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Exploring the intrinsic differences among breast tumor subtypes defined using immunohistochemistry markers based on the decision tree
Exploring the intrinsic differences among breast cancer subtypes is of crucial importance for precise diagnosis and therapeutic decision-making in diseases of high heterogeneity. The subtypes defined with several layers of information are related but not consistent, especially using immunohistochemi...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5082366/ https://www.ncbi.nlm.nih.gov/pubmed/27786176 http://dx.doi.org/10.1038/srep35773 |
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author | Li, Yang Tang, Xu-Qing Bai, Zhonghu Dai, Xiaofeng |
author_facet | Li, Yang Tang, Xu-Qing Bai, Zhonghu Dai, Xiaofeng |
author_sort | Li, Yang |
collection | PubMed |
description | Exploring the intrinsic differences among breast cancer subtypes is of crucial importance for precise diagnosis and therapeutic decision-making in diseases of high heterogeneity. The subtypes defined with several layers of information are related but not consistent, especially using immunohistochemistry markers and gene expression profiling. Here, we explored the intrinsic differences among the subtypes defined by the estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 based on the decision tree. We identified 30 mRNAs and 7 miRNAs differentially expressed along the tree’s branches. The final signature panel contained 30 mRNAs, whose performance was validated using two public datasets based on 3 well-known classifiers. The network and pathway analysis were explored for feature genes, from which key molecules including FOXQ1 and SFRP1 were revealed to be densely connected with other molecules and participate in the validated metabolic pathways. Our study uncovered the differences among the four IHC-defined breast tumor subtypes at the mRNA and miRNA levels, presented a novel signature for breast tumor subtyping, and identified several key molecules potentially driving the heterogeneity of such tumors. The results help us further understand breast tumor heterogeneity, which could be availed in clinics. |
format | Online Article Text |
id | pubmed-5082366 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-50823662016-10-31 Exploring the intrinsic differences among breast tumor subtypes defined using immunohistochemistry markers based on the decision tree Li, Yang Tang, Xu-Qing Bai, Zhonghu Dai, Xiaofeng Sci Rep Article Exploring the intrinsic differences among breast cancer subtypes is of crucial importance for precise diagnosis and therapeutic decision-making in diseases of high heterogeneity. The subtypes defined with several layers of information are related but not consistent, especially using immunohistochemistry markers and gene expression profiling. Here, we explored the intrinsic differences among the subtypes defined by the estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 based on the decision tree. We identified 30 mRNAs and 7 miRNAs differentially expressed along the tree’s branches. The final signature panel contained 30 mRNAs, whose performance was validated using two public datasets based on 3 well-known classifiers. The network and pathway analysis were explored for feature genes, from which key molecules including FOXQ1 and SFRP1 were revealed to be densely connected with other molecules and participate in the validated metabolic pathways. Our study uncovered the differences among the four IHC-defined breast tumor subtypes at the mRNA and miRNA levels, presented a novel signature for breast tumor subtyping, and identified several key molecules potentially driving the heterogeneity of such tumors. The results help us further understand breast tumor heterogeneity, which could be availed in clinics. Nature Publishing Group 2016-10-27 /pmc/articles/PMC5082366/ /pubmed/27786176 http://dx.doi.org/10.1038/srep35773 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Li, Yang Tang, Xu-Qing Bai, Zhonghu Dai, Xiaofeng Exploring the intrinsic differences among breast tumor subtypes defined using immunohistochemistry markers based on the decision tree |
title | Exploring the intrinsic differences among breast tumor subtypes defined using immunohistochemistry markers based on the decision tree |
title_full | Exploring the intrinsic differences among breast tumor subtypes defined using immunohistochemistry markers based on the decision tree |
title_fullStr | Exploring the intrinsic differences among breast tumor subtypes defined using immunohistochemistry markers based on the decision tree |
title_full_unstemmed | Exploring the intrinsic differences among breast tumor subtypes defined using immunohistochemistry markers based on the decision tree |
title_short | Exploring the intrinsic differences among breast tumor subtypes defined using immunohistochemistry markers based on the decision tree |
title_sort | exploring the intrinsic differences among breast tumor subtypes defined using immunohistochemistry markers based on the decision tree |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5082366/ https://www.ncbi.nlm.nih.gov/pubmed/27786176 http://dx.doi.org/10.1038/srep35773 |
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