Unified genetic risk score for prostate cancer enables improved risk stratification for clinical decision-making.

Continuum risk model combining pathogenic variants in predisposition genes (ATM, BRCA2, CHEK2, HOXB13, MSH2) with a polygenic risk score, replacing binary carrier/non-carrier classification.

Inherited prostate cancer risk assessment currently relies on binary pathogenic variant carrier status, ignoring gene-specific heterogeneity and polygenic background. In the UK Biobank (n = 218,484), the authors assessed pathogenic variants in 11 clinically recommended genes and a polygenic risk score against incident prostate cancer using Cox models, then built a continuum model, GenProb-PCa. Five genes (ATM, BRCA2, CHEK2, HOXB13, MSH2) and the polygenic score were independently associated with risk (p < 0.001), and GenProb-PCa outperformed binary models for discrimination (C-index 0.69 vs 0.52; p < 0.001) with a cNRI of 0.58 (p < 0.001), replicated in an independent health-system cohort (Genomic Health Initiative, n = 6,590: C-index 0.64 vs 0.54; cNRI 0.31). Compared with binary models, 20% of non-carriers were reclassified upward and 60% of carriers downward, and the top 8% of the distribution reached a cumulative incidence above 20% by age 75.

Synthesis written by Geno'X. For the full original abstract, please refer to the source publication.

This is polygenic risk combined with monogenic variants, not variant reclassification: nothing here transfers directly to a cancer genetics clinic, where polygenic scores are neither reimbursed nor calibrated on our populations. The genuinely useful message lies elsewhere, in the demonstration that 60% of pathogenic variant carriers are over-classified by the binary approach, which argues for gene-by-gene modulation of how risk is communicated. External validation remains confined to one North American health system and to cohorts of predominantly European ancestry, precluding direct use outside that setting.

Analysis by Dr Thibaut Benquey