METHODS: We performed a genome-wide survival analysis of cause-specific death in 24,023 prostate cancer patients (3,513 disease-specific deaths) from the PRACTICAL and BPC3 consortia. Top findings were assessed for replication in a Norwegian cohort (CONOR).
RESULTS: We observed no significant association between genetic variants and prostate cancer survival.
CONCLUSIONS: Common genetic variants with large impact on prostate cancer survival were not observed in this study.
IMPACT: Future studies should be designed for identification of rare variants with large effect sizes or common variants with small effect sizes.
OBJECTIVE: To investigate the associations between circulating folate and vitamin B12 concentrations and risk of PCa overall and by disease stage and grade.
DESIGN, SETTING, AND PARTICIPANTS: A study was performed with a nested case-control design based on individual participant data from six cohort studies including 6875 cases and 8104 controls; blood collection from 1981 to 2008, and an average follow-up of 8.9 yr (standard deviation 7.3). Odds ratios (ORs) of incident PCa by study-specific fifths of circulating folate and vitamin B12 were calculated using multivariable adjusted conditional logistic regression.
OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Incident PCa and subtype by stage and grade.
RESULTS AND LIMITATIONS: Higher folate and vitamin B12 concentrations were associated with a small increase in risk of PCa (ORs for the top vs bottom fifths were 1.13 [95% confidence interval (CI), 1.02-1.26], ptrend=0.018, for folate and 1.12 [95% CI, 1.01-1.25], ptrend=0.017, for vitamin B12), with no evidence of heterogeneity between studies. The association with folate varied by tumour grade (pheterogeneity<0.001); higher folate concentration was associated with an elevated risk of high-grade disease (OR for the top vs bottom fifth: 2.30 [95% CI, 1.28-4.12]; ptrend=0.001), with no association for low-grade disease. There was no evidence of heterogeneity in the association of folate with risk by stage or of vitamin B12 with risk by stage or grade of disease (pheterogeneity>0.05). Use of single blood-sample measurements of folate and B12 concentrations is a limitation.
CONCLUSIONS: The association between higher folate concentration and risk of high-grade disease, not evident for low-grade disease, suggests a possible role for folate in the progression of clinically relevant PCa and warrants further investigation.
PATIENT SUMMARY: Folate, a vitamin obtained from foods and supplements, is important for maintaining cell health. In this study, however, men with higher blood folate levels were at greater risk of high-grade (more aggressive) prostate cancer compared with men with lower folate levels. Further research is needed to investigate the possible role of folate in the progression of this disease.
MATERIALS AND METHOD: 180 SNPs, shown to be previously associated with prostate cancer, were used to develop a PHS model in men with European ancestry. A machine-learning approach, LASSO-regularized Cox regression, was used to select SNPs and to estimate their coefficients in the training set (75,596 men). Performance of the resulting model was evaluated in the testing/validation set (6,411 men) with two metrics: (1) hazard ratios (HRs) and (2) positive predictive value (PPV) of prostate-specific antigen (PSA) testing. HRs were estimated between individuals with PHS in the top 5% to those in the middle 40% (HR95/50), top 20% to bottom 20% (HR80/20), and bottom 20% to middle 40% (HR20/50). PPV was calculated for the top 20% (PPV80) and top 5% (PPV95) of PHS as the fraction of individuals with elevated PSA that were diagnosed with clinically significant prostate cancer on biopsy.
RESULTS: 166 SNPs had non-zero coefficients in the Cox model (PHS166). All HR metrics showed significant improvements for PHS166 compared to PHS46: HR95/50 increased from 3.72 to 5.09, HR80/20 increased from 6.12 to 9.45, and HR20/50 decreased from 0.41 to 0.34. By contrast, no significant differences were observed in PPV of PSA testing for clinically significant prostate cancer.
CONCLUSIONS: Incorporating 120 additional SNPs (PHS166 vs PHS46) significantly improved HRs for prostate cancer, while PPV of PSA testing remained the same.
SIGNIFICANCE: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932.
METHODS: In total, 299 SNPs previously associated with prostate cancer were evaluated for inclusion in a new PHS, using a LASSO-regularized Cox proportional hazards model in a training dataset of 72,181 men from the PRACTICAL Consortium. The PHS model was evaluated in four testing datasets: African ancestry, Asian ancestry, and two of European Ancestry-the Cohort of Swedish Men (COSM) and the ProtecT study. Hazard ratios (HRs) were estimated to compare men with high versus low PHS for association with clinically significant, with any, and with fatal prostate cancer. The impact of genetic risk stratification on the positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was also measured.
RESULTS: The final model (PHS290) had 290 SNPs with non-zero coefficients. Comparing, for example, the highest and lowest quintiles of PHS290, the hazard ratios (HRs) for clinically significant prostate cancer were 13.73 [95% CI: 12.43-15.16] in ProtecT, 7.07 [6.58-7.60] in African ancestry, 10.31 [9.58-11.11] in Asian ancestry, and 11.18 [10.34-12.09] in COSM. Similar results were seen for association with any and fatal prostate cancer. Without PHS stratification, the PPV of PSA testing for clinically significant prostate cancer in ProtecT was 0.12 (0.11-0.14). For the top 20% and top 5% of PHS290, the PPV of PSA testing was 0.19 (0.15-0.22) and 0.26 (0.19-0.33), respectively.
CONCLUSIONS: We demonstrate better genetic risk stratification for clinically significant prostate cancer than prior versions of PHS in multi-ancestry datasets. This is promising for implementing precision-medicine approaches to prostate cancer screening decisions in diverse populations.