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pmid:39458974
The Identification of New Pharmacological Targets for the Treatment of Glaucoma: A Network Pharmacology Approach.
Erika Giuffrida · Chiara Bianca Maria Platania · Francesca Lazzara · Federica Conti · Nicoletta Marcantonio · Filippo Drago · Claudio Bucolo
Pharmaceuticals (Basel, Switzerland) · 2024 doi:10.3390/ph17101333
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Complete file
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Current glaucoma interventions reduce intraocular pressure but do not address retinal neurodegeneration. In this effort, to identify new pharmacological targets for glaucoma management, we employed a network pharmacology approach. Methods: We first retrieved transcriptomic data from GEO, an NCBI database, and carried out GEO2R (an interactive web tool aimed at comparing two or more groups of samples in a GEO dataset). The GEO2R statistical analysis aimed at identifying the top differentially expressed genes (DEGs) and used these as input of STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) app within Cytoscape software, which builds networks of proteins starting from input DEGs. Analyses of centrality metrics using Cytoscape were carried out to identify nodes (genes or proteins) involved in network stability. We also employed the web-server software MIRNET 2.0 to build miRNA-target interaction networks for a re-analysis of the GSE105269 dataset, which reports analyses of microRNA expressions. Results: The pharmacological targets, identified in silico through analyses of the centrality metrics carried out with Cytoscape, were rescored based on correlations with entries in the PubMed and clinicaltrials.gov databases. When there was no match (82 out of 135 identified central nodes, in 8 analyzed networks), targets were considered \"potential innovative\" targets for the treatment of glaucoma, after further validation studies. Conclusions: Several druggable targets, such as GPCRs (e.g., 5-hydroxytryptamine 5A (5-HT5A) and adenosine A2B receptors) and enzymes (e.g., lactate dehydrogenase A or monoamine oxidase B), were found to be rescored as \"potential innovative\" pharmacological targets for glaucoma treatment.", "claims": [{"id": "claim-method", "statement": "DEGs (p < 0.05) for each sample of the GEO datasets (e.g., glaucoma vs. healthy control) were identified using the GEO2R statistical analysis (https://www.ncbi.nlm.nih.gov/geo/info/geo2r.html accessed on 1 March 2022), applying the Benjamini and Hochberg (false discovery rate) method for the adjustment of p-values using standard parameters in GEO2R [23,123,124].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39458974", "locator": "sections[14] \"4.1. 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