CLINICAL VALIDATION OF AN INTEGRATED RISK ASSESSMENT TEST INCORPORATING GENOMIC AND NON-GENOMIC DATA FOR SPORADIC BREAST CANCER IN COLOMBIA

Harvy Mauricio Velasco¹Danny Stevens Cardona^1,2Cesar Augusto Buitrago¹Melisa Sofía Naranjo Vanegas^1,3*Sebastián Gutiérrez Hincapié³Carolina Jaramillo Jaramillo³Alicia María Cock^1,3Carolina Benavides Duque^3,4Clara Patricia Piedrahita⁵Catalina Bustamante⁵Leonel Andrés Gonzalez Niño^1,3Jen Kintle⁶Scott Kulm⁶Alessandro Bolli⁶Paolo Di Dominico⁶Giordano Bottà PhD⁶George B J Busby⁶Juan Pablo Valencia-Arango²

• ¹Personalized Medicine Group, Unidad de Bioentendimiento, Bioscience Center- Ayudas Diagnósticas SURA., Medellin, Colombia
• ²Data Science Department, Bioscience Center - Ayudas Diagnósticas SURA, Medellin, Colombia
• ³Ayudas Diagnósticas SURA, Medellín, Colombia
• ⁴Clinical Research Group, Bioscience Center – Ayudas Diagnósticas SURA., Medellin, Colombia
• ⁵Medical imaging & AI in health SURA, Bioscience Center – Ayudas Diagnósticas SURA, Medellin, Colombia
• ⁶Allelica Inc, New York, United States

Introduction: Breast cancer risk arises from a complex interaction of genetic, environmental, and physiological factors. Integrating Polygenic Risk Scores (PRS) with clinical risk factors can enhance personalized risk prediction, especially in diverse populations like Colombia.Objective: To evaluate the predictive performance of ancestry-specific PRS combined with clinical and imaging risk factors for breast cancer in Colombian women.We developed and validated ancestry-specific PRS using diverse genetic datasets.A cohort of 1,997 Colombian women, including 510 breast cancer cases (25.5%) and 1,487 controls (74.5%), were recruited. Clinical data, such as breast density and family history, were analyzed for predictive ability using the area under the receiver operating characteristic curve (AUC). Participants were categorized into genetic ancestry groups: Admixed American, African, and European. PRS were applied to the cohort and adjusted for clinical factors to assess risk prediction.Results: Breast density and family history were the strongest individual predictors, with AUCs of 0.66 and 0.64, respectively. Most participants were of Admixed American ancestry (70% of cases, 73% of controls). The combined PRS showed an Odds Ratio per Standard Deviation of 1.56 (95% CI 1.40-1.75) and an AUC of 0.72 (95% CI 0.69-0.74) when adjusted for family history. Incorporating PRS with clinical and imaging data improved the AUC to 0.79 (95% CI 0.76-0.81), significantly enhancing predictive accuracy.Combining ancestry-specific PRS with clinical risk factors provides a more accurate approach for breast cancer risk stratification in Colombian women. These findings support the development of precise, population-specific risk assessment models.