Integrated Analysis of Genetic Ancestry and Genomic Alterations across Cancers

Abstract

SUMMARY Disparities in cancer care have been a long-standing challenge. We estimated the genetic ancestry of The Cancer Genome Atlas patients, and performed a pan-cancer analysis on the influence of genetic ancestry on genomic alterations. Compared with European Americans, African Americans (AA) with breast, head and neck, and endometrial cancers exhibit a higher level of chromosomal instability, while a lower level of chromosomal instability was observed in AAs with kidney cancers. The frequencies of TP53 mutations and amplification of CCNE1 were increased in AAs in the cancer types showing higher levels of chromosomal instability. We observed lower frequencies of genomic alterations affecting genes in the PI3K pathway in AA patients across cancers. Our result provides insight into genomic contribution to cancer disparities.

Population structure and pharmacogenomic risk stratification in the United States

“…In 2005, investigators showed a 99.9% concordance between SIRE and genetically derived clusters for 3,636 individuals from four racial/ethnic groups groups 50 , and a 2007 study reported 100% classification accuracy of individuals from geographically separated population groups when thousands of genetic variants were used for clustering 51 . More recently, a study of >11,000 cancer patients from The Cancer Genome Atlas found an 95.6% concordance between self-reported race (not ethnicity) and GA 52 , and a massive study of >200,000 individuals from the Million Veterans Program found >99.4% concordance between SIRE and GA 53 . The latter two studies relied on machine learning classifiers powered by vectors of 7 and 30 ancestry principal components, respectively, whereas our clustering algorithm uses vectors of only three continental ancestry components to classify individual genomes.…”

Pan‐cancer clinical and molecular analysis of racial disparities

“…19 To define the AA and EA patient groups, data from the Cancer Genome Ancestry Atlas (TCGAA) 11 were used. Because the SEER database lacks comprehensive sociodemographic information, a secondary survival analysis using data from the National Cancer Database (NCDB), another US cancer registry, was performed.…”

“…These survival data were paired with molecular data from The Cancer Genome Atlas (TCGA). 19 To define the AA and EA patient groups, data from the Cancer Genome Ancestry Atlas (TCGAA) 11 were used. TCGA contains data such as clinical information, histopathology, and molecular information derived from information on samples obtained from more than 11,000 patients.…”

“…However, other observations suggest a role for molecular differences in cancer survival disparities. 11 Whereas some studies have explored somatic alterations in individual cancers, [12][13][14] little is known about how the macroenvironment affects the epigenetic landscape among the different races. 9 A comparison of TNBC in AA versus EA patients has demonstrated a gene expression signature consistent with increased loss of BRCA1 expression, increased activation of insulin-like growth factor 1 receptor, and increased expression of vascular endothelial growth factor-activated genes in AA patients.…”

“…10 In addition, AA patients with breast, head and neck, or endometrial cancer have higher levels of chromosomal instability and frequency of TP53 mutations and CCNE1 amplification than white patients. 11 Whereas some studies have explored somatic alterations in individual cancers, [12][13][14] little is known about how the macroenvironment affects the epigenetic landscape among the different races. 15,16 Epigenetic differences are particularly relevant because they can be shaped by environmental factors, such as chronic stress, social interactions, and toxins.…”