{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T10:53:29Z","timestamp":1740135209638,"version":"3.37.3"},"reference-count":25,"publisher":"Springer Science and Business Media LLC","issue":"S10","license":[{"start":{"date-parts":[[2021,5,1]],"date-time":"2021-05-01T00:00:00Z","timestamp":1619827200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,4,19]],"date-time":"2022-04-19T00:00:00Z","timestamp":1650326400000},"content-version":"vor","delay-in-days":353,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100004663","name":"Ministry of Science and Technology, Taiwan","doi-asserted-by":"publisher","award":["MOST 109-2634-F-009-021","MOST 109-2321-B-009-007"],"award-info":[{"award-number":["MOST 109-2634-F-009-021","MOST 109-2321-B-009-007"]}],"id":[{"id":"10.13039\/501100004663","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004737","name":"National Health Research Institutes","doi-asserted-by":"publisher","award":["NHRI-EX109-10504PI"],"award-info":[{"award-number":["NHRI-EX109-10504PI"]}],"id":[{"id":"10.13039\/501100004737","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2021,5]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>The gene signatures have been considered as a promising early diagnosis and prognostic analysis to identify disease subtypes and to determine subsequent treatments. Tissue-specific gene signatures of a specific disease are an emergency requirement for precision medicine to improve the accuracy and reduce the side effects. Currently, many approaches have been proposed for identifying gene signatures for diagnosis and prognostic. However, they often lack of tissue-specific gene signatures.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>Here, we propose a new method, consensus mutual information (CoMI) for analyzing omics data and discovering gene signatures. CoMI can identify differentially expressed genes in multiple cancer omics data for reflecting both cancer-related and tissue-specific signatures, such as <jats:italic>Cell growth and death<\/jats:italic> in multiple cancers, <jats:italic>Xenobiotics biodegradation and metabolism<\/jats:italic> in LIHC, and <jats:italic>Nervous system<\/jats:italic> in GBM. Our method identified 50-gene signatures effectively distinguishing the GBM patients into high- and low-risk groups (log-rank <jats:italic>p<\/jats:italic>\u2009=\u20090.006) for diagnosis and prognosis.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>Our results demonstrate that CoMI can identify significant and consistent gene signatures with tissue-specific properties and can predict clinical outcomes for interested diseases. We believe that CoMI is useful for analyzing omics data and discovering gene signatures of diseases.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12859-022-04682-2","type":"journal-article","created":{"date-parts":[[2022,4,19]],"date-time":"2022-04-19T14:03:24Z","timestamp":1650377004000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["CoMI: consensus mutual information for tissue-specific gene signatures"],"prefix":"10.1186","volume":"22","author":[{"given":"Sing-Han","family":"Huang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yu-Shu","family":"Lo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yong-Chun","family":"Luo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi-Hsuan","family":"Chuang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jung-Yu","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3205-4391","authenticated-orcid":false,"given":"Jinn-Moon","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,4,19]]},"reference":[{"issue":"Suppl 1","key":"4682_CR1","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1159\/000258489","volume":"77","author":"N Normanno","year":"2009","unstructured":"Normanno N, De Luca A, Carotenuto P, Lamura L, Oliva I, D\u2019Alessio A. Prognostic applications of gene expression signatures in breast cancer. Oncology. 2009;77(Suppl 1):2\u20138.","journal-title":"Oncology"},{"issue":"8","key":"4682_CR2","doi-asserted-by":"publisher","first-page":"1160","DOI":"10.1200\/JCO.2008.18.1370","volume":"27","author":"JS Parker","year":"2009","unstructured":"Parker JS, Mullins M, Cheang MC, Leung S, Voduc D, Vickery T, Davies S, Fauron C, He X, Hu Z, et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol. 2009;27(8):1160\u20137.","journal-title":"J Clin Oncol"},{"issue":"6797","key":"4682_CR3","doi-asserted-by":"publisher","first-page":"747","DOI":"10.1038\/35021093","volume":"406","author":"CM Perou","year":"2000","unstructured":"Perou CM, Sorlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, Pollack JR, Ross DT, Johnsen H, Akslen LA, et al. Molecular portraits of human breast tumours. Nature. 2000;406(6797):747\u201352.","journal-title":"Nature"},{"issue":"1","key":"4682_CR4","doi-asserted-by":"publisher","first-page":"7233","DOI":"10.1038\/s41598-019-43829-9","volume":"9","author":"M Ryaboshapkina","year":"2019","unstructured":"Ryaboshapkina M, Hammar M. Tissue-specific genes as an underutilized resource in drug discovery. Sci Rep. 2019;9(1):7233.","journal-title":"Sci Rep"},{"issue":"4","key":"4682_CR5","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1186\/gb-2003-4-4-210","volume":"4","author":"X Cui","year":"2003","unstructured":"Cui X, Churchill GA. Statistical tests for differential expression in cDNA microarray experiments. Genome Biol. 2003;4(4):210.","journal-title":"Genome Biol"},{"issue":"15","key":"4682_CR6","doi-asserted-by":"publisher","first-page":"1945","DOI":"10.1093\/bioinformatics\/btg264","volume":"19","author":"N Jain","year":"2003","unstructured":"Jain N, Thatte J, Braciale T, Ley K, O\u2019Connell M, Lee JK. Local-pooled-error test for identifying differentially expressed genes with a small number of replicated microarrays. Bioinformatics. 2003;19(15):1945\u201351.","journal-title":"Bioinformatics"},{"issue":"9","key":"4682_CR7","doi-asserted-by":"publisher","first-page":"5116","DOI":"10.1073\/pnas.091062498","volume":"98","author":"VG Tusher","year":"2001","unstructured":"Tusher VG, Tibshirani R, Chu G. Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci U S A. 2001;98(9):5116\u201321.","journal-title":"Proc Natl Acad Sci U S A"},{"issue":"5748","key":"4682_CR8","doi-asserted-by":"publisher","first-page":"644","DOI":"10.1126\/science.1117679","volume":"310","author":"SA Tomlins","year":"2005","unstructured":"Tomlins SA, Rhodes DR, Perner S, Dhanasekaran SM, Mehra R, Sun XW, Varambally S, Cao X, Tchinda J, Kuefer R, et al. Recurrent fusion of TMPRSS2 and ETS transcription factor genes in prostate cancer. Science. 2005;310(5748):644\u20138.","journal-title":"Science"},{"issue":"23","key":"4682_CR9","doi-asserted-by":"publisher","first-page":"2950","DOI":"10.1093\/bioinformatics\/btl433","volume":"22","author":"JW MacDonald","year":"2006","unstructured":"MacDonald JW, Ghosh D. COPA-cancer outlier profile analysis. Bioinformatics. 2006;22(23):2950\u20131.","journal-title":"Bioinformatics"},{"issue":"5425","key":"4682_CR10","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1126\/science.285.5425.251","volume":"285","author":"T Galitski","year":"1999","unstructured":"Galitski T, Saldanha AJ, Styles CA, Lander ES, Fink GR. Ploidy regulation of gene expression. Science. 1999;285(5425):251\u20134.","journal-title":"Science"},{"issue":"10","key":"4682_CR11","doi-asserted-by":"publisher","first-page":"6567","DOI":"10.1073\/pnas.082099299","volume":"99","author":"R Tibshirani","year":"2002","unstructured":"Tibshirani R, Hastie T, Narasimhan B, Chu G. Diagnosis of multiple cancer types by shrunken centroids of gene expression. Proc Natl Acad Sci U S A. 2002;99(10):6567\u201372.","journal-title":"Proc Natl Acad Sci U S A"},{"issue":"8","key":"4682_CR12","doi-asserted-by":"publisher","first-page":"938","DOI":"10.1038\/nm.3909","volume":"21","author":"AJ Gentles","year":"2015","unstructured":"Gentles AJ, Newman AM, Liu CL, Bratman SV, Feng W, Kim D, Nair VS, Xu Y, Khuong A, Hoang CD, et al. The prognostic landscape of genes and infiltrating immune cells across human cancers. Nat Med. 2015;21(8):938\u201345.","journal-title":"Nat Med"},{"key":"4682_CR13","doi-asserted-by":"publisher","first-page":"150","DOI":"10.7150\/jca.1.150","volume":"1","author":"CO Madu","year":"2010","unstructured":"Madu CO, Lu Y. Novel diagnostic biomarkers for prostate cancer. J Cancer. 2010;1:150\u201377.","journal-title":"J Cancer"},{"key":"4682_CR14","doi-asserted-by":"publisher","first-page":"13041","DOI":"10.1038\/ncomms13041","volume":"7","author":"E Gaude","year":"2016","unstructured":"Gaude E, Frezza C. Tissue-specific and convergent metabolic transformation of cancer correlates with metastatic potential and patient survival. Nat Commun. 2016;7:13041.","journal-title":"Nat Commun"},{"issue":"4","key":"4682_CR15","doi-asserted-by":"publisher","first-page":"1077","DOI":"10.1016\/j.celrep.2017.10.001","volume":"21","author":"AR Sonawane","year":"2017","unstructured":"Sonawane AR, Platig J, Fagny M, Chen CY, Paulson JN, Lopes-Ramos CM, DeMeo DL, Quackenbush J, Glass K, Kuijjer ML. Understanding tissue-specific gene regulation. Cell Rep. 2017;21(4):1077\u201388.","journal-title":"Cell Rep"},{"issue":"9","key":"4682_CR16","doi-asserted-by":"publisher","first-page":"1003","DOI":"10.1038\/nbt.1487","volume":"26","author":"T Shlomi","year":"2008","unstructured":"Shlomi T, Cabili MN, Herrgard MJ, Palsson BO, Ruppin E. Network-based prediction of human tissue-specific metabolism. Nat Biotechnol. 2008;26(9):1003\u201310.","journal-title":"Nat Biotechnol"},{"issue":"12","key":"4682_CR17","doi-asserted-by":"publisher","first-page":"1899","DOI":"10.3390\/cancers11121899","volume":"11","author":"WY Yang","year":"2019","unstructured":"Yang WY, Rao PS, Luo YC, Lin HK, Huang SH, Yang JM, Yuh CH. Omics-based investigation of diet-induced obesity synergized with HBx, Src, and p53 mutation accelerating hepatocarcinogenesis in Zebrafish model. Cancers (Basel). 2019;11(12):1899.","journal-title":"Cancers (Basel)"},{"issue":"6220","key":"4682_CR18","doi-asserted-by":"publisher","first-page":"1260419","DOI":"10.1126\/science.1260419","volume":"347","author":"M Uhlen","year":"2015","unstructured":"Uhlen M, Fagerberg L, Hallstrom BM, Lindskog C, Oksvold P, Mardinoglu A, Sivertsson A, Kampf C, Sjostedt E, Asplund A, et al. Proteomics. Tissue-based map of the human proteome. Science. 2015;347(6220):1260419.","journal-title":"Science"},{"issue":"5","key":"4682_CR19","doi-asserted-by":"publisher","first-page":"420","DOI":"10.1596\/neo.12432","volume":"14","author":"PA Clark","year":"2012","unstructured":"Clark PA, Iida M, Treisman DM, Kalluri H, Ezhilan S, Zorniak M, Wheeler DL, Kuo JS. Activation of multiple ERBB family receptors mediates glioblastoma cancer stem-like cell resistance to EGFR-targeted inhibition. Neoplasia. 2012;14(5):420\u20138.","journal-title":"Neoplasia"},{"issue":"1","key":"4682_CR20","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1634\/theoncologist.2013-0237","volume":"19","author":"Y Carter","year":"2014","unstructured":"Carter Y, Sippel RS, Chen H. Hypothyroidism after a cancer diagnosis: etiology, diagnosis, complications, and management. Oncologist. 2014;19(1):34\u201343.","journal-title":"Oncologist"},{"key":"4682_CR21","doi-asserted-by":"crossref","unstructured":"Chandran R, Hakki M, Spurgeon S. Infections in leukemia, Sepsis Luciano Azevedo. IntechOpen; 2012.","DOI":"10.5772\/50193"},{"issue":"5","key":"4682_CR22","doi-asserted-by":"publisher","first-page":"646","DOI":"10.1016\/j.cell.2011.02.013","volume":"144","author":"D Hanahan","year":"2011","unstructured":"Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011;144(5):646\u201374.","journal-title":"Cell"},{"key":"4682_CR23","doi-asserted-by":"crossref","unstructured":"Cancer Genome Atlas Research N, Weinstein JN, Collisson EA, Mills GB, Shaw KR, Ozenberger BA, Ellrott K, Shmulevich I, Sander C, Stuart JM. The cancer genome atlas pan-cancer analysis project. Nat Genet. 2013;45(10):1113\u20131120.","DOI":"10.1038\/ng.2764"},{"issue":"7","key":"4682_CR24","doi-asserted-by":"publisher","first-page":"e47","DOI":"10.1093\/nar\/gkv007","volume":"43","author":"ME Ritchie","year":"2015","unstructured":"Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, Smyth GK. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43(7):e47.","journal-title":"Nucleic Acids Res"},{"issue":"5","key":"4682_CR25","doi-asserted-by":"publisher","first-page":"519","DOI":"10.1177\/0962280211428386","volume":"22","author":"J Li","year":"2013","unstructured":"Li J, Tibshirani R. Finding consistent patterns: a nonparametric approach for identifying differential expression in RNA-Seq data. Stat Methods Med Res. 2013;22(5):519\u201336.","journal-title":"Stat Methods Med Res"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-022-04682-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12859-022-04682-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-022-04682-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,20]],"date-time":"2022-04-20T13:06:11Z","timestamp":1650459971000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/s12859-022-04682-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5]]},"references-count":25,"journal-issue":{"issue":"S10","published-print":{"date-parts":[[2021,5]]}},"alternative-id":["4682"],"URL":"https:\/\/doi.org\/10.1186\/s12859-022-04682-2","relation":{},"ISSN":["1471-2105"],"issn-type":[{"type":"electronic","value":"1471-2105"}],"subject":[],"published":{"date-parts":[[2021,5]]},"assertion":[{"value":"8 April 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 April 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 April 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to publish"}},{"value":"The authors declare that they have no conflict of interest.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"624"}}