ArticlePLoS computational biology2015
Deciphering Signaling Pathway Networks to Understand the Molecular Mechanisms of Metformin Action.
Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 13 papers.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 23 citations in OpenAlex.
- AΙ-Driven Drug Repurposing: Applications and Challenges.Medicines (Basel, Switzerland) · 2025Review
- Drug repurposing for cancer therapy.Signal transduction and targeted therapy · 2024Review
- Rewiring Drug Research and Development through Human Data-Driven Discovery (HDPharmaceutics · 2023Review
- Allostery, and how to define and measure signal transduction.Biophysical chemistry · 2022Review
- Integrating protein localization with automated signaling pathway reconstruction.BMC bioinformatics · 2019Article
- Correction: Deciphering Signaling Pathway Networks to Understand the Molecular Mechanisms of Metformin Action.PLoS computational biology · 2019Article
- Meta-path Based Prioritization of Functional Drug Actions with Multi-Level Biological Networks.Scientific reports · 2019Article
- Streptozotocin-induced β-cell damage, high fat diet, and metformin administration regulate Hes3 expression in the adult mouse brain.Scientific reports · 2018Article
- 2017 update on the relationship between diabetes and colorectal cancer: epidemiology, potential molecular mechanisms and therapeutic implications.Oncotarget · 2017Review
- Genomic Characterization of Metformin Hepatic Response.PLoS genetics · 2016Article
- A network-based drug repositioning infrastructure for precision cancer medicine through targeting significantly mutated genes in the human cancer genomes.Journal of the American Medical Informatics Association : JAMIA · 2016Article
- Toward Repurposing Metformin as a Precision Anti-Cancer Therapy Using Structural Systems Pharmacology.Scientific reports · 2016Article
- Providing data science support for systems pharmacology and its implications to drug discovery.Expert opinion on drug discovery · 2016Review
Corrections and comments
- Erratum issued
Authors and funding
13 authors at 4 institutions in 2 countries.
Funding
Abstract
A drug exerts its effects typically through a signal transduction cascade, which is non-linear and involves intertwined networks of multiple signaling pathways. Construction of such a signaling pathway network (SPNetwork) can enable identification of novel drug targets and deep understanding of drug action. However, it is challenging to synopsize critical components of these interwoven pathways into one network. To tackle this issue, we developed a novel computational framework, the Drug-specific Signaling Pathway Network (DSPathNet). The DSPathNet amalgamates the prior drug knowledge and drug-induced gene expression via random walk algorithms. Using the drug metformin, we illustrated this framework and obtained one metformin-specific SPNetwork containing 477 nodes and 1,366 edges. To evaluate this network, we performed the gene set enrichment analysis using the disease genes of type 2 diabetes (T2D) and cancer, one T2D genome-wide association study (GWAS) dataset, three cancer GWAS datasets, and one GWAS dataset of cancer patients with T2D on metformin. The results showed that the metformin network was significantly enriched with disease genes for both T2D and cancer, and that the network also included genes that may be associated with metformin-associated cancer survival. Furthermore, from the metformin SPNetwork and common genes to T2D and cancer, we generated a subnetwork to highlight the molecule crosstalk between T2D and cancer. The follow-up network analyses and literature mining revealed that seven genes (CDKN1A, ESR1, MAX, MYC, PPARGC1A, SP1, and STK11) and one novel MYC-centered pathway with CDKN1A, SP1, and STK11 might play important roles in metformin's antidiabetic and anticancer effects. Some results are supported by previous studies. In summary, our study 1) develops a novel framework to construct drug-specific signal transduction networks; 2) provides insights into the molecular mode of metformin; 3) serves a model for exploring signaling pathways to facilitate understanding of drug action, disease pathogenesis, and identification of drug targets.
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Registered trials
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.