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Sci Rep. 2016 Feb 4;6:20441. doi: 10.1038/srep20441.

Toward Repurposing Metformin as a Precision Anti-Cancer Therapy Using Structural Systems Pharmacology.

Hart T1,2, Dider S2, Han W3, Xu H4, Zhao Z5,6,7,8, Xie L9,10.

Author information

1
The Rockefeller University, New York, New York, United States of America.
2
Department of Biological Sciences, Hunter College, The City University of New York, New York, New York, United States of America.
3
The Key Laboratory for Molecular Enzymology and Engineering, Ministry of Education Jilin University, Changchun, P. R. China.
4
School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America.
5
Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.
6
Department of Psychiatry, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.
7
Department of Cancer Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.
8
Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America.
9
Ph.D. Program in Computer Science, Biology, and Biochemistry, The Graduate Center, The City University of New York, New York, New York, United States of America.
10
Department of Computer Science, Hunter College, The City University of New York, New York, New York, United States of America.

Abstract

Metformin, a drug prescribed to treat type-2 diabetes, exhibits anti-cancer effects in a portion of patients, but the direct molecular and genetic interactions leading to this pleiotropic effect have not yet been fully explored. To repurpose metformin as a precision anti-cancer therapy, we have developed a novel structural systems pharmacology approach to elucidate metformin's molecular basis and genetic biomarkers of action. We integrated structural proteome-scale drug target identification with network biology analysis by combining structural genomic, functional genomic, and interactomic data. Through searching the human structural proteome, we identified twenty putative metformin binding targets and their interaction models. We experimentally verified the interactions between metformin and our top-ranked kinase targets. Notably, kinases, particularly SGK1 and EGFR were identified as key molecular targets of metformin. Subsequently, we linked these putative binding targets to genes that do not directly bind to metformin but whose expressions are altered by metformin through protein-protein interactions, and identified network biomarkers of phenotypic response of metformin. The molecular targets and the key nodes in genetic networks are largely consistent with the existing experimental evidence. Their interactions can be affected by the observed cancer mutations. This study will shed new light into repurposing metformin for safe, effective, personalized therapies.

PMID:
26841718
PMCID:
PMC4740793
DOI:
10.1038/srep20441
[Indexed for MEDLINE]
Free PMC Article

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