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Prognostic signatures in breast cancer: correlation does not imply causation
Testing the statistical associations between microarray-based gene expression signatures and patient outcome has become a popular approach to infer biological and clinical significance of laboratory observations. Venet and colleagues recently demonstrated that the majority of randomly generated gene...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3446329/ https://www.ncbi.nlm.nih.gov/pubmed/22713235 http://dx.doi.org/10.1186/bcr3173 |
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author | Ng, Charlotte Weigelt, Britta Grigoriadis, Anita Reis-Filho, Jorge S |
author_facet | Ng, Charlotte Weigelt, Britta Grigoriadis, Anita Reis-Filho, Jorge S |
author_sort | Ng, Charlotte |
collection | PubMed |
description | Testing the statistical associations between microarray-based gene expression signatures and patient outcome has become a popular approach to infer biological and clinical significance of laboratory observations. Venet and colleagues recently demonstrated that the majority of randomly generated gene signatures are significantly associated with outcome of breast cancer patients, and that this association stems from the fact that a large proportion of the transcriptome is significantly correlated with proliferation, a strong predictor of outcome in breast cancer patients. These findings demonstrate that a statistical association between a gene signature and disease outcome does not necessarily imply biological significance. |
format | Online Article Text |
id | pubmed-3446329 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-34463292012-12-19 Prognostic signatures in breast cancer: correlation does not imply causation Ng, Charlotte Weigelt, Britta Grigoriadis, Anita Reis-Filho, Jorge S Breast Cancer Res Viewpoint Testing the statistical associations between microarray-based gene expression signatures and patient outcome has become a popular approach to infer biological and clinical significance of laboratory observations. Venet and colleagues recently demonstrated that the majority of randomly generated gene signatures are significantly associated with outcome of breast cancer patients, and that this association stems from the fact that a large proportion of the transcriptome is significantly correlated with proliferation, a strong predictor of outcome in breast cancer patients. These findings demonstrate that a statistical association between a gene signature and disease outcome does not necessarily imply biological significance. BioMed Central 2012 2012-06-19 /pmc/articles/PMC3446329/ /pubmed/22713235 http://dx.doi.org/10.1186/bcr3173 Text en Copyright ©2012 BioMed Central Ltd |
spellingShingle | Viewpoint Ng, Charlotte Weigelt, Britta Grigoriadis, Anita Reis-Filho, Jorge S Prognostic signatures in breast cancer: correlation does not imply causation |
title | Prognostic signatures in breast cancer: correlation does not imply causation |
title_full | Prognostic signatures in breast cancer: correlation does not imply causation |
title_fullStr | Prognostic signatures in breast cancer: correlation does not imply causation |
title_full_unstemmed | Prognostic signatures in breast cancer: correlation does not imply causation |
title_short | Prognostic signatures in breast cancer: correlation does not imply causation |
title_sort | prognostic signatures in breast cancer: correlation does not imply causation |
topic | Viewpoint |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3446329/ https://www.ncbi.nlm.nih.gov/pubmed/22713235 http://dx.doi.org/10.1186/bcr3173 |
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