2 -CRY2 and Colorectal Cancer
4
STC1 8p21.2 STC -STC1 and Colorectal Cancer
4
TFRC 3q29 T9, TR, TFR, p90, CD71, TFR1, TRFR, IMD46 -TFRC and Colorectal Cancer
4
WNT11 11q13.5 HWNT11 -WNT11 and Colorectal Cancer
4
DDX5 17q23.3 p68, HLR1, G17P1, HUMP68 -DDX5 and Colorectal Cancer
4
IRF7 11p15.5 IMD39, IRF7A, IRF7B, IRF7C, IRF7H, IRF-7H -IRF7 and Colorectal Cancer
4
CHD5 1p36.31 CHD-5 -CHD5 and Colorectal Cancer
4
MUC5B 11p15.5 MG1, MUC5, MUC9, MUC-5B -MUC5B and Colonic Neoplasms
4
S100A11 1q21.3 MLN70, S100C, HEL-S-43 -S100A11 and Colorectal Cancer
4
CDK2AP1 12q24.31 DOC1, ST19, DORC1, doc-1, p12DOC-1 -CDK2AP1 and Colorectal Cancer
4
STIM1 11p15.4 GOK, TAM, TAM1, IMD10, STRMK, D11S4896E -STIM1 and Colorectal Cancer
4
DRD2 11q23.2 D2R, D2DR -DRD2 and Colorectal Cancer
4
MAD1L1 7p22.3 MAD1, PIG9, TP53I9, TXBP181 -MAD1L1 and Colonic Neoplasms
4
MINA 3q11.2 ROX, MDIG, NO52, MINA53 -MINA and Colonic Neoplasms
4
SNRPF 12q23.1 SMF, Sm-F, snRNP-F -SNRPF and Colorectal Cancer
4
ST7 7q31.2 HELG, RAY1, SEN4, TSG7, ETS7q, FAM4A, FAM4A1 -ST7 and Colorectal Cancer
4
HSD17B1 17q21.2 E2DH, HSD17, EDHB17, EDH17B2, SDR28C1, 17-beta-HSD, 20-alpha-HSD -HSD17B1 and Colorectal Cancer
4
CKS2 9q22.2 CKSHS2 -CKS2 and Colorectal Cancer
4
TRA 14q11.2 IMD7, TCRA, TCRD, TRA@, TRAC -TRA and Colorectal Cancer
4
CDH17 8q22.1 HPT1, CDH16, HPT-1 -CDH17 and Colorectal Cancer
4
GUSB 7q11.21 BG, MPS7 -GUSB and Colorectal Cancer
4
CTBP1 4p16.3 BARS -CTBP1 and Colonic Neoplasms
4
GAB2 11q14.1 -GAB2 and Colorectal Cancer
4
VTI1A 10q25.2 MMDS3, MVti1, VTI1RP2, Vti1-rp2 -VTI1A and Colorectal Cancer
4
EPHA1 7q34-q35 EPH, EPHT, EPHT1 -EPHA1 and Colorectal Cancer
4
FER 5q21.3 TYK3, PPP1R74, p94-Fer -FER and Colonic Neoplasms
4
IL6R 1q21.3 IL6Q, gp80, CD126, IL6RA, IL6RQ, IL-6RA, IL-6R-1 -IL6R and Colonic Neoplasms
4
SPRY2 13q31.1 IGAN3, hSPRY2 -SPRY2 and Colonic Neoplasms
4
NRP2 2q33.3 NP2, NPN2, PRO2714, VEGF165R2 -NRP2 and Colorectal Cancer
4
IFITM1 11p15.5 9-27, CD225, IFI17, LEU13, DSPA2a -IFITM1 and Colorectal Cancer
4
CCR6 6q27 BN-1, DCR2, DRY6, CCR-6, CD196, CKRL3, GPR29, CKR-L3, CMKBR6, GPRCY4, STRL22, CC-CKR-6, C-C CKR-6 -CCR6 and Colorectal Cancer
4
SMAD6 15q22.31 AOVD2, MADH6, MADH7, HsT17432 -SMAD6 and Colorectal Cancer
4
WISP3 6q21 PPD, CCN6, LIBC, PPAC, WISP-3 -WISP3 and Colorectal Cancer
4
ARL11 13q14.2 ARLTS1 -ARL11 and Colorectal Cancer
4
SEC63 6q21 ERdj2, SEC63L, DNAJC23, PRO2507 -SEC63 and Colorectal Cancer
4
ROBO1 3p12 SAX3, DUTT1 -ROBO1 and Colorectal Cancer
4
GAS7 17p13.1 -GAS7 and Colorectal Cancer
4
INHBA 7p14.1 EDF, FRP -INHBA and Colorectal Cancer
4
INHA 2q35 -INHA and Colorectal Cancer
4
HAS3 16q22.1 -HAS3 and Colonic Neoplasms
4
CSMD1 8p23.2 PPP1R24 -CSMD1 and Colorectal Cancer
4
WISP1 8q24.22 CCN4, WISP1c, WISP1i, WISP1tc -WISP1 and Colorectal Cancer
4
IL2RB 22q12.3 CD122, IMD63, IL15RB, P70-75 -IL2RB and Colorectal Cancer
4
LIG4 13q33.3 LIG4S -LIG4 and Colorectal Cancer
4
CCL19 9p13.3 ELC, CKb11, MIP3B, MIP-3b, SCYA19 -CCL19 and Colorectal Cancer
4
USF1 1q23.3 UEF, FCHL, MLTF, FCHL1, MLTFI, HYPLIP1, bHLHb11 -USF1 and Colonic Neoplasms
3
MBD1 18q21.1 RFT, PCM1, CXXC3 -MBD1 and Colonic Neoplasms
3
BIRC2 11q22.2 API1, MIHB, HIAP2, RNF48, cIAP1, Hiap-2, c-IAP1 -BIRC2 and Colonic Neoplasms
3
RBPJ 4p15.2 SUH, csl, AOS3, CBF1, KBF2, RBP-J, RBPJK, IGKJRB, RBPSUH, IGKJRB1 -RBPJ and Colonic Neoplasms
3
ACVR1 2q23-q24 FOP, ALK2, SKR1, TSRI, ACTRI, ACVR1A, ACVRLK2 -ACVR1 and Colonic Neoplasms
3
AKAP9 7q21.2 LQT11, PRKA9, AKAP-9, CG-NAP, YOTIAO, AKAP350, AKAP450, PPP1R45, HYPERION, MU-RMS-40.16A -AKAP9 and Colorectal Cancer
3
HAS1 19q13.41 HAS -HAS1 and Colonic Neoplasms
3
PPP2CA 5q31.1 RP-C, PP2Ac, PP2CA, PP2Calpha -PPP2CA and Colonic Neoplasms
3
MAGEB2 Xp21.2 DAM6, CT3.2, MAGE-XP-2 -MAGEB2 and Colorectal Cancer
3
TXNRD1 12q23.3 TR, TR1, TXNR, TRXR1, GRIM-12 -TXNRD1 and Colorectal Cancer
3
RAD54L 1p34.1 HR54, hHR54, RAD54A, hRAD54 -RAD54L and Colorectal Cancer
3
IGF2-AS 11p15.5 PEG8, IGF2AS, IGF2-AS1 -IGF2-AS and Colorectal Cancer
3
DKC1 Xq28 DKC, CBF5, DKCX, NAP57, NOLA4, XAP101 -DKC1 and Colonic Neoplasms
3
SAT2 17p13.1 SSAT2 -SAT2 and Colorectal Cancer
3
KCNQ1 11p15.5-p15.4 LQT, RWS, WRS, LQT1, SQT2, ATFB1, ATFB3, JLNS1, KCNA8, KCNA9, Kv1.9, Kv7.1, KVLQT1 -KCNQ1 and Colorectal Cancer
3
TM4SF1 3q25.1 L6, H-L6, M3S1, TAAL6 -TM4SF1 and Colorectal Cancer
3
STAT2 12q13.3 P113, IMD44, ISGF-3, STAT113 -STAT2 and Colonic Neoplasms
3
FOSB 19q13.32 AP-1, G0S3, GOS3, GOSB -FOSB and Colonic Neoplasms
3
APOB 2p24-p23 FLDB, LDLCQ4 -APOB and Colonic Neoplasms
3
ATF6 1q23.3 ACHM7, ATF6A -ATF6 and Colonic Neoplasms
3
SEMA3F 3p21.3 SEMA4, SEMAK, SEMA-IV -SEMA3F and Colorectal Cancer
3
SPDEF 6p21.3 PDEF, bA375E1.3 -SPDEF and Colonic Neoplasms
3
ING5 2q37.3 p28ING5 -ING5 and Colorectal Cancer
3
BMPR1B 4q22.3 ALK6, AMDD, BDA2, ALK-6, BDA1D, CDw293 -BMPR1B and Colonic Neoplasms
3
IDO1 8p11.21 IDO, INDO, IDO-1 -IDO1 and Colorectal Cancer
3
NAV1 1q32.1 POMFIL3, UNC53H1, STEERIN1 -NAV1 and Colonic Neoplasms
3
NOX4 11q14.3 KOX, KOX-1, RENOX -NOX4 and Colonic Neoplasms
3
APRT 16q24.3 AMP, APRTD -APRT and Colorectal Cancer
3
BCL2L11 2q13 BAM, BIM, BOD -BCL2L11 and Colorectal Cancer
3
BCL2L12 19q13.33 -BCL2L12 and Colonic Neoplasms
3
MUC7 4q13.3 MG2 -MUC7 and Colorectal Cancer
3
KLK14 19q13.41 KLK-L6 -KLK14 and Colonic Neoplasms
3
PITX1 5q31.1 BFT, CCF, POTX, PTX1, LBNBG -PITX1 and Colorectal Cancer
3
FGF9 13q12.11 GAF, FGF-9, SYNS3, HBFG-9, HBGF-9 -FGF9 and Colonic Neoplasms
3
FHL2 2q12.2 DRAL, AAG11, FHL-2, SLIM3, SLIM-3 -FHL2 and Colonic Neoplasms
3
MAX 14q23.3 bHLHd4 -MAX and Colonic Neoplasms
3
HOXD10 2q31.1 HOX4, HOX4D, HOX4E, Hox-4.4 -HOXD10 and Colonic Neoplasms
3
TNFRSF10C 8p21.3 LIT, DCR1, TRID, CD263, TRAILR3, TRAIL-R3, DCR1-TNFR -TNFRSF10C and Colonic Neoplasms
3
RANBP2 2q12.3 ANE1, TRP1, TRP2, ADANE, IIAE3, NUP358 -RANBP2 and Colorectal Cancer
3
IL12A 3q25.33 P35, CLMF, NFSK, NKSF1, IL-12A -IL12A and Colorectal Cancer
3
NOTO 2p13.2 -NOTO and Colorectal Cancer
3
MAP3K8 10p11.23 COT, EST, ESTF, TPL2, AURA2, MEKK8, Tpl-2, c-COT -MAP3K8 and Colorectal Cancer
3
NNAT 20q11.23 Peg5 -NNAT and Colorectal Cancer
3
MYCL 1p34.2 LMYC, L-Myc, MYCL1, bHLHe38 -MYCL and Colorectal Cancer
3
SELENOP 5p12 SeP, SELP, SEPP, SEPP1 -SEPP1 and Colorectal Cancer
3
MVP 16p11.2 LRP, VAULT1 -MVP and Colonic Neoplasms
3
AQP1 7p14.3 CO, CHIP28, AQP-CHIP -AQP1 and Colonic Neoplasms
3
MAPK3 16p11.2 ERK1, ERT2, ERK-1, PRKM3, P44ERK1, P44MAPK, HS44KDAP, HUMKER1A, p44-ERK1, p44-MAPK -MAPK3 and Colonic Neoplasms
3
PROX1 1q32.3 -PROX1 and Colonic Neoplasms
3
KCNQ1OT1 11p15.5 LIT1, Kncq1, KvDMR1, KCNQ10T1, KCNQ1-AS2, KvLQT1-AS, NCRNA00012 -KCNQ1OT1 and Colorectal Cancer
3
ZFP36 19q13.2 TTP, G0S24, GOS24, TIS11, NUP475, zfp-36, RNF162A -ZFP36 and Colonic Neoplasms
3
GRASP 12q13.13 TAMALIN -GRASP and Colorectal Cancer
3
TSPO 22q13.2 DBI, IBP, MBR, PBR, PBS, BPBS, BZRP, PKBS, PTBR, mDRC, pk18 -TSPO and Colorectal Cancer
3
SNCG 10q23.2 SR, BCSG1 -SNCG and Colonic Neoplasms
3
PTK7 6p21.1-p12.2 CCK4, CCK-4 -PTK7 and Colonic Neoplasms
3
IL12B 5q33.3 CLMF, NKSF, CLMF2, IMD28, IMD29, NKSF2, IL-12B -IL12B and Colorectal Cancer
3
EPAS1 2p21-p16 HLF, MOP2, ECYT4, HIF2A, PASD2, bHLHe73 -EPAS1 and Colorectal Cancer
3
MT2A 16q13 MT2 -MT2A and Colonic Neoplasms
2
MIR100 11q24.1 MIRN100, miR-100 -MIR100 and Colonic Neoplasms
2
PPP1R3A 7q31.1 GM, PP1G, PPP1R3 -PPP1R3A and Colorectal Cancer
2
PCM1 8p22 PTC4, RET/PCM-1 -PCM1 and Colorectal Cancer
2
RIN1 11q13.2 -RIN1 and Colonic Neoplasms
2
WWTR1 3q25.1 TAZ -WWTR1 and Colorectal Cancer
2
C2orf40 2q12.2 ECRG4 -C2orf40 and Colorectal Cancer
2
SFPQ 1p34.3 PSF, POMP100, PPP1R140 -SFPQ and Colonic Neoplasms
2
MAP2K6 17q24.3 MEK6, MKK6, MAPKK6, PRKMK6, SAPKK3, SAPKK-3 -MAP2K6 and Colonic Neoplasms
2
ATP7A Xq21.1 MK, MNK, DSMAX, SMAX3 -ATP7A and Colonic Neoplasms
2
POLL 10q24.32 BETAN, POLKAPPA -POLL and Colonic Neoplasms
2
LTBR 12p13 CD18, TNFCR, TNFR3, D12S370, TNFR-RP, TNFRSF3, TNFR2-RP, LT-BETA-R, TNF-R-III -LTBR and Colorectal Cancer
2
ADGRB1 8q24.3 BAI1, GDAIF -BAI1 and Colorectal Cancer
2
PRKCDBP 11p15.4 SRBC, HSRBC, CAVIN3, cavin-3 -PRKCDBP and Colorectal Cancer
2
TOPBP1 3q22.1 TOP2BP1 -TOPBP1 and Colorectal Cancer
2
BOLL 2q33 BOULE -BOLL and Colonic Neoplasms
2
MYH9 22q12.3 MHA, FTNS, EPSTS, BDPLT6, DFNA17, MATINS, NMMHCA, NMHC-II-A, NMMHC-IIA -MYH9 and Colonic Neoplasms
2
LASP1 17q12 MLN50, Lasp-1 -LASP1 and Colonic Neoplasms
2
RASAL1 12q24.13 RASAL -RASAL1 and Colorectal Cancer
2
HIP1 7q11.23 SHON, HIP-I, ILWEQ, SHONbeta, SHONgamma -HIP1 and Colonic Neoplasms
2
ING2 4q35.1 ING1L, p33ING2 -ING2 and Colonic Neoplasms
2
TACR1 2p12 SPR, NK1R, NKIR, TAC1R -TACR1 and Colorectal Cancer
2
GJB2 13q12.11 HID, KID, PPK, CX26, DFNA3, DFNB1, NSRD1, DFNA3A, DFNB1A -GJB2 and Colorectal Cancer
2
PPP2CB 8p12 PP2CB, PP2Abeta -PPP2CB and Colonic Neoplasms
2
ITGB2 21q22.3 LAD, CD18, MF17, MFI7, LCAMB, LFA-1, MAC-1 -ITGB2 and Colorectal Cancer
2
ADAMTS9 3p14.1 -ADAMTS9 and Colorectal Cancer
2
MIR106A Xq26.2 mir-106, MIRN106A, mir-106a -MIR106A and Colorectal Cancer
2
FAT1 4q35.2 FAT, ME5, CDHF7, CDHR8, hFat1 -FAT1 and Colorectal Cancer
2
MTUS1 8p22 ATBP, ATIP, ICIS, MP44, ATIP3, MTSG1 -MTUS1 and Colonic Neoplasms
2
CASP4 11q22.3 TX, Mih1, ICH-2, Mih1/TX, ICEREL-II, ICE(rel)II -CASP4 and Colonic Neoplasms
2
MUC17 7q22.1 MUC3, MUC-3, MUC-17 -MUC17 and Colonic Neoplasms
2
TPM1 15q22.2 CMH3, TMSA, CMD1Y, LVNC9, C15orf13, HEL-S-265, HTM-alpha -TPM1 and Colonic Neoplasms
2
RALB 2q14.2 -RALB and Colorectal Cancer
2
ZNF350 19q13.41 ZFQR, ZBRK1 -ZNF350 and Colonic Neoplasms
2
MS4A1 11q12.2 B1, S7, Bp35, CD20, CVID5, MS4A2, LEU-16 -MS4A1 and Colorectal Cancer
2
ARHGEF12 11q23.3 LARG, PRO2792 -ARHGEF12 and Colorectal Cancer
2
ADAM29 4q34.1 CT73, svph1 -ADAM29 and Colorectal Cancer
2
SGK1 6q23 SGK -SGK1 and Colonic Neoplasms
2
ADRM1 20q13.33 ARM1, ARM-1, GP110 -ADRM1 and Colorectal Cancer
2
PDLIM4 5q31.1 RIL -PDLIM4 and Colonic Neoplasms
2
PATZ1 22q12.2 ZSG, MAZR, PATZ, RIAZ, ZBTB19, ZNF278, dJ400N23 -PATZ1 and Colorectal Cancer
2
RRM2B 8q22.3 P53R2, MTDPS8A, MTDPS8B -RRM2B and Colonic Neoplasms
2
ERC1 12p13.33 ELKS, Cast2, ERC-1, RAB6IP2 -ERC1 and Colorectal Cancer
1
PDCD6 5p15.33 ALG2, ALG-2, PEF1B -PDCD6 and Colonic Neoplasms
1
MAFG 17q25.3 hMAF -MAFG and Colonic Neoplasms
1
PNN 14q21.1 DRS, DRSP, SDK3, memA -PNN and Colonic Neoplasms
1
MIR1226 3p21.31 MIRN1226, mir-1226, hsa-mir-1226 -MicroRNA miR-1226 and Colorectal Cancer
1
SETD1B 12q24.31 KMT2G, Set1B -SETD1B and Colorectal Cancer
1
IFNA7 9p21.3 IFNA-J, IFN-alphaJ -IFNA7 and Colorectal Cancer
1
NIT2 3q12.2 HEL-S-8a -NIT2 and Colonic Neoplasms
1
COPS6 7q22.1 CSN6, MOV34-34KD -COPS6 and Colorectal Cancer
1
AVPR1B 1q32.1 V1bR, AVPR3 -AVPR1B and Colorectal Cancer
1
REST 4q12 WT6, XBR, NRSF -REST and Colorectal Cancer
1
RAP2A 13q32.1 KREV, RAP2, K-REV, RbBP-30 -RAP2A and Colonic Neoplasms
1
NR3C2 4q31.23 MR, MCR, MLR, NR3C2VIT -NR3C2 and Colorectal Cancer
1
GOLGA5 14q32.12 RFG5, GOLIM5, ret-II -GOLGA5 and Colorectal Cancer
1
MIR1297 13q14.3 MIRN1297, mir-1297, hsa-mir-1297 -MicroRNA miR-1297 and Colorectal Cancer
1
HINT1 5q23.3 HINT, NMAN, PKCI-1, PRKCNH1 -HINT1 and Colonic Neoplasms
1
PTPRH 19q13.42 SAP1, R-PTP-H -PTPRH and Colorectal Cancer
1
NEMF 14q21.3 NY-CO-1, SDCCAG1 -NEMF and Colonic Neoplasms
1
ETV3 1q23.1 PE1, METS, PE-1 -ETV3 and Colorectal Cancer
1
STEAP2 7q21.13 STMP, IPCA1, PUMPCn, STAMP1, PCANAP1 -STEAP2 and Colonic Neoplasms
1
MIR122 18q21.31 MIR122A, MIRN122, mir-122, MIRN122A, miRNA122, miRNA122A, hsa-mir-122 -MIR122 and Colonic Neoplasms
1
SERPINC1 1q25.1 AT3, AT3D, ATIII, THPH7, ATIII-R2, ATIII-T1, ATIII-T2 -SERPINC1 and Colorectal Cancer
1
ITGAL 16p11.2 CD11A, LFA-1, LFA1A -ITGAL and Colorectal Cancer
1
HSP90AA1 14q32.31 EL52, HSPN, LAP2, HSP86, HSPC1, HSPCA, Hsp89, Hsp90, LAP-2, HSP89A, HSP90A, HSP90N, Hsp103, HSPCAL1, HSPCAL4, HEL-S-65p -HSP90AA1 and Colonic Neoplasms
1
PCDH7 4p15.1 BHPCDH, BH-Pcdh, PPP1R120 -PCDH7 and Colonic Neoplasms
1
C2orf44 2p23.3 WDCP, PP384 -C2orf44 and Colorectal Cancer
1
PDCD2 6q27 RP8, ZMYND7 -PDCD2 and Colonic Neoplasms
1
CCKBR 11p15.4 GASR, CCK-B, CCK2R -CCKBR and Colonic Neoplasms

Note: list is not exhaustive. Number of papers are based on searches of PubMed (click on topic title for arbitrary criteria used).

Genetic Syndromes

There are a range of genetic syndromes which predispose to colorectal cancer:

SyndromeMajor gene(s)Notes
Familial Adenomatous Polyposis (FAP)APC
- Attenuated Familial Adenomatous Polyposis (AFAP)APC A variant of FAP characterized by a later age of onset, lower number of polyps compared to FAP, which is defined as > 100 polyps, and more proximal localization of the polyps.
Lynch SyndromeMLH1, MSH2, MSH6 ....Also called: Hereditary Non-Polyposis Colorectal Cancer (HNPCC)
MYH-Associated Polyposis
Familial CRC
PTEN hamartoma tumor syndromesPTEN
- Cowden SyndromePTEN
- Bannayan-Riley-Ruvalcaba Syndrome (BRRS)PTEN
Peutz-Jeghers syndrome (PJS)STK11PJS is an autosomal-dominant condition characterized by the gastrointestinal polyposis, mucocutaneous pigmentation, and predisposition to a range of epithelial cancers: including colorectal, gastric, pancreatic, breast, and ovarian cancers. Women also have increased risk of sex cord tumors with annular tubules.
Juvenile polyposis syndrome (JPS)MADH4, BMPR1A
CHEK2 family cancer syndromeCHEK2Not fully defined
Hereditary mixed polyposis syndrome
Serrated polyposis syndrome

Sources:

Latest Publications

Qin L, Kang A
[Epigenetic research progress in colorectal cancer].
Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2019; 44(7):830-836 [PubMed] Related Publications
Colorectal cancer is one of the common malignant tumors, which seriously threatens human health. Its morbidity and mortality rank the third and the second among all malignant tumors. The progress of colorectal cancer is a complex process involving the accumulation of genetic and epigenetic changes. Epigenetic changes of colorectal cancer mainly include DNA methylation, histone modification, non-coding RNAs (such as microRNAs and lncRNAs), which are of great significance to early diagnosis and prognosis evaluation, and to chemosensitivity assessment for colorectal cancer, providing a new thought for the treatment of colorectal cancer.

Bu X, Qin A, Luo Z, Hu Y
[Overexpression of the long non-coding RNA ADAMTS9-AS2 suppresses colorectal cancer proliferation and metastasis].
Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2019; 44(7):741-748 [PubMed] Related Publications
OBJECTIVE: To investigate the expression, clinical significance, and biological function of the long non-coding RNA (lncRNA) ADAMTS9-AS2 in colorectal cancer (CRC).
 Methods: Gene microarray analysis was performed to explore the expression of ADAMTS9-AS2 in CRC. Real-time PCR was used to verify its expression in 20-paired CRC tissues and adjacent non-tumor tissues. We further explored the relationship between ADAMTS9-AS2 expression and clinicopathological features, and its prognostic role in relapse-free survival (RFS) among early stage CRC patients using Kaplan-Meier and Cox regression analyses. In vitro assays, cell counting kit-8 assay, colony formation assay, and Transwell assay were used to evaluate the biological function of ADAMTS9-AS2 in CRC.
 Results: ADAMTS9-AS2 was down-regulated in CRC patients according to the gene microarray analysis, which was confirmed in CRC tissues and cells. High expression of ADAMTS9-AS2 was associated with a higher 5-year RFS rate (83.8% vs 73.5%, P=0.041) and it was an independent prognostic factor for RFS [hazard ratio (HR)=0.528; 95% CI 0.299 to 0.932; P=0.028] at the early stage of CRC. ADAMTS9-AS2 overexpression in CRC cells inhibited cell proliferation, migration, and invasion, while suppression of ADAMTS9-AS2 showed opposite effects.
 Conclusion: ADAMTS9-AS2 is a valuable prognostic factor for CRC and may function as a tumor suppressor in CRC via inhibiting cell proliferation and metastasis.

Park YY, An CH, Oh ST, et al.
Expression of CD133 is associated with poor prognosis in stage II colorectal carcinoma.
Medicine (Baltimore). 2019; 98(32):e16709 [PubMed] Related Publications
CD133 is currently believed to be one of the best colorectal cancer stem cell markers. This study aimed to evaluate prognostic significance of CD133 expression in colorectal cancer patients.A total of 303 patients with stage I to III colorectal cancer who underwent curative surgical resection from 2003 to 2008 at a single institution were included. CD133 expression was evaluated using immunohistochemical staining, and clinicopathological data were retrospectively reviewed. The patients were dichotomized after scoring CD133 expression (0 to 2+: low CD133 expression vs 3+ to 4+: high CD133 expression) according to the extent of area of CD133 positive tumor cells (<50% vs ≥50%) and pattern of staining (membranous staining of the luminal surface and/or staining of cellular debris in the tumor glands and cytoplasm).The 5-year overall survival (OS) (61.9% vs 80.2%, P = .001) and disease-free survival (64.8% vs 75.8%, P = .026) were poorer in the high CD133 expression group than the low CD133 expression group. In the multivariate analysis for risk factors of OS in the whole population, higher nodal stage (N2 compared to N0: hazard ratio [HR] 3.141; 95% confidence interval [CI] 1.718-5.744, P < .001), perineural invasion (HR 2.262; 95% CI 1.347-3.798, P = .002) and high CD133 expression (HR 1.929; 95% CI 1.221-3.048, P = .005) were independent poor prognostic factors of OS. Subgroup analyses according to each TNM stage revealed that CD133 expression was associated with OS only within the stage II patients (HR 3.167 95% CI 1.221-8.216, P = .018). Furthermore, the stage II patients demonstrating the high CD133 expression showed survival benefit of adjuvant chemotherapy, regardless of high-risk feature positivity (HR 0.201 95% CI 0.054-0.750, P = .017).High CD133 expression is correlated with poor prognosis in colorectal cancer patients after radical resection. The CD133 expression may serve as a more potent and informative biomarker for prognosis than conventional high-risk features in the stage II colorectal cancer patients.

Chao XL, Wang LL, Liu R, et al.
Association between CA repeat polymorphism in IGF1 gene promoter and colorectal cancer risk in a native Chinese population.
Neoplasma. 2019; 2019 [PubMed] Related Publications
Insulin-like growth factor 1 (IGF1) is implicated in normal cell growth. It has been reported that IGF1 has a mitogenic and anti-apoptotic effect on colorectal cancer cells. However, results of studies on the association between cytosine-adenine (CA) repeat polymorphism in IGF1 gene promoter and colorectal cancer (CRC) risk are inconsistent. We aimed to evaluate the association between CA repeat polymorphism and CRC risk, as well as the relationship with the clinicopathological characteristics of CRC and circulating IGF1 level in a native Chinese population. There were 734 participants who were native Chinese in this case-control study, including 367 CRC cases and 367 age- and sex-matched controls. CA repeat polymorphism was genotyped by PCR and fragment analysis. Odds ratios (ORs) and 95% confidence intervals (CIs) were evaluated by unconditional logistic regression analysis. Circulating level of IGF1 in cases was significantly higher than that in controls (P = 0.002), particularly in males. Less than 38 CA repeats were associated with decreased CRC risk after adjusting for age and sex (37 versus 38 CA repeats: OR = 0.45; 95%CI = 0.26-0.78), especially in males. (CA)18/19 genotype showed approximately half reduced CRC risk comparing to (CA)19/19 genotype (OR = 0.46; 95%CI = 0.25-0.85). There was a significant association between the sum of CA repeats and degree of differentiation of CRC (P = 0.044). We observed a trend that circulating level of IGF1 in individuals with CA ≤ 38 repeats was lower than that in individuals with CA > 38 repeats with a borderline statistically significance in overall and males. In conclusion, our findings support the possible role of CA repeat polymorphism in CRC risk.

Gao XH, Zhang W, Liu LJ, Yan HL
[Comprehensive application of various screening strategies of Lynch syndrome].
Zhonghua Wei Chang Wai Ke Za Zhi. 2019; 22(7):684-688 [PubMed] Related Publications
Lynch syndrome (LS), which is the most common hereditary colorectal cancer, accounts for about 3% of all colorectal cancers. However, due to its various clinical manifestations, it is difficult to be diagnosed. The diagnosis of LS requires comprehensive application of various screening criteria (such as the Amsterdam criteria, Bethesda criteria), predictive models, risk factors, immunohistochemistry test of mismatch repair (MMR) protein, microsatellite instability (MSI) detection, MLH1 methylation detection, BRAF gene mutation detection, germline gene mutation detection, and so on. LS can be diagnosed only after the identification of pathogenic germline mutation of MMR gene. The first-degree and second-degree relatives of LS patients are recommended to be tested for the identified mutant gene. For LS patients and gene mutation carriers, LS associated cancer can be detected early or even prevented by monitoring and preventive surgery. Reproductive techniques can be used to prevent this disease from being passed down to the next generation.

Chuo D, Liu F, Chen Y, Yin M
LncRNA MIR503HG is downregulated in Han Chinese with colorectal cancer and inhibits cell migration and invasion mediated by TGF-β2.
Gene. 2019; 713:143960 [PubMed] Related Publications
In this study we investigated the role of lncRNA MIR503HG in colorectal cancer (CRC). We found that MIR503HG was downregulated and TGF-β2 was upregulated in CRC included in this study. Low levels of MIR503HG were associated with poor survival of CRC patients within 5 years after admission. MIR503HG and TGF-β2 were inversely correlated in CRC tissues, and in CRC cells, MIR503HG overexpression was accompanied by TGF-β2 downregulation, while TGF-β2 overexpression did not affect MIR503HG. TGF-β2 overexpression mediated the increased migration and invasion rates of CRC cells. MIR503HG overexpression mediated the decreased migration and invasion rates of CRC cells. Moreover, TGF-β2 overexpression reduced the effects of MIR503HG overexpression. Therefore, MIR503HG overexpression inhibits CRC cell migration and invasion mediated by TGF-β2.

Wang Y, Yang W, Liu T, et al.
Over-expression of SOX8 predicts poor prognosis in colorectal cancer: A retrospective study.
Medicine (Baltimore). 2019; 98(27):e16237 [PubMed] Free Access to Full Article Related Publications
Aberrant expression of SRY-box 8 (SOX8) is closely correlated with the development and progression of many types of cancers in human. Limited studies report the relationship between SOX8 expression and overall survival in colorectal cancer (CRC). This study aimed to collect the pathological tissues and clinical data in order to analyze the relationship between SOX8 expression and clinicopathological parameters and prognosis of CRC patients. Tissue microarrays were constructed from 424 primary CRC patients with clinicopathological information and follow-up data. Immunohistochemistry (IHC) was performed on tissue microarrays to explore the relationship between SOX8 expression and clinicopathological information and patient's prognosis. The expression of SOX8 was higher in CRC tissues than that in non-tumor adjacent tissues (NATs, P <.001). High expression of SOX8 was associated with tumor stage (P = .04) and shorter overall survival (OS) after operation of patients (P = .004). Subsequently, univariate COX analysis identified that high expression of SOX8 (P = .004), differentiation (P = .006), distant metastasis (P <.001), tumor stage (P = .003), and higher rate of lymph node metastasis (P <.001), all significantly predicted decrease in OS. Multivariate analysis demonstrated that distant metastasis (P <.001), high SOX8 expression, (P = .013) and lymph node metastasis (P <.001) were independent poor prognostic factors in CRC patients. This study showed that SOX8 is over-expressed in patients with high T stage, which affects the outcome of prognosis in CRC patients. High expression of SOX8 usually has a poor independent prognostic factor for CRC.

Fu Q, Cheng J, Zhang JD, et al.
[The expression and functional mechanism of long non-coding RNA LINC00339 in colorectal cancer].
Zhonghua Yi Xue Za Zhi. 2019; 99(24):1881-1886 [PubMed] Related Publications

Kobunai T, Matsuoka K, Takechi T
ChIP-seq Analysis to Explore DNA Replication Profile in Trifluridine-treated Human Colorectal Cancer Cells
Anticancer Res. 2019; 39(7):3565-3570 [PubMed] Related Publications
BACKGROUND/AIM: Trifluridine (FTD) is a key component of the novel oral antitumor drug trifluridine/tipiracil that has been approved for the treatment of metastatic colorectal cancer. In this study, a comprehensive analysis of DNA replication profile in FTD-treated colon cancer cells was performed.
MATERIALS AND METHODS: HCT-116 cells were exposed to BrdU or FTD and subjected to DNA immunoprecipitation. Immunoprecipitated DNA was sequenced; the density of aligned reads along the genome was calculated. Peak finding, gene ontology, and motif analysis were performed using MACS, GREAT, and MEME, respectively.
RESULTS: We identified 6,043 and 5,080 high-confidence FTD and BrdU peaks in HCT-116 cells, respectively. Of 6,043 FTD peaks, 2,911 peaks were uncommon to BrdU. We observed that FTD was preferentially incorporated into genomic regions containing simple repeats, CpG islands, and gene bodies. Conserved motifs in FTD peaks contained dinucleotide repeats such as (GT)n.
CONCLUSION: Global FTD incorporation patterns delineated FTD, preferentially incorporating loci in cancer cells.

Kim H, Chung Y, Paik SS, et al.
Mesothelin expression and its prognostic role according to microsatellite instability status in colorectal adenocarcinoma.
Medicine (Baltimore). 2019; 98(26):e16207 [PubMed] Free Access to Full Article Related Publications
The cell-surface glycoprotein, mesothelin, is normally present on mesothelial cells. Overexpression of mesothelin has been reported in many tumors and is correlated with poor outcome. We investigated the clinicopathologic significance of mesothelin expression in colorectal adenocarcinoma with microsatellites instability (MSI) status.Mesothelin expression was evaluated immunohistochemically in tissue microarray blocks from 390 colorectal adenocarcinoma samples. Mesothelin expression was interpreted according to the intensity and extent. A score of 2 was considered high expression. We analyzed the correlation between mesothelin expression and clinicopathologic characteristics.High mesothelin expression was observed in 177 (45.4%) out of 390 colorectal adenocarcinoma samples and was significantly associated with high histologic grade (P = .037), lymphatic invasion (P = .028), lymph node metastasis (P = .028), and high AJCC stage (P = .026). Kaplan-Meier survival curves revealed no significant difference between patients with high mesothelin expression and patients with low mesothelin expression in both recurrence-free survival (RFS) and cancer-specific survival (P = .609 and P = .167, respectively). In subgroup survival analyses, high mesothelin expression was associated with poor RFS in the MSI-High group of colorectal adenocarcinoma (P = .004).High mesothelin expression was significantly associated with aggressive phenotypes and poor patient outcome in MSI-High colorectal adenocarcinoma.

Chen H, Ji L, Liu X, Zhong J
Correlation between the rs7101 and rs1063169 polymorphisms in the FOS noncoding region and susceptibility to and prognosis of colorectal cancer.
Medicine (Baltimore). 2019; 98(26):e16131 [PubMed] Free Access to Full Article Related Publications
BACKGROUND: The FOS gene is located on human chromosome 14q21-31 and encodes the nuclear oncoprotein c-Fos. This study analyzed the correlation between the FOS noncoding region rs7101 and rs1063169 polymorphisms and colorectal cancer susceptibility and prognosis.
METHODS: We analyzed the FOS genotypes in 432 colorectal cancer patients and 315 healthy subjects by PCR/Sanger sequencing. Survival was analyzed by Kaplan-Meier and Cox regression analysis. Western blot was used to detect the expression of c-Fos protein in cancer tissues and adjacent tissues in colorectal cancer patients with different genotypes.
RESULTS: The presence of a T allele at rs7101 and a T allele at rs1063169 in FOS carried a higher risk of colorectal cancer [adjusted odds ratio (OR) = 1.237, 95% confidence interval (95% CI) = 1.131-1.346, P ≤ .001 and adjusted OR = 1.218, 95% CI = 1.111-1.327, P ≤ .001, respectively]. c-Fos protein levels were significantly higher in variant cancer tissues than in normal mucosa tissues (P < .05), and c-Fos proteins levels were also higher in homozygous variant cancer tissues than in heterozygous variant cancer tissues. The 3-year survival rate of patients with wild-type FOS was higher than that of patients with variant FOS (P < .05).
CONCLUSION: The rs7101 and rs1063169 polymorphisms in the noncoding region of FOS are associated with the risk of developing colorectal cancer and the progression of colorectal cancer, which may be because the mutation enhances the expression of c-Fos protein to promote the incidence and development of colorectal cancer.

Ali H, AbdelMageed M, Olsson L, et al.
Utility of G protein-coupled receptor 35 expression for predicting outcome in colon cancer.
Tumour Biol. 2019; 41(6):1010428319858885 [PubMed] Related Publications
The utility of mRNA and protein determinations of G protein-coupled receptor 35, that is, GPR35a (GPR35 V1) and GPR35b (GPR35 V2/3), as indicators of outcome for colon cancer patients after curative surgery was investigated. Expression levels of V1 and V2/3 GPR35, carcinoembryonic antigen and CXCL17 mRNAs were assessed in primary tumours and regional lymph nodes of 121 colon cancer patients (stage I-IV), colon cancer cell lines and control colon epithelial cells using real-time quantitative reverse transcriptase-polymerase chain reaction. Expression of G protein-coupled receptor 35 was investigated by two-colour immunohistochemistry and immunomorphometry. GPR35 V2/3 mRNA, but not V1 mRNA, was expressed in colon cancer cell lines, primary colon tumours and control colon epithelial cells. Haematoxylin and eosin positive (H&E(+)), but not H&E(-), lymph nodes expressed high levels of GPR35 V2/3 mRNA (

Gao YL, Cui Z, Liu JX, et al.
NPCMF: Nearest Profile-based Collaborative Matrix Factorization method for predicting miRNA-disease associations.
BMC Bioinformatics. 2019; 20(1):353 [PubMed] Free Access to Full Article Related Publications
BACKGROUND: Predicting meaningful miRNA-disease associations (MDAs) is costly. Therefore, an increasing number of researchers are beginning to focus on methods to predict potential MDAs. Thus, prediction methods with improved accuracy are under development. An efficient computational method is proposed to be crucial for predicting novel MDAs. For improved experimental productivity, large biological datasets are used by researchers. Although there are many effective and feasible methods to predict potential MDAs, the possibility remains that these methods are flawed.
RESULTS: A simple and effective method, known as Nearest Profile-based Collaborative Matrix Factorization (NPCMF), is proposed to identify novel MDAs. The nearest profile is introduced to our method to achieve the highest AUC value compared with other advanced methods. For some miRNAs and diseases without any association, we use the nearest neighbour information to complete the prediction.
CONCLUSIONS: To evaluate the performance of our method, five-fold cross-validation is used to calculate the AUC value. At the same time, three disease cases, gastric neoplasms, rectal neoplasms and colonic neoplasms, are used to predict novel MDAs on a gold-standard dataset. We predict the vast majority of known MDAs and some novel MDAs. Finally, the prediction accuracy of our method is determined to be better than that of other existing methods. Thus, the proposed prediction model can obtain reliable experimental results.

Odin E, Sondén A, Carlsson G, et al.
Folate pathway genes linked to mitochondrial biogenesis and respiration are associated with outcome of patients with stage III colorectal cancer.
Tumour Biol. 2019; 41(6):1010428319846231 [PubMed] Related Publications
5-fluorouracil in combination with the folate leucovorin is the cornerstone in treatment of colorectal cancer. Transport of leucovorin into cells, and subsequent metabolic action, require expression of several genes. The aim was to analyze if tumoral expression of genes putatively involved in leucovorin transport, polyglutamation, or metabolism was associated with outcome of patients with stage III colorectal cancer treated with adjuvant chemotherapy. A total of 363 stage III colorectal cancer patients who received adjuvant bolus 5-fluorouracil + leucovorin alone, or in combination with oxaliplatin according to Nordic bolus regimes were included. Expression of 11 folate pathway genes was determined in tumors using quantitative real-time polymerase chain reaction and related to disease-free survival. The median follow-up time was 5 years. During follow-up, 114 (31%) patients suffered from recurrent disease. A high tumoral expression of the genes

Wu MH, Hung YW, Gong CL, et al.
Contribution of Caspase-8 Genotypes to Colorectal Cancer Risk in Taiwan.
Anticancer Res. 2019; 39(6):2791-2797 [PubMed] Related Publications
BACKGROUND/AIM: The aim of this study was to examine the role of caspase-8 rs3834129 polymorphism on colorectal cancer (CRC) risk in Taiwanese CRC patients and healthy controls.
MATERIALS AND METHODS: The caspase-8 rs3834129 (-652 6N insertion/deletion) polymorphic genotypes were analyzed in 362 patients with CRC and the same number of age- and gender-matched healthy subjects. The interaction of caspase-8 rs3834129 genotypes with personal behaviors and clinicopathological features were also examined.
RESULTS: The percentage of variants ID and DD for caspase-8 rs3834129 genotype were 37.6 and 5.8% in CRC group and 39.0 and 6.6% in the control group, respectively (p for trend=0.7987). The allelic frequency distribution analysis showed that caspase-8 rs3834129 D allele conferred a non-significant lower susceptibility for CRC compared with I allele (OR=0.92, 95%CI=0.74-1.20, p=0.5063). There was no obvious link between caspase-8 rs3834129 genotype and CRC risk among ever-smokers, non-smokers, non-alcohol drinkers or alcohol drinkers. No statistically significant correlation was observed between caspase-8 rs3834129 genotypic distribution and age, gender, tumor size, location or metastasis status.
CONCLUSION: Overall, caspase-8 rs3834129 genotypes may not serve as predictors for CRC risk or prognosis.

Nakagawa Y, Kuranaga Y, Tahara T, et al.
Induced miR-31 by 5-fluorouracil exposure contributes to the resistance in colorectal tumors.
Cancer Sci. 2019; 110(8):2540-2548 [PubMed] Free Access to Full Article Related Publications
Drug resistance makes treatment difficult in cancers. The present study identifies and analyzes drug resistance-related miRNA in colorectal cancer. We established 4 types of 5-fluorouracil (5-FU)-resistant colon cancer cell lines in vitro and in vivo. We then analyzed the miRNA expression profile by miRNA array in these 4 cell lines, and identified the drug resistance-related miRNAs. We examined the expression levels of the identified miRNA in 112 colorectal tumor samples from the patients. We identified 12 possible miRNAs involved in 5-FU resistance by miRNA arrays. We then examined the relationship between miR-31, which was the most promising among them, and drug resistance. The ectopic expression of mimic miR-31 showed significant 5-FU resistance in the parental DLD-1 cells, while anti-miR-31 caused significant growth inhibition in DLD/F cells; that is, 5-FU-resistant colon cancer cell line DLD-1 under exposure to 5-FU. When we exposed high doses of 5-FU to parent or 5-FU-resistant cells, the expression levels of miR-31 were raised higher than those of controls. Notably, the expression levels of miR-31 were positively correlated with the grade of clinical stages of colorectal tumors. The protein expression levels of factors inhibiting hypoxia-inducible factor 1 were downregulated by transfection of mimic miR-31 into DLD-1 cells. This study provides evidence supporting the association of miR-31 with 5-FU drug resistance and clinical stages of colorectal tumors.

Hobbs GA, Der CJ
RAS Mutations Are Not Created Equal.
Cancer Discov. 2019; 9(6):696-698 [PubMed] Related Publications
In this issue of

Yoshii S, Hayashi Y, Iijima H, et al.
Exosomal microRNAs derived from colon cancer cells promote tumor progression by suppressing fibroblast TP53 expression.
Cancer Sci. 2019; 110(8):2396-2407 [PubMed] Free Access to Full Article Related Publications
The tumor microenvironment offers favorable conditions for tumor progression, and activated fibroblasts, known as cancer-associated fibroblasts, play a pivotal role. TP53-deficient cancer cells are known to induce strong fibroblast activation. We aimed to elucidate the oncogenic role of exosomes derived from TP53-deficient colon cancer cells in fibroblast proliferation and tumor growth. Cancer cell-derived exosomes (CDEs) were isolated from the conditioned media of cancer cells using a sequential ultracentrifugation method. The effects of exosomes on tumor growth were evaluated using human cell lines (TP53-WT colon cancer, HCT116; TP53-mutant colon cancer, HT29; and fibroblasts, CCD-18Co and WI-38) and an immune-deficient nude mouse xenograft model. HCT116 (HCT116

Zhou DJ, Bai FJ
The relationship between c-reactive protein gene +1444C/T, 3407T/C polymorphisms and colorectal cancer susceptibility.
Gene. 2019; 710:145-147 [PubMed] Related Publications
AIM: The present study was conducted to analyze the relationship between c-reactive protein (CRP) gene +1444C/T, 3407T/C (rs2808630) polymorphisms and colorectal cancer susceptibility.
METHODS: A total of 142 colorectal cancer patients and 127 healthy controls were recruited into this case-control study. The genotypes of CRP gene +1444C/T, rs2808630 polymorphisms were tested by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and the genotypes distributions of polymorphisms in controls was assessed whether conformed to Hardy-Weinberg equilibrium (HWE). The calculation of odds ratio (OR) with its 95% confidence interval (95% CI) is used for evaluating the association strength of gene polymorphism and disease.
RESULTS: Through the testing of χ
CONCLUSION: CRP rs2808630 polymorphism was related to the decreased risk of colorectal cancer, but not +1444C/T polymorphism.

Kim HS, Kim KM, Lee SB, et al.
Clinicopathological and biomolecular characteristics of stage IIB/IIC and stage IIIA colon cancer: Insight into the survival paradox.
J Surg Oncol. 2019; 120(3):423-430 [PubMed] Related Publications
BACKGROUND: A survival paradox of stage IIB/IIC and IIIA colon cancer has been consistently observed throughout revisions of the TNM system. This study aimed to understand this paradox with clinicopathological and molecular differences.
METHODS: Clinicopathological characteristics of patients with pathologically confirmed stage IIB/IIC or IIIA colon cancer were retrospectively reviewed from a database. Publicly available molecular data were retrieved, and intrinsic subtypes were identified and subjected to gene sets enrichment analysis (GSEA).
RESULTS: Among the 159 patients included in the clinicopathological analysis, those at stage IIB/IIC had worse 3-year disease-free and overall survival than those at stage IIIA (59.3% vs 91.7%, P < 0.001 and 82.7% vs 98.5%, P < 0.001, respectively), even after adjusting for confounding factors. Data of 95 patients were retrieved from public databases, demonstrating a higher frequency of the microsatellite instable subtype in stage IIB/IIC. The consensus molecular subtype distribution pattern differed between the groups. The GSEA further suggested the protumor inflammatory reaction might be more prominent in stage IIB/IIC.
CONCLUSIONS: The survival paradox in colon cancer was confirmed and appears to be a multifactorial phenomenon not attributed to a single clinicopathologic factor. However, the greater molecular heterogeneity in stage IIB/IIC could contribute to the poor prognosis.

Fu Y, Lin L, Xia L
MiR-107 function as a tumor suppressor gene in colorectal cancer by targeting transferrin receptor 1.
Cell Mol Biol Lett. 2019; 24:31 [PubMed] Free Access to Full Article Related Publications
Background: While microRNAs (miRNAs) are known to play a critical role in the progression of colorectal cancer, the role of miR-107 remains unknown. We evaluated its role and explored the underlying mechanism.
Materials & methods: MTT, wound-healing, transwell migration and transwell invasion assays were performed to evaluate the role of miR-107 in SW629 cell proliferation, migration and invasion. Real time-PCR and dual-luciferase reporter gene, TFR1 overexpression and western blotting assays were used to explore the underlying mechanism.
Results: MiR-107 is downregulated in colorectal cancer tissues and several human colorectal cancer cell lines. Low miR-107 expression often indicates a poor survival rate for colorectal cancer patients. MiR-107 suppresses the proliferation, migration and invasion of SW620 cells by negatively regulating transferrin receptor 1 (TFR1).
Conclusion: MiR-107 suppresses the metastasis of colorectal cancer and could be a potential therapy target in colorectal cancer patients.

Liu XN, Tian Z, Wei XF, et al.
[Combined detection of KRAS, NRAS, BRAF and PIK3CA mutations in the plasma and tumor tissues of colorectal cancer patients].
Zhonghua Bing Li Xue Za Zhi. 2019; 48(5):373-377 [PubMed] Related Publications

Ma CX, Guan X, Wang S, et al.
[Application and prospect of fecal DNA test in colorectal cancer screening].
Zhonghua Wei Chang Wai Ke Za Zhi. 2019; 22(5):491-494 [PubMed] Related Publications
Effective early screening and primary prevention is one of the major initiatives to decrease the morbidity and mortality of colorectal cancer in China. As a new non-invasive screening method for colorectal cancer in recent years, fecal DNA test detects colorectal cancer by analyzing gene mutations from intestinal tumor cells in the feces. The most widely used method among fecal DNA test is multi-target stoolDNA test (MT-sDNA). Many studies abroad on this emerging technique have been carried out to verify its high sensitivity, and it is gradually used in the clinic with continuous improvement and development of technology. Meanwhile, domestic MT-sDNA is still in the prototype stage, and more researches from Chinese population are needed. Compared with traditional screening methods, MT-sDNA technology has the advantages of non-invasiveness, painlessness and convenience. But its defects exist, such as high cost and low specificity. MT-sDNAis in accordance with precision medicine, and can largely make up for the shortcomings of traditional screening methods for colorectal cancer. It also holds a great promise for promoting the screening for colorectal cancer. This paper is aimed to discuss the application value of fecal DNA test by introducing its related researches at home and abroad,and summarizing its merits and demerits.

Yuan C, Renfro L, Ambadwar PB, et al.
Influence of genetic variation in the vitamin D pathway on plasma 25-hydroxyvitamin D
Cancer Causes Control. 2019; 30(7):757-765 [PubMed] Article available free on PMC after 01/07/2020 Related Publications
PURPOSE: The relationships of genetic variation in the vitamin D pathway with circulating 25-hydroxyvitamin D
METHODS: Among 535 patients participating in a randomized trial of chemotherapy for mCRC, we prospectively measured baseline plasma 25(OH)D and examined 124 tagging single-nucleotide polymorphisms (SNPs) within seven genes in the vitamin D pathway, including five SNPs associated with circulating 25(OH)D levels in previous genome-wide association studies (GWAS). We evaluated whether these SNPs were associated with plasma 25(OH)D levels and patient outcome (overall survival, time to progression, and tumor response), using linear, logistic, and Cox proportional hazards regression.
RESULTS: We observed a significant association between 25(OH)D levels and an additive genetic risk score determined by the five GWAS-identified SNPs (p = 0.0009). We did not observe any direct association between 25(OH)D-associated SNPs, individually or as a genetic risk score, and patient outcome. However, we found a significant interaction between 25(OH)D levels and rs12785878 genotype in DHCR7 on overall survival (p
CONCLUSION: Germline genetic variation in the vitamin D pathway informs baseline 25(OH)D levels among patients with mCRC. The association between 25(OH)D levels and overall survival may vary by DHCR7 genotype. ClinicalTrials.gov Identifier: NCT00003594 ( https://clinicaltrials.gov/ct2/show/NCT00003594 ).

Toboeva MK, Shelygin YA, Frolov SA, et al.
MutYH-associated polyposis.
Ter Arkh. 2019; 91(2):97-100 [PubMed] Related Publications
MutYH-associated polyposis is the only polyposis syndrome with an autosomal recessive type of inheritance, often phenotypically similar to a weakened form of familial adenomatous polyposis. For the development of the disease mutations in both alleles of the gene are required, but an increased risk of developing colorectal cancer in carriers of monoallelic mutations is noted. The diagnosis of MutYH-associated polyposis should be suspected in a patient with colorectal cancer over 45 years old on the background of polyps in the colon. The review presents modern algorithms for diagnostic and treatment of the disease.

Li C, Tan F, Pei Q, et al.
Non-coding RNA MFI2-AS1 promotes colorectal cancer cell proliferation, migration and invasion through miR-574-5p/MYCBP axis.
Cell Prolif. 2019; 52(4):e12632 [PubMed] Related Publications
OBJECTIVE: Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) play essential roles in the tumour progression. LncRNAs mostly act as competing endogenous RNAs (ceRNAs) by sponging miRNAs. This study aimed to study the association of a novel lncRNA MFI2-AS1 with miR-574-5p/MYCBP axis in the development of colorectal cancer (CRC).
METHODS: Ninety-four CRC tissues and paired adjacent non-tumour tissues were included in our study. The relative expression level of MFI2-AS1 was detected, and its relationship with clinico-pathological factors was analysed. Then, the CRC cells lines (LoVo and RKO) were transfected with MFI2-AS1 siRNA, miR-574-5p mimics and inhibitors. Cell proliferation, migration, invasion, cell cycle distribution and DNA damage in response to different transfection conditions were examined. Dual-luciferase reporter assay was performed to identify the target interactions between MFI2-AS1 and miR-574-5p, miR-574-5p and MYCBP.
RESULTS: LncRNA MFI2-AS1 and MYCBP were up-regulated in CRC tissues when compared with adjacent non-tumour tissues. The expression levels of MFI2-AS1 were significantly associated with tumour histological grade, lymph and distant metastasis, TNM stage and vascular invasion. Both MFI2-AS1 siRNA and miR-574-5p mimics inhibited proliferation, migration and invasion in LoVo and RKO cells. The transfection of miR-574-5p inhibitor showed MFI2-AS1 siRNA-induced changes in CRC cells. Dual-luciferase reporter assay revealed target interactions between MFI2-AS1 and miR-574-5p, miR-574-5p and MYCBP.
CONCLUSIONS: These findings suggested that lncRNA MFI2-AS1 and MYCBP have promoting effects in CRC tissues. LncRNA MFI2-AS1 promoted CRC cell proliferation, migration and invasion through activating MYCBP and by sponging miR-574-5p.

Law PJ, Timofeeva M, Fernandez-Rozadilla C, et al.
Association analyses identify 31 new risk loci for colorectal cancer susceptibility.
Nat Commun. 2019; 10(1):2154 [PubMed] Article available free on PMC after 01/07/2020 Related Publications
Colorectal cancer (CRC) is a leading cause of cancer-related death worldwide, and has a strong heritable basis. We report a genome-wide association analysis of 34,627 CRC cases and 71,379 controls of European ancestry that identifies SNPs at 31 new CRC risk loci. We also identify eight independent risk SNPs at the new and previously reported European CRC loci, and a further nine CRC SNPs at loci previously only identified in Asian populations. We use in situ promoter capture Hi-C (CHi-C), gene expression, and in silico annotation methods to identify likely target genes of CRC SNPs. Whilst these new SNP associations implicate target genes that are enriched for known CRC pathways such as Wnt and BMP, they also highlight novel pathways with no prior links to colorectal tumourigenesis. These findings provide further insight into CRC susceptibility and enhance the prospects of applying genetic risk scores to personalised screening and prevention.

Shen ML, Xiao A, Yin SJ, et al.
Associations between UGT2B7 polymorphisms and cancer susceptibility: A meta-analysis.
Gene. 2019; 706:115-123 [PubMed] Related Publications
BACKGROUND: UGT2B7 was recently acknowledged as a new critical enzyme involved in biotransformation of a variety of carcinogens, whose function was reported to be significantly associated with its encoding gene (UGT2B7) polymorphisms. However, results regarding the associations between single nucleotide polymorphisms (SNPs) of UGT2B7 and cancer risk still remained controversial. Therefore, a meta-analysis was conducted to further elucidate the role of UGT2B7 SNPs on cancer susceptibilities.
METHODS: PubMed, EMBASE, Cochrane library, Chinese National Knowledge Infrastructure (CNKI), Technology of Chongqing (VIP) and Wan Fang Database were searched for eligible studies until March 2019. All analysis was carried out using the Review Manager 5.3 software. Subgroup analyses were performed by cancer types, ethnicity or source of controls.
RESULTS: 13 studies with a total of 7688 cancer cases and 11,281 controls were included in this meta-analysis. The results showed that UGT2B7 rs7439366 increased the colorectal cancer risk in dominant model (OR = 0.76, 95% CI = 0.61-0.95, P = 0.02). However, as for the rs7435335 and rs12233719, we did not find their associations with cancer risk in all genetic models. In addition, the rs7441774 was found to be associated with breast cancer risk and significantly reduced papillary thyroid cancer risk in rs3924194 was also observed. Nevertheless, these findings remained to be further proven in future studies since these 2 SNPs were only respectively involved in 1 study.
CONCLUSION: This meta-analysis confirmed the association of UGT2B7 rs7439366 with colorectal cancer risk, which may be a potential promising biomarker for prediction of colorectal cancer risk.

Khodadadi Kohlan A, Saidijam M, Amini R, et al.
Induction of let-7e gene expression attenuates oncogenic phenotype in HCT-116 colorectal cancer cells through targeting of DCLK1 regulation.
Life Sci. 2019; 228:221-227 [PubMed] Related Publications
AIMS: MicroRNAs (miRNAs) are small noncoding RNAs that negatively control gene expression at the translational level. There are compelling evidences indicating that the expression of let-7e is downregulated in various cancers, however, the role of let-7e in colorectal cancer (CRC) and its mechanism has been remained unknown. Here, we investigated the potential role of let-7e in regulating CRC cells phenotypes.
MAIN METHODS: Let-7e and DCLK1 siRNA were transfected in HCT-116 cells. Colony formation assay, scratch test, Annexin V/PI flow cytometry, and sphere formation assay were performed to examine the cell proliferation, migration, apoptosis, and stemness, respectively. The expression of let-7e, epithelial-mesenchymal transition (EMT)-related genes, Doublecortin like kinase protein 1 (DCLK1), and cancer stem cells (CSCs) were assessed using RT-qPCR while the protein level of DCLK1 was determined by western blotting.
KEY FINDINGS: Overexpression of let-7e effectively inhibited cell proliferation, suppressed migration, reduced sphere formation, and precluded EMT process as well as stemness factors. Furthermore, let-7e suppressed DCLK1 expression. Additionally, we found that the expression of let-7e was negatively correlated with DCLK1 expression in CRC cells.
SIGNIFICANCE: Let-7e plays an important role as tumor suppressor miRNA in CRC probably through inhibition of DCLK1 expression.

Ricci MT, Volorio S, Signoroni S, et al.
Development, technical validation, and clinical application of a multigene panel for hereditary gastrointestinal cancer and polyposis.
Tumori. 2019; 105(4):338-352 [PubMed] Related Publications
INTRODUCTION: Recent advances in technology and research are rapidly changing the diagnostic approach to hereditary gastrointestinal cancer (HGIC) syndromes. Although the practice of clinical genetics is currently transitioning from targeted criteria-based testing to multigene panels, important challenges remain to be addressed. The aim of this study was to develop and technically validate the performance of a multigene panel for HGIC.
METHODS: CGT-colon-G14 is an amplicon-based panel designed to detect single nucleotide variants and small insertions/deletions in 14 well-established or presumed high-penetrance genes involved in HGIC. The assay parameters tested were sensitivity, specificity, accuracy, and inter-run and intra-run reproducibility. Performance and clinical impact were determined using 48 samples of patients with suspected HGIC/polyposis previously tested with the targeted approach.
RESULTS: The CGT-colon-G14 panel showed 99.99% accuracy and 100% inter- and intra-run reproducibility. Moreover, panel testing detected 1 actionable pathogenic variant and 16 variants with uncertain clinical impact that were missed by the conventional approach because they were located in genes not previously analyzed.
CONCLUSION: Introduction of the CGT-colon-G14 panel into the clinic could provide a higher diagnostic yield than a step-wise approach; however, results may not always be straightforward without the implementation of new genetic counseling models.

Recurrent Structural Abnormalities

Selected list of common recurrent structural abnormalities

This is a highly selective list aiming to capture structural abnormalies which are frequesnt and/or significant in relation to diagnosis, prognosis, and/or characterising specific cancers. For a much more extensive list see the Mitelman Database of Chromosome Aberrations and Gene Fusions in Cancer.

del(8p) in Colorectal Cancers [incl del(8q21)]

Lerebours F, Olschwang S, Thuille B, et al.
Deletion mapping of the tumor suppressor locus involved in colorectal cancer on chromosome band 8p21.
Genes Chromosomes Cancer. 1999; 25(2):147-53 [PubMed] Related Publications
Several somatic genetic alterations have been described in colorectal carcinoma (CRC). Recurrent chromosomal deletions have suggested the presence of tumor suppressor genes (TSG) specifically involved in colorectal carcinogenesis. For one of them, two non-overlapping regions have been proposed on the short arm of chromosome 8, encompassing the LPL and NEFL genes. The short arm of chromosome 8 has been extensively studied in colorectal cancer and in other cancer types. Both regions have been reported as candidate loci for a TSG. In order to delineate a reliable region of deletional overlap on chromosome arm 8p in CRC, a series of 365 CRC samples was selected for the absence of microsatellite instability (RER, replication error); tumor and normal matched DNAs were studied for 54 microsatellite polymorphisms distributed on 8p using multiplex-PCR amplification. After purification of tumor nuclei by flow cytometry based on either the abnormal DNA index or the presence of a high expression of cytokeratin, complete allelic losses on 8p were observed in 48% of cases. Measurement of the DNA index showed that 88% of RER tumors were hyperploid. Complete allelic losses of only part of the short arm were observed on 26 occasions. These data allowed us to define a 1 cM interval of common deletion, flanked by the loci D8S1771 and NEFL, where a putative TSG may be localized.

Fujiwara Y, Emi M, Ohata H, et al.
Evidence for the presence of two tumor suppressor genes on chromosome 8p for colorectal carcinoma.
Cancer Res. 1993; 53(5):1172-4 [PubMed] Related Publications
We have examined loss of heterozygosity on the short arm of chromosome 8 in 133 colorectal carcinomas, using 20 restriction fragment length polymorphism markers. Loss of heterozygosity was observed in 58 (44%) of 131 tumors that were informative with at least one locus. Among these 58, 32 revealed a partial or interstitial deletion of chromosome 8p. Detailed deletion mapping of chromosome 8p in these tumors identified two distinct, commonly deleted regions. One was located between markers C18-266 and pSVL-LPL at 8p23.2-8p22, and the other between CI8-319 and CI8-494 at 8p21.3-8p11.22. The genetic lengths of these two intervals were estimated to be 28 and 18 cM, respectively. The results suggest that at least two tumor suppressor genes associated with colorectal carcinomas are present on chromosome 8p. Correlation of loss of heterozygosity on 8p to the clinicopathological stage was also detected, suggesting that inactivation of a tumor suppressor gene(s) on 8p plays a role in progression of colorectal carcinomas.

18q Loss in Colorectal Cancer

Ogunbiyi OA, Goodfellow PJ, Herfarth K, et al.
Confirmation that chromosome 18q allelic loss in colon cancer is a prognostic indicator.
J Clin Oncol. 1998; 16(2):427-33 [PubMed] Related Publications
PURPOSE: Recent studies suggest that allelic loss of sequences from the long arm of chromosome 18 may be a useful prognostic indicator in colorectal cancer. The aim of the present study was to confirm whether 18q loss of heterozygosity (LOH) is of prognostic value in patients with colon cancer.
METHODS: Genomic DNA was prepared from archival tumor and corresponding normal tissue specimens from 151 patients who had undergone potentially curative surgery for adenocarcinoma of the colon. Polymerase chain reaction (PCR) was used to assess allelic loss of five chromosome 18q microsatellite markers in the tumors. The relationship between allelic loss and disease-free and disease-specific survival was investigated.
RESULTS: LOH was detected in 67 of 126 tumors. Chromosome 18q allelic loss was a negative prognostic indicator of both disease-free (relative risk [RR], 1.65; P = .01) and disease-specific survival (RR, 2.0; P = .003). 18q loss was also associated with significantly reduced disease-free and disease-specific survival in patients with stage II (P = .05 and P = .0156) and III (P = .038 and P = .032) disease.
CONCLUSION: Chromosome 18q allelic loss is a prognostic marker in colorectal cancers. Chromosome 18 LOH studies may be useful in identifying patients with stage II disease who are at high risk for recurrence, and as such might benefit from adjuvant chemotherapy.

Lindforss U, Fredholm H, Papadogiannakis N, et al.
Allelic loss is heterogeneous throughout the tumor in colorectal carcinoma.
Cancer. 2000; 88(12):2661-7 [PubMed] Related Publications
BACKGROUND: Loss of heterozygosity (LOH) at 17p and 18q in colorectal carcinoma has been depicted as a potential prognostic marker for the disease. However, conclusions vary among reports, and evidence of clinically useful genetic prognostic markers is still lacking. As a rule, single biopsies are used. In this study, the authors hypothesized that an important cause of earlier contradictory results was the heterogeneity of colorectal neoplasms.
METHODS: In this study, DNA originating in each quadrant of tumors from 64 patients with colorectal carcinoma was analyzed. Microsatellite markers for chromosome 18q and 17p were amplified by polymerase chain reaction and automatically analyzed.
RESULTS: The authors found that, regardless of stage, LOH and non-LOH in both 17p and 18q varied among biopsies within the tumors in a random fashion. LOH in 18q was detected in all 4 quadrants in 22% and in 1 of 4, 2 of 4, or 3 of 4 quadrants in 56% of the tumors, whereas 22% of the tumors were homogeneously without LOH in 18q. LOH 17p was distributed similarly throughout the tumors and was present in 1 of 4, 2 of 4, or 3 of 4 of the quadrants in 44%. The authors also reexamined a subset of tumors by subdividing one biopsy from each into four. Analysis of the microsatellite markers then yielded identical results. No correlation between the degree of LOH status and patient survival was observed.
CONCLUSIONS: LOH status within a colorectal tumor is extensively heterogeneous. However, it is more homologous on a lower macroscopic level. For relevant genetic analysis, multiple biopsies and DNA sampling preceded by careful morphologic examination must be standard in the preparation of DNA.

LOH 17p in Colorectal Cancer

Khine K, Smith DR, Goh HS
High frequency of allelic deletion on chromosome 17p in advanced colorectal cancer.
Cancer. 1994; 73(1):28-35 [PubMed] Related Publications
BACKGROUND: Colorectal cancers often show allelic loss of chromosomes 5q and 17p, regions where the tumor suppressor genes p53 and adenomatous polyposis coli are known to reside. Currently, the inactivation of tumor suppressor genes and the activation of oncogenes are considered major events involved in tumor development. According to a recent genetic model, ras gene mutations and allelic deletion of chromosome 5q are early changes, whereas chromosome 17p and 18q deletions are late changes in colorectal tumorigenesis. It has been shown that 17p and 18q deletions are associated with an increased tendency of disease dissemination in colorectal cancer. Most of the studies on allelic deletion in colorectal cancer were undertaken with Western population cohorts. The authors examined the association of chromosomes 5q and 17p deletions with clinical parameters, including metastasis in a predominantly Chinese population with a high incidence of colorectal cancer.
METHOD: Allelic deletion was studied with the restriction fragment length polymorphism technique in tumors from 102 and 100 sporadic colorectal cancer cases for chromosomes 5q and 17p, respectively. Probes pi 227 and ECB27 were used for chromosome 5q, and probe YNZ22.1 was used for chromosome 17p.
RESULTS: 5q Deletion was found in 33% of informative cases, whereas 17p deletion was seen in 69% of informative cases. 17p Allelic loss showed significant association with Dukes' Stage D as well as the presence of distant metastasis, whereas 5q deletion showed no such association.
CONCLUSION: Allelic loss on chromosome 17p may be a useful prognostic marker in cases of colorectal cancer.

Takanishi DM, Angriman I, Yaremko ML, et al.
Chromosome 17p allelic loss in colorectal carcinoma. Clinical significance.
Arch Surg. 1995; 130(6):585-8; discussion 588-9 [PubMed] Related Publications
OBJECTIVE: To correlate allelic losses on chromosomes 5q, 8p, 17p, and 18q in colorectal adenocarcinomas with histopathologic features of known prognostic significance.
DESIGN: DNA was extracted from paired samples of 56 fresh-frozen colorectal adenocarcinomas (one classified as Dukes' stage A, 22 as Dukes' stage B, 27 as Dukes' stage C, and six as Dukes'stage D) and adjacent normal mucosa.
SETTING: Specimens were resected at the University of Chicago (Ill) and the University of Padova (Italy) in 1991.
PATIENTS: Samples were obtained from consecutive patients.
INTERVENTIONS: Chromosomes 5q, 8p, 17p, and 18q were studied for loss of heterozygosity by means of Southern hybridization blot analysis of restriction fragment length polymorphisms, and the results were correlated with pathologic tumor stage, degree of differentiation, and lymphatic and/or vascular microinvasion.
RESULTS: Chromosomes 17p and 18q exhibited the highest frequency of loss of heterozygosity (40.6% and 48.8%, respectively). Most of the allelic losses were found in advanced tumors (60% in Dukes' stages C and D combined). A statistically significant correlation was found between loss of heterozygosity on chromosome 17p and the presence of lymphatic and/or vascular microinvasion (P < .01, Fisher's Exact Test).
CONCLUSIONS: There was a significant correlation between loss of heterozygosity on chromosome 17p and the presence of lymphatic and/or vascular microinvasion in colorectal adenocarcinoma, a known stage-independent negative prognostic risk factor. Detection of loss of heterozygosity on chromosome 17p may identify a group of patients who may benefit from more aggressive surgical and/or early adjuvant therapy.

Lindforss U, Fredholm H, Papadogiannakis N, et al.
Allelic loss is heterogeneous throughout the tumor in colorectal carcinoma.
Cancer. 2000; 88(12):2661-7 [PubMed] Related Publications
BACKGROUND: Loss of heterozygosity (LOH) at 17p and 18q in colorectal carcinoma has been depicted as a potential prognostic marker for the disease. However, conclusions vary among reports, and evidence of clinically useful genetic prognostic markers is still lacking. As a rule, single biopsies are used. In this study, the authors hypothesized that an important cause of earlier contradictory results was the heterogeneity of colorectal neoplasms.
METHODS: In this study, DNA originating in each quadrant of tumors from 64 patients with colorectal carcinoma was analyzed. Microsatellite markers for chromosome 18q and 17p were amplified by polymerase chain reaction and automatically analyzed.
RESULTS: The authors found that, regardless of stage, LOH and non-LOH in both 17p and 18q varied among biopsies within the tumors in a random fashion. LOH in 18q was detected in all 4 quadrants in 22% and in 1 of 4, 2 of 4, or 3 of 4 quadrants in 56% of the tumors, whereas 22% of the tumors were homogeneously without LOH in 18q. LOH 17p was distributed similarly throughout the tumors and was present in 1 of 4, 2 of 4, or 3 of 4 of the quadrants in 44%. The authors also reexamined a subset of tumors by subdividing one biopsy from each into four. Analysis of the microsatellite markers then yielded identical results. No correlation between the degree of LOH status and patient survival was observed.
CONCLUSIONS: LOH status within a colorectal tumor is extensively heterogeneous. However, it is more homologous on a lower macroscopic level. For relevant genetic analysis, multiple biopsies and DNA sampling preceded by careful morphologic examination must be standard in the preparation of DNA.

del(1p) in Colorectal Cancer

Matsuzaki M, Nagase S, Abe T, et al.
Detailed deletion mapping on chromosome 1p32-p36 in human colorectal cancer: identification of three distinct regions of common allelic loss.
Int J Oncol. 1998; 13(6):1229-33 [PubMed] Related Publications
Recent studies have suggested the existence of one or several tumor-suppressor genes on chromosome arm 1p in colorectal tumors. To determine the localization of the putative tumor suppressor genes, we performed LOH analysis in 1p in colorectal tumors. A total of 48 paired normal and tumor DNAs of 46 colorectal tumor patients and 21 microsatellite markers on 1p32.1-p36.3 were used for PCR-LOH analysis. Three commonly deleted regions were found: i) 1p36.3 (10-cm); ii) 1p35.1-p36.3 (2-cm); and iii) 1p34.2-p35 (1-cm). These regions overlapped with those reported in several types of tumor. No significant associations were found between LOH and clinicopathologic features. The regions identified in the present study could harbor tumor suppressor genes that would also be associated with several types of human cancer.

Di Vinci A, Infusini E, Nigro S, et al.
Intratumor distribution of 1p deletions in human colorectal adenocarcinoma is commonly homogeneous: indirect evidence of early involvement in colorectal tumorigenesis.
Cancer. 1998; 83(3):415-22 [PubMed] Related Publications
BACKGROUND: Cytogenetics and molecular biology studies have indicated that a large subset of human colorectal adenocarcinomas have distal 1p chromosome arm deletions. The aim of this study was to evaluate the intratumor distribution of 1p deletions under the assumption that homogeneity is an indication of early occurrence.
METHODS: Seventy-nine histologically selected primary sectors (40 superficial and 39 deep) and 3 lymph node metastases obtained from 20 human sporadic adenocarcinomas were analyzed. Interphase two-color fluorescence in situ hybridization (FISH) was applied to cytocentrifuged nuclei using a centromeric probe for chromosome 1 and a telomeric probe mapping to the 1p36 band.
RESULTS: Deletions at 1p were observed in 35 of 82 tumor samples corresponding to 9 of 20 adenocarcinomas analyzed (45%). Seven of the 9 adenocarcinomas with 1p deletions showed an intratumor presence of these aberrations in all the different tumor sectors.
CONCLUSIONS: These data, acquired by FISH interphase cytogenetics, confirm that 1p deletions in colorectal adenocarcinoma are common and suggest that this structural chromosomal aberration occurs mainly as an early event in colorectal tumorigenesis.

LOH 5q in Colorectal Cancer

Arnold CN, Goel A, Niedzwiecki D, et al.
APC promoter hypermethylation contributes to the loss of APC expression in colorectal cancers with allelic loss on 5q.
Cancer Biol Ther. 2004; 3(10):960-4 [PubMed] Related Publications
INTRODUCTION: Germ-line mutations of the APC gene are associated with familial adenomatous polyposis, and somatic mutations occur frequently in sporadic colorectal cancer. However, to abrogate APC function, both alleles must be inactivated. Recently, it has been demonstrated that epigenetic modification of the APC promoter influences APC silencing. Here we examined the influence of APC methylation on APC expression in tumors with and without LOH at the APC locus.
MATERIAL AND METHODS: 137 sporadic colorectal cancer specimens were investigated for LOH at the 5q locus. The methylation status of the APC promoter was determined by methylation-specific PCR. APC expression was performed by immunohistochemistry.
RESULTS: Expression was reduced or lost in 110 of 137 (80%) tumors and LOH at 5q was found in 13 of 132 (10%) tumors. There was no difference in 5q LOH between tumors with or without intact APC expression. Vice versa, there was no difference in the APC expression in tumors with 5q LOH. Aberrant APC promoter methylation was detected in 33 of 118 (28%) tumors investigated. Of the tumors with 5q LOH for which methylation data were available, 4 of 11 (36%) were methylated versus 28 of 105 (27%) of those without LOH. No difference in methylation was observed in tumors without 5q LOH and normal APC expression and those without 5q LOH and reduced or missing APC expression. Importantly, none of the tumors with 5q LOH and normal APC staining were aberrantly methylated, whereas 50% of the cancers with LOH at 5q and reduced or absent staining were hypermethylated.
CONCLUSIONS: This report suggests that tumors with 5q LOH and reduced APC expression are more frequently hypermethylated at the APC promoter compared to those tumors with 5q LOH and normal APC expression. The association among APC promoter methylation status, 5q LOH, and reduced or lost APC expression suggests that de novo methylation plays an important role as a "second hit" in silencing APC expression in colorectal neoplasia.

Sugai T, Habano W, Nakamura S, et al.
Allelic losses of 17p, 5q, and 18q loci in diploid and aneuploid populations of multiploid colorectal carcinomas.
Hum Pathol. 2000; 31(8):925-30 [PubMed] Related Publications
17p, 5q, and 18q allelic losses are involved in the pathogenesis and progression of colorectal carcinoma, and DNA aneuploidy in this type of cancer is thought to result from alterations of these chromosomal loci. However, genetic differences between diploid and aneuploid populations of multiploid carcinoma, defined as the coexistence of diploid and aneuploid populations in the same area, remain unclear. The differences in 17p, 5q, and 18q allelic losses between the diploid and aneuploid populations in 24 sporadic DNA multiploid colorectal carcinomas were analyzed by use of crypt isolation coupled with DNA cytometric sorting and polymerase chain reaction assay. 17p Allelic loss was observed in 7 of 22 diploid populations excluding 1 case of microsatellite instability but was found in 21 of 23 aneuploid populations. Although 5q allelic loss was detected in only 3 of 22 diploid populations, 13 of 22 aneuploid populations had 5q allelic loss. Losses of the 18q allele were frequently found in aneuploid populations (15 of 20), although no 18q allelic loss was detected in corresponding diploid populations. 17p Allelic losses may play an important role in the progression from a diploid status to an aneuploid status in a specific subset of colorectal cancer. However, 18q or 5q allelic losses do not appear to precede nor to facilitate the aneuploid clonal divergence of cancer cells. Multiploidy is a useful model to study genetic alterations between diploid and aneuploid populations.

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