Gastric Cancer

Overview

Literature Analysis

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Tag cloud generated 08 August, 2015 using data from PubMed, MeSH and CancerIndex

Mutated Genes and Abnormal Protein Expression (383)

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
CTNNB1 3p21 CTNNB, MRD19, armadillo -CTNNB1 mutations in Gastric Cancer
361
CDH1 16q22.1 UVO, CDHE, ECAD, LCAM, Arc-1, CD324 -CDH1 and Stomach Cancer
282
TNF 6p21.3 DIF, TNFA, TNFSF2, TNF-alpha -TNF and Stomach Cancer
237
MET 7q31 HGFR, AUTS9, RCCP2, c-Met Prognostic
-C-MET and Stomach Cancer
219
APC 5q21-q22 GS, DP2, DP3, BTPS2, DP2.5, PPP1R46 -APC and Stomach Cancer
168
BAX 19q13.3-q13.4 BCL2L4 -BAX and Stomach Cancer
122
PTGS2 1q25.2-q25.3 COX2, COX-2, PHS-2, PGG/HS, PGHS-2, hCox-2, GRIPGHS -PTGS2 (COX2) and Stomach Cancer
122
KRAS 12p12.1 NS, NS3, CFC2, KRAS1, KRAS2, RASK2, KI-RAS, C-K-RAS, K-RAS2A, K-RAS2B, K-RAS4A, K-RAS4B -KRAS and Stomach Cancer
90
IL10 1q31-q32 CSIF, TGIF, GVHDS, IL-10, IL10A -Interleukin-10 and Stomach Cancer
89
CASP3 4q34 CPP32, SCA-1, CPP32B -CASP3 and Stomach Cancer
86
CEACAM5 19q13.1-q13.2 CEA, CD66e -CEACAM5 and Stomach Cancer
86
RUNX3 1p36 AML2, CBFA3, PEBP2aC -RUNX3 and Stomach Cancer
79
CD44 11p13 IN, LHR, MC56, MDU2, MDU3, MIC4, Pgp1, CDW44, CSPG8, HCELL, HUTCH-I, ECMR-III -CD44 and Stomach Cancer
76
PTEN 10q23.3 BZS, DEC, CWS1, GLM2, MHAM, TEP1, MMAC1, PTEN1, 10q23del -PTEN and Stomach Cancer
71
ABCB1 7q21.12 CLCS, MDR1, P-GP, PGY1, ABC20, CD243, GP170 -ABCB1 and Stomach Cancer
70
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 -MUC1 and Gastric Cancer
-MUC1 polymorphisms and cancer suseptability?
59
MTHFR 1p36.3 -MTHFR and Stomach Cancer
66
PCNA 20pter-p12 ATLD2 -PCNA and Stomach Cancer
66
MMP2 16q12.2 CLG4, MONA, CLG4A, MMP-2, TBE-1, MMP-II Prognostic
-MMP2 and Stomach Cancer
62
MSH2 2p21 FCC1, COCA1, HNPCC, LCFS2, HNPCC1 -MSH2 and Stomach Cancer
61
KITLG 12q22 SF, MGF, SCF, FPH2, FPHH, KL-1, Kitl, SHEP7 -KITLG and Stomach Cancer
57
MUC2 11p15.5 MLP, SMUC, MUC-2 -MUC2 and Stomach Cancer
56
CDKN1B 12p13.1-p12 KIP1, MEN4, CDKN4, MEN1B, P27KIP1 Prognostic
-CDKN1B and Gastric Cancer
54
DCC 18q21.3 CRC18, CRCR1, MRMV1, IGDCC1, NTN1R1 -DCC and Stomach Cancer
51
MALT1 18q21 MLT, MLT1, IMD12 -MALT1 and Stomach Cancer
50
MYC 8q24.21 MRTL, MYCC, c-Myc, bHLHe39 -MYC protein, human and Stomach Cancer
50
MGMT 10q26 -MGMT and Stomach Cancer
49
TGFBR2 3p22 AAT3, FAA3, LDS2, MFS2, RIIC, LDS1B, LDS2B, TAAD2, TGFR-2, TGFbeta-RII -TGFBR2 and Stomach Cancer
48
VEGFA 6p12 VPF, VEGF, MVCD1 -VEGFA and Stomach Cancer
45
FGFR2 10q26 BEK, JWS, BBDS, CEK3, CFD1, ECT1, KGFR, TK14, TK25, BFR-1, CD332, K-SAM -FGFR2 and Stomach Cancer
42
TLR4 9q33.1 TOLL, CD284, TLR-4, ARMD10 -TLR4 and Stomach Cancer
41
PSCA 8q24.2 PRO232 -MUC1 polymorphisms and cancer suseptability?
-PSCA and Stomach Cancer
32
TFF1 21q22.3 pS2, BCEI, HPS2, HP1.A, pNR-2, D21S21 -TFF1 and Stomach Cancer
40
ERCC1 19q13.32 UV20, COFS4, RAD10 -ERCC1 and Stomach Cancer
39
MUC5AC 11p15.5 TBM, leB, MUC5 -MUC5AC and Stomach Cancer
39
SMAD4 18q21.1 JIP, DPC4, MADH4, MYHRS -SMAD4 and Stomach Cancer
38
PIK3CA 3q26.3 MCM, CWS5, MCAP, PI3K, CLOVE, MCMTC, p110-alpha -PIK3CA and Stomach Cancer
38
FHIT 3p14.2 FRA3B, AP3Aase -FHIT and Stomach Cancer
37
PPARG 3p25 GLM1, CIMT1, NR1C3, PPARG1, PPARG2, PPARgamma -PPARG and Stomach Cancer
36
IL1RN 2q14.2 DIRA, IRAP, IL1F3, IL1RA, MVCD4, IL-1RN, IL-1ra, IL-1ra3, ICIL-1RA -IL1RN and Stomach Cancer
35
MUC6 11p15.5 MUC-6 -MUC6 and Stomach Cancer
32
FOS 14q24.3 p55, AP-1, C-FOS -FOS and Stomach Cancer
30
MDM2 12q14.3-q15 HDMX, hdm2, ACTFS -MDM2 and Stomach Cancer
29
CYP2E1 10q26.3 CPE1, CYP2E, P450-J, P450C2E -CYP2E1 and Stomach Cancer
28
DAPK1 9q21.33 DAPK -DAPK1 and Stomach Cancer
25
GAPDH 12p13 G3PD, GAPD, HEL-S-162eP -GAPDH and Stomach Cancer
23
BCL10 1p22 CLAP, mE10, CIPER, IMD37, c-E10, CARMEN -BCL10 and Stomach Cancer
22
VEGFC 4q34.3 VRP, Flt4-L, LMPH1D -VEGFC and Stomach Cancer
22
HLA-A 6p21.3 HLAA -HLA-A and Stomach Cancer
22
DAPK2 15q22.31 DRP1, DRP-1 -DAPK2 and Stomach Cancer
22
ALDH2 12q24.2 ALDM, ALDHI, ALDH-E2 -ALDH2 and Stomach Cancer
20
CHFR 12q24.33 RNF116, RNF196 -CHFR and Stomach Cancer
19
CD82 11p11.2 R2, 4F9, C33, IA4, ST6, GR15, KAI1, SAR2, TSPAN27 -CD82 and Stomach Cancer
19
MMP7 11q22.2 MMP-7, MPSL1, PUMP-1 -MMP7 and Stomach Cancer
19
FAS 10q24.1 APT1, CD95, FAS1, APO-1, FASTM, ALPS1A, TNFRSF6 -FAS and Stomach Cancer
19
MAPK1 22q11.21 ERK, p38, p40, p41, ERK2, ERT1, ERK-2, MAPK2, PRKM1, PRKM2, P42MAPK, p41mapk, p42-MAPK -MAPK1 and Stomach Cancer
18
IL17A 6p12 IL17, CTLA8, IL-17, IL-17A -IL17A and Stomach Cancer
17
TFF2 21q22.3 SP, SML1 -TFF2 and Stomach Cancer
17
CDK6 7q21-q22 MCPH12, PLSTIRE -CDK6 and Stomach Cancer
17
TIMP3 22q12.3 SFD, K222, K222TA2, HSMRK222 -TIMP3 and Stomach Cancer
16
IL17C 16q24 CX2, IL-17C -IL17C and Stomach Cancer
14
CDH17 8q22.1 HPT1, CDH16, HPT-1 -CDH17 and Stomach Cancer
14
MCC 5q21 MCC1 -MCC and Stomach Cancer
14
CDX1 5q32 -CDX1 and Stomach Cancer
13
TLR2 4q32 TIL4, CD282 -TLR2 and Stomach Cancer
13
JAK2 9p24 JTK10, THCYT3 -JAK2 and Stomach Cancer
13
WNT2 7q31.2 IRP, INT1L1 -WNT2 and Stomach Cancer
12
GLI1 12q13.2-q13.3 GLI -GLI1 and Stomach Cancer
12
SMAD7 18q21.1 CRCS3, MADH7, MADH8 -SMAD7 and Stomach Cancer
12
PTP4A3 8q24.3 PRL3, PRL-3, PRL-R -PTP4A3 and Stomach Cancer
12
CISH 3p21.3 CIS, G18, SOCS, CIS-1, BACTS2 -CISH and Stomach Cancer
12
FASLG 1q23 APTL, FASL, CD178, CD95L, ALPS1B, CD95-L, TNFSF6, APT1LG1 -FASLG and Stomach Cancer
12
GRB7 17q12 -GRB7 and Stomach Cancer
11
OLFM4 13q14.3 GC1, OLM4, OlfD, GW112, hGC-1, hOLfD, UNQ362, bA209J19.1 -OLFM4 and Stomach Cancer
11
PTCH1 9q22.3 PTC, BCNS, HPE7, PTC1, PTCH, NBCCS, PTCH11 -PTCH1 and Stomach Cancer
11
IGF2 11p15.5 IGF-II, PP9974, C11orf43 -IGF2 and Stomach Cancer
11
KRT20 17q21.2 K20, CD20, CK20, CK-20, KRT21 -KRT20 and Stomach Cancer
11
EZH2 7q35-q36 WVS, ENX1, EZH1, KMT6, WVS2, ENX-1, EZH2b, KMT6A -EZH2 and Stomach Cancer
11
REG4 1p13.1-p12 GISP, RELP, REG-IV -REG4 and Stomach Cancer
11
UGT1A1 2q37 GNT1, UGT1, UDPGT, UGT1A, HUG-BR1, BILIQTL1, UDPGT 1-1 -UGT1A1 and Stomach Cancer
11
NOS2 17q11.2 NOS, INOS, NOS2A, HEP-NOS -NOS2 and Stomach Cancer
10
WNT5A 3p21-p14 hWNT5A -WNT5A and Stomach Cancer
10
CCND2 12p13 MPPH3, KIAK0002 -CCND2 and Stomach Cancer
10
PTPN11 12q24 CFC, NS1, SHP2, BPTP3, PTP2C, PTP-1D, SH-PTP2, SH-PTP3 -PTPN11 and Stomach Cancer
10
BMI1 10p11.23 PCGF4, RNF51, FLVI2/BMI1 -BMI1 and Stomach Cancer
10
MAGEA3 Xq28 HIP8, HYPD, CT1.3, MAGE3, MAGEA6 -MAGEA3 and Stomach Cancer
10
S100A4 1q21 42A, 18A2, CAPL, FSP1, MTS1, P9KA, PEL98 -S100A4 and Stomach Cancer
10
MMP1 11q22.3 CLG, CLGN -MMP1 and Stomach Cancer
10
BUB1 2q14 BUB1A, BUB1L, hBUB1 -BUB1 and Stomach Cancer
10
MAGEA1 Xq28 CT1.1, MAGE1 -MAGEA1 and Stomach Cancer
9
XAF1 17p13.1 BIRC4BP, XIAPAF1, HSXIAPAF1 -XAF1 and Stomach Cancer
9
H19 11p15.5 ASM, BWS, WT2, ASM1, PRO2605, D11S813E, LINC00008, NCRNA00008 -H19 and Stomach Cancer
9
MMP14 14q11.2 MMP-14, MMP-X1, MT-MMP, MT1MMP, MTMMP1, WNCHRS, MT1-MMP, MT-MMP 1 -MMP14 and Stomach Cancer
9
MIR107 10q23.31 MIRN107, miR-107 -MicroRNA mir-107 and Stomach Cancer
9
TOP2A 17q21-q22 TOP2, TP2A -TOP2A and Stomach Cancer
9
IL4 5q31.1 BSF1, IL-4, BCGF1, BSF-1, BCGF-1 -IL4 and Stomach Cancer
9
EPCAM 2p21 ESA, KSA, M4S1, MK-1, DIAR5, EGP-2, EGP40, KS1/4, MIC18, TROP1, EGP314, HNPCC8, TACSTD1 -EPCAM and Stomach Cancer
8
MMP3 11q22.3 SL-1, STMY, STR1, CHDS6, MMP-3, STMY1 -MMP3 and Stomach Cancer
8
KLF4 9q31 EZF, GKLF -KLF4 and Stomach Cancer
8
KLF6 10p15 GBF, ZF9, BCD1, CBA1, CPBP, PAC1, ST12, COPEB -KLF6 and Stomach Cancer
8
HLA-B 6p21.3 AS, HLAB, SPDA1 -HLA-B and Stomach Cancer
8
SIRT1 10q21.3 SIR2, hSIR2, SIR2L1 -SIRT1 and Stomach Cancer
8
MIF 22q11.23 GIF, GLIF, MMIF -MIF and Stomach Cancer
8
LGR5 12q22-q23 FEX, HG38, GPR49, GPR67, GRP49 -LGR5 and Stomach Cancer
8
ZEB2 2q22.3 SIP1, SIP-1, ZFHX1B, HSPC082, SMADIP1 -ZEB2 and Stomach Cancer
8
HLA-DRB1 6p21.3 SS1, DRB1, DRw10, HLA-DRB, HLA-DR1B -HLA-DRB1 and Stomach Cancer
8
WNT3A 1q42 -WNT3A and Stomach Cancer
8
LGALS3 14q22.3 L31, GAL3, MAC2, CBP35, GALBP, GALIG, LGALS2 -LGALS3 and Stomach Cancer
8
DPYD 1p22 DHP, DPD, DHPDHASE -DPYD and Stomach Cancer
8
ODC1 2p25 ODC -ODC1 and Stomach Cancer
8
SFRP2 4q31.3 FRP-2, SARP1, SDF-5 -SFRP2 and Stomach Cancer
8
ICAM1 19p13.3-p13.2 BB2, CD54, P3.58 -ICAM1 and Stomach Cancer
8
MUC4 3q29 ASGP, MUC-4, HSA276359 -MUC4 and Stomach Cancer
8
MOS 8q11 MSV -MOS and Stomach Cancer
8
SSTR2 17q24 -SSTR2 and Stomach Cancer
8
HLTF 3q25.1-q26.1 ZBU1, HLTF1, RNF80, HIP116, SNF2L3, HIP116A, SMARCA3 -HLTF and Stomach Cancer
7
VIP 6q25 PHM27 -VIP and Stomach Cancer
7
AURKA 20q13 AIK, ARK1, AURA, BTAK, STK6, STK7, STK15, AURORA2, PPP1R47 -AURKA and Stomach Cancer
7
PTER 10p12 HPHRP, RPR-1 -PTER and Stomach Cancer
7
ZNF217 20q13.2 ZABC1 -ZNF217 and Stomach Cancer
7
TPR 1q25 -TPR and Stomach Cancer
7
AICDA 12p13 AID, ARP2, CDA2, HIGM2, HEL-S-284 -AICDA and Stomach Cancer
7
FADD 11q13.3 GIG3, MORT1 -FADD and Stomach Cancer
7
HMGB1 13q12 HMG1, HMG3, SBP-1 -HMGB1 and Stomach Cancer
7
GPX3 5q33.1 GPx-P, GSHPx-3, GSHPx-P -GPX3 and Stomach Cancer
7
DROSHA 5p13.3 RN3, ETOHI2, RNASEN, RANSE3L, RNASE3L, HSA242976 -DROSHA and Stomach Cancer
6
JAK1 1p32.3-p31.3 JTK3, JAK1A, JAK1B -JAK1 and Stomach Cancer
6
STAR 8p11.2 STARD1 -STAR and Stomach Cancer
6
DICER1 14q32.13 DCR1, MNG1, Dicer, HERNA, RMSE2, Dicer1e, K12H4.8-LIKE -DICER1 and Stomach Cancer
6
CLDN3 7q11.23 RVP1, HRVP1, C7orf1, CPE-R2, CPETR2 -CLDN3 and Stomach Cancer
6
GATA4 8p23.1-p22 TOF, ASD2, VSD1, TACHD -GATA4 and Stomach Cancer
6
SCFV 14 -SCFV and Stomach Cancer
6
ADH1B 4q23 ADH2, HEL-S-117 -ADH1B and Stomach Cancer
6
SMO 7q32.3 Gx, SMOH, FZD11 -SMO and Stomach Cancer
6
FZD7 2q33 FzE3 -FZD7 and Stomach Cancer
6
REG1A 2p12 P19, PSP, PTP, REG, ICRF, PSPS, PSPS1 -REG1A and Stomach Cancer
6
SFRP5 10q24.1 SARP3 -SFRP5 and Stomach Cancer
6
TYMS 18p11.32 TS, TMS, HST422 -TYMS and Stomach Cancer
6
IL11 19q13.3-q13.4 AGIF, IL-11 -IL11 and Stomach Cancer
6
MAD2L1 4q27 MAD2, HSMAD2 -MAD2L1 and Stomach Cancer
6
S100A6 1q21 2A9, PRA, 5B10, CABP, CACY -S100A6 and Stomach Cancer
6
APEX1 14q11.2 APE, APX, APE1, APEN, APEX, HAP1, REF1 -APEX1 and Stomach Cancer
6
TP53INP1 8q22 SIP, Teap, p53DINP1, TP53DINP1, TP53INP1A, TP53INP1B -TP53INP1 and Stomach Cancer
5
CLDN4 7q11.23 CPER, CPE-R, CPETR, CPETR1, WBSCR8, hCPE-R -CLDN4 and Stomach Cancer
5
ST7 7q31.2 HELG, RAY1, SEN4, TSG7, ETS7q, FAM4A, FAM4A1 -ST7 and Stomach Cancer
5
FSCN1 7p22 HSN, SNL, p55, FAN1 -FSCN1 and Stomach Cancer
5
ANO1 11q13.3 DOG1, TAOS2, ORAOV2, TMEM16A -ANO1 and Stomach Cancer
5
DIABLO 12q24.31 SMAC, DFNA64 -DIABLO and Stomach Cancer
5
TNKS 8p23.1 TIN1, ARTD5, PARPL, TINF1, TNKS1, pART5, PARP5A, PARP-5a -TNKS and Stomach Cancer
5
PLA2G2A 1p35 MOM1, PLA2, PLA2B, PLA2L, PLA2S, PLAS1, sPLA2 -PLA2G2A and Stomach Cancer
5
POT1 7q31.33 CMM10, HPOT1 -POT1 and Stomach Cancer
5
GATA5 20q13.33 GATAS, bB379O24.1 -GATA5 and Stomach Cancer
5
PINX1 8p23 LPTL, LPTS -PINX1 and Stomach Cancer
5
CXCR3 Xq13 GPR9, MigR, CD182, CD183, Mig-R, CKR-L2, CMKAR3, IP10-R -CXCR3 and Stomach Cancer
5
IL1A 2q14 IL1, IL-1A, IL1F1, IL1-ALPHA -IL1A and Stomach Cancer
5
FH 1q42.1 MCL, FMRD, LRCC, HLRCC, MCUL1 -FH and Stomach Cancer
5
TFPI2 7q22 PP5, REF1, TFPI-2 -TFPI2 and Stomach Cancer
5
S100A2 1q21 CAN19, S100L -S100A2 and Stomach Cancer
5
GNAS 20q13.3 AHO, GSA, GSP, POH, GPSA, NESP, GNAS1, PHP1A, PHP1B, PHP1C, C20orf45 -GNAS and Stomach Cancer
5
ROCK1 18q11.1 ROCK-I, P160ROCK -ROCK1 and Stomach Cancer
5
PCDH10 4q28.3 PCDH19, OL-PCDH -PCDH10 and Stomach Cancer
5
TBX21 17q21.32 TBET, T-PET, T-bet, TBLYM -TBX21 and Stomach Cancer
5
RASSF2 20p13 CENP-34, RASFADIN -RASSF2 and Stomach Cancer
5
PTK2 8q24.3 FAK, FADK, FAK1, FRNK, PPP1R71, p125FAK, pp125FAK -PTK2 and Stomach Cancer
5
CD274 9p24 B7-H, B7H1, PDL1, PD-L1, PDCD1L1, PDCD1LG1 -CD274 and Stomach Cancer
5
CD83 6p23 BL11, HB15 -CD83 and Stomach Cancer
5
NOTO 2p13.2 -NOTO and Stomach Cancer
5
WNT10B 12q13 SHFM6, WNT-12 -WNT10B and Stomach Cancer
5
ING4 12p13.31 my036, p29ING4 -ING4 and Stomach Cancer
5
BCL2L12 19q13.3 -BCL2L12 and Stomach Cancer
5
FYN 6q21 SLK, SYN, p59-FYN -FYN and Stomach Cancer
5
CCL2 17q11.2-q12 HC11, MCAF, MCP1, MCP-1, SCYA2, GDCF-2, SMC-CF, HSMCR30 -CCL2 and Stomach Cancer
5
NIN 14q22.1 SCKL7 -NIN and Stomach Cancer
5
MUC5B 11p15.5 MG1, MUC5, MUC9, MUC-5B -MUC5B and Stomach Cancer
5
ING1 13q34 p33, p47, p33ING1, p24ING1c, p33ING1b, p47ING1a -ING1 Supression in Gastric Cancer
5
GATA6 18q11.1-q11.2 -GATA6 and Stomach Cancer
5
HIC1 17p13.3 hic-1, ZBTB29, ZNF901 -HIC1 and Stomach Cancer
4
SOCS1 16p13.13 JAB, CIS1, SSI1, TIP3, CISH1, SSI-1, SOCS-1 -SOCS1 and Stomach Cancer
4
MBD2 18q21 DMTase, NY-CO-41 -MBD2 and Stomach Cancer
4
FGF3 11q13 INT2, HBGF-3 -FGF3 and Stomach Cancer
4
GPX1 3p21.3 GPXD, GSHPX1 -GPX1 and Stomach Cancer
4
CD55 1q32 CR, TC, DAF, CROM -CD55 and Stomach Cancer
4
CTTN 11q13 EMS1 -CTTN and Stomach Cancer
4
HHIP 4q28-q32 HIP -HHIP and Stomach Cancer
4
CCL5 17q12 SISd, eoCP, SCYA5, RANTES, TCP228, D17S136E, SIS-delta -CCL5 and Stomach Cancer
4
COL1A2 7q22.1 OI4 -COL1A2 and Stomach Cancer
4
S100A11 1q21 MLN70, S100C, HEL-S-43 -S100A11 and Stomach Cancer
4
MTSS1 8p22 MIM, MIMA, MIMB -MTSS1 and Stomach Cancer
4
SULF1 8q13.2 SULF-1, HSULF-1 -SULF1 and Stomach Cancer
4
DKK3 11p15.2 RIG, REIC -DKK3 and Stomach Cancer
4
FOXP1 3p14.1 MFH, QRF1, 12CC4, hFKH1B, HSPC215 -FOXP1 and Stomach Cancer
4
INHBA 7p15-p13 EDF, FRP -INHBA and Stomach Cancer
4
HOXD10 2q31.1 HOX4, HOX4D, HOX4E, Hox-4.4 -HOXD10 and Stomach Cancer
4
IRF1 5q31.1 MAR, IRF-1 -IRF1 and Stomach Cancer
4
PRKCA 17q22-q23.2 AAG6, PKCA, PRKACA, PKC-alpha -PRKCA and Stomach Cancer
4
AKR1C2 10p15-p14 DD, DD2, TDD, BABP, DD-2, DDH2, HBAB, HAKRD, MCDR2, SRXY8, DD/BABP, AKR1C-pseudo -AKR1C2 and Stomach Cancer
4
S100A10 1q21 42C, P11, p10, GP11, ANX2L, CAL1L, CLP11, Ca[1], ANX2LG -S100A10 and Stomach Cancer
4
HMOX1 22q13.1 HO-1, HSP32, HMOX1D, bK286B10 -HMOX1 and Stomach Cancer
4
ITGA4 2q31.3 IA4, CD49D -ITGA4 and Stomach Cancer
4
CYP1B1 2p22.2 CP1B, GLC3A, CYPIB1, P4501B1 -CYP1B1 and Stomach Cancer
4
LGALS4 19q13.2 GAL4, L36LBP -LGALS4 and Stomach Cancer
4
SPHK1 17q25.2 SPHK -SPHK1 and Stomach Cancer
4
CD86 3q21 B70, B7-2, B7.2, LAB72, CD28LG2 -CD86 and Stomach Cancer
4
PPARD 6p21.2 FAAR, NUC1, NUCI, NR1C2, NUCII, PPARB -PPAR delta and Stomach Cancer
4
AQP3 9p13 GIL, AQP-3 -AQP3 and Stomach Cancer
4
SST 3q28 SMST -SST and Stomach Cancer
4
RASAL1 12q23-q24 RASAL -RASAL1 and Stomach Cancer
4
MAGEB2 Xp21.3 DAM6, CT3.2, MAGE-XP-2 -MAGEB2 and Stomach Cancer
4
MAP2K4 17p12 JNKK, MEK4, MKK4, SEK1, SKK1, JNKK1, SERK1, MAPKK4, PRKMK4, SAPKK1, SAPKK-1 -MAP2K4 and Stomach Cancer
4
EGR2 10q21.1 AT591, CMT1D, CMT4E, KROX20 -EGR2 and Stomach Cancer
4
JAK3 19p13.1 JAKL, LJAK, JAK-3, L-JAK, JAK3_HUMAN -JAK3 and Stomach Cancer
4
IQGAP1 15q26.1 SAR1, p195, HUMORFA01 -IQGAP1 and Stomach Cancer
4
CLDN7 17p13.1 CLDN-7, CEPTRL2, CPETRL2, Hs.84359, claudin-1 -CLDN7 and Stomach Cancer
4
CLDN1 3q28-q29 CLD1, SEMP1, ILVASC -CLDN1 and Stomach Cancer
4
CD40 20q12-q13.2 p50, Bp50, CDW40, TNFRSF5 -CD40 and Stomach Cancer
4
PDX1 13q12.1 GSF, IPF1, IUF1, IDX-1, MODY4, PDX-1, STF-1, PAGEN1 -PDX1 and Stomach Cancer
4
MIRLET7G 3p21.1 LET7G, let-7g, MIRNLET7G, hsa-let-7g -MicroRNA let-7g and Stomach Cancer
4
ANGPT2 8p23.1 ANG2, AGPT2 -ANGPT2 and Stomach Cancer
4
IL12A 3q25.33 P35, CLMF, NFSK, NKSF1, IL-12A -IL12A and Stomach Cancer
4
SSTR1 14q13 SS1R, SS1-R, SRIF-2, SS-1-R -SSTR1 and Stomach Cancer
4
NBN 8q21 ATV, NBS, P95, NBS1, AT-V1, AT-V2 -NBN and Stomach Cancer
4
S100A8 1q21 P8, MIF, NIF, CAGA, CFAG, CGLA, L1Ag, MRP8, CP-10, MA387, 60B8AG -S100A8 and Stomach Cancer
4
HBEGF 5q23 DTR, DTS, DTSF, HEGFL -HBEGF and Stomach Cancer
4
CTSB 8p22 APPS, CPSB -CTSB and Stomach Cancer
4
SSTR3 22q13.1 SS3R, SS3-R, SS-3-R, SSR-28 -SSTR3 and Stomach Cancer
4
BCL2L11 2q13 BAM, BIM, BOD -BCL2L11 and Stomach Cancer
4
WNT11 11q13.5 HWNT11 -WNT11 and Stomach Cancer
3
HLA-E 6p21.3 MHC, QA1, EA1.2, EA2.1, HLA-6.2 -HLA-E and Stomach Cancer
3
INHA 2q35 -INHA and Stomach Cancer
3
B2M 15q21.1 -B2M and Stomach Cancer
3
S100A9 1q21 MIF, NIF, P14, CAGB, CFAG, CGLB, L1AG, LIAG, MRP14, 60B8AG, MAC387 -S100A9 and Stomach Cancer
3
ENDOU 12q13.1 P11, PP11, PRSS26 -ENDOU and Stomach Cancer
3
ADH1C 4q23 ADH3 -ADH1C and Stomach Cancer
3
PTK7 6p21.1-p12.2 CCK4, CCK-4 -PTK7 and Stomach Cancer
3
SERPINB5 18q21.33 PI5, maspin -SERPINB5 and Stomach Cancer
3
MCM7 7q21.3-q22.1 MCM2, CDC47, P85MCM, P1CDC47, PNAS146, PPP1R104, P1.1-MCM3 -MCM7 and Stomach Cancer
3
GSTM3 1p13.3 GST5, GSTB, GTM3, GSTM3-3 -GSTM3 and Stomach Cancer
3
EXO1 1q43 HEX1, hExoI -EXO1 and Stomach Cancer
3
PIK3R1 5q13.1 p85, AGM7, GRB1, IMD36, p85-ALPHA -PIK3R1 and Stomach Cancer
3
AKR1B10 7q33 HIS, HSI, ARL1, ARL-1, ALDRLn, AKR1B11, AKR1B12 -AKR1B10 and Stomach Cancer
3
HCK 20q11-q12 JTK9, p59Hck, p61Hck -HCK and Stomach Cancer
3
PAK4 19q13.2 -PAK4 and Stomach Cancer
3
SLPI 20q12 ALP, MPI, ALK1, BLPI, HUSI, WAP4, WFDC4, HUSI-I -SLPI and Stomach Cancer
3
NTRK3 15q25 TRKC, gp145(trkC) -NTRK3 and Stomach Cancer
3
ROR2 9q22 BDB, BDB1, NTRKR2 -ROR2 and Stomach Cancer
3
RARRES1 3q25.32 LXNL, TIG1, PERG-1 -RARRES1 and Stomach Cancer
3
SATB1 3p23 -SATB1 and Stomach Cancer
3
ADIPOR1 1q32.1 CGI45, PAQR1, ACDCR1, CGI-45, TESBP1A -ADIPOR1 and Stomach Cancer
3
HLA-G 6p21.3 MHC-G -HLA-G and Stomach Cancer
3
CBX7 22q13.1 -CBX7 and Stomach Cancer
3
ELF3 1q32.2 ERT, ESX, EPR-1, ESE-1 -ELF3 and Stomach Cancer
3
IFITM1 11p15.5 9-27, CD225, IFI17, LEU13, DSPA2a -IFITM1 and Stomach Cancer
3
HPSE 4q21.3 HPA, HPA1, HPR1, HSE1, HPSE1 -HPSE and Stomach Cancer
3
PER1 17p13.1 PER, hPER, RIGUI -PER1 and Stomach Cancer
3
SNAI1 20q13.2 SNA, SNAH, SNAIL, SLUGH2, SNAIL1, dJ710H13.1 -SNAI1 and Stomach Cancer
3
YWHAZ 8q23.1 HEL4, YWHAD, KCIP-1, HEL-S-3, 14-3-3-zeta -YWHAZ and Stomach Cancer
3
CASP10 2q33-q34 MCH4, ALPS2, FLICE2 -CASP10 and Stomach Cancer
3
MBL2 10q11.2 MBL, MBP, MBP1, MBPD, MBL2D, MBP-C, COLEC1, HSMBPC -MBL2 and Stomach Cancer
3
ROR1 1p31.3 NTRKR1, dJ537F10.1 -ROR1 and Stomach Cancer
3
MSI1 12q24 -MSI1 and Stomach Cancer
3
ANXA1 9q21.13 ANX1, LPC1 -ANXA1 and Stomach Cancer
3
IL13 5q31 P600, IL-13 -IL13 and Stomach Cancer
3
HDAC6 Xp11.23 HD6, JM21, CPBHM, PPP1R90 -HDAC6 and Stomach Cancer
3
RARRES3 11q23 RIG1, TIG3, HRSL4, HRASLS4, PLA1/2-3 -RARRES3 and Stomach Cancer
3
SUFU 10q24.32 SUFUH, SUFUXL, PRO1280 -SUFU and Stomach Cancer
3
CASP1 11q23 ICE, P45, IL1BC -CASP1 and Stomach Cancer
3
MLF1 3q25.1 -MLF1 and Stomach Cancer
3
WNT5B 12p13.3 -WNT5B and Stomach Cancer
3
CFLAR 2q33-q34 CASH, FLIP, MRIT, CLARP, FLAME, Casper, FLAME1, c-FLIP, FLAME-1, I-FLICE, c-FLIPL, c-FLIPR, c-FLIPS, CASP8AP1 -CFLAR and Stomach Cancer
2
GNL3 3p21.1 NS, E2IG3, NNP47, C77032 -GNL3 and Stomach Cancer
2
MAD1L1 7p22 MAD1, PIG9, TP53I9, TXBP181 -MAD1L1 and Stomach Cancer
2
MLH3 14q24.3 HNPCC7 -MLH3 and Stomach Cancer
2
PIN1 19p13 DOD, UBL5 -PIN1 and Stomach Cancer
2
SLC45A3 1q32.1 PRST, IPCA6, IPCA-2, IPCA-6, IPCA-8, PCANAP2, PCANAP6, PCANAP8 -SLC45A3 and Stomach Cancer
2
CASP6 4q25 MCH2 -CASP6 and Stomach Cancer
2
FEZ1 11q24.2 -FEZ1 and Stomach Cancer
2
ARHGEF1 19q13.13 LSC, GEF1, LBCL2, SUB1.5, P115-RHOGEF -ARHGEF1 and Stomach Cancer
2
RASSF10 11p15.2 -RASSF10 and Stomach Cancer
2
CDH3 16q22.1 CDHP, HJMD, PCAD -CDH3 and Stomach Cancer
2
DDX5 17q21 p68, HLR1, G17P1, HUMP68 -DDX5 and Stomach Cancer
2
YWHAE 17p13.3 MDS, HEL2, MDCR, KCIP-1, 14-3-3E -YWHAE and Stomach Cancer
2
LRRC3B 3p24 LRP15 -LRRC3B and Stomach Cancer
2
MIR124-1 8p23.1 MIR124A, MIR124A1, MIRN124-1, MIRN124A1 -microRNA 124-1 and Stomach Cancer
2
IGF1 12q23.2 IGFI, IGF-I, IGF1A -IGF1 and Stomach Cancer
2
NOS3 7q36 eNOS, ECNOS -NOS3 and Stomach Cancer
2
HSD17B1 17q11-q21 HSD17, EDHB17, EDH17B2, SDR28C1 -HSD17B1 and Stomach Cancer
2
ZNF331 19q13.42 RITA, ZNF361, ZNF463 -ZNF331 and Stomach Cancer
2
PDK1 2q31.1 -PDK1 and Stomach Cancer
2
CCND3 6p21 -CCND3 and Stomach Cancer
2
PTCH2 1p34.1 PTC2 -PTCH2 and Stomach Cancer
2
DMBT1 10q26.13 GP340, muclin -DMBT1 and Stomach Cancer
2
TNFRSF17 16p13.1 BCM, BCMA, CD269, TNFRSF13A -TNFRSF17 and Stomach Cancer
2
ST2 11p14.3-p12 -ST2 and Stomach Cancer
2
XRCC5 2q35 KU80, KUB2, Ku86, NFIV, KARP1, KARP-1 -XRCC5 and Stomach Cancer
2
TYK2 19p13.2 JTK1, IMD35 -TYK2 and Stomach Cancer
2
FRAT2 10q24.1 -FRAT2 and Stomach Cancer
2
LAMB3 1q32 AI1A, LAM5, LAMNB1, BM600-125KDA -LAMB3 and Stomach Cancer
2
ADAMTS9 3p14.1 -ADAMTS9 and Stomach Cancer
2
S100A7 1q21 PSOR1, S100A7c -S100A7 and Stomach Cancer
2
TNFRSF6B 20q13.3 M68, TR6, DCR3, M68E, DJ583P15.1.1 Amplification
Prognostic
-TNFRSF6B Amplification and Overexpression in Gastric Cancers
2
MMP13 11q22.3 CLG3, MANDP1, MMP-13 -MMP13 and Stomach Cancer
2
MT2A 16q13 MT2 -MT2A and Stomach Cancer
2
MALAT1 11q13.1 HCN, NEAT2, PRO2853, mascRNA, LINC00047, NCRNA00047 -MALAT1 and Stomach Cancer
2
MMP10 11q22.3 SL-2, STMY2 -MMP10 and Stomach Cancer
2
WRN 8p12 RECQ3, RECQL2, RECQL3 -WRN and Stomach Cancer
2
BAI1 8q24.3 GDAIF -BAI1 and Stomach Cancer
2
ANGPT1 8q23.1 AGP1, AGPT, ANG1 -ANGPT1 and Stomach Cancer
2
HLA-DRA 6p21.3 MLRW, HLA-DRA1 -HLA-DRA and Stomach Cancer
2
SUZ12 17q11.2 CHET9, JJAZ1 -SUZ12 and Stomach Cancer
2
PKD1 16p13.3 PBP, Pc-1, TRPP1 -PKD1 and Stomach Cancer
2
IL23R 1p31.3 -IL23R and Stomach Cancer
2
HSD17B2 16q24.1-q24.2 HSD17, SDR9C2, EDH17B2 -HSD17B2 and Stomach Cancer
2
MIR127 14q32.2 MIRN127, miRNA127 -MicroRNA miR-127 and Stomach Cancer
2
JAG2 14q32 HJ2, SER2 -JAG2 and Stomach Cancer
2
HAVCR2 5q33.3 TIM3, CD366, KIM-3, TIMD3, Tim-3, TIMD-3, HAVcr-2 -HAVCR2 and Stomach Cancer
2
ARNTL 11p15 TIC, JAP3, MOP3, BMAL1, PASD3, BMAL1c, bHLHe5 -ARNTL and Stomach Cancer
2
MUC3A 7q22 MUC3, MUC-3A -MUC3A and Stomach Cancer
2
EP300 22q13.2 p300, KAT3B, RSTS2 -EP300 and Stomach Cancer
2
CXCL16 17p13 SRPSOX, CXCLG16, SR-PSOX -CXCL16 and Stomach Cancer
1
CDK12 17q12 CRK7, CRKR, CRKRS -CDK12 and Stomach Cancer
1
MIR125A 19q13.41 MIRN125A, miRNA125A -MIR125A and Stomach Cancer
1
FOXA2 20p11 HNF3B, TCF3B -FOXA2 and Stomach Cancer
1
PDCD5 19q13.11 TFAR19 -PDCD5 and Stomach Cancer
1
MMP8 11q22.3 HNC, CLG1, MMP-8, PMNL-CL -MMP8 and Stomach Cancer
1
PLK2 5q12.1-q13.2 SNK, hSNK, hPlk2 -PLK2 and Stomach Cancer
1
COMT 22q11.21 HEL-S-98n -COMT and Stomach Cancer
1
TM4SF1 3q21-q25 L6, H-L6, M3S1, TAAL6 -TM4SF1 and Stomach Cancer
1
IRF8 16q24.1 ICSBP, IRF-8, ICSBP1, IMD32A, IMD32B, H-ICSBP -IRF8 and Stomach Cancer
1
PITX1 5q31.1 BFT, CCF, POTX, PTX1, LBNBG -PITX1 and Stomach Cancer
1
CTCFL 20q13.31 CT27, BORIS, CTCF-T, HMGB1L1, dJ579F20.2 -CTCFL and Stomach Cancer
1
PDPK1 16p13.3 PDK1, PDPK2, PDPK2P, PRO0461 -PDPK1 and Stomach Cancer
1
ABCC4 13q32 MRP4, MOATB, MOAT-B -ABCC4 and Stomach Cancer
1
SAT2 17p13.1 SSAT2 -SAT2 and Stomach Cancer
1
CTAG1B Xq28 CTAG, ESO1, CT6.1, CTAG1, LAGE-2, LAGE2B, NY-ESO-1 -CTAG1B and Stomach Cancer
1
LMNA 1q22 FPL, IDC, LFP, CDDC, EMD2, FPLD, HGPS, LDP1, LMN1, LMNC, PRO1, CDCD1, CMD1A, FPLD2, LMNL1, CMT2B1, LGMD1B -LMNA and Stomach Cancer
1
TCEAL7 Xq22.1 WEX5, MPMGp800C04260Q003 -TCEAL7 and Stomach Cancer
1
KDM5A 12p11 RBP2, RBBP2, RBBP-2 -KDM5A and Stomach Cancer
1
LAPTM4B 8q22.1 LC27, LAPTM4beta -LAPTM4B and Stomach Cancer
1
DNAJB4 1p31.1 DjB4, HLJ1, DNAJW -DNAJB4 and Stomach Cancer
1
NRP1 10p12 NP1, NRP, BDCA4, CD304, VEGF165R -NRP1 and Stomach Cancer
1
S100A3 1q21 S100E -S100A3 and Stomach Cancer
1
CBLB 3q13.11 Cbl-b, RNF56, Nbla00127 -CBLB and Stomach Cancer
1
RASSF7 11p15.5 HRC1, HRAS1, C11orf13 -RASSF7 and Stomach Cancer
1
IL16 15q26.3 LCF, NIL16, PRIL16, prIL-16 -IL16 and Stomach Cancer
1
PDCD1LG2 9p24.2 B7DC, Btdc, PDL2, CD273, PD-L2, PDCD1L2, bA574F11.2 -PDCD1LG2 and Stomach Cancer
1
NCKIPSD 3p21 DIP, DIP1, ORF1, WISH, VIP54, AF3P21, SPIN90, WASLBP -NCKIPSD and Stomach Cancer
1
ANXA7 10q22.2 SNX, ANX7, SYNEXIN -ANXA7 and Stomach Cancer
1
CHRNA5 15q24 LNCR2 -CHRNA5 and Stomach Cancer
1
IDO1 8p12-p11 IDO, INDO, IDO-1 -IDO1 and Stomach Cancer
1
RABEP1 17p13.2 RAB5EP, RABPT5 -RABEP1 and Stomach Cancer
1
DOK2 8p21.3 p56DOK, p56dok-2 -DOK2 and Stomach Cancer
1
HSP90AB1 6p12 HSP84, HSPC2, HSPCB, D6S182, HSP90B -HSP90AB1 and Stomach Cancer
1
TPM1 15q22.1 CMH3, TMSA, CMD1Y, LVNC9, C15orf13, HTM-alpha -TPM1 and Stomach Cancer
1
COPS6 7q22.1 CSN6, MOV34-34KD -COPS6 and Stomach Cancer
1
CXADR 21q21.1 CAR, HCAR, CAR4/6 -CXADR and Stomach Cancer
1
SHMT1 17p11.2 SHMT, CSHMT -SHMT1 and Stomach Cancer
1
NOX1 Xq22 MOX1, NOH1, NOH-1, GP91-2 -NOX1 and Stomach Cancer
1
MSI2 17q22 MSI2H -MSI2 and Stomach Cancer
1
PLCD1 3p22-p21.3 NDNC3, PLC-III -PLCD1 and Stomach Cancer
1
HSD3B1 1p13.1 I, HSD3B, HSDB3, HSDB3A, SDR11E1, 3BETAHSD -HSD3B1 and Stomach Cancer
1
CTCF 16q21-q22.3 MRD21 -CTCF and Stomach Cancer
1
SFRP4 7p14.1 FRP-4, FRPHE, sFRP-4 -SFRP4 and Stomach Cancer
1
SACS 13q12 SPAX6, ARSACS, DNAJC29, PPP1R138 -SACS and Stomach Cancer
1
SSTR5 16p13.3 SS-5-R -SSTR5 and Stomach Cancer
1
AQP1 7p14 CO, CHIP28, AQP-CHIP -AQP1 and Stomach Cancer
1
MTA1 14q32.3 -MTA1 and Stomach Cancer
1
CCL22 16q13 MDC, ABCD-1, SCYA22, STCP-1, DC/B-CK, A-152E5.1 -CCL22 and Stomach Cancer
1
HINT1 5q31.2 HINT, NMAN, PKCI-1, PRKCNH1 -HINT1 and Stomach Cancer
1
MIR10B 2q31.1 MIRN10B, mir-10b, miRNA10B, hsa-mir-10b -MIR10B and Stomach Cancer
1
BUB3 10q26 BUB3L, hBUB3 -BUB3 and Stomach Cancer
1
CTSD 11p15.5 CPSD, CLN10, HEL-S-130P -CTSD and Stomach Cancer
1
AFF3 2q11.2-q12 LAF4, MLLT2-like -AFF3 and Stomach Cancer
1
SETD1B 12q24.31 KMT2G, Set1B -SETD1B and Stomach Cancer
1
LRIG1 3p14 LIG1, LIG-1 -LRIG1 and Stomach Cancer
1
PDCD1 2q37.3 PD1, PD-1, CD279, SLEB2, hPD-1, hPD-l, hSLE1 -PDCD1 and Stomach Cancer
1
ZNRF3 22q12.1 RNF203, BK747E2.3 -ZNRF3 and Stomach Cancer
1
NQO2 6p25.2 QR2, DHQV, DIA6, NMOR2 -NQO2 and Stomach Cancer
1
HOXD11 2q31.1 HOX4, HOX4F -HOXD11 and Stomach Cancer
1
CYP2C8 10q23.33 CPC8, CYPIIC8, MP-12/MP-20 -CYP2C8 and Stomach Cancer
1
KLRK1 12p13.2-p12.3 KLR, CD314, NKG2D, NKG2-D, D12S2489E -KLRK1 and Stomach Cancer
1
HDAC4 2q37.3 HD4, AHO3, BDMR, HDACA, HA6116, HDAC-4, HDAC-A -HDAC4 and Stomach Cancer
1
CYBA 16q24 p22-PHOX -CYBA and Stomach Cancer
1
SETD2 3p21.31 HYPB, SET2, HIF-1, HIP-1, KMT3A, HBP231, HSPC069, p231HBP -SETD2 and Stomach Cancer
1

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

Latest Publications

Vernygorodskyi SV, Degtiariova LV, Iatsyna OI, et al.
[Role of transcription factors in transdifferentiation of the gastric mucosa].
Tsitol Genet. 2015 Mar-Apr; 49(2):42-7 [PubMed] Related Publications
The analysis of intestinal differentiation transcription factor CDX2 in the gastric mucosa biopsies has been carried out. It was established that CDX2 by itself promoter activation pathway can obtain intestinal phenotype for gastric mucosa cells. The loss of CDX2 expression in the nuclei of metaplastic epithelium may serve as a predictor of gastric mucosa malignization.

Park YS, Na YS, Ryu MH, et al.
FGFR2 Assessment in Gastric Cancer Using Quantitative Real-Time Polymerase Chain Reaction, Fluorescent In Situ Hybridization, and Immunohistochemistry.
Am J Clin Pathol. 2015; 143(6):865-72 [PubMed] Related Publications
OBJECTIVES: Fibroblast growth factor receptor 2 (FGFR2) amplification has been reported to be a target for treatment in gastric cancer. However, an optimal tissue source and method for evaluating FGFR2 have yet to be established.
METHODS: Copy numbers were compared by quantitative polymerase chain reaction (qPCR) using frozen vs formalin-fixed, paraffin-embedded (FFPE) tissue and biopsy vs surgical specimens. We correlated the results of qPCR and immunohistochemistry (IHC) with fluorescence in situ hybridization (FISH) using stage IV gastric cancer biopsy specimens and validated the results in surgical specimens.
RESULTS: FFPE tissues were suitable for qPCR, and biopsy specimens were equivalent to or better than surgical specimens. qPCR and IHC results exhibited an excellent correlation with FISH at eight or more copies by qPCR in any kind of tissue, 5% or more by IHC in biopsy specimens, and 10% or more by IHC in surgical specimens. FGFR2 amplification was 6.6% in stage IV gastric cancers, and 42% of these showed heterogeneous amplification and overexpression. IHC indicated a good correlation with FISH even in the heterogeneous cases.
CONCLUSIONS: FFPE biopsy tissues are an adequate source for FGFR2 evaluation in gastric carcinomas, and a qPCR-based copy number assay can be used for screening. IHC is also a valid and practical method for evaluating FGFR2, considering frequent heterogeneity.

Labrador L, Torres K, Camargo M, et al.
Association of common variants on chromosome 8q24 with gastric cancer in Venezuelan patients.
Gene. 2015; 566(1):120-4 [PubMed] Related Publications
Gastric cancer remains one of the leading causes of death in the world, being Central and South America among the regions showing the highest incidence and mortality rates worldwide. Although several single nucleotide polymorphisms (SNPs) identified in the chromosomal region 8q24 by genome-wide association studies have been related with the risk of different kinds of cancers, their role in the susceptibility of gastric cancer in Latin American populations has not been evaluated yet. Hereby, we performed a case-control study to explore the associations between three SNPs at 8q24 and gastric cancer risk in Venezuelan patients. We analyzed rs1447295, rs4733616 and rs6983267 SNPs in 122 paraffin-embedded tumor samples from archival bank and 129 samples with chronic gastritis (obtained by upper endoscopy during the study) from the Central Hospital of Barquisimeto (Lara, Venezuela). Genotypes were determined by PCR-RFLP reactions designed in this study for efficient genotyping of formalin-fixed/paraffin-embedded tissues. No significant differences in genotype frequencies between case and control groups were found. However, carriers of the homozygous TT genotype of SNP rs4733616 had an increased risk of developing poorly differentiated gastric cancer according to the codominant (OR=3.59, P=0.035) and the recessive models (OR=4.32, P=0.014, best-fitting model of inheritance), adjusted by age and gender. Our study suggests that the SNP rs4733616 is associated with susceptibility to poorly differentiated gastric cancer in Venezuelans. Additional studies are needed to further interrogate the prognostic value of the rs4733616 marker in this high-risk population for gastric cancer.

Yang G, Song JG, Li Y, Gong SP
[Under hypoxia condition contactin-1 regulates migration of MKN45 cells through RhoA pathway].
Mol Biol (Mosk). 2015 Jan-Feb; 49(1):129-37 [PubMed] Related Publications
Recent studies have suggested that contactin-1 has a key role in cancer cell proliferation and migration, however the detailed mechanism of this process is still unclear. Here, human gastric cancer cell line MKN45 was employed. It was found that under hypoxia conditions contactin-1 mRNA and protein levels were both up-regulated by HIF-1alpha expression. Furthermore, although hypoxia increased the migration rate of MKN45 cells, contactin-1 (CNTN1) shRNA reversed this process. Meanwhile, RhoA V14 and RhoA V14N19 mutation constructs were employed, and it was found that constitutively active form of RhoA reversed the cell migration suppression induced by contactin-1 knockdown, while dominant-negative form of RhoA blocked hypoxia induced hypermigration. Apart from this, contactin-1 displayed the ability to phosphorylate the RhoA activator p115 RhoGEF. Thus, under hypoxia conditions, elevated HIF-1alpha seems to up-regulate contactin-1 expression and by this activate RhoA and facilitate migration of cancer cells.

Jian T, Chen Y
Regulatory mechanisms of transcription factors and target genes on gastric cancer by bioinformatics method.
Hepatogastroenterology. 2015 Mar-Apr; 62(138):524-8 [PubMed] Related Publications
BACKGROUND/AIMS: Gastric cancer is one of the most lethal diseases and has caused a global health problem. We aimed to elucidate the major mechanisms involved in the gastric cancer progression.
METHODOLOGY: The expression profile GSE13911 was downloaded from GEO database, composing of 31 normal and 38 tumor samples. The transcription factor (TF)--target gene regulatory network and protein-protein interaction (PPI) network related to gastric cancer were obtained from TRED and TRANSFAC databases. After combining the two networks, we constructed an integrated network.
RESULTS: In total, 5255 DEGs in tumor samples were identified, which were mainly enriched in 12 pathways including cell cycle. The integrated network of TF--target gene--protein interaction included 7 genes related to cell cycle, in which E2F1 was predicted to mediate the expression of MCM4, MCM5 and CDC6 through regulating the expression of its target gene MCM3.
CONCLUSION: In gastric cancer progression, E2F1 may play vital roles in the involvement of cell cycle pathway through regulating its target gene MCM3, which might interact with MCM4, MCM5 and MCM7. Besides, STAT1 was another potentially critical transcription factor which could regulate multiple target genes.

Cristescu R, Lee J, Nebozhyn M, et al.
Molecular analysis of gastric cancer identifies subtypes associated with distinct clinical outcomes.
Nat Med. 2015; 21(5):449-56 [PubMed] Related Publications
Gastric cancer, a leading cause of cancer-related deaths, is a heterogeneous disease. We aim to establish clinically relevant molecular subtypes that would encompass this heterogeneity and provide useful clinical information. We use gene expression data to describe four molecular subtypes linked to distinct patterns of molecular alterations, disease progression and prognosis. The mesenchymal-like type includes diffuse-subtype tumors with the worst prognosis, the tendency to occur at an earlier age and the highest recurrence frequency (63%) of the four subtypes. Microsatellite-unstable tumors are hyper-mutated intestinal-subtype tumors occurring in the antrum; these have the best overall prognosis and the lowest frequency of recurrence (22%) of the four subtypes. The tumor protein 53 (TP53)-active and TP53-inactive types include patients with intermediate prognosis and recurrence rates (with respect to the other two subtypes), with the TP53-active group showing better prognosis. We describe key molecular alterations in each of the four subtypes using targeted sequencing and genome-wide copy number microarrays. We validate these subtypes in independent cohorts in order to provide a consistent and unified framework for further clinical and preclinical translational research.

Zavalishina LE, Andreeva IuIu, Vinogradov IIu, et al.
[Comparative study of the determination of the HER2 status in gastric cancer in the biopsy and intraoperative specimens].
Arkh Patol. 2014 Nov-Dec; 76(6):22-7 [PubMed] Related Publications
OBJECTIVE: To determine the HER2 status of gastric adenocarcinomas, by using biopsy and intraoperative specimens.
SUBJECTS AND METHODS: Immunohistochemistry and in situ hybridization were used to examine the HER2 status of 346 gastric cancer biopsy and intraoperative specimens.
RESULTS: The study conducted on a large Russian sample of 346 patients showed a positive HER2 status in 10.7% of the examined specimens. Intestinal-type adenocarcinomas exhibited a positive HER2 status in 21.4% of the cases. Comparative analysis of the HER2 status in the biopsy and intraoperative specimens indicated that there were differences in the determination of the tumor HER2 status in less than 1% of the examined specimens. The remaining found differences (14.7%) failed to change the tumor HER2 status and to affect the choice of a treatment regimen.
CONCLUSION: The performed investigation has demonstrated that the tumor HER2 status determined in the biopsy specimen significantly reflects the molecular biological properties of gastric cancer and may be clinically used to determine indications for the use of targeted drugs.

Wu P, Wang F, Wang Y, et al.
Significance of FBX8 in progression of gastric cancer.
Exp Mol Pathol. 2015; 98(3):360-6 [PubMed] Related Publications
F-box only protein 8 (FBX8), a novel component of F-box proteins, has recently been observed in several malignancies. However, its clinical implication in the progression of gastric cancer still remains unclear. The aim of this study was to explore the role of FBX8 in gastric cancer (GC) and analyze its correlation with tumor progression and prognosis. The expression of FBX8 in GC cell lines and matched pairs of fresh gastric cancer tissues were detected by real-time RT-PCR and Western blotting. Immunohistochemistry was used to analyze clinicopathological patterns of FBX8 in 136 cases of clinical paraffin-embedded GC tissues. A series of functional assays were conducted to evaluate the effect of FBX8 on proliferation and invasion in vitro and metastasis in vivo. FBX8 was markedly down-regulated in GC tissues compared to adjacent normal tissues. Patients with low FBX8 had shorter overall survival time and poor prognosis. Knocking down FBX8 obviously promoted proliferation and invasion in BGC823 cells, while over-expression of FBX8 in SGC7901 and AGS cells had the opposite effects. Moreover, FBX8 was sufficient to suppress metastasis in nude mice. Down-regulation of FBX8 significantly correlates with invasion, metastasis and poor survival time in GC patients. FBX8 may serve as a promising therapeutic target for inhibition of GC metastasis.

Cappellesso R, Fassan M, Hanspeter E, et al.
HER2 status in gastroesophageal cancer: a tissue microarray study of 1040 cases.
Hum Pathol. 2015; 46(5):665-72 [PubMed] Related Publications
Among patients with gastric cancer (GC) and gastroesophageal cancer (G-EC), HER2 amplification identifies those who may benefit from trastuzumab. HER2 status assessment, however, is influenced by preanalytic, analytic, and postanalytic variables. In a series of 5426 microarray cancer tissue cores obtained from 1040 GC/G-ECs (824 GC, 216 G-EC) and 720 synchronous nodal metastases, we evaluated both the performances of 2 different immunohistochemistry (IHC) protocols and the HER2 status intratumor variability. The prevalence of HER2 amplification and protein overexpression were assessed by chromogenic in situ hybridization and by 2 IHC protocols (CB11 and 4B5). HER2 was amplified in 114 (11%) of 1040 cases; in 6 (5.3%) of 114 cases, gene amplification only involved nodal metastasis. HER2 amplification prevailed in intestinal-type (P = .001) and low-grade (P < .001) tumors, showing no correlation with patients' age/sex, tumor location, stage, and Ming histotype. Overall, 12.5% and 13.7% of cases IHC scored 2+/3+ using the CB11-IHC and the 4B5-IHC protocol, respectively. HER2 amplification was not associated with protein overexpression (score 0/1+) in 11.4% and 6.2% of cases using the CB11-IHC and the 4B5-IHC protocol, respectively. The 4B5-IHC protocol proved more sensitive than CB11-IHC (93.9% versus 88.6%) and just as specific (96.1% versus 96.9%). Tested by chromogenic in situ hybridization, intratumor HER2 status was "substantially" consistent in different tissue cores obtained from the same case (κ = 0.78). Similar results were obtained for HER2 protein expression (CB11-IHC, κ = 0.78, and 4B5-IHC, κ = 0.83). Immunohistochemistry testing, however, fails in identifying about 10% of HER2-amplified cancers, potentially excluding these patients from anti-HER2 therapy.

Xu Q, Liu JW, Yuan Y
Comprehensive assessment of the association between miRNA polymorphisms and gastric cancer risk.
Mutat Res Rev Mutat Res. 2015 Jan-Mar; 763:148-60 [PubMed] Related Publications
Single nucleotide polymorphisms (SNPs) in pri- or pre-microRNAs (miRNAs) were found to be associated with gastric cancer risk. The aim of this study was to systematically review with update meta-analysis for the association of miRNA SNPs with gastric cancer risk. We systematically reviewed a total of 31 SNPs in the precursor genes of 29 miRNAs associated with overall cancer risk. Meanwhile, 13 case-control studies with a total of 9044 gastric cancer cases and 11,762 controls were included in a meta-analysis of five highly studied pre-miRNA SNPs (miR-146a rs2910164, miR-196a2 rs11614913, miR-499 rs3746444, miR-149 rs2292832 and miR-27a rs895819). Our results show both the homozygous miR-27a rs895819 and the miR-149 rs2292832 heterozygote genotype were associated with a decreased risk of gastric cancer when compared with wild type. In the stratified analysis, in some subgroup, heterozygous miR-146a rs2910164 was associated with a decreased risk of gastric cancer; and the variant genotype of miR-196a-2 rs11614913 was associated with an increased risk. No association was found between miR-499 rs3746444 and gastric cancer risk. In summary, miR-27a rs895819 and miR-149 rs2292832 are of potential forewarning ability for gastric cancer risk.

Zhang L, Xiao A, Ruggeri J, et al.
The germline CDH1 c.48 G>C substitution contributes to cancer predisposition through generation of a pro-invasive mutation.
Mutat Res. 2014; 770:106-11 [PubMed] Related Publications
Mutation screening of CDH1 is a standard of care for patients who meet criteria for Hereditary Diffuse Gastric Cancer (HDGC). In this setting, the classification of the sequence variants found in CDH1 is a critical step for risk management of patients with HDGC. In this report, we describe a germline CDH1 c.48 G>C variant found in a 21 year old woman and her living great uncle, who were both diagnosed with gastric cancer and belong to a family with high incidence of this type of cancer. This variant occurs at the last nucleotide of exon 1 and presumably results in a Gln-to-His change at codon 16 (Q16H). We used cloning strategies to evaluate the effects on mRNA stability and found that 5/27 and 0/17 clones have the "C" mutant allele in patient and her great uncle, respectively. In vitro functional studies revealed that the germline missense mutant (Q16H) had a pro-invasive cell behavior. Both results (functional and clinical) support the conclusion that the CDH1 c.48 G>C (Q16H) variant contributes to HDGC through the generation of a pathogenic missense mutation with loss of anti-invasive function.

Zhang QY, Cheng WX, Li WM, et al.
Occurrence of low frequency PIK3CA and AKT2 mutations in gastric cancer.
Mutat Res. 2014; 769:108-12 [PubMed] Related Publications
The PI3K/AKT signal transduction pathway has distinct functional roles in tumor progression. PIK3CA was reported to harbor the hot-spot in many types of tumor. Akt, the downstream of PI3K, its family members especially AKT2 activation in human cancer has been extensively studied, but its activation by mutation was less reported. The occurrence of PIK3CA and AKT2 mutations in a variety of cancers indicates their important involvement in carcinogenesis. Therefore, we investigated their mutation frequencies in gastric cancer (GC) in China. In our study, we selected hot-spot related exons 9, 18 and 20 of PIK3CA and kinase domain exons 6-14 of AKT2 genes were screened in 10 GC cell lines, 100 advanced primary GC and matched normal tissues. Denaturing high performance liquid chromatography (DHPLC) and DNA sequencing were used to analyze the mutations in the two genes. Two point mutations in the PIK3CA gene were identified in 4 of 10 GC cell lines and in 4 of 100 GC primary tumors. Two polymorphisms in AKT2 were detected in 19 of 100 GC primary tumors. One point mutation in AKT2 was detected in 1 of 10 GC cell lines and 3 of 100 GC primary tumors but no hot spot variation was detected. Our results indicate that PIK3CA and AKT2 mutations occurred at low frequency in GC, and suggest that the PIK3CA/AKT2 pathway might engage other events during gastric carcinogenesis.

Wang S, Lv C, Jin H, et al.
A common genetic variation in the promoter of miR-107 is associated with gastric adenocarcinoma susceptibility and survival.
Mutat Res. 2014; 769:35-41 [PubMed] Related Publications
BACKGROUND: Global miRNA expression profile has been widely used to characterize human cancers. It is well established that genetic variants in miRNAs can modulate miRNA biogenesis and disease risk.
METHODS: Genome-wide miRNA microarray was employed for assessment of miRNA expression profile of gastric adenocarcinoma (GAC). The variants of significantly dysregulated miRNA were genotyped in test (715 cases and 804 controls) and validation (940 cases and 1050 controls) subject sets.
RESULTS: MiRNA microarray revealed that 12 miRNAs including miR-107 significantly dysregulated in GAC tissues. The sequencing of the promoter of miR-107 identified 3 SNPs (rs11185777, rs78591545, and rs2296616) with minor allele frequency (MAF)>5%. Analyzing their association with GAC risk and prognosis revealed that the C allele of rs2296616 (T>C) was significantly associated with the decreased risk of GAC among the test, validation and combined sets (TC/CC vs. TT, adjusted OR=0.39, 95% CI=0.31-0.49 for the combined set). However, the C allele was related to an unfavorable prognosis of Cardia GAC (CGAC) (adjusted HR=1.49, 95% CI=1.01-2.20). In vivo evidence showed that the individuals with the rs2296616C allele had lower miR-107 expression compared with the homozygous T allele carriers.
CONCLUSION: miR-107 is dysregulated in GAC pathogenesis and the SNP rs2296616 may play a role in the process.

Kuo WT, Ho MR, Wu CW, et al.
Interrogation of microRNAs involved in gastric cancer using 5p-arm and 3p-arm annotated microRNAs.
Anticancer Res. 2015; 35(3):1345-52 [PubMed] Related Publications
MicroRNAs are derived from endogenous stem-loop precursors, and play important roles in various biological processes. From next-generation sequencing data, it is suggested that both the 5p-arm and 3p-arm of mature miRNAs could be generated from a single miRNA hairpin precursor; however, the current miRNA databases fail to provide comprehensive arm annotation features, which could result in ambiguous and incomplete analyses. In the present report, we have annotated over 99.7% of miRNAs with the correct 5p-arm and 3p-arm features. The length distribution of all annotated miRNAs is around 22 nucleotides; however, the 5p-arm miRNAs seem to be longer than those of the 3p-arm, which is evident in the 23-nucleotide group. Our study effort generates comprehensive miRNA arm-feature annotation which can be utilized for better interrogation of miRNAs. In further analysis of human gastric cancer tissues, we identified 38 down-regulated miRNAs and 22 up-regulated arm-specific miRNAs using this new comprehensives miRNA list.

Dong Y, Chen G, Gao M, Tian X
Increased expression of MMP14 correlates with the poor prognosis of Chinese patients with gastric cancer.
Gene. 2015; 563(1):29-34 [PubMed] Related Publications
The role of matrix metalloproteinase 14 (MMP14) has been identified to involve tumor progression and prognosis. The purpose of this study is to investigate the role of MMP14 in tumor progression and prognosis of gastric cancer. This study indicated that MMP14 mRNA and protein were overexpressed in gastric cancer tissue (P<0.001 and P=0.037, respectively) and significantly associated with clinical stage (P=0.005), lymph node metastasis (P=0.003), and distant metastasis (P=0.017). Moreover, we found that the overexpression of MMP14 was a significant predictor of poor prognosis for gastric cancer patients (P<0.001). Furthermore, we performed a meta-analysis which included 594 cases from 3 studies and showed that MMP14 overexpression was a significantly poor prognostic factor in Chinese patients with gastric cancer and HR (95% CI) was 2.17 (1.64-2.86). In conclusion, MMP14 plays an important role on gastric cancer progression and prognosis and acts as a convictive biomarker for prognostic prediction for Chinese patients with gastric cancer.

Zhou J, Yong WP, Yap CS, et al.
An integrative approach identified genes associated with drug response in gastric cancer.
Carcinogenesis. 2015; 36(4):441-51 [PubMed] Related Publications
Gastric cancer (GC) is the second leading cause of global cancer mortality worldwide. However, the molecular mechanism underlying its carcinogenesis and drug resistance is not well understood. To identify novel functionally important genes that were differentially expressed due to combinations of genetic and epigenetic changes, we analyzed datasets containing genome-wide mRNA expression, DNA copy number alterations and DNA methylation status from 154 primary GC samples and 47 matched non-neoplastic mucosa tissues from Asian patients. We used concepts of 'within' and 'between' statistical analysis to compare the difference between tumors and controls within each platform, and assessed the correlations between platforms. This 'multi-regulated gene (MRG)' analysis identified 126 differentially expressed genes that underwent a combination of copy number and DNA methylation changes. Most genes were located at genomic loci associated with GC. Statistical enrichment analysis showed that MRGs were enriched for cancer, GC and drug response. We analysed several MRGs that previously had not been associated with GC. Knockdown of DDX27, TH1L or IDH3G sensitized cells to epirubicin or cisplatin, and knockdown of RAI14 reduced cell proliferation. Further studies showed that overexpression of DDX27 reduced epirubicin-induced DNA damage and apoptosis. Levels of DDX27 mRNA and protein were increased in early-stage gastric tumors, and may be a potential diagnostic and prognostic marker for GC. In summary, we used an integrative bioinformatics strategy to identify novel genes that are altered in GC and regulate resistance of GC cells to drugs in vitro.

Shinozaki-Ushiku A, Kunita A, Isogai M, et al.
Profiling of Virus-Encoded MicroRNAs in Epstein-Barr Virus-Associated Gastric Carcinoma and Their Roles in Gastric Carcinogenesis.
J Virol. 2015; 89(10):5581-91 [PubMed] Article available free on PMC after 15/11/2015 Related Publications
UNLABELLED: Epstein-Barr virus (EBV) is one of the major oncogenic viruses and is found in nearly 10% of gastric carcinomas. EBV is known to encode its own microRNAs (miRNAs); however, their roles have not been fully investigated. The present report is the largest series to comprehensively profile the expression of 44 known EBV miRNAs in tissue samples from patients with EBV-associated gastric carcinoma. Several miRNAs were highly expressed in EBV-associated gastric carcinoma, and in silico analysis revealed that the target genes of these EBV miRNAs had functions associated with cancer-related pathways, especially the regulation of apoptosis. Apoptosis was reduced in EBV-associated gastric carcinoma tissue samples, and gastric carcinoma cell lines infected with EBV exhibited downregulation of the proapoptotic protein Bid (the BH3-interacting domain death agonist), a member of the Bcl-2 family. The luciferase activity of the reporter vector containing the 3' untranslated region of BID was inhibited by an ebv-miR-BART4-5p mimic in gastric cancer cell lines. Transfection of an ebv-miR-BART4-5p mimic reduced Bid expression in EBV-negative cell lines, leading to reduced apoptosis under serum deprivation. The inhibition of ebv-miR-BART4-5p expression was associated with partial recovery of Bid levels in EBV-positive cell lines. The results demonstrated the antiapoptotic role of EBV miRNA via regulation of Bid expression in EBV-associated gastric carcinoma. These findings provide novel insights in the roles of EBV miRNAs in gastric carcinogenesis, which would be a potential therapeutic target.
IMPORTANCE: This report is the largest series to comprehensively profile the expression of 44 known EBV miRNAs in clinical samples from EBV-associated gastric carcinoma patients. Of the EBV miRNAs, ebv-miR-BART4-5p plays an important role in gastric carcinogenesis via regulation of apoptosis.

Yamanoi K, Arai E, Tian Y, et al.
Epigenetic clustering of gastric carcinomas based on DNA methylation profiles at the precancerous stage: its correlation with tumor aggressiveness and patient outcome.
Carcinogenesis. 2015; 36(5):509-20 [PubMed] Article available free on PMC after 15/11/2015 Related Publications
The aim of this study was to clarify the significance of DNA methylation alterations during gastric carcinogenesis. Single-CpG resolution genome-wide DNA methylation analysis using the Infinium assay was performed on 109 samples of non-cancerous gastric mucosa (N) and 105 samples of tumorous tissue (T). DNA methylation alterations in T samples relative to N samples were evident for 3861 probes. Since N can be at the precancerous stage according to the field cancerization concept, unsupervised hierarchical clustering based on DNA methylation levels was performed on N samples (βN) using the 3861 probes. This divided the 109 patients into three clusters: A (n = 20), B1 (n = 20), and B2 (n = 69). Gastric carcinomas belonging to Cluster B1 showed tumor aggressiveness more frequently than those belonging to Clusters A and B2. The recurrence-free and overall survival rates of patients in Cluster B1 were lower than those of patients in Clusters A and B2. Sixty hallmark genes for which βN characterized the epigenetic clustering were identified. We then focused on DNA methylation levels in T samples (βT) of the 60 hallmark genes. In 48 of them, including the ADAM23, OLFM4, AMER2, GPSM1, CCL28, DTX1 and COL23A1 genes, βT was again significantly correlated with tumor aggressiveness, and the recurrence-free and/or overall survival rates. Multivariate analyses revealed that βT was a significant prognostic factor, being independent of clinicopathological parameters. These data indicate that DNA methylation profiles at the precancerous stage may be inherited by gastric carcinomas themselves, thus determining tumor aggressiveness and patient outcome.

Xia P, Song CL, Liu JF, et al.
Prognostic value of circulating CD133(+) cells in patients with gastric cancer.
Cell Prolif. 2015; 48(3):311-7 [PubMed] Related Publications
OBJECTIVES: Gastric cancer is an important cause of cancer-related mortality worldwide (1). There is increasing evidence that the existence of cancer stem cells (CSC) is responsible for tumour formation and maintenance.
MATERIALS AND METHODS: The present study was designed to recognise circulating CSCs from blood samples of patients with gastric cancer, using CD133 and ABCG2 as potential markers. CD133(-) , CD133(+)  ABCG2(-) and CD133(+)  ABCG2(+) cells lines were analysed by flow cytometry, immunofluorescence staining, western blotting and real-time PCR. Furthermore, functional assays (clonogenic assay in vitro and tumourigenic assay in vivo) were also performed using these cell lines.
RESULTS: Higher percentages of CD133(+) cells were identified in blood samples from gastric cancer patients compared to normal controls. In addition, we found by using Kaplan-Meier analysis, that numbers of CD133(+) cells correlated with poor prognosis gastric cancer patients. Finally, tumourigenic properties of CD133(+)  ABCG2(+) cells were determined in vitro and in vivo.
CONCLUSIONS: Our in vitro and in vivo experiments demonstrated that CD133(+)  ABCG2(+) cells exhibited well-known CSC characteristics; thus when circulating they could be used as a prognostic marker for gastric cancer.

Miao ZF, Wang ZN, Zhao TT, et al.
TRIM24 is upregulated in human gastric cancer and promotes gastric cancer cell growth and chemoresistance.
Virchows Arch. 2015; 466(5):525-32 [PubMed] Related Publications
The tripartite motif protein tripartite motif-containing 24 (TRIM24) is involved in human cancer progression. However, the expression pattern and biological roles of TRIM24 in human gastric cancer have not been studied. Here, we report that expression of TRIM24 protein was upregulated in 65 of 133 gastric cancer specimens. TRIM24 upregulation positively correlated with clinical stage, local invasion, and poor patient prognosis. We overexpressed TRIM24 by transfection in SGC-7901 cells and used an siRNA strategy to knock down TRIM24 in MKN-1 cells. MTT and colony formation assays showed that transfection of TRIM24 plasmid accelerated, while its depletion inhibited cell proliferation rate. TRIM24 overxpression also induced chemoresistance to 5-FU in gastric cancer cells. Further analysis showed that TRIM24 overexpression upregulated cyclin D1 and Akt phosphorylation. Akt inhibitor LY294002 reversed the role of TRIM24 on chemoresistance. In conclusion, our study shows that TRIM24 is overexpressed in human gastric cancer and accelerates cell growth as well as induce chemoresistance, possibly through the Akt pathway.

Zhang D, Xiao YF, Zhang JW, et al.
miR-1182 attenuates gastric cancer proliferation and metastasis by targeting the open reading frame of hTERT.
Cancer Lett. 2015; 360(2):151-9 [PubMed] Related Publications
In humans, telomerase reverse transcriptase (hTERT) determines the activity of telomerase. hTERT is an ideal anticancer target because it is universally expressed in cancer cells and plays a crucial role in carcinogenesis. In this study, we report the miR-1182-mediated post-transcriptional regulation of hTERT. Over-expression of miR-1182 in different gastric cancer cells decreased hTERT protein levels. Bioinformation and dual-luciferase assays revealed that miR-1182 modulated hTERT by binding to its open reading frame (ORF), and this miRNA recognizes elements in the nucleotide region between 2695 and 2719 of hTERT mRNA. Over-expression of hTERT by transfecting pIRES2-hTERT into U2OS cells was abolished by miR-1182, while pIRES2-hTERT-MT, in which miR-1182 target site was synonymously mutated, failed to respond to miR-1182. Further investigation revealed that miR-1182 inhibited gastric cancer proliferation and migration by targeting the ORF1 of hTERT. We also found that miR-1182 could attenuate the proliferative and metastatic potential of SGC-7901 cell in vivo. Moreover, we found a statistically significant inverse correlation between miR-1182 and hTERT protein levels in tissues from 42 gastric cancer patients. These data indicate that miR-1182 suppresses TERT, and thus it could be an effective target for the treatment of gastric cancer.

Wang J, Song YX, Wang ZN
Non-coding RNAs in gastric cancer.
Gene. 2015; 560(1):1-8 [PubMed] Related Publications
Non-coding RNAs (ncRNAs) have recently become increasingly important in the study of cellular metabolism and regulation such as development, proliferation, differentiation and apoptosis. However, the functions of most ncRNAs have remained largely unknown. Recently, studies have begun to characterize the aberrant regulation of ncRNAs in gastric cancer (GC) cells and tissues. These ncRNAs have a close relationship with drug resistance, and with the occurrence, development, invasion and metastasis of tumors, so they could possibly become new therapeutic targets and treatment tools for GC in the future. The present review summarized current advances in our knowledge of the roles of ncRNAs in GC.

Zhang L, Xia L, Zhao L, et al.
Activation of PAX3-MET pathways due to miR-206 loss promotes gastric cancer metastasis.
Carcinogenesis. 2015; 36(3):390-9 [PubMed] Related Publications
MicroRNAs (miRNAs) are thought to have an important role in tumor metastasis by regulating diverse cellular pathways. Here, we describe the function and regulation network of miR-206 in gastric cancer (GC) metastasis. MiR-206 expression was downregulated in GC cells especially in high metastatic potential cells and was also significantly decreased in metastatic lesions compared with their corresponding primary tumor samples. Both gain- and loss-of-function studies confirmed that miR-206 significantly suppressed GC cell invasion and metastasis both in vitro and in vivo. Mechanistically, paired box gene 3 (PAX3) was identified as a functional target of miR-206 in GC cells. MiR-206 inhibited GC metastasis by negatively regulating expression of PAX3. In addition, PAX3 expression was markedly higher in GC tissues than in adjacent non-cancerous tissues. GC patients with positive PAX3 expression had shorter overall survival times. Transwell assays and in vivo metastasis assays demonstrated that overexpression of PAX3 significantly promoted the invasiveness and pulmonary metastasis of GC cells. On the other hand, downregulation of PAX3 markedly reduced cell metastatic potential. Mechanistic investigations indicated that prometastasis function of PAX3 was mediated by upregulating downstream target MET. Moreover, we found that levels of PAX3 and MET were positively correlated in matched human GC specimens, and their coexpression was associated with poor prognoses. In conclusion, our results reveal that miR-206-PAX3-MET signaling is critical to GC metastasis. Targeting the pathway described here may open new therapeutic prospects to restrict the metastatic potential of GC.

Yanjun X, Wenming C, Lisha Y, et al.
Detection of CDH1 gene variants in early-onset diffuse gastric cancer in Chinese patients.
Clin Lab. 2014; 60(11):1823-30 [PubMed] Related Publications
BACKGROUND: The type and frequency of E-cadherin (CDH1) germline variants in China for the early-onset diffuse gastric cancer (EODGC) has not been well established. Our study tend to screen and characterize germline variants for CDH1 gene in EODGC patients and in general population in China.
METHODS: Peripheral blood samples were collected from 57 EODGC patients (age ≤ 40 years) who underwent resection surgery for primary gastric cancer. DNA was extracted from peripheral blood leucocytes and polymerase chain reaction amplification (PCR) was performed to amplify and sequence the CDH1 gene. Statistical analysis was performed using the SPSS 19 software.
RESULTS: CDH1 genetic screening results: 2 missense in exon 5 (c.778G > C, 26.3%) and 12 (c.2012C > G, 1.8%), and 1 synonymous (c.2200T > C, 72.8%) in exon 13. According to the c.2200T > C variant, the CDH1 C frequency was 62.3% and the T frequency 37.7%, while the CC homozygote frequency was 43.9%, the TT homozygote 19.3% and the CT heterozygote 36.8%. According to the c.778G > C variant, the CDH1 C frequency was 15.8% and the G frequency 84.2%, while the GG homozygote frequency was 68.4%, the GC heterozygote 31.6%. When comes to the c.2012C > G variant, the CDH1 C frequency was 98.2% and the G frequency 1.8%, while the CC homozygote frequency was 96.5%, the GC heterozygote 3.5%. Statistical association was analyzed among the EODGC patients and BDs group tested for the three variants. Lymph node metastasis rate was found to be significantly higher in patients with c.2200T > C (P = 0.04). The difference in OS with or without c.2200T > C variant was found to be sig- nificant (P < 0.05).
CONCLUSIONS: No deletions or insertions were found in the CDH1 exon boundaries. All of the variants resulted com- mon polymorphisms. CDH1 germline variants are present in EODGC patients in Chinese population, but they are mainly missense variants with unknown function which are likely associated with lymph node metastasis and OS.

Oliveira C, Pinheiro H, Figueiredo J, et al.
Familial gastric cancer: genetic susceptibility, pathology, and implications for management.
Lancet Oncol. 2015; 16(2):e60-70 [PubMed] Related Publications
Familial gastric cancer comprises at least three major syndromes: hereditary diffuse gastric cancer, gastric adenocarcinoma and proximal polyposis of the stomach, and familial intestinal gastric cancer. The risk of development of gastric cancer is high in families affected b-y these syndromes, but only hereditary diffuse gastric cancer is genetically explained (caused by germline alterations of CDH1, which encodes E-cadherin). Gastric cancer is also associated with a range of several cancer-associated syndromes with known genetic causes, such as Lynch, Li-Fraumeni, Peutz-Jeghers, hereditary breast-ovarian cancer syndromes, familial adenomatous polyposis, and juvenile polyposis. We present contemporary knowledge on the genetics, pathogenesis, and clinical features of familial gastric cancer, and discuss research and technological developments, which together are expected to open avenues for new genetic testing approaches and novel therapeutic strategies.

Wan X, Ding X, Chen S, et al.
The functional sites of miRNAs and lncRNAs in gastric carcinogenesis.
Tumour Biol. 2015; 36(2):521-32 [PubMed] Article available free on PMC after 15/11/2015 Related Publications
Gastric cancer is one of the most common malignant diseases and has one of the highest mortality rates worldwide. Its molecular mechanisms are poorly understood. Recently, the functions of non-coding RNAs (ncRNAs) in gastric cancer have attracted wide attention. Although the expression levels of various ncRNAs are different, they may work together in a network and contribute to gastric carcinogenesis by altering the expression of oncogenes or tumor suppressor genes. They affect the cell cycle, apoptosis, motility, invasion, and metastasis. Dysregulated microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), including miR-21, miR-106, H19, and ANRIL, directly or indirectly regulate carcinogenic factors or signaling pathways such as PTEN, CDK, caspase, E-cadherin, Akt, and P53. Greater recognition of the roles of miRNAs and lncRNAs in gastric carcinogenesis can provide new insight into the mechanisms of tumor development and identify targets for anticancer drug development.

Huang X, Zhang Y, Gao Z
Plasmablastic lymphoma of the stomach with C-MYC rearrangement in an immunocompetent young adult: a case report.
Medicine (Baltimore). 2015; 94(4):e470 [PubMed] Related Publications
Plasmablastic lymphoma (PBL) is a rare B-cell neoplasm mostly described in human immunodeficiency virus-infected patients. Herein, we described a case of PBL presenting as gastric mass in a 21-year-old young adult without known immunodeficiency. The histological examination of the specimen showed a diffuse proliferation of round- to oval-shaped large cells with scant cytoplasm, and prominent nucleoli. The neoplasm stained positively for CD45, CD38, MUM1, and Vs38C, but typical B-cell and T-cell markers (PAX5, CD20, CD79a, and CD3) were absent. The proliferative index (Ki-67) was about 95%. And the neoplastic cells diffusely expressed the c-myc protein. Epstein-Barr virus-encoded RNA in situ hybridization was negative. Molecular genetic study via interphase fluorescence in situ hybridization disclosed the rearrangement involving c-myc gene. Awareness of this distinctive lymphoma can prevent misdiagnosis by the clinicians and/or the pathologists.

Xu XC, Zhang YH, Zhang WB, et al.
MicroRNA-133a functions as a tumor suppressor in gastric cancer.
J Biol Regul Homeost Agents. 2014 Oct-Dec; 28(4):615-24 [PubMed] Related Publications
MicroRNAs (miRNAs) are small and highly conserved non-coding RNAs that regulate gene expression of target mRNAs through posttranscriptional inhibition involved in the tumorigenesis and progression of multiple malignancies. Although miR-133a has been shown to function as a tumor suppressor in some cancers, the clinical significance and function of miR-133a in gastric cancer remain unclear. Hence, we were focused on the expression and mechanisms of miR-133a in the development of gastric cancer in this study. It was found that the expression of miR-133a was downregulated (P<0.001), while transgelin-2 (TAGLN2) was upregulated (P<0.05) in primary gastric cancer tissues, compared to the adjacent non-cancerous tissues (ANCT). Furthermore, decreased expression of miR-133a and increased expression of TAGLN2 were both associated with lymph node metastases in patients with gastric cancer (P<0.001; P=0.011). Functional analysis studies revealed that ectopic expression of miR-133a reduced cell proliferation and invasion, and induced cell apoptosis and cycle arrest via suppressing the level of TAGLN2 from transcriptional and translational levels and downregulated the expression of proliferating cell nuclear antigen (PCNA) and matrix metalloproteinase-2 (MMP-2) in gastric cancer cells. In conclusion, these results demonstrate that decreased expression of miR-133a is associated with the lymph node metastases of patients with gastric cancer. Overexpression of miR-133a inhibits cell growth and invasion and induces cell apoptosis and cycle arrest through repressing TAGLN2 gene, suggesting that miR-133a might be used as a biomarker or therapeutic target for the treatment of gastric cancer.

Marano L, Roviello F
The distinctive nature of HER2-positive gastric cancers.
Eur J Surg Oncol. 2015; 41(3):271-3 [PubMed] Related Publications

Yang S, Lu M, Chen Y, et al.
Overexpression of eukaryotic elongation factor 1 alpha-2 is associated with poorer prognosis in patients with gastric cancer.
J Cancer Res Clin Oncol. 2015; 141(7):1265-75 [PubMed] Related Publications
PURPOSE: Eukaryotic elongation factor 1 alpha-2 (eEF1A2) is a protein translation factor involved in protein synthesis. It is overexpressed in various cancers, which indicates potential vital functions in tumorigenesis and progression. Our study aims to investigate the expression levels of eEF1A2 in gastric cancer and its roles in clinical practice.
METHODS: A total of 129 patients with pathologically confirmed gastric cancer and 24 normal controls were recruited for this study. The expression levels of eEF1A2 in gastric cancer and normal tissues were evaluated by tissue microarrays, quantitative real-time PCR, and western blot analysis. Kaplan-Meier analysis and Cox's proportional hazards model were used in survival analysis.
RESULTS: Compared with corresponding controls, gastric cancer specimens had significantly increased expressions of eEF1A2 at mRNA and protein levels (both P < 0.05). Moreover, multivariate analysis confirmed that overexpression of eEF1A2 was a significant and independent indicator for predicting poor prognosis of gastric cancer.
CONCLUSIONS: Our results showed for the first time that overexpression of eEF1A2 was correlated with worse outcomes in gastric cancer patients, suggesting its critical roles in the carcinogenesis of gastric cancer.

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