Genetic Ancestry Inference from Cancer-Derived Molecular Data across Genomic and Transcriptomic Platforms

Abstract

Genetic ancestry-oriented cancer research requires the ability to perform accurate and robust genetic ancestry inference from existing cancer-derived data, including whole exome sequencing, transcriptome sequencing, and targeted gene panels, very often in the absence of matching cancer-free genomic data. Here we examined the feasibility and accuracy of computational inference of genetic ancestry relying exclusively on cancer-derived data. A data synthesis framework was developed to optimize and assess the performance of the ancestry inference for any given input cancer-derived molecular profile. In its core procedure, the ancestral background of the profiled patient is replaced with one of any number of individuals with known ancestry. The data synthesis framework is applicable to multiple profiling platforms, making it possible to assess the performance of inference specifically for a given molecular profile and separately for each continental-level ancestry; this ability extends to all ancestries, including those without statistically sufficient representation in the existing cancer data. The inference procedure was demonstrated to be accurate and robust in a wide range of sequencing depths. Testing of the approach in four representative cancer types and across three molecular profiling modalities showed that continental-level ancestry of patients can be inferred with high accuracy, as quantified by its agreement with the gold standard of deriving ancestry from matching cancer-free molecular data. This study demonstrates that vast amounts of existing cancer-derived molecular data are potentially amenable to ancestry-oriented studies of the disease without requiring matching cancer-free genomes or patient self-reported ancestry.

Pancreatic Cancer Health Disparity: Pharmacologic Anthropology

“…Ensuring diversity and representation in genetic research studies is critical to addressing disparities effectively. Efforts should be made to include diverse populations in genetic research initiatives, considering factors such as ancestry, ethnicity, and genetic variations specific to different population groups [115,116]. Improving access to genetic testing, counseling, and precision medicine approaches is essential for reducing disparities.…”

Outcomes in breast cancer—does ethnicity matter?

“… 5 , 6 , 7 Recent studies using single-nucleotide polymorphism (SNP) markers from genome-wide or targeted sequencing rather than self-reported race offer more granular details of the genetic ancestry footprint, with the potential to infer admixture estimates as well. 6 , 7 , 8 , 9 , 10

Figure 1 Interplay between intrinsic and extrinsic factors in shaping host and tumor characteristics, which result in different outcomes. Intrinsic factors include germline genetics which are generally not modifiable.

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