First author, year [ref.] Gene(s)/loci investigated
Endpoint Significant SNPs Conclusion Xu (2009) [ 35] 8q24, 17q12, 3p12, 7p15, 7q21, 9q33, 10q11, 11q13, 17q24, 22q13, Xp11 4674, 2329 PCa risk prediction — A risk prediction model, based on the number of risk alleles of 14 SNPs and family history, can predict a patients’ absolute PCa risk. Sun (2011) [ 36] — 4621 PCa risk prediction rs16901979, rs6983267, rs1447295, rs4430796, rs1855962, rs2660753, rs10486567, rs10993994, rs10896449, rs5945619, rs1465618, rs721048, rs12621278, rs10934853, rs17021918, rs7679673, rs9364554, rs2928679, rs1512268, rs16902094, rs920861, rs4962416, rs7127900, rs12418451, rs8102476, rs2735839, rs5759167 Genetic risk prediction models are interesting to identify a subset of high-risk men at early, curable stage Salinas (2009) [ 33] 17q12, 17q24.3, 8q24 2574 PCa risk prediction rs4430796, rs1859962, rs6983561, rs6983267, rs1447295 Genotyping for five SNPs plus family history is associated with a significant elevation in risk for prostate cancer. They do not improve prediction models for assessing who is at risk of getting or dying from the disease Lindström (2012) [ 37] EHBP1, THADA, ITGA6, EEFSEC, PDLIM5, TET2, SLC22A3, JAZF1, LMTK2, NKX3-1, SLC25A37, CPNE3, CNGB3, MSMB, CTBP2, TCF2, KLK3, BIK, NUDT11 15161 PCa risk prediction rs721048, rs1465618, rs12621278, rs2660753, rs4857841, rs17021918, rs12500426, rs7679673, rs9364554, rs10486567, rs6465657, rs6465657, rs1512268, rs2928679, rs4961199, rs1016343, rs7841060, rs16901979, rs620861, rs6983267, rs1447295, rs4242382, rs7837688, rs16902094, rs1571801, rs10993994, rs4962416, rs7127900, rs12418451, rs7931342, rs10896449, rs11649743, rs4430796, rs7501939, rs1859962, rs266849, rs2735839, rs5759167, rs5945572, rs5945619 Incorporating genetic information and family history in prostate cancer risk models can be useful for identifying younger men that might benefit from prostate-specific antigen screening
Macinnis (2011) [ 38] — 2885 PCa risk prediction rs721048, rs1465618, rs12621278, rs2660753, rs17021918, rs12500426, rs7679673, rs9364554, rs10486567, rs6465657, rs10505483, rs6983267, rs1447295, rs2928679, rs1512268, rs10086908, rs620861, rs10993994, rs4962416, rs7931342, rs7127900, rs4430796, rs1859962, rs2735839, rs5759167, rs5945619 The authors developed a risk prediction algorithm for familial prostate cancer, taking into account genotyping of 26 SNPs and family history. The algorithm can be used on pedigrees of an arbitrary size or structure Zheng (2009) [ 32] 3p12, 7q15, 7q21, 8q24, 9q33, 10q11, 10q13, 17q12, 17q24.3, Xp11 4674 PCa risk prediction rs2660753, rs10486567, rs6465657, rs16901979, rs6983267, rs1447295, rs1571801, rs10993994, rs10896449, rs4430796, rs1859962, rs5945619C The predictive performance for prostate cancer using these genetic variants, family history, and age is similar to that of PSA levels Loeb (2009) [ 48] — 1806 Personalized PSA testing rs10993994, rs2735839, rs2659056 Genotype influences the risk of prostate cancer per unit increase in prostate-specific antigen. Combined use could improve prostate specific antigen test performance
Helfand (2013) [ 49] — 964 Personalized PSA testing rs2736098, rs10788160, rs11067228, rs17632542 Genotyping can be used to adjust a man’s measured prostate-specific antigen concentration and potentially delay or prevent unnecessary prostate biopsies Klein (2012) [ 40] JAZF1, MYC, MSMB, NCOA4, IGF2, INS, TH, TPCN2, MYEOV, HNF1B, DPF1, PPP1R14A, SPINT2, KLK3, TTLL1, BIK, NUDT11 3772 PCa risk prediction rs10486567, rs11228565, rs17632542, rs5759167 Prostate cancer risk prediction with SNPs alone is less accurate than with PSA at baseline, with no benefit from combining SNPs with PSA Nam (2009) [ 41] 17q12, 17q24.3, 8q24, ERG, HOGG1-326, KLK2, TNF, 9p22, HPC1, ETV1 3004 Early detection rs1447295, rs1859962, rs1800629, rs2348763 When incorporated into a nomogram, genotype status contributed more significantly than PSA. The positive predictive value of the PSA test ranged from 42% to 94% depending on the number of variant genotypes carried Aly (2011) [ 42] THADA, EHBP1, ITGA6, EEFSEC, PDLIM5, FLJ20032, SLC22A3, JAZF1, LMTK2, NKX3-1, MSMB, CTBP2, HNF1B, PPP1R14A, KLK3, TNRC6B, BIK, NUDT11, 8q24.21, 11q15.5, 11q13.2, 17q24.3 5241 PCa risk prediction rs721048, rs12621278, rs7679673, rs10086908, rs1016343, rs13252298, rs6983561, rs16901979, rs16902094, rs6983267, rs1447295, rs10993994, rs7127900, rs10896449, rs11649743, rs4430796, rs1859962, rs8102476, rs2735839, rs5759167, rs5945619 Using a genetic risk score, implemented in a risk-prediction model, there was a 22.7% reduction in biopsies at a cost of missing a PCa diagnosis in 3% of patients characterized as having an aggressive disease Hirata (2009) [ 70] P53, p21, MDM2, PTEN, GNAS1, bcl2 167 BCR after RP rs2279115 Bcl2 promotor region −938 C/C genotype carriers more frequently show biochemical recurrence than −938 C/A + A/A carriers Perez (2010) [ 58] EGFR 212 BCR after RP rs8844019 Statistically significant association between the SP and prostate biochemical recurrence after radical prostatectomy Morote (2010) [ 71] KLK2, SULT1A1, TLR4 703 BCR after RP rs198977, rs9282861, rs11536889 Predicting biochemical recurrence after radical prostatectomy based on clinicopathological data can be significantly improved by including patient genetic information Audet-Walsh (2011) [ 61] SRD5A1, SRD5A2 846 BCR after RP rs2208532, rs12470143, rs523349, rs4952197, rs518673, rs12470143 Multiple SRD5A1 and SRD5A2 variations are associated with increased/decreased rates of BCR after RP Audet-Walsh (2012) [ 60] HSD17B1, HSD17B2, HSD17B3, HSD17B4, HSD17B5, HSD17B12 526 BCR after RP rs1364287, rs8059915, rs2955162, rs4243229, rs1119933, rs9934209, rs7201637, rs10739847, rs2257157, rs1810711, rs11037662, rs7928523, rs12800235, rs10838151 Twelve SNPs distributed across HSD17B2, HSD17B3, and HSD17B12 were associated with increased risk of BCR in localized PCa after RP Jaboin (2011) [ 67] MMP7 212 BCR after RP rs10895304 The A/G genotype is predictive of decreased recurrence-free survival in patients with clinically localized prostate cancer Wang (2009) [ 68] PCGF2 (MEL-18) 124 BCR after RP rs708692 Patients with the G/G genotype have a significantly higher rate of BCR after RP. Bachmann (2011) [ 69] bcl2 290 BCR after RP rs2279115 The −938 A/A genotype carriers more frequently show biochemical recurrence than −938 C/A + C/C carriers Huang (2010) [ 64] CTNNB1, APC 307 BCR after RP rs3846716 There is a potential prognostic role of the GA/AA genotype of the SNP on BCR after RP. Chang (2013) [ 65] IGF1, IGF1R 320 BCR after RP rs2946834, rs2016347 A genetic interaction between IGF1 rs2946834 and IGF1R rs2016347 is associated with BCR after RP.
Borque (2013) [ 72] KLK3, KLK2, SULT1A1, BGLAP 670 BCR after RP rs2569733, rs198977, rs9282861, rs1800247 A nomogram, including SNPs and clinicopathological factors, improves the preoperative prediction of early BCR after RP Langsenlehner (2011) [ 73] XRCC1 603 RT toxicity rs25489 The XRCC1 Arg280His polymorphism may be protective against the development of high-grade late toxicity after radiotherapy. Damaraju (2006) [ 77] BRCA1, BRCA2, ESR1, XRCC1, XRCC2, XRCC3, NBN, RAD51, RAD2-52, LIG4, ATM, BCL2, TGFB1, MSH6, ERCC2, XPF, NR3C1, CYP1A1, CYP2C9, CYP2C19, CYP3A5, CYP2D6, CYP11B2, CYP17A1 83 RT toxicity rs1805386, rs1052555, rs1800716 SNPs in LIG4, ERC22, and CYP2D6 are putative markers to predict individuals at risk for complications arising from radiation therapy De Langhe (2013) [ 78] TGF β1 322 RT toxicity rs1800469, rs1982073 Radical prostatectomy, the presence of pretreatment nocturia symptoms, and the variant alleles of TGF β1 −509 C > T and codon 10 T > C are identified as factors involved in the development of acute radiation-induced nocturia when treated with IMRT Fachal (2012) [ 79] ATM, ERCC2, LIG4, MLH1, XRCC3 698 RT toxicity rs1799794 The SNP and the mean dose received by the rectum are associated with the development of gastrointestinal toxicity after 3D-CRT. Fachal (2012) [ 80] TGF β1 413 RT toxicity None Neither of the investigated SNPs or haplotypes were found to be associated with the risk of late toxicity. Popanda (2009) [ 81] XRCC1, APEX1, hOGG1, XRCC2, XRCC3, NBN, XPA, ERCC1, XPC, TP53, P21, MDM2 405 RT toxicity rs25487, rs861539 The XRCC1 Arg399Gln polymorphism is associated with an increase in risk for heterozygous individuals and for Gln carriers. For XRCC3 Thr241Met, the Met variant increases the risk in Met carriers Suga (2008) [ 82] SART1, ID3, EPDR1, PAH, XRCC6 197 RT toxicity rs2276015, rs2742946, rs1376264, rs1126758, rs2267437 Two-stage AUC-ROC curve reached a maximum of 0.86 (training set) in predicting late genitourinary morbidity Cesaretti (2005) [ 85] ATM 37 RT toxicity (Brachy) — There is a strong association between sequence variants in the ATM gene and erectile dysfunction/rectal bleeding Cesaretti (2007) [ 84] ATM 108 RT toxicity (Brachy) — The possession of SNPs in the ATM gene is associated with the development of radiation-induced proctitis after brachytherapy Peters (2008) [ 86] TGF β1 141 RT toxicity (Brachy) rs1982073, rs1800469, rs1800471 Presence of certain TGF β1 genotypes is associated with the development of both erectile dysfunction and late rectal bleeding in patients treated with radiotherapy. Pugh (2009) [ 87] ATM, BRCA1, ERCC2, H2AFX, LIG4, MDC1, MRE11A, RAD50 41 RT toxicity (Brachy) rs28986317 The high toxicity group is enriched for at least one LIG4 SNP. One SNP in MDC1 is associated with increased radiosensitivity. Burri (2008) [ 88] SOD2, XRCC1, XRCC3 135 RT toxicity rs25489, rs4880, rs861539 A XRCC1 SNP is associated with erectile dysfunction. A combination of a SNP in SOD2 and XRCC3 is associated with late rectal bleeding Barnett (2012) [ 89] ABCA1, ALAD, APEX1, ATM, BAX, CD44, CDKN1A, DCLRE1C, EPDR1, ERCC2, ERCC4, GSTA1, GSTP1, HIF1A, IL12RB2, LIG3, LIG4, MED2L2, MAP3K7, MAT1A, MLH1, MPO, MRE11A, MSH2, NEIL3, NFE2L2, NOS3, PAH, PRKDC, PTTG1, RAD17, RAD21, RAD9A, REV3L, SART1, SH3GL1, SOD2, TGFB1, TGFB3, TP53, XPC, XRCC1, XRCC3, XRCC5, XRCC6 637 RT toxicity None None of the previously reported associations were confirmed by this study, after adjustment for multiple comparisons. The
value distribution of the SNPs tested against overall toxicity score was not different from that expected by chance
Ross (2008) [ 97] AKR1C1, AKR1C2, AKR1C3, AR, CYP11A1, CYP11B1, CYP17A1, CYP19A1, CYP21A2, CYP3A4, DHRS9, HSD17B3, HSD17B4, HSD3B1, HSD3B2, MAOA, SRD5A1, SRD5A2, SREBF2, UGT2B15 529 ADT efficacy rs1870050, rs1856888, rs7737181 Three polymorphisms in separate genes are significantly associated with time to progression during ADT. Teixeira (2008) [ 100] EGF 275 ADT efficacy rs4444903 EGF functional polymorphism may contribute to earlier relapse in ABT patients, supporting the involvement of EGF as an alternative pathway in hormone-resistant prostatic tumors Yang (2011) [ 101] SLCO2B1, SLCO1B3 538 ADT efficacy rs12422149, rs1789693, rs1077858 Three SNPs in SLCO2B1 were associated with time to progression (TTP) on ADT. Patients carrying both SLCO2B1 and SLCO1B3 genotypes, which import androgens more efficiently, exhibited a median 2-year shorter TTP on ADT Teixeira (2013) [ 102] TGFBR2 1765 ADT efficacy — TGFBR2-875GG homozygous patients have an increased risk of an early relapse after ADT. Combining clinicopathological and genetic information resulted in an increased capacity to predict the risk of ADT failure Kohli (2012) [ 103] TRMT11, HSD17B12, PRMT3, WBSCR22, CYP3A4, PRMT2, SULT2B1, SRD5A1, AKR1D1, UGT2A1, SULT1E, HSD3B1, UGT2A3, UGT2B11, UGT2B28, CYP19A1, PRMT7, METTL2B, HSD17B3, LCMT1, UGT2B7, SRD5A2, CYP11B2, CARM1, METTL6, HSD17B1, HEMK1, CYP11B1, ESR1, UGT2B10, SERPINE1, PRMT6, HSD11B1, THBS1, SULT2A1, UGT2B4, PRMT5, PRMT8, HSD3B2, UGT1A4, ARSE, UGT1A8, UGT1A5, UGT1A10, ESR2, LCMT2, UGT1A9, AR, UGT1A6, UGT1A7, AKR1C4, STS, HSD17B8, ARSD, HSD17B2, HSD17B7, UGT1A1, UGT1A3, 304 ADT efficacy rs1268121, rs6900796 TRMT11 showed the strongest association with time to ADT failure, with two of 4 TRMT 11 tagSNPs associated with time to ADT failure. Bao (2011) [ 104] KIF3C, CDON, ETS1, IFI30, has-mir-423, PALLD, ACSL1, GABRA1, SYT9, ZDHHC7, MTRR 601 ADT efficacy rs6728684, rs3737336, rs1045747, rs1071738, rs998754, rs4351800 KIF3C rs6728684, CDON rs3737336, and IFI30 rs1045747 genotypes remained as significant predictors for disease progression in multivariate models that included clinicopathologic predictors. A greater number of unfavorable genotypes were associated with a shorter time to progression and worse prostate cancer-specific survival during ADT. Huang (2012) [ 106] SPRED2, GNPDA2, BNC2, ZNF521, ZNF507, ALPK1, SKAP2, TACC2, SKAP1, KLHL14, NR4A2, FBXO32, AATF 601 ADT efficacy rs16934641, rs3763763, rs2051778, rs3763763 Genetic variants in BNC2, TACC2, and ALPK1 are associated with clinical outcomes after ADT, with a cumulative effect on ACM following ADT of combinations of genotypes across the two loci of interest. Huang (2012) [ 105] ACTN2, NR2F1, ARRDC3, XRCC6BP1, FLT1, PSMD7, SKAP1, FBXO32, FLRT3 601 ADT efficacy rs2939244, rs9508016, rs6504145, rs7830622, rs9508016 Genetic variants in ARRDC3, FLT1, and SKAP1 are significant predictors for PCSM and genetic variants in FBXO32 and FLT1 remained significant predictors for ACM. There was a strong combined genotype effect on PCSM and ACM. Huang (2012) [ 107] BMP5, NCOR2, IRS2, MAP2K6, RXRA, ERG, BMPR1A 601 ADT efficacy rs4862396, rs3734444, rs7986346 Genetic variants in CASP3, BMP5, and IRS2 are associated with ACM. Genetic variation in BMP5 and IRS2 is significantly related to PCSM. Patients carrying a greater number of unfavorable genotypes at the loci of interest have a shorter time to ACM and PCSM during ADT. Tsuchiya (2013) [ 108] IGF-1 251 Metastatic PCa outcome — When the sum of the risk genetic factors in each LD block was considered, patients with all the risk factors had significantly shorter cancer-specific survival than those with 0–2 risk factors. Pastina (2010) [ 112] CYP1B1 60 Docetaxel response rs1056836 The polymorphism is a possible predictive marker of response and clinical outcome to docetaxel in CRPC patients. Sissung (2008) [ 113] CYP1B1 52 Docetaxel response rs1056836 Individuals carrying two copies of the polymorphic variant have a poor prognosis after docetaxel-based therapies compared with individuals carrying at least one copy of the allele. Sissung (2008) [ 114] ABCB1 73 Docetaxel response — Docetaxel-induced neuropathy, neutropenia grade, and overall survival could be linked to ABCB1 allelic variants (diplotypes).