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Application of RNAi-induced gene expression profiles for prognostic prediction in breast cancer
Homologous recombination (HR) is the primary pathway for repairing double-strand DNA breaks implicating in the development of cancer. RNAi-based knockdowns of BRCA1 and RAD51 in this pathway have been performed to investigate the resulting transcriptomic profiles. Here we propose a computational fra...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5084341/ https://www.ncbi.nlm.nih.gov/pubmed/27788678 http://dx.doi.org/10.1186/s13073-016-0363-3 |
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author | Wang, Yue Mark, Kenneth M. K. Ung, Matthew H. Kettenbach, Arminja Miller, Todd Xu, Wei Cheng, Wenqing Xia, Tian Cheng, Chao |
author_facet | Wang, Yue Mark, Kenneth M. K. Ung, Matthew H. Kettenbach, Arminja Miller, Todd Xu, Wei Cheng, Wenqing Xia, Tian Cheng, Chao |
author_sort | Wang, Yue |
collection | PubMed |
description | Homologous recombination (HR) is the primary pathway for repairing double-strand DNA breaks implicating in the development of cancer. RNAi-based knockdowns of BRCA1 and RAD51 in this pathway have been performed to investigate the resulting transcriptomic profiles. Here we propose a computational framework to utilize these profiles to calculate a score, named RNA-Interference derived Proliferation Score (RIPS), which reflects cell proliferation ability in individual breast tumors. RIPS is predictive of breast cancer classes, prognosis, genome instability, and neoadjuvant chemosensitivity. This framework directly translates the readout of knockdown experiments into potential clinical applications and generates a robust biomarker in breast cancer. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13073-016-0363-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5084341 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-50843412016-10-28 Application of RNAi-induced gene expression profiles for prognostic prediction in breast cancer Wang, Yue Mark, Kenneth M. K. Ung, Matthew H. Kettenbach, Arminja Miller, Todd Xu, Wei Cheng, Wenqing Xia, Tian Cheng, Chao Genome Med Method Homologous recombination (HR) is the primary pathway for repairing double-strand DNA breaks implicating in the development of cancer. RNAi-based knockdowns of BRCA1 and RAD51 in this pathway have been performed to investigate the resulting transcriptomic profiles. Here we propose a computational framework to utilize these profiles to calculate a score, named RNA-Interference derived Proliferation Score (RIPS), which reflects cell proliferation ability in individual breast tumors. RIPS is predictive of breast cancer classes, prognosis, genome instability, and neoadjuvant chemosensitivity. This framework directly translates the readout of knockdown experiments into potential clinical applications and generates a robust biomarker in breast cancer. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13073-016-0363-3) contains supplementary material, which is available to authorized users. BioMed Central 2016-10-27 /pmc/articles/PMC5084341/ /pubmed/27788678 http://dx.doi.org/10.1186/s13073-016-0363-3 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Method Wang, Yue Mark, Kenneth M. K. Ung, Matthew H. Kettenbach, Arminja Miller, Todd Xu, Wei Cheng, Wenqing Xia, Tian Cheng, Chao Application of RNAi-induced gene expression profiles for prognostic prediction in breast cancer |
title | Application of RNAi-induced gene expression profiles for prognostic prediction in breast cancer |
title_full | Application of RNAi-induced gene expression profiles for prognostic prediction in breast cancer |
title_fullStr | Application of RNAi-induced gene expression profiles for prognostic prediction in breast cancer |
title_full_unstemmed | Application of RNAi-induced gene expression profiles for prognostic prediction in breast cancer |
title_short | Application of RNAi-induced gene expression profiles for prognostic prediction in breast cancer |
title_sort | application of rnai-induced gene expression profiles for prognostic prediction in breast cancer |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5084341/ https://www.ncbi.nlm.nih.gov/pubmed/27788678 http://dx.doi.org/10.1186/s13073-016-0363-3 |
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