Article (Scientific journals)
Identifying and targeting cancer-specific metabolism with network-based drug target prediction
Pacheco, Maria; Bintener, Tamara Jean Rita; Ternes, Dominik et al.
2019In EBioMedicine, 43 (May 2019), p. 98-106
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Keywords :
Metabolic modelling; Cancer; Machine learning; Drug repurposing
Abstract :
[en] Background Metabolic rewiring allows cancer cells to sustain high proliferation rates. Thus, targeting only the cancer-specific cellular metabolism will safeguard healthy tissues. Methods We developed the very efficient FASTCORMICS RNA-seq workflow (rFASTCORMICS) to build 10,005 high-resolution metabolic models from the TCGA dataset to capture metabolic rewiring strategies in cancer cells. Colorectal cancer (CRC) was used as a test case for a repurposing workflow based on rFASTCORMICS. Findings Alternative pathways that are not required for proliferation or survival tend to be shut down and, therefore, tumours display cancer-specific essential genes that are significantly enriched for known drug targets. We identified naftifine, ketoconazole, and mimosine as new potential CRC drugs, which were experimentally validated. Interpretation The here presented rFASTCORMICS workflow successfully reconstructs a metabolic model based on RNA-seq data and successfully predicted drug targets and drugs not yet indicted for colorectal cancer.
Disciplines :
Life sciences: Multidisciplinary, general & others
Author, co-author :
Pacheco, Maria ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit
Bintener, Tamara Jean Rita ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit
Ternes, Dominik ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit
Kulms, Dagmar;  Technical University Dresden > Department of Dermatology > Experimental Dermatology ; Technical University Dresden > Center for Regenerative Therapies
Haan, Serge ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit
Letellier, Elisabeth ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit
Sauter, Thomas ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit
External co-authors :
yes
Language :
English
Title :
Identifying and targeting cancer-specific metabolism with network-based drug target prediction
Publication date :
May 2019
Journal title :
EBioMedicine
ISSN :
2352-3964
Publisher :
Elsevier, Amsterdam, Netherlands
Volume :
43
Issue :
May 2019
Pages :
98-106
Peer reviewed :
Peer Reviewed verified by ORBi
Focus Area :
Systems Biomedicine
Available on ORBilu :
since 29 July 2019

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