{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T10:28:32Z","timestamp":1774434512317,"version":"3.50.1"},"reference-count":65,"publisher":"Oxford University Press (OUP)","issue":"D1","license":[{"start":{"date-parts":[[2021,9,27]],"date-time":"2021-09-27T00:00:00Z","timestamp":1632700800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2020YFE0202200"],"award-info":[{"award-number":["2020YFE0202200"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2017YFC1700105"],"award-info":[{"award-number":["2017YFC1700105"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["32088101"],"award-info":[{"award-number":["32088101"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31871341"],"award-info":[{"award-number":["31871341"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"State Key Laboratory of Proteomics of China","award":["SKLPO202010"],"award-info":[{"award-number":["SKLPO202010"]}]},{"DOI":"10.13039\/501100017616","name":"Beijing Talents foundation","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100017616","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,1,7]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>To date, only some cancer patients can benefit from chemotherapy and targeted therapy. Drug resistance continues to be a major and challenging problem facing current cancer research. Rapidly accumulated patient-derived clinical transcriptomic data with cancer drug response bring opportunities for exploring molecular determinants of drug response, but meanwhile pose challenges for data management, integration, and reuse. Here we present the Cancer Treatment Response gene signature DataBase (CTR-DB, http:\/\/ctrdb.ncpsb.org.cn\/), a unique database for basic and clinical researchers to access, integrate, and reuse clinical transcriptomes with cancer drug response. CTR-DB has collected and uniformly reprocessed 83 patient-derived pre-treatment transcriptomic source datasets with manually curated cancer drug response information, involving 28 histological cancer types, 123 drugs, and 5139 patient samples. These data are browsable, searchable, and downloadable. Moreover, CTR-DB supports single-dataset exploration (including differential gene expression, receiver operating characteristic curve, functional enrichment, sensitizing drug search, and tumor microenvironment analyses), and multiple-dataset combination and comparison, as well as biomarker validation function, which provide insights into the drug resistance mechanism, predictive biomarker discovery and validation, drug combination, and resistance mechanism heterogeneity.<\/jats:p>","DOI":"10.1093\/nar\/gkab860","type":"journal-article","created":{"date-parts":[[2021,9,15]],"date-time":"2021-09-15T11:17:00Z","timestamp":1631704620000},"page":"D1184-D1199","source":"Crossref","is-referenced-by-count":45,"title":["CTR-DB, an omnibus for patient-derived gene expression signatures correlated with cancer drug response"],"prefix":"10.1093","volume":"50","author":[{"given":"Zhongyang","family":"Liu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China"},{"name":"College of Chemistry and Environmental Science, Hebei University, Baoding 071002, China"}]},{"given":"Jiale","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7905-3831","authenticated-orcid":false,"given":"Xinyue","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4559-5450","authenticated-orcid":false,"given":"Xun","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China"}]},{"given":"Qiaosheng","family":"Xie","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, China-Japan Friendship Hospital, Beijing 100029, China"}]},{"given":"Xinlei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Beijing Geneworks Technology Co., Ltd., Beijing 100101, China"}]},{"given":"Xiangya","family":"Kong","sequence":"additional","affiliation":[{"name":"Beijing Geneworks Technology Co., Ltd., Beijing 100101, China"}]},{"given":"Mengqi","family":"He","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China"}]},{"given":"Yuting","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Immunology, Medical College of Qingdao University, Qingdao 266071, China"}]},{"given":"Xinru","family":"Deng","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China"}]},{"given":"Lele","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Chemistry and Environmental Science, Hebei University, Baoding 071002, China"}]},{"given":"Yaning","family":"Qi","sequence":"additional","affiliation":[{"name":"College of Chemistry and Environmental Science, Hebei University, Baoding 071002, China"}]},{"given":"Jiajun","family":"Li","sequence":"additional","affiliation":[{"name":"College of Chemistry and Environmental Science, Hebei University, Baoding 071002, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2866-4904","authenticated-orcid":false,"given":"Yuan","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China"}]},{"given":"Liying","family":"Yuan","sequence":"additional","affiliation":[{"name":"College of Chemistry and Environmental Science, Hebei University, Baoding 071002, China"}]},{"given":"Lihong","family":"Diao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China"}]},{"given":"Fuchu","family":"He","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8680-0468","authenticated-orcid":false,"given":"Dong","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China"},{"name":"College of Chemistry and Environmental Science, Hebei University, Baoding 071002, China"}]}],"member":"286","published-online":{"date-parts":[[2021,9,27]]},"reference":[{"key":"2022010507354290800_B1","doi-asserted-by":"crossref","first-page":"3817","DOI":"10.1200\/JCO.2015.61.5997","article-title":"Impact of precision medicine in diverse cancers: a meta-analysis of phase II clinical trials","volume":"33","author":"Schwaederle","year":"2015","journal-title":"J. Clin. Oncol."},{"key":"2022010507354290800_B2","doi-asserted-by":"crossref","first-page":"714","DOI":"10.1038\/nrc3599","article-title":"Cancer drug resistance: an evolving paradigm","volume":"13","author":"Holohan","year":"2013","journal-title":"Nat. Rev. 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Invest."},{"key":"2022010507354290800_B7","doi-asserted-by":"crossref","first-page":"D1083","DOI":"10.1093\/nar\/gkaa968","article-title":"CellMiner cross-database (CellMinerCDB) version 1.2: exploration of patient-derived cancer cell line pharmacogenomics","volume":"49","author":"Luna","year":"2021","journal-title":"Nucleic Acids Res."},{"key":"2022010507354290800_B8","doi-asserted-by":"crossref","first-page":"W148","DOI":"10.1093\/nar\/gky434","article-title":"GDA, a web-based tool for genomics and drugs integrated analysis","volume":"46","author":"Caroli","year":"2018","journal-title":"Nucleic Acids Res."},{"key":"2022010507354290800_B9","doi-asserted-by":"crossref","first-page":"4539","DOI":"10.1158\/0008-5472.CAN-19-0349","article-title":"Integrative pharmacogenomics analysis of patient-derived xenografts","volume":"79","author":"Mer","year":"2019","journal-title":"Cancer Res."},{"key":"2022010507354290800_B10","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1186\/s12920-020-00759-0","article-title":"Cancer gene expression profiles associated with clinical outcomes to chemotherapy treatments","volume":"13","author":"Borisov","year":"2020","journal-title":"BMC Med. 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Oncol."},{"key":"2022010507354290800_B13","doi-asserted-by":"crossref","first-page":"804","DOI":"10.1093\/carcin\/bgab024","article-title":"Gene expression-based biomarkers designating glioblastomas resistant to multiple treatment strategies","volume":"42","author":"Menyhart","year":"2021","journal-title":"Carcinogenesis"},{"key":"2022010507354290800_B14","first-page":"237","article-title":"CDRgator: an integrative navigator of cancer drug resistance gene signatures","volume":"42","author":"Jang","year":"2019","journal-title":"Mol. 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R. Stat. Soc."},{"key":"2022010507354290800_B43","doi-asserted-by":"crossref","first-page":"15545","DOI":"10.1073\/pnas.0506580102","article-title":"Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles","volume":"102","author":"Subramanian","year":"2005","journal-title":"Proc. Natl. Acad. Sci. U.S.A."},{"key":"2022010507354290800_B44","doi-asserted-by":"crossref","first-page":"100141","DOI":"10.1016\/j.xinn.2021.100141","article-title":"clusterProfiler 4.0: A universal enrichment tool for interpreting omics data","volume":"2","author":"Wu","year":"2021","journal-title":"The Innovation"},{"key":"2022010507354290800_B45","doi-asserted-by":"crossref","first-page":"16015","DOI":"10.1038\/npjsba.2016.15","article-title":"L1000CDS2: LINCS L1000 characteristic direction signatures search engine","volume":"2","author":"Duan","year":"2016","journal-title":"NPJ Syst. Biol. 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Cancer Inst."},{"key":"2022010507354290800_B54","doi-asserted-by":"crossref","first-page":"D1420","DOI":"10.1093\/nar\/gkaa1020","article-title":"TISCH: a comprehensive web resource enabling interactive single-cell transcriptome visualization of tumor microenvironment","volume":"49","author":"Sun","year":"2021","journal-title":"Nucleic Acids Res."},{"key":"2022010507354290800_B55","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1038\/nature12626","article-title":"Influence of tumour micro-environment heterogeneity on therapeutic response","volume":"501","author":"Junttila","year":"2013","journal-title":"Nature"},{"key":"2022010507354290800_B56","doi-asserted-by":"crossref","first-page":"1121","DOI":"10.2217\/bmm.15.84","article-title":"Predictive biomarkers for treatment selection: statistical considerations","volume":"9","author":"Chen","year":"2015","journal-title":"Biomarkers Med."},{"key":"2022010507354290800_B57","doi-asserted-by":"crossref","first-page":"672","DOI":"10.3389\/fcell.2020.00672","article-title":"Resistance mechanisms of anti-PD1\/PDL1 therapy in solid tumors","volume":"8","author":"Lei","year":"2020","journal-title":"Front. 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