{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,12]],"date-time":"2026-04-12T14:04:00Z","timestamp":1776002640478,"version":"3.50.1"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,1,12]],"date-time":"2021-01-12T00:00:00Z","timestamp":1610409600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2021,1,12]],"date-time":"2021-01-12T00:00:00Z","timestamp":1610409600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"NHBLI\/NIH","award":["T32HL007567"],"award-info":[{"award-number":["T32HL007567"]}]},{"name":"Case\/UHC Center for AIDS research","award":["P30AI036219"],"award-info":[{"award-number":["P30AI036219"]}]},{"name":"Psoriasis Center of Research Translation","award":["P50AR070590"],"award-info":[{"award-number":["P50AR070590"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2021,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>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<jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/github.com\/sxf296\/drug_targeting\">https:\/\/github.com\/sxf296\/drug_targeting<\/jats:ext-link>.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>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.<\/jats:p><\/jats:sec>","DOI":"10.1186\/s12859-020-03929-0","type":"journal-article","created":{"date-parts":[[2021,1,12]],"date-time":"2021-01-12T21:08:06Z","timestamp":1610485686000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Drug perturbation gene set enrichment analysis (dpGSEA): a new transcriptomic drug screening approach"],"prefix":"10.1186","volume":"22","author":[{"given":"Mike","family":"Fang","sequence":"first","affiliation":[]},{"given":"Brian","family":"Richardson","sequence":"additional","affiliation":[]},{"given":"Cheryl M.","family":"Cameron","sequence":"additional","affiliation":[]},{"given":"Jean-Eudes","family":"Dazard","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4768-4094","authenticated-orcid":false,"given":"Mark J.","family":"Cameron","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,1,12]]},"reference":[{"issue":"3","key":"3929_CR1","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1038\/nrd.2017.226","volume":"17","author":"SA Dugger","year":"2018","unstructured":"Dugger SA, Platt A, Goldstein DB. Drug development in the era of precision medicine. Nat Rev Drug Discov. 2018;17(3):183\u201396.","journal-title":"Nat Rev Drug Discov"},{"issue":"1","key":"3929_CR2","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1038\/nrd.2018.168","volume":"18","author":"S Pushpakom","year":"2019","unstructured":"Pushpakom S, et al. Drug repurposing: progress, challenges and recommendations. Nat Rev Drug Discov. 2019;18(1):41\u201358.","journal-title":"Nat Rev Drug Discov."},{"issue":"1","key":"3929_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/nrd.2018.92","volume":"18","author":"A Breckenridge","year":"2019","unstructured":"Breckenridge A, Jacob R. Overcoming the legal and regulatory barriers to drug repurposing. Nat Rev Drug Discov. 2019;18(1):1\u20132.","journal-title":"Nat Rev Drug Discov"},{"key":"3929_CR4","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1016\/j.jbi.2016.09.019","volume":"64","author":"Y Chen","year":"2016","unstructured":"Chen Y, Xu R. Drug repurposing for glioblastoma based on molecular subtypes. J Biomed Inform. 2016;64:131\u20138.","journal-title":"J Biomed Inform"},{"issue":"7270","key":"3929_CR5","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1038\/nature08506","volume":"462","author":"MJ Keiser","year":"2009","unstructured":"Keiser MJ, et al. Predicting new molecular targets for known drugs. Nature. 2009;462(7270):175\u201381.","journal-title":"Nature"},{"key":"3929_CR6","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1186\/1471-2105-14-181","volume":"14","author":"R Xu","year":"2013","unstructured":"Xu R, Wang Q. Large-scale extraction of accurate drug-disease treatment pairs from biomedical literature for drug repurposing. BMC Bioinform. 2013;14:181.","journal-title":"BMC Bioinform"},{"issue":"4","key":"3929_CR7","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1093\/bib\/bbr005","volume":"12","author":"C Andronis","year":"2011","unstructured":"Andronis C, et al. Literature mining, ontologies and information visualization for drug repurposing. Brief Bioinform. 2011;12(4):357\u201368.","journal-title":"Brief Bioinform"},{"issue":"4","key":"3929_CR8","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1093\/bib\/bbr013","volume":"12","author":"JT Dudley","year":"2011","unstructured":"Dudley JT, Deshpande T, Butte AJ. Exploiting drug-disease relationships for computational drug repositioning. Brief Bioinform. 2011;12(4):303\u201311.","journal-title":"Brief Bioinform"},{"issue":"3","key":"3929_CR9","doi-asserted-by":"publisher","first-page":"791","DOI":"10.15252\/msb.20145486","volume":"11","author":"A Wagner","year":"2015","unstructured":"Wagner A, et al. Drugs that reverse disease transcriptomic signatures are more effective in a mouse model of dyslipidemia. Mol Syst Biol. 2015;11(3):791.","journal-title":"Mol Syst Biol"},{"issue":"6","key":"3929_CR10","doi-asserted-by":"publisher","first-page":"627","DOI":"10.1016\/j.cmet.2011.03.020","volume":"13","author":"SD Kunkel","year":"2011","unstructured":"Kunkel SD, et al. mRNA expression signatures of human skeletal muscle atrophy identify a natural compound that increases muscle mass. Cell Metab. 2011;13(6):627\u201338.","journal-title":"Cell Metab"},{"key":"3929_CR11","doi-asserted-by":"publisher","first-page":"17784","DOI":"10.1038\/srep17784","volume":"5","author":"E Shin","year":"2015","unstructured":"Shin E, et al. Drug signature-based finding of additional clinical use of LC28-0126 for neutrophilic bronchial asthma. Sci Rep. 2015;5:17784.","journal-title":"Sci Rep"},{"issue":"1","key":"3929_CR12","doi-asserted-by":"publisher","first-page":"863","DOI":"10.1038\/s41467-019-08854-2","volume":"10","author":"S Fourati","year":"2019","unstructured":"Fourati S, et al. Integrated systems approach defines the antiviral pathways conferring protection by the RV144 HIV vaccine. Nat Commun. 2019;10(1):863.","journal-title":"Nat Commun"},{"issue":"1","key":"3929_CR13","doi-asserted-by":"publisher","first-page":"3967","DOI":"10.1038\/s41467-018-05528-3","volume":"9","author":"JC Mudd","year":"2018","unstructured":"Mudd JC, et al. Hallmarks of primate lentiviral immunodeficiency infection recapitulate loss of innate lymphoid cells. Nat Commun. 2018;9(1):3967.","journal-title":"Nat Commun"},{"issue":"6","key":"3929_CR14","doi-asserted-by":"publisher","first-page":"1528","DOI":"10.1038\/mi.2015.146","volume":"9","author":"RS Veazey","year":"2016","unstructured":"Veazey RS, et al. Prevention of SHIV transmission by topical IFN-beta treatment. Mucosal Immunol. 2016;9(6):1528\u201336.","journal-title":"Mucosal Immunol"},{"issue":"1","key":"3929_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1093\/nar\/gkn923","volume":"37","author":"W da Huang","year":"2009","unstructured":"da Huang W, Sherman BT, Lempicki RA. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 2009a;37(1):1\u201313.","journal-title":"Nucleic Acids Res"},{"issue":"43","key":"3929_CR16","doi-asserted-by":"publisher","first-page":"15545","DOI":"10.1073\/pnas.0506580102","volume":"102","author":"A Subramanian","year":"2005","unstructured":"Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005;102(43):15545\u201350.","journal-title":"Proc Natl Acad Sci U S A"},{"key":"3929_CR17","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1186\/1471-2105-14-7","volume":"14","author":"S Hanzelmann","year":"2013","unstructured":"Hanzelmann S, Castelo R, Guinney J. GSVA: gene set variation analysis for microarray and RNA-seq data. BMC Bioinform. 2013;14:7.","journal-title":"BMC Bioinform"},{"issue":"1","key":"3929_CR18","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1038\/nprot.2008.211","volume":"4","author":"W da Huang","year":"2009","unstructured":"da Huang W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009b;4(1):44\u201357.","journal-title":"Nat Protoc"},{"issue":"D1","key":"3929_CR19","doi-asserted-by":"publisher","first-page":"D419","DOI":"10.1093\/nar\/gky1038","volume":"47","author":"H Mi","year":"2019","unstructured":"Mi H, et al. PANTHER version 14: more genomes, a new PANTHER GO-slim and improvements in enrichment analysis tools. Nucleic Acids Res. 2019;47(D1):D419\u201326.","journal-title":"Nucleic Acids Res"},{"issue":"9","key":"3929_CR20","doi-asserted-by":"publisher","first-page":"1498","DOI":"10.1093\/bioinformatics\/btx800","volume":"34","author":"F Napolitano","year":"2018","unstructured":"Napolitano F, et al. gene2drug: a computational tool for pathway-based rational drug repositioning. Bioinformatics. 2018;34(9):1498\u2013505.","journal-title":"Bioinformatics"},{"issue":"2","key":"3929_CR21","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1093\/bioinformatics\/btv536","volume":"32","author":"F Napolitano","year":"2016","unstructured":"Napolitano F, et al. Drug-set enrichment analysis: a novel tool to investigate drug mode of action. Bioinformatics. 2016;32(2):235\u201341.","journal-title":"Bioinformatics"},{"key":"3929_CR22","doi-asserted-by":"publisher","first-page":"236","DOI":"10.1186\/1471-2105-10-236","volume":"10","author":"SD Zhang","year":"2009","unstructured":"Zhang SD, Gant TW. sscMap: an extensible Java application for connecting small-molecule drugs using gene-expression signatures. BMC Bioinform. 2009;10:236.","journal-title":"BMC Bioinform"},{"key":"3929_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/npjsba.2016.15","volume":"2","author":"Q Duan","year":"2016","unstructured":"Duan Q, et al. L1000CDS(2): LINCS L1000 characteristic direction signatures search engine. NPJ Syst Biol Appl. 2016;2:1\u201312.","journal-title":"NPJ Syst Biol Appl"},{"issue":"5795","key":"3929_CR24","doi-asserted-by":"publisher","first-page":"1929","DOI":"10.1126\/science.1132939","volume":"313","author":"J Lamb","year":"2006","unstructured":"Lamb J, et al. The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease. Science. 2006;313(5795):1929\u201335.","journal-title":"Science"},{"issue":"6","key":"3929_CR25","doi-asserted-by":"publisher","first-page":"1437","DOI":"10.1016\/j.cell.2017.10.049","volume":"171","author":"A Subramanian","year":"2017","unstructured":"Subramanian A, et al. A next generation connectivity map: l1000 platform and the first 1,000,000 profiles. Cell. 2017;171(6):1437\u201352.","journal-title":"Cell"},{"issue":"7","key":"3929_CR26","doi-asserted-by":"publisher","first-page":"e47","DOI":"10.1093\/nar\/gkv007","volume":"43","author":"ME Ritchie","year":"2015","unstructured":"Ritchie ME, et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43(7):e47.","journal-title":"Nucleic Acids Res"},{"issue":"7","key":"3929_CR27","doi-asserted-by":"publisher","first-page":"979","DOI":"10.1038\/s41588-018-0138-4","volume":"50","author":"MJ Alvarez","year":"2018","unstructured":"Alvarez MJ, et al. A precision oncology approach to the pharmacological targeting of mechanistic dependencies in neuroendocrine tumors. Nat Genet. 2018;50(7):979\u201389.","journal-title":"Nat Genet"},{"issue":"11","key":"3929_CR28","doi-asserted-by":"publisher","first-page":"5083","DOI":"10.1172\/JCI120245","volume":"128","author":"SA Younes","year":"2018","unstructured":"Younes SA, et al. Cycling CD4+ T cells in HIV-infected immune nonresponders have mitochondrial dysfunction. J Clin Invest. 2018;128(11):5083\u201394.","journal-title":"J Clin Invest"},{"issue":"Pt 1","key":"3929_CR29","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1042\/BJ20050017","volume":"390","author":"K Yamaguchi","year":"2005","unstructured":"Yamaguchi K, et al. Evidence for mitochondrial localization of a novel human sialidase (NEU4). Biochem J. 2005;390(Pt 1):85\u201393.","journal-title":"Biochem J"},{"issue":"10","key":"3929_CR30","doi-asserted-by":"publisher","first-page":"3484","DOI":"10.1128\/AAC.00344-08","volume":"52","author":"K Hata","year":"2008","unstructured":"Hata K, et al. Limited inhibitory effects of oseltamivir and zanamivir on human sialidases. Antimicrob Agents Chemother. 2008;52(10):3484\u201391.","journal-title":"Antimicrob Agents Chemother"},{"issue":"2","key":"3929_CR31","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1007\/s00380-016-0891-1","volume":"32","author":"Y Wang","year":"2017","unstructured":"Wang Y, et al. Ibutilide protects against cardiomyocytes injury via inhibiting endoplasmic reticulum and mitochondrial stress pathways. Heart Vessels. 2017;32(2):208\u201315.","journal-title":"Heart Vessels"},{"issue":"Series B","key":"3929_CR32","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","volume":"57","author":"Y Benjamini","year":"1995","unstructured":"Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Statist Soc. 1995;57(Series B):289\u2013300.","journal-title":"J R Statist Soc"},{"issue":"1","key":"3929_CR33","doi-asserted-by":"publisher","first-page":"256","DOI":"10.1186\/s12859-017-1674-0","volume":"18","author":"J Zyla","year":"2017","unstructured":"Zyla J, et al. Ranking metrics in gene set enrichment analysis: do they matter? BMC Bioinform. 2017;18(1):256.","journal-title":"BMC Bioinform"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-020-03929-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/s12859-020-03929-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-020-03929-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,22]],"date-time":"2024-08-22T06:52:56Z","timestamp":1724309576000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/s12859-020-03929-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,12]]},"references-count":33,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,12]]}},"alternative-id":["3929"],"URL":"https:\/\/doi.org\/10.1186\/s12859-020-03929-0","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1,12]]},"assertion":[{"value":"1 April 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 December 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 January 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"No ethics approval was required for this study.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"22"}}