ArticlePloS one2014
Functional Module Connectivity Map (FMCM): a framework for searching repurposed drug compounds for systems treatment of cancer and an application to colorectal adenocarcinoma.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Reconciling multiple connectivity-based systems biology methods for drug repurposing.Briefings in bioinformatics · 2025Review
- Article
- Navigating Transcriptomic Connectivity Mapping Workflows to Link Chemicals with Bioactivities.Chemical research in toxicology · 2022Review
- IdentifyingJournal of immunology research · 2022Article
- Systems-level biomarkers identification and drug repositioning in colorectal cancer.World journal of gastrointestinal oncology · 2021Review
- Parkinson's Disease Master Regulators on Substantia Nigra and Frontal Cortex and Their Use for Drug Repositioning.Molecular neurobiology · 2021Article
- Differential Interactome Based Drug Repositioning Unraveled Abacavir, Exemestane, Nortriptyline Hydrochloride, and Tolcapone as Potential Therapeutics for Colorectal Cancers.Frontiers in bioinformatics · 2021Article
- The Advantages of Connectivity Map Applied in Traditional Chinese Medicine.Frontiers in pharmacology · 2021Review
- Article
- Article
- Drug Repositioning for P-Glycoprotein Mediated Co-Expression Networks in Colorectal Cancer.Frontiers in oncology · 2020Article
- Integrated transcriptomics reveals master regulators of lung adenocarcinoma and novel repositioning of drug candidates.Cancer medicine · 2019Article
- Drug repurposing in oncology: Compounds, pathways, phenotypes and computational approaches for colorectal cancer.Biochimica et biophysica acta. Reviews on cancer · 2019Review
- Revisiting Connectivity Map from a gene co-expression network analysis.Experimental and therapeutic medicine · 2018Article
- A review of connectivity map and computational approaches in pharmacogenomics.Briefings in bioinformatics · 2018Review
- Master Regulators Connectivity Map: A Transcription Factors-Centered Approach to Drug Repositioning.Frontiers in pharmacology · 2018Article
- A linear programming computational framework integrates phosphor-proteomics and prior knowledge to predict drug efficacy.BMC systems biology · 2017Article
- DeSigN: connecting gene expression with therapeutics for drug repurposing and development.BMC genomics · 2017Article
- Commonly prescribed drugs associate with cognitive function: a cross-sectional study in UK Biobank.BMJ open · 2016Article
- Quantitative Identification of Compound-Dependent On-Modules and Differential Allosteric Modules From Homologous Ischemic Networks.CPT: pharmacometrics & systems pharmacology · 2016Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Drug repurposing has become an increasingly attractive approach to drug development owing to the ever-growing cost of new drug discovery and frequent withdrawal of successful drugs caused by side effect issues. Here, we devised Functional Module Connectivity Map (FMCM) for the discovery of repurposed drug compounds for systems treatment of complex diseases, and applied it to colorectal adenocarcinoma. FMCM used multiple functional gene modules to query the Connectivity Map (CMap). The functional modules were built around hub genes identified, through a gene selection by trend-of-disease-progression (GSToP) procedure, from condition-specific gene-gene interaction networks constructed from sets of cohort gene expression microarrays. The candidate drug compounds were restricted to drugs exhibiting predicted minimal intracellular harmful side effects. We tested FMCM against the common practice of selecting drugs using a genomic signature represented by a single set of individual genes to query CMap (IGCM), and found FMCM to have higher robustness, accuracy, specificity, and reproducibility in identifying known anti-cancer agents. Among the 46 drug candidates selected by FMCM for colorectal adenocarcinoma treatment, 65% had literature support for association with anti-cancer activities, and 60% of the drugs predicted to have harmful effects on cancer had been reported to be associated with carcinogens/immune suppressors. Compounds were formed from the selected drug candidates where in each compound the component drugs collectively were beneficial to all the functional modules while no single component drug was harmful to any of the modules. In cell viability tests, we identified four candidate drugs: GW-8510, etacrynic acid, ginkgolide A, and 6-azathymine, as having high inhibitory activities against cancer cells. Through microarray experiments we confirmed the novel functional links predicted for three candidate drugs: phenoxybenzamine (broad effects), GW-8510 (cell cycle), and imipenem (immune system). We believe FMCM can be usefully applied to repurposed drug discovery for systems treatment of other types of cancer and other complex diseases.
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