Francisco M. De La Vega

Background:Despite differences in tumor alterations across genetic ancestries, investigations of the colorectal cancer molecular landscape have used self-reported ethnicity instead of genetic ancestry. Methods:We used tumor and matched normal whole-exome sequencing data from 16,388 patients with stage I to IV colorectal cancer to investigate colorectal cancer’s germline and somatic molecular landscape and the potential influence of socioeconomic factors (Distressed Communities Index, DCI) across diverse genetic ancestries. Genetic ancestry determined via supervised local ancestry inference included African (AFR, N = 1,697), Native American (AMR, N = 1,291), East Asian (EAS, N = 2,247), European (EUR, N = 9,726), Levantine Middle Eastern (LME, N = 1,192), and South Asian (SAS, N = 184). Results:Microsatellite instability (MSI) was the most common form of hypermutation (80.8%), higher in the EUR genetic ancestry than in the AFR, AMR, and EAS genetic ancestry. Among germline findings, positive results were most common in high-penetrance genes associated with Lynch syndrome. Enrichment patterns included MLH1 (SAS) and PMS2 (AFR). There were significant differences in the frequency of driver mutations in APC, BRAF, KRAS, TP53, and PIK3CA between the EUR and other ancestry groups in both MSI and microsatellite stable tumors. Mutational signatures suggested enrichment of reactive oxygen species and POLE in AFR, colibactin in EAS, and aflatoxin and NTHL1 in SAS. DCI scores differed by ancestry (higher distress in AFR/AMR than in EUR), but driver mutation frequencies did not vary across DCI quintiles. Conclusions:Genetic ancestry shapes hereditary risk, tumor biology, and environmental exposures. Impact:These findings suggest that incorporating ancestry into screening, trials, and precision oncology may improve equity, though outcome-linked prospective studies and implementation research are warranted.

Supplemental Figure S2. Stage distribution based on microsatellite status across all patients and tumor purity by genetic ancestry

Supplemental Figure S4. Germline findings across genetic ancestries with common EUR germline variants excluded from analysis

Supplemental Figure S3. Other mechanisms of hypermutation

Supplemental Figure S1. Genetic ancestry by patient

Supplemental Table S1. Genes included in germline analysis, by penetrance

Supplemental Figure S5. Germline findings by age across genetic ancestries

Supplemental Figure S6. Geographic and socioeconomic status

Background: Despite differences in tumor alterations across genetic ancestries, investigations of the colorectal cancer molecular landscape have used self-reported ethnicity instead of genetic ancestry. Methods: We used tumor and matched normal whole-exome sequencing data from 16,388 patients with stage I to IV colorectal cancer to investigate colorectal cancer’s germline and somatic molecular landscape and the potential influence of socioeconomic factors (Distressed Communities Index, DCI) across diverse genetic ancestries. Genetic ancestry determined via supervised local ancestry inference included African (AFR, N = 1,697), Native American (AMR, N = 1,291), East Asian (EAS, N = 2,247), European (EUR, N = 9,726), Levantine Middle Eastern (LME, N = 1,192), and South Asian (SAS, N = 184). Results: Microsatellite instability (MSI) was the most common form of hypermutation (80.8%), higher in the EUR genetic ancestry than in the AFR, AMR, and EAS genetic ancestry. Among germline findings, positive results were most common in high-penetrance genes associated with Lynch syndrome. Enrichment patterns included MLH1 (SAS) and PMS2 (AFR). There were significant differences in the frequency of driver mutations in APC, BRAF, KRAS, TP53, and PIK3CA between the EUR and other ancestry groups in both MSI and microsatellite stable tumors. Mutational signatures suggested enrichment of reactive oxygen species and POLE in AFR, colibactin in EAS, and aflatoxin and NTHL1 in SAS. DCI scores differed by ancestry (higher distress in AFR/AMR than in EUR), but driver mutation frequencies did not vary across DCI quintiles. Conclusions: Genetic ancestry shapes hereditary risk, tumor biology, and environmental exposures. Impact: These findings suggest that incorporating ancestry into screening, trials, and precision oncology may improve equity, though outcome-linked prospective studies and implementation research are warranted.

Motivation: Whole-genome sequencing (WGS) is increasingly preferred for clinical applications due to its comprehensive coverage, effectiveness in detecting copy number variants (CNVs), and declining costs. However, systematic evaluations of WGS CNV callers tailored to germline clinical testing—where high sensitivity and confirmation of reported CNVs are essential—remain necessary. Clinical reporting typically emphasizes CNVs affecting coding regions over precise breakpoint detection. This study benchmarks several short-read WGS CNV detection tools using reference cell lines to inform their clinical use. Results: While tools vary in sensitivity (7%–83%) and precision (1%–76%), few meet the sensitivity needed for clinical testing. Callers generally perform better for deletions (up to 88% sensitivity) than duplications (up to 47% sensitivity), with poor detection of duplications under 5 kb. Notably, for CNVs in genes commonly included in clinical panels, significantly improved sensitivity and precision were observed when benchmarking against 25 cell lines with known CNVs. DRAGEN v4.2 high-sensitivity CNV calls, post-processed with custom filters, achieved 100% sensitivity and 77% precision on the optimized gene panel after excluding recurring artifacts. This level of performance may support clinical use with orthogonal confirmation of reportable CNVs, pending validation on laboratory-specific samples. Availability and implementation: The data underlying this article are available in the European Nucleo-tide Archive under project accession PRJEB87628.