{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,17]],"date-time":"2026-05-17T07:25:58Z","timestamp":1779002758145,"version":"3.51.4"},"reference-count":35,"publisher":"Oxford University Press (OUP)","issue":"17","license":[{"start":{"date-parts":[[2016,10,2]],"date-time":"2016-10-02T00:00:00Z","timestamp":1475366400000},"content-version":"vor","delay-in-days":772,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/3.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,9,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Analysis of relationships of drug structure to biological response is key to understanding off-target and unexpected drug effects, and for developing hypotheses on how to tailor drug therapies. New methods are required for integrated analyses of a large number of chemical features of drugs against the corresponding genome-wide responses of multiple cell models.<\/jats:p>\n               <jats:p>Results: In this article, we present the first comprehensive multi-set analysis on how the chemical structure of drugs impacts on genome-wide gene expression across several cancer cell lines [Connectivity Map (CMap) database]. The task is formulated as searching for drug response components across multiple cancers to reveal shared effects of drugs and the chemical features that may be responsible. The components can be computed with an extension of a recent approach called Group Factor Analysis. We identify 11 components that link the structural descriptors of drugs with specific gene expression responses observed in the three cell lines and identify structural groups that may be responsible for the responses. Our method quantitatively outperforms the limited earlier methods on CMap and identifies both the previously reported associations and several interesting novel findings, by taking into account multiple cell lines and advanced 3D structural descriptors. The novel observations include: previously unknown similarities in the effects induced by 15-delta prostaglandin J2 and HSP90 inhibitors, which are linked to the 3D descriptors of the drugs; and the induction by simvastatin of leukemia-specific response, resembling the effects of corticosteroids.<\/jats:p>\n               <jats:p>Availability and implementation: Source Code implementing the method is available at: http:\/\/research.ics.aalto.fi\/mi\/software\/GFAsparse<\/jats:p>\n               <jats:p>Contact: \u00a0suleiman.khan@aalto.fi or samuel.kaski@aalto.fi<\/jats:p>\n               <jats:p>Supplementary Information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btu456","type":"journal-article","created":{"date-parts":[[2014,8,26]],"date-time":"2014-08-26T11:23:57Z","timestamp":1409052237000},"page":"i497-i504","source":"Crossref","is-referenced-by-count":34,"title":["Identification of structural features in chemicals associated with cancer drug response: a systematic data-driven analysis"],"prefix":"10.1093","volume":"30","author":[{"given":"Suleiman A.","family":"Khan","sequence":"first","affiliation":[{"name":"1 Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, 00076 Espoo, 2Institute for Molecular Medicine Finland FIMM, University of Helsinki, 00014 Helsinki, 3School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, 70211 Kuopio and 4Department of Computer Science, Helsinki Institute for Information Technology HIIT, University Of Helsinki, 00014 Helsinki, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Seppo","family":"Virtanen","sequence":"additional","affiliation":[{"name":"1 Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, 00076 Espoo, 2Institute for Molecular Medicine Finland FIMM, University of Helsinki, 00014 Helsinki, 3School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, 70211 Kuopio and 4Department of Computer Science, Helsinki Institute for Information Technology HIIT, University Of Helsinki, 00014 Helsinki, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Olli P.","family":"Kallioniemi","sequence":"additional","affiliation":[{"name":"1 Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, 00076 Espoo, 2Institute for Molecular Medicine Finland FIMM, University of Helsinki, 00014 Helsinki, 3School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, 70211 Kuopio and 4Department of Computer Science, Helsinki Institute for Information Technology HIIT, University Of Helsinki, 00014 Helsinki, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Krister","family":"Wennerberg","sequence":"additional","affiliation":[{"name":"1 Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, 00076 Espoo, 2Institute for Molecular Medicine Finland FIMM, University of Helsinki, 00014 Helsinki, 3School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, 70211 Kuopio and 4Department of Computer Science, Helsinki Institute for Information Technology HIIT, University Of Helsinki, 00014 Helsinki, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Antti","family":"Poso","sequence":"additional","affiliation":[{"name":"1 Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, 00076 Espoo, 2Institute for Molecular Medicine Finland FIMM, University of Helsinki, 00014 Helsinki, 3School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, 70211 Kuopio and 4Department of Computer Science, Helsinki Institute for Information Technology HIIT, University Of Helsinki, 00014 Helsinki, Finland"},{"name":"1 Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, 00076 Espoo, 2Institute for Molecular Medicine Finland FIMM, University of Helsinki, 00014 Helsinki, 3School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, 70211 Kuopio and 4Department of Computer Science, Helsinki Institute for Information Technology HIIT, University Of Helsinki, 00014 Helsinki, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Samuel","family":"Kaski","sequence":"additional","affiliation":[{"name":"1 Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, 00076 Espoo, 2Institute for Molecular Medicine Finland FIMM, University of Helsinki, 00014 Helsinki, 3School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, 70211 Kuopio and 4Department of Computer Science, Helsinki Institute for Information Technology HIIT, University Of Helsinki, 00014 Helsinki, Finland"},{"name":"1 Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, 00076 Espoo, 2Institute for Molecular Medicine Finland FIMM, University of Helsinki, 00014 Helsinki, 3School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, 70211 Kuopio and 4Department of Computer Science, Helsinki Institute for Information Technology HIIT, University Of Helsinki, 00014 Helsinki, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2014,8,22]]},"reference":[{"key":"2023012711535270900_btu456-B1","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1089\/cmb.2010.0255","article-title":"An algorithmic framework for predicting side-effects of drugs","volume":"18","author":"Atias","year":"2011","journal-title":"J. Comput. Biol."},{"key":"2023012711535270900_btu456-B2","doi-asserted-by":"crossref","first-page":"e69513","DOI":"10.1371\/journal.pone.0069513","article-title":"Integrated analysis of drug-induced gene expression profiles predicts novel hERG inhibitors","volume":"8","author":"Babcock","year":"2013","journal-title":"PLoS One"},{"key":"2023012711535270900_btu456-B3","doi-asserted-by":"crossref","first-page":"2881","DOI":"10.1093\/bioinformatics\/btq550","article-title":"Investigating the correlations among the chemical structures, bioactivity profiles and molecular targets of small molecules","volume":"26","author":"Cheng","year":"2010","journal-title":"Bioinformatics"},{"key":"2023012711535270900_btu456-B4","doi-asserted-by":"crossref","first-page":"482","DOI":"10.1182\/blood.V10.5.482.482","article-title":"Response of patients with leukemia to 8-azaguanine","volume":"10","author":"Colsky","year":"1955","journal-title":"Blood"},{"key":"2023012711535270900_btu456-B5","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1021\/ja00226a005","article-title":"Comparative molecular field analysis (CoMFA), effect of shape on binding of steroids to carrier proteins","volume":"110","author":"Cramer","year":"1988","journal-title":"J. Am. Chem. Soc."},{"key":"2023012711535270900_btu456-B6","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1093\/nar\/gkm791","article-title":"ChEBI: a database and ontology for Chemical Entities of Biological Interest","volume":"36","author":"Degtyarenko","year":"2008","journal-title":"Nucleic Acids Res."},{"key":"2023012711535270900_btu456-B7","doi-asserted-by":"crossref","first-page":"1813","DOI":"10.1021\/ci800037t","article-title":"Development and validation of AMANDA, a new algorithm for selecting highly relevant regions in molecular interaction fields","volume":"48","author":"Duran","year":"2008","journal-title":"J. Chem. Inf. Model"},{"key":"2023012711535270900_btu456-B8","doi-asserted-by":"crossref","first-page":"1246","DOI":"10.1124\/mol.107.038042","article-title":"Inhibition of trail gene expression by cyclopentenonic prostaglandin 15-deoxy-delta12,14-prostaglandin J2 in T lymphocytes","volume":"72","author":"Fionda","year":"2007","journal-title":"Mol. Pharmacol."},{"key":"2023012711535270900_btu456-B9","first-page":"199","article-title":"Circular fingerprints: flexible molecular descriptors with applications from physical chemistry to ADME","volume":"9","author":"Glen","year":"2006","journal-title":"IDrugs"},{"key":"2023012711535270900_btu456-B10","doi-asserted-by":"crossref","first-page":"496","DOI":"10.1038\/msb.2011.26","article-title":"PREDICT: a method for inferring novel drug indications with application to personalized medicine","volume":"7","author":"Gottlieb","year":"2011","journal-title":"Mol. Syst. Biol."},{"key":"2023012711535270900_btu456-B11","doi-asserted-by":"crossref","first-page":"840","DOI":"10.1038\/nchembio.1367","article-title":"Niche-based screening identifies small-molecule inhibitors of leukemia stem cells","volume":"9","author":"Hartwell","year":"2013","journal-title":"Nat. Chem. Biol."},{"key":"2023012711535270900_btu456-B12","doi-asserted-by":"crossref","first-page":"6909","DOI":"10.1182\/blood-2010-11-317750","article-title":"\u039412-prostaglandin J3, an omega-3 fatty acid-derived metabolite, selectively ablates leukemia stem cells in mice","volume":"118","author":"Hegde","year":"2011","journal-title":"Blood"},{"key":"2023012711535270900_btu456-B13","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1093\/biomet\/28.3-4.321","article-title":"Relations between two sets of variants","volume":"28","author":"Hotelling","year":"1936","journal-title":"Biometrika"},{"key":"2023012711535270900_btu456-B14","doi-asserted-by":"crossref","first-page":"14621","DOI":"10.1073\/pnas.1000138107","article-title":"Discovery of drug mode of action and drug repositioning from transcriptional responses","volume":"107","author":"Iorio","year":"2010","journal-title":"Proc. Natl Acad. Sci. USA"},{"key":"2023012711535270900_btu456-B15","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1093\/nar\/gng015","article-title":"Summaries of Affymetrix GeneChip probe level data","volume":"31","author":"Irizarry","year":"2003","journal-title":"Nucleic Acids Res."},{"key":"2023012711535270900_btu456-B16","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1371\/journal.pcbi.1000925","article-title":"Drug-induced regulation of target expression","volume":"6","author":"Iskar","year":"2010","journal-title":"PLoS Comput. Biol."},{"key":"2023012711535270900_btu456-B17","doi-asserted-by":"crossref","first-page":"609","DOI":"10.1016\/j.copbio.2011.11.010","article-title":"Drug discovery in the age of systems biology: the rise of computational approaches for data integration","volume":"23","author":"Iskar","year":"2012","journal-title":"Curr. Opin. Biotechnol."},{"key":"2023012711535270900_btu456-B18","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1038\/nature08506","article-title":"Predicting new molecular targets for known drugs","volume":"462","author":"Keiser","year":"2009","journal-title":"Nature"},{"key":"2023012711535270900_btu456-B19","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1186\/1471-2105-13-112","article-title":"Comprehensive data-driven analysis of the impact of chemoinformatic structure on the genome-wide biological response profiles of cancer cells to 1159 drugs","volume":"13","author":"Khan","year":"2012","journal-title":"BMC Bioinformatics"},{"key":"2023012711535270900_btu456-B20","doi-asserted-by":"crossref","first-page":"876","DOI":"10.1002\/cbic.200400369","article-title":"GPCR antitarget modeling: pharmacophore models for biogenic amine binding GPCRs to avoid GPCR-mediated side effects","volume":"6","author":"Klabunde","year":"2005","journal-title":"ChemBioChem"},{"key":"2023012711535270900_btu456-B21","first-page":"965","article-title":"Bayesian canonical correlation analysis","volume":"14","author":"Klami","year":"2013","journal-title":"J. Mach. Learn. Res."},{"key":"2023012711535270900_btu456-B22","doi-asserted-by":"crossref","first-page":"1676","DOI":"10.1039\/c3mb25438k","article-title":"Finding the targets of a drug by integration of gene expression data with a protein interaction network","volume":"9","author":"Laenen","year":"2013","journal-title":"Mol. Biosyst."},{"key":"2023012711535270900_btu456-B23","doi-asserted-by":"crossref","first-page":"1929","DOI":"10.1126\/science.1132939","article-title":"The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease","volume":"313","author":"Lamb","year":"2006","journal-title":"Science"},{"key":"2023012711535270900_btu456-B24","doi-asserted-by":"crossref","first-page":"1251","DOI":"10.1021\/tx200148a","article-title":"Predicting drug-induced hepatotoxicity using QSAR and toxicogenomics approaches","volume":"24","author":"Low","year":"2011","journal-title":"Chem. Res. Toxicol."},{"key":"2023012711535270900_btu456-B25","doi-asserted-by":"crossref","first-page":"e61318","DOI":"10.1371\/journal.pone.0061318","article-title":"Machine learning prediction of cancer cell sensitivity to drugs based on genomic and chemical properties","volume":"8","author":"Menden","year":"2013","journal-title":"PLoS One"},{"key":"2023012711535270900_btu456-B26","article-title":"Bayesian learning for neural networks","author":"Neal","year":"1995"},{"key":"2023012711535270900_btu456-B27","doi-asserted-by":"crossref","first-page":"742","DOI":"10.1021\/ci100050t","article-title":"Extended-connectivity fingerprints","volume":"50","author":"Rogers","year":"2010","journal-title":"J. Chem. Inf. Model"},{"key":"2023012711535270900_btu456-B28","doi-asserted-by":"crossref","first-page":"1441","DOI":"10.1002\/etc.2249","article-title":"Predicting modes of toxic action from chemical structure","volume":"32","author":"Russom","year":"2013","journal-title":"Environ. Toxicol. Chem."},{"key":"2023012711535270900_btu456-B29","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1038\/nrd3139","article-title":"Virtual screening: an endless staircase? Nat","volume":"9","author":"Schneider","year":"2010","journal-title":"Rev. Drug Discov."},{"key":"2023012711535270900_btu456-B30","first-page":"1269","article-title":"Bayesian group factor analysis. In Proceedings of AISTATS","volume":"22","author":"Virtanen","year":"2012","journal-title":"J. Mach. Learn. Res. W&CP"},{"key":"2023012711535270900_btu456-B31","doi-asserted-by":"crossref","first-page":"625","DOI":"10.1111\/and.12127","article-title":"A computational bioinformatics analysis of gene expression identifies candidate agent for prostate cancer","volume":"46","author":"Wen","year":"2013","journal-title":"Andrologia"},{"key":"2023012711535270900_btu456-B32","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1146\/annurev-pharmtox-010611-134630","article-title":"Novel computational approaches to polypharmacology as a means to define responses to individual drugs","volume":"52","author":"Xie","year":"2012","journal-title":"Annu. Rev. Pharmacol."},{"key":"2023012711535270900_btu456-B33","doi-asserted-by":"crossref","first-page":"6771","DOI":"10.1021\/jm200666a","article-title":"Chemical structural novelty: on-targets and off-targets","volume":"54","author":"Yera","year":"2011","journal-title":"J. Med. Chem."},{"key":"2023012711535270900_btu456-B34","doi-asserted-by":"crossref","first-page":"2234","DOI":"10.1158\/1535-7163.MCT-06-0134","article-title":"Potential use of alexidine dihydrochloride as an apoptosis-promoting anticancer agent","volume":"5","author":"Yip","year":"2006","journal-title":"Mol. Cancer Ther."},{"key":"2023012711535270900_btu456-B35","doi-asserted-by":"crossref","first-page":"3071","DOI":"10.1158\/0008-5472.CAN-09-2877","article-title":"The Connectivity Map links iron regulatory protein-1-mediated inhibition of hypoxia-inducible factor-2a translation to the anti-inflammatory 15-deoxy-delta12,14-prostaglandin J2","volume":"70","author":"Zimmer","year":"2010","journal-title":"Cancer Res."}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/30\/17\/i497\/48927005\/bioinformatics_30_17_i497.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/30\/17\/i497\/48927005\/bioinformatics_30_17_i497.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,27]],"date-time":"2023-01-27T12:26:22Z","timestamp":1674822382000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/30\/17\/i497\/200498"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,8,22]]},"references-count":35,"journal-issue":{"issue":"17","published-print":{"date-parts":[[2014,9,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btu456","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2014,9,1]]},"published":{"date-parts":[[2014,8,22]]}}}