Association of Genetic Ancestry with Molecular Tumor Profiles in Colorectal Cancer

Abstract

Purpose: Prior research in the molecular correlates of disparities in incidence and outcomes of colorectal cancer (CRC) by race and ethnicity have typically used self-reported or observed categories, which can be missing or inaccurate. Furthermore, race and ethnicity do not always capture genetic similarity well, particularly in admixed populations. To overcome these limitations, we examined associations of CRC tumor molecular profiles with genetic ancestry. Experimental Design: Sequencing was performed with the Tempus xT NGS 648-gene panel and whole exome capture RNA-Seq for 8,454 CRC patients. Genetic ancestry proportions were estimated for five continental groups, Africa (AFR), Americas (AMR), East Asia (EAS), Europe (EUR), and South Asia (SAS), using ancestry informative markers. We assessed association of genetic ancestry proportions and genetic ancestry-imputed race and ethnicity categories with somatic mutations in relevant CRC genes and in expression profiles, including consensus molecular subtypes (CMS). Results: Increased AFR ancestry was associated with higher odds of somatic mutations in APC, KRAS and PIK3CA and lower odds of BRAF mutations. Additionally, increased EAS ancestry was associated with lower odds of mutations in KRAS, EUR with higher odds in BRAF, and the Hispanic/Latino category with lower odds in BRAF. Greater AFR ancestry and the non-Hispanic Black category were associated with higher than expected CMS3, while patients in the Hispanic/Latino category had higher indeterminate CMS. Conclusions: Use of genetic ancestry enables identification of molecular differences in CRC tumor mutation frequencies and gene expression that may underlie observed differences by race and ethnicity, and suggests that subtype classifications such as CMS may benefit from more diversity in representation.

Incorporating Real-World Clinico-Genomic Insights to Inform Diversity Enrollment Targets in Oncology Trials

“…63 Another example is the colorectal cancer consensus molecular subtypes (CMS) classifiers, 64 which were developed mostly from data from White patients and may experience R/E biases and increased no-call rates in some groups. 65 Care must be taken to assess whether these scores/classifiers are biased due to disparities in training data and the potential impact of such biases on R/E distributions. 16,66…”

“…63 Another example is the colorectal cancer consensus molecular subtypes (CMS) classifiers, 64 which were developed mostly from data from White patients and may experience R/E biases and increased no-call rates in some groups. 65 Care must be taken to assess whether these scores/classifiers are biased due to disparities in training data and the potential impact of such biases on R/E distributions. 16,66 In our methodology, we introduce a scaling factor (α) to decide the extent of adjustment to the final R/E distribution based on the identified disparity between expected incidence data and the RWD cohort.…”

Genetic Ancestry and Somatic Mutations in Lung Adenocarcinoma: Insights from Real-World Clinico-Genomic Data

“…We determined proportions of continental genetic ancestry employing a supervised variant of the ADMIXTURE algorithm for global genetic ancestry inference, 27 following methodologies outlined in prior research. 22,28 We estimated ancestry proportions across five major super-populations—Africa (AFR), American Indigenous (AMR), East Asia (EAS), Europe (EUR), and South Asia (SAS)—utilizing a custom set of 654 ancestry informative markers (AIMs) previously identified in the targeted sequencing regions of the Tempus xT assay. 22 Reference allele frequencies for these AIMs were derived from the 1,000 Genomes Project, 29 the Human Genome Diversity Project, 3033 and the Simons Genome Diversity Project 31 databases.…”