OBJECTIVES

For prostate cancer (PCa), hundreds of risk variants have been identified. It remains unknown whether the polygenic risk score (PRS) that combines the effects of these variants is also a sufficiently informative metric with relevance to the molecular mechanisms of carcinogenesis in prostate. We aimed to understand the biological basis of PRS and racial disparities in the cancer.

METHODS

We performed a comprehensive analysis of the data generated (deposited in) by several genomic and/or transcriptomic projects (databases), including the GTEx, TCGA, 1000 Genomes, GEO and dbGap. PRS was constructed from 260 PCa risk variants that were identified by a recent trans-ancestry meta-analysis and contained in the GTEx dataset. The dosages of risk variants and the multi-ancestry effects on PCa incidence estimated by the meta-analysis were used in calculating individual PRS values.

RESULTS

The following novel results were obtained from our analyses. (1) In normal prostate samples from healthy European Americans (EAs), the expression levels of 540 genes (termed PRS genes) were associated with the PRS ( < .01). (2) Ubiquitin-proteasome system in high-PRS individuals' prostates was more active than that in low-PRS individuals' prostates. (3) Nine PRS genes play roles in the cancer progression-relevant parts, which are frequently hit by somatic mutations in PCa, of PI3K-Akt/RAS-MAPK/mTOR signaling pathways. (4) The expression profiles of the top significant PRS genes in tumor samples were capable of predicting malignant PCa relapse after prostatectomy. (5) The transcriptomic differences between African American and EA samples were incompatible with the patterns of the aforementioned associations between PRS and gene expression levels.

CONCLUSIONS

This study provided unique insights into the relationship between PRS and the molecular mechanisms of carcinogenesis in prostate. The new findings, alongside the moderate but significant heritability of PCa susceptibility contributed by the risk variants, suggest the aptness and inaptness of PRS for explaining PCa and disparities.