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Cross-species DNA copy number analyses identifies multiple 1q21-q23 subtype-specific driver genes for breast cancer

A large number of DNA copy number alterations (CNAs) exist in human breast cancers, and thus characterizing the most frequent CNAs is key to advancing therapeutics because it is likely that these regions contain breast tumor ‘drivers’ (i.e., cancer causal genes). This study aims to characterize the...

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Autores principales: Silva, Grace O., He, Xiaping, Parker, Joel S., Gatza, Michael L., Carey, Lisa A., Hou, Jack P., Moulder, Stacy L., Marcom, Paul K., Ma, Jian, Rosen, Jeffrey M., Perou, Charles M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4491106/
https://www.ncbi.nlm.nih.gov/pubmed/26109346
http://dx.doi.org/10.1007/s10549-015-3476-2
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author Silva, Grace O.
He, Xiaping
Parker, Joel S.
Gatza, Michael L.
Carey, Lisa A.
Hou, Jack P.
Moulder, Stacy L.
Marcom, Paul K.
Ma, Jian
Rosen, Jeffrey M.
Perou, Charles M.
author_facet Silva, Grace O.
He, Xiaping
Parker, Joel S.
Gatza, Michael L.
Carey, Lisa A.
Hou, Jack P.
Moulder, Stacy L.
Marcom, Paul K.
Ma, Jian
Rosen, Jeffrey M.
Perou, Charles M.
author_sort Silva, Grace O.
collection PubMed
description A large number of DNA copy number alterations (CNAs) exist in human breast cancers, and thus characterizing the most frequent CNAs is key to advancing therapeutics because it is likely that these regions contain breast tumor ‘drivers’ (i.e., cancer causal genes). This study aims to characterize the genomic landscape of breast cancer CNAs and identify potential subtype-specific drivers using a large set of human breast tumors and genetically engineered mouse (GEM) mammary tumors. Using a novel method called SWITCHplus, we identified subtype-specific DNA CNAs occurring at a 15 % or greater frequency, which excluded many well-known breast cancer-related drivers such as amplification of ERBB2, and deletions of TP53 and RB1. A comparison of CNAs between mouse and human breast tumors identified regions with shared subtype-specific CNAs. Additional criteria that included gene expression-to-copy number correlation, a DawnRank network analysis, and RNA interference functional studies highlighted candidate driver genes that fulfilled these multiple criteria. Numerous regions of shared CNAs were observed between human breast tumors and GEM mammary tumor models that shared similar gene expression features. Specifically, we identified chromosome 1q21-23 as a Basal-like subtype-enriched region with multiple potential driver genes including PI4KB, SHC1, and NCSTN. This step-wise computational approach based on a cross-species comparison is applicable to any tumor type for which sufficient human and model system DNA copy number data exist, and in this instance, highlights that a single region of amplification may in fact harbor multiple driver genes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10549-015-3476-2) contains supplementary material, which is available to authorized users.
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spelling pubmed-44911062015-07-08 Cross-species DNA copy number analyses identifies multiple 1q21-q23 subtype-specific driver genes for breast cancer Silva, Grace O. He, Xiaping Parker, Joel S. Gatza, Michael L. Carey, Lisa A. Hou, Jack P. Moulder, Stacy L. Marcom, Paul K. Ma, Jian Rosen, Jeffrey M. Perou, Charles M. Breast Cancer Res Treat Preclinical Study A large number of DNA copy number alterations (CNAs) exist in human breast cancers, and thus characterizing the most frequent CNAs is key to advancing therapeutics because it is likely that these regions contain breast tumor ‘drivers’ (i.e., cancer causal genes). This study aims to characterize the genomic landscape of breast cancer CNAs and identify potential subtype-specific drivers using a large set of human breast tumors and genetically engineered mouse (GEM) mammary tumors. Using a novel method called SWITCHplus, we identified subtype-specific DNA CNAs occurring at a 15 % or greater frequency, which excluded many well-known breast cancer-related drivers such as amplification of ERBB2, and deletions of TP53 and RB1. A comparison of CNAs between mouse and human breast tumors identified regions with shared subtype-specific CNAs. Additional criteria that included gene expression-to-copy number correlation, a DawnRank network analysis, and RNA interference functional studies highlighted candidate driver genes that fulfilled these multiple criteria. Numerous regions of shared CNAs were observed between human breast tumors and GEM mammary tumor models that shared similar gene expression features. Specifically, we identified chromosome 1q21-23 as a Basal-like subtype-enriched region with multiple potential driver genes including PI4KB, SHC1, and NCSTN. This step-wise computational approach based on a cross-species comparison is applicable to any tumor type for which sufficient human and model system DNA copy number data exist, and in this instance, highlights that a single region of amplification may in fact harbor multiple driver genes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10549-015-3476-2) contains supplementary material, which is available to authorized users. Springer US 2015-06-25 2015 /pmc/articles/PMC4491106/ /pubmed/26109346 http://dx.doi.org/10.1007/s10549-015-3476-2 Text en © The Author(s) 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial 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.
spellingShingle Preclinical Study
Silva, Grace O.
He, Xiaping
Parker, Joel S.
Gatza, Michael L.
Carey, Lisa A.
Hou, Jack P.
Moulder, Stacy L.
Marcom, Paul K.
Ma, Jian
Rosen, Jeffrey M.
Perou, Charles M.
Cross-species DNA copy number analyses identifies multiple 1q21-q23 subtype-specific driver genes for breast cancer
title Cross-species DNA copy number analyses identifies multiple 1q21-q23 subtype-specific driver genes for breast cancer
title_full Cross-species DNA copy number analyses identifies multiple 1q21-q23 subtype-specific driver genes for breast cancer
title_fullStr Cross-species DNA copy number analyses identifies multiple 1q21-q23 subtype-specific driver genes for breast cancer
title_full_unstemmed Cross-species DNA copy number analyses identifies multiple 1q21-q23 subtype-specific driver genes for breast cancer
title_short Cross-species DNA copy number analyses identifies multiple 1q21-q23 subtype-specific driver genes for breast cancer
title_sort cross-species dna copy number analyses identifies multiple 1q21-q23 subtype-specific driver genes for breast cancer
topic Preclinical Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4491106/
https://www.ncbi.nlm.nih.gov/pubmed/26109346
http://dx.doi.org/10.1007/s10549-015-3476-2
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