Table 1.

Listing all the SNPs being discussed in the referred papers.

First author, year [ref.]	Gene(s)/loci investigated	N	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]	TGFβ1	322	RT toxicity	rs1800469, rs1982073	Radical 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, 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]	TGFβ1	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]	TGFβ1	141	RT toxicity (Brachy)	rs1982073, rs1800469, rs1800471	Presence 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, 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 P 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).

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.