Ahwan Pandey

Supplementary Figure 10. Multivariable analysis examining the association between PRS and platinum-free interval in high-grade non-mucinous ovarian cancer, adjusted for age, stage, and residual disease status.

Background:Ovarian cancer is characterized by high mortality and lacks effective screening, making prevention critical. A polygenic risk score (PRS), which aggregates the effects of multiple common alleles, may capture a proportion of currently unexplained genetic risk. Although PRSs have been evaluated for risk prediction, their association with treatment response and survival remains unclear. This study assessed the utility of a PRS for predicting high-grade serous ovarian cancer (HGSOC) risk in an Australian population and its association with chemotherapy response and outcomes. Methods:PRSs were calculated for 1,097 cases with HGSOC and 812 controls using data from Australian research programs. Associations among PRS, ovarian cancer risk, chemotherapy response, and survival were analyzed. Results:Each standard-deviation increase in PRS was associated with a 40% increase in HGSOC risk [odds ratio (OR), 1.40; P < 0.001]. Women in the top 1% of the PRS distribution had a lifetime ovarian cancer risk approaching 3%. Higher PRS values showed a trend toward poorer outcomes; however, these associations were not consistent across analyses. Conclusions:PRSs were not clearly associated with chemotherapy response or survival but represent a significant risk factor for the development of HGSOC. Incorporating PRS into clinical models may improve risk stratification and support targeted prevention. Impact:As the first study to evaluate how PRS relates to both HGSOC risk and chemotherapy response and outcomes, we show that PRSs are unlikely to serve as therapeutic biomarkers but support their use for enhanced risk-stratified prevention.

Supplementary Figure 1. Kaplan Meier overall survival analyses for patients with high-grade serous ovarian cancer stratified according to disease stage, residual disease status, and germline pathogenic variant status, demonstrating differences in survival outcomes across prognostic subgroups.

Supplementary Figure 2. Distribution of standardized polygenic risk score (PRS) values among individuals with and without high-grade non-mucinous ovarian cancer, illustrating differences PRS between cases and controls.

Supplementary Figure 11. Association between PRS and time to subsequent chemotherapy in high-grade serous ovarian cancer, including analyses of time to second-line and third-line chemotherapy adjusted for age, stage, and residual disease.

Supplementary Figure 12. Association between PRS and time to subsequent chemotherapy in high-grade non-mucinous ovarian cancer, including analyses of time to second-line and third-line chemotherapy while accounting for clinical prognostic factors.

Supplementary Figure 4. Association between PRS and risk of high-grade non-mucinous ovarian cancer across multiple analytical models, including analyses of all cases, exclusion of pathogenic variant carriers, unique study cases, and comparisons stratified by pathogenic variant status.

Supplementary Figure 5. Univariable analysis evaluating the association between categorical PRS groups and high grade serous ovarian cancer risk, showing odds ratios and confidence intervals for low-, intermediate-, and high-risk PRS categories.

Supplementary Figure 3. Comparison of standardized PRS distributions generated using different testing methodologies in the OCAC and TRACEBACK cohorts, demonstrating consistency of PRS estimates analytical approaches.

Supplementary Figure 7. Age-related cumulative ovarian cancer risk stratified by polygenic risk score categories in high-grade non-mucinous ovarian cancer excluding pathogenic variant carriers and in high-grade serous ovarian cancer including pathogenic variant carriers, demonstrating differences in cumulative risk across PRS groups.