Susceptibility loci associated with prostate cancer progression and mortality.
Gallagher DJ., Vijai J., Cronin AM., Bhatia J., Vickers AJ., Gaudet MM., Fine S., Reuter V., Scher HI., Halldén C., Dutra-Clarke A., Klein RJ., Scardino PT., Eastham JA., Lilja H., Kirchhoff T., Offit K.
PURPOSE: Prostate cancer is a heterogeneous disease with a variable natural history that is not accurately predicted by currently used prognostic tools. EXPERIMENTAL DESIGN: We genotyped 798 prostate cancer cases of Ashkenazi Jewish ancestry treated for localized prostate cancer between June 1988 and December 2007. Blood samples were prospectively collected and de-identified before being genotyped and matched to clinical data. The survival analysis was adjusted for Gleason score and prostate-specific antigen. We investigated associations between 29 single nucleotide polymorphisms (SNP) and biochemical recurrence, castration-resistant metastasis, and prostate cancer-specific survival. Subsequently, we did an independent analysis using a high-resolution panel of 13 SNPs. RESULTS: On univariate analysis, two SNPs were associated (P<0.05) with biochemical recurrence, three SNPs were associated with clinical metastases, and one SNP was associated with prostate cancer-specific mortality. Applying a Bonferroni correction (P<0.0017), one association with biochemical recurrence (P=0.0007) was significant. Three SNPs showed associations on multivariable analysis, although not after correcting for multiple testing. The secondary analysis identified an additional association with prostate cancer-specific mortality in KLK3 (P<0.0005 by both univariate and multivariable analysis). CONCLUSIONS: We identified associations between prostate cancer susceptibility SNPs and clinical end points. The rs61752561 in KLK3 and rs2735839 in the KLK2-KLK3 intergenic region were strongly associated with prostate cancer-specific survival, and rs10486567 in the 7JAZF1 gene were associated with biochemical recurrence. A larger study will be required to independently validate these findings and determine the role of these SNPs in prognostic models.