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Histological subtypes of mouse mammary tumors reveal conserved relationships to human cancers
Human breast cancer has been characterized by extensive transcriptional heterogeneity, with dominant patterns reflected in the intrinsic subtypes. Mouse models of breast cancer also have heterogeneous transcriptomes and we noted that specific histological subtypes were associated with particular sub...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5773092/ https://www.ncbi.nlm.nih.gov/pubmed/29346386 http://dx.doi.org/10.1371/journal.pgen.1007135 |
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author | Hollern, Daniel P. Swiatnicki, Matthew R. Andrechek, Eran R. |
author_facet | Hollern, Daniel P. Swiatnicki, Matthew R. Andrechek, Eran R. |
author_sort | Hollern, Daniel P. |
collection | PubMed |
description | Human breast cancer has been characterized by extensive transcriptional heterogeneity, with dominant patterns reflected in the intrinsic subtypes. Mouse models of breast cancer also have heterogeneous transcriptomes and we noted that specific histological subtypes were associated with particular subsets. We hypothesized that unique sets of genes define each tumor histological type across mouse models of breast cancer. Using mouse models that contained both gene expression data and expert pathologist classification of tumor histology on a sample by sample basis, we predicted and validated gene expression signatures for Papillary, EMT, Microacinar and other histological subtypes. These signatures predict known histological events across murine breast cancer models and identify counterparts of mouse mammary tumor types in subtypes of human breast cancer. Importantly, the EMT, Adenomyoepithelial, and Solid signatures were predictive of clinical events in human breast cancer. In addition, a pan-cancer comparison revealed that the histological signatures were active in a variety of human cancers such as lung, oral, and esophageal squamous tumors. Finally, the differentiation status and transcriptional activity implicit within these signatures was identified. These data reveal that within tumor histology groups are unique gene expression profiles of differentiation and pathway activity that stretch well beyond the transgenic initiating events and that have clear applicability to human cancers. As a result, our work provides a predictive resource and insights into possible mechanisms that govern tumor heterogeneity. |
format | Online Article Text |
id | pubmed-5773092 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-57730922018-01-26 Histological subtypes of mouse mammary tumors reveal conserved relationships to human cancers Hollern, Daniel P. Swiatnicki, Matthew R. Andrechek, Eran R. PLoS Genet Research Article Human breast cancer has been characterized by extensive transcriptional heterogeneity, with dominant patterns reflected in the intrinsic subtypes. Mouse models of breast cancer also have heterogeneous transcriptomes and we noted that specific histological subtypes were associated with particular subsets. We hypothesized that unique sets of genes define each tumor histological type across mouse models of breast cancer. Using mouse models that contained both gene expression data and expert pathologist classification of tumor histology on a sample by sample basis, we predicted and validated gene expression signatures for Papillary, EMT, Microacinar and other histological subtypes. These signatures predict known histological events across murine breast cancer models and identify counterparts of mouse mammary tumor types in subtypes of human breast cancer. Importantly, the EMT, Adenomyoepithelial, and Solid signatures were predictive of clinical events in human breast cancer. In addition, a pan-cancer comparison revealed that the histological signatures were active in a variety of human cancers such as lung, oral, and esophageal squamous tumors. Finally, the differentiation status and transcriptional activity implicit within these signatures was identified. These data reveal that within tumor histology groups are unique gene expression profiles of differentiation and pathway activity that stretch well beyond the transgenic initiating events and that have clear applicability to human cancers. As a result, our work provides a predictive resource and insights into possible mechanisms that govern tumor heterogeneity. Public Library of Science 2018-01-18 /pmc/articles/PMC5773092/ /pubmed/29346386 http://dx.doi.org/10.1371/journal.pgen.1007135 Text en © 2018 Hollern et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Hollern, Daniel P. Swiatnicki, Matthew R. Andrechek, Eran R. Histological subtypes of mouse mammary tumors reveal conserved relationships to human cancers |
title | Histological subtypes of mouse mammary tumors reveal conserved relationships to human cancers |
title_full | Histological subtypes of mouse mammary tumors reveal conserved relationships to human cancers |
title_fullStr | Histological subtypes of mouse mammary tumors reveal conserved relationships to human cancers |
title_full_unstemmed | Histological subtypes of mouse mammary tumors reveal conserved relationships to human cancers |
title_short | Histological subtypes of mouse mammary tumors reveal conserved relationships to human cancers |
title_sort | histological subtypes of mouse mammary tumors reveal conserved relationships to human cancers |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5773092/ https://www.ncbi.nlm.nih.gov/pubmed/29346386 http://dx.doi.org/10.1371/journal.pgen.1007135 |
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