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Transcriptomic classification of genetically engineered mouse models of breast cancer identifies human subtype counterparts

BACKGROUND: 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...

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Autores principales: Pfefferle, Adam D, Herschkowitz, Jason I, Usary, Jerry, Harrell, Joshua Chuck, Spike, Benjamin T, Adams, Jessica R, Torres-Arzayus, Maria I, Brown, Myles, Egan, Sean E, Wahl, Geoffrey M, Rosen, Jeffrey M, Perou, Charles M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4053990/
https://www.ncbi.nlm.nih.gov/pubmed/24220145
http://dx.doi.org/10.1186/gb-2013-14-11-r125
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author Pfefferle, Adam D
Herschkowitz, Jason I
Usary, Jerry
Harrell, Joshua Chuck
Spike, Benjamin T
Adams, Jessica R
Torres-Arzayus, Maria I
Brown, Myles
Egan, Sean E
Wahl, Geoffrey M
Rosen, Jeffrey M
Perou, Charles M
author_facet Pfefferle, Adam D
Herschkowitz, Jason I
Usary, Jerry
Harrell, Joshua Chuck
Spike, Benjamin T
Adams, Jessica R
Torres-Arzayus, Maria I
Brown, Myles
Egan, Sean E
Wahl, Geoffrey M
Rosen, Jeffrey M
Perou, Charles M
author_sort Pfefferle, Adam D
collection PubMed
description BACKGROUND: 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.
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spelling pubmed-40539902014-06-12 Transcriptomic classification of genetically engineered mouse models of breast cancer identifies human subtype counterparts Pfefferle, Adam D Herschkowitz, Jason I Usary, Jerry Harrell, Joshua Chuck Spike, Benjamin T Adams, Jessica R Torres-Arzayus, Maria I Brown, Myles Egan, Sean E Wahl, Geoffrey M Rosen, Jeffrey M Perou, Charles M Genome Biol Research BACKGROUND: 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. BioMed Central 2013 2013-11-12 /pmc/articles/PMC4053990/ /pubmed/24220145 http://dx.doi.org/10.1186/gb-2013-14-11-r125 Text en Copyright © 2013 Pfefferle et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Pfefferle, Adam D
Herschkowitz, Jason I
Usary, Jerry
Harrell, Joshua Chuck
Spike, Benjamin T
Adams, Jessica R
Torres-Arzayus, Maria I
Brown, Myles
Egan, Sean E
Wahl, Geoffrey M
Rosen, Jeffrey M
Perou, Charles M
Transcriptomic classification of genetically engineered mouse models of breast cancer identifies human subtype counterparts
title Transcriptomic classification of genetically engineered mouse models of breast cancer identifies human subtype counterparts
title_full Transcriptomic classification of genetically engineered mouse models of breast cancer identifies human subtype counterparts
title_fullStr Transcriptomic classification of genetically engineered mouse models of breast cancer identifies human subtype counterparts
title_full_unstemmed Transcriptomic classification of genetically engineered mouse models of breast cancer identifies human subtype counterparts
title_short Transcriptomic classification of genetically engineered mouse models of breast cancer identifies human subtype counterparts
title_sort transcriptomic classification of genetically engineered mouse models of breast cancer identifies human subtype counterparts
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4053990/
https://www.ncbi.nlm.nih.gov/pubmed/24220145
http://dx.doi.org/10.1186/gb-2013-14-11-r125
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