Journal
BIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS
Volume 495, Issue 1, Pages 659-665Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.bbrc.2017.11.065
Keywords
Biomarkers; Statin; Graphical models
Categories
Funding
- National Institutes of Health [TR000496, T32EB001026, T32CA082084, R01LM012087, U01HL137159]
- Veterans Administration Merit grant
- Japan Society for the Promotion of Science [JP26890019, JP16K18439]
- NATIONAL CANCER INSTITUTE [T32CA082084, F30CA199947] Funding Source: NIH RePORTER
- NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES [UH3TR000496, UH2TR000496] Funding Source: NIH RePORTER
- NATIONAL HEART, LUNG, AND BLOOD INSTITUTE [U01HL137159] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERING [T32EB001026] Funding Source: NIH RePORTER
- NATIONAL LIBRARY OF MEDICINE [R01LM012087] Funding Source: NIH RePORTER
- Veterans Affairs [I01BX003368] Funding Source: NIH RePORTER
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Statins are potent cholesterol reducing drugs that have been shown to reduce tumor cell proliferation in vitro and tumor growth in animal models. Moreover, retrospective human cohort studies demonstrated decreased cancer-specific mortality in patients taking statins. We previously implicated membrane E-cadherin expression as both a marker and mechanism for resistance to atorvastatin-mediated growth suppression of cancer cells; however, a transcriptome-profile-based biomarker signature for statin sensitivity has not yet been reported. Here, we utilized transcriptome data from fourteen NCI-60 cancer cell lines and their statin dose-response data to produce gene expression signatures that identify statin sensitive and resistant cell lines. We experimentally confirmed the validity of the identified biomarker signature in an independent set of cell lines and extended this signature to generate a proposed statin-sensitive subset of tumors listed in the TCGA database. Finally, we predicted drugs that would synergize with statins and found several predicted combination therapies to be experimentally confirmed. The combined bioinformatics-experimental approach described here can be used to generate an initial biomarker signature for anticancer drug therapy. (C) 2017 Elsevier Inc. All rights reserved.
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