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dc.contributor.authorPfefferle, Adam Den_US
dc.contributor.authorHerschkowitz, Jason Ien_US
dc.contributor.authorUsary, Jerryen_US
dc.contributor.authorHarrell, Joshua Chucken_US
dc.contributor.authorSpike, Benjamin Ten_US
dc.contributor.authorAdams, Jessica Ren_US
dc.contributor.authorTorres-Arzayus, Maria Ien_US
dc.contributor.authorBrown, Mylesen_US
dc.contributor.authorEgan, Sean Een_US
dc.contributor.authorWahl, Geoffrey Men_US
dc.contributor.authorRosen, Jeffrey Men_US
dc.contributor.authorPerou, Charles Men_US
dc.date.accessioned2014-07-07T17:03:26Z
dc.date.issued2013en_US
dc.identifier.citationPfefferle, A. D., J. I. Herschkowitz, J. Usary, J. C. Harrell, B. T. Spike, J. R. Adams, M. I. Torres-Arzayus, et al. 2013. “Transcriptomic classification of genetically engineered mouse models of breast cancer identifies human subtype counterparts.” Genome Biology 14 (11): R125. doi:10.1186/gb-2013-14-11-r125. http://dx.doi.org/10.1186/gb-2013-14-11-r125.en
dc.identifier.issn1465-6906en
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:12406691
dc.description.abstractBackground: Human breast cancer is a heterogeneous disease consisting of multiple molecular subtypes. Genetically engineered mouse models are a useful resource for studying mammary cancers in vivo under genetically controlled and immune competent conditions. Identifying murine models with conserved human tumor features will facilitate etiology determinations, highlight the effects of mutations on pathway activation, and should improve preclinical drug testing. Results: Transcriptomic profiles of 27 murine models of mammary carcinoma and normal mammary tissue were determined using gene expression microarrays. Hierarchical clustering analysis identified 17 distinct murine subtypes. Cross-species analyses using three independent human breast cancer datasets identified eight murine classes that resemble specific human breast cancer subtypes. Multiple models were associated with human basal-like tumors including TgC3(1)-Tag, TgWAP-Myc and Trp53-/-. Interestingly, the TgWAPCre-Etv6 model mimicked the HER2-enriched subtype, a group of human tumors without a murine counterpart in previous comparative studies. Gene signature analysis identified hundreds of commonly expressed pathway signatures between linked mouse and human subtypes, highlighting potentially common genetic drivers of tumorigenesis. Conclusions: This study of murine models of breast carcinoma encompasses the largest comprehensive genomic dataset to date to identify human-to-mouse disease subtype counterparts. Our approach illustrates the value of comparisons between species to identify murine models that faithfully mimic the human condition and indicates that multiple genetically engineered mouse models are needed to represent the diversity of human breast cancers. The reported trans-species associations should guide model selection during preclinical study design to ensure appropriate representatives of human disease subtypes are used.en
dc.language.isoen_USen
dc.publisherBioMed Centralen
dc.relation.isversionofdoi:10.1186/gb-2013-14-11-r125en
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC4053990/pdf/en
dash.licenseLAAen_US
dc.titleTranscriptomic classification of genetically engineered mouse models of breast cancer identifies human subtype counterpartsen
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden
dc.relation.journalGenome Biologyen
dash.depositing.authorTorres-Arzayus, Maria Ien_US
dc.date.available2014-07-07T17:03:26Z
dc.identifier.doi10.1186/gb-2013-14-11-r125*
dash.authorsorderedfalse
dash.contributor.affiliatedTorres-Arzayus, Maria I
dash.contributor.affiliatedBrown, Myles


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