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Susceptibility loci associated with prostate cancer progression and mortality
David J Gallagher1, Joseph Vijai, Angel M Cronin
1Department of Medicine, Clinical Genetics Service, Sloan-Kettering Institute, Memorial Sloan-Kettering Cancer Center, Albert Einstein College of Medicine, New York, New York 10065, USA.
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.
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