Biomarker identification for statin sensitivity of cancer cell lines

Vineet K. Raghu, Colin H. Beckwitt, Katsuhiko Warita, Alan Wells, Panayiotis V. Benos, Zoltán N. Oltvai

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)659-665
Number of pages7
JournalBiochemical and Biophysical Research Communications
Issue number1
StatePublished - Jan 1 2018

Bibliographical note

Funding Information:
We thank J.R. Chaillet for comment on the manuscript. This work was supported by the National Institutes of Health [ TR000496 to AW., T32EB001026 to CB., T32CA082084 to VR., R01LM012087 and U01HL137159 to PVB.], a Veterans Administration Merit grant to AW, and by the Japan Society for the Promotion of Science KAKENHI grants [ JP26890019 and JP16K18439 to KW]. Appendix A

Publisher Copyright:
© 2017 Elsevier Inc.


  • Biomarkers
  • Graphical models
  • Statin

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