Table 1: Listing all the SNPs being discussed in the referred papers.

First author,
year [ref.]
Gene(s)/loci investigated EndpointSignificant SNPsConclusion

Xu (2009) [35]8q24, 17q12, 3p12, 7p15, 7q21, 9q33, 10q11, 11q13, 17q24, 22q13, Xp114674, 2329PCa risk predictionA 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]4621PCa risk predictionrs16901979, 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, rs5759167Genetic risk prediction models are interesting to identify a subset of high-risk men at early, curable stage

Salinas (2009) [33]17q12, 17q24.3, 8q242574PCa risk predictionrs4430796, rs1859962, rs6983561, rs6983267, rs1447295Genotyping 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, NUDT1115161PCa risk predictionrs721048, 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]2885PCa risk predictionrs721048, rs1465618, rs12621278, rs2660753, rs17021918, rs12500426, rs7679673, rs9364554, rs10486567, rs6465657, rs10505483, rs6983267, rs1447295, rs2928679, rs1512268, rs10086908, rs620861, rs10993994, rs4962416, rs7931342, rs7127900, rs4430796, rs1859962, rs2735839, rs5759167, rs5945619The 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, Xp114674PCa risk predictionrs2660753, rs10486567, rs6465657, rs16901979, rs6983267, rs1447295, rs1571801, rs10993994, rs10896449, rs4430796, rs1859962, rs5945619CThe predictive performance for prostate cancer using these genetic variants, family history, and age is similar to that of PSA levels

Loeb (2009) [48]1806Personalized PSA testingrs10993994, rs2735839, rs2659056Genotype 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]964Personalized PSA testingrs2736098, rs10788160, rs11067228, rs17632542Genotyping 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, NUDT113772PCa risk predictionrs10486567, rs11228565, rs17632542, rs5759167Prostate 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, ETV13004Early detectionrs1447295, rs1859962, rs1800629, rs2348763When 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, 17q24.35241PCa risk predictionrs721048, rs12621278, rs7679673, rs10086908, rs1016343, rs13252298, rs6983561, rs16901979, rs16902094, rs6983267, rs1447295, rs10993994, rs7127900, rs10896449, rs11649743, rs4430796, rs1859962, rs8102476, rs2735839, rs5759167, rs5945619Using 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, bcl2167BCR after RPrs2279115Bcl2 promotor region −938 C/C genotype carriers more frequently show biochemical recurrence than −938 C/A + A/A carriers

Perez (2010) [58]EGFR212BCR after RPrs8844019Statistically significant association between the SP and prostate biochemical recurrence after radical prostatectomy

Morote (2010) [71]KLK2, SULT1A1, TLR4703BCR after RPrs198977, rs9282861, rs11536889Predicting biochemical recurrence after radical prostatectomy based on clinicopathological data can be significantly improved by including patient genetic information

Audet-Walsh (2011) [61]SRD5A1, SRD5A2846BCR after RPrs2208532, rs12470143, rs523349, rs4952197, rs518673, rs12470143Multiple SRD5A1 and SRD5A2 variations are associated with increased/decreased rates of BCR after RP

Audet-Walsh (2012) [60]HSD17B1, HSD17B2, HSD17B3, HSD17B4, HSD17B5, HSD17B12526BCR after RPrs1364287, rs8059915, rs2955162, rs4243229, rs1119933, rs9934209, rs7201637, rs10739847, rs2257157, rs1810711, rs11037662, rs7928523, rs12800235, rs10838151Twelve SNPs distributed across HSD17B2, HSD17B3, and HSD17B12 were associated with increased risk of BCR in localized PCa after RP

Jaboin (2011) [67]MMP7212BCR after RPrs10895304The A/G genotype is predictive of decreased recurrence-free survival in patients with clinically localized prostate cancer

Wang (2009) [68]PCGF2 (MEL-18)124BCR after RPrs708692Patients with the G/G genotype have a significantly higher rate of BCR after RP.

Bachmann (2011) [69]bcl2290BCR after RPrs2279115The −938 A/A genotype carriers more frequently show biochemical recurrence than −938 C/A + C/C carriers

Huang (2010) [64]CTNNB1, APC307BCR after RPrs3846716There is a potential prognostic role of the GA/AA genotype of the SNP on BCR after RP.

Chang (2013) [65]IGF1, IGF1R320BCR after RPrs2946834, rs2016347A genetic interaction between IGF1 rs2946834 and IGF1R rs2016347 is associated with BCR after RP.

Borque (2013) [72]KLK3, KLK2, SULT1A1, BGLAP670BCR after RPrs2569733, rs198977, rs9282861, rs1800247A nomogram, including SNPs and clinicopathological factors, improves the preoperative prediction of early BCR after RP

Langsenlehner (2011) [73] XRCC1603RT toxicityrs25489The 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, CYP17A183RT toxicityrs1805386, rs1052555, rs1800716SNPs in LIG4, ERC22, and CYP2D6 are putative markers to predict individuals at risk for complications arising from radiation therapy

De Langhe (2013) [78]TGFβ1322RT toxicityrs1800469, rs1982073Radical prostatectomy, the presence of pretreatment nocturia symptoms, and the variant alleles of TGFβ1 −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, XRCC3698RT toxicityrs1799794The SNP and the mean dose received by the rectum are associated with the development of gastrointestinal toxicity after 3D-CRT.

Fachal (2012) [80]TGFβ1413RT toxicityNoneNeither 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, MDM2405RT toxicityrs25487, rs861539The 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, XRCC6197RT toxicity
rs2276015, rs2742946, rs1376264, rs1126758, rs2267437Two-stage AUC-ROC curve reached a maximum of 0.86 (training set) in predicting late genitourinary morbidity

Cesaretti (2005) [85]ATM37RT toxicity (Brachy)There is a strong association between sequence variants in the ATM gene and erectile dysfunction/rectal bleeding

Cesaretti (2007) [84]ATM108RT toxicity (Brachy)The possession of SNPs in the ATM gene is associated with the development of radiation-induced proctitis after brachytherapy

Peters (2008) [86]TGFβ1141RT toxicity (Brachy)rs1982073, rs1800469, rs1800471Presence of certain TGFβ1 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, RAD5041RT toxicity (Brachy)rs28986317The 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, XRCC3135RT toxicityrs25489, rs4880, rs861539A 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, XRCC6637RT toxicityNoneNone 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, UGT2B15529ADT efficacyrs1870050, rs1856888, rs7737181Three polymorphisms in separate genes are significantly associated with time to progression during ADT.

Teixeira (2008) [100]EGF275ADT efficacyrs4444903EGF 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, SLCO1B3538ADT efficacyrs12422149, rs1789693, rs1077858Three 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]TGFBR21765ADT efficacyTGFBR2-875GG 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, 304ADT efficacyrs1268121, rs6900796TRMT11 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, MTRR601ADT efficacyrs6728684, 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, AATF601ADT efficacyrs16934641, rs3763763, rs2051778, rs3763763Genetic 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, FLRT3601ADT efficacyrs2939244, rs9508016, rs6504145, rs7830622, rs9508016Genetic 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, BMPR1A601ADT efficacyrs4862396, rs3734444, rs7986346Genetic 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-1251Metastatic PCa outcomeWhen 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]CYP1B160Docetaxel responsers1056836The polymorphism is a possible predictive marker of response and clinical outcome to docetaxel in CRPC patients.

Sissung (2008) [113]CYP1B152Docetaxel responsers1056836Individuals 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]ABCB173Docetaxel responseDocetaxel-induced neuropathy, neutropenia grade, and overall survival could be linked to ABCB1 allelic variants (diplotypes).

Listing all the studies being discussed. From left to right: author (ref), genes/loci tested, number of patients included in the cohort, general endpoint of the study, significant SNPs, and conclusions.