Abstract

e15527 Background: Blood-based ECD has the potential to reduce mortality rates by improving strategies for adoption of and adherence to screening. As health disparities in the incidence of CRC across minority populations are known to exist, we evaluated the genomic landscape in patients with CRC across genetic ancestries. Methods: De-identified patients (N = 16,337) with stage I-IV CRC had personalized, tumor-informed commercial ctDNA testing (SignateraTM) based on whole exome sequencing. Genetic ancestry determined via supervised local ancestry inference (pmid36042219) included African (AFR, n = 1697), Ashkenazi Jewish (ASJ, n = 1192), East Asian (EAS, n = 2247), European (EUR, n = 9726), Latino (LAT, n = 1291), and South Asian (SAS, n = 184) ancestries. Somatic driver mutations and pathogenic germline variants (PVs) in CRC-associated genes were evaluated. Somatic single nucleotide variants were used for mutational signature inference. Results: Across ancestries, 47-67% of the patients were male and most were aged > 50 years. Among 35 to 50-year-olds, microsatellite instability (MSI) rates were higher in LAT (12.9%, p = 0.04) and SAS (28.3%, p < 0.001) vs EUR (8.2%). Among > 50-year-olds, MSI rates were lower in AFR (10.7%, p < 0.001), EAS (7.9%, p < 0.001), and LAT (10.4%, p < 0.001) vs EUR (16.0%). The POLE signature was more common in AFR (2%, p = 0.001) vs EUR (1.1%). There were significant differences in the frequency of driver mutations and PV rates between non-EUR vs EUR ancestry groups (Table, *p < 0.05, **p < 0.001). Gene-level enrichment was observed in MLH1 for SAS (8.7%, p < 0.001) and LAT (1.8%, p = 0.03), CHEK2 for AFR (0.4%, p = 0.03) and EAS (0.1%, p < 0.001), and PMS2 (1.4%, p = 0.006) for AFR. Among patients aged ≤50 years, similar findings were observed, with differences driven by MSI rates and germline findings in Lynch syndrome (LS) genes. Conclusions: This is the first study to investigate genomic differences between multiple ancestry groups in the largest cohort to date, including EAS, LAT, and SAS populations. The differences observed between ancestries could provide insight into differences in both hereditary risk and subsequent tumor initiation and growth. Findings from this study may provide information for developing risk stratification and prevention strategies for the early detection of cancer and provide the rationale for precision treatment based on ancestry. [Table: see text]

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