Mike Fang1, Brian Richardson1,2, Cheryl M Cameron3,2, Jean-Eudes Dazard4,5, Mark J Cameron6,7. 1. Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Wolstein Research Building, 2103 Cornell Road, Suite 1-314, Cleveland, OH, 44106-7295, USA. 2. Systems Biology and Bioinformatics Program, Case Western Reserve University, Cleveland, OH, USA. 3. Department of Nutrition, Case Western Reserve University, Cleveland, OH, USA. 4. Center for Proteomics and Bioinformatics, Case Western Reserve University, Cleveland, OH, USA. jxd101@case.edu. 5. Systems Biology and Bioinformatics Program, Case Western Reserve University, Cleveland, OH, USA. jxd101@case.edu. 6. Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Wolstein Research Building, 2103 Cornell Road, Suite 1-314, Cleveland, OH, 44106-7295, USA. mark.cameron@case.edu. 7. Systems Biology and Bioinformatics Program, Case Western Reserve University, Cleveland, OH, USA. mark.cameron@case.edu.
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.
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.
Entities:
Keywords:
Drug discovery; Gene set enrichment analysis; Transcriptomics
Authors: Aravind Subramanian; Pablo Tamayo; Vamsi K Mootha; Sayan Mukherjee; Benjamin L Ebert; Michael A Gillette; Amanda Paulovich; Scott L Pomeroy; Todd R Golub; Eric S Lander; Jill P Mesirov Journal: Proc Natl Acad Sci U S A Date: 2005-09-30 Impact factor: 11.205