{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T15:37:16Z","timestamp":1790696236825,"version":"4.1.0"},"reference-count":40,"publisher":"Oxford University Press (OUP)","issue":"21","license":[{"start":{"date-parts":[[2016,10,7]],"date-time":"2016-10-07T00:00:00Z","timestamp":1475798400000},"content-version":"vor","delay-in-days":2667,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/2.0\/uk\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2009,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: One of the most deadly cancer diagnoses is the carcinoma of unknown primary origin. Without the knowledge of the site of origin, treatment regimens are limited in their specificity and result in high mortality rates. Though supervised classification methods have been developed to predict the site of origin based on gene expression data, they require large numbers of previously classified tumors for training, in part because they do not account for sample heterogeneity, which limits their application to well-studied cancers.<\/jats:p>\n               <jats:p>Results: We present ISOLATE, a new statistical method that simultaneously predicts the primary site of origin of cancers and addresses sample heterogeneity, while taking advantage of new high-throughput sequencing technology that promises to bring higher accuracy and reproducibility to gene expression profiling experiments. ISOLATE makes predictions de novo, without having seen any training expression profiles of cancers with identified origin. Compared with previous methods, ISOLATE is able to predict the primary site of origin, de-convolve and remove the effect of sample heterogeneity and identify differentially expressed genes with higher accuracy, across both synthetic and clinical datasets. Methods such as ISOLATE are invaluable tools for clinicians faced with carcinomas of unknown primary origin.<\/jats:p>\n               <jats:p>Availability: ISOLATE is available for download at: http:\/\/morrislab.med.utoronto.ca\/software<\/jats:p>\n               <jats:p>Contact: \u00a0gerald.quon@utoronto.ca; quaid.morris@utoronto.ca<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btp378","type":"journal-article","created":{"date-parts":[[2009,6,20]],"date-time":"2009-06-20T00:30:54Z","timestamp":1245457854000},"page":"2882-2889","source":"Crossref","is-referenced-by-count":36,"title":["ISOLATE: a computational strategy for identifying the primary origin of cancers using high-throughput sequencing"],"prefix":"10.1093","volume":"25","author":[{"given":"Gerald","family":"Quon","sequence":"first","affiliation":[{"name":"1 Department of Computer Science, 2 Banting and Best Department of Medical Research, 3 Department of Molecular Genetics and 4 Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Canada"},{"name":"1 Department of Computer Science, 2 Banting and Best Department of Medical Research, 3 Department of Molecular Genetics and 4 Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Quaid","family":"Morris","sequence":"additional","affiliation":[{"name":"1 Department of Computer Science, 2 Banting and Best Department of Medical Research, 3 Department of Molecular Genetics and 4 Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Canada"},{"name":"1 Department of Computer Science, 2 Banting and Best Department of Medical Research, 3 Department of Molecular Genetics and 4 Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Canada"},{"name":"1 Department of Computer Science, 2 Banting and Best Department of Medical Research, 3 Department of Molecular Genetics and 4 Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Canada"},{"name":"1 Department of Computer Science, 2 Banting and Best Department of Medical Research, 3 Department of Molecular Genetics and 4 Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2009,6,19]]},"reference":[{"key":"2023013112190342200_B1","author":"American Cancer Society","year":"2001","journal-title":"ACS Cancer Facts and Figures."},{"key":"2023013112190342200_B2","doi-asserted-by":"crossref","first-page":"536","DOI":"10.1038\/35020115","article-title":"Molecular classification of cutaneous malignant melaoma by gene expression profiling","volume":"406","author":"Bittner","year":"2000","journal-title":"Nature"},{"key":"2023013112190342200_B3","doi-asserted-by":"crossref","first-page":"1089","DOI":"10.1111\/j.1600-0463.2003.apm1111203.x","article-title":"Cancer of unknown primary: clinicopathologic correlations","volume":"111","author":"Blaszyk","year":"2003","journal-title":"APMIS"},{"key":"2023013112190342200_B4","first-page":"993","article-title":"Latent Dirichlet allocation","volume":"3","author":"Blei","year":"2003","journal-title":"J. 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