Introduction

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 realworld data (RWD) patient cohort to examine associations of genetic ancestry with somatic alterations in cancer driver genes.

Methods

We used 654 ancestry informative markers selected to overlap the capture regions of the assay to infer global ancestry proportions at the continental level: Africa (AFR), America (AMR), Europe (EUR), East Asia (EAS), and South Asia (SAS). Whereas most patients are of European descent (72%), our cohort includes 4.7- and 3.8-fold more patients with substantial (>50%) AFR and AMR ancestry, correspondingly, than The Cancer Genome Atlas. Logistic regression was used to directly test for associations between continental ancestry proportions and presence of actionable somatic mutations (OncoKB, Levels 1 &2, R1/2) in cancer genes, controlling for assay version, gender, and age. P-values were adjusted for multiple testing by the Benjamini-Hochberg method to control the false discovery rate at 5%, and all associations reported were significant with p <0.0001.

Results

We identify an association between actionable somatic mutations in EGFR with EAS ancestry in lung cancer (OR=1.48, per 20% increase in ancestry proportion), which has been previously reported using race categories. Furthermore, we also identify five novel significant associations with AFR ancestry including: PIK3CA in breast (OR=0.91) and colorectal (OR=1.11) cancers; BRAF in colorectal cancer (OR=0.73); EGFR in lung cancer (OR=0.77); and KIT in sarcomas (OR=1.23).

Conclusions

Our results support the use of genetic ancestry inference on RWD to improve upon the use of race and ethnicity to understand the impact of ancestry cancer incidence, progression, and outcomes.

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