Ancestral characterization of 1018 cancer cell lines highlights disparities and reveals gene expression and mutational differences. Issue 12 (13th March 2019)

• Record Type: Journal Article
• Authors: Kessler, Michael D.; Bateman, Nicholas W.; Conrads, Thomas P.; Maxwell, George L.; Dunning Hotopp, Julie C.; O'Connor, Timothy D.
• Is Part Of: Cancer. Volume 125:Issue 12(2019)
• Page Start: 2076
• Page End: 2088
• Publication Date: 2019-03-13
• Subjects: admixture -- African ancestry -- Asian ancestry -- cancer genomics -- clinical genetics -- genomic ancestry -- population genetics -- precision medicine; Cancer -- Periodicals; Cancer -- Cytopathology -- Periodicals; 616.99405
• DOI: 10.1002/cncr.32020
• Languages: English
• ISSNs: 0008-543X

Abstract

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. Abstract : Preclinical cancer cell line research is often conducted without an awareness of ancestral background, which results in incongruities between the genetic backgrounds of used cell lines and the patient populations they are intended to represent. By calculating genetic ancestry for 1018 common cancer cell lines and identifying ancestry‐specific expression and somatic mutation patterns, the importance of ancestral awareness is emphasized, and a resource is provided that can be used by cancer researchers to ensure that their cell lines are ancestrally representative of the populations they aim to impact.