Leading edge genes in the T cell receptor-signaling pathway, the top-ranking pathway in tumor-adjacent normal prostate tissue differentially expressed in ever versus never statin users, as identified by age-adjusted gene set enrichment analysis
ARTICLE ABSTRACTStatins are associated with lower risk of aggressive prostate cancer, but lethal prostate cancer is understudied and contributing mechanisms are unclear. We prospectively examined statins and lethal prostate cancer risk in the Health Professionals Follow-up Study (HPFS), tested associations with molecular subtypes, and integrated gene expression profiling to identify putative mechanisms.
Our study included 44,126 men cancer-free in 1990, followed for prostate cancer incidence through 2014, with statin use recorded on biennial questionnaires. We used multivariable Cox regression to examine associations between statins and prostate cancer risk overall, by measures of clinically significant disease, and by ERG and PTEN status. In an exploratory analysis, age-adjusted gene set enrichment analysis identified statin-associated pathways enriched in tumor and adjacent normal prostate tissue.
During 24 years of follow-up, 6,305 prostate cancers were diagnosed and 801 (13%) were lethal (metastatic at diagnosis or metastatic/fatal during follow-up). Relative to never/past use, current statin use was inversely associated with risk of lethal prostate cancer [HR, 0.76; 95% confidence interval (CI), 0.60–0.96] but not overall disease. We found a strong inverse association for risk of PTEN-null cancers (HR, 0.40; 95% CI, 0.19–0.87) but not PTEN-intact cancers (HR, 1.18; 95% CI, 0.95–1.48; P heterogeneity = 0.01). Associations did not differ by ERG. Inflammation and immune pathways were enriched in normal prostate tissue of statin ever (n = 10) versus never users (n = 103).
Molecular tumor classification identified PTEN and inflammation/immune activation as potential mechanisms linking statins with lower lethal prostate cancer risk. These findings support a potential causal association and could inform selection of relevant biomarkers for statin clinical trials.