2. Academic Validation
  3. Accurate Drug Repositioning through Non-tissue-Specific Core Signatures from Cancer Transcriptomes

Accurate Drug Repositioning through Non-tissue-Specific Core Signatures from Cancer Transcriptomes

  • Cell Rep. 2018 Oct 9;25(2):523-535.e5. doi: 10.1016/j.celrep.2018.09.031.
Chi Xu 1,  Daosheng Ai 2,  Dawei Shi 2,  Shengbao Suo 2,  Xingwei Chen 1,  Yizhen Yan 1,  Yaqiang Cao 1,  Rui Zhang 2,  Na Sun 2,  Weizhong Chen 2,  Joseph McDermott 2,  Shiqiang Zhang 1,  Yingying Zeng 1,  Jing-Dong Jackie Han 3
Affiliations

Affiliations

  • 1 Key Laboratory of Computational Biology, Chinese Academy of Sciences Center for Excellence in Molecular Cell Science, Collaborative Innovation Center for Genetics and Developmental Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of Sciences, Beijing 100049, China.
  • 2 Key Laboratory of Computational Biology, Chinese Academy of Sciences Center for Excellence in Molecular Cell Science, Collaborative Innovation Center for Genetics and Developmental Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
  • 3 Key Laboratory of Computational Biology, Chinese Academy of Sciences Center for Excellence in Molecular Cell Science, Collaborative Innovation Center for Genetics and Developmental Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China. Electronic address: jdhan@picb.ac.cn.
PMID: 30304690 DOI: 10.1016/j.celrep.2018.09.031
Abstract

Experimental large-scale screens for drug repositioning are limited by restriction to in vitro conditions and lack of applicability to real human conditions. Here, we developed an in silico screen in human in vivo conditions using a reference of single gene mutations' non-tissue-specific "core transcriptome signatures" (CSs) of 8,476 genes generated from the TCGA database. We developed the core-signature drug-to-gene (csD2G) software to scan 3,546 drug treatment profiles against the reference signatures. csD2G significantly outperformed conventional cell line-based gene perturbation signatures and existing drug-repositioning methods in both coverage and specificity. We highlight this with 3 demonstrated applications: (1) repositioned category of psychiatric drugs to inhibit the TGF-β pathway; (2) antihypertensive Calcium Channel blockers predicted to activate AMPK and inhibit Akt pathways, and validated by clinical electronic medical records; and (3) 7 drugs predicted and validated to selectively target the AKT-FOXO and AMPK pathways and thus regulate worm lifespan.

Keywords

cancer genomics; data integrative analysis; drug repositioning; drug target.

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