4.5 Article

Statin-induced changes in gene expression in EBV-transformed and native B-cells

期刊

HUMAN MOLECULAR GENETICS
卷 23, 期 5, 页码 1202-1210

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OXFORD UNIV PRESS
DOI: 10.1093/hmg/ddt512

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资金

  1. National Institute of Health [1T32 HL 098057-01, U19 HL069757, R01 HL 1041 33, U01 HL 065899, R01 HL 092197, R01 NR 013391]
  2. Dairy Research Institute (DMI) [1052]

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Human lymphoblastoid cell lines (LCLs), generated through Epstein-Barr Virus (EBV) transformation of B-lymphocytes (B-cells), are a commonly used model system for identifying genetic influences on human diseases and on drug responses. We have previously used LCLs to examine the cellular effects of genetic variants that modulate the efficacy of statins, the most prescribed class of cholesterol-lowering drugs used for the prevention and treatment of cardiovascular disease. However, statin-induced gene expression differences observed in LCLs may be influenced by their transformation, and thus differ from those observed in native B-cells. To assess this possibility, we prepared LCLs and purified B-cells from the same donors, and compared mRNA profiles after 24 h incubation with simvastatin (2 mu M) or sham buffer. Genes involved in cholesterol metabolism were similarly regulated between the two cell types under both the statin and sham-treated conditions, and the statin-induced changes were significantly correlated. Genes whose expression differed between the native and transformed cells were primarily implicated in cell cycle, apoptosis and alternative splicing. We found that ChIP-seq signals for MYC and EBNA2 (an EBV transcriptional co-activator) were significantly enriched in the promoters of genes up-regulated in the LCLs compared with the B-cells, and could be involved in the regulation of cell cycle and alternative splicing. Taken together, the results support the use of LCLs for the study of statin effects on cholesterol metabolism, but suggest that drug effects on cell cycle, apoptosis and alternative splicing may be affected by EBV transformation. This dataset is now uploaded to GEO at the accession number GSE51444

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