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Discovery and validation of breast cancer subtypes
BACKGROUND: Previous studies demonstrated breast cancer tumor tissue samples could be classified into different subtypes based upon DNA microarray profiles. The most recent study presented evidence for the existence of five different subtypes: normal breast-like, basal, luminal A, luminal B, and ERB...
Autores principales: | , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2006
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1574316/ https://www.ncbi.nlm.nih.gov/pubmed/16965636 http://dx.doi.org/10.1186/1471-2164-7-231 |
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author | Kapp, Amy V Jeffrey, Stefanie S Langerød, Anita Børresen-Dale, Anne-Lise Han, Wonshik Noh, Dong-Young Bukholm, Ida RK Nicolau, Monica Brown, Patrick O Tibshirani, Robert |
author_facet | Kapp, Amy V Jeffrey, Stefanie S Langerød, Anita Børresen-Dale, Anne-Lise Han, Wonshik Noh, Dong-Young Bukholm, Ida RK Nicolau, Monica Brown, Patrick O Tibshirani, Robert |
author_sort | Kapp, Amy V |
collection | PubMed |
description | BACKGROUND: Previous studies demonstrated breast cancer tumor tissue samples could be classified into different subtypes based upon DNA microarray profiles. The most recent study presented evidence for the existence of five different subtypes: normal breast-like, basal, luminal A, luminal B, and ERBB2(+). RESULTS: Based upon the analysis of 599 microarrays (five separate cDNA microarray datasets) using a novel approach, we present evidence in support of the most consistently identifiable subtypes of breast cancer tumor tissue microarrays being: ESR1(+)/ERBB2(-), ESR1(-)/ERBB2(-), and ERBB2(+ )(collectively called the ESR1/ERBB2 subtypes). We validate all three subtypes statistically and show the subtype to which a sample belongs is a significant predictor of overall survival and distant-metastasis free probability. CONCLUSION: As a consequence of the statistical validation procedure we have a set of centroids which can be applied to any microarray (indexed by UniGene Cluster ID) to classify it to one of the ESR1/ERBB2 subtypes. Moreover, the method used to define the ESR1/ERBB2 subtypes is not specific to the disease. The method can be used to identify subtypes in any disease for which there are at least two independent microarray datasets of disease samples. |
format | Text |
id | pubmed-1574316 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2006 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-15743162006-09-25 Discovery and validation of breast cancer subtypes Kapp, Amy V Jeffrey, Stefanie S Langerød, Anita Børresen-Dale, Anne-Lise Han, Wonshik Noh, Dong-Young Bukholm, Ida RK Nicolau, Monica Brown, Patrick O Tibshirani, Robert BMC Genomics Research Article BACKGROUND: Previous studies demonstrated breast cancer tumor tissue samples could be classified into different subtypes based upon DNA microarray profiles. The most recent study presented evidence for the existence of five different subtypes: normal breast-like, basal, luminal A, luminal B, and ERBB2(+). RESULTS: Based upon the analysis of 599 microarrays (five separate cDNA microarray datasets) using a novel approach, we present evidence in support of the most consistently identifiable subtypes of breast cancer tumor tissue microarrays being: ESR1(+)/ERBB2(-), ESR1(-)/ERBB2(-), and ERBB2(+ )(collectively called the ESR1/ERBB2 subtypes). We validate all three subtypes statistically and show the subtype to which a sample belongs is a significant predictor of overall survival and distant-metastasis free probability. CONCLUSION: As a consequence of the statistical validation procedure we have a set of centroids which can be applied to any microarray (indexed by UniGene Cluster ID) to classify it to one of the ESR1/ERBB2 subtypes. Moreover, the method used to define the ESR1/ERBB2 subtypes is not specific to the disease. The method can be used to identify subtypes in any disease for which there are at least two independent microarray datasets of disease samples. BioMed Central 2006-09-11 /pmc/articles/PMC1574316/ /pubmed/16965636 http://dx.doi.org/10.1186/1471-2164-7-231 Text en Copyright © 2006 Kapp 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 Article Kapp, Amy V Jeffrey, Stefanie S Langerød, Anita Børresen-Dale, Anne-Lise Han, Wonshik Noh, Dong-Young Bukholm, Ida RK Nicolau, Monica Brown, Patrick O Tibshirani, Robert Discovery and validation of breast cancer subtypes |
title | Discovery and validation of breast cancer subtypes |
title_full | Discovery and validation of breast cancer subtypes |
title_fullStr | Discovery and validation of breast cancer subtypes |
title_full_unstemmed | Discovery and validation of breast cancer subtypes |
title_short | Discovery and validation of breast cancer subtypes |
title_sort | discovery and validation of breast cancer subtypes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1574316/ https://www.ncbi.nlm.nih.gov/pubmed/16965636 http://dx.doi.org/10.1186/1471-2164-7-231 |
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