Dataset Information

Identifying and targeting cancer-specific metabolism with network-based drug target prediction.

ABSTRACT:

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. FUND: This study was supported by the University of Luxembourg (IRP grant scheme; R-AGR-0755-12), the Luxembourg National Research Fund (FNR PRIDE PRIDE15/10675146/CANBIO), the Fondation Cancer (Luxembourg), the European Union's Horizon2020 research and innovation programme under the Marie Sklodowska- Curie grant agreement No 642295 (MEL-PLEX), and the German Federal Ministry of Education and Research (BMBF) within the project MelanomSensitivity (BMBF/BM/7643621).

SUBMITTER: Pacheco MP

PROVIDER: S-EPMC6558238 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Publications

Identifying and targeting cancer-specific metabolism with network-based drug target prediction.

Pacheco Maria Pires MP Bintener Tamara T Ternes Dominik D Kulms Dagmar D Haan Serge S Letellier Elisabeth E Sauter Thomas T

EBioMedicine 20190522

<h4>Background</h4>Metabolic rewiring allows cancer cells to sustain high proliferation rates. Thus, targeting only the cancer-specific cellular metabolism will safeguard healthy tissues.<h4>Methods</h4>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 rFASTCOR ...[more]

PMID: 31126892

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Dataset Information

Identifying and targeting cancer-specific metabolism with network-based drug target prediction.

Background

Methods

Findings

Interpretation

Publications

Identifying and targeting cancer-specific metabolism with network-based drug target prediction.

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