Genetic ancestry correlates of the cancer somatic mutational landscape from tumor profiling data of 50,000 patients with cancer.

Abstract

10573 Background: The incidence and mortality of cancer vary widely across race and ethnicity. This is attributed to an interplay of socioeconomic factors, environmental exposures, and genetic background. Cancer genomic studies have underrepresented minorities and individuals of non-European descent, thus limiting a comprehensive understanding of disparities in the diagnosis, prognosis, and treatment of cancer among these populations. Furthermore, the social constructs of race and ethnicity are far from precise categories to understand the biological underpinnings of such differences. In this study, we use a large real-world data (RWD) patient cohort to examine associations of genetic ancestry with somatic alterations in known cancer driver genes. Methods: We inferred genetic ancestry from approximately 50,000 de-identified records from cancer patients of diverse histology who underwent tumor genomic profiling with the Tempus xT next-generation sequencing (NGS) assay. Our cohort includes patients with brain, breast, colorectal, hematopoietic, lung, and ovarian cancers, among others. We used 654 ancestry informative markers selected to overlap the target regions of the 648-gene Tempus xT NGS assay to infer global ancestry proportions at the continental level: Africa (AFR), America (AMR), Europe (EUR), East Asia (EAS), and South Asia (SAS). We imputed race/ethnicity categories using ancestry proportions on subjects lacking such metadata. Results: Most patients were of European descent (72%), however, continental genetic ancestry inference identified 4.7 and 3.8-fold more patients with substantial (> 50%) AFR and AMR ancestry, correspondingly, compared with TCGA. We observed higher percentages of AFR ancestry patients with prostate, breast, and colorectal cancer (1.8-3.1%) and AMR ancestry patients with colorectal cancer (2.4%) compared to the overall cohort-level distributions (p < 0.05). Using imputation, we identified 60% and 121% more patients as likely Black and Hispanic/Latino, respectively. We observed several associations between genetic ancestry with tumor mutation burden (TMB), e.g., a reduction in median TMB in Asian breast cancer patients (Asian TMB mean = 2.3 m/Mb vs 4.4 for Black, 3.3 for Hispanic, and 4.2 for White; p < 0.0001), in paired tumor/normal sequencing data. Furthermore, we found associations between ancestry and nonsynonymous somatic mutations in cancer genes, e.g. in CTNNB1 with EAS ancestry (OR = 1.18) and EGFR with EAS (OR = 1.24), AMR (OR = 1.30), and EUR (OR = 0.89) ancestries (all p < 0.001) in lung cancer patients. Conclusions: Our results support the use of genetic ancestry inference on RWD to improve upon the social constructs of race and ethnicity, allowing us to better understand the impact of shared germline genetic or exposure backgrounds into cancer mutational processes that influence incidence, progression, and outcomes.