A Tailored Polygenic Risk Score for Predicting Progression in Prostate Cancer Under Active Surveillance

Overview

Prostate cancer is the most common malignancy in men, and in patients with low-risk disease, active surveillance represents the preferred initial approach to avoid unnecessary treatments. However, up to 50% of men under active surveillance develop clinical progression or histological upgrading within five years, making improved risk stratification essential. A family history of prostate cancer is a well-established risk factor and reflects the importance of genetic predisposition. Genome-wide studies have identified numerous common variants associated with disease risk, enabling the development of polygenic risk scores (PRS) that integrate the effects of multiple genetic loci. Recent evidence suggests that these PRS may also correlate with tumor aggressiveness and the likelihood of progression in patients undergoing active surveillance. This study aims to analyze 185 patients, stratified according to the presence or absence of family history and progression during active surveillance, using germline DNA that has already been biobanked and analyzed with the Axiom™ PMDA array. PRS will be calculated as a weighted sum of risk variants. The objective is to identify PRS models capable of accurately predicting progression, with particular focus on men with a family history, thereby improving the personalization of clinical monitoring. By integrating genomic and clinical data, the study seeks to support a precision oncology approach in patients with early-stage prostate cancer.

Prostate cancer (PCa) is the most frequently diagnosed malignancy among men in many countries. For many patients with low-risk disease-defined by favorable clinical and pathological features-active surveillance (AS) represents the preferred initial management strategy, aiming to avoid overtreatment and related morbidity by delaying radical therapy until progression is detected. Nonetheless, AS has limitations: long-term data indicate that up to 50% of men initially classified as low-risk experience histological upgrading or clinical progression within five years, ultimately requiring curative treatment. Accurate baseline risk stratification is therefore essential to improve patient selection and tailor follow-up intensity. A positive family history is a well-established risk factor for PCa, underscoring the contribution of inherited genetic susceptibility. Beyond rare high-penetrance mutations, genome-wide association studies have identified numerous common variants associated with PCa risk, enabling the development of polygenic risk scores (PRS) that aggregate the effects of multiple low-penetrance loci weighted by their effect sizes. While PRS have traditionally been used to estimate lifetime PCa risk, emerging evidence suggests that they may also correlate with tumor aggressiveness and progression, including in men undergoing AS. Progression-specific or aggressiveness-tailored PRS could therefore enhance the prognostic accuracy of existing clinical models and support more precise decision-making. Based on currently available biobank samples, 185 patients are included and distributed into four groups: (1) familial history with progression during AS; (2) familial history without progression; (3) no familial history with progression; and (4) no familial history without progression. Germline DNA is extracted from already biobanked peripheral blood using the Maxwell® RSC Whole Blood DNA Kit from patients enrolled at the institution who have already provided informed consent for research use (ClinicalTrials.gov ID: NCT06187870). SNP analysis is performed, after pseudonymization, using the Applied Biosystems™ Axiom™ Precision Medicine Diversity Research Array (PMDA). PRS is calculated as the weighted sum of risk allele dosages. One or more PRS models are expected to demonstrate significant predictive utility for AS progression, particularly among men with a family history of PCa. Participants with high PRS may benefit from intensified monitoring or earlier intervention, whereas those with low PRS may safely undergo less intensive surveillance, reducing the burden of repeat biopsies and associated complications. Integrating PRS with established clinical parameters may strengthen risk discrimination and support a precision oncology framework that merges genomic and clinical data to optimize outcomes for men with early-stage prostate cancer.