Your browser doesn't support javascript.
loading
Accurate Drug Repositioning through Non-tissue-Specific Core Signatures from Cancer Transcriptomes.
Xu, Chi; Ai, Daosheng; Shi, Dawei; Suo, Shengbao; Chen, Xingwei; Yan, Yizhen; Cao, Yaqiang; Zhang, Rui; Sun, Na; Chen, Weizhong; McDermott, Joseph; Zhang, Shiqiang; Zeng, Yingying; Han, Jing-Dong Jackie.
Afiliación
  • Xu C; 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 Bi
  • Ai D; 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 Bi
  • Shi D; 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 Bi
  • Suo S; 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 Bi
  • Chen X; 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 Bi
  • Yan Y; 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 Bi
  • Cao Y; 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 Bi
  • Zhang R; 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 Bi
  • Sun N; 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 Bi
  • Chen W; 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 Bi
  • McDermott J; 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 Bi
  • Zhang S; 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 Bi
  • Zeng Y; 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 Bi
  • Han JJ; 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 Bi
Cell Rep ; 25(2): 523-535.e5, 2018 10 09.
Article en En | MEDLINE | ID: mdl-30304690
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-ß 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.
Asunto(s)
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Transducción de Señal / Regulación Neoplásica de la Expresión Génica / Bases de Datos Factuales / Biología Computacional / Reposicionamiento de Medicamentos / Transcriptoma / Neoplasias Tipo de estudio: Prognostic_studies Límite: Animals / Humans Idioma: En Revista: Cell Rep Año: 2018 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Transducción de Señal / Regulación Neoplásica de la Expresión Génica / Bases de Datos Factuales / Biología Computacional / Reposicionamiento de Medicamentos / Transcriptoma / Neoplasias Tipo de estudio: Prognostic_studies Límite: Animals / Humans Idioma: En Revista: Cell Rep Año: 2018 Tipo del documento: Article