Lung Cancer

Overview

Literature Analysis

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

Mutated Genes and Abnormal Protein Expression (829)

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
SCLC1 3p23-p21 SCCL, SCLC -SCLC1 and Lung Cancer
3000
EGFR 7p11.2 ERBB, HER1, mENA, ERBB1, PIG61, NISBD2 -EGFR and Lung Cancer
3000
KRAS 12p12.1 NS, NS3, CFC2, RALD, KRAS1, KRAS2, RASK2, KI-RAS, C-K-RAS, K-RAS2A, K-RAS2B, K-RAS4A, K-RAS4B, c-Ki-ras2 -KRAS and Lung Cancer
1345
TP53 17p13.1 P53, BCC7, LFS1, TRP53 -TP53 mutations in Lung Cancer
1314
MKI67 10q26.2 KIA, MIB-, MIB-1, PPP1R105 -MKI67 and Lung Cancer
566
ALK 2p23 CD246, NBLST3 -ALK and Lung Cancer
555
ERBB2 17q12 NEU, NGL, HER2, TKR1, CD340, HER-2, MLN 19, HER-2/neu -ERBB2 and Lung Cancer
489
CDKN2A 9p21.3 ARF, MLM, P14, P16, P19, CMM2, INK4, MTS1, TP16, CDK4I, CDKN2, INK4A, MTS-1, P14ARF, P19ARF, P16INK4, P16INK4A, P16-INK4A -CDKN2A and Lung Cancer
453
MET 7q31.2 HGFR, AUTS9, RCCP2, c-Met, DFNB97 -C-MET and Lung Cancer
441
PTEN 10q23.31 BZS, DEC, CWS1, GLM2, MHAM, TEP1, MMAC1, PTEN1, 10q23del -PTEN and Lung Cancer
405
GSTM1 1p13.3 MU, H-B, GST1, GTH4, GTM1, MU-1, GSTM1-1, GSTM1a-1a, GSTM1b-1b -GSTM1 and Lung Cancer
-Tabacco smoke, GSTM1 Polymorphisms and Suceptability to Lung Cancer
274
BRAF 7q34 NS7, B-raf, BRAF1, RAFB1, B-RAF1 -BRAF and Lung Cancer
357
MTOR 1p36.22 SKS, FRAP, FRAP1, FRAP2, RAFT1, RAPT1 -MTOR and Lung Cancer
326
EML4 2p21 C2orf2, ELP120, EMAP-4, EMAPL4, ROPP120 -EML4 and Lung Cancer
290
CTNNB1 3p22.1 CTNNB, MRD19, armadillo -CTNNB1 and Lung Cancer
265
AKT1 14q32.33 AKT, PKB, RAC, CWS6, PRKBA, PKB-ALPHA, RAC-ALPHA -AKT1 and Lung Cancer
260
ERCC1 19q13.32 UV20, COFS4, RAD10 -ERCC1 and Lung Cancer
259
CASP3 4q35.1 CPP32, SCA-1, CPP32B -CASP3 and Lung Cancer
246
ROS1 6q22.1 ROS, MCF3, c-ros-1 -ROS1 and Lung Cancer
241
PIK3CA 3q26.32 MCM, CWS5, MCAP, PI3K, CLOVE, MCMTC, PI3K-alpha, p110-alpha -PIK3CA and Lung Cancer
227
CYP1A1 15q24.1 AHH, AHRR, CP11, CYP1, CYPIA1, P1-450, P450-C, P450DX -CYP1A1 and Lung Cancer
222
KIT 4q12 PBT, SCFR, C-Kit, CD117 -KIT and Lung Cancer
219
CD9 12p13.31 MIC3, MRP-1, BTCC-1, DRAP-27, TSPAN29, TSPAN-29 -CD9 and Lung Cancer
215
SRC 20q11.23 ASV, SRC1, THC6, c-SRC, p60-Src -SRC and Lung Cancer
213
RET 10q11.21 PTC, MTC1, HSCR1, MEN2A, MEN2B, RET51, CDHF12, CDHR16, RET-ELE1 -RET-KIF5B fusion in Adenocarcinoma Lung Cancer
-RET and Lung Cancer
167
TNF 6p21.33 DIF, TNFA, TNFSF2, TNLG1F, TNF-alpha -TNF and Lung Cancer
195
BAX 19q13.33 BCL2L4 -BAX and Lung Cancer
192
PROC 2q13-q14 PC, APC, PROC1, THPH3, THPH4 -PROC and Lung Cancer
191
CDKN1A 6p21.2 P21, CIP1, SDI1, WAF1, CAP20, CDKN1, MDA-6, p21CIP1 -CDKN1A and Lung Cancer
181
XRCC1 19q13.31 RCC -XRCC1 and Lung Cancer
172
PTGS2 1q31.1 COX2, COX-2, PHS-2, PGG/HS, PGHS-2, hCox-2, GRIPGHS -PTGS2 (COX2) and Lung Cancer
171
STAT3 17q21.2 APRF, HIES, ADMIO, ADMIO1 -STAT3 and Lung Cancer
171
BIRC5 17q25.3 API4, EPR-1 -Survivin Expression in Non Small Lung Cancer
152
GSTT1 22q11.23 -GSTT1 and Lung Cancer
151
NODAL 10q22.1 HTX5 -NODAL and Lung Cancer
147
KITLG 12q22 SF, MGF, SCF, FPH2, FPHH, KL-1, Kitl, SHEP7 -KITLG and Lung Cancer
143
RASSF1 3p21.31 123F2, RDA32, NORE2A, RASSF1A, REH3P21 -RASSF1 and Lung Cancer
134
HIF1A 14q23.2 HIF1, MOP1, PASD8, HIF-1A, bHLHe78, HIF-1alpha, HIF1-ALPHA, HIF-1-alpha -HIF1A and Lung Cancer
127
KIF5B 10p11.22 KNS, KINH, KNS1, UKHC, HEL-S-61 -KIF5B and Lung Cancer
-RET-KIF5B fusion in Adenocarcinoma Lung Cancer
-KIF5B-ALK Rearrangements in Lung Cancer
53
ERCC2 19q13.32 EM9, TTD, XPD, TTD1, COFS2, TFIIH -ERCC2 and Lung Cancer
122
VEGFA 6p21.1 VPF, VEGF, MVCD1 -VEGFA and Lung Cancer
117
RRM1 11p15.4 R1, RR1, RIR1 -RRM1 and Lung Cancer
115
PCNA 20p12.3 ATLD2 -PCNA and Lung Cancer
114
STK11 19p13.3 PJS, LKB1, hLKB1 -STK11 and Lung Cancer
109
TERT 5p15.33 TP2, TRT, CMM9, EST2, TCS1, hTRT, DKCA2, DKCB4, hEST2, PFBMFT1 -TERT and Lung Cancer
108
CEACAM5 19q13.2 CEA, CD66e -CEACAM5 and Lung Cancer
106
RB1 13q14.2 RB, pRb, OSRC, pp110, p105-Rb, PPP1R130 -RB1 and Lung Cancer
103
MYC 8q24.21 MRTL, MYCC, c-Myc, bHLHe39 -MYC and Lung Cancer
96
MUC1 1q22 EMA, MCD, PEM, PUM, KL-6, MAM6, MCKD, PEMT, CD227, H23AG, MCKD1, MUC-1, ADMCKD, ADMCKD1, CA 15-3, MUC-1/X, MUC1/ZD, MUC-1/SEC Overexpression
Prognostic
-MUC1 and Lung Cancer
95
TGFB1 19q13.2 CED, LAP, DPD1, TGFB, TGFbeta -TGFB1 and Lung Cancer
93
BCL2 18q21.33 Bcl-2, PPP1R50 -BCL2 and Lung Cancer
92
FGFR1 8p11.23 CEK, FLG, HH2, OGD, ECCL, FLT2, KAL2, BFGFR, CD331, FGFBR, FLT-2, HBGFR, N-SAM, FGFR-1, HRTFDS, bFGF-R-1 -FGFR1 and Lung Cancer
90
HGF 7q21.11 SF, HGFB, HPTA, F-TCF, DFNB39 -HGF and Lung Cancer
88
IGF1R 15q26.3 IGFR, CD221, IGFIR, JTK13 -IGF1R and Lung Cancer
82
MIR21 17q23.1 MIRN21, miR-21, miRNA21, hsa-mir-21 -MicroRNA miR-21 and Lung Cancer
82
SNAI1 20q13.13 SNA, SNAH, SNAIL, SLUGH2, SNAIL1, dJ710H13.1 -SNAI1 and Lung Cancer
75
SOX2 3q26.33 ANOP3, MCOPS3 -SOX2 and Lung Cancer
73
ABCB1 7q21.12 CLCS, MDR1, P-GP, PGY1, ABC20, CD243, GP170 -ABCB1 and Lung Cancer
71
CCND1 11q13.3 BCL1, PRAD1, U21B31, D11S287E -CCND1 and Lung Cancer
70
ACHE 7q22.1 YT, ACEE, ARACHE, N-ACHE -ACHE and Lung Cancer
69
TTF1 9q34.13 TTF-1, TTF-I -TTF1 and Lung Cancer
69
BCL2L1 20q11.21 BCLX, BCL2L, Bcl-X, PPP1R52, BCL-XL/S -BCL2L1 and Lung Cancer
68
CYP2E1 10q26.3 CPE1, CYP2E, P450-J, P450C2E -CYP2E1 and Lung Cancer
68
FTCDNL1 2q33.1 FONG -FONG and Lung Cancer
68
FOS 14q24.3 p55, AP-1, C-FOS -FOS and Lung Cancer
67
ABCG2 4q22.1 MRX, MXR, ABCP, BCRP, BMDP, MXR1, ABC15, BCRP1, CD338, GOUT1, MXR-1, CDw338, UAQTL1, EST157481 -ABCG2 and Lung Cancer
65
TGFBR2 3p24.1 AAT3, FAA3, LDS2, MFS2, RIIC, LDS1B, LDS2B, TAAD2, TGFR-2, TGFbeta-RII -TGFBR2 and Lung Cancer
64
CHRNA5 15q25.1 LNCR2 -CHRNA5 and Lung Cancer
63
NQO1 16q22.1 DTD, QR1, DHQU, DIA4, NMOR1, NMORI -NQO1 and Lung Cancer
63
CCNB1 5q13.2 CCNB -CCNB1 and Lung Cancer
62
OGG1 3p25.3 HMMH, MUTM, OGH1, HOGG1 -OGG1 and Lung Cancer
60
BAD 11q13.1 BBC2, BCL2L8 -BAD and Lung Cancer
60
XRCC3 14q32.33 CMM6 -XRCC3 and Lung Cancer
59
CALU 7q32.1 -CALU and Lung Cancer
58
PARP1 1q42.12 PARP, PPOL, ADPRT, ARTD1, ADPRT1, PARP-1, ADPRT 1, pADPRT-1 -PARP1 and Lung Cancer
54
ABCC1 16p13.11 MRP, ABCC, GS-X, MRP1, ABC29 -ABCC1 (MRP1) and Lung Cancer
54
TWIST1 7p21.1 CRS, CSO, SCS, ACS3, CRS1, BPES2, BPES3, TWIST, bHLHa38 -TWIST1 and Lung Cancer
52
MYCN 2p24.3 NMYC, ODED, MODED, N-myc, bHLHe37 -MYCN in Lung Cancer
51
AKT2 19q13.2 PKBB, PRKBB, HIHGHH, PKBBETA, RAC-BETA -AKT2 and Lung Cancer
51
RHOA 3p21.31 ARHA, ARH12, RHO12, RHOH12 -RHOA and Lung Cancer
51
CDH1 16q22.1 UVO, CDHE, ECAD, LCAM, Arc-1, CD324 -CDH1 and Lung Cancer
50
RAC1 7p22.1 MIG5, Rac-1, TC-25, p21-Rac1 -RAC1 and Lung Cancer
50
SLC2A1 1p34.2 CSE, PED, DYT9, GLUT, DYT17, DYT18, EIG12, GLUT1, HTLVR, GLUT-1, SDCHCN, GLUT1DS Prognostic
-GLUT1 Overexpression and Lung Cancer
49
MCL1 1q21.2 TM, EAT, MCL1L, MCL1S, Mcl-1, BCL2L3, MCL1-ES, bcl2-L-3, mcl1/EAT -MCL1 and Lung Cancer
49
XPC 3p25.1 XP3, RAD4, XPCC, p125 -XPC and Lung Cancer
48
CHRNA3 15q25.1 LNCR2, PAOD2, NACHRA3 -CHRNA3 and Lung Cancer
47
NFE2L2 2q31 NRF2 -NFE2L2 and Lung Cancer
46
EPHX1 1q42.12 MEH, EPHX, EPOX, HYL1 -EPHX1 and Lung Cancer
46
DROSHA 5p13.3 RN3, ETOHI2, RNASEN, RANSE3L, RNASE3L, HSA242976 -DROSHA and Lung Cancer
46
GAPDH 12p13.31 G3PD, GAPD, HEL-S-162eP -GAPDH and Lung Cancer
46
DDR2 1q23.3 TKT, WRCN, MIG20a, NTRKR3, TYRO10 -DDR2 and Lung Cancer
45
ZEB1 10p11.22 BZP, TCF8, AREB6, FECD6, NIL2A, PPCD3, ZFHEP, ZFHX1A, DELTAEF1 -ZEB1 and Lung Cancer
45
RELA 11q13.1 p65, NFKB3 -RELA and Lung Cancer
44
HEBP1 12p13.1 HBP, HEBP -HEBP1 and Lung Cancer
44
NAT2 8p22 AAC2, PNAT, NAT-2 -NAT2 and Lung Cancer
44
IL6 7p15.3 CDF, HGF, HSF, BSF2, IL-6, BSF-2, IFNB2, IFN-beta-2 -IL6 and Lung Cancer
42
CD274 9p24.1 B7-H, B7H1, PDL1, PD-L1, PDCD1L1, PDCD1LG1 -CD274 and Lung Cancer
42
DICER1 14q32.13 DCR1, MNG1, Dicer, HERNA, RMSE2, Dicer1e, K12H4.8-LIKE -DICER1 and Lung Cancer
41
SMAD4 18q21.2 JIP, DPC4, MADH4, MYHRS -SMAD4 and Lung Cancer
41
JUN 1p32.1 AP1, p39, AP-1, cJUN, c-Jun -c-Jun and Lung Cancer
41
RECK 9p13.3 ST15 -RECK and Lung Cancer
41
CD82 11p11.2 R2, 4F9, C33, IA4, ST6, GR15, KAI1, SAR2, TSPAN27 -CD82 and Lung Cancer
41
MIR126 9q34.3 MIRN126, mir-126, miRNA126 -MicroRNA mir-126 and Lung Cancer
40
CLPTM1L 5p15.33 CRR9 -CLPTM1L and Lung Cancer
40
NKX2-1 14q13.3 BCH, BHC, NK-2, TEBP, TTF1, NKX2A, NMTC1, T/EBP, TITF1, TTF-1, NKX2.1 -NKX2-1 and Lung Cancer
40
VEGFC 4q34.3 VRP, Flt4-L, LMPH1D -VEGFC and Lung Cancer
40
CXCL12 10q11.21 IRH, PBSF, SDF1, TLSF, TPAR1, SCYB12 -CXCL12 and Lung Cancer
40
CXCR4 2q21 FB22, HM89, LAP3, LCR1, NPYR, WHIM, CD184, LAP-3, LESTR, NPY3R, NPYRL, WHIMS, HSY3RR, NPYY3R, D2S201E -CXCR4 and Lung Cancer
40
TP63 3q28 AIS, KET, LMS, NBP, RHS, p40, p51, p63, EEC3, OFC8, p73H, p73L, SHFM4, TP53L, TP73L, p53CP, TP53CP, B(p51A), B(p51B) -TP63 and Lung Cancer
39
CXCL1 4q13.3 FSP, GRO1, GROa, MGSA, NAP-3, SCYB1, MGSA-a -CXCL1 and Lung Cancer
38
DNMT3B 20q11.21 ICF, ICF1, M.HsaIIIB -DNMT3B and Lung Cancer
38
ASCL1 12q23.2 ASH1, HASH1, MASH1, bHLHa46 -ASCL1 and Lung Cancer
38
NME1 17q21.33 NB, AWD, NBS, GAAD, NDKA, NM23, NDPKA, NDPK-A, NM23-H1 -NME1 and Lung Cancer
38
CDC42 1p36.12 TKS, G25K, CDC42Hs -CDC42 and Lung Cancer
37
CYP2A6 19q13.2 CPA6, CYP2A, CYP2A3, P450PB, CYPIIA6, P450C2A -CYP2A6 and Lung Cancer
37
CDH13 16q23.3 CDHH, P105 -CDH13 and Lung Cancer
37
NF2 22q12.2 ACN, SCH, BANF -NF2 and Lung Cancer
37
RHOC 1p13.2 H9, ARH9, ARHC, RHOH9 -RHOC and Lung Cancer
36
PTK2 8q24.3 FAK, FADK, FAK1, FRNK, PPP1R71, p125FAK, pp125FAK -PTK2 and Lung Cancer
36
SERPINB5 18q21.33 PI5, maspin -SERPIN-B5 and Lung Cancer
35
BAP1 3p21.1 UCHL2, hucep-6, HUCEP-13 -BAP1 and Lung Cancer
35
SMAD2 18q21.1 JV18, MADH2, MADR2, JV18-1, hMAD-2, hSMAD2 -SMAD2 and Lung Cancer
34
CCK 3p22.1 -CCK and Lung Cancer
34
ERBB3 12q13 HER3, LCCS2, ErbB-3, c-erbB3, erbB3-S, MDA-BF-1, c-erbB-3, p180-ErbB3, p45-sErbB3, p85-sErbB3 -ERBB3 and Lung Cancer
34
MAP2K1 15q22.31 CFC3, MEK1, MKK1, MAPKK1, PRKMK1 -MAP2K1 and Lung Cancer
33
FGFR2 10q26.13 BEK, JWS, BBDS, CEK3, CFD1, ECT1, KGFR, TK14, TK25, BFR-1, CD332, K-SAM -FGFR2 and Lung Cancer
33
CYP1B1 2p22.2 CP1B, GLC3A, CYPIB1, P4501B1 -CYP1B1 and Lung Cancer
32
TSC2 16p13.3 LAM, TSC4, PPP1R160 -TSC2 and Lung Cancer
32
RAP1A 1p13.2 RAP1, C21KG, G-22K, KREV1, KREV-1, SMGP21 -Lung Cancer and RAP1A
32
AXL 19q13.2 ARK, UFO, JTK11, Tyro7 -AXL and Lung Cancer
31
SKP2 5p13.2 p45, FBL1, FLB1, FBXL1 -SKP2 and Lung Cancer
31
ALDH1A1 9q21.13 ALDC, ALDH1, HEL-9, HEL12, PUMB1, ALDH11, RALDH1, ALDH-E1, HEL-S-53e -ALDH1A1 and Lung Cancer
31
HMGA2 12q14.3 BABL, LIPO, HMGIC, HMGI-C, STQTL9 -HMGA2 and Lung Cancer
31
XPA 9q22.33 XP1, XPAC -XPA and Lung Cancer
31
RAD51 15q15.1 RECA, BRCC5, FANCR, MRMV2, HRAD51, RAD51A, HsRad51, HsT16930 -RAD51 and Lung Cancer
31
POMC 2p23.3 LPH, MSH, NPP, POC, ACTH, CLIP -POMC and Lung Cancer
30
MCC 5q22.2 MCC1 -MCC and Lung Cancer
30
TUBB3 16q24.3 CDCBM, FEOM3, TUBB4, CDCBM1, CFEOM3, beta-4, CFEOM3A -TUBB3 and Lung Cancer
30
MMP1 11q22.2 CLG, CLGN -MMP1 and Lung Cancer
30
CD74 5q33.1 II, DHLAG, HLADG, Ia-GAMMA Translocation
-CD74 and Lung Cancer
-CD74-NTRK1 fusion in Lung Cancer
27
RUNX3 1p36.11 AML2, CBFA3, PEBP2aC -RUNX3 and Lung Cancer
29
KDR 4q12 FLK1, CD309, VEGFR, VEGFR2 -KDR and Lung Cancer
29
CD24 6q21 CD24A -CD24 and Lung Cancer
29
TSC1 9q34.13 LAM, TSC -TSC1 and Lung Cancer
29
VIP 6q25.2 PHM27 -VIP and Lung Cancer
28
TYMS 18p11.32 TS, TMS, HST422 -TYMS and Lung Cancer
28
FAS 10q23.31 APT1, CD95, FAS1, APO-1, FASTM, ALPS1A, TNFRSF6 -FAS and Lung Cancer
28
FOXM1 12p13 MPP2, TGT3, HFH11, HNF-3, INS-1, MPP-2, PIG29, FKHL16, FOXM1B, HFH-11, TRIDENT, MPHOSPH2 -FOXM1 and Lung Cancer
28
EP300 22q13.2 p300, KAT3B, MKHK2, RSTS2 -EP300 and Lung Cancer
27
CYP1A2 15q24.1 CP12, P3-450, P450(PA) -CYP1A2 and Lung Cancer
27
SMARCA4 19p13.2 BRG1, CSS4, SNF2, SWI2, MRD16, RTPS2, BAF190, SNF2L4, SNF2LB, hSNF2b, BAF190A -SMARCA4 and Lung Cancer
27
CCL2 17q12 HC11, MCAF, MCP1, MCP-1, SCYA2, GDCF-2, SMC-CF, HSMCR30 -CCL2 and Lung Cancer
26
EGR1 5q31.2 TIS8, AT225, G0S30, NGFI-A, ZNF225, KROX-24, ZIF-268 -EGR1 and Lung Cancer
26
MMP7 11q22.2 MMP-7, MPSL1, PUMP-1 -MMP7 and Lung Cancer
26
CHIA 1p13.2 CHIT2, AMCASE, TSA1902 -CHIA and Lung Cancer
26
CHRNB4 15q25.1 -CHRNB4 and Lung Cancer
26
POU5F1 6p21.33 OCT3, OCT4, OTF3, OTF4, OTF-3, Oct-3, Oct-4 -POU5F1 and Lung Cancer
26
CDK1 10q21.2 CDC2, CDC28A, P34CDC2 -CDK1 and Lung Cancer
26
SNAI2 8q11.21 SLUG, WS2D, SLUGH, SLUGH1, SNAIL2 -SNAI2 and Lung Cancer
25
FGFR3 4p16.3 ACH, CEK2, JTK4, CD333, HSFGFR3EX -FGFR3 and Lung Cancer
25
HNRNPA2B1 7p15.2 RNPA2, HNRPA2, HNRPB1, SNRPB1, HNRNPA2, HNRNPB1, IBMPFD2, HNRPA2B1 -HNRNPA2B1 and Lung Cancer
25
MMP3 11q22.2 SL-1, STMY, STR1, CHDS6, MMP-3, STMY1 -MMP3 and Lung Cancer
24
PRC1 15q26.1 ASE1 -PRC1 and Lung Cancer
24
CADM1 11q23.3 BL2, ST17, IGSF4, NECL2, RA175, TSLC1, IGSF4A, Necl-2, SYNCAM, sgIGSF, sTSLC-1, synCAM1 -CADM1 and Lung Cancer
24
SIRT1 10q21.3 SIR2, SIR2L1, SIR2alpha -SIRT1 and Lung Cancer
23
TPM3 1q21.3 TM3, TM5, TRK, CFTD, NEM1, TM-5, TM30, CAPM1, TM30nm, TPM3nu, TPMsk3, hscp30, HEL-189, HEL-S-82p, OK/SW-cl.5 -TPM3 and Lung Cancer
23
CAV1 7q31.2 CGL3, PPH3, BSCL3, LCCNS, VIP21, MSTP085 -CAV1 and Lung Cancer
23
CISH 3p21.2 CIS, G18, SOCS, CIS-1, BACTS2 -CISH and Lung Cancer
22
TIMP2 17q25.3 DDC8, CSC-21K -TIMP2 Expression in Lung Cancer
22
S100A4 1q21.3 42A, 18A2, CAPL, FSP1, MTS1, P9KA, PEL98 -S100A4 and Lung Cancer
22
GPC3 Xq26.2 SGB, DGSX, MXR7, SDYS, SGBS, OCI-5, SGBS1, GTR2-2 -GPC3 and Lung Cancer
22
SLC2A3 12p13.31 GLUT3 -GLUT3 and Lung cancer
22
EIF4E 4q23 CBP, EIF4F, AUTS19, EIF4E1, eIF-4E, EIF4EL1 -EIF4E and Lung Cancer
22
FASLG 1q24.3 APTL, FASL, CD178, CD95L, ALPS1B, CD95-L, TNFSF6, TNLG1A, APT1LG1 -FASLG and Lung Cancer
22
CBL 11q23.3 CBL2, NSLL, C-CBL, RNF55, FRA11B -CBL and Lung Cancer
22
MAGEA3 Xq28 HIP8, HYPD, CT1.3, MAGE3, MAGEA6 -MAGEA3 and Lung Cancer
22
TERC 3q26.2 TR, hTR, TRC3, DKCA1, PFBMFT2, SCARNA19 -TERC and Lung Cancer
22
SPP1 4q22.1 OPN, BNSP, BSPI, ETA-1 -SPP1 and Lung Cancer
21
FOXO3 6q21 FOXO2, AF6q21, FKHRL1, FOXO3A, FKHRL1P2 -FOXO3 and Lung Cancer
21
SPARC 5q33.1 ON, OI17, BM-40 -SPARC and Lung Cancer
21
PLK1 16p12.2 PLK, STPK13 -PLK1 and Lung Cancer
20
STMN1 1p36.11 Lag, SMN, OP18, PP17, PP19, PR22, LAP18, C1orf215 -STMN1 and Lung Cancer
20
HES1 3q29 HHL, HRY, HES-1, bHLHb39 -HES1 and Lung Cancer
20
POLE 12q24.3 FILS, POLE1, CRCS12 -POLE and Lung Cancer
20
BECN1 17q21.31 ATG6, VPS30, beclin1 -BECN1 and Lung Cancer
20
NFKBIA 14q13.2 IKBA, MAD-3, NFKBI -NFKBIA and Lung Cancer
19
LOX 5q23.1 AAT10 -LOX and Lung Cancer
19
WIF1 12q14.3 WIF-1 -WIF1 and Lung Cancer
19
CCNA2 4q27 CCN1, CCNA -CCNA2 and Lung Cancer
19
CDH2 18q12.1 CDHN, NCAD, CD325, CDw325 -CDH2 and Lung Cancer
19
GSTM3 1p13.3 GST5, GSTB, GTM3, GSTM3-3 -GSTM3 and Lung Cancer
19
TIMP3 22q12.3 SFD, K222, K222TA2, HSMRK222 -TIMP3 and Lung Cancer
19
MIRLET7B 22q13.31 LET7B, let-7b, MIRNLET7B, hsa-let-7b -MicroRNA let-7b and Lung Cancer
19
CYP3A4 7q22.1 HLP, CP33, CP34, CYP3A, NF-25, CYP3A3, P450C3, CYPIIIA3, CYPIIIA4, P450PCN1 -CYP3A4 and Lung Cancer
19
MALT1 18q21.32 MLT, MLT1, IMD12, PCASP1 -MALT1 and Lung Cancer
18
RAF1 3p25.2 NS5, CRAF, Raf-1, c-Raf, CMD1NN -RAF1 and Lung Cancer
18
NOTCH3 19p13.12 IMF2, LMNS, CASIL, CADASIL, CADASIL1 -NOTCH3 and Lung Cancer
18
EPHA2 1p36.13 ECK, CTPA, ARCC2, CTPP1, CTRCT6 -EPHA2 and Lung Cancer
18
PRKDC 8q11.21 HYRC, p350, DNAPK, DNPK1, HYRC1, IMD26, XRCC7, DNA-PKcs -PRKDC and Lung Cancer
18
KDM1A 1p36.12 AOF2, CPRF, KDM1, LSD1, BHC110 -KDM1A and Lung Cancer
18
THBS1 15q14 TSP, THBS, TSP1, TSP-1, THBS-1 -THBS1 and Lung Cancer
18
CDC25C 5q31.2 CDC25, PPP1R60 -CDC25C and Lung Cancer
18
CRK 17p13.3 p38, CRKII -CRK and Lung Cancer
17
CCDC6 10q21.2 H4, PTC, TPC, TST1, D10S170 -CCDC6 and Lung Cancer
17
NANOG 12p13.31 -NANOG and Lung Cancer
17
MIF 22q11.23 GIF, GLIF, MMIF -MIF and Lung Cancer
17
TUSC2 3p21.31 PAP, FUS1, PDAP2, C3orf11 -TUSC2 and Lung Cancer
17
FOSL1 11q13.1 FRA, FRA1, fra-1 -FOSL1 and Lung Cancer
17
ERCC5 13q33.1 XPG, UVDR, XPGC, COFS3, ERCM2, ERCC5-201 -ERCC5 and Lung Cancer
17
GADD45A 1p31.3 DDIT1, GADD45 -GADD45A and Lung Cancer
17
SSTR2 17q25.1 -SSTR2 and Lung Cancer
17
CDC20 1p34.2 CDC20A, p55CDC, bA276H19.3 -CDC20 and Lung Cancer
17
MIRLET7C 21q21.1 LET7C, let-7c, MIRNLET7C, hsa-let-7c -MicroRNA let-7c and Lung Cancer
16
CREB1 2q34 CREB -CREB1 and Lung Cancer
16
GPX1 3p21.31 GPXD, GSHPX1 -GPX1 and Lung Cancer
16
AKT3 1q43-q44 MPPH, PKBG, MPPH2, PRKBG, STK-2, PKB-GAMMA, RAC-gamma, RAC-PK-gamma -AKT3 and Lung Cancer
16
BRD4 19p13.12 CAP, MCAP, HUNK1, HUNKI -BRD4 and Lung Cancer
16
S100A2 1q21.3 CAN19, S100L -S100A2 and Lung Cancer
16
MMP12 11q22.2 ME, HME, MME, MMP-12 -MMP12 and Lung Cancer
16
CRP 1q23.2 PTX1 -CRP and Lung Cancer
16
SLC19A1 21q22.3 RFC, CHMD, FOLT, IFC1, REFC, RFC1, hRFC, IFC-1, RFT-1 -SLC19A1 and Lung Cancer
16
ATF3 1q32.3 -ATF3 and Lung Cancer
16
WNT5A 3p14.3 hWNT5A -WNT5A and Lung Cancer
16
RBM5 3p21.31 G15, H37, RMB5, LUCA15 -RBM5 and Lung Cancer
16
MUC5AC 11p15.5 TBM, leB, MUC5, mucin -MUC5AC and Lung Cancer
16
COL18A1 21q22.3 KS, KNO, KNO1 -COL18A1 and Lung Cancer
15
SLC34A2 4p15.2 NPTIIb, NAPI-3B, NAPI-IIb -SLC34A2 and Lung Cancer
15
DKK1 10q21.1 SK, DKK-1 -DKK1 and Lung Cancer
15
S100P 4p16.1 MIG9 -S100P and Lung Cancer
15
NRG1 8p12 GGF, HGL, HRG, NDF, ARIA, GGF2, HRG1, HRGA, SMDF, MST131, MSTP131, NRG1-IT2 -NRG1 and Lung Cancer
15
PLAUR 19q13.31 CD87, UPAR, URKR, U-PAR -PLAUR and Lung Cancer
15
EPCAM 2p21 ESA, KSA, M4S1, MK-1, DIAR5, EGP-2, EGP40, KS1/4, MIC18, TROP1, EGP314, HNPCC8, TACSTD1 -EPCAM and Lung Cancer
15
CYP24A1 20q13.2 CP24, HCAI, CYP24, HCINF1, P450-CC24 -CYP24A1 and Lung Cancer
15
ATF4 22q13.1 CREB2, TXREB, CREB-2, TAXREB67 -ATF4 and Lung Cancer
15
MALAT1 11q13.1 HCN, NEAT2, PRO2853, LINC00047, NCRNA00047 -MALAT1 and Lung Cancer
15
FOXA2 20p11.21 HNF3B, TCF3B -FOXA2 and Lung Cancer
15
SOD2 6q25.3 IPOB, IPO-B, MNSOD, MVCD6, Mn-SOD -SOD2 and Lung Cancer
15
MOS 8q12.1 MSV -MOS and Lung Cancer
15
SEMA3B 3p21.31 SemA, SEMA5, SEMAA, semaV, LUCA-1 -SEMA3B and Lung Cancer
15
WWOX 16q23.1-q23.2 FOR, WOX1, EIEE28, FRA16D, SCAR12, HHCMA56, PRO0128, SDR41C1, D16S432E -WWOX and Lung Cancer
15
IGF1 12q23.2 IGFI, IGF-I, IGF1A -IGF1 and Lung Cancer
14
MTDH 8q22.1 3D3, AEG1, AEG-1, LYRIC, LYRIC/3D3 -MTDH and Lung Cancer
14
SCGB1A1 11q12.3 UGB, UP1, CC10, CC16, CCSP, UP-1, CCPBP -SCGB1A1 and Lung Cancer
14
TOP2A 17q21.2 TOP2, TP2A -TOP2A Expression in Lung Cancer
14
H19 11p15.5 ASM, BWS, WT2, ASM1, D11S813E, LINC00008, NCRNA00008 -H19 and Lung Cancer
14
FGFR4 5q35.2 TKF, JTK2, CD334 -FGFR4 and Lung Cancer
14
KRT5 12q13.13 K5, CK5, DDD, DDD1, EBS2, KRT5A -KRT5 and Lung Cancer
14
BMP2 20p12.3 BDA2, BMP2A, SSFSC -BMP2 and Lung Cancer
14
PPP1R13L 19q13.32 RAI, RAI4, IASPP, NKIP1 -PPP1R13L and Lung Cancer
14
MARCO 2q14.2 SCARA2 -MARCO and Lung Cancer
14
BIRC7 20q13.33 KIAP, LIVIN, MLIAP, RNF50, ML-IAP -BIRC7 and Lung Cancer
14
YAP1 11q22.1 YAP, YKI, COB1, YAP2, YAP65 -YAP1 and Lung Cancer
14
IL17C 16q24.2 CX2, IL-17C -IL17C and Lung Cancer
13
TPX2 20q11.21 DIL2, p100, DIL-2, HCTP4, FLS353, HCA519, REPP86, C20orf1, C20orf2, GD:C20orf1 -TPX2 and Lung Cancer
13
WNT3A 1q42.13 -WNT3A and Lung Cancer
13
ZEB2 2q22.3 SIP1, SIP-1, ZFHX1B, HSPC082, SMADIP1 -ZEB2 and Lung Cancer
13
YBX1 1p34.2 YB1, BP-8, CSDB, DBPB, YB-1, CBF-A, CSDA2, EFI-A, NSEP1, NSEP-1, MDR-NF1 -YBX1 and Lung Cancer
13
TNFRSF1A 12p13.31 FPF, p55, p60, TBP1, TNF-R, TNFAR, TNFR1, p55-R, CD120a, TNFR55, TNFR60, TNF-R-I, TNF-R55 -TNFRSF1A and Lung Cancer
13
IL1B 2q14 IL-1, IL1F2, IL1-BETA -IL1B and Lung Cancer
13
CDC25A 3p21.31 CDC25A2 -CDC25A and Lung Cancer
13
LGALS1 22q13.1 GBP, GAL1 -LGALS1 and Lung Cancer
13
STAR 8p11.23 STARD1 -STAR and Lung Cancer
13
MMP14 14q11.2 MMP-14, MMP-X1, MT-MMP, MT1MMP, MTMMP1, WNCHRS, MT1-MMP, MT-MMP 1 -MMP14 and Lung Cancer
13
JUND 19p13.11 AP-1 -JUND and Lung Cancer
13
DKK3 11p15.3 RIG, REIC -DKK3 and Lung Cancer
13
SOX4 6p22.3 EVI16 -SOX4 and Lung Cancer
13
TFE3 Xp11.23 TFEA, RCCP2, RCCX1, bHLHe33 -TFE3 and Lung Cancer
13
LATS2 13q12.11 KPM -LATS2 and Lung Cancer
13
CD68 17p13.1 GP110, LAMP4, SCARD1 -CD68 and Lung Cancer
13
VEGFB 11q13.1 VRF, VEGFL -VEGFB and Lung Cancer
13
XIST Xq13.2 SXI1, swd66, DXS1089, DXS399E, LINC00001, NCRNA00001 -XIST and Lung Cancer
13
PDPN 1p36.21 T1A, GP36, GP40, Gp38, OTS8, T1A2, TI1A, T1A-2, AGGRUS, HT1A-1, PA2.26 -PDPN and Lung Cancer
13
ETS2 21q22.2 ETS2IT1 -ETS2 and Lung Cancer
13
ITCH 20q11.22 AIF4, AIP4, ADMFD, NAPP1 -ITCH and Lung Cancer
13
MSN Xq12 HEL70, IMD50 -MSN and Lung Cancer
13
ACTB 7p22.1 BRWS1, PS1TP5BP1 -ACTB and Lung Cancer
12
SMARCA2 9p24.3 BRM, SNF2, SWI2, hBRM, NCBRS, Sth1p, BAF190, SNF2L2, SNF2LA, hSNF2a -SMARCA2 and Lung Cancer
12
SHC1 1q21.3 SHC, SHCA -SHC1 and Lung Cancer
12
BTG2 1q32.1 PC3, APRO1, TIS21 -BTG2 and Lung Cancer
12
E2F3 6p22.3 E2F-3 -E2F3 and Lung Cancer
12
ERBB4 2q33.3-q34 HER4, ALS19, p180erbB4 -ERBB4 and Lung Cancer
12
PTHLH 12p11.22 HHM, PLP, BDE2, PTHR, PTHRP -PTHLH and Lung Cancer
12
XRCC6 22q13.2 ML8, KU70, TLAA, CTC75, CTCBF, G22P1 -XRCC6 and Lung Cancer
12
RHOB 2p24 ARH6, ARHB, RHOH6, MST081, MSTP081 -RHOB and Lung Cancer
12
DLC1 8p22 HP, ARHGAP7, STARD12, p122-RhoGAP -DLC1 and Lung Cancer
12
GATA3 10p14 HDR, HDRS -GATA3 and Lung Cancer
12
RRM2 2p25-p24 R2, RR2, RR2M -RRM2 and Lung Cancer
12
EIF3E 8q23.1 INT6, EIF3S6, EIF3-P48, eIF3-p46 -EIF3E and Lung Cancer
12
ATG5 6q21 ASP, APG5, APG5L, hAPG5, APG5-LIKE -ATG5 and Lung Cancer
12
ABCC4 13q32.1 MRP4, MOATB, MOAT-B -ABCC4 and Lung Cancer
12
PLA2G4A 1q31.1 GURDP, cPLA2, PLA2G4, cPLA2-alpha -PLA2G4A and Lung Cancer
12
HMGB1 13q12.3 HMG1, HMG3, HMG-1, SBP-1 -HMGB1 and Lung Cancer
12
MAGEA4 Xq28 CT1.4, MAGE4, MAGE4A, MAGE4B, MAGE-41, MAGE-X2 -MAGEA4 and Lung Cancer
12
CD63 12q13.2 MLA1, ME491, LAMP-3, OMA81H, TSPAN30 -CD63 and Lung Cancer
12
TIMP1 Xp11.3 EPA, EPO, HCI, CLGI, TIMP, TIMP-1 Prognostic
-TIMP1 and Non Small Cell Lung Cancer
12
CHFR 12q24.33 RNF116, RNF196 -CHFR and Lung Cancer
12
PRKN 6q26 PDJ, AR-JP, LPRS2, PARK2 -PARK2 and Lung Cancer
12
CXCL5 4q13.3 SCYB5, ENA-78 -CXCL5 and Lung Cancer
12
SQSTM1 5q35.3 p60, p62, A170, DMRV, OSIL, PDB3, ZIP3, p62B, NADGP, FTDALS3 -SQSTM1 and Lung Cancer
11
MAD2L1 4q27 MAD2, HSMAD2 -MAD2L1 and Lung Cancer
11
MUC4 3q29 ASGP, MUC-4, HSA276359 -MUC4 and Lung Cancer
11
HSPB1 7q11.23 CMT2F, HMN2B, HSP27, HSP28, Hsp25, SRP27, HS.76067, HEL-S-102 -HSPB1 and Lung Cancer
11
ATF1 12q13.12 TREB36, EWS-ATF1, FUS/ATF-1 -ATF1 and Lung Cancer
11
ERCC4 16p13.12 XPF, RAD1, FANCQ, XFEPS, ERCC11 -ERCC4 and Lung Cancer
11
BCAR1 16q23.1 CAS, CAS1, CASS1, CRKAS, P130Cas -BCAR1 and Lung Cancer
11
BBC3 19q13.32 JFY1, PUMA, JFY-1 -BBC3 and Lung Cancer
11
ADAM9 8p11.22 MCMP, MDC9, CORD9, Mltng -ADAM9 and Lung Cancer
11
PDK1 2q31.1 -PDK1 and Lung Cancer
11
ENO1 1p36.23 NNE, PPH, MPB1, ENO1L1, HEL-S-17 -ENO1 and Lung Cancer
11
CTAG1B Xq28 CTAG, ESO1, CT6.1, CTAG1, LAGE-2, LAGE2B, NY-ESO-1 -CTAG1B and Lung Cancer
11
TP73 1p36.32 P73 -TP73 and Lung Cancer
11
SOCS3 17q25.3 CIS3, SSI3, ATOD4, Cish3, SSI-3, SOCS-3 -SOCS3 and Lung Cancer
11
ANXA2 15q22.2 P36, ANX2, LIP2, LPC2, CAL1H, LPC2D, ANX2L4, PAP-IV, HEL-S-270 -ANXA2 and Lung Cancer
11
CCNB2 15q22.2 HsT17299 -CCNB2 and Lung Cancer
10
TNFRSF10A 8p21.3 DR4, APO2, CD261, TRAILR1, TRAILR-1 -TNFRSF10A and Lung Cancer
10
MAML2 11q21 MAM2, MAM3, MAM-3, MLL-MAML2 -MAML2 and Lung Cancer
10
RAD52 12p13.33 -RAD52 and Lung Cancer
10
NFKB1 4q24 p50, KBF1, p105, EBP-1, CVID12, NF-kB1, NFKB-p50, NFkappaB, NF-kappaB, NFKB-p105, NF-kappa-B -NFKB1 and Lung Cancer
10
CRKL 22q11.21 -CRKL and Lung Cancer
10
MMP11 22q11.23 ST3, SL-3, STMY3 -MMP11 and Lung Cancer
10
NAT1 8p22 AAC1, MNAT, NATI, NAT-1 -NAT1 and Lung Cancer
10
UBE2C 20q13.12 UBCH10, dJ447F3.2 -UBE2C and Lung Cancer
10
RARB 3p24.2 HAP, RRB2, NR1B2, MCOPS12, RARbeta1 -RARB and Lung Cancer
10
EPB41L3 18p11.31 4.1B, DAL1, DAL-1 -EPB41L3 and Lung Cancer
10
SLIT2 4p15.31 SLIL3, Slit-2 -SLIT2 and Lung Cancer
10
CLDN1 3q28-q29 CLD1, SEMP1, ILVASC -CLDN1 and Lung Cancer
10
RBL2 16q12.2 Rb2, P130 -RBL2 and Lung Cancer
10
NEDD9 6p24.2 CAS2, CASL, HEF1, CAS-L, CASS2 -NEDD9 and Lung Cancer
10
ITGB3 17q21.32 GT, CD61, GP3A, BDPLT2, GPIIIa, BDPLT16 -ITGB3 and Lung Cancer
10
DUSP1 5q35.1 HVH1, MKP1, CL100, MKP-1, PTPN10 -DUSP1 and Lung Cancer
10
POSTN 13q13.3 PN, OSF2, OSF-2, PDLPOSTN -POSTN and Lung Cancer
10
CCR7 17q21.2 BLR2, EBI1, CCR-7, CD197, CDw197, CMKBR7, CC-CKR-7 -CCR7 and Lung Cancer
10
IFNG 12q15 IFG, IFI -IFNG and Lung Cancer
10
CASP10 2q33-q34 MCH4, ALPS2, FLICE2 -CASP10 and Lung Cancer
10
CCN1 1p22.3 GIG1, CYR61, IGFBP10 -CYR61 and Lung Cancer
9
CEACAM1 19q13.2 BGP, BGP1, BGPI -CEACAM1 and Lung Cancer
9
ARNT 1q21.3 HIF1B, TANGO, bHLHe2, HIF1BETA, HIF-1beta, HIF1-beta, HIF-1-beta -ARNT and Lung Cancer
9
DDR1 6p21.33 CAK, DDR, NEP, HGK2, PTK3, RTK6, TRKE, CD167, EDDR1, MCK10, NTRK4, PTK3A -DDR1 and Lung Cancer
9
MAPK8 10q11.22 JNK, JNK1, PRKM8, SAPK1, JNK-46, JNK1A2, SAPK1c, JNK21B1/2 -MAPK8 and Lung Cancer
9
MDC1 6p21.33 NFBD1 -MDC1 and Lung Cancer
9
CYP2A13 19q13.2 CPAD, CYP2A, CYPIIA13 -CYP2A13 and Lung Cancer
9
RAG2 11p12 RAG-2 -RAG2 and Lung Cancer
9
TGFBR3 1p22.1 BGCAN, betaglycan -TGFBR3 and Lung Cancer
9
CXCL10 4q21.1 C7, IFI10, INP10, IP-10, crg-2, mob-1, SCYB10, gIP-10 -CXCL10 and Lung Cancer
9
CDC25B 20p13 -CDC25B and Lung Cancer
9
ROCK1 18q11.1 ROCK-I, P160ROCK -ROCK1 and Lung Cancer
9
MIR1290 1p36.13 MIRN1290, hsa-mir-1290 -MIRN1290 microRNA, human and Lung Cancer
9
CYP2C19 10q23.33 CPCJ, CYP2C, P450C2C, CYPIIC17, CYPIIC19, P450IIC19 -CYP2C19 and Lung Cancer
9
TNFRSF11A 18q21.33 FEO, OFE, ODFR, OSTS, PDB2, RANK, CD265, OPTB7, TRANCER, LOH18CR1 -TNFRSF11A and Lung Cancer
9
HOXA1 7p15.2 BSAS, HOX1, HOX1F -HOXA1 and Lung Cancer
9
AKR1B10 7q33 HIS, HSI, ARL1, ARL-1, ALDRLn, AKR1B11, AKR1B12 -AKR1B10 and Lung Cancer
9
PTTG1 5q33.3 EAP1, PTTG, HPTTG, TUTR1 -PTTG1 and Lung Cancer
9
HYAL2 3p21.3 LUCA2 -HYAL2 and Lung Cancer
9
CAST 5q15 BS-17, PLACK -CAST and Lung Cancer
9
ALDH3A1 17p11.2 ALDH3, ALDHIII -ALDH3A1 and Lung Cancer
9
NDRG1 8q24.22 GC4, RTP, DRG1, NDR1, NMSL, TDD5, CAP43, CMT4D, DRG-1, HMSNL, RIT42, TARG1, PROXY1 -NDRG1 and Lung Cancer
9
TP53BP1 15q15.3 TP53, p202, 53BP1, TDRD30, p53BP1 -TP53BP1 and Lung Cancer
9
MYCL 1p34.2 LMYC, L-Myc, MYCL1, bHLHe38 -MYCL and Lung Cancer
9
UCHL1 4p13 NDGOA, PARK5, PGP95, SPG79, PGP9.5, Uch-L1, HEL-117, PGP 9.5, HEL-S-53 -UCHL1 and Lung Cancer
9
AVPR1A 12q14.2 V1aR, AVPR1, AVPR V1a -AVPR1A and Lung Cancer
9
BDNF 11p14.1 ANON2, BULN2 -BDNF and Lung Cancer
9
CFTR 7q31.2 CF, MRP7, ABC35, ABCC7, CFTR/MRP, TNR-CFTR, dJ760C5.1 -CFTR and Lung Cancer
9
XRCC5 2q35 KU80, KUB2, Ku86, NFIV, KARP1, KARP-1 -XRCC5 and Lung Cancer
9
DIABLO 12q24.31 SMAC, DFNA64 -DIABLO and Lung Cancer
9
FEN1 11q12.2 MF1, RAD2, FEN-1 -FEN1 and Lung Cancer
9
HOXA5 7p15.2 HOX1, HOX1C, HOX1.3 -HOXA5 and Lung Cancer
9
MAP2K4 17p12 JNKK, MEK4, MKK4, SEK1, SKK1, JNKK1, SERK1, MAPKK4, PRKMK4, SAPKK1, SAPKK-1 -MAP2K4 and Lung Cancer
9
BRMS1 11q13.2 -BRMS1 and Lung Cancer
9
S100A9 1q21.3 MIF, NIF, P14, CAGB, CFAG, CGLB, L1AG, LIAG, MRP14, 60B8AG, MAC387 -S100A9 and Lung Cancer
9
CDK5 7q36.1 LIS7, PSSALRE -CDK5 and Lung Cancer
9
GAB1 4q31.21 -GAB1 and Lung Cancer
8
MBD2 18q21.2 DMTase, NY-CO-41 -MBD2 and Lung Cancer
8
FGF9 13q12.11 GAF, FGF-9, SYNS3, HBFG-9, HBGF-9 -FGF9 and Lung Cancer
8
TNFRSF10B 8p21.3 DR5, CD262, KILLER, TRICK2, TRICKB, ZTNFR9, TRAILR2, TRICK2A, TRICK2B, TRAIL-R2, KILLER/DR5 -TNFRSF10B and Lung Cancer
8
MIRLET7G 3p21.1 LET7G, let-7g, MIRNLET7G, hsa-let-7g -MicroRNA let-7g and Lung Cancer
8
BMP7 20q13.31 OP-1 -BMP7 and Lung Cancer
8
CLMP 11q24.1 ACAM, ASAM, CSBM, CSBS -CLMP and Lung Cancer
8
EREG 4q13.3 ER, Ep, EPR -EREG and Lung Cancer
8
GATA6 18q11.2 -GATA6 and Lung Cancer
8
LPP 3q27.3-q28 -LPP and Lung Cancer
8
EXO1 1q43 HEX1, hExoI -EXO1 and Lung Cancer
8
IL2RG Xq13.1 P64, CIDX, IMD4, CD132, SCIDX, IL-2RG, SCIDX1 -IL2RG and Lung Cancer
8
TXNIP 1q21.1 THIF, VDUP1, ARRDC6, HHCPA78, EST01027 -TXNIP and Lung Cancer
8
SUV39H1 Xp11.23 MG44, KMT1A, SUV39H, H3-K9-HMTase 1 -SUV39H1 and Lung Cancer
8
AIDA 1q41 C1orf80 -AIDA and Lung Cancer
8
SPRY2 13q31.1 IGAN3, hSPRY2 -SPRY2 and Lung Cancer
8
PRKCA 17q24.2 AAG6, PKCA, PRKACA, PKC-alpha -PRKCA and Lung Cancer
8
RARS 5q34 HLD9, ArgRS, DALRD1 -RARS and Lung Cancer
8
PTPRD 9p24.1-p23 HPTP, PTPD, HPTPD, HPTPDELTA, RPTPDELTA -PTPRD and Lung Cancer
8
NUMB 14q24.2-q24.3 S171, C14orf41, c14_5527 -NUMB and Lung Cancer
8
ABCC2 10q24.2 DJS, MRP2, cMRP, ABC30, CMOAT -ABCC2 and Lung Cancer
8
SSTR1 14q21.1 SS1R, SS1-R, SRIF-2, SS-1-R -SSTR1 and Lung Cancer
8
HYAL1 3p21.31 MPS9, NAT6, LUCA1, HYAL-1 -HYAL1 and Lung Cancer
8
TBK1 12q14.1 NAK, T2K -TBK1 and Lung Cancer
8
XRCC2 7q36.1 FANCU -XRCC2 and Lung Cancer
8
PWAR1 15q11.2 PAR1, PAR-1, D15S227E -PAR1 and Lung Cancer
8
CRTC1 19p13.11 MECT1, TORC1, TORC-1, WAMTP1 -CRTC1 and Lung Cancer
8
TNFSF11 13q14.11 ODF, OPGL, sOdf, CD254, OPTB2, RANKL, TNLG6B, TRANCE, hRANKL2 -TNFSF11 and Lung Cancer
8
LYN 8q12.1 JTK8, p53Lyn, p56Lyn -LYN and Lung Cancer
8
ING1 13q34 p33, p47, p33ING1, p24ING1c, p33ING1b, p47ING1a -ING1 and Lung Cancer
8
MCM2 3q21 BM28, CCNL1, CDCL1, cdc19, D3S3194, MITOTIN -MCM2 and Lung Cancer
8
DUSP6 12q21.33 HH19, MKP3, PYST1 -DUSP6 and Lung Cancer
8
DNAJB4 1p31.1 DjB4, HLJ1, DNAJW -DNAJB4 and Lung Cancer
8
LCN2 9q34.11 p25, 24p3, MSFI, NGAL -LCN2 and Lung Cancer
8
EZR 6q25.3 CVL, CVIL, VIL2, HEL-S-105 -EZR and Lung Cancer
8
ACTN4 19q13.2 FSGS, FSGS1, ACTININ-4 -ACTN4 and Lung Cancer
8
MTAP 9p21.3 BDMF, MSAP, DMSFH, LGMBF, DMSMFH, c86fus, HEL-249 -MTAP and Lung Cancer
8
KL 13q13.1 -KL and Lung Cancer
8
HOTAIR 12q13.13 HOXAS, HOXC-AS4, HOXC11-AS1, NCRNA00072 -HOTAIR and Lung Cancer
8
HDGF 1q23.1 HMG1L2 -HDGF and Lung Cancer
8
AKR1C1 10p15.1 C9, DD1, DDH, DDH1, H-37, HBAB, MBAB, HAKRC, DD1/DD2, 2-ALPHA-HSD, 20-ALPHA-HSD -AKR1C1 and Lung Cancer
8
ESR2 14q23.2-q23.3 Erb, ESRB, ESTRB, NR3A2, ER-BETA, ESR-BETA -ESR2 and Lung Cancer
8
ING4 12p13.31 my036, p29ING4 -ING4 and Lung Cancer
7
HNF4A 20q13.12 TCF, HNF4, MODY, FRTS4, MODY1, NR2A1, TCF14, HNF4a7, HNF4a8, HNF4a9, NR2A21, HNF4alpha -HNF4A and Lung Cancer
7
MVP 16p11.2 LRP, VAULT1 -MVP and Lung Cancer
7
NR0B1 Xp21.2 AHC, AHX, DSS, GTD, HHG, AHCH, DAX1, DAX-1, NROB1, SRXY2 -NR0B1 and Lung Cancer
7
PPP2R1B 11q23.1 PR65B, PP2A-Abeta -PPP2R1B and Lung Cancer
7
LIN28B 6q16.3-q21 CSDD2 -LIN28B and Lung Cancer
7
GATA5 20q13.33 CHTD5, GATAS, bB379O24.1 -GATA5 and Lung Cancer
7
ZMYND10 3p21.31 BLU, FLU, CILD22 -ZMYND10 and Lung Cancer
7
ACTA2 10q23.31 AAT6, ACTSA, MYMY5 -ACTA2 and Lung Cancer
7
TRAF6 11p12 RNF85, MGC:3310 -TRAF6 and Lung Cancer
7
SOX18 20q13.33 HLTS, HLTRS -SOX18 and Lung Cancer
7
RASSF5 1q32.1 RAPL, Maxp1, NORE1, NORE1A, NORE1B, RASSF3 -RASSF5 and Lung Cancer
7
CHGA 14q32.12 CGA -CHGA and Lung Cancer
7
CYP27B1 12q14.1 VDR, CP2B, CYP1, PDDR, VDD1, VDDR, VDDRI, CYP27B, P450c1, CYP1alpha -CYP27B1 and Lung Cancer
7
CALCA 11p15.2 CT, KC, PCT, CGRP, CALC1, CGRP1, CGRP-I -CALCA and Lung Cancer
7
PRB2 12p13.2 Ps, cP7, IB-9, PRPPRB1 -PRB2 and Lung Cancer
7
DMBT1 10q26.13 SAG, GP340, SALSA, muclin -DMBT1 and Lung Cancer
7
CTCFL 20q13.31 CT27, BORIS, CTCF-T, HMGB1L1, dJ579F20.2 -CTCFL and Lung Cancer
7
AMFR 16q13 GP78, RNF45 -AMFR and Lung Cancer
7
NFATC2 20q13.2 NFAT1, NFATP -NFATC2 and Lung Cancer
7
FOXC2 16q24.1 LD, MFH1, MFH-1, FKHL14 -FOXC2 and Lung Cancer
7
HEY1 8q21.13 CHF2, OAF1, HERP2, HESR1, HRT-1, hHRT1, BHLHb31 -HEY1 and Lung Cancer
7
CTNNA1 5q31.2 MDPT2, CAP102 -CTNNA1 and Lung Cancer
7
U2AF1 21q22.3 RN, FP793, U2AF35, U2AFBP, RNU2AF1 -U2AF1 and Lung Cancer
7
ID2 2p25 GIG8, ID2A, ID2H, bHLHb26 Prognostic
-ID2 Expression in Lung Cancer
7
WNT7A 3p25 -WNT7A and Lung Cancer
7
REST 4q12 WT6, XBR, NRSF -REST and Lung Cancer
7
XRCC4 5q14.2 SSMED -XRCC4 and Lung Cancer
7
PTPN13 4q21.3 PNP1, FAP-1, PTP1E, PTPL1, PTPLE, PTP-BL, hPTP1E, PTP-BAS -PTPN13 and Lung Cancer
7
TACC3 4p16.3 ERIC1, ERIC-1 -TACC3 and Lung Cancer
7
DDB2 11p11.2 XPE, DDBB, UV-DDB2 -DDB2 and Lung Cancer
7
MBD1 18q21.1 RFT, PCM1, CXXC3 -MBD1 and Lung Cancer
7
SEMA3F 3p21.3 SEMA4, SEMAK, SEMA-IV -SEMA3F and Lung Cancer
7
SDC4 20q13.12 SYND4 -SDC4 and Lung Cancer
7
BCHE 3q26.1-q26.2 E1, CHE1, CHE2 -BCHE and Lung Cancer
7
NEK2 1q32.3 NLK1, RP67, NEK2A, HsPK21, PPP1R111 -NEK2 and Lung Cancer
7
GATA4 8p23.1 TOF, ASD2, VSD1, TACHD -GATA4 and Lung Cancer
7
CD46 1q32.2 MCP, TLX, AHUS2, MIC10, TRA2.10 -CD46 and Lung Cancer
7
SEMA3A 7q21.11 HH16, SemD, COLL1, SEMA1, SEMAD, SEMAL, coll-1, Hsema-I, SEMAIII, Hsema-III -SEMA3A and Lung Cancer
6
POLK 5q13.3 DINP, POLQ, DINB1 -POLK and Lung Cancer
6
FOLR1 11q13.4 FBP, FOLR -FOLR1 and Lung Cancer
6
ECT2 3q26.31 ARHGEF31 -ECT2 and Lung Cancer
6
SPRR1B 1q21.3 SPRR1, GADD33, SPR-IB, CORNIFIN -SPRR1B and Lung Cancer
6
NSD3 8p11.23 KMT3F, KMT3G, WHISTLE, WHSC1L1, pp14328 -WHSC1L1 and Lung Cancer
6
NOX4 11q14.3 KOX, KOX-1, RENOX -NOX4 and Lung Cancer
6
PIAS3 1q21.1 ZMIZ5 -PIAS3 and Lung Cancer
6
PDPK1 16p13.3 PDK1, PDPK2, PDPK2P, PRO0461 -PDPK1 and Lung Cancer
6
SMYD3 1q44 KMT3E, ZMYND1, ZNFN3A1, bA74P14.1 -SMYD3 and Lung Cancer
6
AQP1 7p14.3 CO, CHIP28, AQP-CHIP -AQP1 and Lung Cancer
6
MAX 14q23.3 bHLHd4 -MAX and Lung Cancer
6
PDCD1 2q37.3 PD1, PD-1, CD279, SLEB2, hPD-1, hPD-l, hSLE1 -PDCD1 and Lung Cancer
6
WARS 14q32.2 IFI53, IFP53, GAMMA-2 -WARS and Lung Cancer
6
CXCR3 Xq13.1 GPR9, MigR, CD182, CD183, Mig-R, CKR-L2, CMKAR3, IP10-R -CXCR3 and Lung Cancer
6
ROR1 1p31.3 NTRKR1, dJ537F10.1 -ROR1 and Lung Cancer
6
AGR2 7p21.1 AG2, AG-2, HPC8, GOB-4, HAG-2, XAG-2, PDIA17, HEL-S-116 -AGR2 and Lung Cancer
6
CCNA1 13q13.3 CT146 -CCNA1 and Lung Cancer
6
HSP90AB1 6p21.1 HSP84, HSPC2, HSPCB, D6S182, HSP90B -HSP90AB1 and Lung Cancer
6
SPINK1 5q32 TCP, PCTT, PSTI, TATI, Spink3 -SPINK1 and Lung Cancer
6
ROBO1 3p12 SAX3, DUTT1 -ROBO1 and Lung Cancer
6
DLEC1 3p22.2 F56, DLC1, DLC-1, CFAP81 -DLEC1 and Lung Cancer
6
SLC29A1 6p21.1 ENT1 -SLC29A1 and Lung Cancer
6
CEBPB 20q13.13 TCF5, IL6DBP, NF-IL6, C/EBP-beta -CEBPB and Lung Cancer
6
CRTC2 1q21.3 TORC2, TORC-2 -CRTC2 and Lung Cancer
6
TTL 2q13 -TTL and Lung Cancer
6
CDCP1 3p21.31 CD318, TRASK, SIMA135 -CDCP1 and Lung Cancer
6
CDC6 17q21.2 CDC18L, HsCDC6, MGORS5, HsCDC18 -CDC6 and Lung Cancer
6
SULF2 20q13.12 HSULF-2 -SULF2 and Lung Cancer
6
NEUROD1 2q32 BETA2, BHF-1, MODY6, NEUROD, bHLHa3 -NEUROD1 and Lung Cancer
6
DLX4 17q21.33 BP1, DLX7, DLX8, DLX9, OFC15 -DLX4 and Lung Cancer
6
WISP1 8q24.22 CCN4, WISP1c, WISP1i, WISP1tc -WISP1 and Lung Cancer
6
CUL4A 13q34 -CUL4A and Lung Cancer
6
FPGS 9q34.11 -FPGS and Lung Cancer
6
TJP1 15q13.1 ZO-1 -TJP1 and Lung Cancer
6
HIP1 7q11.23 SHON, HIP-I, ILWEQ, SHONbeta, SHONgamma -HIP1 and Lung Cancer
6
FOSB 19q13.32 AP-1, G0S3, GOS3, GOSB -FOSB and Lung Cancer
6
JAG2 14q32.33 HJ2, SER2 -JAG2 and Lung Cancer
6
AGO2 8q24.3 PPD, Q10, CASC7, EIF2C2, LINC00980 -EIF2C2 and Lung Cancer
6
FEV 2q36 PET-1, HSRNAFEV -FEV and Lung Cancer
6
MEG3 14q32.2 GTL2, FP504, prebp1, PRO0518, PRO2160, LINC00023, NCRNA00023, onco-lncRNA-83 -MEG3 and Lung Cancer
6
RALBP1 18p11.22 RIP1, RLIP1, RLIP76 -RALBP1 and Lung Cancer
6
MMP10 11q22.2 SL-2, STMY2 -MMP10 and Lung Cancer
6
SALL4 20q13.2 DRRS, HSAL4, ZNF797 -SALL4 and Lung Cancer
6
TFG 3q12.2 TF6, HMSNP, SPG57, TRKT3 -TFG and Lung Cancer
6
PPARD 6p21.31 FAAR, NUC1, NUCI, NR1C2, NUCII, PPARB -PPAR delta and Lung Cancer
6
DRD2 11q23.2 D2R, D2DR -DRD2 and Lung Cancer
6
CCNE2 8q22.1 CYCE2 -CCNE2 and Lung Cancer
6
ARHGDIB 12p12.3 D4, GDIA2, GDID4, LYGDI, Ly-GDI, RAP1GN1, RhoGDI2 -ARHGDIB and Lung Cancer
6
PITX1 5q31.1 BFT, CCF, POTX, PTX1, LBNBG -PITX1 and Lung Cancer
6
LIG4 13q33.3 LIG4S -LIG4 and Lung Cancer
6
PGK1 Xq21.1 PGKA, MIG10, HEL-S-68p -PGK1 and Lung Cancer
6
SHMT1 17p11.2 SHMT, CSHMT -SHMT1 and Lung Cancer
6
IKBKE 1q32.1 IKKE, IKKI, IKK-E, IKK-i -IKBKE and Lung Cancer
5
TLE1 9q21.32 ESG, ESG1, GRG1 -TLE1 and Lung Cancer
5
MACC1 7p21.1 7A5, SH3BP4L -MACC1 and Lung Cancer
5
ALCAM 3q13.1 MEMD, CD166 -ALCAM and Lung Cancer
5
CD36 7q21.11 FAT, GP4, GP3B, GPIV, CHDS7, PASIV, SCARB3, BDPLT10 -CD36 and Lung Cancer
5
FRS2 12q15 SNT, SNT1, FRS1A, FRS2A, SNT-1, FRS2alpha -FRS2 and Lung Cancer
5
PYGM 11q13.1 -PYGM and Lung Cancer
5
IL15 4q31.21 IL-15 -IL15 and Lung Cancer
5
CCL19 9p13.3 ELC, CKb11, MIP3B, MIP-3b, SCYA19 -CCL19 and Lung Cancer
5
TAGLN 11q23.3 SM22, SMCC, TAGLN1, WS3-10 -TAGLN and Lung Cancer
5
SCGB3A1 5q35.3 HIN1, HIN-1, LU105, UGRP2, PnSP-2 -SCGB3A1 and Lung Cancer
5
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 Lung Cancer
5
EFEMP1 2p16 DHRD, DRAD, FBNL, MLVT, MTLV, S1-5, FBLN3, FIBL-3 -EFEMP1 and Lung Cancer
5
SMAD6 15q22.31 AOVD2, MADH6, MADH7, HsT17432 -SMAD6 and Lung Cancer
5
RPS6 9p22.1 S6 -RPS6 and Lung Cancer
5
TMEFF2 2q32.3 TR, HPP1, TPEF, TR-2, TENB2, CT120.2 -TMEFF2 and Lung Cancer
5
LOXL2 8p21.3 LOR, LOR2, WS9-14 -LOXL2 and Lung Cancer
5
BRAP 12q24.12 IMP, BRAP2, RNF52 -BRAP and Lung Cancer
5
STK4 20q13.12 KRS2, MST1, YSK3 -STK4 and Lung Cancer
5
HDAC4 2q37.3 HD4, AHO3, BDMR, HDACA, HA6116, HDAC-4, HDAC-A -HDAC4 and Lung Cancer
5
EPHB6 7q34 HEP -EPHB6 and Lung Cancer
5
MAD1L1 7p22.3 MAD1, PIG9, TP53I9, TXBP181 -MAD1L1 and Lung Cancer
5
HSPA1B 6p21.3 HSP70-2, HSP70.2, HSP70-1B -HSPA1B and Lung Cancer
5
CYP2C9 10q23.33 CPC9, CYP2C, CYP2C10, CYPIIC9, P450IIC9 -CYP2C9 and Lung Cancer
5
DLL4 15q15.1 AOS6, hdelta2 -DLL4 and Lung Cancer
5
CAV2 7q31.2 CAV -CAV2 and Lung Cancer
5
LEPR 1p31.3 OBR, OB-R, CD295, LEP-R, LEPRD -LEPR and Lung Cancer
5
MIR107 10q23.31 MIRN107, miR-107 -MIRN107 microRNA, human and Lung Cancer
5
ADAMTS1 21q21.3 C3-C5, METH1 -ADAMTS1 and Lung Cancer
5
SSTR5 16p13.3 SS-5-R -SSTR5 and Lung Cancer
5
PTGER2 14q22.1 EP2 -PTGER2 and Lung Cancer
5
IGFBP5 2q35 IBP5 -IGFBP5 and Lung Cancer
5
ASPSCR1 17q25.3 TUG, ASPL, ASPS, RCC17, UBXD9, UBXN9, ASPCR1 -ASPSCR1 and Lung Cancer
5
LAPTM4B 8q22.1 LC27, LAPTM4beta -LAPTM4B and Lung Cancer
5
IL24 1q32.1 C49A, FISP, MDA7, MOB5, ST16, IL10B -IL24 and Lung Cancer
5
RPA1 17p13.3 HSSB, RF-A, RP-A, REPA1, RPA70, MST075 -RPA1 and Lung Cancer
5
PON1 7q21.3 ESA, PON, MVCD5 -PON1 and Lung Cancer
5
CEACAM6 19q13.2 NCA, CEAL, CD66c -CEACAM6 and Lung Cancer
5
TGFB3 14q24.3 ARVD, LDS5, RNHF, ARVD1, TGF-beta3 -TGFB3 and Lung Cancer
5
AKAP12 6q25.1 SSeCKS, AKAP250 -AKAP12 and Lung Cancer
5
DEC1 9q33.1 CTS9 -DEC1 and Lung Cancer
5
NOTO 2p13.2 -NOTO and Lung Cancer
5
SLC7A5 16q24.2 E16, CD98, LAT1, 4F2LC, MPE16, D16S469E -SLC7A5 and Lung Cancer
5
ELF3 1q32.1 ERT, ESX, EPR-1, ESE-1 -ELF3 and Lung Cancer
5
CXCL14 5q31.1 KEC, KS1, BMAC, BRAK, NJAC, MIP2G, MIP-2g, SCYB14 -CXCL14 and Lung Cancer
5
VCAN 5q14.2-q14.3 WGN, ERVR, GHAP, PG-M, WGN1, CSPG2 -VCAN and Lung Cancer
5
CHUK 10q24.31 IKK1, IKKA, IKBKA, TCF16, NFKBIKA, IKK-alpha -CHUK and Lung Cancer
5
S100A11 1q21.3 MLN70, S100C, HEL-S-43 -S100A11 and Lung Cancer
5
PYCARD 16p11.2 ASC, TMS, TMS1, CARD5, TMS-1 -PYCARD and Lung Cancer
5
MIRLET7D 9q22.32 LET7D, let-7d, MIRNLET7D, hsa-let-7d -None and MicroRNA let-d Cancer
5
FURIN 15q26.1 FUR, PACE, SPC1, PCSK3 -FURIN and Lung Cancer
5
MTA2 11q12.3 PID, MTA1L1 -MTA2 and Lung Cancer
5
MYH9 22q12.3 MHA, FTNS, EPSTS, BDPLT6, DFNA17, MATINS, NMMHCA, NMHC-II-A, NMMHC-IIA -MYH9 and Lung Cancer
5
PRDX1 1p34.1 PAG, PAGA, PAGB, PRX1, PRXI, MSP23, NKEFA, TDPX2, NKEF-A -PRDX1 and Lung Cancer
5
MBD4 3q21.3 MED1 -MBD4 and Lung Cancer
5
CLDN3 7q11.23 RVP1, HRVP1, C7orf1, CPE-R2, CPETR2 -CLDN3 and Lung Cancer
5
TSG101 11p15.1 TSG10, VPS23 -TSG101 and Lung Cancer
5
MINA 3q11.2 ROX, MDIG, NO52, MINA53 -MINA and Lung Cancer
5
ERCC6 10q11.23 CSB, CKN2, COFS, ARMD5, COFS1, POF11, RAD26, UVSS1 -ERCC6 and Lung Cancer
5
IL1A 2q14 IL1, IL-1A, IL1F1, IL1-ALPHA -IL1A and Lung Cancer
5
MIRLET7E 19q13.41 LET7E, let-7e, MIRNLET7E, hsa-let-7e -MicroRNA let-7e and Lung Cancer
5
DACH1 13q21.33 DACH -DACH1 and Lung Cancer
5
CD276 15q24.1 B7H3, B7-H3, B7RP-2, 4Ig-B7-H3 -CD276 and Lung Cancer
5
GAS6 13q34 AXSF, AXLLG -GAS6 and Lung Cancer
5
ZBTB7A 19p13.3 LRF, FBI1, FBI-1, TIP21, ZBTB7, ZNF857A, pokemon -ZBTB7A and Lung Cancer
5
RALA 7p14.1 RAL -RALA and Lung Cancer
5
PGLS 19p13.11 6PGL, HEL-S-304 -PGLS and Lung Cancer
5
AQP3 9p13.3 GIL, AQP-3 -AQP3 and Lung Cancer
4
BMP6 6p24.3 VGR, VGR1 -BMP6 and Lung Cancer
4
PPM1D 17q23.2 WIP1, PP2C-DELTA -PPM1D and Lung Cancer
4
NRP1 10p11.22 NP1, NRP, BDCA4, CD304, VEGF165R -NRP1 and Lung Cancer
4
CASP6 4q25 MCH2 -CASP6 and Lung Cancer
4
CCL20 2q36.3 CKb4, LARC, ST38, MIP3A, Exodus, MIP-3a, SCYA20, MIP-3-alpha -CCL20 and Lung Cancer
4
DOK2 8p21.3 p56DOK, p56dok-2 -DOK2 and Lung Cancer
4
CD151 11p15.5 GP27, MER2, RAPH, SFA1, PETA-3, TSPAN24 -CD151 and Lung Cancer
4
GFRA1 10q25.3 GDNFR, RET1L, RETL1, TRNR1, GDNFRA, GFR-ALPHA-1 -GFRA1 and Lung Cancer
4
CCR1 3p21 CKR1, CD191, CKR-1, HM145, CMKBR1, MIP1aR, SCYAR1 -CCR1 and Lung Cancer
4
HOXA4 7p15.2 HOX1, HOX1D -HOXA4 and Lung Cancer
4
MAGEB2 Xp21.2 DAM6, CT3.2, MAGE-XP-2 -MAGEB2 and Lung Cancer
4
NRP2 2q33.3 NP2, NPN2, PRO2714, VEGF165R2 -NRP2 and Lung Cancer
4
SERPINA1 14q32.13 PI, A1A, AAT, PI1, A1AT, PRO2275, alpha1AT -SERPINA1 and Lung Cancer
4
HOXA11 7p15.2 HOX1, HOX1I, RUSAT1 -HOXA11 and Lung Cancer
4
HPSE 4q21.23 HPA, HPA1, HPR1, HSE1, HPSE1 -HPSE and Lung Cancer
4
FER 5q21.3 TYK3, PPP1R74, p94-Fer -FER and Lung Cancer
4
CD81 11p15.5 S5.7, CVID6, TAPA1, TSPAN28 -CD81 and Lung Cancer
4
TP53I3 2p23.3 PIG3 -TP53I3 and Lung Cancer
4
LRP1B 2q21.2 LRPDIT, LRP-DIT -LRP1B and Lung Cancer
4
ARID2 12q12 p200, BAF200 -ARID2 and Lung Cancer
4
LAMC2 1q25.3 B2T, CSF, EBR2, BM600, EBR2A, LAMB2T, LAMNB2 -LAMC2 and Lung Cancer
4
RALGDS 9q34.13-q34.2 RGF, RGDS, RalGEF -RALGDS and Lung Cancer
4
TGFBI 5q31.1 CSD, CDB1, CDG2, CSD1, CSD2, CSD3, EBMD, LCD1, BIGH3, CDGG1 -TGFBI and Lung Cancer
4
MIRLET7I 12q14.1 LET7I, let-7i, MIRNLET7I, hsa-let-7i -MicroRNA let-7i and Lung Cancer
4
MED1 17q12 PBP, CRSP1, RB18A, TRIP2, PPARBP, CRSP200, DRIP205, DRIP230, PPARGBP, TRAP220 -MED1 and Lung Cancer
4
SSTR3 22q13.1 SS3R, SS3-R, SS-3-R, SSR-28 -SSTR3 and Lung Cancer
4
SOS1 2p21 GF1, HGF, NS4, GGF1, GINGF -SOS1 and Lung Cancer
4
PLAU 10q22.2 ATF, QPD, UPA, URK, u-PA, BDPLT5 -PLAU and Lung Cancer
4
CCL3 17q12 MIP1A, SCYA3, G0S19-1, LD78ALPHA, MIP-1-alpha -CCL3 and Lung Cancer
4
IQGAP1 15q26.1 SAR1, p195, HUMORFA01 -IQGAP1 and Lung Cancer
4
RBX1 22q13.2 ROC1, RNF75, BA554C12.1 -RBX1 and Lung Cancer
4
CASP2 7q34 ICH1, NEDD2, CASP-2, NEDD-2, PPP1R57 -CASP2 and Lung Cancer
4
XAF1 17p13.1 BIRC4BP, XIAPAF1, HSXIAPAF1 -XAF1 and Lung Cancer
4
CCL21 9p13.3 ECL, SLC, CKb9, TCA4, 6Ckine, SCYA21 -CCL21 and Lung Cancer
4
MAPK14 6p21.31 RK, p38, CSBP, EXIP, Mxi2, CSBP1, CSBP2, CSPB1, PRKM14, PRKM15, SAPK2A, p38ALPHA -MAPK14 and Lung Cancer
4
CDH3 16q22.1 CDHP, HJMD, PCAD -CDH3 and Lung Cancer
4
LARS 5q32 LRS, LEUS, LFIS, ILFS1, LARS1, LEURS, PIG44, RNTLS, HSPC192, hr025Cl -LARS and Lung Cancer
4
USP7 16p13.2 TEF1, HAUSP -USP7 and Lung Cancer
4
MAPKAPK2 1q32.1 MK2, MK-2, MAPKAP-K2 -MAPKAPK2 and Lung Cancer
4
ROR2 9q22.31 BDB, BDB1, NTRKR2 -ROR2 and Lung Cancer
4
INHA 2q35 -INHA and Lung Cancer
4
MUC5B 11p15.5 MG1, MUC5, MUC9, MUC-5B -MUC5B and Lung Cancer
4
ATG7 3p25.3 GSA7, APG7L, APG7-LIKE -ATG7 and Lung Cancer
4
FGF19 11q13.3 -FGF19 and Lung Cancer
4
SKP1 5q31.1 OCP2, p19A, EMC19, SKP1A, OCP-II, TCEB1L -SKP1 and Lung Cancer
4
TFPI 2q32 EPI, TFI, LACI, TFPI1 -TFPI and Lung Cancer
4
CLDN7 17p13.1 CLDN-7, CEPTRL2, CPETRL2, Hs.84359, claudin-1 -CLDN7 and Lung Cancer
4
KLK10 19q13.41 NES1, PRSSL1 -KLK10 and Non-Small Cell Lung Cancer
4
ASH1L 1q22 ASH1, KMT2H, MRD52, ASH1L1 -ASH1L and Lung Cancer
4
ADAR 1q21.3 DSH, AGS6, G1P1, IFI4, P136, ADAR1, DRADA, DSRAD, IFI-4, K88DSRBP -ADAR and Lung Cancer
4
ATF2 2q32 HB16, CREB2, TREB7, CREB-2, CRE-BP1 -ATF2 and Lung Cancer
4
FOXO4 Xq13.1 AFX, AFX1, MLLT7 -FOXO4 and Lung Cancer
4
HTATIP2 11p15.1 CC3, TIP30, SDR44U1 -HTATIP2 and Lung Cancer
4
SATB1 3p23 -SATB1 and Lung Cancer
4
VIPR1 3p22.1 II, HVR1, RDC1, V1RG, VIPR, VIRG, VAPC1, VPAC1, VPAC1R, VIP-R-1, VPCAP1R, PACAP-R2, PACAP-R-2 -VIPR1 and Lung Cancer
4
KIAA1524 3q13.13 p90, CIP2A -KIAA1524 and Lung Cancer
4
SOX1 13q34 -SOX1 and Lung Cancer
4
CDK7 5q13.2 CAK, CAK1, HCAK, MO15, STK1, CDKN7, p39MO15 -CDK7 and Lung Cancer
4
TNKS 8p23.1 TIN1, ARTD5, PARPL, TINF1, TNKS1, pART5, PARP5A, PARP-5a -TNKS and Lung Cancer
4
PRDX6 1q25.1 PRX, p29, AOP2, 1-Cys, NSGPx, aiPLA2, HEL-S-128m -PRDX6 and Lung Cancer
4
BCL2L11 2q13 BAM, BIM, BOD -BCL2L11 and Lung Cancer
4
MALL 2q13 BENE -MALL and Lung Cancer
4
TANK 2q24.2 ITRAF, TRAF2, I-TRAF -TANK and Lung Cancer
4
ATP7A Xq21.1 MK, MNK, DSMAX, SMAX3 -ATP7A and Lung Cancer
4
FGF10 5p12 -FGF10 and Lung Cancer
4
WNT2 7q31.2 IRP, INT1L1 -WNT2 and Lung Cancer
4
BCL2L2 14q11.2 BCLW, BCL-W, PPP1R51, BCL2-L-2 -BCL2L2 and Lung Cancer
4
CXCR1 2q35 C-C, CD128, CD181, CKR-1, IL8R1, IL8RA, CMKAR1, IL8RBA, CDw128a, C-C-CKR-1 -CXCR1 and Lung Cancer
4
RAD23B 9q31.2 P58, HR23B, HHR23B -RAD23B and Lung Cancer
4
PPARGC1A 4p15.2 LEM6, PGC1, PGC1A, PGC-1v, PPARGC1, PGC-1alpha, PGC-1(alpha) -PPARGC1A and Lung Cancer
4
PEA15 1q23.2 PED, MAT1, HMAT1, MAT1H, PEA-15, HUMMAT1H, PED-PEA15, PED/PEA15 -PEA15 and Lung Cancer
4
MTSS1 8q24.13 MIM, MIMA, MIMB -MTSS1 and Lung Cancer
4
MAP3K8 10p11.23 COT, EST, ESTF, TPL2, AURA2, MEKK8, Tpl-2, c-COT -MAP3K8 and Lung Cancer
4
TXNRD1 12q23.3 TR, TR1, TXNR, TRXR1, GRIM-12 -TXNRD1 and Lung Cancer
4
GUSB 7q11.21 BG, MPS7 -GUSB and Lung Cancer
4
PDCD6 5p15.33 ALG2, ALG-2, PEF1B -PDCD6 and Lung Cancer
4
TFRC 3q29 T9, TR, TFR, p90, CD71, TFR1, TRFR, IMD46 -TFRC and Lung Cancer
4
GREM1 15q13.3 DRM, HMPS, MPSH, PIG2, CRAC1, CRCS4, DAND2, HMPS1, IHG-2, DUP15q, C15DUPq, GREMLIN, CKTSF1B1 -GREM1 and Lung Cancer
4
BAGE 21p11.1 BAGE1, CT2.1 -BAGE and Lung Cancer
3
AGTR2 Xq23 AT2, ATGR2, MRX88 -AGTR2 and Lung Cancer
3
KLK14 19q13.41 KLK-L6 -KLK14 and Lung Cancer
3
MCM4 8q11.21 NKCD, CDC21, CDC54, NKGCD, hCdc21, P1-CDC21 -MCM4 and Lung Cancer
3
GPX2 14q23.3 GPRP, GPx-2, GI-GPx, GPRP-2, GPx-GI, GSHPx-2, GSHPX-GI -GPX2 and Lung Cancer
3
PVT1 8q24.21 MYC, LINC00079, NCRNA00079, onco-lncRNA-100 -PVT1 and Lung Cancer
3
KISS1R 19p13.3 HH8, CPPB1, GPR54, AXOR12, KISS-1R, HOT7T175 -KISS1R and Lung Cancer
3
NTRK1 1q23.1 MTC, TRK, TRK1, TRKA, Trk-A, p140-TrkA Translocation
-CD74-NTRK1 fusion in Lung Cancer
3
RAP1GDS1 4q23 GDS1, SmgGDS -RAP1GDS1 and Lung Cancer
3
GJB2 13q12.11 HID, KID, PPK, CX26, DFNA3, DFNB1, NSRD1, DFNA3A, DFNB1A -GJB2 and Lung Cancer
3
HOXD10 2q31.1 HOX4, HOX4D, HOX4E, Hox-4.4 -HOXD10 and Lung Cancer
3
NEFL 8p21.2 NFL, NF-L, NF68, CMT1F, CMT2E, PPP1R110 -NEFL and Lung Cancer
3
BOLL 2q33 BOULE -BOLL and Lung Cancer
3
CBX7 22q13.1 -CBX7 and Lung Cancer
3
KLK5 19q13.41 SCTE, KLKL2, KLK-L2 -KLK5 and Lung Cancer
3
PRKCDBP 11p15.4 SRBC, HSRBC, CAVIN3, cavin-3 -PRKCDBP and Lung Cancer
3
SKIL 3q26 SNO, SnoA, SnoI, SnoN -SKIL and Lung Cancer
3
MARS 12q13.3 MRS, ILLD, CMT2U, ILFS2, METRS, MTRNS, SPG70 -MARS and Lung Cancer
3
CDK9 9q34.11 TAK, C-2k, CTK1, CDC2L4, PITALRE -CDK9 and Lung Cancer
3
ITGB2 21q22.3 LAD, CD18, MF17, MFI7, LCAMB, LFA-1, MAC-1 -ITGB2 and Lung Cancer
3
LMO4 1p22.3 -LMO4 and Lung Cancer
3
PDCD1LG2 9p24.1 B7DC, Btdc, PDL2, CD273, PD-L2, PDCD1L2, bA574F11.2 -PDCD1LG2 and Lung Cancer
3
SIRT3 11p15.5 SIR2L3 -SIRT3 and Lung Cancer
3
GAGE1 Xp11.23 CT4.1, CT4.4, GAGE4, GAGE-1, GAGE-4 -GAGE1 and Lung Cancer
3
UGT2B17 4q13.2 BMND12, UDPGT2B17 -UGT2B17 and Lung Cancer
3
CMBL 5p15.2 JS-1 -CMBL and Lung Cancer
3
HOXB4 17q21.32 HOX2, HOX2F, HOX-2.6 -HOXB4 and Lung Cancer
3
CTSD 11p15.5 CPSD, CLN10, HEL-S-130P -CTSD and Lung Cancer
3
LZTS1 8p21.3 F37, FEZ1 -LZTS1 and Lung Cancer
3
LIMD1 3p21.31 -LIMD1 and Lung Cancer
3
RALB 2q14.2 -RALB and Lung Cancer
3
CDH17 8q22.1 HPT1, CDH16, HPT-1 -CDH17 and Lung Cancer
3
NOX1 Xq22.1 MOX1, NOH1, NOH-1, GP91-2 -NOX1 and Lung Cancer
3
DUSP4 8p12 TYP, HVH2, MKP2, MKP-2 -DUSP4 and Lung Cancer
3
CCL17 16q21 TARC, ABCD-2, SCYA17, A-152E5.3 -CCL17 and Lung Cancer
3
HMMR 5q34 CD168, IHABP, RHAMM -HMMR and Lung Cancer
3
CX3CR1 3p21.3 V28, CCRL1, GPR13, CMKDR1, GPRV28, CMKBRL1 -CX3CR1 and Lung Cancer
3
POLB 8p11.21 -POLB and Lung Cancer
3
TRA 14q11.2 IMD7, TCRA, TCRD, TRA@, TRAC -TRA and Lung Cancer
3
TNFRSF1B 1p36.22 p75, TBPII, TNFBR, TNFR2, CD120b, TNFR1B, TNFR80, TNF-R75, p75TNFR, TNF-R-II -TNFRSF1B and Lung Cancer
3
TNFRSF10D 8p21.3 DCR2, CD264, TRUNDD, TRAILR4, TRAIL-R4 -TNFRSF10D and Lung Cancer
3
LIMK1 7q11.23 LIMK, LIMK-1 -LIMK1 and Lung Cancer
3
TRIM24 7q33-q34 PTC6, TF1A, TIF1, RNF82, TIF1A, hTIF1, TIF1ALPHA -TRIM24 and Lung Cancer
3
CASP5 11q22.3 ICH-3, ICEREL-III, ICE(rel)III -CASP5 and Lung Cancer
3
LGALS4 19q13.2 GAL4, L36LBP -LGALS4 and Lung Cancer
3
CCL22 16q21 MDC, ABCD-1, SCYA22, STCP-1, DC/B-CK, A-152E5.1 -CCL22 and Lung Cancer
3
IRF7 11p15.5 IMD39, IRF7A, IRF7B, IRF7C, IRF7H, IRF-7H -IRF7 and Lung Cancer
3
PLA2G2A 1p36.13 MOM1, PLA2, PLA2B, PLA2L, PLA2S, PLAS1, sPLA2 -PLA2G2A and Lung Cancer
3
SPDEF 6p21.3 PDEF, bA375E1.3 -SPDEF and Lung Cancer
3
OPCML 11q25 OPCM, OBCAM, IGLON1 -OPCML and Lung Cancer
3
SMPD1 11p15.4 ASM, NPD, ASMASE -SMPD1 and Lung Cancer
3
GJA1 6q22.31 HSS, CMDR, CX43, EKVP, GJAL, ODDD, AVSD3, HLHS1 -GJA1 and Lung Cancer
3
RTEL1 20q13.33 NHL, RTEL, DKCA4, DKCB5, PFBMFT3, C20orf41 -RTEL1 and Lung Cancer
3
KLF5 13q22.1 CKLF, IKLF, BTEB2 -KLF5 and Lung Cancer
3
ING2 4q35.1 ING1L, p33ING2 -ING2 and Lung Cancer
3
ROCK2 2p24 ROCK-II -ROCK2 and Lung Cancer
3
PTK7 6p21.1-p12.2 CCK4, CCK-4 -PTK7 and Lung Cancer
3
REV1 2q11.1-q11.2 REV1L -REV1 and Lung Cancer
3
NNAT 20q11.23 Peg5 -NNAT and Lung Cancer
3
PBRM1 3p21.1 PB1, BAF180 -PBRM1 and Lung Cancer
3
S100A10 1q21.3 42C, P11, p10, GP11, ANX2L, CAL1L, CLP11, Ca[1], ANX2LG -S100A10 and Lung Cancer
3
LAMB3 1q32.2 AI1A, LAM5, LAMNB1, BM600-125KDA -LAMB3 and Lung Cancer
3
MSLN 16p13.3 MPF, SMRP -MSLN and Lung Cancer
3
CX3CL1 16q21 NTN, NTT, CXC3, CXC3C, SCYD1, ABCD-3, C3Xkine, fractalkine, neurotactin -CX3CL1 and Lung Cancer
3
RAD17 5q13.2 CCYC, R24L, RAD24, HRAD17, RAD17SP -RAD17 and Lung Cancer
3
BAG3 10q26.11 BIS, MFM6, BAG-3, CAIR-1 -BAG3 and Lung Cancer
3
HOXB7 17q21.32 HOX2, HOX2C, HHO.C1, Hox-2.3 -HOXB7 and Lung Cancer
3
IL17A 6p12.2 IL17, CTLA8, IL-17, CTLA-8, IL-17A -IL17A and Lung Cancer
3
TNFSF13 17p13.1 APRIL, CD256, TALL2, ZTNF2, TALL-2, TNLG7B, TRDL-1, UNQ383/PRO715 -TNFSF13 and Lung Cancer
3
POLI 18q21.2 RAD30B, RAD3OB -POLI and Lung Cancer
3
TBX21 17q21.32 TBET, T-PET, T-bet, TBLYM -TBX21 and Lung Cancer
3
DAB2IP 9q33.2 AIP1, AIP-1, AF9Q34, DIP1/2 -DAB2IP and Lung Cancer
3
MT1G 16q13 MT1, MT1K -MT1G and Lung Cancer
3
MME 3q25.2 NEP, SFE, CD10, CALLA, CMT2T, SCA43 -MME and Lung Cancer
3
MEST 7q32.2 PEG1 -MEST and Lung Cancer
3
CBLB 3q13.11 Cbl-b, RNF56, Nbla00127 -CBLB and Lung Cancer
3
YWHAZ 8q22.3 HEL4, YWHAD, KCIP-1, HEL-S-3, HEL-S-93, 14-3-3-zeta -YWHAZ and Lung Cancer
3
HSD11B1 1q32.2 HDL, 11-DH, HSD11, HSD11B, HSD11L, CORTRD2, SDR26C1, 11-beta-HSD1 -HSD11B1 and Lung Cancer
2
VTI1A 10q25.2 MMDS3, MVti1, VTI1RP2, Vti1-rp2 -VTI1A and Lung Cancer
2
THBS2 6q27 TSP2 -THBS2 and Lung Cancer
2
EPHB3 3q27.1 EK2, ETK2, HEK2, TYRO6 -EPHB3 and Lung Cancer
2
BRD3 9q34.2 ORFX, RING3L -BRD3 and Lung Cancer
2
CD3D 11q23.3 T3D, IMD19, CD3-DELTA -CD3D and Lung Cancer
2
GOPC 6q22.1 CAL, FIG, PIST, GOPC1, dJ94G16.2 -GOPC and Lung Cancer
2
SPRR1A 1q21.3 SPRK -SPRR1A and Lung Cancer
2
LRP1 12q13.3 APR, LRP, A2MR, CD91, APOER, LRP1A, TGFBR5, IGFBP3R -LRP1 and Lung Cancer
2
SACS 13q12.12 SPAX6, ARSACS, DNAJC29, PPP1R138 -SACS and Lung Cancer
2
PPP2CA 5q31.1 RP-C, PP2Ac, PP2CA, PP2Calpha -PPP2CA and Lung Cancer
2
PTGER4 5p13.1 EP4, EP4R -PTGER4 and Lung Cancer
2
HHIP 4q31.21 HIP -HHIP and Lung Cancer
2
TPM1 15q22.2 CMH3, TMSA, CMD1Y, LVNC9, C15orf13, HEL-S-265, HTM-alpha -TPM1 and Lung Cancer
2
SRPX Xp11.4 DRS, ETX1, SRPX1, HEL-S-83p -SRPX and Lung Cancer
2
PDE4DIP 1q21.2 MMGL, CMYA2 -PDE4DIP and Lung Cancer
2
PDCD5 19q13.11 TFAR19 -PDCD5 and Lung Cancer
2
MIR125A 19q13.41 MIRN125A, mir-125a, miRNA125A -MIR125A and Lung Cancer
2
PCM1 8p22 PTC4, RET/PCM-1 -PCM1 and Lung Cancer
2
ATIC 2q35 PURH, AICAR, AICARFT, IMPCHASE, HEL-S-70p -ATIC and Lung Cancer
2
HAS3 16q22.1 -HAS3 and Lung Cancer
2
MMP8 11q22.2 HNC, CLG1, MMP-8, PMNL-CL -MMP8 and Lung Cancer
2
ALOX5 10q11.21 5-LO, 5LPG, LOG5, 5-LOX -ALOX5 and Lung Cancer
2
HOXB3 17q21.32 HOX2, HOX2G, Hox-2.7 -HOXB3 and Lung Cancer
2
MAFG 17q25.3 hMAF -MAFG and Lung Cancer
2
PTPRH 19q13.42 SAP1, R-PTP-H -PTPRH and Lung Cancer
2
GAS7 17p13.1 -GAS7 and Lung Cancer
2
RRM2B 8q22.3 P53R2, MTDPS8A, MTDPS8B -RRM2B and Lung Cancer
2
PLAT 8p11.21 TPA, T-PA -PLAT and Lung Cancer
2
AKAP9 7q21.2 LQT11, PRKA9, AKAP-9, CG-NAP, YOTIAO, AKAP350, AKAP450, PPP1R45, HYPERION, MU-RMS-40.16A -AKAP9 and Lung Cancer
2
RIN1 11q13.2 -RIN1 and Lung Cancer
2
CHAT 10q11.23 CMS6, CMS1A, CMS1A2, CHOACTASE -CHAT and Lung Cancer
2
MIR1258 2q31.3 MIRN1258, mir-1258, hsa-mir-1258 -MicroRNA miR-1258 and Lung Cancer
2
ASAH1 8p22 AC, PHP, ASAH, PHP32, ACDase, SMAPME -ASAH1 and Lung Cancer
2
ST5 11p15.4 HTS1, p126, DENND2B -ST5 and Lung Cancer
2
RARRES3 11q12.3 RIG1, TIG3, HRSL4, HRASLS4, PLA1/2-3 -RARRES3 and Lung Cancer
2
TPM4 19p13.12-p13.11 HEL-S-108 -TPM4 and Lung Cancer
2
RCVRN 17p13.1 RCV1 -RCVRN and Lung Cancer
2
STC1 8p21.2 STC -STC1 and Lung Cancer
2
SLPI 20q13.12 ALP, MPI, ALK1, BLPI, HUSI, WAP4, WFDC4, HUSI-I -SLPI and Lung Cancer
2
NEMF 14q21.3 NY-CO-1, SDCCAG1 -NEMF and Lung Cancer
2
DKC1 Xq28 DKC, CBF5, DKCX, NAP57, NOLA4, XAP101 -DKC1 and Lung Cancer
2
CLTC 17q23.1 Hc, CHC, CHC17, CLH-17, CLTCL2 -CLTC and Lung Cancer
2
TLR7 Xp22.2 TLR7-like -TLR7 and Lung Cancer
2
FRAT1 10q24.1 -FRAT1 and Lung Cancer
2
ARL11 13q14.2 ARLTS1 -ARL11 and Lung Cancer
2
KDM5A 12p13.33 RBP2, RBBP2, RBBP-2 -KDM5A and Lung Cancer
2
IL23R 1p31.3 -IL23R and Lung Cancer
2
KPNA2 17q24.2 QIP2, RCH1, IPOA1, SRP1alpha, SRP1-alpha -KPNA2 and Lung Cancer
2
CTSL 9q21.33 MEP, CATL, CTSL1 -CTSL and Lung Cancer
2
PPP1R3A 7q31.1 GM, PP1G, PPP1R3 -PPP1R3A and Lung Cancer
2
PTPRF 1p34.2 LAR, BNAH2 -PTPRF and Lung Cancer
2
SLC22A18 11p15.4 HET, ITM, BWR1A, IMPT1, TSSC5, ORCTL2, BWSCR1A, SLC22A1L, p45-BWR1A -SLC22A18 and Lung Cancer
2
MUC7 4q13.3 MG2 -MUC7 and Lung Cancer
2
ADGRB1 8q24.3 BAI1, GDAIF -BAI1 and Lung Cancer
2
HTRA1 10q26.13 L56, HtrA, ARMD7, ORF480, PRSS11, CARASIL, CADASIL2 -HTRA1 and Lung Cancer
2
ARHGEF5 7q35 P60, TIM, GEF5, TIM1 -ARHGEF5 and Lung Cancer
2
CXCL11 4q21.1 IP9, H174, IP-9, b-R1, I-TAC, SCYB11, SCYB9B -CXCL11 and Lung Cancer
2
GRASP 12q13.13 TAMALIN -GRASP and Lung Cancer
2
OCLN 5q13.2 BLCPMG, PPP1R115 -OCLN and Lung Cancer
2
RAC3 17q25.3 -RAC3 and Lung Cancer
2
C2orf44 2p23.3 WDCP, PP384 -C2orf44 and Lung Cancer
1
PECAM1 17q23.3 CD31, PECA1, GPIIA', PECAM-1, endoCAM, CD31/EndoCAM -PECAM1 and Lung Cancer
1
PLCD1 3p22.2 NDNC3, PLC-III -PLCD1 and Lung Cancer
1
PNN 14q21.1 DRS, DRSP, SDK3, memA -PNN and Lung Cancer
1
ZNRF3 22q12.1 RNF203, BK747E2.3 -ZNRF3 and Lung Cancer
1
ENDOU 12q13.1 P11, PP11, PRSS26 -ENDOU and Lung Cancer
1
KMT2A 11q23.3 HRX, MLL, MLL1, TRX1, ALL-1, CXXC7, HTRX1, MLL1A, WDSTS -KMT2A and Lung Cancer
1
HERPUD1 16q13 SUP, HERP, Mif1 -HERPUD1 and Lung Cancer
1
GPHN 14q23.3-q24.1 GPH, GEPH, HKPX1, GPHRYN, MOCODC -GPHN and Lung Cancer
1
CEACAM3 19q13.2 CEA, CGM1, W264, W282, CD66D -CEACAM3 and Lung Cancer
1
MIR1271 5q35.2 MIRN1271, hsa-mir-1271 -MIRN1271 microRNA, human and Lung Cancer
1
VIPR2 7q36.3 VPAC2, VPAC2R, VIP-R-2, VPCAP2R, PACAP-R3, DUP7q36.3, PACAP-R-3, C16DUPq36.3 -VIPR2 and Lung Cancer
1
IGFBP4 17q21.2 BP-4, IBP4, IGFBP-4, HT29-IGFBP -IGFBP4 and Lung Cancer
1
CBLC 19q13.32 CBL-3, RNF57, CBL-SL -CBLC and Lung Cancer
1
CTNND1 11q12.1 CAS, p120, CTNND, P120CAS, P120CTN, p120(CAS), p120(CTN) -CTNND1 and Lung Cancer
1
TNFRSF6B 20q13.33 M68, TR6, DCR3, M68E, DJ583P15.1.1 -TNFRSF6B Amplification in Lung Cancer
1
CHCHD7 8q12.1 COX23 -CHCHD7 and Lung Cancer
1
RXRB 6p21.3 NR2B2, DAUDI6, RCoR-1, H-2RIIBP -RXRB and Lung Cancer
1
PRIM1 12q13 p49 -PRIM1 and Lung Cancer
1
SNRPE 1q32.1 SME, Sm-E, HYPT11, snRNP-E -SNRPE and Lung Cancer
1
NR0B2 1p36.11 SHP, SHP1 -NR0B2 and Lung Cancer
1
RXRG 1q23.3 RXRC, NR2B3 -RXRG and Lung Cancer
1
TRD 14q11.2 TCRD, TRD@, TCRDV1 -TRD and Lung Cancer
1
ARHGAP26 5q31.3 GRAF, GRAF1, OPHN1L, OPHN1L1 -ARHGAP26 and Lung Cancer
1
MIR1297 13q14.3 MIRN1297, mir-1297, hsa-mir-1297 -MicroRNA miR-1297 and Lung Cancer
1
MIR10B 2q31.1 MIRN10B, mir-10b, miRNA10B, hsa-mir-10b -MIR10B and Lung Cancer
1
IDO1 8p11.21 IDO, INDO, IDO-1 -IDO1 and Lung Cancer
1
ANXA5 4q27 PP4, ANX5, ENX2, RPRGL3, HEL-S-7 -ANXA5 and Lung Cancer
1
SERPINB2 18q21.33-q22.1 PAI, PAI2, PAI-2, PLANH2, HsT1201 -SERPINB2 and Lung Cancer
1
BANP 16q24.2 BEND1, SMAR1, SMARBP1 -BANP and Lung Cancer
1
PCSK7 11q23.3 LPC, PC7, PC8, SPC7 -PCSK7 and Lung Cancer
1
MIR1301 2 MIRN1301, mir-1301, hsa-mir-1301 -MicroRNA miR-1301 and Lung Cancer
1
PATZ1 22q12.2 ZSG, MAZR, PATZ, RIAZ, ZBTB19, ZNF278, dJ400N23 -PATZ1 and Lung Cancer
1
TUBE1 6q21 TUBE, dJ142L7.2 -TUBE1 and Lung Cancer
SPRR2C 1q21.3 -SPRR2C and Lung Cancer
AVPR1B 1q32.1 V1bR, AVPR3 -AVPR1B and Lung Cancer
SPRR2A 1q21.3 -SPRR2A and Lung Cancer
NR3C2 4q31.23 MR, MCR, MLR, NR3C2VIT -NR3C2 and Lung Cancer
PDLIM4 5q31.1 RIL -PDLIM4 and Lung Cancer
ANXA8 10q11.22 ANX8, CH17-360D5.2 -ANXA8 and Lung Cancer
SPRR2B 1q21.3 -SPRR2B and Lung Cancer
PPP2CB 8p12 PP2CB, PP2Abeta -PPP2CB and Lung Cancer

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

Latest Publications

Sun Y, Ling C
Analysis of the long non-coding RNA LINC01614 in non-small cell lung cancer.
Medicine (Baltimore). 2019; 98(30):e16437 [PubMed] Related Publications
The aim of this study was toexplore the long non-coding RNA (lncRNA) expression pattern of non-small cell lung cancer (NSCLC) on a genome-wide scale and investigate their potential biological function in NSCLC.LncRNAs were investigated in 6 pairs of NSCLC and matched adjacent non-tumor lung tissues (NTL) by microarray. A validation cohort was obtained from The Cancer Genome Atlas (TCGA) database and the effect of LINC01614 on diagnosis and prognosis in NSCLC was analyzed. Gene set enrichment analysis (GSEA) was used to predict the potential molecular mechanism of LINC01614, one identified lncRNA.A total of 1392 differentially expressed lncRNAs were identified. LINC01614 was the most aberrantly expressed lncRNA in NSCLC compared with NTL. We confirmed the significantly upregulated LINC01614 in NSCLC patients from TCGA database. Furthermore, in TCGA database, LINC01614 was significantly upregulated in both adenocarcinoma and squamous cell carcinoma. And high expression of LINC01614 indicated poor overall survival of NSCLC patients. A sensitivity of 93% was calculated conditional on a high specificity of 95% for the discrimination of NSCLC tissues from normal tissues. Furthermore, the expression levels of LINC01614 were associated with the stage of tumor, but had no relationship with age and sex. Additionally, GSEA found that LINC01614 might be involved in TGF-β-, P53-, IGF-IR-mediated, Wnt and RTK/Ras/MAPK signaling pathways.lncRNAs may play key roles in the development of NSCLC. LINC01614 is the most aberrantly expressed lncRNA in NSCLC tissues in our experiment and is also significantly differentially expressed in NSCLC patients from TCGA database. LINC01614 could be a prognostic indicator and has the potential to be a diagnostic biomarker of NSCLC.

Yang X, Li X, Quan X, et al.
Association Between Two Polymorphisms in the Promoter Region of miR-143/miR-145 and the Susceptibility of Lung Cancer in Northeast Chinese Nonsmoking Females.
DNA Cell Biol. 2019; 38(8):814-823 [PubMed] Related Publications
Lung cancer is known to cause high mortality and morbidity. The study aimed to explore the association between rs3733845 and rs3733846 polymorphisms in the promoter region of miR-143/145 and the risk of lung cancer among 575 nonsmoking cases and 575 cancer-free controls in a Chinese female population. We genotyped two single nucleotide polymorphisms (SNPs) in the promoter region of miR-143/145 in 575 cases and 575 controls using TaqMan allelic discrimination method. Logistic regression analysis was conducted to assess the association between polymorphisms in the promoter of miR-143/miR-145 and risk of lung cancer females. Crossover analysis was used to explore the interaction between the two SNPs and environmental risk factors (cooking oil fume exposure and passive smoking exposure). The results showed that both rs3733845 and rs3733846 polymorphisms were associated with an increased lung adenocarcinoma risk in dominant model (adjusted odds ratio [OR] = 1.329, 95% confidence intervals [CIs] = 1.026-1.723,

Naghizadeh S, Mohammadi A, Baradaran B, Mansoori B
Overcoming multiple drug resistance in lung cancer using siRNA targeted therapy.
Gene. 2019; 714:143972 [PubMed] Related Publications
Among cancers, lung cancer is the most morbidity and mortality disease that is remaining the fatalist. Generally, there are multiple treatment procedures for lung cancer, such as surgery, immunotherapy, radiotherapy and chemotherapy. There is, therefore, an urgent need for more specified and efficient methods for treatment of lung cancer such as RNAi, which in combination with traditional therapies could silence genes that are involved in the drug resistance. These genes may either be motivators of apoptosis inhibition, EMT and DNA repair system promoters or a member of intracellular signaling pathways, such as JAK/STAT, RAS/RAF/MEK, PI3K/AKT, NICD, B-catenin/TCF/LEF and their stimulator receptors including IGFR, EGFR, FGFR, VEGFR, CXCR4, MET, INTEGRINS, NOTCH1 and FRIZZLED, so could be considered as appropriate targets. In current review, the results of multiple studies which have employed drug application after one specific gene silencing or more than one gene from distinct pathways also simultaneous drug and RNAi usage in vitro and in vivo in lung cancer were summarized.

Qian Z, Yang J, Liu H, et al.
The miR-1204 regulates apoptosis in NSCLC cells by targeting DEK.
Folia Histochem Cytobiol. 2019; 57(2):64-73 [PubMed] Related Publications
INTRODUCTION: This study endeavors to analyze the effects of miR-1204 on the expression of DEK oncogene in non-small cell lung cancer (NSCLC) cell lines and to study the molecular mechanisms of these effects.
MATERIAL AND METHODS: The miR-1204 mimics and inhibitors were transfected into the (A549 and SPC) NSCLC cells. Then the mRNA levels, cell viability, apoptosis rate, morphology and caspase activity were determined. The expression of apoptosis-related proteins Bcl-2 and Bax was also analyzed.
RESULTS: In NSCLC cell lines (A549 and SPC), DEK mRNA levels were down-regulated in miR-1204 overex-pression group. In miR-1204 inhibition group, the expression of DEK mRNA showed an opposite trend. The overexpression of miR-1204 increases the apoptosis rate in NSCLC cells. The Bcl-2 levels in the miR-1204 over-expression group were decreased, while the Bax level was increased. In the miR-1204 inhibition group, expression of Bcl-2 and Bax showed opposite trends. Cell staining revealed cell's morphological changes; the apoptosis in the miR-1204 overexpression group revealed significant morphological features, such as brighter nuclei and nu-clear condensation. Results indicated a typical characteristic of apoptosis in the miR-1204 overexpression group. Caspase-9 and Caspase-3 were involved in the apoptosis pathway, which was mediated by miR-1204 and DEK.
CONCLUSIONS: The miR-1204 induces apoptosis of NSCLC cells by inhibiting the expression of DEK. The mech-anism of apoptosis involves down-regulation of Bcl-2 and up-regulation of Bax expression. Moreover, the apoptosis was mediated by mitochondria-related caspase 9/3 pathway.

Kage H, Kohsaka S, Shinozaki-Ushiku A, et al.
Small lung tumor biopsy samples are feasible for high quality targeted next generation sequencing.
Cancer Sci. 2019; 110(8):2652-2657 [PubMed] Free Access to Full Article Related Publications
Next-generation sequencing (NGS) has been implemented in clinical oncology to analyze multiple genes and to guide therapy. In patients with advanced lung cancer, small biopsies such as computed tomography-guided needle biopsy (CTNB), endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) and transbronchial biopsy (TBB) are less invasive and are preferable to resection to make a pathological diagnosis. However, the quality of DNA/RNA and NGS from small lung tumor biopsy samples is unknown. Between April 2017 and March 2018, 107 consecutive samples were obtained from thoracic tumors or metastatic sites for targeted NGS analysis. Fifteen samples were obtained through CTNB, 11 through EBUS-TBNA, 11 through TBB and 70 through surgical resection. All samples were formalin-fixed and paraffin-embedded. DNA and RNA quality was measured using the ddCq method and the percentage of RNA fragments above 200 nucleotides (DV200), respectively. Our custommade probes were designed to capture exon sequences of 464 cancer-related genes and transcripts of 463 genes. DNA and RNA yield from the 3 biopsy methods were similar, and less than the yield obtained from resected samples. The quality of DNA and RNA was similar across all methods. Overall, 12 of 15 CTNB samples (80%), all 11 EBUS-TBNA samples, and 9 of 11 TBB samples (82%) underwent successful NGS assays from DNA. NGS analysis from RNA was successful in all 12 CTNB samples, 9 of 11 EBUS-TBNA samples (82%), and 8 of 11 TBB samples (73%). CTNB, EBUS-TBNA and TBB mostly resulted in adequate DNA and RNA quality and enabled high-quality targeted NGS analysis.

Chen H, Chong W, Teng C, et al.
The immune response-related mutational signatures and driver genes in non-small-cell lung cancer.
Cancer Sci. 2019; 110(8):2348-2356 [PubMed] Free Access to Full Article Related Publications
Immune checkpoint blockade (ICB) therapy has achieved remarkable clinical benefit in non-small-cell lung cancer (NSCLC), but our understanding of biomarkers that predict the response to ICB remain obscure. Here we integrated somatic mutational profile and clinicopathologic information from 113 NSCLC patients treated by ICB (CTLA-4/PD-1). High tumor mutation burden (TMB) and neoantigen burden were identified significantly associated with improved efficacy in NSCLC immunotherapy. Furthermore, we identified apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like (APOBEC) mutational signature was markedly associated with responding of ICB therapy (log-rank test, P = .001; odds ratio (OR), 0.18 [95% CI, 0.06-0.50], P < .001). The association with progression-free survival remained statistically significant after controlling for age, sex, histological type, smoking, PD-L1 expression, hypermutation, smoking signature and mismatch repair (MMR) (HR, 0.30 [95% CI, 0.12-0.75], P = .010). Combined high TMB with APOBEC signature preferably predict immunotherapy responders in NSCLC cohort. The CIBERSORT algorithm revealed that high APOBEC mutational activity samples were associated with increased infiltration of CD4 memory activated T cells, CD8

Hill A, Gupta R, Zhao D, et al.
Targeted Therapies in Non-small-Cell Lung Cancer.
Cancer Treat Res. 2019; 178:3-43 [PubMed] Related Publications
The treatment landscape for non-small-cell lung cancer (NSCLC) has dramatically shifted over the past two decades. Targeted or precision medicine has primarily been responsible for this shift. Older paradigms of treating metastatic NSCLC with cytotoxic chemotherapy, while still important, have given way to evaluating tumor tissues for specific driver mutations that can be treated with targeted agents. Patients treated with targeted agents frequently have improved progression-free survival and overall survival compared to patients without a targetable driver mutation, highlighting the clinical benefit of precision medicine. In this chapter, we explore the historic landmark trials, the current state of the field, and potential future targets under investigation, in this exciting, rapidly evolving discipline of precision medicine in lung cancer.

Davalos V, Esteller M
Disruption of Long Noncoding RNAs Targets Cancer Hallmark Pathways in Lung Tumorigenesis.
Cancer Res. 2019; 79(12):3028-3030 [PubMed] Related Publications
Advances in high-throughput genomic and epigenomic technologies have revealed the tremendous complexity of the transcriptional landscape. Beyond protein-coding RNAs (derived from only ∼1.5% of the genome), noncoding RNAs (ncRNA) are emerging as versatile key regulators of gene information involved in multiple major biological processes. Accordingly, deregulation of ncRNA expression has been associated with multiple diseases, including cancer. In this issue of

Zhong R, Chen Q, Zhang X, et al.
Association between methylenetetrahydrofolate reductase (MTHFR) polymorphisms and lung cancer risk in Chinese people: An updated meta-analysis.
Medicine (Baltimore). 2019; 98(24):e16037 [PubMed] Free Access to Full Article Related Publications
BACKGROUND: The association between Methylenetetrahydrofolate Reductase (MTHFR) polymorphisms and lung cancer risk in Chinese people has been widely explored; however, the results remain controversial. Thus, we conducted a meta-analysis to investigate the association between MTHFR gene polymorphisms and susceptibility to lung cancer in Chinese people.
OBJECTIVE: We performed an updated meta-analysis to investigate the association between MTHFR gene polymorphisms and susceptibility to lung cancer in Chinese people.
METHODS: PubMed, EMBASE, WANFANG database, and CNKI were searched to collect eligible articles. The associations of MTHFR gene polymorphism with lung cancer risk were evaluated by calculating the pooled odds ratios (ORs) and the 95% confidence interval (CI). The dominant, recessive, heterozygous, homozygous, and allelic genetic models were used to calculate the combined ORs.
RESULTS: A total of 16 eligible studies were identified in the present meta-analysis. Evidence from the pooled results indicated a significant association between the MTHFR C677T polymorphism and lung cancer susceptibility in Chinese people under the dominant, recessive, homozygous and allelic genetic models (T vs C: OR = 1.252, 95% CI, 1.090-1.437; TT vs CC: OR = 1.741, 95% CI, 1.252-2.420. (TT + CT) vs CC: OR = 1.227, 95% CI, 1.030-1.426. TT vs (CT + CC): OR = 1.606, 95% CI, 1.207-2.137).
CONCLUSION: The present updated meta-analysis demonstrated that the MTHFR C677T polymorphism was significantly associated with susceptibility to lung cancer in Chinese people. Additional case-control studies with large sample sizes are needed to validate our findings.

Jones GG, Del Río IB, Sari S, et al.
SHOC2 phosphatase-dependent RAF dimerization mediates resistance to MEK inhibition in RAS-mutant cancers.
Nat Commun. 2019; 10(1):2532 [PubMed] Free Access to Full Article Related Publications
Targeted inhibition of the ERK-MAPK pathway, upregulated in a majority of human cancers, has been hindered in the clinic by drug resistance and toxicity. The MRAS-SHOC2-PP1 (SHOC2 phosphatase) complex plays a key role in RAF-ERK pathway activation by dephosphorylating a critical inhibitory site on RAF kinases. Here we show that genetic inhibition of SHOC2 suppresses tumorigenic growth in a subset of KRAS-mutant NSCLC cell lines and prominently inhibits tumour development in autochthonous murine KRAS-driven lung cancer models. On the other hand, systemic SHOC2 ablation in adult mice is relatively well tolerated. Furthermore, we show that SHOC2 deletion selectively sensitizes KRAS- and EGFR-mutant NSCLC cells to MEK inhibitors. Mechanistically, SHOC2 deletion prevents MEKi-induced RAF dimerization, leading to more potent and durable ERK pathway suppression that promotes BIM-dependent apoptosis. These results present a rationale for the generation of SHOC2 phosphatase targeted therapies, both as a monotherapy and to widen the therapeutic index of MEK inhibitors.

Chaszczewska-Markowska M, Kosacka M, Chryplewicz A, et al.
Anticancer Res. 2019; 39(6):3269-3272 [PubMed] Related Publications
BACKGROUND/AIM: Although genetic factors are presumed to account only for a part of the inter-individual variation in lung cancer susceptibility, the results are conflicting and there are no data available regarding the Polish population. We, therefore, performed a case-control study to investigate the association of seven selected single nucleotide polymorphisms (SNPs), in genes coding for excision repair cross-complimentary group 1 (ERCC1: rs11615, rs3212986, rs2298881), nuclear factor ĸB (NFKB2: rs7897947, rs12769316), bone morphogenetic protein 4 (BMP4: rs1957860), complement receptor 1 (CR1: rs7525160) and del/ins polymorphism in the family hypoxia inducible factor 2 gene (EGLN2: rs10680577), with non-small cell lung cancer (NSCLC) risk.
MATERIALS AND METHODS: Real-time PCR with melting curve analysis was used for genotyping of NSCLC patients and healthy individuals of Polish origin.
RESULTS: The ERCC1 rs11615 T allele and rs3212986 GG homozygosity were found to be associated with a higher risk of developing NSCLC. In addition, NFKB2 rs12769316 GG homozygosity was more frequently detected among male patients than controls, while no significant differences were found between the five polymorphisms.
CONCLUSION: ERCC1 polymorphisms may affect NSCLC risk in the Polish population, while the NFKB2 variant may be a possible marker of the disease in males.

Lu G, Zhang Y
MicroRNA-340-5p suppresses non-small cell lung cancer cell growth and metastasis by targeting ZNF503.
Cell Mol Biol Lett. 2019; 24:34 [PubMed] Free Access to Full Article Related Publications
Background: MicroRNAs (miRNAs) have been reported to play crucial roles in cancer cell processes, including proliferation, metastasis and cell cycle progression. We aimed to identify miRNAs that could act as suppressors of cell growth and invasion in non-small cell lung cancer (NSCLC).
Methods: Fifteen paired NSCLC tissue samples and pericarcinomatous normal tissues were collected and preserved in liquid nitrogen. The expression levels of miR-340-5p and ZNF503 mRNA were detected using a qPCR assay. The transfection of plasmids was conducted using Lipofectamine 3000 according to the manufacturer's protocol. Cell proliferation was determined using a CCK-8 assay. The protein levels of endothelial-mesenchymal transition markers were measured using a western blot assay. Cell invasive ability was evaluated using a transwell assay. TargetScan was used to predict targets of miR-340. A dual luciferase reporter assay was performed to confirm a potential direct interaction between miR-340-5p and ZNF503.
Results: The expression level of miR-340-5p was frequently found to be lower in NSCLC tissues than in matched pericarcinomatous normal tissues. Overexpression of miR-340-5p significantly inhibited the proliferation and invasion NCI-H1650 (a NSCLC cell line), while inhibition of miR-340-5p stimulated cell growth. Using TargetScan, we predicted that ZNF503 could be a target of miR-340-5p. Further mechanistic studies demonstrated that the forced expression of ZNF503 could partially abrogate the miR-340-5p-mediated decrease in NCI-H1650 cell viability and invasion, suggesting that miR-340-5p suppressed cell growth and invasion in a ZNF503-dependent manner.
Conclusion: Our findings indicate that miR-340-5p inhibits NCI-H1650 cell proliferation and invasion by directly targeting ZNF503 and that miR-340-5p can serve as a potential therapeutic target for treating NSCLC.

Wei W, Dong Z, Gao H, et al.
MicroRNA-9 enhanced radiosensitivity and its mechanism of DNA methylation in non-small cell lung cancer.
Gene. 2019; 710:178-185 [PubMed] Related Publications
In order to improve the therapeutic effect of non-small cell lung cancer (NSCLC), it is critical to combine radiation and gene therapy. Our study found that the activation of microRNA-9 (miR-9) conferred ionizing radiation (IR) sensitivity in cancer cells. Furthermore, increased microRNA-9 promoter methylation level was observed after IR. Our study combined the IR and microRNA-9 overexpression treatment which leads to a significant enhancement in the therapeutic efficiency in lung cancer both in vitro and in vivo. Therefore, it is plausible that microRNA-9 can be used as a novel therapeutic strategy of NSCLC. MTT assay was performed to detect the effect of microRNA-9 on the survival and growth of NSCLC cells. Flow cytometry results showed that microRNA-9 enhanced the apoptosis of NSCLC cells. Wound healing assay found that microRNA-9 can inhibit the migration of NSCLC cells and enhance the effect of radiation on the migration of NSCLC cells. In addition, bisulfate sequencing PCR was performed to analyze the methylation status of the microRNA-9 promoter. In order to determine the effect of microRNA-9 and its promoter methylation status on proliferation and radio-sensitivity in vivo, a subcutaneous tumor formation assay in nude mice was performed. Results have shown that microRNA-9 overexpression increased the radiosensitivity of A549 cells by inhibiting cell activity and migration, and by increasing apoptosis. In addition, the promoter methylation status of the microRNA-9 gene increased in response to ionizing radiation. Our study demonstrated that microRNA-9 enhanced radiosensitivity in NSCLC and this effect is highly regulated by its promoter methylation status. These results will help to clarify regulatory mechanisms of radiation resistance thus stimulate new methods for improving radiotherapy for NSCLC.

Kim Y, Shiba-Ishii A, Ramirez K, et al.
Carcinogen-induced tumors in SFN-transgenic mice harbor a characteristic mutation spectrum of human lung adenocarcinoma.
Cancer Sci. 2019; 110(8):2431-2441 [PubMed] Free Access to Full Article Related Publications
The landscape of genetic alterations in disease models such as transgenic mice or mice with carcinogen-induced tumors has provided a huge amount of information that has shed light on the process of tumorigenesis in human non-small-cell lung cancer (NSCLC). We have previously identified stratifin (SFN) as a potent oncogene, and generated SFN-transgenic (Tg-SPC-SFN

Tian L, Dong X, Freytag S, et al.
Benchmarking single cell RNA-sequencing analysis pipelines using mixture control experiments.
Nat Methods. 2019; 16(6):479-487 [PubMed] Related Publications
Single cell RNA-sequencing (scRNA-seq) technology has undergone rapid development in recent years, leading to an explosion in the number of tailored data analysis methods. However, the current lack of gold-standard benchmark datasets makes it difficult for researchers to systematically compare the performance of the many methods available. Here, we generated a realistic benchmark experiment that included single cells and admixtures of cells or RNA to create 'pseudo cells' from up to five distinct cancer cell lines. In total, 14 datasets were generated using both droplet and plate-based scRNA-seq protocols. We compared 3,913 combinations of data analysis methods for tasks ranging from normalization and imputation to clustering, trajectory analysis and data integration. Evaluation revealed pipelines suited to different types of data for different tasks. Our data and analysis provide a comprehensive framework for benchmarking most common scRNA-seq analysis steps.

Zhu D, Zhou J, Liu Y, et al.
LncRNA TP73-AS1 is upregulated in non-small cell lung cancer and predicts poor survival.
Gene. 2019; 710:98-102 [PubMed] Related Publications
The present study was carried out to investigate the role of lncRNA TP73-AS1 in non-small cell lung cancer (NSCLC). We found that TP73-AS1 was upregulated in tumor tissues than in non-tumor tissues of NSCLC patients, and high expression levels of TP73-AS1 predicted poor survival. MiR-21 was also upregulated in tumor tissues and positively correlated with TP73-AS1. TP73-AS1 overexpression led to miR-21 upregulation, while miR-21 overexpression failed to affect TP73-AS1. TP73-AS1 and miR-21 overexpression caused the accelerated invasion and migration of NSCLC cells. However, TP73-AS1 overexpression failed to affect cell proliferation. Therefore, TP73-AS1 may upregulate miR-21 to promote NSCLC cell migration and invasion.

Shao L, Zuo X, Yang Y, et al.
The inherited variations of a p53-responsive enhancer in 13q12.12 confer lung cancer risk by attenuating TNFRSF19 expression.
Genome Biol. 2019; 20(1):103 [PubMed] Free Access to Full Article Related Publications
BACKGROUND: Inherited factors contribute to lung cancer risk, but the mechanism is not well understood. Defining the biological consequence of GWAS hits in cancers is a promising strategy to elucidate the inherited mechanisms of cancers. The tag-SNP rs753955 (A>G) in 13q12.12 is highly associated with lung cancer risk in the Chinese population. Here, we systematically investigate the biological significance and the underlying mechanism behind 13q12.12 risk locus in vitro and in vivo.
RESULTS: We characterize a novel p53-responsive enhancer with lung tissue cell specificity in a 49-kb high linkage disequilibrium block of rs753955. This enhancer harbors 3 highly linked common inherited variations (rs17336602, rs4770489, and rs34354770) and six p53 binding sequences either close to or located between the variations. The enhancer effectively protects normal lung cell lines against pulmonary carcinogen NNK-induced DNA damages and malignant transformation by upregulating TNFRSF19 through chromatin looping. These variations significantly weaken the enhancer activity by affecting its p53 response, especially when cells are exposed to NNK. The effect of the mutant enhancer alleles on TNFRSF19 target gene in vivo is supported by expression quantitative trait loci analysis of 117 Chinese NSCLC samples and GTEx data. Differentiated expression of TNFRSF19 and its statistical significant correlation with tumor TNM staging and patient survival indicate a suppressor role of TNFRSF19 in lung cancer.
CONCLUSION: This study provides evidence of how the inherited variations in 13q12.12 contribute to lung cancer risk, highlighting the protective roles of the p53-responsive enhancer-mediated TNFRSF19 activation in lung cells under carcinogen stress.

Hu Z, Wang X, Yang Y, et al.
MicroRNA expression profiling of lung adenocarcinoma in Xuanwei, China: A preliminary study.
Medicine (Baltimore). 2019; 98(21):e15717 [PubMed] Free Access to Full Article Related Publications
MicroRNAs (miRNAs) have been proved to be related to the development and progression of lung cancer. However, the expression signatures of miRNAs in lung adenocarcinoma in Xuanwei are not yet clear. The current study aimed to identify the potential miRNA profiles in lung adenocarcinoma in Xuanwei by microarray.The miRNA profiles in 24 lung adenocarcinoma and paired non-tumor tissues in Xuanwei were ascertained by using the Exiqon miRCURY LNA microRNA Array (v.18.0). The results of the microarrays were further verified by quantitative real-time polymerase chain reaction (qRT-PCR) detection. Bioinformatics analysis was used to carry out the functional annotations of differentially expressed miRNAs.One hundred fifty five differentially expressed (≥2-fold change) miRNAs were identified (65 upregulated and 90 downregulated). QRT-PCR was used to validate the top 4 most upregulated and downregulated miRNAs, and the results were generally consisted with microarray. Furthermore, the differentially expressed miRNAs were significantly enriched in numerous common pathways that were bound up with cancer. The pathways included focal adhesion and signaling pathways, such as cyclic guanosine monophosphate -protein kinase G (cGMP-PKG) signaling pathways, mitogen-activated protein kinase (MAPK) signaling pathway, and Hippo signaling pathway, etc.Our study identified the potential miRNA profiles in lung adenocarcinoma in Xuanwei by microarray. These miRNAs might be used as biomarkers for diagnosis and/or prognosis for lung cancer in Xuanwei and therefore warrant further investigation. Further study is needed to reveal the potential role of these miRNAs in the carcinogenesis of XuanWei Lung Cancer (XWLC).

Hong MH, Kim HR, Ahn BC, et al.
Real-World Analysis of the Efficacy of Rebiopsy and
Yonsei Med J. 2019; 60(6):525-534 [PubMed] Free Access to Full Article Related Publications
PURPOSE: Standard treatment for cases of non-small cell lung cancer (NSCLC) exhibiting acquired drug resistance includes tumor rebiopsy, epidermal growth factor receptor (
MATERIALS AND METHODS: The present study used statistical models to evaluate data collected by the ASTRIS trial (NCT02474355) conducted at Yonsei Cancer Center, including the rebiopsy success rate, incidence of T790M mutations in collected tissue and plasma samples, and association of administered osimertinib treatment efficacy.
RESULTS: In a total of 188 screened patients, 112 underwent rebiopsy. An adequate tumor specimen was obtained in 95 of these patients, the greatest majority of whom (43.8%) were subjected to bronchoscopy. T790M mutations were detected in 53.3% of successfully EGFR-tested rebiopsy samples. A total of 88 patients received osimertinib treatment, and the objective response rate and median progression-free survival time was 44.3% and 32.7 weeks, respectively, among the treated patients overall, but 57.8% and 45.0 weeks, and 35.2% and 20.4 weeks among patients who exhibited T790M-positive tissue (n=45) and plasma (n=54) samples, respectively.
CONCLUSION: Approximately 60% of patients in the analyzed real-world cohort were eligible for tissue rebiopsy upon NSCLC progression. Osimertinib activity was higher in patients in whom T790M mutations were detected in tissues rather than in plasma samples.

Yang Q, Li J, Hu Y, et al.
MiR-218-5p Suppresses the Killing Effect of Natural Killer Cell to Lung Adenocarcinoma by Targeting SHMT1.
Yonsei Med J. 2019; 60(6):500-508 [PubMed] Free Access to Full Article Related Publications
PURPOSE: Lung adenocarcinoma (LA) is one of the major types of lung cancer. MicroRNAs (miRNAs) play an essential role in regulating responses of natural killer (NK) cells to cancer malignancy. However, the mechanism of miR-218-5p involved in the killing effect of NK cells to LA cells remains poorly understood.
MATERIALS AND METHODS: The expression of miR-218-5p was examined by quantitative real-time polymerase chain reaction (qRT-PCR). Serine hydroxymethyl transferase 1 (SHMT1) level was detected by qRT-PCR or western blots. Cytokines production of interferon-γ (IFN-γ) and tumor necrosis factor-α (TNF-α) were detected by ELISA. The killing effect of NK cells to LA cells was investigated using lactate dehydrogenase cytotoxicity assay kit. The interaction of miR-218-5p and SHMT1 was probed by luciferase activity assay. Xenograft model was established to investigate the killing effect of NK cells
RESULTS: miR-218-5p was enhanced and SHMT1 was inhibited in NK cells of LA patients, whereas stimulation of interleukin-2 (IL-2) reversed their abundances. Addition of miR-218-5p reduced IL-2-induced cytokines expression and cytotoxicity in NK-92 against LA cells. Moreover, SHMT1 was negatively regulated by miR-218-5p and attenuated miR-218-5p-mediated effect on cytotoxicity, IFN-γ and TNF-α secretion in IL-2-activated NK cells. In addition, miR-218-5p exhaustion inhibited tumor growth by promoting killing effect of NK cells.
CONCLUSION: miR-218-5p suppresses the killing effect of NK cells to LA cells by targeting SHMT1, providing a potential target for LA treatment by ameliorating NK cells function.

Wang X, Zhong D
[Advanced Research on Non-small Cell Lung Cancer with De Novo T790M Mutation].
Zhongguo Fei Ai Za Zhi. 2019; 22(5):324-328 [PubMed] Related Publications
With the development of sequencing technology, the detection rate of de novo T790M mutation is increasing. The emergence of the third generation of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) provide treatment opportunities. Secondary T790M mutation is often emphasized in clinic, but de novo T790M mutation is neglected. This review found that the incidence of de novo T790M mutation fluctuated greatly, which was mainly affected by sequencing techniques. The de novo T790M mutation is mainly low in mutation abundance, easy to combine with other gene changes, a poor predictor and prognostic factor and the efficacy of the first and second generation EGFR-TKIs is limited. The therapeutic value of osimertinib needs to be studied.
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Huang Z, Li S, Ma Y, et al.
[Expression of MiR-148b-3p in Lung Adenocarcinoma and Its Correlation with Prognosis].
Zhongguo Fei Ai Za Zhi. 2019; 22(5):306-311 [PubMed] Free Access to Full Article Related Publications
BACKGROUND: MiR-148b-3p is an important microRNA that has been reported to be significantly related to various types of cancer, but its role in lung adenocarcinoma remains elusive. The purpose of this study is to detect the expression level of miR-148b-3p in lung adenocarcinoma specimens, and to analyze its correlation with the clinicopathological features as well as the prognosis of patients with lung adenocarcinoma.
METHODS: A total of 123 tumor specimens from lung adenocarcinoma patients who underwent surgical resection in our department from January 2011 to December 2012 were collected. The expression of miR-148b-3p was detected by quantitative real-time PCR (qRT-PCR), and its correlation with clinicopathological features of patients with lung adenocarcinoma was analyzed. Multivariate Cox proportional hazard models were used to analyze independent predictors of overall survival in patients with lung adenocarcinoma. The overall survival (OS) of patients in miR-148b-3p high expression group and miR-148b-3p low expression group were estimated by means of the Kaplan-Meier method and were compared using the Log-rank test method.
RESULTS: Of the 123 patients with lung adenocarcinoma, 71 were in miR-148b-3p high expression group and 52 in low expression group. MiR-148b-3p was significantly associated with tumor grade (P=0.001) and tumor size (P=0.007), but not with age, gender, smoking history, history of alcohol, tumor thrombus, pleural invasion, node status or metastasis status. Multivariate Cox proportional hazard model analysis showed that tumor size (P=0.032), node status (P=0.005) and miR-148b-3p expression level (P=0.047) were significant independent predictors of overall survival of patients with lung adenocarcinoma. Kaplan-Meier survival analysis showed that the overall survival of patients with high expression of miR-148b-3p was significantly better than that of patients with low expression (P=0.010).
CONCLUSIONS: MiR-148b-3p was significantly associated with tumor grade and tumor size in lung adenocarcinoma, and served as an independent predictor of overall survival of patients with lung adenocarcinoma. The overall survival of patients with high expression level of miR-148b-3p was significantly better than that of patients with low expression.

Shi Y, Li P, Li B, et al.
[Characteristics of Epidermal Growth Factor Receptor with Rare Mutations in Non-small Cell Lung Cancer and the Effect of EGFR Tyrosine Kinase Inhibitors on Them].
Zhongguo Fei Ai Za Zhi. 2019; 22(5):299-305 [PubMed] Free Access to Full Article Related Publications
BACKGROUND: Adenocarcinoma is the most common type of lung cancer. It has been clinically evaluated that therapiestargeting against the epidermal growth factor receptor (EGFR) as the clinical standard first-line treatment. The response and outcome of EGFR-tyrosine kinase inhibitors (TKIs) in patients harboring common mutations in EGFR kinase domain (deletion in exon19 and L858R in exon 21) has been well demonstrated, but not in rare or complex mutations.
METHODS: A total of 150 patients that harbored rare or complex mutations in EGFR diagnosed by histopathology were included in this retrospective study. The clinical-pathological characteristics of all 150 patients as well as the response and progression-free survival (PFS) in 48 patients that received EGFR-TKIs in first/second/third line treatments weredescribed and analyzed.
RESULTS: Patients were divided into four groups based on the mutation types: single G719X point mutation in exon 18 (n=46, 30.7%), single L861Q point mutation in exon 21 (n=45, 30.0%), other single rare mutation (n=14, 9.3%) and complex mutations (n=45, 30.0%). The result indicated thatthere was no correlation of EGFR mutation typeswith other parameters such as gender, age, clinical stage, pathology and smoking history. For the 48 patients that received EGFR-TKIs treatment, there were no significant differencesamong 4 groups in terms of objective response rate (ORR) and disease control rate (DCR) (54.5% vs 30.0% vs 0.0% vs 35.7%, χ²=3.200, P=0.34; 90.9% vs 85.0% vs 66.7% vs 92.9%, χ²=2.162, P=0.59). The median progress-free survival (mPFS) was 11.0 months (95%CI: 4.4-17.6), and in each group of different EGFR mutation types are 15.8 months (95%CI: 9.5-22.2), 8.0 months (95%CI: 5.1-11.0), 4.9 months (95%CI: 1.4-8.4) and 23.1 months (95%CI: 15.8-30.4)(χ²=7.876, P=0.049).
CONCLUSIONS: The efficiency of targeting EGFR-TKIs on different types of rare or complex mutations was heterogeneous. The PFS may be better in patients that harbored complex mutations than those with single rare mutations. Further studies with larger sample size are necessary. Moreover, to discover novel therapeutic targets and develop new drugs are imminentfor those patientswith no response to the existing treatments.

Li W, Li Y, Zhang H, et al.
[Study on the Difference of Gene Expression between Central and Peripheral Lung Squamous Cell Carcinoma Based on TCGA Database].
Zhongguo Fei Ai Za Zhi. 2019; 22(5):280-288 [PubMed] Free Access to Full Article Related Publications
BACKGROUND: Lung cancer is a malignant tumor disease with high morbidity and high mortality. The non-small cell lung cancer (NSCLC) is the most common type, among them, lung squamous cell carcinoma own special pathological type and specific treatment, is a subtype of non-small cell lung cancer and can be divided into peripheral type and central type according to clinical phenotype. This study explores the differences in gene levels and their potential values based on clinical differences between central and peripheral in lung squamous cell carcinoma.
METHODS: The lung squamous cell carcinoma dataset was collected from The Cancer Genome Atlas (TCGA) database, clinical information and the corresponding gene expression profiles were downloaded. Then we further sort and analyze all these data.
RESULTS: In clinical characteristics analysis, result showed that central lung squamous cell carcinoma was more likely to metastasis with lymph node than peripheral lung squamous cell carcinoma (46.2%, 67/145 vs 28.9%, 26/90; P=0.019), while there were no significant differences in gender, age, tumor size, distant metastasis, tumor node metastasis (TNM) stage, and EGFR mutation. Gene expression analysis showed 1,031 differentially expressed genes between central and peripheral lung squamous cell carcinoma, of which 629 genes were up-regulated and 402 genes were down-regulated (peripheral vs central). Further enrichment analysis showed differentially expressed genes were mainly riched in 6 signaling pathways. Among them, the neuroactive ligand-receptor interaction pathway was the main enrichment pathway of differentially expressed genes, and other differential expressed genes were mainly involved in lipid metabolism and glucose metabolism. The analysis of interaction network showed that hepatocyte nuclear factor 1 homeobox A (HNF1A) and cytochrome p450 family, Cytochrome P450 3A4 (CYP3A4) own widely effect in up-regulated genes, while ALB and APOA1 at the key positions of the network in down-regulated genes were CONCLUSIONS: Central and peripheral lung squamous cell carcinoma showed clinical phenotype difference not only reflected in the incidence of lymph node metastasis, but also in gene expression profiles. Among them, HNF1A, CYP3A4, ALB, APOA1 at the key position of the differential gene interaction network and maybe as regulatory factors in the phenotypic difference.

Cao Y, Zhu W, Chen W, et al.
Prognostic Value of BIRC5 in Lung Adenocarcinoma Lacking EGFR, KRAS, and ALK Mutations by Integrated Bioinformatics Analysis.
Dis Markers. 2019; 2019:5451290 [PubMed] Free Access to Full Article Related Publications
Objective: This study was aimed at investigating the prognostic significance of Baculoviral IAP repeat containing 5 (BIRC5) in lung adenocarcinoma (LAD) lacking EGFR, KRAS, and ALK mutations (triple-negative (TN) adenocarcinomas).
Methods: The gene expression profiles were obtained from Gene Expression Omnibus (GEO). The identification of the differentially expressed genes (DEGs) was performed by GeneSpring GX. Gene set enrichment analysis (GSEA) was used to execute gene ontology function and pathway enrichment analysis. The protein interaction network was constructed by Cytoscape. The hub genes were extracted by MCODE and cytoHubba plugin from the network. Then, using BIRC5 as a candidate, the prognostic value in LAD and TN adenocarcinomas was verified by the Kaplan-Meier plotter and The Cancer Genome Atlas (TCGA) database, respectively. Finally, the mechanism of BIRC5 was predicted by a coexpressed network and enrichment analysis.
Results: A total of 38 upregulated genes and 121 downregulated genes were identified. 9 hub genes were extracted. Among them, the mRNA expression of 5 genes, namely, BIRC5, MCM4, CDC20, KIAA0101, and TRIP13, were significantly upregulated among TN adenocarcinomas (all
Conclusion: Overexpressed in tumors, BIRC5 is associated with unfavorable overall survival in TN adenocarcinomas. BIRC5 is a potential predictor and therapeutic target in TN adenocarcinomas.

Kawachi H, Fujimoto D, Yamashita D, et al.
Association Between Formalin Fixation Time and Programmed Cell Death Ligand 1 Expression in Patients With Non-Small Cell Lung Cancer.
Anticancer Res. 2019; 39(5):2561-2567 [PubMed] Related Publications
BACKGROUND/AIM: The expression of programmed cell death ligand 1 (PD-L1) determined by immunohistochemistry (IHC) may be associated with tissue formalin fixation time in non-small cell lung cancer (NSCLC) samples. We investigated the association between the PD-L1 expression and formalin fixation time, and clarified the optimal duration of fixation for accurate PD-L1 evaluation.
MATERIALS AND METHODS: We collected 55 tumor specimens from resected NSCLC patients. The samples were halved and immediately fixed in 10% buffered formalin for 12-24 h (normal fixation), or 96-120 h (prolonged fixation). Each specimen was stained using two assay systems (22C3 and SP263) for PD-L1.
RESULTS: The mean PD-L1 tumor proportion score was not significantly different between normal and prolonged fixation groups for either 22C3 or SP263 (normal fixation: 18.8%; prolonged fixation: 16.3%, p=0.277; normal fixation: 16.2%; prolonged fixation: 17.6%, p=0.560, respectively).
CONCLUSION: Formalin fixation duration for up to 120 h does not affect PD-L1 IHC expression. PD-L1 tumor proportion score of tumor specimens can be evaluated by IHC even if these have been fixed in formalin outside the recommended duration in clinical practice.

Ercan S, Arinc S, Yilmaz SG, et al.
Investigation of Caspase 9 Gene Polymorphism in Patients With Non-small Cell Lung Cancer.
Anticancer Res. 2019; 39(5):2437-2441 [PubMed] Related Publications
BACKGROUND/AIM: Non-small cell lung cancer (NSCLC) is one of the most common forms of lung cancer and the leading cause of cancer-related deaths in the world. Caspase 9 (CASP9) plays a central role in the intrinsic apoptotic pathway. The aim of the study was to investigate the role of caspase 9 gene polymorphism in patients with non-small cell lung cancer.
MATERIALS AND METHODS: The study included 96 NSCLC cases and 67 controls. CASP9 Ex5+32 G>A polymorphism was investigated by real-time polymerase chain reaction.
RESULTS: There was a significant difference between the groups in the frequency of CASP9 genotypes (p=0.008). The number of the carriers of the ancestral GG genotype, was significantly higher in the NSCLC group than in the control (p=0.009). The heterozygote GA genotype and mutant A allele frequency were significantly higher in the control group compared to the NSCLC group (p=0.005, p=0.009, respectively). Serum CASP9 levels were significantly lower in the patients group than in the control group (p<0.0001).
CONCLUSION: CASP9 Ex5+32 GG genotype was a risk factor whereas the variant A allele could be a risk-reducing factor for NSCLC.

Jones MR, Williamson LM, Topham JT, et al.
Clin Cancer Res. 2019; 25(15):4674-4681 [PubMed] Related Publications
PURPOSE: Gene fusions involving neuregulin 1 (
EXPERIMENTAL DESIGN: Forty-seven patients with pancreatic ductal adenocarcinoma received comprehensive whole-genome and transcriptome sequencing and analysis. Two patients with gene fusions involving
RESULTS: Three of 47 (6%) patients with advanced pancreatic ductal adenocarcinoma were identified as
CONCLUSIONS: This work adds to a growing body of evidence that

Byun Y, Choi YC, Jeong Y, et al.
MiR-200c downregulates HIF-1α and inhibits migration of lung cancer cells.
Cell Mol Biol Lett. 2019; 24:28 [PubMed] Free Access to Full Article Related Publications
Background: Hypoxia-inducible factor-1α (HIF-1α) is a transcription factor with a pivotal role in physiological and pathological responses to hypoxia. While HIF-1α is known to be involved in hypoxia-induced upregulation of microRNA (miRNA) expression, HIF-1α is also targeted by miRNAs. In this study, miRNAs targeting HIF-1α were identified and their effects on its expression and downstream target genes under hypoxic conditions were investigated. Cell migration under the same conditions was also assessed.
Methods: microRNAs that target
Results: Several of the 19 screened miRNAs considerably decreased the luciferase activity. Transfection with miR-200c had substantial impact on the expression level and transcription activity of HIF-1α. The mRNA level of HIF-1α downstream genes decreased in response to miR-200c overexpression. MiR-200c inhibited cell migration in normoxia and, to a greater extent, in hypoxia. These effects were partly reversed by HIF-1α expression under hypoxic conditions.
Conclusion: miR-200c negatively affects hypoxia-induced responses by downregulating HIF-1α, a key regulator of hypoxia. Therefore, overexpression of miR-200c might have therapeutic potential as an anticancer agent that inhibits tumor hypoxia.

Pang C, Ma H, Qin J, et al.
Pleural effusion as a substitute for tumor tissue in detecting EGFR/ALK mutations in non-small cell lung cancer: A systematic review and meta-analysis.
Medicine (Baltimore). 2019; 98(18):e15450 [PubMed] Free Access to Full Article Related Publications
BACKGROUND: Pleural effusion (PE) has been reported useful in many studies for testing epidermal growth factor receptor (EGFR) mutations in non-small cell lung cancer (NSCLC) with variable results. This systematic review and meta-analysis was performed to elucidate whether PE could be used as a surrogate for tumor tissue to detect EGFR mutations.
METHODS: We extracted 2 × 2 diagnostic table from each included study and calculated data on specificity, sensitivity, negative likelihood ratio (NLR), positive likelihood ratio (PLR) ,and diagnostic odds ratio (DOR). We used the area under curve (AUC) and summary receiver operating characteristic curve (SROC) to summarize the overall diagnostic performance and assessed publication bias by Deeks' funnel plot.
RESULTS: Our meta-analysis included 15 eligible publications. The following summary estimates for diagnostic parameters of the EGFR mutations detection in PE were made: sensitivity, 0.86 (95%CI 0.83-0.89); specificity, 0.93 (95%CI 0.91-0.95); PLR, 8.53 (95%CI 5,94-12.25); NLR, 0.18 (95%CI 0.13-0.25); DOR, 63.40 (95%CI 38.83-103.51); and AUC, 0.94. Funnel plot indicated publication bias insignificant.
CONCLUSIONS: The meta-analysis suggests that EGFR mutation detecting in PE, especially supernatants, is a promising surrogate for tumor tissue in EGFR mutations testing of patients with NSCLC.

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(3p) in Lung Cancer

Hung J, Kishimoto Y, Sugio K, et al.
Allele-specific chromosome 3p deletions occur at an early stage in the pathogenesis of lung carcinoma.
JAMA. 1995; 273(7):558-63 [PubMed] Related Publications
BACKGROUND: Deletions in the short arm of chromosome 3 (3p) are present in most lung carcinomas.
OBJECTIVE: To investigate the role of these chromosome 3p deletions in the pathogenesis of non-small cell lung carcinomas.
DESIGN: Seven archival, paraffin-embedded, surgically resected lung cancer specimens were studied. Fifty precisely identified malignant and preneoplastic lesions present in bronchi, bronchioles, and alveoli were microdissected from stained slides and analyzed for allele loss using polymerase chain reaction-based assays for dinucleotide repeat polymorphisms at three chromosome 3p loci (3p14, 3p21.3, and 3p25).
SETTING: University-based medical center and affiliated hospitals.
SUBJECTS: Samples were analyzed from seven patients who underwent surgical resection with curative intent for non-small cell lung cancer and whose specimens included extensive multifocal areas of preneoplastic lesions (hyperplasia, metaplasia, dysplasia, or noninvasive cancer).
RESULTS: Lymphocytes from all seven cases were heterozygous (ie, informative) for all three microsatellites analyzed. Six (86%) of seven invasive cancers had loss of heterozygosity at one or more chromosome 3p sites. In the accompanying preneoplastic lesions, loss of heterozygosity was detected in none of two normal bronchioles, 13 (76%) of 17 hyperplasias, six (86%) of seven dysplasias, and four (100%) of four noninvasive cancers. Loss of heterozygosity was detected throughout the respiratory tract, in bronchi, bronchioles, and alveoli. In 18 (78%) of 23 preneoplastic lesions, the specific alleles lost were identical to those lost in the corresponding carcinomas. The probability of this happening by chance is 5.3 x 10(-3).
CONCLUSIONS: Deletions in the short arm of chromosome 3 occur at the earliest stage (hyperplasia) in the pathogenesis of lung cancer and involve all regions of the respiratory tract. Allele loss is highly specific, but its mechanism remains unknown. Our findings may be of considerable biologic, prognostic, and clinical significance.

Hosoe S, Shigedo Y, Ueno K, et al.
Detailed deletion mapping of the short arm of chromosome 3 in small cell and non-small cell carcinoma of the lung.
Lung Cancer. 1994; 10(5-6):297-305 [PubMed] Related Publications
We constructed a detailed deletion map of the short arm of chromosome 3 (3p) for 55 lung cancer cases by using 17 restriction fragment length polymorphism (RFLP) probes. Initially, we examined 40 small cell lung cancer (SCLC) cases and found three regions of deletion at 3p25-26, 3p21.3 and 3p14-cen, suggesting the possibility of at least three different tumor-suppressor genes on 3p. In order to obtain more detailed deletion area, and to compare the pattern of 3p deletion, we also examined 15 non-small cell lung cancer (NSCLC) cases. Compared to NSCLC cases, most of SCLC cases have widespread deletion on 3p, suggesting multiple tumor-suppressor genes on 3p may be inactivated in this type of cancer. In 3p21.3 area, minimum overlapping area of deletion lays between two probes which are close to each other. These data will be useful to isolate the putative tumor-suppressor genes located on the chromosome 3p.

Kohno H, Hiroshima K, Toyozaki T, et al.
p53 mutation and allelic loss of chromosome 3p, 9p of preneoplastic lesions in patients with nonsmall cell lung carcinoma.
Cancer. 1999; 85(2):341-7 [PubMed] Related Publications
BACKGROUND: An accumulation of mutations can result in carcinogenesis. Comparing genetic alterations in preneoplastic lesions with those seen in cancer in the same patient may be helpful in the early diagnosis of lung carcinoma or preneoplastic lesions.
METHODS: To identify genetic alterations that may play a role in the development of nonsmall cell lung carcinoma (NSCLC), the authors examined the p53 gene and microsatellite markers on chromosome 3p (D3S643, D3S1317), 9p (D9S171, IFNA) in 35 bronchial metaplastic lesions and 28 alveolar hyperplastic lesions from 61 patients.
RESULTS: A total of 8 metaplastic lesions (1 squamous metaplasia and 7 dysplasias) and 3 alveolar hyperplastic lesions (with atypia) showed genetic alterations, including loss of heterozygosity (LOH) of 3p, 9p and mutations of the p53 gene. In an analysis of microsatellite markers, 5 of 35 cases of squamous cell carcinoma (SCC) and 3 of 26 cases of adenocarcinoma (Ad) showed LOH in both preneoplastic lesions and synchronous cancers. Nine patients (25.7%) with SCC and 6 patients (23.1%) with Ad were shown to have mutations of the p53 gene by single-strand conformation polymorphism. In 2 of these 9 patients with SCC, the same mutation was observed in both dysplasia and SCC.
CONCLUSIONS: These findings suggest that several genetic alterations may occur in preneoplastic lesions or the early stage of SCC of the lung, whereas the genetic alterations examined appeared to occur relatively late in the pathogenesis of pulmonary adenocarcinoma.

del(9p) in Lung Cancer

Kishimoto Y, Sugio K, Hung JY, et al.
Allele-specific loss in chromosome 9p loci in preneoplastic lesions accompanying non-small-cell lung cancers.
J Natl Cancer Inst. 1995; 87(16):1224-9 [PubMed] Related Publications
BACKGROUND: Carcinogenesis is a multistep process, which may begin as a consequence of chromosomal changes. Deletions in the short arm of chromosome 9 (9p) have been observed in lung carcinomas. In addition, morphologically recognizable preneoplastic lesions, frequently multiple in number, precede onset of invasive carcinomas.
PURPOSE: We tested for deletions and loss of heterozygosity (LOH) at 9p loci in preneoplastic and neoplastic foci in lungs of patients with non-small-cell lung carcinomas (NSCLCs).
METHODS: Seven archival, paraffin-embedded, surgically resected NSCLC specimens were selected. They were predominantly from patients with adenocarcinomas and contained multiple preneoplastic lesions, including hyperplasia, metaplasia, dysplasia, and carcinoma in situ (CIS). Fifty-three histologically identified preneoplastic and malignant lesions present in bronchi, bronchioles, and alveoli were precisely microdissected from stained tissue sections with a micromanipulator. Stromal lymphocytes were used to determine constitutional heterozygosity. The specimens were analyzed for LOH using polymerase chain reaction-based assays for polymorphism in dinucleotide repeats (microsatellite markers) in interferon alfa (IFNA) and D9S171 loci on 9p.
RESULTS: All seven cases were constitutionally heterozygous for one or both microsatellite markers. Five of seven cases had LOH at one or both 9p loci in the invasive primary cancers (doubly informative cases). Four of these five cases also revealed LOH in preneoplastic foci. In the doubly informative cases, LOH was detected in five (38%) of 13 foci of hyperplasia, four (80%) of five foci of dysplasia, and three (100%) of three CIS lesions. LOH was detected in preneoplastic lesions from all regions of the respiratory tract, including bronchi, bronchioles, and alveoli, and involved five different cell types. The identical allele was lost from both the preneoplastic lesions and the corresponding tumors (12 of 12 lesions, 17 of 17 comparisons), a phenomenon we have referred to as "allele-specific mutation." Statistical analyses employing a cumulative binomial test demonstrated that the probabilities of such findings occurring by chance are 2.4 x 10(-4) and 7.6 x 10(-6), respectively. From comparisons with the previously published data on other chromosomal abnormalities in the same tissue specimens, it appears that LOH at 3p and 9p loci occurred early in the hyperplasia stage, but the ras gene point mutations were relatively late, at the CIS stage.
CONCLUSIONS: LOH at 9p loci occurs at the earliest stage in the pathogenesis of lung cancer and involves all regions of the respiratory tract. LOH in NSCLC is not random but targets a specific allele in individuals. Studying preneoplastic lesions may help identify intermediate markers for risk assessment and chemoprevention.

Kohno H, Hiroshima K, Toyozaki T, et al.
p53 mutation and allelic loss of chromosome 3p, 9p of preneoplastic lesions in patients with nonsmall cell lung carcinoma.
Cancer. 1999; 85(2):341-7 [PubMed] Related Publications
BACKGROUND: An accumulation of mutations can result in carcinogenesis. Comparing genetic alterations in preneoplastic lesions with those seen in cancer in the same patient may be helpful in the early diagnosis of lung carcinoma or preneoplastic lesions.
METHODS: To identify genetic alterations that may play a role in the development of nonsmall cell lung carcinoma (NSCLC), the authors examined the p53 gene and microsatellite markers on chromosome 3p (D3S643, D3S1317), 9p (D9S171, IFNA) in 35 bronchial metaplastic lesions and 28 alveolar hyperplastic lesions from 61 patients.
RESULTS: A total of 8 metaplastic lesions (1 squamous metaplasia and 7 dysplasias) and 3 alveolar hyperplastic lesions (with atypia) showed genetic alterations, including loss of heterozygosity (LOH) of 3p, 9p and mutations of the p53 gene. In an analysis of microsatellite markers, 5 of 35 cases of squamous cell carcinoma (SCC) and 3 of 26 cases of adenocarcinoma (Ad) showed LOH in both preneoplastic lesions and synchronous cancers. Nine patients (25.7%) with SCC and 6 patients (23.1%) with Ad were shown to have mutations of the p53 gene by single-strand conformation polymorphism. In 2 of these 9 patients with SCC, the same mutation was observed in both dysplasia and SCC.
CONCLUSIONS: These findings suggest that several genetic alterations may occur in preneoplastic lesions or the early stage of SCC of the lung, whereas the genetic alterations examined appeared to occur relatively late in the pathogenesis of pulmonary adenocarcinoma.

del(1p36) in Lung Cancer

Nomoto S, Haruki N, Tatematsu Y, et al.
Frequent allelic imbalance suggests involvement of a tumor suppressor gene at 1p36 in the pathogenesis of human lung cancers.
Genes Chromosomes Cancer. 2000; 28(3):342-6 [PubMed] Related Publications
The short arm of chromosome 1 is among the most frequently affected regions in various types of common adult cancers as well as in neuroblastoma. In a previous study of ours, frequent allelic imbalance at the TP73 locus at 1p36 was noted in lung cancer despite the absence of TP73 mutations. This suggested the possible existence of an as yet unidentified tumor suppressor gene on 1p. Our initial attempt using the candidate gene approach did not yield any somatic mutations in the 14-3-3sigma gene (official gene symbol, SFN), a mediator of G2 arrest by TP53. Detailed deletion mapping of the telomeric region of 1p was thus carried out as an initial step toward positional cloning. We used seven polymorphic markers in addition to TP73 to examine 61 primary lung cancers. Allelic imbalance at one or more loci of 1p36 was observed in 30 of the 61 cases, whereas D1S508 at 1p36.2 exhibited the highest frequency (45%) of allelic imbalance among the 1p36 markers examined. In contrast, two proximal markers at 1p32-34 showed significantly less frequent (11-14%) allelic imbalance. Consequently, the present study identified the shortest region of overlap between D1S507 and TP73, which included the most frequently affected marker, D1S508. In addition, several cases exhibited allelic imbalance confined to a subtelomeric region distal to D1S2845 at 1p36.3. The present findings warrant future studies to identify the putative tumor suppressor gene(s) at 1p36 to gain a better understanding of the molecular pathogenesis of lung cancer. Genes Chromosomes Cancer 28:342-346, 2000.

Yanada M, Yaoi T, Shimada J, et al.
Frequent hemizygous deletion at 1p36 and hypermethylation downregulate RUNX3 expression in human lung cancer cell lines.
Oncol Rep. 2005; 14(4):817-22 [PubMed] Related Publications
Runt-related transcription factor 3 (RUNX3) has been recognized as a tumor suppressor gene in gastric cancer because its expression level was reduced or disappeared due to epigenetic changes. To evaluate the usefulness of the RUNX3 gene as a biomarker of lung cancer, we have analyzed the expression of the RUNX3 gene in 15 lung cancer cell lines by real-time reverse transcription-polymerase chain reaction (RT-PCR), and demonstrated that RUNX3 gene expression was reduced or disappeared in all cell lines examined (100%). In addition, we have attempted to classify all the cell lines into three groups according to the expression level; less than 10% (group I), 10-30% (group II) and approximately 50% (group III). We further investigated methylation status of the CpG sites in the exon 1 region of RUNX3 by methylation specific PCR (MSP), and studied the correlation between the expression level and hemizygous deletion as revealed by bicolor fluorescence in situ hybridization (FISH). The CpG sites were hypermethylated in 8 cell lines (53%) and the RUNX3 loci were hemizygously deleted in another 8 cell lines (53%). Furthermore group I, II, and III corresponded well to methylation-positive cell lines, cell lines showing hemizygous deletion, and the rest of cell lines without methylation or hemizygous deletion, respectively. These results suggest that a comprehensive study on RUNX3 using real-time RT-PCR, MSP, and FISH could be beneficial in understanding the pathogenetic mechanisms of human lung cancer at the molecular level.

Shibukawa K, Miyokawa N, Tokusashi Y, et al.
High incidence of chromosomal abnormalities at 1p36 and 9p21 in early-stage central type squamous cell carcinoma and squamous dysplasia of bronchus detected by autofluorescence bronchoscopy.
Oncol Rep. 2009; 22(1):81-7 [PubMed] Related Publications
Heavy smokers with central type squamous cell carcinoma (SCC) frequently have multiple cancerous lesions in the bronchus. Autofluorescence bronchoscopy (AFB) is useful in the detection of early bronchogenic cancer and dysplastic lesions. We investigated the loss of heterozygosity (LOH) and microsatellite instability (MSI) and expression of four proteins in 13 early stage SCC (early SCC) and 9 squamous dysplasia detected by AFB and 19 cases of surgically resected invasive SCC (invasive SCC). In early SCC and squamous dysplasia, LOH/MSI of chromosome 1p36 was found in 62 and 33%, respectively, and of 9p21 in 54 and 63%, respectively. TAp73 expression of early SCC and squamous dysplasia was lower than that of normal bronchial epithelium, and p16 expression was not detectable in these lesions. These results suggested that the genetic abnormalities had already developed in the early stage of carcinogenesis of SCC, including squamous dysplasia. The AFB system was able to reveal abnormal autofluorescence in these precancerous lesions, including squamous dysplasia.

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