Abstract 3117: Molecular and clinical correlates of genetic ancestry in a diverse, admixed cancer dataset

Abstract The objective of this study is to determine whether genetic ancestry analysis can provide additional insight into the genetic determinants of cancer disparities distinct from socially constructed variables like self-reported race and ethnicity. The Oncology Research Information Exchange Network (ORIEN) “Avatar” project is a diverse dataset of extensive, longitudinal clinical and molecular data from 18 cancer centers across the U.S.; the ORIEN Intermember Ancestry Project cohort described in this study is a subset of the larger dataset. Using paired tumor/germline whole exome sequencing data from ORIEN, the Genome Aggregation Database (gnomAD) dataset of ancestry reference individuals, and the software tools ADMIXTURE and RFMix, we have estimated genetic ancestry for cancer cases from both ORIEN and The Cancer Genome Atlas (TCGA). The ORIEN dataset has 2.6X greater representation of self-reported Hispanic/Latinos than does TCGA, with Hispanic/Latinos making up 9% of the ORIEN dataset vs. 4% in TCGA. As expected, individuals of Hispanic/Latino ethnicity are heterogeneous in their admixture proportions of Indigenous American, African, and European ancestries. We performed statistical analyses in R to identify molecular and clinical correlations with ancestry. This study highlights the clinical utility of genetic ancestry analysis as an approach to understand the genetic contributions to cancer disparities in diverse, admixed populations. Citation Format: Mackenzie D. Postel, Jamie K. Teer, Steven A. Eschrich, Julie Dutil, Erin M. Siegel, William D. Cress, John D. Carpten, David W. Craig. Molecular and clinical correlates of genetic ancestry in a diverse, admixed cancer dataset [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3117.