4.6 Article

Biomarker identification for statin sensitivity of cancer cell lines

期刊

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.bbrc.2017.11.065

关键词

Biomarkers; Statin; Graphical models

资金

  1. National Institutes of Health [TR000496, T32EB001026, T32CA082084, R01LM012087, U01HL137159]
  2. Veterans Administration Merit grant
  3. Japan Society for the Promotion of Science [JP26890019, JP16K18439]
  4. NATIONAL CANCER INSTITUTE [T32CA082084, F30CA199947] Funding Source: NIH RePORTER
  5. NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES [UH3TR000496, UH2TR000496] Funding Source: NIH RePORTER
  6. NATIONAL HEART, LUNG, AND BLOOD INSTITUTE [U01HL137159] Funding Source: NIH RePORTER
  7. NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERING [T32EB001026] Funding Source: NIH RePORTER
  8. NATIONAL LIBRARY OF MEDICINE [R01LM012087] Funding Source: NIH RePORTER
  9. Veterans Affairs [I01BX003368] Funding Source: NIH RePORTER

向作者/读者索取更多资源

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.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据