Ancestral characterization of 1018 cancer cell lines highlights disparities and reveals gene expression and mutational differences.

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Ancestral characterization of 1018 cancer cell lines highlights disparities and reveals gene expression and mutational differences.

Cancer. 2019 06 15;125(12):2076-2088

Authors: Kessler MD, Bateman NW, Conrads TP, Maxwell GL, Dunning Hotopp JC, O’Connor TD

Abstract
BACKGROUND: Although cell lines are an essential resource for studying cancer biology, many are of unknown ancestral origin, and their use may not be optimal for evaluating the biology of all patient populations.
METHODS: An admixture analysis was performed using genome-wide chip data from the Catalogue of Somatic Mutations in Cancer (COSMIC) Cell Lines Project to calculate genetic ancestry estimates for 1018 cancer cell lines. After stratifying the analyses by tissue and histology types, linear models were used to evaluate the influence of ancestry on gene expression and somatic mutation frequency.
RESULTS: For the 701 cell lines with unreported ancestry, 215 were of East Asian origin, 30 were of African or African American origin, and 453 were of European origin. Notable imbalances were observed in ancestral representation across tissue type, with the majority of analyzed tissue types having few cell lines of African American ancestral origin, and with Hispanic and South Asian ancestry being almost entirely absent across all cell lines. In evaluating gene expression across these cell lines, expression levels of the genes neurobeachin line 1 (NBEAL1), solute carrier family 6 member 19 (SLC6A19), HEAT repeat containing 6 (HEATR6), and epithelial cell transforming 2 like (ECT2L) were associated with ancestry. Significant differences were also observed in the proportions of somatic mutation types across cell lines with varying ancestral proportions.
CONCLUSIONS: By estimating genetic ancestry for 1018 cancer cell lines, the authors have produced a resource that cancer researchers can use to ensure that their cell lines are ancestrally representative of the populations they intend to affect. Furthermore, the novel ancestry-specific signal identified underscores the importance of ancestral awareness when studying cancer.

PMID: 30865299 [PubMed – indexed for MEDLINE]