Evidence map›Paper›PMID 24475102›Full record

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.

Feng-Hsiang Chung, Yun-Ru Chiang, Ai-Lun Tseng, Yung-Chuan Sung, Jean Lu, Min-Chang Huang, Nianhan Ma, Hoong-Chien Lee

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed.

  1. Review
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  4. IdentifyingJournal of immunology research · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Feng-Hsiang ChungInstitute of Systems Biology and Bioinformatics, National Central University, Zhongli, Taiwan ; Center for Dynamical Biomarkers and Translational Medicine, National Central University, Zhongli, Taiwan.
Yun-Ru ChiangInstitute of Systems Biology and Bioinformatics, National Central University, Zhongli, Taiwan.
Ai-Lun TsengInstitute of Systems Biology and Bioinformatics, National Central University, Zhongli, Taiwan.
Yung-Chuan SungDivision of Hematology and Oncology, Cathay General Hospital, Taipei, Taiwan.
Jean LuInstitute of Biomedical Science, Academia Sinica, Nangang, Taipei, Taiwan.
Min-Chang HuangDepartment of Physics, Chung Yuan Christian University, Zhongli, Taiwan.
Nianhan MaInstitute of Systems Biology and Bioinformatics, National Central University, Zhongli, Taiwan.
Hoong-Chien LeeInstitute of Systems Biology and Bioinformatics, National Central University, Zhongli, Taiwan ; Center for Dynamical Biomarkers and Translational Medicine, National Central University, Zhongli, Taiwan ; Department of Physics, Chung Yuan Christian University, Zhongli, Taiwan ; Cathay Medical Research Institute, Cathay General Hospital, Taipei, Taiwan ; Physics Division, National Center for Theoretical Sciences, Hsinchu, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AlgorithmsAdenocarcinomaColorectal NeoplasmsDrug RepositioningEpistasis, GeneticEthacrynic AcidGene Regulatory NetworksGinkgolidesHumansImipenemIndolesLactonesMicroarray AnalysisPhenoxybenzamineSensitivity and SpecificityThymine6-azathymineEthacrynic Acidginkgolide AGinkgolidesGW8510ImipenemIndolesLactonesPhenoxybenzamineThymine

Identifiers

PMID24475102
PMCPMC3903539

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.