Prostate Cancer- Molecular Biology

Overview

Prostate cancer is the most common malignancy found in men, incidence is highest among American Blacks and lowest in East Asian populations. Prostate specific Antigen (PSA) is an important marker in the diagnosis and monitoring of prostate cancer, and the percentage free PSA has been shown to have prognostic significance in some studies.

Androgens, which exert their effects via the androgen receptor (AR), are essential for the normal prostate. They are also required by prostate cancer cells. Therefore, androgen ablation and antiandrogen therapy are important in the treatment of the disease, though most patients go on to develop androgen-independent prostate cancer. Androgen receptor mutations are observed in late stage prostate cancer.

Caveolin-1 is overexpressed in about a quarter of human prostate cancers (Yang, 1999) . Caveolin expression is thought to induce androgen sensitivity in androgen-insensitive prostate cancer cells.

Mutations in a diverse range of other genes have been implicated in prostate cancer including PTEN, KAI1, SRD5A2, and IL6. Most of these relate to disease progression.

Hereditary prostate cancer accounts for about 9% of cases. A prostate cancer susceptibility locus (HPC1) on chromosome 1q24-25 was identified by Smith (1996). However, subsequent studies suggest that mutations in HPC1 are uncommon and are restricted to people with early onset disease. A second gene (HPC2 on chromosome 1q42.2-q43 was proposed by Berthon (1998), though again subsequent linkage studies indicate this gene could only account for a small proportion of cases. Other specific gene(s) associated with hereditary prostate cancer have yet to be identified.

See also: Prostate Cancer - clinical resources (38)

Literature Analysis

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

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

Mutated Genes and Abnormal Protein Expression (622)

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
KLK3 19q13.33 APS, PSA, hK3, KLK2A1 Overexpression
-PSA expression in Prostate Cancer
3000
AR Xq12 KD, AIS, AR8, TFM, DHTR, SBMA, HYSP1, NR3C4, SMAX1, HUMARA -AR and Prostate Cancer
1974
TMPRSS2 21q22.3 PP9284, PRSS10 Intronic Deletion or Translocation
-ERG-TMPRSS2 Fusion in Prostate Cancer
-ETV1 translocations in Prostate Cancer
-TMPRSS2 and Prostate Cancer
534
PTEN 10q23.31 BZS, DEC, CWS1, GLM2, MHAM, TEP1, MMAC1, PTEN1, 10q23del -PTEN and Prostate Cancer
502
MKI67 10q26.2 KIA, MIB-, MIB-1, PPP1R105 -MKI67 and Prostate Cancer
460
CTNNB1 3p22.1 CTNNB, MRD19, armadillo -CTNNB1 and Prostate Cancer
372
TP53 17p13.1 P53, BCC7, LFS1, TRP53 -TP53 and Prostate Cancer
370
BRCA1 17q21.31 IRIS, PSCP, BRCAI, BRCC1, FANCS, PNCA4, RNF53, BROVCA1, PPP1R53 -BRCA1 and Prostate Cancer
210
BRCA2 13q13.1 FAD, FACD, FAD1, GLM3, BRCC2, FANCD, PNCA2, FANCD1, XRCC11, BROVCA2 -BRCA2 and Prostate Cancer
198
MTOR 1p36.22 SKS, FRAP, FRAP1, FRAP2, RAFT1, RAPT1 -MTOR and Prostate Cancer
154
CDKN1A 6p21.2 P21, CIP1, SDI1, WAF1, CAP20, CDKN1, MDA-6, p21CIP1 -CDKN1A Expression in Prostate Cancer
141
PROC 2q13-q14 PC, APC, PROC1, THPH3, THPH4 -PROC and Prostate Cancer
135
NKX3-1 8p21.2 NKX3, BAPX2, NKX3A, NKX3.1 -NKX3-1 and Prostate Cancer
132
SRC 20q11.23 ASV, SRC1, THC6, c-SRC, p60-Src -SRC and Prostate Cancer
130
SRD5A2 2p23 -SRD5A2 and Prostate Cancer
120
CDKN1B 12p13.1 KIP1, MEN4, CDKN4, MEN1B, P27KIP1 -CDKN1B and Prostate Cancer
104
PCA3 9q21.2 DD3, PCAT3, NCRNA00019 -PCA3 and Prostate Cancer
103
CD44 11p13 IN, LHR, MC56, MDU2, MDU3, MIC4, Pgp1, CDW44, CSPG8, HCELL, HUTCH-I, ECMR-III -CD44 and Prostate Cancer
102
ETV1 7p21.2 ER81 Translocation
-ETV1 translocations in Prostate Cancer
99
PTGS2 1q31.1 COX2, COX-2, PHS-2, PGG/HS, PGHS-2, hCox-2, GRIPGHS -PTGS2 (COX2) and Prostate Cancer
99
EZH2 7q36.1 WVS, ENX1, EZH1, KMT6, WVS2, ENX-1, EZH2b, KMT6A -EZH2 and Prostate Cancer
98
HIF1A 14q23.2 HIF1, MOP1, PASD8, HIF-1A, bHLHe78, HIF-1alpha, HIF1-ALPHA, HIF-1-alpha -HIF1A and Prostate Cancer
97
KITLG 12q22 SF, MGF, SCF, FPH2, FPHH, KL-1, Kitl, SHEP7 -KITLG and Prostate Cancer
96
CYP17A1 10q24.32 CPT7, CYP17, S17AH, P450C17 -CYP17A1 and Prostate Cancer
91
TGFB1 19q13.2 CED, LAP, DPD1, TGFB, TGFbeta -TGFB1 and Prostate Cancer
91
GSTM1 1p13.3 MU, H-B, GST1, GTH4, GTM1, MU-1, GSTM1-1, GSTM1a-1a, GSTM1b-1b -GSTM1 and Prostate Cancer
81
IGFBP3 7p12.3 IBP3, BP-53 -IGFBP3 and Prostate Cancer
79
MSMB 10q11.22 MSP, PSP, IGBF, MSPB, PN44, PRPS, HPC13, PSP57, PSP94, PSP-94 -MSMB and Prostate Cancer
-Prostate cancer susceptibility variant (MSMB) rs10993994
54
JUN 1p32.1 AP1, p39, AP-1, cJUN, c-Jun -c-Jun and Prostate Cancer
72
E2F1 20q11.22 RBP3, E2F-1, RBAP1, RBBP3 -E2F1 and Prostate Cancer
68
IL10 1q32.1 CSIF, TGIF, GVHDS, IL-10, IL10A -Interleukin-10 and Prostate Cancer
68
CAMP 3p21.31 LL37, CAP18, CRAMP, HSD26, CAP-18, FALL39, FALL-39 -CAMP and Prostate Cancer
66
AMACR 5p13.2 RM, RACE, CBAS4, P504S, AMACRD -AMACR and Prostate Cancer
60
ELAC2 17p12 ELC2, HPC2, COXPD17 -ELAC2 and Prostate Cancer
59
IGF1R 15q26.3 IGFR, CD221, IGFIR, JTK13 -IGF1R and Prostate Cancer
59
SERPINB5 18q21.33 PI5, maspin -SERPIN-B5 and Prostate Cancer
58
FOXA1 14q21.1 HNF3A, TCF3A -FOXA1 and Prostate Cancer
55
TRPM2 21q22.3 KNP3, EREG1, TRPC7, LTRPC2, NUDT9H, LTrpC-2, NUDT9L1 -TRPM2 and Prostate Cancer
54
CD82 11p11.2 R2, 4F9, C33, IA4, ST6, GR15, KAI1, SAR2, TSPAN27 -CD82 and Prostate Cancer
50
VEGFA 6p21.1 VPF, VEGF, MVCD1 -VEGFA and Prostate Cancer
50
CLU 8p21.1 CLI, AAG4, APOJ, CLU1, CLU2, KUB1, SGP2, APO-J, SGP-2, SP-40, TRPM2, TRPM-2, NA1/NA2 -CLU and Prostate Cancer
48
MET 7q31.2 HGFR, AUTS9, RCCP2, c-Met, DFNB97 -C-MET and Prostate Cancer
48
KLK2 19q13.33 hK2, hGK-1, KLK2A2 -KLK2 and Prostate Cancer
47
RASSF1 3p21.31 123F2, RDA32, NORE2A, RASSF1A, REH3P21 -RASSF1 and Prostate Cancer
46
PSCA 8q24.3 PRO232 -PSCA and Prostate Cancer
46
CYP3A4 7q22.1 HLP, CP33, CP34, CYP3A, NF-25, CYP3A3, P450C3, CYPIIIA3, CYPIIIA4, P450PCN1 -CYP3A4 and Prostate Cancer
46
CYP1A1 15q24.1 AHH, AHRR, CP11, CYP1, CYPIA1, P1-450, P450-C, P450DX -CYP1A1 and Prostate Cancer
44
CHEK2 22q12.1 CDS1, CHK2, LFS2, RAD53, hCds1, HuCds1, PP1425 -CHEK2 and Prostate Cancer
44
FOS 14q24.3 p55, AP-1, C-FOS -FOS and Prostate Cancer
44
MSR1 8p22 SRA, SR-A, CD204, SR-AI, phSR1, phSR2, SCARA1, SR-AII, SR-AIII -MSR1 and Prostate Cancer
43
CYP3A5 7q22.1 CP35, PCN3, CYPIIIA5, P450PCN3 -CYP3A5 and Prostate Cancer
42
IL6 7p15.3 CDF, HGF, HSF, BSF2, IL-6, BSF-2, IFNB2, IFN-beta-2 -IL6 and Prostate Cancer
42
RELA 11q13.1 p65, NFKB3 -RELA and Prostate Cancer
40
ETV4 17q21.31 E1AF, PEA3, E1A-F, PEAS3 -ETV4 and Prostate Cancer
37
FGF2 4q28.1 BFGF, FGFB, FGF-2, HBGF-2 -FGF2 and Prostate Cancer
36
EGR1 5q31.2 TIS8, AT225, G0S30, NGFI-A, ZNF225, KROX-24, ZIF-268 -EGR1 and Prostate Cancer
36
CAPS 19p13.3 CAPS1 -CAPS and Prostate Cancer
34
XRCC1 19q13.31 RCC -XRCC1 and Prostate Cancer
34
HGF 7q21.11 SF, HGFB, HPTA, F-TCF, DFNB39 -HGF and Prostate Cancer
33
CXCR4 2q21 FB22, HM89, LAP3, LCR1, NPYR, WHIM, CD184, LAP-3, LESTR, NPY3R, NPYRL, WHIMS, HSY3RR, NPYY3R, D2S201E -CXCR4 and Prostate Cancer
33
TNFRSF11A 18q21.33 FEO, OFE, ODFR, OSTS, PDB2, RANK, CD265, OPTB7, TRANCER, LOH18CR1 -TNFRSF11A and Prostate Cancer
32
SPINK1 5q32 TCP, PCTT, PSTI, TATI, Spink3 -SPINK1 and Prostate Cancer
32
ITGB1 10p11.22 CD29, FNRB, MDF2, VLAB, GPIIA, MSK12, VLA-BETA -ITGB1 (CD29) and Prostate Cancer
31
CAV1 7q31.2 CGL3, PPH3, BSCL3, LCCNS, VIP21, MSTP085 -CAV1 and Prostate Cancer
31
SHBG 17p13.1 ABP, SBP, TEBG -SHBG and Prostate Cancer
30
CYP24A1 20q13.2 CP24, HCAI, CYP24, HCINF1, P450-CC24 -CYP24A1 and Prostate Cancer
30
SLC45A3 1q32.1 PRST, IPCA6, IPCA-2, IPCA-6, IPCA-8, PCANAP2, PCANAP6, PCANAP8 -SLC45A3 and Prostate Cancer
29
AURKA 20q13.2 AIK, ARK1, AURA, BTAK, STK6, STK7, STK15, PPP1R47 -AURKA and Prostate Cancer
29
TLR4 9q33.1 TOLL, CD284, TLR-4, ARMD10 -TLR4 and Prostate Cancer
28
ESR1 6q25.1-q25.2 ER, ESR, Era, ESRA, ESTRR, NR3A1 -ESR1 and Prostate Cancer
28
ERBB2 17q12 NEU, NGL, HER2, TKR1, CD340, HER-2, MLN 19, HER-2/neu -ERBB2 and Prostate Cancer
27
SKP2 5p13.2 p45, FBL1, FLB1, FBXL1 -SKP2 and Prostate Cancer
27
RUNX2 6p21.1 CCD, AML3, CCD1, CLCD, OSF2, CBFA1, OSF-2, PEA2aA, PEBP2aA, CBF-alpha-1 -RUNX2 and Prostate Cancer
27
KLF6 10p15.2 GBF, ZF9, BCD1, CBA1, CPBP, PAC1, ST12, COPEB -KLF6 and Prostate Cancer
26
SOD2 6q25.3 IPOB, IPO-B, MNSOD, MVCD6, Mn-SOD -SOD2 and Prostate Cancer
25
CYP27B1 12q14.1 VDR, CP2B, CYP1, PDDR, VDD1, VDDR, VDDRI, CYP27B, P450c1, CYP1alpha -CYP27B1 and Prostate Cancer
24
HDAC1 1p35.2-p35.1 HD1, RPD3, KDAC1, GON-10, RPD3L1 -HDAC1 and Prostate Cancer
23
NANOG 12p13.31 -NANOG and Prostate Cancer
23
LOX 5q23.1 AAT10 -LOX and Prostate Cancer
23
UGT2B17 4q13.2 BMND12, UDPGT2B17 -UGT2B17 and Prostate Cancer
23
HPCX Xq27-q28 -HPCX and Prostate Cancer
22
UGT2B15 4q13.2 HLUG4, UGT2B8, UDPGTH3, UDPGT 2B8, UDPGT2B15 -UGT2B15 and Prostate Cancer
22
HNF1B 17q12 FJHN, HNF2, LFB3, TCF2, HPC11, LF-B3, MODY5, TCF-2, VHNF1, HNF-1B, HNF1beta, HNF-1-beta -HNF1B and Prostate Cancer
22
IKBKB 8p11.21 IKK2, IKKB, IMD15, NFKBIKB, IKK-beta -IKBKB and Prostate Cancer
21
SLC2A1 1p34.2 CSE, PED, DYT9, GLUT, DYT17, DYT18, EIG12, GLUT1, HTLVR, GLUT-1, SDCHCN, GLUT1DS -GLUT1 expression in Prostate Cancer
21
NDRG1 8q24.22 GC4, RTP, DRG1, NDR1, NMSL, TDD5, CAP43, CMT4D, DRG-1, HMSNL, RIT42, TARG1, PROXY1 -NDRG1 and Prostate Cancer
21
SIRT1 10q21.3 SIR2, SIR2L1, SIR2alpha -SIRT1 and Prostate Cancer
21
SRD5A1 5p15.31 S5AR 1 -SRD5A1 and Prostate Cancer
21
GDF15 19p13.11 PDF, MIC1, PLAB, MIC-1, NAG-1, PTGFB, GDF-15 -GDF15 and Prostate Cancer
20
AKR1C3 10p15.1 DD3, DDX, PGFS, HAKRB, HAKRe, HA1753, HSD17B5, hluPGFS -AKR1C3 and Prostate Cancer
20
GPX1 3p21.31 GPXD, GSHPX1 -GPX1 and Prostate Cancer
20
PIM1 6p21.2 PIM -PIM1 and Prostate Cancer
20
TTPA 8q12.3 ATTP, AVED, TTP1, alphaTTP -TTPA and Prostate Cancer
19
CCK 3p22.1 -CCK and Prostate Cancer
19
NCOA4 10q11.22 RFG, ELE1, PTC3, ARA70 -NCOA4 and Prostate Cancer
19
SOX9 17q24.3 CMD1, SRA1, CMPD1, SRXX2, SRXY10 -SOX9 and Prostate Cancer
18
TIMP2 17q25.3 DDC8, CSC-21K -TIMP2 and Prostate Cancer
18
FGF8 10q24.32 HH6, AIGF, KAL6, FGF-8, HBGF-8 -FGF8 and Prostate Cancer
18
CCL2 17q12 HC11, MCAF, MCP1, MCP-1, SCYA2, GDCF-2, SMC-CF, HSMCR30 -CCL2 and Prostate Cancer
18
ETV5 3q27.2 ERM -ETV5 and Prostate Cancer
18
BMI1 10p12.2 PCGF4, RNF51, FLVI2/BMI1, flvi-2/bmi-1 -BMI1 and Prostate Cancer
18
TRPM8 2q37.1 TRPP8, LTRPC6 -TRPM8 and Prostate Cancer
18
SNAI2 8q11.21 SLUG, WS2D, SLUGH, SLUGH1, SNAIL2 -SNAI2 and Prostate Cancer
18
KDM1A 1p36.12 AOF2, CPRF, KDM1, LSD1, BHC110 -KDM1A and Prostate Cancer
18
NCOA2 8q13.3 SRC2, TIF2, GRIP1, KAT13C, NCoA-2, bHLHe75 -NCOA2 and Prostate Cancer
18
COMT 22q11.21 HEL-S-98n -COMT and Prostate Cancer
18
RFX6 6q22.1 MTFS, MTCHRS, RFXDC1, dJ955L16.1 -rs339331 Polymorphism and Prostate Cancer susceptibility
-RFX6 and Prostate Cancer
9
KLK4 19q13.41 ARM1, EMSP, PSTS, AI2A1, EMSP1, KLK-L1, PRSS17, kallikrein -KLK4 and Prostate Cancer
17
TACSTD2 1p32.1 EGP1, GP50, M1S1, EGP-1, TROP2, GA7331, GA733-1 -TACSTD2 and Prostate Cancer
17
NOS3 7q36.1 eNOS, ECNOS -NOS3 and Prostate Cancer
17
GADD45A 1p31.3 DDIT1, GADD45 -GADD45A and Prostate Cancer
17
CD24 6q21 CD24A -CD24 and Prostate Cancer
16
JUND 19p13.11 AP-1 -JUND and Prostate Cancer
16
ESR2 14q23.2-q23.3 Erb, ESRB, ESTRB, NR3A2, ER-BETA, ESR-BETA -ESR2 and Prostate Cancer
16
MCAM 11q23.3 CD146, MUC18 -MCAM and Prostate Cancer
16
ELK1 Xp11.23 -ELK1 and Prostate Cancer
15
CASP9 1p36.21 MCH6, APAF3, APAF-3, PPP1R56, ICE-LAP6 -CASP9 and Prostate Cancer
15
RARB 3p24.2 HAP, RRB2, NR1B2, MCOPS12, RARbeta1 -RARB and Prostate Cancer
15
HSD3B1 1p12 HSD3B, HSDB3, HSDB3A, SDR11E1, 3BETAHSD -HSD3B1 and Prostate Cancer
15
FASN 17q25.3 FAS, OA-519, SDR27X1 -FASN and Prostate Cancer
15
MIRLET7C 21q21.1 LET7C, let-7c, MIRNLET7C, hsa-let-7c -MicroRNA let-7c and Prostate Cancer
15
HMOX1 22q12.3 HO-1, HSP32, HMOX1D, bK286B10 -HMOX1 and Prostate Cancer
15
VEGFC 4q34.3 VRP, Flt4-L, LMPH1D -VEGFC and Prostate Cancer
15
PITX2 4q25 RS, RGS, ARP1, Brx1, IDG2, IGDS, IHG2, PTX2, RIEG, ASGD4, IGDS2, IRID2, Otlx2, RIEG1 -PITX2 and Prostate Cancer
14
HSD17B2 16q23.3 HSD17, SDR9C2, EDH17B2 -HSD17B2 and Prostate Cancer
14
HSPB1 7q11.23 CMT2F, HMN2B, HSP27, HSP28, Hsp25, SRP27, HS.76067, HEL-S-102 -HSPB1 and Prostate Cancer
14
ETS2 21q22.2 ETS2IT1 -ETS2 and Prostate Cancer
14
DAB2IP 9q33.2 AIP1, AIP-1, AF9Q34, DIP1/2 -DAB2IP and Prostate Cancer
14
IGFBP2 2q35 IBP2, IGF-BP53 -IGFBP2 and Prostate Cancer
13
FOXP3 Xp11.23 JM2, AIID, IPEX, PIDX, XPID, DIETER -FOXP3 and Prostate Cancer
13
ANXA2 15q22.2 P36, ANX2, LIP2, LPC2, CAL1H, LPC2D, ANX2L4, PAP-IV, HEL-S-270 -ANXA2 and Prostate Cancer
13
MIR126 9q34.3 MIRN126, mir-126, miRNA126 -MIRN126 microRNA, human and Prostate Cancer
13
SPDEF 6p21.3 PDEF, bA375E1.3 -SPDEF and Prostate Cancer
13
EDNRB 13q22.3 ETB, ET-B, ETB1, ETBR, ETRB, HSCR, WS4A, ABCDS, ET-BR, HSCR2 -EDNRB and Prostate Cancer
13
KLF4 9q31.2 EZF, GKLF -KLF4 and Prostate Cancer
13
NCOA3 20q13.12 ACTR, AIB1, RAC3, SRC3, pCIP, AIB-1, CTG26, SRC-3, CAGH16, KAT13B, TNRC14, TNRC16, TRAM-1, bHLHe42 -NCOA3 and Prostate Cancer
13
UBE2C 20q13.12 UBCH10, dJ447F3.2 -UBE2C and Prostate Cancer
12
SREBF1 17p11.2 SREBP1, bHLHd1, SREBP1a, SREBP-1c -SREBF1 and Prostate Cancer
12
BMP7 20q13.31 OP-1 -BMP7 and Prostate Cancer
12
STAT5A 17q21.2 MGF, STAT5 -STAT5A and Prostate Cancer
12
AGR2 7p21.1 AG2, AG-2, HPC8, GOB-4, HAG-2, XAG-2, PDIA17, HEL-S-116 -AGR2 and Prostate Cancer
12
TPD52 8q21.13 D52, N8L, PC-1, PrLZ, hD52 -TPD52 and Prostate Cancer
12
VIP 6q25.2 PHM27 -VIP and Prostate Cancer
12
DKK3 11p15.3 RIG, REIC -DKK3 and Prostate Cancer
12
MXI1 10q25.2 MXI, MAD2, MXD2, bHLHc11 -MXI1 and Prostate Cancer
12
KLF5 13q22.1 CKLF, IKLF, BTEB2 -KLF5 and Prostate Cancer
12
ELK4 1q32.1 SAP1 -ELK4 and Prostate Cancer
12
NFKBIA 14q13.2 IKBA, MAD-3, NFKBI -NFKBIA and Prostate Cancer
12
HOXC6 12q13.13 CP25, HOX3, HOX3C, HHO.C8 -HOXC6 and Prostate Cancer
11
NBN 8q21.3 ATV, NBS, P95, NBS1, AT-V1, AT-V2 -NBN and Prostate Cancer
11
RECK 9p13.3 ST15 -RECK and Prostate Cancer
11
MED1 17q12 PBP, CRSP1, RB18A, TRIP2, PPARBP, CRSP200, DRIP205, DRIP230, PPARGBP, TRAP220 -MED1 and Prostate Cancer
11
MAF 16q23.2 CCA4, AYGRP, c-MAF, CTRCT21 -MAF and Prostate Cancer
11
PTER 10p13 HPHRP, RPR-1 -PTER and Prostate Cancer
11
HSD3B2 1p12 HSDB, HSD3B, SDR11E2 -HSD3B2 and Prostate Cancer
11
FGF1 5q31.3 AFGF, ECGF, FGFA, ECGFA, ECGFB, FGF-1, HBGF1, HBGF-1, GLIO703, ECGF-beta, FGF-alpha -FGF1 and Prostate Cancer
11
JAZF1 7p15.2-p15.1 TIP27, ZNF802 -JAZF1 and Prostate Cancer
11
GPX3 5q33.1 GPx-P, GSHPx-3, GSHPx-P -GPX3 and Prostate Cancer
11
GATA2 3q21.3 DCML, IMD21, NFE1B, MONOMAC -GATA2 and Prostate Cancer
11
NCOA1 2p23 SRC1, KAT13A, RIP160, F-SRC-1, bHLHe42, bHLHe74 -NCOA1 and Prostate Cancer
11
E2F3 6p22.3 E2F-3 -E2F3 and Prostate Cancer
11
CDC25C 5q31.2 CDC25, PPP1R60 -CDC25C and Prostate Cancer
11
EPHB2 1p36.12 DRT, EK5, ERK, CAPB, Hek5, PCBC, EPHT3, Tyro5, BDPLT22 -EPHB2 and Prostate Cancer
11
HMGB1 13q12.3 HMG1, HMG3, HMG-1, SBP-1 -HMGB1 and Prostate Cancer
11
TNFSF11 13q14.11 ODF, OPGL, sOdf, CD254, OPTB2, RANKL, TNLG6B, TRANCE, hRANKL2 -TNFSF11 and Prostate Cancer
11
CTNNA1 5q31.2 MDPT2, CAP102 -CTNNA1 and Prostate Cancer
11
CRP 1q23.2 PTX1 -CRP and Prostate Cancer
11
CASP1 11q22.3 ICE, P45, IL1BC -CASP1 and Prostate Cancer
11
FYN 6q21 SLK, SYN, p59-FYN -FYN and Prostate Cancer
11
CHIA 1p13.2 CHIT2, AMCASE, TSA1902 -CHIA and Prostate Cancer
10
CCN1 1p22.3 GIG1, CYR61, IGFBP10 -CYR61 and Prostate Cancer
10
TMEFF2 2q32.3 TR, HPP1, TPEF, TR-2, TENB2, CT120.2 -TMEFF2 and Prostate Cancer
10
FGF7 15q21.2 KGF, HBGF-7 -FGF7 and Prostate Cancer
10
WNT5A 3p14.3 hWNT5A -WNT5A and Prostate Cancer
10
ERBB4 2q33.3-q34 HER4, ALS19, p180erbB4 -ERBB4 and Prostate Cancer
10
MBD2 18q21.2 DMTase, NY-CO-41 -MBD2 and Prostate Cancer
10
MED12 Xq13.1 OKS, FGS1, HOPA, OPA1, OHDOX, ARC240, CAGH45, MED12S, TNRC11, TRAP230 -MED12 and Prostate Cancer
10
IGFBP5 2q35 IBP5 -IGFBP5 and Prostate Cancer
10
CYP11A1 15q24.1 CYP11A, CYPXIA1, P450SCC -CYP11A1 and Prostate Cancer
10
ATF3 1q32.3 -ATF3 and Prostate Cancer
10
EIF3E 8q23.1 INT6, EIF3S6, EIF3-P48, eIF3-p46 -EIF3E and Prostate Cancer
10
BMP2 20p12.3 BDA2, BMP2A, SSFSC -BMP2 and Prostate Cancer
10
FGFR4 5q35.2 TKF, JTK2, CD334 -FGFR4 and Prostate Cancer
10
SMAD1 4q31.21 BSP1, JV41, BSP-1, JV4-1, MADH1, MADR1 -SMAD1 and Prostate Cancer
10
CCNA2 4q27 CCN1, CCNA -CCNA2 and Prostate Cancer
10
TLR9 3p21.2 CD289 -TLR9 and Prostate Cancer
10
MCL1 1q21.2 TM, EAT, MCL1L, MCL1S, Mcl-1, BCL2L3, MCL1-ES, bcl2-L-3, mcl1/EAT -MCL1 and Prostate Cancer
10
SUZ12 17q11.2 CHET9, JJAZ1 -SUZ12 and Prostate Cancer
10
BNIP3 10q26.3 NIP3 -BNIP3 and Prostate Cancer
10
AKT3 1q43-q44 MPPH, PKBG, MPPH2, PRKBG, STK-2, PKB-GAMMA, RAC-gamma, RAC-PK-gamma -AKT3 and Prostate Cancer
10
MIF 22q11.23 GIF, GLIF, MMIF -MIF and Prostate Cancer
10
NCOR1 17p12-p11.2 N-CoR, TRAC1, N-CoR1, hN-CoR, PPP1R109 -NCOR1 and Prostate Cancer
10
DLC1 8p22 HP, ARHGAP7, STARD12, p122-RhoGAP -DLC1 and Prostate Cancer
10
SOD1 21q22.11 ALS, SOD, ALS1, IPOA, hSod1, HEL-S-44, homodimer -SOD1 and Prostate Cancer
10
IRS1 2q36 HIRS-1 -IRS1 and Prostate Cancer
10
CCR2 3p21.31 CKR2, CCR-2, CCR2A, CCR2B, CD192, CKR2A, CKR2B, CMKBR2, MCP-1-R, CC-CKR-2 -CCR2 and Prostate Cancer
9
EPHX1 1q42.12 MEH, EPHX, EPOX, HYL1 -EPHX1 and Prostate Cancer
9
CREB1 2q34 CREB -CREB1 and Prostate Cancer
9
FOXA2 20p11.21 HNF3B, TCF3B -FOXA2 and Prostate Cancer
9
ALOX15 17p13.2 12-LOX, 15LOX-1, 15-LOX-1 -ALOX15 and Prostate Cancer
9
CCR5 3p21.31 CKR5, CCR-5, CD195, CKR-5, CCCKR5, CMKBR5, IDDM22, CC-CKR-5 -CCR5 and Prostate Cancer
9
PGK1 Xq21.1 PGKA, MIG10, HEL-S-68p -PGK1 and Prostate Cancer
9
CDH2 18q12.1 CDHN, NCAD, CD325, CDw325 -CDH2 and Prostate Cancer
9
COL18A1 21q22.3 KS, KNO, KNO1 -COL18A1 and Prostate Cancer
9
HOXB13 17q21.32 PSGD Germline
-Germline mutations of HOXB13 in Familiar Prostate Cancer?
-rs339331 Polymorphism and Prostate Cancer susceptibility
9
EEF1A1 6q13 CCS3, EF1A, PTI1, CCS-3, EE1A1, EEF-1, EEF1A, EF-Tu, LENG7, eEF1A-1, GRAF-1EF, HNGC:16303 -EEF1A1 and Prostate Cancer
9
RELB 19q13.32 IREL, I-REL, REL-B -RELB and Prostate Cancer
9
PLAU 10q22.2 ATF, QPD, UPA, URK, u-PA, BDPLT5 -PLAU and Prostate Cancer
9
AGO2 8q24.3 PPD, Q10, CASC7, EIF2C2, LINC00980 -AGO2 and Prostate Cancer
9
MECP2 Xq28 RS, RTS, RTT, PPMX, MRX16, MRX79, MRXSL, AUTSX3, MRXS13 -MECP2 and Prostate Cancer
9
PHIP 6q14.1 ndrp, BRWD2, WDR11, DCAF14 -PHIP and Prostate Cancer
9
CAST 5q15 BS-17, PLACK -CAST and Prostate Cancer
9
MCM7 7q22.1 MCM2, CDC47, P85MCM, P1CDC47, PNAS146, PPP1R104, P1.1-MCM3 -MCM7 and Prostate Cancer
9
ASAH1 8p22 AC, PHP, ASAH, PHP32, ACDase, SMAPME -ASAH1 and Prostate Cancer
8
FOXP1 3p13 MFH, QRF1, 12CC4, hFKH1B, HSPC215 -FOXP1 and Prostate Cancer
8
SOX4 6p22.3 EVI16 -SOX4 and Prostate Cancer
8
PLAUR 19q13.31 CD87, UPAR, URKR, U-PAR -PLAUR and Prostate Cancer
8
APOE 19q13.32 AD2, LPG, APO-E, ApoE4, LDLCQ5 -APOE and Prostate Cancer
8
SPRY1 4q28.1 hSPRY1 -SPRY1 and Prostate Cancer
8
TNFRSF25 1p36.31 DR3, TR3, DDR3, LARD, APO-3, TRAMP, WSL-1, GEF720, WSL-LR, PLEKHG5, TNFRSF12 -TNFRSF25 and Prostate Cancer
8
OGG1 3p25.3 HMMH, MUTM, OGH1, HOGG1 -OGG1 and Prostate Cancer
8
NFKB2 10q24.32 p52, p100, H2TF1, LYT10, CVID10, LYT-10, NF-kB2, p49/p100 -NFKB2 and Prostate Cancer
8
HOXA4 7p15.2 HOX1, HOX1D -HOXA4 and Prostate Cancer
8
DAB2 5p13.1 DOC2, DOC-2 -DAB2 and Prostate Cancer
8
CTAG1B Xq28 CTAG, ESO1, CT6.1, CTAG1, LAGE-2, LAGE2B, NY-ESO-1 -CTAG1B and Prostate Cancer
8
NEFL 8p21.2 NFL, NF-L, NF68, CMT1F, CMT2E, PPP1R110 -NEFL and Prostate Cancer
8
CDC6 17q21.2 CDC18L, HsCDC6, MGORS5, HsCDC18 -CDC6 and Prostate Cancer
8
SELENOP 5p12 SeP, SELP, SEPP, SEPP1 -SEPP1 and Prostate Cancer
8
E2F4 16q22.1 E2F-4 -E2F4 and Prostate Cancer
8
ADAM9 8p11.22 MCMP, MDC9, CORD9, Mltng -ADAM9 and Prostate Cancer
8
ARNT 1q21.3 HIF1B, TANGO, bHLHe2, HIF1BETA, HIF-1beta, HIF1-beta, HIF-1-beta -ARNT and Prostate Cancer
8
MAP2K4 17p12 JNKK, MEK4, MKK4, SEK1, SKK1, JNKK1, SERK1, MAPKK4, PRKMK4, SAPKK1, SAPKK-1 -MAP2K4 and Prostate Cancer
8
PWAR1 15q11.2 PAR1, PAR-1, D15S227E -PAR1 and Prostate Cancer
8
KLK5 19q13.41 SCTE, KLKL2, KLK-L2 -KLK5 and Prostate Cancer
8
YBX1 1p34.2 YB1, BP-8, CSDB, DBPB, YB-1, CBF-A, CSDA2, EFI-A, NSEP1, NSEP-1, MDR-NF1 -YBX1 and Prostate Cancer
8
CD14 5q31.3 -CD14 and Prostate Cancer
7
TXNRD1 12q23.3 TR, TR1, TXNR, TRXR1, GRIM-12 -TXNRD1 and Prostate Cancer
7
STAT6 12q13.3 STAT6B, STAT6C, D12S1644, IL-4-STAT -STAT6 and Prostate Cancer
7
S100P 4p16.1 MIG9 -S100P and Prostate Cancer
7
NEDD4 15q21.3 RPF1, NEDD4-1 -NEDD4 and Prostate Cancer
7
SOX11 2p25 MRD27 -SOX11 and Prostate Cancer
7
RICTOR 5p13.1 PIA, AVO3, hAVO3 -RICTOR and Prostate Cancer
7
TP53BP1 15q15.3 TP53, p202, 53BP1, TDRD30, p53BP1 -TP53BP1 and Prostate Cancer
7
CSK 15q24.1 -CSK and Prostate Cancer
7
KRT18 12q13.13 K18, CK-18, CYK18 -KRT18 and Prostate Cancer
7
TFF3 21q22.3 ITF, P1B, TFI -TFF3 and Prostate Cancer
7
GLIPR1 12q21.2 GLIPR, RTVP1, CRISP7 -GLIPR1 and Prostate Cancer
7
TLR6 4p14 CD286 -TLR6 and Prostate Cancer
7
CKAP4 12q23.3 p63, CLIMP-63, ERGIC-63 -CKAP4 and Prostate Cancer
7
AKR1C2 10p15.1 DD, DD2, TDD, BABP, DD-2, DDH2, HBAB, HAKRD, MCDR2, SRXY8, DD/BABP, AKR1C-pseudo -AKR1C2 and Prostate Cancer
7
FOXO4 Xq13.1 AFX, AFX1, MLLT7 -FOXO4 and Prostate Cancer
7
GAS6 13q34 AXSF, AXLLG -GAS6 and Prostate Cancer
7
ALOX5 10q11.21 5-LO, 5LPG, LOG5, 5-LOX -ALOX5 and Prostate Cancer
7
CYP1A2 15q24.1 CP12, P3-450, P450(PA) -CYP1A2 and Prostate Cancer
7
TSG101 11p15.1 TSG10, VPS23 -TSG101 and Prostate Cancer
7
PON1 7q21.3 ESA, PON, MVCD5 -PON1 and Prostate Cancer
7
TNFRSF10A 8p21.3 DR4, APO2, CD261, TRAILR1, TRAILR-1 -TNFRSF10A and Prostate Cancer
7
ROCK1 18q11.1 ROCK-I, P160ROCK -ROCK1 and Prostate Cancer
7
KLK14 19q13.41 KLK-L6 -KLK14 and Prostate Cancer
7
SSTR5 16p13.3 SS-5-R -SSTR5 and Prostate Cancer
7
LIG4 13q33.3 LIG4S -LIG4 and Prostate Cancer
7
IRS2 13q34 IRS-2 -IRS2 and Prostate Cancer
7
CDH13 16q23.3 CDHH, P105 -CDH13 and Prostate Cancer
7
CXCL5 4q13.3 SCYB5, ENA-78 -CXCL5 and Prostate Cancer
7
IGFBP1 7p12.3 AFBP, IBP1, PP12, IGF-BP25, hIGFBP-1 -IGFBP1 and Prostate Cancer
7
SERPINE1 7q22.1 PAI, PAI1, PAI-1, PLANH1 -SERPINE1 and Prostate Cancer
7
IL11 19q13.42 AGIF, IL-11 -IL11 and Prostate Cancer
6
B2M 15q21.1 IMD43 -B2M and Prostate Cancer
6
BMP6 6p24.3 VGR, VGR1 -BMP6 and Prostate Cancer
6
KAT5 11q13.1 TIP, ESA1, PLIP, TIP60, cPLA2, HTATIP, ZC2HC5, HTATIP1 -KAT5 and Prostate Cancer
6
PDK1 2q31.1 -PDK1 and Prostate Cancer
6
BMPR2 2q33-q34 BMR2, PPH1, BMPR3, BRK-3, POVD1, T-ALK, BMPR-II -BMPR2 and Prostate Cancer
6
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 Prostate Cancer
6
SKP1 5q31.1 OCP2, p19A, EMC19, SKP1A, OCP-II, TCEB1L -SKP1 and Prostate Cancer
6
SOCS2 12q22 CIS2, SSI2, Cish2, SSI-2, SOCS-2, STATI2 -SOCS2 and Prostate Cancer
6
DAPK1 9q21.33 DAPK -DAPK1 and Prostate Cancer
6
GHRH 20q11.23 GRF, INN, GHRF -GHRH and Prostate Cancer
6
RARRES1 3q25.32 LXNL, TIG1, PERG-1 -RARRES1 and Prostate Cancer
6
TRPS1 8q23.3 GC79, LGCR -TRPS1 and Prostate Cancer
6
HLA-DRB1 6p21.32 SS1, DRB1, HLA-DRB, HLA-DR1B -HLA-DRB1 and Prostate Cancer
6
NCOR2 12q24 SMRT, TRAC, CTG26, SMRTE, TRAC1, N-CoR2, TNRC14, TRAC-1, SMAP270, SMRTE-tau -NCOR2 and Prostate Cancer
6
CCNB2 15q22.2 HsT17299 -CCNB2 and Prostate Cancer
6
CEACAM1 19q13.2 BGP, BGP1, BGPI -CEACAM1 and Prostate Cancer
6
PPARG 3p25.2 GLM1, CIMT1, NR1C3, PPARG1, PPARG2, PPARgamma -PPARG and Prostate Cancer
6
SPRY2 13q31.1 IGAN3, hSPRY2 -SPRY2 and Prostate Cancer
6
AIDA 1q41 C1orf80 -AIDA and Prostate Cancer
6
KLK10 19q13.41 NES1, PRSSL1 -KLK10 and Prostate Cancer
6
BCAR1 16q23.1 CAS, CAS1, CASS1, CRKAS, P130Cas -BCAR1 and Prostate Cancer
6
IL1B 2q14 IL-1, IL1F2, IL1-BETA -IL1B and Prostate Cancer
6
MST1 3p21 MSP, HGFL, NF15S2, D3F15S2, DNF15S2 -MST1 and Prostate Cancer
6
CXCL14 5q31.1 KEC, KS1, BMAC, BRAK, NJAC, MIP2G, MIP-2g, SCYB14 -CXCL14 and Prostate Cancer
6
CXCR2 2q35 CD182, IL8R2, IL8RA, IL8RB, CMKAR2, CDw128b -CXCR2 and Prostate Cancer
6
SOCS3 17q25.3 CIS3, SSI3, ATOD4, Cish3, SSI-3, SOCS-3 -SOCS3 and Prostate Cancer
6
XRCC6 22q13.2 ML8, KU70, TLAA, CTC75, CTCBF, G22P1 -XRCC6 and Prostate Cancer
6
RBX1 22q13.2 ROC1, RNF75, BA554C12.1 -RBX1 and Prostate Cancer
6
PDGFD 11q22.3 IEGF, SCDGFB, MSTP036, SCDGF-B -PDGFD and Prostate Cancer
6
ACPP 3q22.1 ACP3, 5'-NT, ACP-3 Prognostic
-ACPP expression in Prostate Cancer
6
BAG1 9p13.3 HAP, BAG-1, RAP46 Overexpression
-BAG1 overexpression in Prostate Cancer
6
MIB1 18q11.2 MIB, DIP1, ZZZ6, DIP-1, LVNC7, ZZANK2 -MIB1 and Prostate Cancer
6
FABP5 8q21.13 EFABP, KFABP, E-FABP, PAFABP, PA-FABP -FABP5 and Prostate Cancer
6
SGK1 6q23 SGK -SGK1 and Prostate Cancer
6
FHL2 2q12.2 DRAL, AAG11, FHL-2, SLIM3, SLIM-3 -FHL2 and Prostate Cancer
6
NDRG2 14q11.2 SYLD -NDRG2 and Prostate Cancer
5
DUSP1 5q35.1 HVH1, MKP1, CL100, MKP-1, PTPN10 -DUSP1 and Prostate Cancer
5
NGFR 17q21.33 CD271, p75NTR, TNFRSF16, p75(NTR), Gp80-LNGFR -NGFR and Prostate Cancer
5
TAGLN 11q23.3 SM22, SMCC, TAGLN1, WS3-10 -TAGLN and Prostate Cancer
5
STK4 20q13.12 KRS2, MST1, YSK3 -STK4 and Prostate Cancer
5
KDM4C 9p24.1 GASC1, JHDM3C, JMJD2C, TDRD14C -KDM4C and Prostate Cancer
5
DAXX 6p21.32 DAP6, EAP1, BING2 -DAXX and Prostate Cancer
5
PHLPP1 18q21.33 SCOP, PHLPP, PPM3A, PLEKHE1 -PHLPP1 and Prostate Cancer
5
BTG2 1q32.1 PC3, APRO1, TIS21 -BTG2 and Prostate Cancer
5
KDM6A Xp11.3 UTX, KABUK2, bA386N14.2 -KDM6A and Prostate Cancer
5
MUC6 11p15.5 MUC-6 -MUC6 and Prostate Cancer
5
MYBL2 20q13.12 BMYB, B-MYB -MYBL2 and Prostate Cancer
5
LIMK1 7q11.23 LIMK, LIMK-1 -LIMK1 and Prostate Cancer
5
HBEGF 5q31.3 DTR, DTS, DTSF, HEGFL -HBEGF and Prostate Cancer
5
CD151 11p15.5 GP27, MER2, RAPH, SFA1, PETA-3, TSPAN24 -CD151 and Prostate Cancer
5
PPIA 7p13 CYPA, CYPH, HEL-S-69p -PPIA and Prostate Cancer
5
PKD1 16p13.3 PBP, PC1, Pc-1, TRPP1 -PKD1 and Prostate Cancer
5
HIP1 7q11.23 SHON, HIP-I, ILWEQ, SHONbeta, SHONgamma -HIP1 and Prostate Cancer
5
ABCA1 9q31.1 TGD, ABC1, CERP, ABC-1, HDLDT1 -ABCA1 and Prostate Cancer
5
HRK 12q24.22 DP5, HARAKIRI -HRK and Prostate Cancer
5
CHGA 14q32.12 CGA -CHGA and Prostate Cancer
5
WEE1 11p15.4 WEE1A, WEE1hu -WEE1 and Prostate Cancer
5
ZBTB7A 19p13.3 LRF, FBI1, FBI-1, TIP21, ZBTB7, ZNF857A, pokemon -ZBTB7A and Prostate Cancer
5
BIRC7 20q13.33 KIAP, LIVIN, MLIAP, RNF50, ML-IAP -BIRC7 and Prostate Cancer
5
XAF1 17p13.1 BIRC4BP, XIAPAF1, HSXIAPAF1 -XAF1 and Prostate Cancer
5
GREB1 2p25.1 -GREB1 and Prostate Cancer
5
SLCO1B3 12p12.2 LST3, HBLRR, LST-2, OATP8, OATP-8, OATP1B3, SLC21A8, LST-3TM13 -SLCO1B3 and Prostate Cancer
5
TNFRSF10B 8p21.3 DR5, CD262, KILLER, TRICK2, TRICKB, ZTNFR9, TRAILR2, TRICK2A, TRICK2B, TRAIL-R2, KILLER/DR5 -TNFRSF10B and Prostate Cancer
5
TLR2 4q31.3 TIL4, CD282 -TLR2 and Prostate Cancer
5
IL18 11q23.1 IGIF, IL-18, IL-1g, IL1F4 -IL18 and Prostate Cancer
5
UGT1A1 2q37 GNT1, UGT1, UDPGT, UGT1A, HUG-BR1, BILIQTL1, UDPGT 1-1 -UGT1A1 and Prostate Cancer
5
TES 7q31.2 TESS, TESS-2 -TES and Prostate Cancer
5
TRAF6 11p12 RNF85, MGC:3310 -TRAF6 and Prostate Cancer
5
GSTA1 6p12.2 GST2, GTH1, GSTA1-1, GST-epsilon -GSTA1 and Prostate Cancer
5
HSD17B1 17q21.2 E2DH, HSD17, EDHB17, EDH17B2, SDR28C1, 17-beta-HSD, 20-alpha-HSD -HSD17B1 and Prostate Cancer
5
MX1 21q22.3 MX, MxA, IFI78, IFI-78K -MX1 and Prostate Cancer
5
KPNA2 17q24.2 QIP2, RCH1, IPOA1, SRP1alpha, SRP1-alpha -KPNA2 and Prostate Cancer
5
FOXP4 6p21.1 hFKHLA -FOXP4 and Prostate Cancer
5
CHUK 10q24.31 IKK1, IKKA, IKBKA, TCF16, NFKBIKA, IKK-alpha -CHUK and Prostate Cancer
5
CCNE2 8q22.1 CYCE2 -CCNE2 and Prostate Cancer
5
THRB 3p24.2 GRTH, PRTH, THR1, ERBA2, NR1A2, THRB1, THRB2, C-ERBA-2, C-ERBA-BETA -THRB and Prostate Cancer
5
CXCL16 17p13.2 SRPSOX, CXCLG16, SR-PSOX -CXCL16 and Prostate Cancer
5
PEBP1 12q24.23 PBP, HCNP, PEBP, RKIP, HCNPpp, PEBP-1, HEL-210, HEL-S-34 -PEBP1 and Prostate Cancer
5
CLMP 11q24.1 ACAM, ASAM, CSBM, CSBS -CLMP and Prostate Cancer
5
TLR1 4p14 TIL, CD281, rsc786, TIL. LPRS5 -TLR1 and Prostate Cancer
5
CXCR1 2q35 C-C, CD128, CD181, CKR-1, IL8R1, IL8RA, CMKAR1, IL8RBA, CDw128a, C-C-CKR-1 -CXCR1 and Prostate Cancer
5
CASR 3q13 CAR, FHH, FIH, HHC, EIG8, HHC1, NSHPT, PCAR1, GPRC2A, HYPOC1 -CASR and Prostate Cancer
5
CUL1 7q36.1 -CUL1 and Prostate Cancer
5
GPRC6A 6q22.1 GPCR, bA86F4.3 -GPRC6A and Prostate Cancer
5
ADIPOR1 1q32.1 CGI45, PAQR1, ACDCR1, CGI-45, TESBP1A -ADIPOR1 and Prostate Cancer
5
PARK7 1p36.23 DJ1, DJ-1, GATD2, HEL-S-67p -PARK7 and Prostate Cancer
5
HNRNPA2B1 7p15.2 RNPA2, HNRPA2, HNRPB1, SNRPB1, HNRNPA2, HNRNPB1, IBMPFD2, HNRPA2B1 -HNRNPA2B1 and Prostate Cancer
5
ADIPOQ 3q27 ACDC, ADPN, APM1, APM-1, GBP28, ACRP30, ADIPQTL1 -ADIPOQ and Prostate Cancer
5
SSTR1 14q21.1 SS1R, SS1-R, SRIF-2, SS-1-R -SSTR1 and Prostate Cancer
4
TGFBR3 1p22.1 BGCAN, betaglycan -TGFBR3 and Prostate Cancer
4
TGFB3 14q24.3 ARVD, LDS5, RNHF, ARVD1, TGF-beta3 -TGFB3 and Prostate Cancer
4
DDX5 17q23.3 p68, HLR1, G17P1, HUMP68 -DDX5 and Prostate Cancer
4
LDLR 19p13.2 FH, FHC, LDLCQ2 -LDLR and Prostate Cancer
4
MTSS1 8q24.13 MIM, MIMA, MIMB -MTSS1 and Prostate Cancer
4
ADAR 1q21.3 DSH, AGS6, G1P1, IFI4, P136, ADAR1, DRADA, DSRAD, IFI-4, K88DSRBP -ADAR and Prostate Cancer
4
PPP2CA 5q31.1 RP-C, PP2Ac, PP2CA, PP2Calpha -PPP2CA and Prostate Cancer
4
FGF10 5p12 -FGF10 and Prostate Cancer
4
ST14 11q24.3 HAI, MTSP1, SNC19, ARCI11, MT-SP1, PRSS14, TADG15, TMPRSS14 -ST14 and Prostate Cancer
4
GAS1 9q21.33 -GAS1 and Prostate Cancer
4
BTG1 12q21.33 APRO2 -BTG1 and Prostate Cancer
4
GNL3 3p21.1 NS, E2IG3, NNP47, C77032 -GNL3 and Prostate Cancer
4
LEPR 1p31.3 OBR, OB-R, CD295, LEP-R, LEPRD -LEPR and Prostate Cancer
4
RAD23B 9q31.2 P58, HR23B, HHR23B -RAD23B and Prostate Cancer
4
IKBKE 1q32.1 IKKE, IKKI, IKK-E, IKK-i -IKBKE and Prostate Cancer
4
ELF3 1q32.1 ERT, ESX, EPR-1, ESE-1 -ELF3 and Prostate Cancer
4
CTBP1 4p16.3 BARS -CTBP1 and Prostate Cancer
4
INHA 2q35 -INHA and Prostate Cancer
4
ADRB2 5q32 BAR, B2AR, ADRBR, ADRB2R, BETA2AR -ADRB2 and Prostate Cancer
4
GADD45B 19p13.3 MYD118, GADD45BETA -GADD45B and Prostate Cancer
4
AMFR 16q13 GP78, RNF45 -AMFR and Prostate Cancer
4
ANXA7 10q22.2 SNX, ANX7, SYNEXIN -ANXA7 and Prostate Cancer
4
CRY1 12q23.3 PHLL1 -CRY1 and Prostate Cancer
4
LCN2 9q34.11 p25, 24p3, MSFI, NGAL -LCN2 and Prostate Cancer
4
SHMT1 17p11.2 SHMT, CSHMT -SHMT1 and Prostate Cancer
4
NKX2-5 5q35.1 CSX, CSX1, VSD3, CHNG5, HLHS2, NKX2E, NKX2.5, NKX4-1 -NKX2-5 and Prostate Cancer
4
PYCARD 16p11.2 ASC, TMS, TMS1, CARD5, TMS-1 -PYCARD and Prostate Cancer
4
YWHAZ 8q22.3 HEL4, YWHAD, KCIP-1, HEL-S-3, HEL-S-93, 14-3-3-zeta -YWHAZ and Prostate Cancer
4
MBD4 3q21.3 MED1 -MBD4 and Prostate Cancer
4
KDM5B 1q32.1 CT31, PLU1, PUT1, MRT65, PLU-1, JARID1B, PPP1R98, RBP2-H1, RBBP2H1A -KDM5B and Prostate Cancer
4
MUC2 11p15.5 MLP, SMUC, MUC-2 -MUC2 and Prostate Cancer
4
CEBPD 8q11.21 CELF, CRP3, C/EBP-delta, NF-IL6-beta -CEBPD and Prostate Cancer
4
PDLIM4 5q31.1 RIL -PDLIM4 and Prostate Cancer
4
NR3C1 5q31.3 GR, GCR, GRL, GCCR, GCRST -NR3C1 and Prostate Cancer
4
PVT1 8q24.21 MYC, LINC00079, NCRNA00079, onco-lncRNA-100 -PVT1 and Prostate Cancer
4
TNFRSF10D 8p21.3 DCR2, CD264, TRUNDD, TRAILR4, TRAIL-R4 -TNFRSF10D and Prostate Cancer
4
ADAM17 2p25 CSVP, TACE, NISBD, ADAM18, CD156B, NISBD1 -ADAM17 and Prostate Cancer
4
AKR1C1 10p15.1 C9, DD1, DDH, DDH1, H-37, HBAB, MBAB, HAKRC, DD1/DD2, 2-ALPHA-HSD, 20-ALPHA-HSD -AKR1C1 and Prostate Cancer
4
MDC1 6p21.33 NFBD1 -MDC1 and Prostate Cancer
4
LTA 6p21.33 LT, TNFB, TNFSF1, TNLG1E -LTA and Prostate Cancer
4
PTK6 20q13.33 BRK -PTK6 and Prostate Cancer
4
ADAMTS1 21q21.3 C3-C5, METH1 -ADAMTS1 and Prostate Cancer
4
IL16 15q25.1 LCF, NIL16, PRIL16, prIL-16 -IL16 and Prostate Cancer
4
PIM2 Xp11.23 -PIM2 and Prostate Cancer
4
UCP2 11q13.4 UCPH, BMIQ4, SLC25A8 -UCP2 and Prostate Cancer
4
NRP1 10p11.22 NP1, NRP, BDCA4, CD304, VEGF165R -NRP1 and Prostate Cancer
4
POU2F1 1q24.2 OCT1, OTF1, oct-1B -POU2F1 and Prostate Cancer
4
FLNA Xq28 FLN, FMD, MNS, OPD, ABPX, CSBS, CVD1, FGS2, FLN1, NHBP, OPD1, OPD2, XLVD, XMVD, FLN-A, ABP-280 -FLNA and Prostate Cancer
4
LZTS1 8p21.3 F37, FEZ1 -LZTS1 and Prostate Cancer
4
NOX1 Xq22.1 MOX1, NOH1, NOH-1, GP91-2 -NOX1 and Prostate Cancer
4
CARS 11p15.4 CARS1, CYSRS, MGC:11246 -CARS and Prostate Cancer
4
PER3 1p36.23 GIG13, FASPS3 -PER3 and Prostate Cancer
4
PRLR 5p13.2 HPRL, MFAB, hPRLrI -PRLR and Prostate Cancer
4
ITGB3 17q21.32 GT, CD61, GP3A, BDPLT2, GPIIIa, BDPLT16 -ITGB3 and Prostate Cancer
4
MT2A 16q13 MT2 -MT2A and Prostate Cancer
4
PER1 17p13.1 PER, hPER, RIGUI -PER1 and Prostate Cancer
4
TNFRSF11B 8q24.12 OPG, TR1, OCIF, PDB5 -TNFRSF11B and Prostate Cancer
4
MBD1 18q21.1 RFT, PCM1, CXXC3 -MBD1 and Prostate Cancer
4
STEAP2 7q21.13 STMP, IPCA1, PUMPCn, STAMP1, PCANAP1 -STEAP2 and Prostate Cancer
4
CMBL 5p15.2 JS-1 -CMBL and Prostate Cancer
3
PPARGC1A 4p15.2 LEM6, PGC1, PGC1A, PGC-1v, PPARGC1, PGC-1alpha, PGC-1(alpha) -PPARGC1A and Prostate Cancer
3
HAS3 16q22.1 -HAS3 and Prostate Cancer
3
PTPRF 1p34.2 LAR, BNAH2 -PTPRF and Prostate Cancer
3
HMMR 5q34 CD168, IHABP, RHAMM -HMMR and Prostate Cancer
3
UGT2B7 4q13.2 UGT2B9, UDPGTH2, UDPGT2B7, UDPGTh-2, UDPGT 2B7, UDPGT 2B9 -UGT2B7 and Prostate Cancer
3
CRTC2 1q21.3 TORC2, TORC-2 -CRTC2 and Prostate Cancer
3
DDIT4 10q22.1 Dig2, REDD1, REDD-1 -DDIT4 and Prostate Cancer
3
KLK6 19q13.41 hK6, Bssp, Klk7, SP59, PRSS9, PRSS18 -KLK6 and Prostate Cancer
3
IRAK2 3p25.3 IRAK-2 -IRAK2 and Prostate Cancer
3
CBX7 22q13.1 -CBX7 and Prostate Cancer
3
FER 5q21.3 TYK3, PPP1R74, p94-Fer -FER and Prostate Cancer
3
MIR10A 17q21.32 MIRN10A, mir-10a, miRNA10A, hsa-mir-10a -None and Prostate Cancer
3
NBL1 1p36.13 NB, DAN, NO3, DAND1, D1S1733E -NBL1 and Prostate Cancer
3
E2F5 8q21.2 E2F-5 -E2F5 and Prostate Cancer
3
SNRPN 15q11.2 SMN, PWCR, SM-D, sm-N, RT-LI, HCERN3, SNRNP-N, SNURF-SNRPN -SNRPN and Prostate Cancer
3
CRY2 11p11.2 HCRY2, PHLL2 -CRY2 and Prostate Cancer
3
APOD 3q29 -APOD and Prostate Cancer
3
DGCR8 22q11.21 Gy1, pasha, DGCRK6, C22orf12 -DGCR8 and Prostate Cancer
3
CTDSPL 3p22.2 PSR1, SCP3, HYA22, RBSP3, C3orf8 -CTDSPL and Prostate Cancer
3
ACTA2 10q23.31 AAT6, ACTSA, MYMY5 -ACTA2 and Prostate Cancer
3
PLA2G2A 1p36.13 MOM1, PLA2, PLA2B, PLA2L, PLA2S, PLAS1, sPLA2 -PLA2G2A and Prostate Cancer
3
PIAS3 1q21.1 ZMIZ5 -PIAS3 and Prostate Cancer
3
TNFRSF10C 8p21.3 LIT, DCR1, TRID, CD263, TRAILR3, TRAIL-R3, DCR1-TNFR -TNFRSF10C and Prostate Cancer
3
IL13RA1 Xq24 NR4, CT19, CD213A1, IL-13Ra -IL13RA1 and Prostate Cancer
3
BIN1 2q14 AMPH2, AMPHL, SH3P9 -BIN1 and Prostate Cancer
3
ATF2 2q32 HB16, CREB2, TREB7, CREB-2, CRE-BP1 -ATF2 and Prostate Cancer
3
TERF2 16q22.1 TRF2, TRBF2 -TERF2 and Prostate Cancer
3
GNAS 20q13.32 AHO, GSA, GSP, POH, GPSA, NESP, SCG6, SgVI, GNAS1, PITA3, C20orf45 -GNAS and Prostate Cancer
3
SUV39H1 Xp11.23 MG44, KMT1A, SUV39H, H3-K9-HMTase 1 -SUV39H1 and Prostate Cancer
3
PLAT 8p11.21 TPA, T-PA -PLAT and Prostate Cancer
3
STRADA 17q23.3 LYK5, PMSE, Stlk, STRAD, NY-BR-96 -STRADA and Prostate Cancer
3
AIFM1 Xq26.1 AIF, AUNX1, CMT2D, CMTX4, COWCK, DFNX5, NADMR, NAMSD, PDCD8, COXPD6 -AIFM1 and Prostate Cancer
3
KDM6B 17p13.1 JMJD3 -KDM6B and Prostate Cancer
3
TGM4 3p21.31 TGP, hTGP -TGM4 and Prostate Cancer
3
RAC3 17q25.3 -RAC3 and Prostate Cancer
3
CARM1 19p13.2 PRMT4 -CARM1 and Prostate Cancer
3
ENO1 1p36.23 NNE, PPH, MPB1, ENO1L1, HEL-S-17 -ENO1 and Prostate Cancer
3
CXCL11 4q21.1 IP9, H174, IP-9, b-R1, I-TAC, SCYB11, SCYB9B -CXCL11 and Prostate Cancer
3
BAG3 10q26.11 BIS, MFM6, BAG-3, CAIR-1 -BAG3 and Prostate Cancer
3
CAV2 7q31.2 CAV -CAV2 and Prostate Cancer
3
SLC7A5 16q24.2 E16, CD98, LAT1, 4F2LC, MPE16, D16S469E -SLC7A5 and Prostate Cancer
3
UPRT Xq13.3 UPP, FUR1 -UPRT and Prostate Cancer
3
LAMB3 1q32.2 AI1A, LAM5, LAMNB1, BM600-125KDA -LAMB3 and Prostate Cancer
3
XIST Xq13.2 SXI1, swd66, DXS1089, DXS399E, LINC00001, NCRNA00001 -XIST and Prostate Cancer
3
SMAD5 5q31.1 DWFC, JV5-1, MADH5 -SMAD5 and Prostate Cancer
3
SEMA3A 7q21.11 HH16, SemD, COLL1, SEMA1, SEMAD, SEMAL, coll-1, Hsema-I, SEMAIII, Hsema-III -SEMA3A and Prostate Cancer
3
NAV1 1q32.1 POMFIL3, UNC53H1, STEERIN1 -NAV1 and Prostate Cancer
3
WNT11 11q13.5 HWNT11 -WNT11 and Prostate Cancer
3
CTSB 8p23.1 APPS, CPSB -CTSB and Prostate Cancer
3
CDT1 16q24.3 DUP, RIS2 -CDT1 and Prostate Cancer
3
PDPK1 16p13.3 PDK1, PDPK2, PDPK2P, PRO0461 -PDPK1 and Prostate Cancer
3
TBX3 12q24.21 UMS, XHL, TBX3-ISO -TBX3 and Prostate Cancer
3
RALBP1 18p11.22 RIP1, RLIP1, RLIP76 -RALBP1 and Prostate Cancer
3
MUC4 3q29 ASGP, MUC-4, HSA276359 -MUC4 and Prostate Cancer
3
MUC5AC 11p15.5 TBM, leB, MUC5, mucin -MUC5AC and Prostate Cancer
3
CUL3 2q36.2 CUL-3, PHA2E -CUL3 and Prostate Cancer
3
ARL11 13q14.2 ARLTS1 -ARL11 and Prostate Cancer
3
LARS 5q32 LRS, LEUS, LFIS, ILFS1, LARS1, LEURS, PIG44, RNTLS, HSPC192, hr025Cl -LARS and Prostate Cancer
3
NEK2 1q32.3 NLK1, RP67, NEK2A, HsPK21, PPP1R111 -NEK2 and Prostate Cancer
3
PLAGL1 6q24.2 ZAC, LOT1, ZAC1 -PLAGL1 and Prostate Cancer
3
LRP1 12q13.3 APR, LRP, A2MR, CD91, APOER, LRP1A, TGFBR5, IGFBP3R -LRP1 and Prostate Cancer
3
IRF3 19q13.33 IIAE7 -IRF3 and Prostate Cancer
3
TM4SF1 3q25.1 L6, H-L6, M3S1, TAAL6 -TM4SF1 and Prostate Cancer
3
IL27 16p12.1-p11.2 p28, IL30, IL-27, IL27A, IL-27A, IL27p28 -IL27 and Prostate Cancer
3
PRDX1 1p34.1 PAG, PAGA, PAGB, PRX1, PRXI, MSP23, NKEFA, TDPX2, NKEF-A -PRDX1 and Prostate Cancer
3
RXRA 9q34.2 NR2B1 -RXRA and Prostate Cancer
3
BMPR1B 4q22.3 ALK6, AMDD, BDA2, ALK-6, BDA1D, CDw293 -BMPR1B and Prostate Cancer
3
FLNC 7q32.1 ABPA, ABPL, FLN2, MFM5, MPD4, RCM5, CMH26, ABP-280, ABP280A -FLNC and Prostate Cancer
3
REG4 1p12 GISP, RELP, REG-IV -REG4 and Prostate Cancer
3
AGTR2 Xq23 AT2, ATGR2, MRX88 -AGTR2 and Prostate Cancer
3
CKS2 9q22.2 CKSHS2 -CKS2 and Prostate Cancer
3
KRT8 12q13 K8, KO, CK8, CK-8, CYK8, K2C8, CARD2 -KRT8 and Prostate Cancer
3
POLL 10q24.32 BETAN, POLKAPPA -POLL and Prostate Cancer
2
GNMT 6p12 -GNMT and Prostate Cancer
2
WNT10B 12q13.12 SHFM6, STHAG8, WNT-12 -WNT10B and Prostate Cancer
2
NKTR 3p22.1 p104 -NKTR and Prostate Cancer
2
SLC43A1 11q12.1 LAT3, PB39, POV1, R00504 -SLC43A1 and Prostate Cancer
2
CCR3 3p21.3 CKR3, CD193, CMKBR3, CC-CKR-3 -CCR3 and Prostate Cancer
2
LTBR 12p13 CD18, TNFCR, TNFR3, D12S370, TNFR-RP, TNFRSF3, TNFR2-RP, LT-BETA-R, TNF-R-III -LTBR and Prostate Cancer
2
INHBA 7p14.1 EDF, FRP -INHBA and Prostate Cancer
2
GPX2 14q23.3 GPRP, GPx-2, GI-GPx, GPRP-2, GPx-GI, GSHPx-2, GSHPX-GI -GPX2 and Prostate Cancer
2
RAP2A 13q32.1 KREV, RAP2, K-REV, RbBP-30 -RAP2A and Prostate Cancer
2
EGR2 10q21.3 AT591, CMT1D, CMT4E, KROX20 -EGR2 and Prostate Cancer
2
CUL4A 13q34 -CUL4A and Prostate Cancer
2
MIR107 10q23.31 MIRN107, miR-107 -MicroRNA mir-107 and Prostate Cancer
2
ACSL3 2q34-q35 ACS3, FACL3, PRO2194 -ACSL3 and Prostate Cancer
2
STIM1 11p15.4 GOK, TAM, TAM1, IMD10, STRMK, D11S4896E -STIM1 and Prostate Cancer
2
VIPR2 7q36.3 VPAC2, VPAC2R, VIP-R-2, VPCAP2R, PACAP-R3, DUP7q36.3, PACAP-R-3, C16DUPq36.3 -VIPR2 and Prostate Cancer
2
HLA-DQB1 6p21.32 IDDM1, CELIAC1, HLA-DQB -HLA-DQB1 and Prostate Cancer
2
FEZ1 11q24.2 UNC-76 -FEZ1 and Prostate Cancer
2
UHRF1 19p13.3 Np95, hNP95, ICBP90, RNF106, TDRD22, hUHRF1, huNp95 -UHRF1 and Prostate Cancer
2
TRIM24 7q33-q34 PTC6, TF1A, TIF1, RNF82, TIF1A, hTIF1, TIF1ALPHA -TRIM24 and Prostate Cancer
2
PTPRK 6q22.33 R-PTP-kappa -PTPRK and Prostate Cancer
2
GNRHR 4q13.2 HH7, GRHR, LRHR, LHRHR, GNRHR1 -GNRHR and Prostate Cancer
2
ST7 7q31.2 HELG, RAY1, SEN4, TSG7, ETS7q, FAM4A, FAM4A1 -ST7 and Prostate Cancer
2
PAWR 12q21 PAR4, Par-4 -PAWR and Prostate Cancer
2
CCNG2 4q21.1 -CCNG2 and Prostate Cancer
2
PIK3CD 1p36.22 APDS, PI3K, IMD14, p110D, P110DELTA -PIK3CD and Prostate Cancer
2
CDH3 16q22.1 CDHP, HJMD, PCAD -CDH3 and Prostate Cancer
2
CTSD 11p15.5 CPSD, CLN10, HEL-S-130P -CTSD and Prostate Cancer
2
NQO2 6p25.2 QR2, DHQV, DIA6, NMOR2 -NQO2 and Prostate Cancer
2
HYAL1 3p21.31 MPS9, NAT6, LUCA1, HYAL-1 -HYAL1 and Prostate Cancer
2
HPGD 4q34.1 PGDH, PGDH1, PHOAR1, 15-PGDH, SDR36C1 -HPGD and Prostate Cancer
2
RRM2B 8q22.3 P53R2, MTDPS8A, MTDPS8B -RRM2B and Prostate Cancer
2
PCGF2 17q12 MEL-18, RNF110, ZNF144 -PCGF2 and Prostate Cancer
2
PSEN2 1q42.13 AD4, PS2, AD3L, STM2, CMD1V -PSEN2 and Prostate Cancer
2
RAD17 5q13.2 CCYC, R24L, RAD24, HRAD17, RAD17SP -RAD17 and Prostate Cancer
2
IER3 6p21.3 DIF2, IEX1, PRG1, DIF-2, GLY96, IEX-1, IEX-1L -IER3 and Prostate Cancer
2
WNT4 1p36.12 WNT-4, SERKAL -WNT4 and Prostate Cancer
2
REST 4q12 WT6, XBR, NRSF -REST and Prostate Cancer
2
IRAK1 Xq28 IRAK, pelle -IRAK1 and Prostate Cancer
2
PRDX6 1q25.1 PRX, p29, AOP2, 1-Cys, NSGPx, aiPLA2, HEL-S-128m -PRDX6 and Prostate Cancer
2
FOXC1 6p25 ARA, IGDA, IHG1, FKHL7, IRID1, RIEG3, FREAC3, FREAC-3 -FOXC1 and Prostate Cancer
2
AIM2 1q23.1-q23.2 PYHIN4 -AIM2 and Prostate Cancer
2
ITGA6 2q31.1 CD49f, VLA-6, ITGA6B -ITGA6 and Prostate Cancer
2
HDGF 1q23.1 HMG1L2 -HDGF and Prostate Cancer
2
PPP2CB 8p12 PP2CB, PP2Abeta -PPP2CB and Prostate Cancer
2
HTATIP2 11p15.1 CC3, TIP30, SDR44U1 -HTATIP2 and Prostate Cancer
2
LASP1 17q12 MLN50, Lasp-1 -LASP1 and Prostate Cancer
2
MMP8 11q22.2 HNC, CLG1, MMP-8, PMNL-CL -MMP8 and Prostate Cancer
2
IMP3 15q24.2 BRMS2, MRPS4, C15orf12 -IMP3 and Prostate Cancer
2
MME 3q25.2 NEP, SFE, CD10, CALLA, CMT2T, SCA43 -MME and Prostate Cancer
2
TFRC 3q29 T9, TR, TFR, p90, CD71, TFR1, TRFR, IMD46 -TFRC and Prostate Cancer
2
ATF6 1q23.3 ACHM7, ATF6A -ATF6 and Prostate Cancer
2
ARNTL 11p15.3 TIC, JAP3, MOP3, BMAL1, PASD3, BMAL1c, bHLHe5 -ARNTL and Prostate Cancer
2
CYP2C19 10q23.33 CPCJ, CYP2C, P450C2C, CYPIIC17, CYPIIC19, P450IIC19 -CYP2C19 and Prostate Cancer
2
IL7 8q21.13 IL-7 -IL7 and Prostate Cancer
2
PAK4 19q13.2 -PAK4 and Prostate Cancer
2
ROCK2 2p24 ROCK-II -ROCK2 and Prostate Cancer
2
BMPR1A 10q23.2 ALK3, SKR5, CD292, ACVRLK3, 10q23del -BMPR1A and Prostate Cancer
2
MCM5 22q12.3 CDC46, MGORS8, P1-CDC46 -MCM5 and Prostate Cancer
2
PINX1 8p23.1 LPTL, LPTS -PINX1 and Prostate Cancer
2
IFITM1 11p15.5 9-27, CD225, IFI17, LEU13, DSPA2a -IFITM1 and Prostate Cancer
2
DKC1 Xq28 DKC, CBF5, DKCX, NAP57, NOLA4, XAP101 -DKC1 and Prostate Cancer
2
MAD1L1 7p22.3 MAD1, PIG9, TP53I9, TXBP181 -MAD1L1 and Prostate Cancer
2
ODC1 2p25 ODC -ODC1 and Prostate Cancer
2
RXRB 6p21.3 NR2B2, DAUDI6, RCoR-1, H-2RIIBP -RXRB and Prostate Cancer
2
TFPI2 7q21.3 PP5, REF1, TFPI-2 -TFPI2 and Prostate Cancer
2
SOX5 12p12.1 L-SOX5, LAMSHF, L-SOX5B, L-SOX5F -SOX5 and Prostate Cancer
2
P2RX7 12q24 P2X7 -P2RX7 and Prostate Cancer
2
NFIB 9p23-p22.3 CTF, NF1-B, NFI-B, NFIB2, NFIB3, NF-I/B, NFI-RED, HMGIC/NFIB -NFIB and Prostate Cancer
2
MIRLET7D 9q22.32 LET7D, let-7d, MIRNLET7D, hsa-let-7d -MicroRNA let-d and Prostate Cancer
2
TRIO 5p15.2 tgat, MEBAS, MRD44, ARHGEF23 -TRIO and Prostate Cancer
2
NSD1 5q35.3 STO, KMT3B, SOTOS, ARA267, SOTOS1 -NSD1 and Prostate Cancer
2
FGF23 12p13.32 ADHR, FGFN, HYPF, HPDR2, PHPTC -FGF23 and Prostate Cancer
2
BUB1B 15q15.1 MVA1, SSK1, BUBR1, Bub1A, MAD3L, hBUBR1, BUB1beta -BUB1B and Prostate Cancer
2
CSMD1 8p23.2 PPP1R24 -CSMD1 and Prostate Cancer
2
PTGER4 5p13.1 EP4, EP4R -PTGER4 and Prostate Cancer
2
CANT1 17q25.3 DBQD, DBQD1, SCAN1, SHAPY, SCAN-1 -CANT1 and Prostate Cancer
2
BTRC 10q24.32 FWD1, FBW1A, FBXW1, bTrCP, FBXW1A, bTrCP1, betaTrCP, BETA-TRCP -BTRC and Prostate Cancer
2
SPRED1 15q14 NFLS, hSpred1, spred-1, PPP1R147 -SPRED1 and Prostate Cancer
2
BIRC2 11q22.2 API1, MIHB, HIAP2, RNF48, cIAP1, Hiap-2, c-IAP1 -BIRC2 and Prostate Cancer
2
KLLN 10q23.31 CWS4, KILLIN -KLLN and Prostate Cancer
2
FRS2 12q15 SNT, SNT1, FRS1A, FRS2A, SNT-1, FRS2alpha -FRS2 and Prostate Cancer
2
TSC22D1 13q14.11 Ptg-2, TSC22, TGFB1I4 -TSC22D1 and Prostate Cancer
2
HERPUD1 16q13 SUP, HERP, Mif1 -HERPUD1 and Prostate Cancer
2
MYCBP 1p34.3 AMY-1 -MYCBP and Prostate Cancer
2
RABEP1 17p13.2 RAB5EP, RABPT5 -RABEP1 and Prostate Cancer
1
PAFAH1B2 11q23.3 HEL-S-303 -PAFAH1B2 and Prostate Cancer
1
MIRLET7I 12q14.1 LET7I, let-7i, MIRNLET7I, hsa-let-7i -MicroRNA let-7i and Prostate Cancer
1
CCNC 6q21 CycC -CCNC and Prostate Cancer
1
SBDS 7q11.21 SDS, SWDS, CGI-97 -SBDS and Prostate Cancer
1
RASSF10 11p15.3 -RASSF10 and Prostate Cancer
1
EPB41 1p35.3 HE, EL1, 4.1R -EPB41 and Prostate Cancer
1
ESPL1 12q13.13 ESP1, SEPA -ESPL1 and Prostate Cancer
1
KAT6B 10q22.2 qkf, MORF, MOZ2, GTPTS, MYST4, ZC2HC6B, querkopf -KAT6B and Prostate Cancer
1
ARHGAP26 5q31.3 GRAF, GRAF1, OPHN1L, OPHN1L1 -ARHGAP26 and Prostate Cancer
1
RMI1 9q21.32 BLAP75, FAAP75, C9orf76 -RMI1 and Prostate Cancer
1
CDR2 16p12.2 Yo, CDR62 -CDR2 and Prostate Cancer
1
LAPTM4B 8q22.1 LC27, LAPTM4beta -LAPTM4B and Prostate Cancer
1
PLA2G16 11q12.3-q13.1 AdPLA, HRSL3, HRASLS3, HREV107, HREV107-1, HREV107-3, H-REV107-1 -PLA2G16 and Prostate Cancer
1
MIR1271 5q35.2 MIRN1271, hsa-mir-1271 -MicroRNA miR-1271and Prostate Cancer
1
SST 3q27.3 SMST -SST and Prostate Cancer
1
SAT2 17p13.1 SSAT2 -SAT2 and Prostate Cancer
1
SNRPE 1q32.1 SME, Sm-E, HYPT11, snRNP-E -SNRPE and Prostate Cancer
1
FBXO11 2p16.3 UBR6, VIT1, FBX11, PRMT9, UG063H01 -FBXO11 and Prostate Cancer
1
MIR1256 1p36.12 MIRN1256, hsa-mir-1256 -MicroRNA miR-1256 and Prostate Cancer
1
KMT2A 11q23.3 HRX, MLL, MLL1, TRX1, ALL-1, CXXC7, HTRX1, MLL1A, WDSTS -KMT2A and Prostate Cancer
1
MS4A1 11q12.2 B1, S7, Bp35, CD20, CVID5, MS4A2, LEU-16 -MS4A1 and Prostate Cancer
1
HMGN2P46 15q21.1 D-PCa-2, C15orf21 -HMGN2P46 and Prostate Cancer
1
LARGE1 22q12.3 LARGE, MDC1D, MDDGA6, MDDGB6 -LARGE1 and Prostate Cancer
1
SLC22A18 11p15.4 HET, ITM, BWR1A, IMPT1, TSSC5, ORCTL2, BWSCR1A, SLC22A1L, p45-BWR1A -SLC22A18 and Prostate Cancer
1
FOXG1 14q12 BF1, BF2, QIN, FKH2, HBF2, HFK1, HFK2, HFK3, KHL2, FHKL3, FKHL1, FKHL2, FKHL3, FKHL4, HBF-1, HBF-2, HBF-3, FOXG1A, FOXG1B, FOXG1C, HBF-G2 -FOXG1 and Prostate Cancer
1
ARHGEF12 11q23.3 LARG, PRO2792 -ARHGEF12 and Prostate Cancer
1
GPHN 14q23.3-q24.1 GPH, GEPH, HKPX1, GPHRYN, MOCODC -GPHN and Prostate Cancer
1
LRRC3B 3p24.1 LRP15 -LRRC3B and Prostate Cancer
1
PRRX1 1q24.2 PMX1, PRX1, AGOTC, PHOX1, PRX-1 -PRRX1 and Prostate Cancer
1
DLG1 3q29 hdlg, DLGH1, SAP97, SAP-97, dJ1061C18.1.1 -DLG1 and Prostate Cancer
1
MIR106B 7q22.1 MIRN106B, mir-106b -MIR106B and Prostate Cancer
1
SRPX Xp11.4 DRS, ETX1, SRPX1, HEL-S-83p -SRPX and Prostate Cancer
1
PDE11A 2q31.2 PPNAD2 -PDE11A and Prostate Cancer
1
MYH9 22q12.3 MHA, FTNS, EPSTS, BDPLT6, DFNA17, MATINS, NMMHCA, NMHC-II-A, NMMHC-IIA -MYH9 and Prostate Cancer
1
PCDH10 4q28.3 PCDH19, OL-PCDH -PCDH10 and Prostate Cancer
1
NR0B2 1p36.11 SHP, SHP1 -NR0B2 and Prostate Cancer
1
MTUS1 8p22 ATBP, ATIP, ICIS, MP44, ATIP3, MTSG1 -MTUS1 and Prostate Cancer
1
GSTO1 10q25.1 P28, SPG-R, GSTO 1-1, GSTTLp28, HEL-S-21 -GSTO1 and Prostate Cancer
1
ERRFI1 1p36.23 MIG6, RALT, MIG-6, GENE-33 -ERRFI1 and Prostate Cancer
1
MIR122 18q21.31 MIR122A, MIRN122, mir-122, MIRN122A, miRNA122, miRNA122A, hsa-mir-122 -MIR122 and Prostate Cancer
1
ANP32A 15q23 LANP, MAPM, PP32, HPPCn, PHAP1, PHAPI, I1PP2A, C15orf1 -ANP32A and Prostate Cancer
1
PCDH7 4p15.1 BHPCDH, BH-Pcdh, PPP1R120 -PCDH7 and Prostate Cancer
1
NR3C2 4q31.23 MR, MCR, MLR, NR3C2VIT -NR3C2 and Prostate Cancer
SERPINB2 18q21.33-q22.1 PAI, PAI2, PAI-2, PLANH2, HsT1201 -SERPINB2 and Prostate Cancer
SRY Yp11.2 TDF, TDY, SRXX1, SRXY1 deletion
-Loss of SRY in prostate cancer
MIR1297 13q14.3 MIRN1297, mir-1297, hsa-mir-1297 -MicroRNA miR-1297 and Prostate Cancer
FLCN 17p11.2 BHD, FLCL -FLCN and Prostate Cancer
ERG 21q22.2 p55, erg-3 Intronic Deletion or Translocation
-ERG-TMPRSS2 Fusion in Prostate 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

Sinha AA
Electron Microscopic Analysis of Stem Cells in Human Prostate Cancer, Including Inverted Capsule Embedding Methods for Archival Sections and Falcon Films for Prostate Cancer Cell Lines.
Anticancer Res. 2019; 39(8):4171-4177 [PubMed] Related Publications
BACKGROUND/AIM: Identification of prostatic stem cells in primary prostate tissue sections, organ cultures of prostate and cell lines requires a range of techniques that allows characterization of stem cells for their potential use in the treatment of patients. Isolated cells usually round-up and develop changes in shape, size and cellular characteristics. The aim of this study was to provide a range of methods for identifying prostatic stem cells and characterizing them with regard to ultrastructure, nuclear morphology, cytoplasmic organelles, and/or expression stem cell marker CD133.
MATERIALS AND METHODS: Prostate biopsy and prostatectomy specimens were used for studying prostatic stem cells and their known marker CD133 in tissue sections by light and/or electron microscopy. Inverted capsule embedding was used to study archival metastatic prostate in pelvic nodes and Du145 cell line in a monolayer culture.
RESULTS: Staining for CD133 positively identified stem cells that were found in benign prostatic hyperplasia, benign prostate, and prostate cancer cells. Paraffin embedded sections showed a single type of stem cells, whereas methylene blue-stained Epon sections showed both light and dark stem cells. Electron microscopy showed that both basal and stem cells were closely associated with the basement membrane (basal lamina). Stem cells had smooth plasma and nuclear membranes, a prominent nucleolus, small mitochondria, and few ribosomes. Du145 cells were separated by intercellular spaces in monolayer culture.
CONCLUSION: The inverted capsule embedding method allowed the study of metastasized prostate cancer in pelvic lymph nodes. Our approach enabled the assessment of stem cells in tissue sections by light and electron microscopy.

Cao HM, Wan Z, Wu Y, et al.
Development and internal validation of a novel model and markers to identify the candidates for lymph node metastasis in patients with prostate cancer.
Medicine (Baltimore). 2019; 98(30):e16534 [PubMed] Related Publications
BACKGROUND: High-grade prostate cancer (PCa) has a poor prognosis, and up to 15% of patients worldwide experience lymph node invasion (LNI). To further improve the prediction lymph node invasion in prostate cancer, we adopted risk scores of the genes expression based on the nomogram in guidelines.
METHODS: We analyzed clinical data from 320 PCa patients from the Cancer Genome Atlas database. Weighted gene coexpression network analysis was used to identify the genes that were significantly associated with LNI in PCa (n = 390). Analyses using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases were performed to identify the activated signaling pathways. Univariate and multivariate logistic regression analyses were performed to identify the independent risk factors for the presence of LNI.
RESULTS: We found that patients with actual LNI and predicted LNI had the worst survival outcomes. The 7 most significant genes (CTNNAL1, ENSA, MAP6D1, MBD4, PRCC, SF3B2, TREML1) were selected for further analysis. Pathways in the cell cycle, DNA replication, oocyte meiosis, and 9 other pathways were dramatically activated during LNI in PCa. Multivariate analyses identified that the risk score (odds ratio [OR] = 1.05 for 1% increase, 95% confidence interval [CI]: 1.04-1.07, P < .001), serum PSA level, clinical stage, primary biopsy Gleason grade (OR = 2.52 for a grade increase, 95% CI: 1.27-5.22, P = .096), and secondary biopsy Gleason grade were independent predictors of LNI. A nomogram built using these predictive variables showed good calibration and a net clinical benefit, with an area under the curve (AUC) value of 90.2%.
CONCLUSIONS: In clinical practice, the application of our nomogram might contribute significantly to the selection of patients who are good candidates for surgery with extended pelvic lymph node dissection.

Liu JB, Yan YJ, Shi J, et al.
Upregulation of microRNA-191 can serve as an independent prognostic marker for poor survival in prostate cancer.
Medicine (Baltimore). 2019; 98(29):e16193 [PubMed] Related Publications
MicroRNA-191 (miR-191) has been identified as being upregulated in several types of cancers, and plays the role of oncogene. The expression of miR-191 has been found to be upregulated in prostate cancer tissues as well as cell lines. In this study, we analyzed the correlation of miR-191 expression with clinicopathologic factors and prognosis in prostate cancer.Prostate cancer tissue samples and adjacent normal prostate tissue samples were collected from 146 patients who underwent laparoscopic radical prostatectomy between April 2013 and March 2018. Student two-tailed t-test was used for comparisons of 2 independent groups. The relationships between miR-191 expression and different clinicopathological characteristics were evaluated using the Chi-squared test. Kaplan-Meier survival plots and log-rank tests were used to assess the differences in overall survival of the different subgroups of prostate cancer patients.miR-191 expression was significantly higher in prostate cancer tissues compared with normal adjacent prostate tissues (P < .001). miR-191 expression was observed to be significantly correlated with Gleason score (P < .001), pelvic lymph node metastasis (P = .006), bone metastases (P < .001), and T stage (P = .005). Kaplan-Meier analysis showed that patients with higher levels of miR-191 had significantly poorer survival than those with lower expression of this miRNA in prostate cancer patients (log rank test, P = .011). Multivariate analysis revealed that miR-191 expression (hazard ratio [HR] = 2.311, 95% confidence interval, [CI]: 1.666-9.006; P = .027) was independently associated with the overall survival of prostate cancer patients.Our results demonstrated that miR-191 might serve as an independent prognostic indicator for prostate cancer patients.

Wang Y, Chen L, Guo YL, et al.
[Effect of long-chain non-coding RNA-AC024560.2 on proliferation and invasion of prostate cancer cells by targeted regulation of miR-30a-5p].
Zhonghua Yi Xue Za Zhi. 2019; 99(26):2042-2046 [PubMed] Related Publications

Li Y, He S, Zhan Y, et al.
microRNA-183-3p Inhibits Progression of Human Prostate Cancer by Downregulating High-Mobility Group Nucleosome Binding Domain 5.
DNA Cell Biol. 2019; 38(8):840-848 [PubMed] Related Publications
microRNAs are a class of noncoding RNAs that play important roles in cancer progression. microRNA-183-3p (miR-183-3p) is a novel microRNA that is dysregulated in many kinds of cancers. Our previous studies found high expression and oncologic role of high-mobility group nucleosome binding domain 5 (

Maehana S, Matsumoto Y, Kojima F, Kitasato H
Interleukin-24 Transduction Modulates Human Prostate Cancer Malignancy Mediated by Regulation of Anchorage Dependence.
Anticancer Res. 2019; 39(7):3719-3725 [PubMed] Related Publications
BACKGROUND: Hormone therapy and chemotherapy are not effective for castrate-resistant prostate cancer, thus development of novel treatment strategies is required. Gene therapy involving transient high-copy transfection of interleukin (IL)-24 with an adenoviral vector can exert antitumor activity; however, the effects of stable IL-24 transfection are not fully understood. The aim of this study was to investigate the effects of IL-24 overexpression in prostate cancer cells, in vitro.
MATERIALS AND METHODS: DU145 cells were transfected the IL-24 gene using a retroviral vector. Apoptosis induction was investigated by the cell death detection ELISA, and the gene expression was analyzed by real time RT-PCR.
RESULTS: IL-24 transduction suppressed the growth of prostate cancer and induced tumor cell apoptosis. In addition, up-regulation of epithelial markers and down-regulation of mesenchymal markers were noted, suggesting that tumor aggressiveness was reduced.
CONCLUSION: Introduction of IL-24 displays antitumor activity both by induction of apoptosis and regulation of anchorage dependence.

Lopes MB, Casimiro S, Vinga S
Twiner: correlation-based regularization for identifying common cancer gene signatures.
BMC Bioinformatics. 2019; 20(1):356 [PubMed] Free Access to Full Article Related Publications
BACKGROUND: Breast and prostate cancers are typical examples of hormone-dependent cancers, showing remarkable similarities at the hormone-related signaling pathways level, and exhibiting a high tropism to bone. While the identification of genes playing a specific role in each cancer type brings invaluable insights for gene therapy research by targeting disease-specific cell functions not accounted so far, identifying a common gene signature to breast and prostate cancers could unravel new targets to tackle shared hormone-dependent disease features, like bone relapse. This would potentially allow the development of new targeted therapies directed to genes regulating both cancer types, with a consequent positive impact in cancer management and health economics.
RESULTS: We address the challenge of extracting gene signatures from transcriptomic data of prostate adenocarcinoma (PRAD) and breast invasive carcinoma (BRCA) samples, particularly estrogen positive (ER+), and androgen positive (AR+) triple-negative breast cancer (TNBC), using sparse logistic regression. The introduction of gene network information based on the distances between BRCA and PRAD correlation matrices is investigated, through the proposed twin networks recovery (twiner) penalty, as a strategy to ensure similarly correlated gene features in two diseases to be less penalized during the feature selection procedure.
CONCLUSIONS: Our analysis led to the identification of genes that show a similar correlation pattern in BRCA and PRAD transcriptomic data, and are selected as key players in the classification of breast and prostate samples into ER+ BRCA/AR+ TNBC/PRAD tumor and normal tissues, and also associated with survival time distributions. The results obtained are supported by the literature and are expected to unveil the similarities between the diseases, disclose common disease biomarkers, and help in the definition of new strategies for more effective therapies.

Hu J, Luo H, Xu Y, et al.
The Prognostic Significance of
Cancer Invest. 2019; 37(4-5):199-208 [PubMed] Related Publications
Prostate cancer (PCa) is the most common malignant tumor for men. But the mechanism is unclear.

Drobková H, Jurečeková J, Sivoňová MK, et al.
Associations Between Gene Polymorphisms of Vascular Endothelial Growth Factor and Prostate Cancer.
Anticancer Res. 2019; 39(6):2903-2909 [PubMed] Related Publications
BACKGROUND/AIM: The aim of this study was to evaluate the association between selected polymorphisms of the vascular endothelial growth factor gene (rs699947, rs144854329, rs833061, rs2010963, rs3025039) and the risk of prostate cancer development and progression.
MATERIALS AND METHODS: The present study included 446 patients with prostate cancer and 241 healthy men. Genotyping was performed by polymerase-chain reaction-restriction fragment length polymorphism analysis.
RESULTS: No significant association between the individual polymorphisms studied and the risk of prostate cancer development was detected. A statistically significantly increased risk of prostate cancer development associated with the presence of 9 or 10 risky alleles was found considering the whole group of patients, as well as in patients with low-grade carcinomas (Gleason score <7).
CONCLUSION: Individual polymorphisms of VEGF do not appear to contribute to prostate cancer. However, a combination of risky alleles of the studied polymorphisms significantly increases the risk of prostate cancer in Slovak patients.

Toropovsky AN, Nikitin AG, Pavlova ON, Viktorov DA
[Perspectives of improvement of the diagnosis of prostate cancer based on analysis of PCA3 gene expression].
Urologiia. 2019; (2):82-86 [PubMed] Related Publications
Prostate cancer is the second leading cause of cancer death. The widespread introduction into the clinical practice of test for prostate specific antigen (PSA) led to an increase in the number of prostate biopsies performed. At the same time, a decrease in the threshold of age-specific PSA standards has resulted in an increase in the number of unnecessary biopsies. In this regard, a need has arisen for new prostate cancer biomarkers. PCA3 is a non-coding mRNA that is exclusively expressed by prostate cells. Currently, three generations of test diagnostic systems based on the quantitative analysis of the PCA3 mRNA in the urine or its cell sediment has already developed, and they differ in the type of material studied and the method for estimating the amount of PCA3 mRNA. Clinical studies of the developed test systems have shown that a high level of PCA3 expression in the patients urine correlates with the probability of detecting prostate cancer. PCA3 test has higher positive and negative predictive values than previously used PSA test. These data are repeatedly confirmed by studies conducted in different clinics. Thus, the introduction of the method of quantitative determination of PCA3 in clinical practice can significantly improve the efficiency of diagnosis of prostate cancer and reduce the number of unnecessary biopsies.

Lindh C, Kis L, Delahunt B, et al.
PD-L1 expression and deficient mismatch repair in ductal adenocarcinoma of the prostate.
APMIS. 2019; 127(8):554-560 [PubMed] Related Publications
This study aimed to investigate the expression of programmed death receptor ligand 1 (PD-L1) and deficient mismatch repair (dMMR) in ductal adenocarcinoma of the prostate. A tissue microarray of 32 ductal and 42 grade-matched acinar adenocarcinomas was used. Slides were stained for PD-L1, PD-L2, MMR proteins, CD4 and CD8. PD-L1 expression in tumor cells was only seen in 3% (1/34) of ductal and 5% (2/42) of acinar adenocarcinomas (p = 1.0), while PD-L1 expression in tumor-infiltrating immune cells was seen in 29% (10/34) of ductal and 14% (6/42) of acinar adenocarcinomas (p = 0.16). dMMR, as defined by loss of one or more of the MMR proteins, was identified in 5% (4/73) of cases, including 1 ductal and 3 acinar adenocarcinomas. There was a suggested association between infiltration of CD8+ lymphocytes and ductal subtype (p = 0.04) but not between CD4+ lymphocytes and tumor type (p = 0.28). The study shows that both dMMR and PD-L1 expression is uncommon in tumor cells of both ductal and acinar adenocarcinoma of the prostate, while PD-L1 expression in tumor-infiltrating immune cells is a more common finding.

Echevarria MI, Awasthi S, Cheng CH, et al.
African American Specific Gene Panel Predictive of Poor Prostate Cancer Outcome.
J Urol. 2019; 202(2):247-255 [PubMed] Related Publications
PURPOSE: Most prostate cancer in African American men lacks the ETS (E26 transforming specific) family fusion event (ETS-). We aimed to establish clinically relevant biomarkers in African American men by studying ETS dependent gene expression patterns to identified race specific genes predictive of outcomes.
MATERIALS AND METHODS: Two multicenter cohorts of a total of 1,427 men were used for the discovery and validation (635 and 792 men, respectively) of race specific predictive biomarkers. We used false discovery rate adjusted q values to identify race and ETS dependent genes which were differentially expressed in African American men who experienced biochemical recurrence within 5 years. Principal component modeling along with survival analysis was done to assess the accuracy of the gene panel in predicting recurrence.
RESULTS: We identified 3,047 genes which were differentially expressed based on ETS status. Of these genes 362 were differentially expressed in a race specific manner (false discovery rate 0.025 or less). A total of 81 genes were race specific and over expressed in African American men who experienced biochemical recurrence. The final gene panel included APOD, BCL6, EMP1, MYADM, SRGN and TIMP3. These genes were associated with 5-year biochemical recurrence (HR 1.97, 95% CI 1.27-3.06, p = 0.002) and they improved the predictive accuracy of clinicopathological variables only in African American men (60-month time dependent AUC 0.72).
CONCLUSIONS: In an effort to elucidate biological features associated with prostate cancer aggressiveness in African American men we identified ETS dependent biomarkers predicting early onset biochemical recurrence only in African American men. Thus, these ETS dependent biomarkers representing ideal candidates for biomarkers of aggressive disease in this patient population.

Dudzik P, Trojan SE, Ostrowska B, et al.
The Epigenetic Modifier 5-Aza-2-deoxycytidine Triggers the Expression of
Anticancer Res. 2019; 39(5):2395-2403 [PubMed] Related Publications
BACKGROUND/AIM: During cancer progression cells undergo epithelial-to-mesenchymal transition (EMT). Although EMT is a complex process, recently, it has been reported that CD146 overexpression in prostate cancer cells is sufficient to induce mesenchymal phenotype. The following study aimed to investigate whether the expression of CD146 is altered by an epigenetic modifier in prostate cancer cells, in vitro.
MATERIALS AND METHODS: Three human prostate cancer cell lines were treated with 5-aza-2-deoxycytidine; the expression of CD146 and EMT-related factors was analyzed by RT-PCR and western Blot. The methylation status of the CD146 promoter area was assessed using bisulfite sequencing.
RESULTS: Our data showed that, the expression of CD146 was evidently increased in all three studied cell lines in response to a demethylating agent, both at the mRNA and protein level, suggesting epigenetic regulation of the analyzed gene. However, there was no methylation in the studied CpG island in CD146 gene promoter. Moreover, the demethylating agent induced the expression of EMT-related transcription factors (SNAI1, SNAI2, TWIST1 and ZEB1), the pattern of which differed among the cell lines, as well as alterations in cell morphology; altogether accounting for the mesenchymal phenotype.
CONCLUSION: The demethylating agent 5-aza-2-deoxycytidine triggers the expression of CD146 in prostate cancer cells independently on the methylation status of the analyzed CpG island fragment in CD146 gene promoter. Moreover, demethylation treatment induces a mesenchymal profile in prostate cancer cells.

Li G, Zhang Y, Mao J, et al.
LncRNA TUC338 is overexpressed in prostate carcinoma and downregulates miR-466.
Gene. 2019; 707:224-230 [PubMed] Related Publications
LncRNA TUC338 has recently been characterized as an oncogene in several types of cancer. Our study aimed to characterize the functionality of TUC338 in prostate carcinoma. It was observed that TUC338 was upregulated in tumor tissues comparing to adjacent healthy tissues of prostate carcinoma patients. Plasma levels of TUC338 were also higher in prostate carcinoma patients than in healthy controls. A 5-year follow-up study showed that high plasma level of TUC338 was correlated with poor survival. miR-466 was downregulated in tumor tissues compared with adjacent healthy tissues of prostate carcinoma patients. TUC338 and miR-466 were inversely correlated in tumor tissues. miR-466 overexpression failed to affect TUC338 expression, while TUC338 overexpression led to downregulated miR-466 expression. TUC338 overexpression failed to significantly affect cancer cell proliferation, but promoted cancer cell migration and invasion. MiR-466 overexpression resulted in reduced rates of cancer cell migration and invasion, and also attenuated the effect of TUC338 overexpression. Therefore, TUC338 may serve as an oncogenic lncRNA in prostate carcinoma by downregulating miR-466.

Sciarra A, Gentilucci A, Silvestri I, et al.
Androgen receptor variant 7 (AR-V7) in sequencing therapeutic agents for castratrion resistant prostate cancer: A critical review.
Medicine (Baltimore). 2019; 98(19):e15608 [PubMed] Free Access to Full Article Related Publications
BACKGROUND: androgen receptor variant 7 (AR-V7) has been suggested as potential marker for treatment selection in men with metastatic castration-resistant prostate cancer (mCRPC). The aim of the present review is to critically analyze: frequency of the AR-V7 expression in mCRPC cases-impact of AR-V7 expression on abiraterone, enzalutamide, and taxane therapy.
METHODS: we searched in the Medline and Cochrane Library database from the literature of the past 10 years. We critically evaluated the level of evidence according to the European Association of Urology (EAU) guidelines.
RESULTS: 12 clinical trials were selected. The determination of AR-V7 in peripheral blood using circulating tumor cells mRNA seems to be the preferred method. At baseline, the mean percentage of cases with AR-V7 positivity was 18.3% (range 17.8%-28.8%). All data on mCRPC submitted to enzalutamide or abiraterone reported a significantly (P <.05) lower clinical progression-free survival (CPFS) and overall survival (OS) in AR-V7+ than AR-V7- cases (CPFS hazard ratio [HR]: 2.3; 95% CI 1.1-4.9; OS HR: 3.0; 95% CI 1.4-6.3). In mCRPC cases submitted to chemotherapies data are not homogeneous and some studies showed no association between CPFS or OS and AR-V7 status (OS HR 1.6; 95% CI 0.6-4.4; P = .40).
CONCLUSIONS: the suggestion is that taxane therapy is more efficacious than abiraterone or enzalutamide for men with AR-V7+ CRPC. On the contrary, clinical outcomes did not seem to differ significantly on the basis of the type of therapy used among AR-V7- cases.

Duan Y, Tan Z, Yang M, et al.
PC-3-Derived Exosomes Inhibit Osteoclast Differentiation by Downregulating miR-214 and Blocking NF-
Biomed Res Int. 2019; 2019:8650846 [PubMed] Free Access to Full Article Related Publications
Prostate cancer is a serious disease that can invade bone tissues. These bone metastases can greatly decrease a patient's quality of life, pose a financial burden, and even result in death. In recent years, tumor cell-secreted microvesicles have been identified and proposed to be a key factor in cell interaction. However, the impact of cancer-derived exosomes on bone cells remains unclear. Herein, we isolated exosomes from prostate cancer cell line PC-3 and investigated their effects on human osteoclast differentiation by tartrate-resistant acid phosphatase (TRAP) staining. The potential mechanism was evaluated by qRT-PCR, western blotting, and microRNA transfection experiments. The results showed that PC-3-derived exosomes dramatically inhibited osteoclast differentiation. Marker genes of mature osteoclasts, including CTSK, NFATc1, ACP5, and miR-214, were all downregulated in the presence of PC-3 exosomes. Furthermore, transfection experiments showed that miR-214 downregulation severely impaired osteoclast differentiation, whereas overexpression of miR-214 promoted differentiation. Furthermore, we demonstrated that PC-3-derived exosomes block the NF-

Zanusso C, Dreussi E, Bortolus R, et al.
rs4143815-
Int J Mol Sci. 2019; 20(9) [PubMed] Free Access to Full Article Related Publications
Up to 30-50% of patients with locally advanced prostate cancer (PCa) undergoing radiotherapy (RT) experience biochemical recurrence (BCR). The immune system affects the RT response. Immunogenetics could define new biomarkers for personalization of PCa patients' treatment. The aim of this study is to define the immunogenetic biomarkers of 10 year BCR (primary aim), 10 year overall survival (OS) and 5 year BCR (secondary aims). In this mono-institutional retrospective study, 549 Caucasian patients (a discovery set

Sengupta D, Deb M, Kar S, et al.
miR-193a targets MLL1 mRNA and drastically decreases MLL1 protein production: Ectopic expression of the miRNA aberrantly lowers H3K4me3 content of the chromatin and hampers cell proliferation and viability.
Gene. 2019; 705:22-35 [PubMed] Related Publications
Mixed-lineage leukaemia 1 (MLL1) enzyme plays major role in regulating genes associated with vertebrate development. Cell physiology and homeostasis is regulated by microRNAs in diverse microenvironment. In this investigation we have identified conserved miR-193a target sites within the 3'-UTR of MLL1 gene transcript. Utilizing wild type and mutated 3'-UTR constructs and luciferase reporter assays we have clearly demonstrated that miR-193a directly targets the 3'-UTR region of the MLL1 mRNA. Ectopic expression of miR-193a modulated global H3K4 mono-, di- and tri-methylation levels and affects the expression of CAV1, a gene which is specifically modulated by H3K4me3. To determine the implications of this in vitro finding in aberrant physiological conditions we analyzed prostate cancer tissue samples. In this context miR-193a RNA was undetectable and MLL1 was highly expressed with concomitantly high levels of H3K4me, H3K4me2, and H3K4me3 enrichment in the promoters of MLL1 responsive genes. Finally, we showed that prolonged ectopic expression of miR-193a inhibits growth and cell migration, and induces apoptosis. Thus, while our study unveils amplitude of the epigenome, including miRnome it establishes that; (i) miR-193a directly target MLL1 mRNA, (ii) miR-193a impair MLL1 protein production, (iii) miR-193a reduces the overall methylation marks of the genome.

Zhang J, Wang J, Luan T, et al.
Deubiquitinase USP9X regulates the invasion of prostate cancer cells by regulating the ERK pathway and mitochondrial dynamics.
Oncol Rep. 2019; 41(6):3292-3304 [PubMed] Free Access to Full Article Related Publications
The ubiquitin‑specific protease 9X (USP9X) is a conserved deubiquitinase that has been investigated in several types of human cancer. However, the clinical significance and the biological roles of USP9X in prostate cancer remain unexplored. In the present study, an investigation into the expression and clinical significance of USP9X in prostate cancer revealed that USP9X expression was downregulated in prostate cancer tissues compared with that in healthy tissues. In addition, decreased USP9X expression was associated with a higher Gleason score and local invasion. Depletion of USP9X in prostate cancer LNCaP and PC‑3 cells by small interfering RNA promoted cell invasion and migration. Furthermore, USP9X depletion upregulated matrix metalloproteinase 9 (MMP9) and the phosphorylation of dynamin‑related protein 1 (DRP1). Notably, a significant increase in phosphorylated extracellular signal‑regulated kinase (ERK), an upstream activator of MMP9 and DRP1, was observed. To investigate whether ERK activation was able to increase MMP9 protein levels and induce DRP1 phosphorylation, an ERK inhibitor was used, demonstrating that ERK‑mediated MMP9 production and change in mitochondrial function was critical for the biological function of USP9X in prostate cancer cells. In conclusion, the present study demonstrated that USP9X is downregulated in prostate cancer and functions as an inhibitor of tumor cell invasion, possibly through the regulation of the ERK signaling pathway.

Zhang KG, Zhou YH, Shao YK, et al.
[Novel tumor metastasis suppressorgene LASS2/TMSG1 S248A mutant promotes invasion of prostate cancer cells through increasing ATP6V0C expression].
Beijing Da Xue Xue Bao Yi Xue Ban. 2019; 51(2):210-220 [PubMed] Related Publications
OBJECTIVE: LASS2/TMSG1 gene is a novel tumor metastasis suppressor gene cloned from human prostate cancer cell line PC-3M in 1999 by Department of Pathology,Peking University of Basic Medical Sciences. It was found out that protein encoded by LASS2/TMSG1 could interact with the c subunit of vacuolar-ATPase (ATP6V0C). In this study, we explored the effect of LASS2/TMSG1 and its mutants on proliferation, migration and invasion of human prostate cancer cells and its molecular mechanism.
METHODS: We constructed four LASS2/TMSG1 mutants and stably transfected the variants to human prostate cancer cell line PC-3M-1E8 cell with high metastatic potential. The stable transfectants were identified by qPCR and Western blot through analyzing the expression of LASS2/TMSG1 and ATP6V0C, the cell biology functions of LASS2/TMSG1 and its four mutants were studied using growth curve,MTT assay, soft agar colony formation assay, wound migration assay, Matrigel invasion study and flow cytometry. Furthermore, immunofluorescence was used to analysis the interaction of LASS2/ TMSG1 mutants and ATP6V0C.
RESULTS: LASS2/TMSG1 mRNA and protein in LASS2/TMSG1 group and Mut1-Mut4 groups were higher than that in Vector group; Western blot showed that ATP6V0C protein in LASS2/TMSG1 wild group was lower than that in Vector group, but ATP6V0C protein in LASS2/TMSG1 S248A group was obviously higher than that in Vector group. MTT test and growth curve assay showed growth ability in LASS2/TMSG1 S248A group was increasing compared with other groups from day 5. Soft Agar colony formation experiment showed anchor independent growth ability in LASS2/TMSG1 S248A group was higher than those in the other groups (P<0.05), Cell migrations (from 35.3%±3.2% to 70.3%±3%) in LASS2/TMSG1 S248A group was increasing compared with LASS2/TMSG1 wild group (P<0.01), and more cells passed through Matrigel in LASS2/TMSG1 S248A group compared with LASS2/TMSG1 wild group (from 50±3.2 to 203±6.5, P<0.01), the apoptosis rate in LASS2/TMSG1 S248A group was obviously higher than that in LASS2/TMSG1 wild group (from 7% to 15.1%, P<0.05), and the G0/G1 ratio in LASS2/TMSG1 S248A group was obviously higher than that in LASS2/TMSG1 wild group (from 51.0% to 85.4%). Furthermore, double immunofluorescent staining observed the colocalization between ATP6V0C and LASS2/TMSG1 protein and its mutations, the expression of ATP6V0C in LASS2/TMSG1 S248A group increased significantly compared with the other groups.
CONCLUSION: LASS2/TMSG1 S248A promotes proliferation, migration and invasion of prostate cancer cells through increasing ATP6V0C expression, suggesting that aa248-250 is an important function site for LASS2/TMSG1 in invasion suppression of prostate cancer cells.

Zhang Y, Zhang D, Lv J, et al.
LncRNA SNHG15 acts as an oncogene in prostate cancer by regulating miR-338-3p/FKBP1A axis.
Gene. 2019; 705:44-50 [PubMed] Related Publications
Long non-coding RNAs (lncRNAs) are crucial regulators in the progression of various diseases. Although the role of lncRNAs in prostate cancer (PCa) has been studied in recent years, there are still numerous lncRNAs need to be elucidated. This study aims to detect the role of lncRNA small nucleolar RNA host gene 15 (SNHG15) in human prostate cancer. Using qRT-PCR analysis, we identified the upregulation of SNHG15 in PCa cell lines. Loss-of function assays were conducted to determine the regulatory effect of SNHG15 on PCa cell proliferation, migration and epithelial-mesenchymal transition (EMT). According to the results of functional assays, we found that knockdown of SNHG15 impaired cell viability, suppressed cell proliferation, inhibited cell migration and invasion, reversed EMT progress. All these findings revealed the oncogenic function of SNHG15 in PCa. Mechanism investigation revealed that SNHG15 was located in the cytoplasm of PCa cells and acted as a molecular sponge of microRNA-338-3p (miR-338-3p). Moreover, FKBP prolyl isomerase 1A (FKBP1A) was a target of miR-338-3p. This investigation demonstrated that SNHG15 may serve as a competing endogenous RNA (ceRNA) to regulate miR-338-3p and FKBP1A. Finally, the involvement of miR-338-3p and FKBP1A in SNHG15-mediated biological function was demonstrated by performing rescue assays. In summary, our study revealed the function of a novel pathway in PCa.

Baruah MM, Sharma N
In silico identification of key genes and signaling pathways targeted by a panel of signature microRNAs in prostate cancer.
Med Oncol. 2019; 36(5):43 [PubMed] Related Publications
Accumulating evidence have suggested that some microRNAs are aberrantly expressed in prostate cancer. In our previous work, we had identified a panel of four differentially expressed microRNAs in prostate cancer. In the present study, we have investigated common molecular targets of this panel of miRNAs (DEMs) and key hub genes that can serve as potential candidate biomarkers in the pathogenesis and progression of prostate cancer. A joint bioinformatics approach was employed to identify differentially expressed genes (DEGs) in prostate cancer. Gene enrichment analysis followed by the protein-protein interaction (PPI) network construction and selection of hub genes was further performed using String and Cytoscape, respectively. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the identified hub genes was conducted using the Database for Annotation, Visualization and Integrated Discovery (DAVID) tool. In total, 496 genes were identified to be common targets of DEMs in prostate cancer and 13 key hub genes were identified from three modules of the PPI network of the DEGs. Further top five genes viz Rhoa, PI3KCA, CDC42, MAPK3, TP53 were used for Enrichment analysis which revealed their association with vital cellular and functional pathways in prostate cancer indicating their potential as candidate biomarkers in prostate cancer.

Turanli B, Zhang C, Kim W, et al.
Discovery of therapeutic agents for prostate cancer using genome-scale metabolic modeling and drug repositioning.
EBioMedicine. 2019; 42:386-396 [PubMed] Free Access to Full Article Related Publications
BACKGROUND: Genome-scale metabolic models (GEMs) offer insights into cancer metabolism and have been used to identify potential biomarkers and drug targets. Drug repositioning is a time- and cost-effective method of drug discovery that can be applied together with GEMs for effective cancer treatment.
METHODS: In this study, we reconstruct a prostate cancer (PRAD)-specific GEM for exploring prostate cancer metabolism and also repurposing new therapeutic agents that can be used in development of effective cancer treatment. We integrate global gene expression profiling of cell lines with >1000 different drugs through the use of prostate cancer GEM and predict possible drug-gene interactions.
FINDINGS: We identify the key reactions with altered fluxes based on the gene expression changes and predict the potential drug effect in prostate cancer treatment. We find that sulfamethoxypyridazine, azlocillin, hydroflumethiazide, and ifenprodil can be repurposed for the treatment of prostate cancer based on an in silico cell viability assay. Finally, we validate the effect of ifenprodil using an in vitro cell assay and show its inhibitory effect on a prostate cancer cell line.
INTERPRETATION: Our approach demonstate how GEMs can be used to predict therapeutic agents for cancer treatment based on drug repositioning. Besides, it paved a way and shed a light on the applicability of computational models to real-world biomedical or pharmaceutical problems.

Lee RS, Zhang L, Berger A, et al.
Characterization of the ERG-regulated Kinome in Prostate Cancer Identifies TNIK as a Potential Therapeutic Target.
Neoplasia. 2019; 21(4):389-400 [PubMed] Free Access to Full Article Related Publications
Approximately 50% of prostate cancers harbor the TMPRSS2:ERG fusion, resulting in elevated expression of the ERG transcription factor. Despite the identification of this subclass of prostate cancers, no personalized therapeutic strategies have achieved clinical implementation. Kinases are attractive therapeutic targets as signaling networks are commonly perturbed in cancers. The impact of elevated ERG expression on kinase signaling networks in prostate cancer has not been investigated. Resolution of this issue may identify novel therapeutic approaches for ERG-positive prostate cancers. In this study, we used quantitative mass spectrometry-based kinomic profiling to identify ERG-mediated changes to cellular signaling networks. We identified 76 kinases that were differentially expressed and/or phosphorylated in DU145 cells engineered to express ERG. In particular, the Traf2 and Nck-interacting kinase (TNIK) was markedly upregulated and phosphorylated on multiple sites upon ERG overexpression. Importantly, TNIK has not previously been implicated in prostate cancer. To validate the clinical relevance of these findings, we characterized expression of TNIK and TNIK phosphorylated at serine 764 (pS764) in a localized prostate cancer patient cohort and showed that nuclear enrichment of TNIK (pS764) was significantly positively correlated with ERG expression. Moreover, TNIK protein levels were dependent upon ERG expression in VCaP cells and primary cells established from a prostate cancer patient-derived xenograft. Furthermore, reduction of TNIK expression and activity by silencing TNIK expression or using the TNIK inhibitor NCB-0846 reduced cell viability, colony formation and anchorage independent growth. Therefore, TNIK represents a novel and actionable therapeutic target for ERG-positive prostate cancers that could be exploited to develop new treatments for these patients.

Chen L, Hu W, Li G, et al.
Inhibition of miR-9-5p suppresses prostate cancer progress by targeting StarD13.
Cell Mol Biol Lett. 2019; 24:20 [PubMed] Free Access to Full Article Related Publications
Background: This study aims to investigate the effects of inhibiting microRNA-9-5p (miR-9-5p) on the expression of StAR-related lipid transfer domain containing 13 (StarD13) and the progress of prostate cancer.
Methods: The mRNA expression levels of miR-9-5p and StarD13 were determined in several prostate cancer cell lines. We chose DU145 and PC-3 cells for further research. The CCK8 assay was used to measure the cell viability. The cell invasion and wound-healing assays were respectively applied to evaluate invasion and migration. The expression of E-cadherin (E-cad), N-cadherin (N-cad) and vimentin were measured via western blot. DU145 and PC-3 cells overexpressing StarD13 were generated to investigate the variation in proliferation, invasion and migration. A luciferase reporter assay was used to identify the target of miR-9-5p.
Results: Our results show that miR-9-5p was highly expressed and StarD13 was suppressed in prostate cancer cells. MiR-9-5p inhibition repressed the cells' viability, invasion and migration. It also increased the expression of E-cad and decreased that of N-cad and vimentin. StarD13 overexpression gave the same results as silencing of miR-9-5p: suppression of cell proliferation, invasion and migration. The bioinformatics analysis predicted StarD13 as a target gene of miR-9-5p. Quantitative RT-PCR, western blot analysis and the dual-luciferase reporter assay were employed to confirm the prediction.
Conclusion: Our results show that miR-9-5p plays a powerful role in the growth, invasion, migration and epithelial-mesenchymal transition (EMT) of prostate cancer cells by regulating StarD13. A therapeutic agent inhibiting miR-9-5p could act as a tumor suppressor for prostate cancer.

Xiang Y, Zhang L, Huang Y, et al.
Microarray-based data mining reveals key genes and potential therapeutic drugs for Cadmium-induced prostate cell malignant transformation.
Environ Toxicol Pharmacol. 2019; 68:141-147 [PubMed] Related Publications
Increasing evidence showed that Cadmium (Cd) can accumulate in the body and damage cells, resulting in cancerigenesis of the prostate with complex mechanisms. In the present study, we aimed to explore the possible key genes, pathways and therapeutic drugs using bioinformatics methods. Microarray-based data were retrieved and analyzed to screen differentially expressed genes (DEGs) between Cd-treated prostate cells and controls. Then, functions of the DEGs were annotated and hub genes were screened. Next, key genes were selected from the hub genes via validation in a prostate cancer cohort from The Cancer Genome Atlas (TCGA). Afterward, potential drugs were further predicted. Consequently, a gene expression profile, GSE9951, was retrieved. Then, 361 up-regulated and 30 down-regulated DEGs were screened out, which were enriched in various pathways. Among the DEGs, seven hub genes (HSPA5, HSP90AB1, RHOA, HSPD1, MAD2L1, SKP2, and CCT2) were dysregulated in prostate cancer compared to normal controls, and two of them (HSPD1 and CCT2) might influence the prostate cancer prognosis. Lastly, ionomycin was predicted to be a potential agent reversing Cd-induced prostate cell malignant transformation. In summary, the present study provided novel evidence regarding the mechanisms of Cd-induced prostate cell malignant transformation, and identified ionomycin as a potential small molecule against Cd toxicity.

Imtiaz H, Afroz S, Hossain MA, et al.
Genetic polymorphisms in CDH1 and Exo1 genes elevate the prostate cancer risk in Bangladeshi population.
Tumour Biol. 2019; 41(3):1010428319830837 [PubMed] Related Publications
The polymorphisms of invasion suppressor gene CDH1 and DNA mismatch repair gene Exo1 have been reported to play critical role in the development, tumorigenesis, and progression of several kinds of cancers including prostate cancer. This study was designed to analyze the contribution of single-nucleotide polymorphisms of the CDH1 (-160C/A) and Exo1 (K589E) to prostate cancer susceptibility in Bangladeshi population. The study included 100 prostate cancer cases and age-matched 100 healthy controls. Polymerase chain reaction-restriction fragment length polymorphism analysis was used to determine the genetic polymorphisms. A significant association was found between CDH1 -160C/A (rs16260) and Exo1 (rs1047840, K589E) polymorphisms and prostate cancer risk. In case of CDH1 -160C/A polymorphism, the frequencies of the three genotypes C/C,C/A, and A/A were 45%, 48%, and 7% in cases and 63%, 32%, and 5% in controls, respectively. The heterozygote C/A genotype and combined C/A + A/A genotypes showed 2.10-fold (odds ratio = 2.1000, 95% confidence interval = 1.2956-4.0905, p = 0.013) and 2.08-fold (odds ratio = 2.0811, 95% confidence interval = 1.1820-3.6641, p = 0.011) increased risk of prostate cancer, respectively, when compared with homozygous C/C genotypes. The variant A allele also was associated with increased risk of prostate cancer (odds ratio = 1.6901, 95% confidence interval = 1.0740-2.6597, p = 0.0233). In case of Exo1 (K589E) polymorphism, G/A heterozygote, A/A homozygote, and combined G/A + A/A genotypes were found to be associated with 2.30-, 4.85-, and 3.04-fold higher risk of prostate cancer, respectively (odds ratio = 2.3021, 95% confidence interval = 2.956-4.0905, p = 0.0031; odds ratio = 4.8462, 95% confidence interval = 1.0198-23.0284, p = 0.0291; OR = 3.0362, 95% confidence interval = 1.7054-5.4053, p = 0.0001, respectively). The "A" allele showed significant association with increased susceptibility (2.29-fold) to prostate cancer (odds ratio = 2.2955, 95% confidence interval = 1.4529-3.6270, p = 0.0004). Our results suggest that CDH1 -160C/A and Exo1 K589E polymorphisms are associated with increased susceptibility to prostate cancer in Bangladeshi population.

Mamidi TKK, Wu J, Hicks C
Integrating germline and somatic variation information using genomic data for the discovery of biomarkers in prostate cancer.
BMC Cancer. 2019; 19(1):229 [PubMed] Free Access to Full Article Related Publications
BACKGROUND: Prostate cancer (PCa) is the most common diagnosed malignancy and the second leading cause of cancer-related deaths among men in the United States. High-throughput genotyping has enabled discovery of germline genetic susceptibility variants (herein referred to as germline mutations) associated with an increased risk of developing PCa. However, germline mutation information has not been leveraged and integrated with information on acquired somatic mutations to link genetic susceptibility to tumorigenesis. The objective of this exploratory study was to address this knowledge gap.
METHODS: Germline mutations and associated gene information were derived from genome-wide association studies (GWAS) reports. Somatic mutation and gene expression data were derived from 495 tumors and 52 normal control samples obtained from The Cancer Genome Atlas (TCGA). We integrated germline and somatic mutation information using gene expression data. We performed enrichment analysis to discover molecular networks and biological pathways enriched for germline and somatic mutations.
RESULTS: We discovered a signature of 124 genes containing both germline and somatic mutations. Enrichment analysis revealed molecular networks and biological pathways enriched for germline and somatic mutations, including, the PDGF, P53, MYC, IGF-1, PTEN and Androgen receptor signaling pathways.
CONCLUSION: Integrative genomic analysis links genetic susceptibility to tumorigenesis in PCa and establishes putative functional bridges between the germline and somatic variation, and the biological pathways they control.

Ergün S
Cross-Kingdom Gene regulation via miRNAs of Hypericum perforatum (St. John's wort) flower dietetically absorbed: An in silico approach to define potential biomarkers for prostate cancer.
Comput Biol Chem. 2019; 80:16-22 [PubMed] Related Publications
Prostate cancer (PCa) is the most frequent type of cancer in men. Hypericum perforatum (H. Perforatum) extract (HPE) administration provides remarkable decrease of PCa development. H. perforatum contains 7 conserved miRNAs (Hyp-miR-156a, Hyp-miR-156b, Hyp-miR-166, Hyp-miR-390, Hyp-miR-394, Hyp-miR-396 and Hyp-miR-414) with different targets. In this study, we aimed to investigate cross-kingdom gene regulation via miRNAs of H. perforatum flower dietetically absorbed in manner of an in silico approach to define potential biomarkers for PCa. psRNATarget database was used to find human genes targeted by 7 pre-defined H. perforatum miRNAs. We defined the mostly affected gene families from these miRNAs as ZNF, TMEM, SLC and FAM gene families. GeneMANIA database was used to define the most affected genes (TMEM41B and SLC4A7) from these 7 miRNAs. cBioPortal database was used to define alteration frequencies of TMEM41B and SLC4A7 on different types of PCa and to measure the mutual interaction potency and significance of co-occurence in PCa. This analysis showed that neuroendocrine prostate cancer (NEPC) had the highest total mutation frequency (22%) of TMEM41B and SLC4A7 genes. Also, TMEM41B and SLC4A7 genes had an average 2.1% pathway change potential among all different types of PCa. Moreover, TMEM41B and SLC4A7 gene pair was found significantly co-occurrent in PCa (p < 0.001). Finally, via GEPIA database, we used Spearman correlation analysis to measure the correlation degree of TMEM41B and SLC4A7 genes in PCa and found their significant correlation with PCa (p = 1.2 × 10

Renard-Penna R, Gauthé M
The future of molecular and functional imaging in prostate cancer.
Arch Esp Urol. 2019; 72(2):150-156 [PubMed] Related Publications
The major goal of prostate cancer imaging in the next decade will be more accurate disease diagnostic, characterization and staging through the synthesisof anatomic, functional and molecular imaging.Changes are happening regarding the use of prostate MRI for evaluating primary prostate cancer and PET CT for the staging and recurrence staging of prostate cancer.This review presents a multidisciplinary perspective of the role of prostate MRI and molecular imaging in prostate cancer.

Recurrent Structural Abnormalities

Selected list of common recurrent structural abnormalities

Abnormality Type Gene(s)
del(8p22) in Prostate CancerDeletion
ERG-TMPRSS2 Fusion in Prostate CancerIntronic Deletion or TranslocationERG (21q22.2)TMPRSS2 (21q22.3)
ETV1 translocations in Prostate CancerTranslocationETV1 (7p21.2)TMPRSS2 (21q22.3)

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(8p22) in Prostate Cancer

Arbieva ZH, Banerjee K, Kim SY, et al.
High-resolution physical map and transcript identification of a prostate cancer deletion interval on 8p22.
Genome Res. 2000; 10(2):244-57 [PubMed] Free Access to Full Article Related Publications
A genomic interval of approximately 1-1.5 Mb centered at the MSR marker on 8p22 has emerged as a possible site for a tumor suppressor gene, based on high rates of allele loss and the presence of a homozygous deletion found in metastatic prostate cancer. The objective of this study was to prepare a bacterial contig of this interval, integrate the contig with radiation hybrid (RH) databases, and use these resources to identify transcription units that might represent the candidate tumor suppressor genes. Here we present a complete bacterial contig across the interval, which was assembled using 22 published and 17 newly originated STSs. The physical map provides twofold or greater coverage over much of the interval, including 17 BACs, 15 P1s, 2 cosmids, and 1 PAC clone. The position of the selected markers across the interval in relation to the other markers on the larger chromosomal scale was confirmed by RH mapping using the Stanford G3 RH panel. Transcribed units within the deletion region were identified by exon amplification, searching of the Human Transcript Map, placement of unmapped expressed sequence tags (ESTs) from the Radiation Hybrid Database (RHdb), and from other published sources, resulting in the isolation of six unique expressed sequences. The transcript map of the deletion interval now includes two known genes (MSR and N33) and six novel ESTs.

Bova GS, MacGrogan D, Levy A, et al.
Physical mapping of chromosome 8p22 markers and their homozygous deletion in a metastatic prostate cancer.
Genomics. 1996; 35(1):46-54 [PubMed] Related Publications
Numerous studies have implicated the short arm of chromosome 8 as the site of one or more tumor suppressor genes inactivated in carcinogenesis of the prostate, colon, lung, and liver. Previously, we identified a homozygous deletion on chromosome 8p22 in a metastatic prostate cancer. To map this homozygous deletion physically, long-range restriction mapping was performed using yeast artificial chromosomes (YACs) spanning approximately 2 Mb of chromosome band 8p22. Subcloned genomic DNA and cDNA probes isolated by hybrid capture from these YACs were mapped in relation to one another, reinforcing map integrity. Mapped single-copy probes from the region were then applied to DNA isolated from a metastatic prostate cancer containing a chromosome 8p22 homozygous deletion and indicated that its deletion spans 730-970 kb. Candidate genes PRLTS (PDGF-receptor beta-like tumor suppressor) and CTSB (cathepsin B) are located outside the region of homozygous deletion. Généthon marker D8S549 is located approximately at the center of this region of homozygous deletion. Two new microsatellite polymorphisms, D8S1991 and D8S1992, also located within the region of homozygous deletion on chromosome 8p22, are described. Physical mapping places cosmid CI8-2644 telomeric to MSR (macrophage scavenger receptor), the reverse of a previously published map, altering the interpretation of published deletion studies. This work should prove helpful in the identification of candidate tumor suppressor genes in this region.

Familial Prostate Cancer

Hereditary prostate cancer accounts for about 9% of cases. A prostate cancer susceptibility locus (HPC1) on chromosome 1q24-25 was idenified by Smith (1996). However, McIndoe (1997) found no evidence of HPC1 mutation in 49 high-risk families. Also in a study of "small" families [3-5 affected members], Dunsmuir (1998) found less than 8% of cases had allelic loss in HPC1. Other studies suggest that mutations in HPC1 are uncommon and are restricted to people with early onset disease.

Other candidate genes have been proposed. HPCX at chromosome Xq27-28 was identified by a large international linkage study of 360 families (Xu, 1998). Another locus - HPC2 (PCAP) on chromosome 1q42.2-q43 was proposed by Berthon (1998), though a subsequent linkage study (Gibbs, 1999) indicated this gene could only account for a small proportion of cases.

Other specific gene(s) associated with familial prostate cancer have yet to be identified.

Disclaimer: This site is for educational purposes only; it can not be used in diagnosis or treatment.

Cite this page: Cotterill SJ. Prostate Cancer- Molecular Biology, Cancer Genetics Web: http://www.cancer-genetics.org/X0904.htm Accessed:

Creative Commons License
This page in Cancer Genetics Web by Simon Cotterill is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Note: content of abstracts copyright of respective publishers - seek permission where appropriate.

 [Home]    Page last revised: 29 August, 2019     Cancer Genetics Web, Established 1999