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Ancestral characterization of 1018 cancer cell lines highlights disparities and reveals gene expression and mutational differences
Author(s) -
Kessler Michael D.,
Bateman Nicholas W.,
Conrads Thomas P.,
Maxwell George L.,
Dunning Hotopp Julie C.,
O’Connor Timothy D.
Publication year - 2019
Publication title -
cancer
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.052
H-Index - 304
eISSN - 1097-0142
pISSN - 0008-543X
DOI - 10.1002/cncr.32020
Subject(s) - medicine , gene , genetics , cancer , gene expression , computational biology , evolutionary biology , biology
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.