{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,22]],"date-time":"2025-11-22T11:10:05Z","timestamp":1763809805693,"version":"3.32.0"},"reference-count":41,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2017,12,1]],"date-time":"2017-12-01T00:00:00Z","timestamp":1512086400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2017,12,1]],"date-time":"2017-12-01T00:00:00Z","timestamp":1512086400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["1U54HD090215\u201001"],"award-info":[{"award-number":["1U54HD090215\u201001"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Quant. Biol."],"published-print":{"date-parts":[[2017,12]]},"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Precision medicine attempts to tailor the right therapy for the right patient. Recent progress in large\u2010scale collection of patents\u2019 tumor molecular profiles in The Cancer Genome Atlas (TCGA) provides a foundation for systematic discovery of potential drug targets specific to different types of cancer. However, we still lack powerful computational methods to effectively integrate multiple omics data and protein\u2010protein interaction network technology for an optimum target and drug recommendation for an individual patient.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>In this study, a computation method, Precision Medicine Target\u2010\nDrug Selection (PMTDS) based on genetic interaction networks is developed to select the optimum targets and associated drugs for precision medicine style treatment of cancer. The PMTDS system includes three parts: a personalized medicine knowledgebase for each cancer type, a genetic interaction network\u2010based algorithm and a single patient molecular profiles. The knowledgebase integrates cancer drugs, drug\u2010target databases and gene biological pathway networks. The molecular profiles of each tumor consists of DNA copy number alteration, gene mutation, and tumor gene expression variation compared to its adjacent normal tissue.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The novel integrated PMTDS system is applied to select candidate target\u2010drug pairs for 178 TCGA pancreatic adenocarcinoma (PDAC) tumors. The experiment results show known drug targets (EGFR, IGF1R, ERBB2, NR1I2 and AKR1B1) of PDAC treatment are identified, which provides important evidence of the PMTDS algorithm\u2019s accuracy. Other potential targets PTK6, ATF, SYK are, also, recommended for PDAC. Further validation is provided by comparison of selected targets with, both, cell line molecular profiles from the Cancer Cell Line Encyclopedia (CCLE) and drug response data from the Cancer Therapeutics Response Portal (CTRP). Results from experimental analysis of forty six individual pancreatic cancer samples show that drugs selected by PMTDS have more sample\u2010specific efficacy than the current clinical PDAC therapies.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>A novelty target and drug priority algorithm PMTDS is developed to identify optimum target\u2010drug pairs by integrating the knowledgebase base with a single patient\u2019s genomics. The PMTDS system provides an accurate and reliable source for target and off\u2010label drug selection for precision cancer medicine.<\/jats:p><\/jats:sec>","DOI":"10.1007\/s40484-017-0126-1","type":"journal-article","created":{"date-parts":[[2017,11,23]],"date-time":"2017-11-23T12:16:04Z","timestamp":1511439364000},"page":"380-394","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["PMTDS: a computational method based on genetic interaction networks for Precision Medicine Target\u2010Drug Selection in cancer"],"prefix":"10.1002","volume":"5","author":[{"given":"Varshini","family":"Vasudevaraja","sequence":"first","affiliation":[{"name":"<!--1--> Department of Biomedical Informatics College of Medicine Ohio State University Columbus OH 43210 USA"},{"name":"<!--2--> Department of Medical and Molecular Genetics School of Medicine Indiana University Indianapolis IN 46202 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