Genome-wide Scan Identifies Role for AOX1 in Prostate Cancer Survival.

BACKGROUND: Most men diagnosed with prostate cancer have low-risk cancers. How to predict prostate cancer progression at the time of diagnosis remains challenging.

OBJECTIVE: To identify single nucleotide polymorphisms (SNPs) associated with death from prostate cancer.

DESIGN, SETTING, AND PARTICIPANTS: Blood samples from 11 506 men in Sweden were collected during 1991-1996. Of these, 1053 men were diagnosed with prostate cancer and 245 died from the disease. Stage and grade at diagnosis and outcome information were obtained, and DNA from all cases was genotyped.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: A total of 6 126 633 SNPs were tested for association with prostate-cancer-specific survival time using a Cox proportional hazard model, adjusted for age, stage, and grade at diagnosis. A value of 1×10-6 was used as suggestive significance threshold. Positive candidate SNPs were tested for association with gene expression using expression quantitative trait locus analysis.

RESULTS AND LIMITATIONS: We found 12 SNPs at seven independent loci associated with prostate-cancer-specific survival time. One of 6 126 633 SNPs tested reached genome-wide significance (p<5×10-8 ) and replicated in an independent cohort: rs73055188 (p=5.27×10-9 , per-allele hazard ratio [HR]=2.27, 95% confidence interval [CI] 1.72-2.98) in the AOX1 gene. A second SNP reached a suggestive level of significance (p<1×10-6 ) and replicated in an independent cohort: rs2702185 (p=7.1×10-7 , per-allele HR=2.55, 95% CI=1.76-3.69) in the SMG7 gene. The SNP rs73055188 is correlated with AOX1 expression levels, which is associated with biochemical recurrence of prostate cancer in independent cohorts. This association is yet to be validated in other ethnic groups.

CONCLUSIONS: The SNP rs73055188 at the AOX1 locus is associated with prostate-cancer-specific survival time, and AOX1 gene expression level is correlated with biochemical recurrence of prostate cancer.

PATIENT SUMMARY: We identify two genetic markers that are associated with prostate-cancer-specific survival time.