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Biochem Biophys Res Commun. 2018 Jan 1;495(1):659-665. doi: 10.1016/j.bbrc.2017.11.065. Epub 2017 Nov 14.

Biomarker identification for statin sensitivity of cancer cell lines.

Author information

1
Department of Computational & Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15260, USA; Department of Computer Science, University of Pittsburgh, Pittsburgh, PA 15213, USA.
2
Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA.
3
Department of Veterinary Anatomy, School of Veterinary Medicine, Tottori University, Tottori 680-8553, Japan.
4
Department of Computational & Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15260, USA; Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA; University of Pittsburgh Cancer Institute, Pittsburgh, PA 15213, USA.
5
Department of Computational & Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15260, USA; Department of Computer Science, University of Pittsburgh, Pittsburgh, PA 15213, USA. Electronic address: benos@pitt.edu.
6
Department of Computational & Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15260, USA; Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA. Electronic address: oltvai@pitt.edu.

Abstract

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.

KEYWORDS:

Biomarkers; Graphical models; Statin

PMID:
29146185
PMCID:
PMC5827944
DOI:
10.1016/j.bbrc.2017.11.065
[Indexed for MEDLINE]
Free PMC Article

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