Evaluation of Polygenic Risk Score for Epithelial OVarian cancEr Risk Prediction: the PROVE Study

Fondazione Policlinico Universitario Agostino Gemelli IRCCS1,300 enrolled

Overview

The goal of this observational study is to evaluate whether polygenic risk score (PRS) assessment can help predict the onset of epithelial ovarian cancer in women aged over 18, comparing those with a histologically confirmed diagnosis of epithelial ovarian or fallopian tube cancer (cases) to women with no personal history of ovarian cancer (controls). The main questions it aims to answer are: * Is there an association between PRS and the presence of epithelial ovarian cancer? * Can PRS improve the prediction of ovarian cancer risk when adjusted for other clinical factors? Researchers will compare PRS values between cases and controls to see if higher PRS percentiles are associated with an increased risk of ovarian cancer. Participants will: * Complete a questionnaire on socio-economic status, lifestyle, and dietary habits. * Undergo blood sampling, for the analysis of BRCA1-2, PALB2, RAD51C, RAD51D pathogenic variants. * Undergo PRS analysis.

Study Type

OBSERVATIONAL

Enrollment

1,300

Conditions

Ovarian Cancer

Interventions

Polygenic Risk ScoreGENETIC

For the PRS analysis, SNPs for genotyping will be selected based on the latest findings from GWAS on EOC, particularly leveraging the results, as reported by Dareng et al. (doi:10.1038/s41431-021-00987-7). The PRS will be calculated as a weighted sum of risk alleles based on the selected SNPs.

Eligibility

Sex: FEMALEMin age: 18 YearsHealthy volunteers:

Medical Language ↔ Plain English

Inclusion Criteria: * For cases: women with a first-time diagnosis of histologically confirmed epithelial ovarian or fallopian tube cancer. * For Controls women with no concomitant or past OC diagnosis. Exclusion Criteria: * For both cases and controls: the presence of concurrent malignancies other from OC.

Outcomes

Primary Outcomes

Odds of developing EOC by different PRS percentiles

Correlation between PRS percentiles and EOC risk

Time frame: At enrollment

Secondary Outcomes

Correlation of PRS percentiles and covariates

Correlation between PRS percentiles and: age, familiarity with OC, stage, histotype, grading (1-2 versus 3), BRCA1-2, PALB2, RAD51C, RAD51D, FANCM status, type of surgery, residual tumor (RT) at histology, type of chemotherapy, maintenance, chemo-resistance, response to treatment, recurrences, progressions, cancer-specific deaths, Disease Free survival (DFS) hazard ratio (HR), Overall Survival (OS) HR.