Drug Perturbation Gene Set Enrichment Analysis (dpGSEA): a New Transcriptomic Drug Screening Approach

Overview

Journal BMC Bioinformatics

Publisher Biomed Central

Specialty Biology

Date 2021 Jan 13

PMID 33435872

Citations 4

Authors

Mike Fang

Brian Richardson

Cheryl M Cameron

Jean-Eudes Dazard

Mark J Cameron

Affiliations

Soon will be listed here.

Abstract

Background: In this study, we demonstrate that our modified Gene Set Enrichment Analysis (GSEA) method, drug perturbation GSEA (dpGSEA), can detect phenotypically relevant drug targets through a unique transcriptomic enrichment that emphasizes biological directionality of drug-derived gene sets.

Results: We detail our dpGSEA method and show its effectiveness in detecting specific perturbation of drugs in independent public datasets by confirming fluvastatin, paclitaxel, and rosiglitazone perturbation in gastroenteropancreatic neuroendocrine tumor cells. In drug discovery experiments, we found that dpGSEA was able to detect phenotypically relevant drug targets in previously published differentially expressed genes of CD4+T regulatory cells from immune responders and non-responders to antiviral therapy in HIV-infected individuals, such as those involved with virion replication, cell cycle dysfunction, and mitochondrial dysfunction. dpGSEA is publicly available at https://github.com/sxf296/drug_targeting .

Conclusions: dpGSEA is an approach that uniquely enriches on drug-defined gene sets while considering directionality of gene modulation. We recommend dpGSEA as an exploratory tool to screen for possible drug targeting molecules.

Citing Articles

Navigating the Gene Co-Expression Network and Drug Repurposing Opportunities for Brain Disorders Associated with Neurocognitive Impairment.

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Drug mechanism enrichment analysis improves prioritization of therapeutics for repurposing.

Garana B, Joly J, Delfarah A, Hong H, Graham N BMC Bioinformatics. 2023; 24(1):215.

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An Innovative Drug Repurposing Approach to Restrain Endometrial Cancer Metastatization.

Torricelli F, Sauta E, Manicardi V, Mandato V, Palicelli A, Ciarrocchi A Cells. 2023; 12(5).

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Screening Potential Drugs for the Development of NAFLD Based on Drug Perturbation Gene Set.

Gao Z, Dai L, Zhang H Comput Math Methods Med. 2022; 2022:7606716.

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