Weng L, Ziliak D, Im HK, Gamazon ER, Philips S, Nguyen AT, Desta Z, Skaar TC, Flockhart DA, Huang RS. Genome-wide discovery of genetic variants affecting tamoxifen sensitivity and their clinical and functional validation.
Ann Oncol 2013;
24:1867-1873. [PMID:
23508821 PMCID:
PMC3690911 DOI:
10.1093/annonc/mdt125]
[Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2013] [Revised: 02/12/2013] [Accepted: 02/14/2013] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND
Beyond estrogen receptor (ER), there are no validated predictors for tamoxifen (TAM) efficacy and toxicity. We utilized a genome-wide cell-based model to comprehensively evaluate genetic variants for their contribution to cellular sensitivity to TAM.
DESIGN
Our discovery model incorporates multidimensional datasets, including genome-wide genotype, gene expression, and endoxifen-induced cellular growth inhibition in the International HapMap lymphoblastoid cell lines (LCLs). Genome-wide findings were further evaluated in NCI60 cancer cell lines. Gene knock-down experiments were performed in four breast cancer cell lines. Genetic variants identified in the cell-based model were examined in 245 Caucasian breast cancer patients who underwent TAM treatment.
RESULTS
We identified seven novel single-nucleotide polymorphisms (SNPs) associated with endoxifen sensitivity through the expression of 10 genes using the genome-wide integrative analysis. All 10 genes identified in LCLs were associated with TAM sensitivity in NCI60 cancer cell lines, including USP7. USP7 knock-down resulted in increasing resistance to TAM in four breast cancer cell lines tested, which is consistent with the finding in LCLs and in the NCI60 cells. Furthermore, we identified SNPs that were associated with TAM-induced toxicities in breast cancer patients, after adjusting for other clinical factors.
CONCLUSION
Our work demonstrates the utility of a cell-based model in genome-wide identification of pharmacogenomic markers.
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