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 08 August, 2015 using data from PubMed, MeSH and CancerIndex

Mutated Genes and Abnormal Protein Expression (482)

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 5q21-q22 GS, DP2, DP3, BTPS2, DP2.5, PPP1R46 -APC and Colorectal Cancer
2273
KRAS 12p12.1 NS, NS3, CFC2, KRAS1, KRAS2, RASK2, KI-RAS, C-K-RAS, K-RAS2A, K-RAS2B, K-RAS4A, K-RAS4B -KRAS and Colorectal Cancer
1547
MSH2 2p21 FCC1, COCA1, HNPCC, LCFS2, HNPCC1 -MSH2 and Colorectal Cancer
1414
BRAF 7q34 NS7, BRAF1, RAFB1, B-RAF1 -BRAF and Colorectal Cancer
1092
MLH1 3p21.3 FCC2, COCA2, HNPCC, hMLH1, HNPCC2 Germline
-MLH1 and Lynch Syndrome
1080
CTNNB1 3p21 CTNNB, MRD19, armadillo -CTNNB1 and Colorectal Cancer
1013
PTGS2 1q25.2-q25.3 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
360
EGFR 7p12 ERBB, HER1, mENA, ERBB1, PIG61, NISBD2 -EGFR and Colorectal Cancer
734
MSH6 2p16 GTBP, HSAP, p160, GTMBP, HNPCC5 -MSH6 and Colorectal Cancer
499
TP53 17p13.1 P53, BCC7, LFS1, TRP53 -TP53 and Colorectal Cancer
489
CDKN2A 9p21 ARF, MLM, P14, P16, P19, CMM2, INK4, MTS1, TP16, CDK4I, CDKN2, INK4A, MTS-1, P14ARF, P19ARF, P16INK4, P16INK4A, P16-INK4A -CDKN2A and Colorectal Cancer
352
CEACAM5 19q13.1-q13.2 CEA, CD66e -CEACAM5 and Colorectal Cancer
330
DCC 18q21.3 CRC18, CRCR1, MRMV1, IGDCC1, NTN1R1 -DCC and Colorectal Cancer
279
PIK3CA 3q26.3 MCM, CWS5, MCAP, PI3K, CLOVE, MCMTC, p110-alpha -PIK3CA and Colorectal Cancer
267
MTHFR 1p36.3 -MTHFR mutations and polymorphisms and Colorectal Cancer
237
PPARG 3p25 GLM1, CIMT1, NR1C3, PPARG1, PPARG2, PPARgamma -PPARG and Colorectal Cancer
232
CDKN1A 6p21.2 P21, CIP1, SDI1, WAF1, CAP20, CDKN1, MDA-6, p21CIP1 Prognostic
-CDKN1A Expression in Colorectal Cancer
228
MUTYH 1p34.1 MYH -MUTYH and Colorectal Cancer
191
SMAD4 18q21.1 JIP, DPC4, MADH4, MYHRS -SMAD4 and Colorectal Cancer
189
MYC 8q24.21 MRTL, MYCC, c-Myc, bHLHe39 -MYC and Colorectal Cancer
165
TCF4 18q21.1 E2-2, ITF2, PTHS, SEF2, ITF-2, SEF-2, TCF-4, SEF2-1, SEF2-1A, SEF2-1B, SEF2-1D, bHLHb19 -TCF4 and Colorectal Cancer
145
GSTM1 1p13.3 MU, H-B, GST1, GTH4, GTM1, MU-1, GSTM1-1, GSTM1a-1a, GSTM1b-1b -GSTM1 and Colorectal Cancer
142
TGFBR2 3p22 AAT3, FAA3, LDS2, MFS2, RIIC, LDS1B, LDS2B, TAAD2, TGFR-2, TGFbeta-RII -TGFBR2 and Colorectal Cancer
136
BRCA1 17q21 IRIS, PSCP, BRCAI, BRCC1, FANCS, PNCA4, RNF53, BROVCA1, PPP1R53 -BRCA1 germliine mutation and increased risk of Colorectal Cancer?
128
BAX 19q13.3-q13.4 BCL2L4 -BAX and Colonic Neoplasms
122
NRAS 1p13.2 NS6, CMNS, NCMS, ALPS4, N-ras, NRAS1 -NRAS and Colorectal Cancer
121
UGT1A1 2q37 GNT1, UGT1, UDPGT, UGT1A, HUG-BR1, BILIQTL1, UDPGT 1-1 -UGT1A1 and Colorectal Cancer
117
VEGFA 6p12 VPF, VEGF, MVCD1 -VEGFA and Colorectal Cancer
116
NODAL 10q22.1 HTX5 -NODAL and Colorectal Cancer
113
PCNA 20pter-p12 ATLD2 -PCNA and Colorectal Cancer
111
IGF2 11p15.5 IGF-II, PP9974, C11orf43 -IGF2 and Colorectal Cancer
98
TCF7L2 10q25.3 TCF4, TCF-4 -TCF7L2 and Colorectal Cancer
97
NAT2 8p22 AAC2, PNAT, NAT-2 -NAT2 and Colorectal Cancer
97
CDX2 13q12.3 CDX3, CDX-3, CDX2/AS -CDX2 and Colorectal Cancer
96
MSH3 5q14.1 DUP, MRP1 -MSH3 and Colorectal Cancer
93
GSTT1 22q11.23 -GSTT1 and Colorectal Cancer
90
MCC 5q21 MCC1 -MCC and Colorectal Cancer
90
MMP2 16q12.2 CLG4, MONA, CLG4A, MMP-2, TBE-1, MMP-II -MMP2 and Colorectal Cancer
89
XRCC1 19q13.2 RCC -XRCC1 and Colorectal Cancer
87
MUC2 11p15.5 MLP, SMUC, MUC-2 -MUC2 and Colorectal Cancer
81
CDH1 16q22.1 UVO, CDHE, ECAD, LCAM, Arc-1, CD324 -CDH1 and Colorectal Cancer
77
MET 7q31 HGFR, AUTS9, RCCP2, c-Met -C-MET and Colorectal Cancer
77
S100A4 1q21 42A, 18A2, CAPL, FSP1, MTS1, P9KA, PEL98 -S100A4 and Colorectal Cancer
-S100A4 and Colorectal Cancer
59
RUNX3 1p36 AML2, CBFA3, PEBP2aC -RUNX3 and Colorectal Cancer
72
MUC1 1q21 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
71
CDKN1B 12p13.1-p12 KIP1, MEN4, CDKN4, MEN1B, P27KIP1 Prognostic
-CDKN1B and Colorectal Cancer
68
MIR21 17q23.1 MIRN21, miR-21, miRNA21, hsa-mir-21 -MicroRNA miR-21 and Colorectal Cancer
67
SMAD2 18q21.1 JV18, MADH2, MADR2, JV18-1, hMAD-2, hSMAD2 -SMAD2 and Colorectal Cancer
64
TGFBR1 9q22 AAT5, ALK5, ESS1, LDS1, MSSE, SKR4, ALK-5, LDS1A, LDS2A, TGFR-1, ACVRLK4, tbetaR-I -TGFBR1 and Colorectal Cancer
63
PMS1 2q31.1 PMSL1, hPMS1, HNPCC3 -PMS1 and Colorectal Cancer
60
TGFA 2p13 TFGA -TGFA and Colonic Neoplasms
56
FOS 14q24.3 p55, AP-1, C-FOS -FOS and Colonic Neoplasms
52
CHEK2 22q12.1 CDS1, CHK2, LFS2, RAD53, hCds1, HuCds1, PP1425 -CHEK2 and Colorectal Cancer
51
IGFBP3 7p12.3 IBP3, BP-53 -IGFBP3 and Colorectal Cancer
50
ABCC1 16p13.1 MRP, ABCC, GS-X, MRP1, ABC29 -ABCC1 (MRP1) and Colorectal Cancer
50
CACNA1G 17q22 NBR13, Cav3.1, Ca(V)T.1 -CACNA1G and Colorectal Cancer
49
NEUROG1 5q23-q31 AKA, ngn1, Math4C, bHLHa6, NEUROD3 -NEUROG1 and Colorectal Cancer
49
SOCS1 16p13.13 JAB, CIS1, SSI1, TIP3, CISH1, SSI-1, SOCS-1 -SOCS1 and Colorectal Cancer
48
DNMT1 19p13.2 AIM, DNMT, MCMT, CXXC9, HSN1E, ADCADN -DNMT1 and Colorectal Cancer
47
DNMT3B 20q11.2 ICF, ICF1, M.HsaIIIB -DNMT3B and Colorectal Cancer
47
ERCC2 19q13.3 EM9, TTD, XPD, COFS2, TFIIH -ERCC2 and Colorectal Cancer
46
EPCAM 2p21 ESA, KSA, M4S1, MK-1, DIAR5, EGP-2, EGP40, KS1/4, MIC18, TROP1, EGP314, HNPCC8, TACSTD1 -EPCAM and Colorectal Cancer
46
AXIN2 17q24.1 AXIL, ODCRCS -AXIN2 and Colorectal Cancer
45
BMPR1A 10q22.3 ALK3, SKR5, CD292, ACVRLK3, 10q23del -BMPR1A and Colorectal Cancer
45
NAT1 8p22 AAC1, MNAT, NATI, NAT-1 -NAT1 and Colorectal Cancer
43
TYMS 18p11.32 TS, TMS, HST422 -TYMS and Colorectal Cancer
42
DPYD 1p22 DHP, DPD, DHPDHASE -DPYD and Colorectal Cancer
38
KRT20 17q21.2 K20, CD20, CK20, CK-20, KRT21 -KRT20 and Colorectal Cancer
38
SFRP1 8p11.21 FRP, FRP1, FrzA, FRP-1, SARP2 -SFRP1 and Colorectal Cancer
38
LGR5 12q22-q23 FEX, HG38, GPR49, GPR67, GRP49 -LGR5 and Colorectal Cancer
38
OGG1 3p26.2 HMMH, MUTM, OGH1, HOGG1 -OGG1 and Colorectal Cancer
38
TNFRSF10B 8p22-p21 DR5, CD262, KILLER, TRICK2, TRICKB, ZTNFR9, TRAILR2, TRICK2A, TRICK2B, TRAIL-R2, KILLER/DR5 -TNFRSF10B and Colonic Neoplasms
38
TGFB1 19q13.1 CED, LAP, DPD1, TGFB, TGFbeta -TGFB1 and Colorectal Cancer
37
CRABP1 15q24 RBP5, CRABP, CRABPI, CRABP-I -CRABP1 and Colorectal Cancer
37
FLT1 13q12 FLT, FLT-1, VEGFR1, VEGFR-1 -FLT1 and Colorectal Cancer
36
ESR1 6q25.1 ER, ESR, Era, ESRA, ESTRR, NR3A1 -ESR1 and Colorectal Cancer
36
NQO1 16q22.1 DTD, QR1, DHQU, DIA4, NMOR1, NMORI -NQO1 and Colorectal Cancer
35
PPARD 6p21.2 FAAR, NUC1, NUCI, NR1C2, NUCII, PPARB -PPAR delta and Colorectal Cancer
35
PTGS1 9q32-q33.3 COX1, COX3, PHS1, PCOX1, PES-1, PGHS1, PTGHS, PGG/HS, PGHS-1 -PTGS1 and Colorectal Cancer
34
THBS1 15q15 TSP, THBS, TSP1, TSP-1, THBS-1 -THBS1 and Colorectal Cancer
34
GAPDH 12p13 G3PD, GAPD, HEL-S-162eP -GAPDH and Colorectal Cancer
34
CYP1A2 15q24.1 CP12, P3-450, P450(PA) -CYP1A2 and Colorectal Cancer
33
RAC1 7p22 MIG5, Rac-1, TC-25, p21-Rac1 -RAC1 and Colorectal Cancer
33
XRCC3 14q32.3 CMM6 -XRCC3 and Colorectal Cancer
32
CHFR 12q24.33 RNF116, RNF196 -CHFR and Colorectal Cancer
31
LOX 5q23.2 -LOX and Colorectal Cancer
30
MMP7 11q22.2 MMP-7, MPSL1, PUMP-1 -MMP7 and Colorectal Cancer
29
MLH3 14q24.3 HNPCC7 -MLH3 and Colorectal Cancer
28
SFRP2 4q31.3 FRP-2, SARP1, SDF-5 -SFRP2 and Colorectal Cancer
28
EPHB2 1p36.1-p35 DRT, EK5, ERK, CAPB, Hek5, PCBC, EPHT3, Tyro5 -EPHB2 and Colorectal Cancer
28
EPHX1 1q42.1 MEH, EPHX, EPOX, HYL1 -EPHX1 and Colorectal Cancer
28
XIAP Xq25 API3, ILP1, MIHA, XLP2, BIRC4, IAP-3, hIAP3, hIAP-3 -XIAP and Colonic Neoplasms
28
FOXP3 Xp11.23 JM2, AIID, IPEX, PIDX, XPID, DIETER -FOXP3 and Colorectal Cancer
27
IGF1 12q23.2 IGFI, IGF-I, IGF1A -IGF1 and Colorectal Cancer
27
FBXW7 4q31.3 AGO, CDC4, FBW6, FBW7, hAgo, FBX30, FBXW6, SEL10, hCdc4, FBXO30, SEL-10 -FBXW7 and Colorectal Cancer
26
MUC5AC 11p15.5 TBM, leB, MUC5 -MUC5AC and Colorectal Cancer
26
TIMP3 22q12.3 SFD, K222, K222TA2, HSMRK222 -TIMP3 and Colorectal Cancer
26
CYP2C9 10q24 CPC9, CYP2C, CYP2C10, CYPIIC9, P450IIC9 -CYP2C9 and Colorectal Cancer
26
POLE 12q24.3 FILS, POLE1, CRCS12 -POLE and Colorectal Cancer
25
PTP4A3 8q24.3 PRL3, PRL-3, PRL-R -PTP4A3 and Colorectal Cancer
25
ALDH2 12q24.2 ALDM, ALDHI, ALDH-E2 -ALDH2 and Colorectal Cancer
25
RAD50 5q31 NBSLD, RAD502, hRad50 -RAD50 and Colorectal Cancer
24
NOS2 17q11.2 NOS, INOS, NOS2A, HEP-NOS -NOS2 and Colorectal Cancer
24
HIC1 17p13.3 hic-1, ZBTB29, ZNF901 -HIC1 and Colorectal Cancer
24
CLDN1 3q28-q29 CLD1, SEMP1, ILVASC -CLDN1 and Colorectal Cancer
23
TLR4 9q33.1 TOLL, CD284, TLR-4, ARMD10 -TLR4 and Colorectal Cancer
23
MIR126 9q34.3 MIRN126, mir-126, miRNA126 -MicroRNA mir-126 and Colorectal Cancer
23
CDX1 5q32 -CDX1 and Colorectal Cancer
23
IRS1 2q36 HIRS-1 -IRS1 and Colorectal Cancer
23
TWIST1 7p21.2 CRS, CSO, SCS, ACS3, CRS1, BPES2, BPES3, TWIST, bHLHa38 -TWIST1 and Colorectal Cancer
22
BMP4 14q22-q23 ZYME, BMP2B, OFC11, BMP2B1, MCOPS6 -BMP4 and Colorectal Cancer
22
MRE11A 11q21 ATLD, HNGS1, MRE11, MRE11B -MRE11A and Colorectal Cancer
21
EXO1 1q43 HEX1, hExoI -EXO1 and Colorectal Cancer
21
SEPT9 17q25 MSF, MSF1, NAPB, SINT1, PNUTL4, SeptD1, AF17q25 -SEPT9 and Colorectal Cancer
20
TIAM1 21q22.11 -TIAM1 and Colorectal Cancer
20
LEF1 4q23-q25 LEF-1, TCF10, TCF7L3, TCF1ALPHA -LEF1 and Colonic Neoplasms
20
AREG 4q13.3 AR, SDGF, AREGB, CRDGF -AREG and Colorectal Cancer
19
SMO 7q32.3 Gx, SMOH, FZD11 -SMO and Colorectal Cancer
19
MTRR 5p15.31 MSR, cblE -MTRR and Colorectal Cancer
19
ZEB1 10p11.2 BZP, TCF8, AREB6, FECD6, NIL2A, PPCD3, ZFHEP, ZFHX1A, DELTAEF1 -ZEB1 and Colonic Neoplasms
19
SOX9 17q24.3 CMD1, SRA1, CMPD1 -SOX9 and Colorectal Cancer
19
WIF1 12q14.3 WIF-1 -WIF1 and Colorectal Cancer
19
HLTF 3q25.1-q26.1 ZBU1, HLTF1, RNF80, HIP116, SNF2L3, HIP116A, SMARCA3 -HLTF and Colorectal Cancer
19
CCK 3p22.1 -CCK and Colonic Neoplasms
19
BUB1 2q14 BUB1A, BUB1L, hBUB1 -BUB1 and Colorectal Cancer
18
NOD2 16q21 CD, ACUG, BLAU, IBD1, NLRC2, NOD2B, CARD15, CLR16.3, PSORAS1 -NOD2 and Colorectal Cancer
18
E2F4 16q22.1 E2F-4 -E2F4 and Colorectal Cancer
18
BMP2 20p12 BDA2, BMP2A -BMP2 and Colorectal Cancer
18
MBD4 3q21.3 MED1 -MBD4 and Colorectal Cancer
17
HFE 6p21.3 HH, HFE1, HLA-H, MVCD7, TFQTL2 -HFE and Colorectal Cancer
17
CLOCK 4q12 KAT13D, bHLHe8 -CLOCK and Colorectal Cancer
17
BNIP3 10q26.3 NIP3 -BNIP3 and Colorectal Cancer
17
WNT3A 1q42 -WNT3A and Colorectal Cancer
16
ADIPOQ 3q27 ACDC, ADPN, APM1, APM-1, GBP28, ACRP30, ADIPQTL1 -ADIPOQ and Colorectal Cancer
16
CXCL1 4q21 FSP, GRO1, GROa, MGSA, NAP-3, SCYB1, MGSA-a -CXCL1 and Colonic Neoplasms
16
CASR 3q13 CAR, FHH, FIH, HHC, EIG8, HHC1, NSHPT, PCAR1, GPRC2A, HYPOC1 -CASR and Colorectal Cancer
16
WRN 8p12 RECQ3, RECQL2, RECQL3 -WRN and Colorectal Cancer
16
AXIN1 16p13.3 AXIN, PPP1R49 -AXIN1 and Colorectal Cancer
16
TMEFF2 2q32.3 TR, HPP1, TPEF, TR-2, TENB2, CT120.2 -TMEFF2 and Colorectal Cancer
16
MACC1 7p21.1 7A5, SH3BP4L -MACC1 and Colorectal Cancer
15
CDH13 16q23.3 CDHH, P105 -CDH13 and Colorectal Cancer
15
KLF4 9q31 EZF, GKLF -KLF4 and Colonic Neoplasms
15
ALOX15 17p13.3 12-LOX, 15LOX-1, 15-LOX-1 -ALOX15 and Colorectal Cancer
15
IL17A 6p12 IL17, CTLA8, IL-17, IL-17A -IL17A and Colorectal Cancer
15
FASN 17q25 FAS, OA-519, SDR27X1 -FASN and Colorectal Cancer
15
ATF3 1q32.3 -ATF3 and Colorectal Cancer
15
APOE 19q13.2 AD2, LPG, APO-E, LDLCQ5 -APOE and Colorectal Cancer
14
IRS2 13q34 IRS-2 -IRS2 and Colorectal Cancer
14
ARHGEF1 19q13.13 LSC, GEF1, LBCL2, SUB1.5, P115-RHOGEF -ARHGEF1 and Colorectal Cancer
14
GSTA1 6p12.1 GST2, GTH1, GSTA1-1 -GSTA1 and Colorectal Cancer
14
PHIP 6q14 ndrp, BRWD2, WDR11, DCAF14 -PHIP and Colonic Neoplasms
14
BAG1 9p12 HAP, BAG-1, RAP46 Overexpression
Prognostic
-BAG1 overexpression in Colorectal Cancer
14
PLAUR 19q13 CD87, UPAR, URKR, U-PAR -PLAUR and Colonic Neoplasms
14
ALCAM 3q13.1 MEMD, CD166 -ALCAM and Colorectal Cancer
14
EREG 4q13.3 ER -EREG and Colorectal Cancer
13
GDF15 19p13.11 PDF, MIC1, PLAB, MIC-1, NAG-1, PTGFB, GDF-15 -GDF15 and Colorectal Cancer
13
REG4 1p13.1-p12 GISP, RELP, REG-IV -REG4 and Colorectal Cancer
13
FCGR3A 1q23 CD16, FCG3, CD16A, FCGR3, IGFR3, IMD20, FCR-10, FCRIII, FCGRIII, FCRIIIA -FCGR3A and Colorectal Cancer
13
MED1 17q12 PBP, CRSP1, RB18A, TRIP2, PPARBP, CRSP200, DRIP205, DRIP230, PPARGBP, TRAP220 -MED1 and Colorectal Cancer
13
CXCL2 4q21 GRO2, GROb, MIP2, MIP2A, SCYB2, MGSA-b, MIP-2a, CINC-2a -CXCL2 and Colorectal Cancer
13
IL17C 16q24 CX2, IL-17C -IL17C and Colorectal Cancer
13
YES1 18p11.31-p11.21 Yes, c-yes, HsT441, P61-YES -Proto-Oncogene Proteins c-yes and Colonic Neoplasms
13
TAP1 6p21.3 APT1, PSF1, ABC17, ABCB2, PSF-1, RING4, TAP1N, D6S114E, TAP1*0102N -TAP1 and Colorectal Cancer
13
GREM1 15q13.3 DRM, HMPS, MPSH, PIG2, CRAC1, CRCS4, DAND2, HMPS1, IHG-2, DUP15q, C15DUPq, GREMLIN, CKTSF1B1 -GREM1 and Colorectal Cancer
13
PLA2G2A 1p35 MOM1, PLA2, PLA2B, PLA2L, PLA2S, PLAS1, sPLA2 -PLA2G2A and Colorectal Cancer
12
PRINS 10p12.1 NCRNA00074 -PRINS and Colorectal Cancer
12
CCNA2 4q27 CCN1, CCNA -CCNA2 and Colorectal Cancer
12
B2M 15q21.1 -B2M and Colorectal Cancer
12
ESR2 14q23.2 Erb, ESRB, ESTRB, NR3A2, ER-BETA, ESR-BETA -ESR2 and Colorectal Cancer
12
KLF5 13q22.1 CKLF, IKLF, BTEB2 -KLF5 and Colorectal Cancer
12
IGFBP7 4q12 AGM, PSF, TAF, FSTL2, IBP-7, MAC25, IGFBP-7, RAMSVPS, IGFBP-7v, IGFBPRP1 -IGFBP7 and Colorectal Cancer
12
CTNNA1 5q31.2 CAP102 -CTNNA1 and Colonic Neoplasms
12
NFKB1 4q24 p50, KBF1, p105, EBP-1, NF-kB1, NFKB-p50, NFkappaB, NF-kappaB, NFKB-p105, NF-kappa-B -NFKB1 and Colorectal Cancer
12
LGALS1 22q13.1 GBP, GAL1 -LGALS1 and Colorectal Cancer
12
DKK1 10q11.2 SK, DKK-1 -DKK1 and Colonic Neoplasms
12
VIP 6q25 PHM27 -VIP and Colorectal Cancer
12
TCF3 19p13.3 E2A, E47, ITF1, VDIR, TCF-3, bHLHb21 -TCF3 and Colorectal Cancer
11
CCKBR 11p15.4 GASR, CCK-B, CCK2R -CCKBR and Colonic Neoplasms
11
ADH1B 4q23 ADH2, HEL-S-117 -ADH1B and Colorectal Cancer
11
TNFRSF10A 8p21 DR4, APO2, CD261, TRAILR1, TRAILR-1 -TNFRSF10A and Colorectal Cancer
11
IL4 5q31.1 BSF1, IL-4, BCGF1, BSF-1, BCGF-1 -IL4 and Colorectal Cancer
11
PTPN13 4q21.3 PNP1, FAP-1, PTP1E, PTPL1, PTPLE, PTP-BL, hPTP1E, PTP-BAS -PTPN13 and Colorectal Cancer
11
HMGB1 13q12 HMG1, HMG3, SBP-1 -HMGB1 and Colorectal Cancer
11
RASSF2 20p13 CENP-34, RASFADIN -RASSF2 and Colorectal Cancer
11
WNT2 7q31.2 IRP, INT1L1 -WNT2 and Colorectal Cancer
11
ABCC2 10q24 DJS, MRP2, cMRP, ABC30, CMOAT -ABCC2 and Colorectal Cancer
10
FPGS 9q34.1 -FPGS and Colorectal Cancer
10
TAP2 6p21.3 APT2, PSF2, ABC18, ABCB3, PSF-2, RING11, D6S217E -TAP2 and Colorectal Cancer
10
FOSL1 11q13 FRA, FRA1, fra-1 -FOSL1 and Colon Cancer
10
CYP24A1 20q13 CP24, HCAI, CYP24, P450-CC24 -CYP24A1 and Colonic Neoplasms
10
VIM 10p13 HEL113, CTRCT30 -VIM and Colorectal Cancer
10
TOP1 20q12-q13.1 TOPI -TOP1 and Colonic Neoplasms
10
CRP 1q23.2 PTX1 -CRP and Colorectal Cancer
10
CEACAM1 19q13.2 BGP, BGP1, BGPI -CEACAM1 and Colorectal Cancer
10
XAF1 17p13.1 BIRC4BP, XIAPAF1, HSXIAPAF1 -XAF1 and Colonic Neoplasms
10
TACSTD2 1p32 EGP1, GP50, M1S1, EGP-1, TROP2, GA7331, GA733-1 -TACSTD2 and Colorectal Cancer
10
REG1A 2p12 P19, PSP, PTP, REG, ICRF, PSPS, PSPS1 -REG1A and Colorectal Cancer
9
BCL9 1q21 LGS -BCL9 and Colorectal Cancer
9
PRDM2 1p36.21 RIZ, KMT8, RIZ1, RIZ2, MTB-ZF, HUMHOXY1 -PRDM2 and Colorectal Cancer
9
MYOD1 11p15.4 PUM, MYF3, MYOD, bHLHc1 -MYOD1 and Colorectal Cancer
9
WNT5A 3p21-p14 hWNT5A -WNT5A and Colonic Neoplasms
9
XRCC2 7q36.1 -XRCC2 and Colorectal Cancer
9
APAF1 12q23 CED4, APAF-1 -APAF1 and Colorectal Cancer
9
EPHB4 7q22 HTK, MYK1, TYRO11 -EPHB4 and Colorectal Cancer
9
PTPRJ 11p11.2 DEP1, SCC1, CD148, HPTPeta, R-PTP-ETA -PTPRJ and Colorectal Cancer
9
POLD1 19q13.3 CDC2, MDPL, POLD, CRCS10 -POLD1 and Colorectal Cancer
9
INSR 19p13.3-p13.2 HHF5, CD220 -INSR and Colorectal Cancer
9
KRT7 12q13.13 K7, CK7, SCL, K2C7 -KRT7 and Colorectal Cancer
8
FZD7 2q33 FzE3 -FZD7 and Colorectal Cancer
8
TAGLN 11q23.2 SM22, SMCC, TAGLN1, WS3-10 -TAGLN and Colorectal Cancer
8
CYP2A6 19q13.2 CPA6, CYP2A, CYP2A3, P450PB, CYPIIA6, P450C2A -CYP2A6 and Colorectal Cancer
8
ZNF217 20q13.2 ZABC1 -ZNF217 and Colorectal Cancer
8
SFRP4 7p14.1 FRP-4, FRPHE, sFRP-4 -SFRP4 and Colorectal Cancer
8
ADIPOR1 1q32.1 CGI45, PAQR1, ACDCR1, CGI-45, TESBP1A -ADIPOR1 and Colorectal Cancer
8
SLCO1B1 12p LST1, HBLRR, LST-1, OATP2, OATPC, OATP-C, OATP1B1, SLC21A6 -SLCO1B1 and Colorectal Cancer
8
TFPI2 7q22 PP5, REF1, TFPI-2 -TFPI2 and Colorectal Cancer
8
TLR2 4q32 TIL4, CD282 -TLR2 and Colorectal Cancer
8
VCAN 5q14.3 WGN, ERVR, GHAP, PG-M, WGN1, CSPG2 -VCAN and Colorectal Cancer
8
UCHL1 4p14 NDGOA, PARK5, PGP95, PGP9.5, Uch-L1, HEL-117, PGP 9.5 -UCHL1 and Colorectal Cancer
8
CCL20 2q36.3 CKb4, LARC, ST38, MIP3A, Exodus, MIP-3a, SCYA20, MIP-3-alpha -CCL20 and Colorectal Cancer
8
CFTR 7q31.2 CF, MRP7, ABC35, ABCC7, CFTR/MRP, TNR-CFTR, dJ760C5.1 -CFTR and Colonic Neoplasms
8
CXCR2 2q35 CD182, IL8R2, IL8RA, IL8RB, CMKAR2, CDw128b -CXCR2 and Colonic Neoplasms
8
TCF7 5q31.1 TCF-1 -TCF7 and Colorectal Cancer
8
AKAP12 6q24-q25 SSeCKS, AKAP250 -AKAP12 and Colorectal Cancer
8
PTGER2 14q22 EP2 -PTGER2 and Colorectal Cancer
8
ALOX5 10q11.2 5-LO, 5LPG, LOG5, 5-LOX -ALOX5 and Colorectal Cancer
8
DUSP4 8p12-p11 TYP, HVH2, MKP2, MKP-2 -DUSP4 and Colorectal Cancer
8
PER2 2q37.3 FASPS, FASPS1 -PER2 and Colorectal Cancer
8
PLA2G4A 1q25 PLA2G4, cPLA2-alpha -PLA2G4A and Colorectal Cancer
8
SFRP5 10q24.1 SARP3 -SFRP5 and Colonic Neoplasms
8
ADH1C 4q23 ADH3 -ADH1C and Colorectal Cancer
7
FCGR2A 1q23 CD32, FCG2, FcGR, CD32A, CDw32, FCGR2, IGFR2, FCGR2A1 -FCGR2A and Colorectal Cancer
7
FSCN1 7p22 HSN, SNL, p55, FAN1 -FSCN1 and Colorectal Cancer
7
PTPRQ 12q21.2 DFNB84, DFNB84A, PTPGMC1, R-PTP-Q -PTPRQ and Colorectal Cancer
7
ERCC6 10q11.23 CSB, CKN2, COFS, ARMD5, COFS1, RAD26, UVSS1 -ERCC6 and Colorectal Cancer
7
PTPRH 19q13.4 SAP1, R-PTP-H -PTPRH and Colorectal Cancer
7
FEN1 11q12 MF1, RAD2, FEN-1 -FEN1 and Colorectal Cancer
7
PEBP1 12q24.23 PBP, HCNP, PEBP, RKIP, HCNPpp, PEBP-1, HEL-210, HEL-S-34 -PEBP1 and Colorectal Cancer
7
NR4A2 2q22-q23 NOT, RNR1, HZF-3, NURR1, TINUR -NR4A2 and Colorectal Cancer
7
MTSS1 8p22 MIM, MIMA, MIMB -MTSS1 and Colorectal Cancer
7
GLI3 7p13 PHS, ACLS, GCPS, PAPA, PAPB, PAP-A, PAPA1, PPDIV, GLI3FL, GLI3-190 -GLI3 and Colorectal Cancer
7
SLC5A8 12q23.1 AIT, SMCT, SMCT1 -SLC5A8 and Colonic Neoplasms
7
NDRG1 8q24.3 GC4, RTP, DRG1, NDR1, NMSL, TDD5, CAP43, CMT4D, DRG-1, HMSNL, RIT42, TARG1, PROXY1 -NDRG1 and Colorectal Cancer
7
HPGD 4q34-q35 PGDH, PGDH1, PHOAR1, 15-PGDH, SDR36C1 -HPGD and Colorectal Cancer
7
LAMC2 1q25-q31 B2T, CSF, EBR2, BM600, EBR2A, LAMB2T, LAMNB2 -LAMC2 and Colorectal Cancer
7
EPHB3 3q27.1 ETK2, HEK2, TYRO6 -EPHB3 and Colorectal Cancer
7
BLM 15q26.1 BS, RECQ2, RECQL2, RECQL3 -BLM and Colorectal Cancer
7
CSK 15q24.1 -CSK and Colonic Neoplasms
7
STAT6 12q13 STAT6B, STAT6C, D12S1644, IL-4-STAT -STAT6 and Colonic Neoplasms
7
RRM2 2p25-p24 R2, RR2, RR2M -RRM2 and Colorectal Cancer
7
NR4A1 12q13 HMR, N10, TR3, NP10, GFRP1, NAK-1, NGFIB, NUR77 -NR4A1 and Colonic Neoplasms
7
SMAD5 5q31 DWFC, JV5-1, MADH5 -SMAD5 and Colorectal Cancer
7
ATG5 6q21 ASP, APG5, APG5L, hAPG5, APG5-LIKE -ATG5 and Colorectal Cancer
7
CHIA 1p13.2 CHIT2, AMCASE, TSA1902 -CHIA and Colorectal Cancer
7
IL23R 1p31.3 -IL23R and Colorectal Cancer
7
OLFM4 13q14.3 GC1, OLM4, OlfD, GW112, hGC-1, hOLfD, UNQ362, bA209J19.1 -OLFM4 and Colorectal Cancer
7
ATOH1 4q22 ATH1, HATH1, MATH-1, bHLHa14 -ATOH1 and Colonic Neoplasms
7
ELAVL1 19p13.2 HUR, Hua, MelG, ELAV1 -ELAVL1 and Colonic Neoplasms
6
HDAC3 5q31 HD3, RPD3, RPD3-2 -HDAC3 and Colonic Neoplasms
6
TNFSF13 17p13.1 APRIL, CD256, TALL2, ZTNF2, TALL-2, TRDL-1, UNQ383/PRO715 -TNFSF13 and Colorectal Cancer
6
CDH3 16q22.1 CDHP, HJMD, PCAD -CDH3 and Colorectal Cancer
6
SLIT2 4p15.2 SLIL3, Slit-2 -SLIT2 and Colorectal Cancer
6
LINC00632 Xq27.1 -RP1-177G6.2 and Colorectal Cancer
6
GPX2 14q24.1 GPRP, GPx-2, GI-GPx, GPRP-2, GPx-GI, GSHPx-2, GSHPX-GI -GPX2 and Colorectal Cancer
6
CEACAM6 19q13.2 NCA, CEAL, CD66c -CEACAM6 and Colorectal Cancer
6
AGR2 7p21.3 AG2, GOB-4, HAG-2, XAG-2, PDIA17, HEL-S-116 -AGR2 and Colorectal Cancer
6
GATA4 8p23.1-p22 TOF, ASD2, VSD1, TACHD -GATA4 and Colorectal Cancer
6
ODC1 2p25 ODC -ODC1 and Colorectal Cancer
6
BCL2L2 14q11.2-q12 BCLW, BCL-W, PPP1R51, BCL2-L-2 -BCL2L2 and Colorectal Cancer
6
POLB 8p11.2 -POLB and Colorectal Cancer
6
MTHFD1 14q24 MTHFC, MTHFD -MTHFD1 and Colorectal Cancer
6
PTGER4 5p13.1 EP4, EP4R -PTGER4 and Colorectal Cancer
6
TDGF1 3p21.31 CR, CRGF, CRIPTO -TDGF1 and Colonic Neoplasms
6
AIM2 1q22 PYHIN4 -AIM2 and Colorectal Cancer
6
S100P 4p16 MIG9 -S100P and Colonic Neoplasms
6
NDRG2 14q11.2 SYLD -NDRG2 and Colorectal Cancer
6
RFC1 4p14-p13 A1, RFC, PO-GA, RECC1, MHCBFB, RFC140 -RFC1 and Colorectal Cancer
6
CSE1L 20q13 CAS, CSE1, XPO2 -CSE1L and Colorectal Cancer
6
KISS1 1q32 HH13, KiSS-1 -KISS1 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
SNAI1 20q13.2 SNA, SNAH, SNAIL, SLUGH2, SNAIL1, dJ710H13.1 -SNAI1 and Colonic Neoplasms
6
TJP1 15q13 ZO-1 -TJP1 and Colorectal Cancer
6
MUC3A 7q22 MUC3, MUC-3A -MUC3A and Colorectal Cancer
6
CYP27B1 12q14.1 VDR, CP2B, CYP1, PDDR, VDD1, VDDR, VDDRI, CYP27B, P450c1, CYP1alpha -CYP27B1 and Colonic Neoplasms
6
POLK 5q13 DINP, POLQ, DINB1 -POLK and Colorectal Cancer
6
MSI1 12q24 -MSI1 and Colorectal Cancer
5
CASP5 11q22.2-q22.3 ICH-3, ICEREL-III, ICE(rel)III -CASP5 and Colorectal Cancer
5
PPARGC1A 4p15.1 LEM6, PGC1, PGC1A, PGC-1v, PPARGC1, PGC-1(alpha) -PPARGC1A and Colorectal Cancer
5
DMPK 19q13.3 DM, DM1, DMK, MDPK, DM1PK, MT-PK -DMPK and Colorectal Cancer
5
ANGPTL4 19p13.3 NL2, ARP4, FIAF, HARP, PGAR, HFARP, TGQTL, UNQ171, pp1158, ANGPTL2 -ANGPTL4 and Colorectal Cancer
5
EPHA7 6q16.1 EHK3, EK11, EHK-3, HEK11 -EPHA7 and Colorectal Cancer
5
ACTB 7p22 BRWS1, PS1TP5BP1 -ACTB and Colorectal Cancer
5
ADIPOR2 12p13.31 PAQR2, ACDCR2 -ADIPOR2 and Colorectal Cancer
5
SLCO1B3 12p12 LST3, HBLRR, LST-2, OATP8, OATP-8, OATP1B3, SLC21A8, LST-3TM13 -SLCO1B3 and Colorectal Cancer
5
PLCE1 10q23 PLCE, PPLC, NPHS3 -PLCE1 and Colorectal Cancer
5
LGALS4 19q13.2 GAL4, L36LBP -LGALS4 and Colorectal Cancer
5
CHEK1 11q24.2 CHK1 -CHEK1 and Colorectal Cancer
5
MAPK14 6p21.3-p21.2 RK, p38, CSBP, EXIP, Mxi2, CSBP1, CSBP2, CSPB1, PRKM14, PRKM15, SAPK2A, p38ALPHA -MAPK14 and Colonic Neoplasms
5
MAD1L1 7p22 MAD1, PIG9, TP53I9, TXBP181 -MAD1L1 and Colonic Neoplasms
5
CEACAM7 19q13.2 CEA, CGM2 -CEACAM7 and Colorectal Cancer
5
PER1 17p13.1 PER, hPER, RIGUI -PER1 and Colorectal Cancer
5
ITGB3 17q21.32 GT, CD61, GP3A, BDPLT2, GPIIIa, BDPLT16 -ITGB3 and Colorectal Cancer
5
SLC4A3 2q36 AE3, SLC2C -SLC4A3 and Colonic Neoplasms
5
CD1A 1q23.1 R4, T6, CD1, FCB6, HTA1 -CD1A and Colorectal Cancer
5
CD55 1q32 CR, TC, DAF, CROM -CD55 and Colorectal Cancer
5
MT1G 16q13 MT1, MT1K -MT1G and Colorectal Cancer
5
UBE2C 20q13.12 UBCH10, dJ447F3.2 -UBE2C and Colorectal Cancer
5
PCDH10 4q28.3 PCDH19, OL-PCDH -PCDH10 and Colorectal Cancer
5
ST14 11q24-q25 HAI, MTSP1, SNC19, ARCI11, MT-SP1, PRSS14, TADG15, TMPRSS14 -ST14 and Colorectal Cancer
5
LTA 6p21.3 LT, TNFB, TNFSF1 -LTA and Colorectal Cancer
5
LMNA 1q22 FPL, IDC, LFP, CDDC, EMD2, FPLD, HGPS, LDP1, LMN1, LMNC, PRO1, CDCD1, CMD1A, FPLD2, LMNL1, CMT2B1, LGMD1B -LMNA and Colorectal Cancer
5
CCL21 9p13 ECL, SLC, CKb9, TCA4, 6Ckine, SCYA21 -CCL21 and Colorectal Cancer
5
SATB1 3p23 -SATB1 and Colorectal Cancer
5
MMP12 11q22.3 ME, HME, MME, MMP-12 -MMP12 and Colorectal Cancer
4
ST7 7q31.2 HELG, RAY1, SEN4, TSG7, ETS7q, FAM4A, FAM4A1 -ST7 and Colorectal Cancer
4
SEC63 6q21 ERdj2, SEC63L, DNAJC23, PRO2507 -SEC63 and Colorectal Cancer
4
LOXL2 8p21.3 LOR2, WS9-14 -LOXL2 and Colorectal Cancer
4
CD58 1p13 ag3, LFA3, LFA-3 -CD58 and Colonic Neoplasms
4
CLDN7 17p13.1 CLDN-7, CEPTRL2, CPETRL2, Hs.84359, claudin-1 -CLDN7 and Colorectal Cancer
4
HAS3 16q22.1 -HAS3 and Colonic Neoplasms
4
TRA 14q11.2 IMD7, TCRA, TCRD, TRA@, TRAC -TRA and Colorectal Cancer
4
HHIP 4q28-q32 HIP -HHIP and Colorectal Cancer
4
CSMD1 8p23.2 PPP1R24 -CSMD1 and Colorectal Cancer
4
HNF4A 20q13.12 TCF, HNF4, MODY, FRTS4, MODY1, NR2A1, TCF14, HNF4a7, HNF4a8, HNF4a9, NR2A21, HNF4alpha -HNF4A and Colonic Neoplasms
4
MINA 3q11.2 ROX, MDIG, NO52, MINA53 -MINA and Colonic Neoplasms
4
PSMD10 Xq22.3 p28, p28(GANK), dJ889N15.2 -PSMD10 and Colorectal Cancer
4
WNT11 11q13.5 HWNT11 -WNT11 and Colorectal Cancer
4
HSD17B1 17q11-q21 HSD17, EDHB17, EDH17B2, SDR28C1 -HSD17B1 and Colorectal Cancer
4
WISP1 8q24.22 CCN4, WISP1c, WISP1i, WISP1tc -WISP1 and Colorectal Cancer
4
CCL19 9p13 ELC, CKb11, MIP3B, MIP-3b, SCYA19 -CCL19 and Colorectal Cancer
4
STC1 8p21.2 STC -STC1 and Colorectal Cancer
4
HLA-E 6p21.3 MHC, QA1, EA1.2, EA2.1, HLA-6.2 -HLA-E and Colorectal Cancer
4
ROBO1 3p12 SAX3, DUTT1 -ROBO1 and Colorectal Cancer
4
ARL11 13q14.2 ARLTS1 -ARL11 and Colorectal Cancer
4
AKR1B10 7q33 HIS, HSI, ARL1, ARL-1, ALDRLn, AKR1B11, AKR1B12 -AKR1B10 and Colorectal Cancer
4
SPRY2 13q31.1 hSPRY2 -SPRY2 and Colonic Neoplasms
4
PGK1 Xq13.3 PGKA, MIG10, HEL-S-68p -PGK1 and Colorectal Cancer
4
TOP2A 17q21-q22 TOP2, TP2A -TOP2A Expression in Colorectal Cancer
4
SACS 13q12 SPAX6, ARSACS, DNAJC29, PPP1R138 -SACS and Colorectal Cancer
4
S100A11 1q21 MLN70, S100C, HEL-S-43 -S100A11 and Colorectal Cancer
4
ADAMTS1 21q21.2 C3-C5, METH1 -ADAMTS1 and Colorectal Cancer
4
SMYD3 1q44 KMT3E, ZMYND1, ZNFN3A1, bA74P14.1 -SMYD3 and Colorectal Cancer
4
SPHK1 17q25.2 SPHK -SPHK1 and Colonic Neoplasms
4
INHA 2q35 -INHA and Colorectal Cancer
4
CDK2AP1 12q24.31 DOC1, ST19, DORC1, doc-1, p12DOC-1 -CDK2AP1 and Colorectal Cancer
4
DRD2 11q23 D2R, D2DR -DRD2 and Colorectal Cancer
4
NFKBIA 14q13 IKBA, MAD-3, NFKBI -NFKBIA and Colorectal Cancer
4
TNFRSF10C 8p22-p21 LIT, DCR1, TRID, CD263, TRAILR3, TRAIL-R3, DCR1-TNFR -TNFRSF10C and Colonic Neoplasms
4
LEPR 1p31 OBR, OB-R, CD295, LEP-R, LEPRD -LEPR and Colorectal Cancer
4
NOX1 Xq22 MOX1, NOH1, NOH-1, GP91-2 -NOX1 and Colonic Neoplasms
4
SNRPF 12q23.1 SMF, Sm-F, snRNP-F -SNRPF and Colorectal Cancer
4
KLK6 19q13.3 hK6, Bssp, Klk7, SP59, PRSS9, PRSS18 -KLK6 and Colonic Neoplasms
4
CKS2 9q22 CKSHS2 -CKS2 and Colorectal Cancer
4
PER3 1p36.23 GIG13 -PER3 and Colorectal Cancer
4
NRP2 2q33.3 NP2, NPN2, PRO2714, VEGF165R2 -NRP2 and Colorectal Cancer
4
ACTA2 10q23.3 AAT6, ACTSA, MYMY5 -ACTA2 and Colonic Neoplasms
4
CTBP1 4p16 BARS -CTBP1 and Colonic Neoplasms
4
IL16 15q26.3 LCF, NIL16, PRIL16, prIL-16 -IL16 and Colorectal Cancer
3
MAX 14q23 bHLHd4 -MAX and Colonic Neoplasms
3
APOB 2p24-p23 FLDB, LDLCQ4 -APOB and Colonic Neoplasms
3
RANBP2 2q12.3 ANE1, TRP1, TRP2, ADANE, IIAE3, NUP358 -RANBP2 and Colorectal Cancer
3
DDX5 17q21 p68, HLR1, G17P1, HUMP68 -DDX5 and Colorectal Cancer
3
SMAD6 15q22.31 AOVD2, MADH6, MADH7, HsT17432 -SMAD6 and Colorectal Cancer
3
NNAT 20q11.2-q12 Peg5 -NNAT and Colorectal Cancer
3
MAP3K8 10p11.23 COT, EST, ESTF, TPL2, AURA2, MEKK8, Tpl-2, c-COT -MAP3K8 and Colorectal Cancer
3
EPHA1 7q34 EPH, EPHT, EPHT1 -EPHA1 and Colorectal Cancer
3
PROX1 1q41 -PROX1 and Colonic Neoplasms
3
GRASP 12q13.13 TAMALIN -GRASP and Colorectal Cancer
3
IL12A 3q25.33 P35, CLMF, NFSK, NKSF1, IL-12A -IL12A and Colorectal Cancer
3
VTI1A 10q25.2 MMDS3, MVti1, VTI1RP2, Vti1-rp2 -VTI1A and Colorectal Cancer
3
CD276 15q23-q24 B7H3, B7-H3, B7RP-2, 4Ig-B7-H3 -CD276 and Colorectal Cancer
3
MVP 16p11.2 LRP, VAULT1 -MVP and Colonic Neoplasms
3
PTK7 6p21.1-p12.2 CCK4, CCK-4 -PTK7 and Colonic Neoplasms
3
FGF9 13q11-q12 GAF, FGF-9, SYNS3, HBFG-9, HBGF-9 -FGF9 and Colonic Neoplasms
3
FER 5q21 TYK3, PPP1R74, p94-Fer -FER and Colonic Neoplasms
3
TNFRSF6B 20q13.3 M68, TR6, DCR3, M68E, DJ583P15.1.1 Amplification
-TNFRSF6B Amplification and Overexpression in Colon Cancer
3
INHBA 7p15-p13 EDF, FRP -INHBA and Colorectal Cancer
3
USF1 1q22-q23 UEF, FCHL, MLTF, FCHL1, MLTFI, HYPLIP1, bHLHb11 -USF1 and Colonic Neoplasms
3
ACVR1 2q23-q24 FOP, ALK2, SKR1, TSRI, ACTRI, ACVR1A, ACVRLK2 -ACVR1 and Colonic Neoplasms
3
SAT2 17p13.1 SSAT2 -SAT2 and Colorectal Cancer
3
WISP3 6q21 PPD, CCN6, LIBC, PPAC -WISP3 and Colorectal Cancer
3
SNCG 10q23.2-q23.3 SR, BCSG1 -SNCG and Colonic Neoplasms
3
BIRC2 11q22 API1, MIHB, HIAP2, RNF48, cIAP1, Hiap-2, c-IAP1 -BIRC2 and Colonic Neoplasms
3
DKC1 Xq28 DKC, CBF5, DKCX, NAP57, NOLA4, XAP101 -DKC1 and Colonic Neoplasms
3
RALGDS 9q34.3 RGF, RGDS, RalGEF -RALGDS and Colorectal Cancer
3
CASP8AP2 6q15 CED-4, FLASH, RIP25 -CASP8AP2 and Colorectal Cancer
3
HAS1 19q13.4 HAS -HAS1 and Colonic Neoplasms
3
ARNTL 11p15 TIC, JAP3, MOP3, BMAL1, PASD3, BMAL1c, bHLHe5 -ARNTL and Colorectal Cancer
3
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
3
TXNRD1 12q23-q24.1 TR, TR1, TXNR, TRXR1, GRIM-12 -TXNRD1 and Colorectal Cancer
3
CHD5 1p36.31 CHD-5 -CHD5 and Colorectal Cancer
3
BMPR1B 4q22-q24 ALK6, ALK-6, CDw293 -BMPR1B and Colonic Neoplasms
3
LARS 5q32 LRS, LEUS, LFIS, ILFS1, LARS1, LEURS, PIG44, RNTLS, HSPC192, hr025Cl -LARS and Colorectal Cancer
3
APRT 16q24 AMP, APRTD -APRT and Colorectal Cancer
3
GATA5 20q13.33 GATAS, bB379O24.1 -GATA5 and Colorectal Cancer
3
TSPO 22q13.31 DBI, IBP, MBR, PBR, PBS, BPBS, BZRP, PKBS, PTBR, mDRC, pk18 -TSPO and Colorectal Cancer
3
MBD1 18q21 RFT, PCM1, CXXC3 -MBD1 and Colonic Neoplasms
3
TFRC 3q29 T9, TR, TFR, p90, CD71, TFR1, TRFR -TFRC and Colorectal Cancer
3
MUC5B 11p15.5 MG1, MUC5, MUC9, MUC-5B -MUC5B and Colonic Neoplasms
3
SPDEF 6p21.3 PDEF, bA375E1.3 -SPDEF and Colonic Neoplasms
3
LIG4 13q33-q34 LIG4S -LIG4 and Colorectal Cancer
3
MYCL 1p34.2 LMYC, L-Myc, MYCL1, bHLHe38 -MYCL and Colorectal Cancer
3
MAGEB2 Xp21.3 DAM6, CT3.2, MAGE-XP-2 -MAGEB2 and Colorectal Cancer
3
EPAS1 2p21-p16 HLF, MOP2, ECYT4, HIF2A, PASD2, bHLHe73 -EPAS1 and Colorectal Cancer
3
FOSB 19q13.32 AP-1, G0S3, GOS3, GOSB -FOSB and Colonic Neoplasms
3
RAD54L 1p32 HR54, hHR54, RAD54A, hRAD54 -RAD54L and Colorectal Cancer
3
ING5 2q37.3 p28ING5 -ING5 and Colorectal Cancer
3
BCL2L11 2q13 BAM, BIM, BOD -BCL2L11 and Colorectal Cancer
3
NOTO 2p13.2 -NOTO and Colorectal Cancer
3
GUSB 7q21.11 BG, MPS7 -GUSB and Colorectal Cancer
3
STAT2 12q13.3 P113, ISGF-3, STAT113 -STAT2 and Colonic Neoplasms
3
FHL2 2q12.2 DRAL, AAG11, FHL-2, SLIM3, SLIM-3 -FHL2 and Colonic Neoplasms
3
MIRLET7I 12q14.1 LET7I, MIRNLET7I, hsa-let-7i -MicroRNA let-7i and Colorectal Cancer
3
RBPJ 4p15.2 SUH, csl, AOS3, CBF1, KBF2, RBP-J, RBPJK, IGKJRB, RBPSUH, IGKJRB1 -RBPJ and Colonic Neoplasms
3
HOXD10 2q31.1 HOX4, HOX4D, HOX4E, Hox-4.4 -HOXD10 and Colonic Neoplasms
3
EIF3E 8q22-q23 INT6, EIF3S6, EIF3-P48, eIF3-p46 -EIF3E and Colonic Neoplasms
3
CRY1 12q23-q24.1 PHLL1 -CRY1 and Colorectal Cancer
3
IL6R 1q21 IL6Q, gp80, CD126, IL6RA, IL6RQ, IL-6RA, IL-6R-1 -IL6R and Colonic Neoplasms
3
SEMA3F 3p21.3 SEMA4, SEMAK, SEMA-IV -SEMA3F and Colorectal Cancer
3
SEPP1 5q31 SeP, SELP, SEPP -SEPP1 and Colorectal Cancer
3
ADAMTS9 3p14.1 -ADAMTS9 and Colorectal Cancer
2
TPM1 15q22.1 CMH3, TMSA, CMD1Y, LVNC9, C15orf13, HTM-alpha -TPM1 and Colonic Neoplasms
2
MTUS1 8p22 ATBP, ATIP, ICIS, MP44, MTSG1 -MTUS1 and Colonic Neoplasms
2
BOLL 2q33 BOULE -BOLL and Colonic Neoplasms
2
MUC7 4q13.3 MG2 -MUC7 and Colorectal Cancer
2
MUC17 7q22.1 MUC3 -MUC17 and Colonic Neoplasms
2
GJB2 13q11-q12 HID, KID, PPK, CX26, DFNA3, DFNB1, NSRD1, DFNA3A, DFNB1A -GJB2 and Colorectal Cancer
2
SGK1 6q23 SGK -SGK1 and Colonic Neoplasms
2
FAT1 4q35 FAT, ME5, CDHF7, CDHR8, hFat1 -FAT1 and Colorectal Cancer
2
AKAP9 7q21-q22 LQT11, PRKA9, AKAP-9, CG-NAP, YOTIAO, AKAP350, AKAP450, PPP1R45, HYPERION, MU-RMS-40.16A -AKAP9 and Colorectal Cancer
2
ZFP36 19q13.1 TTP, G0S24, GOS24, TIS11, NUP475, zfp-36, RNF162A -ZFP36 and Colonic Neoplasms
2
RALB 2q14.2 -RALB and Colorectal Cancer
2
MT2A 16q13 MT2 -MT2A and Colonic Neoplasms
2
RRM2B 8q23.1 P53R2, MTDPS8A, MTDPS8B -RRM2B and Colonic Neoplasms
2
ADAM29 4q34 CT73, svph1 -ADAM29 and Colorectal Cancer
2
LASP1 17q11-q21.3 MLN50, Lasp-1 -LASP1 and Colonic Neoplasms
2
HIP1 7q11.23 HIP-I, ILWEQ -HIP1 and Colonic Neoplasms
2
ATP7A Xq21.1 MK, MNK, DSMAX, SMAX3 -ATP7A and Colonic Neoplasms
2
RIN1 11q13.2 -RIN1 and Colonic Neoplasms
2
ADRM1 20q13.33 ARM1, ARM-1, GP110 -ADRM1 and Colorectal Cancer
2
IL12B 5q33.3 CLMF, NKSF, CLMF2, IMD28, IMD29, NKSF2, IL-12B -IL12B and Colorectal Cancer
2
PPP1R3A 7q31.1 GM, PP1G, PPP1R3 -PPP1R3A and Colorectal Cancer
2
TOPBP1 3q22.1 TOP2BP1 -TOPBP1 and Colorectal Cancer
2
MAP2K6 17q24.3 MEK6, MKK6, MAPKK6, PRKMK6, SAPKK3, SAPKK-3 -MAP2K6 and Colonic Neoplasms
2
PCM1 8p22-p21.3 PTC4 -PCM1 and Colorectal Cancer
2
TACR1 2p12 SPR, NK1R, NKIR, TAC1R -TACR1 and Colorectal Cancer
2
WWTR1 3q23-q24 TAZ -WWTR1 and Colorectal Cancer
2
NAV1 1q32.3 POMFIL3, UNC53H1, STEERIN1 -NAV1 and Colonic Neoplasms
2
ATF6 1q23.3 ATF6A -ATF6 and Colonic Neoplasms
2
SFPQ 1p34.3 PSF, POMP100, PPP1R140 -SFPQ and Colonic Neoplasms
2
C2orf40 2q12.2 ECRG4 -C2orf40 and Colorectal Cancer
2
BAI1 8q24.3 GDAIF -BAI1 and Colorectal Cancer
2
KLK14 19q13.3-q13.4 KLK-L6 -KLK14 and Colonic Neoplasms
2
PITX1 5q31.1 BFT, CCF, POTX, PTX1, LBNBG -PITX1 and Colorectal Cancer
2
LTBR 12p13 CD18, TNFCR, TNFR3, D12S370, TNFR-RP, TNFRSF3, TNFR2-RP, LT-BETA-R, TNF-R-III -LTBR and Colorectal Cancer
2
CASP4 11q22.2-q22.3 TX, ICH-2, Mih1/TX, ICEREL-II, ICE(rel)II -CASP4 and Colonic Neoplasms
2
ARHGEF12 11q23.3 LARG, PRO2792 -ARHGEF12 and Colorectal Cancer
2
BCL2L12 19q13.3 -BCL2L12 and Colonic Neoplasms
2
TM4SF1 3q21-q25 L6, H-L6, M3S1, TAAL6 -TM4SF1 and Colorectal Cancer
2
PRKCDBP 11p15.4 SRBC, HSRBC, CAVIN3, cavin-3 -PRKCDBP and Colorectal Cancer
2
ZNF350 19q13.41 ZFQR, ZBRK1 -ZNF350 and Colonic Neoplasms
2
GAS7 17p13.1 MLL/GAS7 -GAS7 and Colorectal Cancer
2
RASAL1 12q23-q24 RASAL -RASAL1 and Colorectal Cancer
2
ING2 4q35.1 ING1L, p33ING2 -ING2 and Colonic Neoplasms
2
ERC1 12p13.3 ELKS, Cast2, ERC-1, RAB6IP2 -ERC1 and Colorectal Cancer
1
MIR1297 13 MIRN1297, hsa-mir-1297 -MicroRNA miR-1297 and Colorectal Cancer
1
RAP2A 13q34 KREV, RAP2, K-REV, RbBP-30 -RAP2A and Colonic Neoplasms
1
MIR122 18q21.31 MIR122A, MIRN122, MIRN122A, miRNA122, miRNA122A, hsa-mir-122 -MIR122 and Colonic Neoplasms
1
NEMF 14q22 NY-CO-1, SDCCAG1 -NEMF and Colonic Neoplasms
1
REST 4q12 XBR, NRSF -REST and Colorectal Cancer
1
STEAP2 7q21.13 STMP, IPCA1, PUMPCn, STAMP1, PCANAP1 -STEAP2 and Colonic Neoplasms
1
ETV3 1q21-q23 PE1, METS, PE-1, bA110J1.4 -ETV3 and Colorectal Cancer
1
HINT1 5q31.2 HINT, NMAN, PKCI-1, PRKCNH1 -HINT1 and Colonic Neoplasms
1
PCDH7 4p15 BHPCDH, BH-Pcdh, PPP1R120 -PCDH7 and Colonic Neoplasms
1
PDCD6 5p15.33 ALG2, ALG-2, PEF1B -PDCD6 and Colonic Neoplasms
1
MAFG 17q25.3 hMAF -MAFG and Colonic Neoplasms
1
MIR1226 3p21.31 MIRN1226, mir-1226, hsa-mir-1226 -MicroRNA miR-1226 and Colorectal Cancer
1
GOLGA5 14q32.12 RFG5, GOLIM5, ret-II -GOLGA5 and Colorectal Cancer
1
SETD1B 12q24.31 KMT2G, Set1B -SETD1B and Colorectal Cancer
1
HSP90AA1 14q32.33 EL52, HSPN, LAP2, HSP86, HSPC1, HSPCA, Hsp89, Hsp90, LAP-2, HSP89A, HSP90A, HSP90N, HSPCAL1, HSPCAL4 -HSP90AA1 and Colonic Neoplasms
1
C2orf44 2p23.3 WDCP, PP384 -C2orf44 and Colorectal Cancer
1
SMAD7 18q21.1 CRCS3, MADH7, MADH8 -SMAD7 and Colorectal Cancer

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

Kit OI, Vladimirova LY, Vodolazhskiy DI, et al.
[The role of assessing UGT1A1 gene polymorphism in the prediction of irinotecan-induced toxicity in the course of chemotherapy for colorectal cancer].
Vopr Onkol. 2015; 61(2):266-9 [PubMed] Related Publications
There was performed a molecular genetic study of UGTlAl gene allelic variants polymorphism in patients with colorectal cancer who had had chemotherapy irinotecan-containing regimens FOLFIRI. Comparison of toxicity and the results of polymorphism of UGTlAl showed that dose-limiting hematologic and non-hematologic toxicities in patients with moderate and high risk of toxicity were higher (p = 0.050- 0.061) and the frequency of thrombocytopenia (p = 0.0257) and hyperbilirubinemia (p = 0.0439) were significantly higher compared to the low-risk group. Molecular genetic study of a complex examination of patients, which was planned to irinotecan should be performed to select the optimal dose and reduce the risk of toxicity of chemotherapy.

Teruya T, Nakachi A, Shimabukuro N, et al.
[Examination of UGT1A1 polymorphisms and irinotecan-induced neutropenia in patients with Colorectal cancer].
Gan To Kagaku Ryoho. 2015; 42(5):585-9 [PubMed] Related Publications
Irinotecan is an effective drug in the treatment of colorectal cancer. However, there are reports of an association between certain UGT1A1 genetic polymorphisms and the development of adverse reactions(such as neutropenia)related to irinotecan metabolism. We retrospectively investigated UGT1A1 genetic polymorphisms and the occurrences of irinotecan-induced neutropenia in 25 patients of colorectal cancer at our hospital. Analysis of UGT1A1 genetic polymorphisms in these patients yielded the following classifications: a wild-type group( *1/*1)comprising 13 patients(52%), a heterozygous group(*1/ *28, *1/*6)of 10 patients(40%), and a homozygous group(*28/*28, *6/*6)of 2 patients(8%). The frequency of neutropenia was 15.4%(2/13)in the wild-type group, 30%(3/10)in the heterozygous group, and 100%(2/2)in the homozygous group. Grade 4 neutropenia only occurred in the homozygous group. These results suggest that a dose reduction of irinotecan should be considered for patients who fall into the homozygous group upon analysis of their UGT1A1 genetic polymorphisms, as such patients might be susceptible to grade 4 neutropenia.

Zhang H, Zhang X, Wang J, et al.
Comparison of high-resolution melting analysis, Sanger sequencing and ARMS for KRAS mutation detection in metastatic colorectal cancer.
Clin Lab. 2015; 61(3-4):435-9 [PubMed] Related Publications
BACKGROUND: Treatment of metastatic colon carcinoma with the anti-epidermal growth factor receptor antibody cetuximab/panitumumab is reported to be ineffective in KRAS-mutant tumors; therefore, it is necessary to perform KRAS mutation analysis before cetuximab or panitumumab treatment is initiated.
METHODS: This study was designed to compare and evaluate the efficacy of three different methodologies--high resolution melting (HRM), Sanger sequencing, and Amplification Refractory Mutation System (ARMS)--for KRAS mutation detection in a clinical setting.
RESULTS: In total, 55 samples from patients with metastatic colorectal cancer were analyzed. Compared to Sanger sequencing, good consistency was found between the results of the ARMS (Kappa = 0.839) and HRM (Kappa = 0.839). The sensitivities of the methods were compared after a consensus was reached: if two of the three methodologies showed a similar result, it was considered as the consensus result. The frequency of KRAS mutations in our population was 34.5%, and discordant findings were observed in five samples. No significant difference in sensitivity was found among the three methodologies.
CONCLUSIONS: From the results, we can conclude that after careful in-laboratory validation, HRM is a good alternative to the ARMS and Sanger sequencing for KRAS mutation testing.

Gleeson FC, Kipp BR, Voss JS, et al.
Endoscopic ultrasound fine-needle aspiration cytology mutation profiling using targeted next-generation sequencing: personalized care for rectal cancer.
Am J Clin Pathol. 2015; 143(6):879-88 [PubMed] Related Publications
OBJECTIVES: In an era of precision medicine, our aim was to determine the frequency and theranostic potential of mutations identified in malignant lymph nodes (LNs) sampled by endoscopic ultrasound fine-needle aspiration (EUS FNA) of patients with rectal cancer by targeted next-generation sequencing (NGS).
METHODS: The NGS Ion AmpliSeq Cancer Hotspot Panel v2 (Life Technologies, Carlsbad, CA) and MiSeq (Illumina, San Diego, CA) sequencers were used to sequence and assess for 2,800 or more possible mutations in 50 established cancer-associated genes.
RESULTS: Among 102 patients, 89% had 194 pathogenic alterations identified in 19 genes. The identification of KRAS, NRAS, or BRAF mutations suggests that 42% are likely nonresponders to anti-epidermal growth factor receptor therapy. Among KRAS, NRAS, or BRAF wild-type patients, alterations in eight genes linked to alternative therapies were identified in 44%.
CONCLUSIONS: Our data demonstrate the successful ability to apply a single multiplex test to allow multigene mutation detection from malignant LN cytology specimen DNA collected by EUS FNA.

Saha A, Shree Padhi S, Roy S, Banerjee B
HCT116 colonospheres shows elevated expression of hTERT and β-catenin protein - a short report.
J Stem Cells. 2014; 9(4):243-51 [PubMed] Related Publications
AIM: Clonospheres formed due to modified culture conditions are often studied for their stem cell like behaviour. The main objective of the current study is to compare the stem cell markers and link it to hTERT levels by monitoring their quantitative gene expression as they are potential targets for new generation combination therapeutics.
METHOD: In the present study we created stable colonospheres of Human colon cancer cell line HCT-116 long term culture conditions of Serum deprivation. Clonospheres formed after 15 days were collected by gentle and enzymatic dissociation was performed. Single cell suspension was obtained by mechanically dissociating the cells through a 22G needle. Single cells were replanted at a density 1200 cells/ml in Serum Free Medium in the 6 well plates for further passage. Passaging of cells was done at an interval of 8 days. The spheres formed were cyto-spun in special slides for Immunocytochemistry (ICC) studies for β-catenin protein and hTERT. The colonospheres were also processed for real time PCR expression studies for the same genes to confirm.
RESULTS: In this present study, immunofluorescence studies revealed high β-catenin expression in the nucleus in colonospheres as compared to that of differentiated cancer cell line HCT-116 where the signal was localized mostly in the membranous and non-nuclear regions. Also increased TRF2 signal in colonospheres indicated higher activity of hTERT gene as TRF2 is the direct activator of hTERT to protect the telomere. Quantitative PCR studies showed that there was a significant over expression (p<0.05) at the mRNA level of the hTERT, TRF2, Rap1 genes along with the β-catenin over expression. Immunofluorescence analysis also revealed higher expression of CSC marker CD44 and ALDH1in colonospheres compared to the parental population.
CONCLUSION: Clonospheres sub-population is showing higher degree of hTERT gene expression along with β-catenin when compared to the parental HCT-116 cancer cells. We also checked the co expression of other telomere maintenance genes mainly TRF 2 and Rap1 which also showed similar results. Therefore, we conclude that not only hTERT but possibly other Sheltrin proteins are regulated by β-catenin which is co expressed.

Lan YT, Jen-Kou L, Lin CH, et al.
Mutations in the RAS and PI3K pathways are associated with metastatic location in colorectal cancers.
J Surg Oncol. 2015; 111(7):905-10 [PubMed] Related Publications
BACKGROUND AND OBJECTIVES: Identification of mutations in the downstream epidermal growth factor receptor (EGFR) signaling pathway could provide important insights of EGFR-targeted therapies in colorectal cancers. We analyzed the mutation spectra of the PI3K/PTEN/AKT and RAS/RAF/MAPK pathways in colorectal cancers and the associations of these mutations with sites of metastases or recurrence.
METHODS: The study population comprised 1,492 retrospectively collected stages I-IV colorectal cancer specimens. Tissue was obtained between 2000 and 2010 at a single hospital. We analyzed 61 hot spots using MALDI-TOF mass spectrometry for nucleic acid analysis.
RESULTS: Mutations were found in the RAS pathway in 47.3% of patients and in the PI3K pathway in 14.3% of patients, with 9.2% of patients carrying mutations in both pathways. Both the RAS and PI3K pathway mutations were significantly associated with proximal tumors, mucinous tumors, and microsatellite instability. Tumors carrying a RAS pathway mutation exhibited a higher frequency of lung and peritoneal metastasis than did tumors with a wild-type gene (P = 0.025 and 0.009, respectively). NRAS gene mutation was significantly associated with lung metastasis (P = 0.001).
CONCLUSIONS: Somatic mutations in the RAS pathway of the primary tumor in colorectal cancer can influence patterns of metastasis and recurrence.

Yanmaz MT, Demir G, Erdamar S, et al.
Epidermal growth factor receptor in CRC patients in the era of the RAS.
Hepatogastroenterology. 2015 Jan-Feb; 62(137):40-4 [PubMed] Related Publications
The aim of this study was to investigate EGFR expression patterns and the effect of EGFR expression on stage, prognosis and response to conventional chemotherapy agents other than monoclonal antibodies in CRC patients. This study included 59 metastatic CRC patients. The expression of EGFR was quantified by immunochemistry in biopsy specimens that were obtained before treatment was initiated. The cases were considered to be positive for EGFR if >1% of the tumor cells had complete circumferential membranous staining. The median age of the patients was 54.6 years, and 59% of the patients were male. Twenty-six patients presented with stage IV disease, and the remaining patients developed distant metastasis during follow-up. Fifty-one patients were treated with regimens containing irinotecan. The numbers of patients with EGFR expression in the primary tumors, the metastatic lymph nodes and the normal colonic tissue were 34 (65.4%), 10 (76.9%) and 34 (65.4%) respectively. The initial disease stage and lymph node stage were correlated with EGFR expression (p<0.05). Additionally, EGFR positivity was correlated with a statistically significant reduction in the response rate to chemotherapy, the overall survival (21 vs. 28 months) and the progression-free survival (15 vs. 22 months) in metastatic patiens treated with chemotherapy other than targeted therapies. In conclusion, EGFR expression in correlated with stage in all CRC patients and response to chemotherapy and survival in metastatic CRC patients.

Rui Y, Wang C, Zhou Z, et al.
K-Ras mutation and prognosis of colorectal cancer: a meta-analysis.
Hepatogastroenterology. 2015 Jan-Feb; 62(137):19-24 [PubMed] Related Publications
BACKGROUND/AIMS: Colorectal cancer (CRC) is one of the most common malignant tumors worldwide. Kirsten ras (K-ras) gene is considered to participate in the progression from adenoma to carcinoma of colorectal neoplasms. The correlation between K-ras mutation and the prognosis of CRC is sill controversial. This study aimed at quantitatively summarizing the evidence for such a relationship.
METHODOLOGY: The literature search was based on Pub Med. Population-based and hospital-based case-control studies concerning K-ras mutation and prognosis were eligible for analysis.
RESULTS: 13 literatures were included in the meta-analysis, with 1 multicenter study and 12 case control studies. Totally, 3771 patients were enrolled in the analysis, 1202 of which had K-ras mutation. There were significant difference between the survival of patients with normal and mutated K-ras gene, but no statistic differences were found between either Condon 12 or Condon 13 mutations and prognosis.
CONCLUSION: Current available evidences demonstrated the K-ras mutation is a predictive molecular mark of colorectal cancer patients' survivals, further studies are needed to investigate the race difference and the relationship between certain K-ras mutation and prognosis.

Asl JM, Almasi S, Tabatabaiefar MA
High frequency of BRAF proto-oncogene hot spot mutation V600E in cohort of colorectal cancer patients from Ahvaz City, southwest Iran.
Pak J Biol Sci. 2014; 17(4):565-9 [PubMed] Related Publications
Colorectal cancer (CRC) is one of the most common forms of cancer around the world. Sporadic CRCs are caused by accumulation of mutations in essential genes regulating normal proliferation and differentiation of cells. The proto-oncogene BRAF encoded by the BRAF gene is involved in the RAS/RAF/MAPK pathway of signal transduction during cell growth. Acquired mutations in BRAF have been found at high frequencies in adult patients with papillary thyroid carcinoma and sporadic CRC. One of the predominant hot spot point mutations is T1799A (V600E) mutation among a cohort of CRC patients from Ahvaz city, southwest Iran. The aim of this study was to estimate the frequency of V600E mutation in CRC patients from Ahvaz city, southwest Iran. We analyzed exon 15 of the BRAF gene in isolated DNA from 80 Formalin Fixed Paraffin-embedded (FFPE) CRC tumor tissues using PCR-RFLP method. Data were analyzed using SPSS statistical program. According to our results 37 out of 80 cases (46.25%) were heterozygous for the mutation while the remaining 43 cases (53.75%) had normal homozygous genotype. No homozygous mutant genotype was found. Based on our findings, the frequency of V600E mutation appears to be significantly increased among CRC patients of the studied population but there was no significant relationship between genotypes and age and sex. In conclusion, these findings might prove the effect of V600E mutation on CRC pathogenesis. However, the exact effect of the mutation in CRC progression requires further work.

Liu Y, Zhang X, Han C, et al.
TP53 loss creates therapeutic vulnerability in colorectal cancer.
Nature. 2015; 520(7549):697-701 [PubMed] Article available free on PMC after 30/10/2015 Related Publications
TP53, a well-known tumour suppressor gene that encodes p53, is frequently inactivated by mutation or deletion in most human tumours. A tremendous effort has been made to restore p53 activity in cancer therapies. However, no effective p53-based therapy has been successfully translated into clinical cancer treatment owing to the complexity of p53 signalling. Here we demonstrate that genomic deletion of TP53 frequently encompasses essential neighbouring genes, rendering cancer cells with hemizygous TP53 deletion vulnerable to further suppression of such genes. POLR2A is identified as such a gene that is almost always co-deleted with TP53 in human cancers. It encodes the largest and catalytic subunit of the RNA polymerase II complex, which is specifically inhibited by α-amanitin. Our analysis of The Cancer Genome Atlas (TCGA) and Cancer Cell Line Encyclopedia (CCLE) databases reveals that POLR2A expression levels are tightly correlated with its gene copy numbers in human colorectal cancer. Suppression of POLR2A with α-amanitin or small interfering RNAs selectively inhibits the proliferation, survival and tumorigenic potential of colorectal cancer cells with hemizygous TP53 loss in a p53-independent manner. Previous clinical applications of α-amanitin have been limited owing to its liver toxicity. However, we found that α-amanitin-based antibody-drug conjugates are highly effective therapeutic agents with reduced toxicity. Here we show that low doses of α-amanitin-conjugated anti-epithelial cell adhesion molecule (EpCAM) antibody lead to complete tumour regression in mouse models of human colorectal cancer with hemizygous deletion of POLR2A. We anticipate that inhibiting POLR2A will be a new therapeutic approach for human cancers containing such common genomic alterations.

Zhou F, Huang X, Zhang Z, et al.
Functional polymorphisms of ITGB1 are associated with clinical outcome of Chinese patients with resected colorectal cancer.
Cancer Chemother Pharmacol. 2015; 75(6):1207-15 [PubMed] Related Publications
PURPOSE: Integrin β1 (ITGB1) has been recognized to play a major role in tumor growth, invasion and metastasis. However, effects of single-nucleotide polymorphisms (SNPs) in ITGB1 gene on the prognosis of patients with colorectal cancer (CRC) have not been reported.
METHODS: A total of 372 patients with resected colorectal adenocarcinoma were enrolled in our study. Three functional SNPs (rs2230395, rs1187075 and rs1187076) in ITGB1 were selected and genotyped using the Sequenom iPLEX genotyping system.
RESULTS: We identified two SNPs (rs2230395 and rs1187075) in ITGB1 gene to be significantly associated with CRC overall survival (OS). Compared with the homozygous wild-type (AA) and heterozygous variant (AC), rs2230395 homozygous variant (CC) conferred a 1.55-fold (95 % CI 1.00-2.41, P = 0.049) increased risk of death. Similar result was obtained for homozygous variant (AA) in rs1187075 with a 1.62-fold (95 % CI 1.08-2.42, P = 0.020). In stratified analysis, this association in rs2230395 remained to be significant in patients receiving chemotherapy, but not in those without chemotherapy. We further evaluated the effects of chemotherapy on CRC survival in subgroups stratified by rs2230395 and rs1187075 genotypes. We found that chemotherapy resulted in a significantly better OS in patients with the homozygous wild-type (WW) or heterozygous variant (WV) genotype in both rs2230395 and rs1187075 when compared with patients with homozygous variant (VV) genotype.
CONCLUSIONS: Our data suggest that ITGB1 SNPs might be a prognostic biomarker for CRC patients, especially in those receiving chemotherapy. Our findings warrant validation in larger independent populations.

Durno CA, Sherman PM, Aronson M, et al.
Phenotypic and genotypic characterisation of biallelic mismatch repair deficiency (BMMR-D) syndrome.
Eur J Cancer. 2015; 51(8):977-83 [PubMed] Related Publications
Lynch syndrome, the most common inherited colorectal cancer syndrome in adults, is an autosomal dominant condition caused by heterozygous germ-line mutations in DNA mismatch repair (MMR) genes MLH1, MSH2, MSH6 and PMS2. Inheriting biallelic (homozygous) mutations in any of the MMR genes results in a different clinical syndrome termed biallelic mismatch repair deficiency (BMMR-D) that is characterised by gastrointestinal tumours, skin lesions, brain tumours and haematologic malignancies. This recently described and under-recognised syndrome can present with adenomatous polyps leading to early-onset small bowel and colorectal adenocarcinoma. An important clue in the family history that suggests underling BMMR-D is consanguinity. Interestingly, pedigrees of BMMR-D patients typically show a paucity of Lynch syndrome cancers and most parents are unaffected. Therefore, a family history of cancers is often non-contributory. Detection of BMMR-D can lead to more appropriate genetic counselling and the implementation of targeted surveillance protocols to achieve earlier tumour detection that will allow surgical resection. This review describes an approach for diagnosis and management of these patients and their families.

Ye D, Wang Q, Zhang J, Liu Q
[Transfection of thymidine phosphorylase cDNA with lentiviral vector enhances the anticancer effect of 5'-deoxy-5-fluorouridine on colorectal cancer cell lines HT29 and LS174T].
Zhonghua Zhong Liu Za Zhi. 2015; 37(1):18-24 [PubMed] Related Publications
OBJECTIVE: To explore the changes of anticancer efficiency of 5'-deoxy-5-fluorouridine (5'-DFUR) and 5-fluorouracil (5-Fu) in colorectal cancer cell line HT29 and LS174T cells after transfection of thymidine phosphorylase (TP) cDNA with a lentiviral vector.
METHODS: TP cDNA was transfected into human colorectal cancer cell lines HT29 and LS174T with the lentiviral vector pLenti6.3-MCS-IRES2-EGFP, and the transfection efficiency of the two cell lines passed 5 generations was analyzed by flow cytometry. The expression of TP protein and the relative quantitative expression of TP mRNA in these 2 cell lines were detected by Western blot and RT-PCR, respectively. The 50% inhibitory concentration (IC50) of 5'-DFUR and 5-Fu in both HT29 and LS174T parent cells and TP-transfected cells were assessed by MTS assay. Finally, the concentration of converted 5-Fu was detected by high performance liquid chromatography (HPLC) either in the medium containing a series of concentrations of 5'-DFUR, in which HT29/HT29-TP or LS174T/LS174T-TP cells were cultured, or in the cell culture lysates.
RESULTS: The HT29 and LS174T cells transfected with human TP cDNA were monitored for 5 generations, and their transfection efficiency was about 95.0%. Immunohistochemical staining showed that both the parent cells and TP-transfected HT29 and LS174T cells were TP-positive, while vector-transfected cells were TP-negative. Western blotting showed that the TP protein expression in HT29-TP and LS174T-TP cells were significantly increased compared with that in their parents cells. The relative quantity (RQ) values of TP mRNA in HT29-TP and LS174T-TP cells were 8.45 ± 0.15 and 2 615.02 ± 253.97, respectively, which were significantly higher than that in their parents cells (P < 0.01). The IC50 values of 5'-DFUR on HT29-TP cells and its parents cell were (14.33 ± 0.74) µmol/L and (707.66 ± 5.66) µmol/L, respectively (P < 0.05), while (0.59 ± 0.11) µmol/L in LS174T-TP cells and (239.20 ± 21.83) µmol/L in its parent cells, respectively (P < 0.05). The IC50 values of 5-Fu of HT29-TP cells and its parents cells were (5.42 ± 0.75) µmol/L and (14.19 ± 0.97) µmol/L, respectively (P < 0.05), while (4.41 ± 0.96)µmol/L in LS174T-TP cells and (16.42 ± 2.12)µmol/L in its parents cells, respectively (P < 0.05). The HPLC results showed that the 5-Fu concentration detected from media contained a series of concentrations of 5'-DFUR for culturing HT29-TP and LS174T-TP cells were 12.2 to 28.7-folds and 13.1 to 23.6-folds, respectively, higher than that in their parents cells, (P < 0.01 for all). Otherwise, just a little of 5-Fu was detected in the two TP-transfected cells lysate, about 0.9% to 4.2% of 5-Fu detected in the media of the same cultured cells, whereas no 5-Fu was detected in the two parent cell lysates.
CONCLUSIONS: Transfection of TP cDNA into colorectal cancer cell lines HT29 and LS174T with lentiviral vector can improve the expression of both TP mRNA and TP protein levels in passaged cells, enhance the conversion of 5-Fu from 5'-DFUR in the medium, and result in an enhanced anticancer effect on these two cell lines.

Cheng JM, Yao MR, Zhu Q, et al.
Silencing of stat4 gene inhibits cell proliferation and invasion of colorectal cancer cells.
J Biol Regul Homeost Agents. 2015 Jan-Mar; 29(1):85-92 [PubMed] Related Publications
Signal transducers and activators of transcription (STAT) play critical roles in development, proliferation, and immune defense. However the consequences of STAT hyperactivity can predispose to diseases, including colorectal cancer. In the present study, we aimed to evaluate the function of STAT4 in human colorectal cancer (CRC). The expression of STAT4 was examined by immunohistochemical assay using a tissue microarray procedure. A loss-of-function experiment was carried out to investigate the effects of lentivirus-mediated STAT4 shRNA (Lv-shSTAT4) on cell proliferation and invasive potential indicated by MTT and Transwell assays in CRC cell lines (SW480 and Caco2). As a consequence, it was found that the expression of STAT4 protein was significantly increased in CRC tissues compared with that in adjacent non-cancerous tissues (ANCT) (71.1% vs 44.4%, P=0.015), and was related with the Duke’s staging and depth of invasion in CRC patients (P=0.022; P=0.001). Silencing of STAT4 gene suppressed cell proliferation and invasion of CRC cells. Taken together, these findings demonstrate that increased expression of STAT4 is positively correlated with the depth of invasion in CRC patients, and inhibition of STAT4 expression represses the growth and invasion of CRC cells, suggesting that STAT4 may be a promising therapeutic target for the treatment of CRC.

Tougeron D, Sickersen G, Mouillet G, et al.
Predictors of disease-free survival in colorectal cancer with microsatellite instability: An AGEO multicentre study.
Eur J Cancer. 2015; 51(8):925-34 [PubMed] Related Publications
BACKGROUND: A microsatellite instability (MSI) phenotype is found in about 12% of colorectal cancers (CRCs) and is associated with a low recurrence rate after curative surgery. Several studies have identified clinical and pathological factors predictive of recurrence in resected CRC, but not in the MSI subgroup.
PATIENTS AND METHODS: This multicentre retrospective study included patients with stage I, II or III MSI CRCs. Disease-free survival (DFS) was calculated with the Kaplan-Meier method. Factors associated with DFS were identified in univariate and multivariate Cox analyses.
RESULTS: We studied 521 patients with MSI CRC. Respectively 11%, 51% and 38% of patients were at stage I, II and III. Mean age was 68.7years and 36% of the patients received adjuvant chemotherapy. Median follow-up was 32.8months. The disease recurrence rates were 6% and 21% in stage II and III patients, respectively. The 3-year DFS rate was 77%. In univariate analysis, age, bowel obstruction, lymph node invasion, stage T4, vascular emboli, lymphatic invasion and perinervous invasion were associated with poorer DFS (P<0.05). Three relevant independent predictors of poor DFS were identified in multivariate analysis, namely bowel obstruction (HR=2.46; 95%CI 1.31-4.62, P=0.005), vascular emboli (HR=2.79; 95%CI 1.74-4.47, P<0.001) and stage T4 (HR=2.16; 95%CI 1.31-3.56, P=0.002).
CONCLUSIONS: Bowel obstruction, vascular emboli and stage T4 are independently associated with MSI CRC recurrence, suggesting that screening for vascular emboli in routine clinical practice may assist with adjuvant chemotherapy decision-making.

Pardini B, Bermejo JL, Naccarati A, et al.
Inherited variability in a master regulator polymorphism (rs4846126) associates with survival in 5-FU treated colorectal cancer patients.
Mutat Res. 2014 Aug-Sep; 766-767:7-13 [PubMed] Related Publications
BACKGROUND: Treatment with 5-fluorouracil (5-FU) is known to improve survival in many cancers including colorectal cancer. Response to the treatment, overall survival and recurrence show inter-individual variation.
METHODS: In this study we employed a strategy to search eQTL variants influencing the expression of a large number of genes. We identified four single nucleotide polymorphisms, defined as master regulators of transcription, and genotyped them in a set of 218 colorectal cancer patients undergoing adjuvant 5-FU based therapy.
RESULTS: Our results showed that the minor allele variant of the rs4846126 polymorphism was associated with poor overall and progression-free survival. Patients that were homozygous for the variant allele showed an over two fold increased risk of death (HR 2.20 95%CI 1.05-4.60) and progression (HR 2.88, 95% 1.47-5.63). The integration of external information from publicly available gene expression repositories suggested that the rs4846126 polymorphism deserves further investigation. This variant potentially regulates the gene expression of 273 genes with some of them possibly associated to the patient's response to 5-FU treatment or colorectal cancer.
CONCLUSIONS: Present results show that mining of public data repositories in combination with own data can be a fruitful approach to identify markers that affect therapy outcome. In particular, a genetic screen of master regulators may help in order to search for the polymorphisms involved in treatment response in cancer patients.

Kondratova VN, Botezatu IV, Shelepov VP, Likhtenshtein AV
[Transcripts of satellite DNA in blood plasma: probable markers of tumor growth].
Mol Biol (Mosk). 2014 Nov-Dec; 48(6):999-1007 [PubMed] Related Publications
A recent study of human normal and tumor tissues revealed a high transcriptional activity of pericentromeric satellite DNA repeats (they produce half of all transcripts in tumor cells that is many times higher than in normal ones). It was found also that the two subtypes of satellite DNA (HSATII and GSATII) are transcribed reciprocally, i.e. there is a sharp prevalence of HSATII transcription in tumors, while GSATII transcription prevails in the corresponding normal tissues. As different RNAs are present in blood plasma, and some of them serve as effectivetumor markers, we attempted for the first time to evaluate satellite HSATII and GSATII RNAs in the blood plasma of healthy donors and cancer patients. The RT-PCR protocol designed for this purpose allowed us to detect transcripts of both HSATII and GSATII repeats. As it has been shown, HSATII transcripts are more abundant than GSATII ones in plasma of healthy donors and vice versa in plasma of cancer patients; these ratios being diametrically opposed to those that exist within the cells. Some suggestions concerning origins of circulating satellite RNAs and their probable role as tumor markers are discussed.

Xu Z, Chen H, Liu D, Huo J
Fibulin-1 is downregulated through promoter hypermethylation in colorectal cancer: a CONSORT study.
Medicine (Baltimore). 2015; 94(13):e663 [PubMed] Related Publications
Fibulin-1 (FBLN1) is involved in the progression of some types of cancer. However, the role of FBLN1 in colorectal cancer (CRC) has not been examined. The purpose of this study was to understand the molecular mechanisms and clinical significance of FBLN1 inactivation in CRC. The expression of FBLN1 in CRC tissues and adjacent normal tissues was analyzed by immunohistochemical analysis and quantitative real-time polymerase chain reaction (qRT-PCR). Methylation-specific polymerase chain reaction (MSP) and bisulfite sequencing PCR (BSP) were performed to examine the methylation status of the FBLN1 gene promoter. Furthermore, the methylated level of FBLN1 was analyzed with the clinicopathological characteristics. Immunohistochemical analysis and qRT-PCR analysis showed that FBLN1 protein and messenger RNA (mRNA) levels in tumor tissues were both significantly decreased compared with that in adjacent nontumor tissues. The methylation rate of FBLN1 promoter was significantly higher in CRC tissues than that in adjacent nontumor tissues (P < 0.001). In addition, the correlation between FBLN1 hypermethylation, protein expression, and overall survival (OS) was statistically significant. Our results indicated that the FBLN1 gene may be a novel candidate of tumor suppressor gene in CRC, and that promoter hypermethylation of FBLN1 is an important reason for its downregulation and is also a good predictor of OS for CRC.

de Macêdo MP, de Melo FM, Lisboa BC, et al.
KRAS gene mutation in a series of unselected colorectal carcinoma patients with prognostic morphological correlations: a pyrosequencing method improved by nested PCR.
Exp Mol Pathol. 2015; 98(3):563-7 [PubMed] Related Publications
INTRODUCTION: Inhibition of EGFR is a strategy for treating metastatic colorectal cancer (CRC) patients. KRAS sequencing is mandatory for selecting wild-type tumor patients who might benefit from this treatment. DNA from formalin-fixed paraffin-embedded (FFPE) tissues is commonly used for routine clinical detection of mutations, and its amplification succeeds only when all preanalytical histological processes have been controlled. In cases that are not properly processed, the DNA results can be poor, with low peak pyrosequencing findings. We designed and tested a pair of forward and reverse primers for a nested PCR method, followed by pyrosequencing, in a single Latin American institution series of 422 unselected CRC patients, correlating KRAS mutations with pathological and clinical data.
MATERIALS AND METHODS: Patient DNA samples from tumors were obtained by scraping or laser microdissection of cells from FFPE tissue and extracted using a commercial kit. DNA was first amplified by PCR using 2 primers that we designed; then, nested PCR was performed with the amplicon from the preamplification PCR using the KRAS PyroMark™ Q96 V2.0 kit (Qiagen). Pathological data were retrieved from pathology reports.
RESULTS: KRAS mutation was observed in 33% of 421 cases. Codon 12 was mutated in 76% of cases versus codon 13 in 24%. Right-sided CRCs harbored more KRAS mutations than left-sided tumors, as did tumors that presented with perineural invasion.
CONCLUSION: Our findings in this Latin American population are consistent with the literature regarding the frequency of KRAS mutations in CRC, their distribution between codons 12 and 13, and type of nucleotide substitution. By combining nested PCR and pyrosequencing, we achieved a high rate of conclusive results in testing KRAS mutations in CRC samples - a method that can be used as an ancillary test for failed assays by conventional PCR.

Qu F, Chen Y, Wang X, et al.
Leukocyte mitochondrial DNA content: a novel biomarker associated with prognosis and therapeutic outcome in colorectal cancer.
Carcinogenesis. 2015; 36(5):543-52 [PubMed] Related Publications
Compelling evidence has indicated a significant association between leukocyte mitochondrial DNA (mtDNA) content and incidence risks of several malignancies in a cancer-specific manner. However, to date, whether leukocyte mtDNA content can predict clinical outcome of cancer patients has never been investigated. In the present study, we measured leukocyte mtDNA content using real-time PCR-based method in a total of 598 colorectal cancer (CRC) patients and explored its prognostic values. To explore potential mechanism, we detected the immunophenotypes of peripheral blood mononuclear cells and plasma concentrations of several cytokines in CRC patients. We found that patients with high mtDNA content showed significantly worse overall survival (OS) and relapse-free survival (RFS) than those with low mtDNA content in all patient sets. Furthermore, mtDNA content and tumor node metastasis (TNM) stage exhibited a notable joint effect in prognosis prediction. Integration of TNM stage and leukocyte mtDNA content significantly improved the prognosis prediction efficacy for CRC. Importantly, patients with high mtDNA content showed OS and RFS benefits from adjuvant chemotherapy. In addition, we found that patients with high mtDNA content had a higher frequency of CD4(+)CD25(+)FOXP3(+) regulatory T cells, higher plasma interleukin-2 and transforming growth factor-β1 and lower tumor necrosis factor-α concentration than those with low mtDNA content, suggesting a stronger immunosuppressive phenotype. In conclusion, our study for the first time demonstrates that leukocyte mtDNA content is an independent prognostic marker complementing TNM stage and associated with immunosuppression in CRC patients. Additionally, leukocyte mtDNA content might serve as a potential biomarker to select CRC patients who will benefit from adjuvant chemotherapy.

Kim H, Verhaak RG
Transcriptional mimicry by tumor-associated stroma.
Nat Genet. 2015; 47(4):307-9 [PubMed] Related Publications
Recent molecular classification of colorectal cancer (CRC) has identified a poor-prognosis transcriptional subtype associated with mesenchymal traits. New studies used CRC transcriptomic data to show that tumor-associated stroma mimics the gene signature of epithelial-to-mesenchymal transition (EMT) and found no evidence for EMT of colorectal tumor cells.

Song M, Nishihara R, Wu K, et al.
Marine ω-3 polyunsaturated fatty acids and risk of colorectal cancer according to microsatellite instability.
J Natl Cancer Inst. 2015; 107(4) [PubMed] Article available free on PMC after 01/04/2016 Related Publications
BACKGROUND: Chronic inflammation is involved in the development of colorectal cancer (CRC) and microsatellite instability (MSI), a distinct phenotype of CRC. Experimental evidence indicates an anti-inflammatory and antineoplastic effect of marine ω-3 polyunsaturated fatty acids (PUFAs). However, epidemiologic data remain inconclusive.
METHODS: We investigated whether the association between marine ω-3 PUFAs and CRC varies by MSI-defined subtypes of tumors in the Nurses' Health Study and Health Professionals Follow-up Study. We documented and classified 1125 CRC cases into either MSI-high tumors, in which 30% or more of the 10 microsatellite markers demonstrated instability, or microsatellite-stable (MSS) tumors. Cox proportional hazards model was used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) of MSS tumors and MSI-high tumors in relation to marine ω-3 PUFA intake. All statistical tests were two-sided.
RESULTS: Marine ω-3 PUFA intake was not associated with overall incidence of CRC. However, a statistically significant difference was detected by MSI status (P heterogeneity = .02): High marine ω-3 PUFA intake was associated with a lower risk of MSI-high tumors (comparing ≥0.30g/d with <0.10g/d: multivariable HR = 0.54, 95% CI = 0.35 to 0.83, P linearity = .03) but not MSS tumors (HR = 0.97, 95% CI = 0.78 to 1.20, P linearity = .28). This differential association appeared to be independent of CpG island methylator phenotype and BRAF mutation status.
CONCLUSIONS: High marine ω-3 PUFA intake is associated with lower risk of MSI-high CRC but not MSS tumors, suggesting a potential role of ω-3 PUFAs in protection against CRC through DNA mismatch repair. Further research is needed to confirm our findings and elucidate potential underlying mechanisms.

Abu-Remaileh M, Bender S, Raddatz G, et al.
Chronic inflammation induces a novel epigenetic program that is conserved in intestinal adenomas and in colorectal cancer.
Cancer Res. 2015; 75(10):2120-30 [PubMed] Related Publications
Chronic inflammation represents a major risk factor for tumor formation, but the underlying mechanisms have remained largely unknown. Epigenetic mechanisms can record the effects of environmental challenges on the genome level and could therefore play an important role in the pathogenesis of inflammation-associated tumors. Using single-base methylation maps and transcriptome analyses of a colitis-induced mouse colon cancer model, we identified a novel epigenetic program that is characterized by hypermethylation of DNA methylation valleys that are characterized by low CpG density and active chromatin marks. This program is conserved and functional in mouse intestinal adenomas and results in silencing of active intestinal genes that are involved in gastrointestinal homeostasis and injury response. Further analyses reveal that the program represents a prominent feature of human colorectal cancer and can be used to correctly classify colorectal cancer samples with high accuracy. Together, our results show that inflammatory signals establish a novel epigenetic program that silences a specific set of genes that contribute to inflammation-induced cellular transformation.

Zhunussova G, Zhunusbekova B, Djansugurova L
Association between glutathione S-transferase M1 and T1 polymorphisms and colorectal cancer risk in patients from Kazakhstan.
Clin Lab. 2015; 61(1-2):161-8 [PubMed] Related Publications
BACKGROUND: Colorectal cancer (CRC) is one of the most common malignancies worldwide and the incidence is increasing in developed as well as developing countries including Kazakhstan. Glutathione S-transferases (GSTs) are considered to be cancer susceptibility genes as they play a role in the detoxification of carcinogenic species. In this case-control study the influence of GSTM1 and GSTT1 polymorphisms on CRC risk in Kazakhstan population were evaluated.
METHODS: Blood samples were collected from patients diagnosed with rectal or colon cancer (300 individuals) as well as a control cohort of healthy volunteers (300 individuals), taking into account the age, gender, ethnicity, and smoking habits of the CRC patients. Deletion polymorphisms were genotyped employing a multiplex PCR amplification method. Association between polymorphisms and CRC susceptibility risk was calculated using multivariate analysis and logistic regression for odd ratio (OR).
RESULTS: The homozygous GSTM1 null genotype was associated with significantly increased risk of CRC (OR = 2.01, 95% CI = 1.45-2.79, p = 0.0001) while the homozygous GSST1 null genotype was not associated with the risk of developing CRC (OR = 1.10, 95% CI = 0.78-1.55, p = 0.001), but the heterozygous genotype correlated with CRC susceptibility (OR = 1.98, 95% CI = 1.30-3.00, p = 0.001). Also, separate analyses of each of the main ethnic groups (Kazakh and Russian) showed a strong association of GSTM1 null genotype with CRC risk (for Kazakhs OR = 2.36, 95% CI = 1.35-4.10, p = 0.006 and for Russians OR = 1.84, 95% CI = 1.17-2.89, p = 0.003). The CRC risk of GSTM1 null genotype in smokers was considerably higher (OR = 3.37, 95% CI = 1.78-6.38, p = 0.0007). The combination of the GSTM1 and GSTT1 null genotypes in combined mixed population of Kazakhstan showed a trend to increasing the risk of developing CRC (OR = 1.60, 95% CI = 1.00-2.56), but it was not statistically significant.
CONCLUSIONS: In conclusion, the results of this case-control study for sporadic cases of CRC show that GSTM1 deletion polymorphisms can have predictive value for susceptibility to CRC (OR = 2.01, p = 0.0001) for the mixed population from Kazakhstan and for both main ethnic groups (Kazakhs and Russians (OR = 2.36 and OR = 1.84, respectively)).

Yu B, Swatkoski S, Holly A, et al.
Oncogenesis driven by the Ras/Raf pathway requires the SUMO E2 ligase Ubc9.
Proc Natl Acad Sci U S A. 2015; 112(14):E1724-33 [PubMed] Article available free on PMC after 07/10/2015 Related Publications
The small GTPase KRAS is frequently mutated in human cancer and currently there are no targeted therapies for KRAS mutant tumors. Here, we show that the small ubiquitin-like modifier (SUMO) pathway is required for KRAS-driven transformation. RNAi depletion of the SUMO E2 ligase Ubc9 suppresses 3D growth of KRAS mutant colorectal cancer cells in vitro and attenuates tumor growth in vivo. In KRAS mutant cells, a subset of proteins exhibit elevated levels of SUMOylation. Among these proteins, KAP1, CHD1, and EIF3L collectively support anchorage-independent growth, and the SUMOylation of KAP1 is necessary for its activity in this context. Thus, the SUMO pathway critically contributes to the transformed phenotype of KRAS mutant cells and Ubc9 presents a potential target for the treatment of KRAS mutant colorectal cancer.

He HL, Lee YE, Chen HP, et al.
Overexpression of DNAJC12 predicts poor response to neoadjuvant concurrent chemoradiotherapy in patients with rectal cancer.
Exp Mol Pathol. 2015; 98(3):338-45 [PubMed] Related Publications
Genes associated with protein folding have been found to have certain prognostic significance in a subset of cancers. The aim of this study is to evaluate the clinical impact of DNAJC12 expression in patients with rectal cancers receiving neoadjuvant concurrent chemoradiotherapy (CCRT) followed by surgery. Through data mining from a public transcriptomic dataset of rectal cancer focusing on genes associated with protein folding, we found that DNAJC12, a member of the HSP40/DNAJ family, was the most significant such gene correlated with the CCRT response. We further evaluated the expression of DNAJC12 by immunohistochemistry in the pre-treatment tumor specimens from 172 patients with rectal cancers. From this set, we statistically analyzed the association of DNAJC12 expression with various clinicopathological factors, tumor regression grade, overall survival (OS), disease-free survival (DFS) and local recurrence-free survival (LRFS). High expression of DNAJC12 was significantly associated with advanced pre- and post-treatment tumor status (P<0.001), advanced pre- and post-treatment nodal status (P<0.001), increased vascular invasion (P=0.015), increased perineural invasion (P=0.023) and lower tumor regression grade (P=0.009). More importantly, high expression of DNAJC12 was found to be correlated with poor prognosis for OS (P=0.0012), DFS (P<0.0001) and LRFS (P=0.0001). In multivariate analysis, DNAJC12 overexpression still emerged as an independent prognosticator for shorter OS (P=0.040), DFS (P<0.001) and LRFS (P=0.016). The data indicate that DNAJC12 overexpression acts as a negative predictive factor for the response to neoadjuvant CCRT and was significantly associated with shorter survival in patients with rectal cancers receiving neoadjuvant CCRT followed by surgery.

Taniguchi H, Yamazaki K, Yoshino T, et al.
Japanese Society of Medical Oncology Clinical Guidelines: RAS (KRAS/NRAS) mutation testing in colorectal cancer patients.
Cancer Sci. 2015; 106(3):324-7 [PubMed] Related Publications
The Japanese guidelines for the testing of KRAS mutations in colorectal cancer have been used for the past 5 years. However, new findings of RAS (KRAS/NRAS) mutations that can further predict the therapeutic effects of anti-epidermal growth factor receptor (EGFR) antibody therapy necessitated a revision of the guidelines. The revised guidelines included the following five basic requirements for RAS mutation testing to highlight a patient group in which anti-EGFR antibody therapy may be ineffective: First, anti-EGFR antibody therapy may not offer survival benefit and/or tumor shrinkage to patients with expanded RAS mutations. Thus, current methods to detect KRAS exon 2 (codons 12 and 13) mutations are insufficient for selecting appropriate candidates for this therapy. Additional testing of extended KRAS/NRAS mutations is recommended. Second, repeated tests are not required for the detection; tissue materials of either primary or metastatic lesions are applicable for RAS mutation testing. Evaluating RAS mutations prior to anti-EGFR antibody therapy is recommended. Third, direct sequencing with manual dissection or allele-specific PCR-based methods is currently applicable for RAS mutation testing. Fourth, thinly sliced sections of formalin-fixed, paraffin-embedded tissue blocks are applicable for RAS mutation testing. One section stained with H&E should be provided to histologically determine whether the tissue contains sufficient amount of tumor cells for testing. Finally, RAS mutation testing must be performed in laboratories with appropriate testing procedures and specimen management practices.

Vignot S, Lefebvre C, Frampton GM, et al.
Comparative analysis of primary tumour and matched metastases in colorectal cancer patients: evaluation of concordance between genomic and transcriptional profiles.
Eur J Cancer. 2015; 51(7):791-9 [PubMed] Related Publications
PURPOSE: Focal and temporal tumour heterogeneity can represent a major challenge for biology-guided therapies. This study proposes to investigative molecular discrepancies between primary colorectal cancer (CRC) samples and matched metastases.
EXPERIMENTAL DESIGN: Surgical samples from primary and matched metastatic tissues from 13 CRC patients along with their adjacent normal tissue were evaluated. A mutational analysis was performed using a targeted Next Generation Sequencing assay (Foundation Medicine) with a focus on known recurrent somatic mutations as surrogate of key oncogenic events. Gene expression analysis was also performed to investigate transcriptional discrepancies.
RESULTS: Among the 26 samples, 191 mutations were identified including mutations in APC (13 pts), TP53 (11 pts), and KRAS (7 pts). Global concordance rate for mutations was 78% between primary and metastatic tumours and raised to 90% for 12 known recurrent mutations in CRC. Differential gene expression analysis revealed a low number of significantly variant transcripts between primary and metastatic tumours once the tissue effect was taken into account. Only two pathways (ST_ADRENERGIC, PID_REELINPATHWAY) were differentially up-regulated in metastases among 17 variant pathways. A common profile in primary and metastatic tumours revealed conserved pathways mostly involved in cell cycle regulation. Only two pathways were significantly down regulated compared to normal control, including regulation of autophagy (KEGG_REGULATION_OF_AUTOPHAGY).
CONCLUSION: These results suggest that profiles of primary tumour can identify key alterations present in matched CRC metastases at first metastatic progression. Gene expression analysis identified mainly conserved pathways between primary tumour and matched liver metastases.

Goldstein DA, Shaib WL, Flowers CR
Costs and effectiveness of genomic testing in the management of colorectal cancer.
Oncology (Williston Park). 2015; 29(3):175-83 [PubMed] Related Publications
Numerous genomic tests are available for use in colorectal cancer, with a widely variable evidence base for their effectiveness and cost-effectiveness. In this review, we highlight many of these tests, with a focus on their proposed role, the evidence base to support that role, and the associated costs and risks. The tests with the strongest evidence base are KRAS genetic testing in the metastatic setting and microsatellite instability testing in selected patients and in stage II disease. There also may be a role for delineating recurrence-risk signatures for selected patients with stage II disease. The evidence to support broad utilization of uridine 5'-diphospho-glucuronosyltransferase 1A1 (UGT1A1) and dihydropyrimidine dehydrogenase (DPD) testing to guide irinotecan and fluorouracil dosing remains limited. There is much anticipation that next-generation sequencing will herald a new era of targeted therapy for patients with colorectal cancer; however, currently there are no data to support the introduction of widespread testing.

Papaconstantinou I, Mantzos DS, Asimakoula K, et al.
A 12-year experience at a tertiary hospital on patients with multiple primary malignant neoplasms.
J BUON. 2015 Jan-Feb; 20(1):332-7 [PubMed] Related Publications
PURPOSE: The incidence of multiple primary malignant neoplasms (MPMN) has dramatically increased. The purpose of this retrospective study was to present the 12-year experience at a University Hospital in patients with MPMN and to investigate the role of genetic factors in their pathogenesis.
METHODS: The medical records of 7516 cancer patients, treated in our Institution from 2000 to 2012, were reviewed. Diagnosis of MPMN was based on the Warren and Gates' criteria.
RESULTS: Among 7516 patients, 39 (0.5%) (10 men, mean age 70.0±6.98 years, and 29 women, mean age 64.7±8.24 years) presented with MPMN. Eighty-two percent of them developed 2 primary malignant neoplasms (PMNs), whereas 3 PMNs were developed in 7 patients. Breast cancer was the most common cancer type diagnosed among female patients (59%); 14 and 3 had 2 and 3 PMNs, respectively. Eight had a family history of breast cancer while in 3 genetic testing revealed mutations in BRCA1 and BRCA2 genes. The second most common type of malignancy was colorectal cancer (24%); 5 developed 2 PMNs, whereas 2 developed 3 PMNs. Five patients had a family history of colorectal cancer. Colon cancer was the most frequent neoplasm among male patients (50%; 3 developed 2 and 2 3 PMNs. In 2 patients the family history was positive for colorectal cancer.
CONCLUSIONS: Although many factors may contribute to MPMN development, positive family history and inherent mutations significantly predispose to MPMN appearance. Thus, management of MPMN patients should be based on a detailed family history and genetic testing.

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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