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Association Analysis of Somatic Copy Number Alteration Burden With Breast Cancer Survival
The increasing prevalence of diagnosed breast cancer cases emphasizes the urgent demand for developing new prognostic breast cancer biomarkers. Copy number alteration (CNA) burden measured as the percentage of the genome affected by CNAs has emerged as a potential candidate to this aim. Using somati...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6178888/ https://www.ncbi.nlm.nih.gov/pubmed/30337938 http://dx.doi.org/10.3389/fgene.2018.00421 |
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author | Zhang, Linfan Feizi, Nikta Chi, Chen Hu, Pingzhao |
author_facet | Zhang, Linfan Feizi, Nikta Chi, Chen Hu, Pingzhao |
author_sort | Zhang, Linfan |
collection | PubMed |
description | The increasing prevalence of diagnosed breast cancer cases emphasizes the urgent demand for developing new prognostic breast cancer biomarkers. Copy number alteration (CNA) burden measured as the percentage of the genome affected by CNAs has emerged as a potential candidate to this aim. Using somatic CNA data obtained from METABRIC (Molecular Taxonomy of Breast Cancer International Consortium), we implemented Kaplan-Meier estimators and Cox proportional hazards models to examine the association of CNA burden with patient’s overall survival (OS) and disease specific survival (DSS). We also evaluated the association by considering patients’ age and tumor subtypes using stratified Cox models. We delineated the distribution of CNA burden in sample genomes and highlighted chromosomes 1, 8, and 16 as the carriers of the highest CNA burden. We identified a strong association between CNA burden and age as well as CNA burden and breast cancer PAM50 subtypes. We found that controlling the effects of both age (bound by 45-year) and PAM50 subtypes on patient survival using stratified Cox models, would still result in significant association between CNA burden and patients overall survival in both Discovery and Validation data. The same trend was observed in disease specific survival when only PAM50 subtypes were controlled in the stratified Cox models. Our analysis showed that there is a significant association between CNA burden and breast cancer survival. This result is also validated by using TCGA (The Cancer Genome Atlas) data. CNA burden of breast cancer patients has a considerable potential to be used as a novel prognostic biomarker. |
format | Online Article Text |
id | pubmed-6178888 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-61788882018-10-18 Association Analysis of Somatic Copy Number Alteration Burden With Breast Cancer Survival Zhang, Linfan Feizi, Nikta Chi, Chen Hu, Pingzhao Front Genet Genetics The increasing prevalence of diagnosed breast cancer cases emphasizes the urgent demand for developing new prognostic breast cancer biomarkers. Copy number alteration (CNA) burden measured as the percentage of the genome affected by CNAs has emerged as a potential candidate to this aim. Using somatic CNA data obtained from METABRIC (Molecular Taxonomy of Breast Cancer International Consortium), we implemented Kaplan-Meier estimators and Cox proportional hazards models to examine the association of CNA burden with patient’s overall survival (OS) and disease specific survival (DSS). We also evaluated the association by considering patients’ age and tumor subtypes using stratified Cox models. We delineated the distribution of CNA burden in sample genomes and highlighted chromosomes 1, 8, and 16 as the carriers of the highest CNA burden. We identified a strong association between CNA burden and age as well as CNA burden and breast cancer PAM50 subtypes. We found that controlling the effects of both age (bound by 45-year) and PAM50 subtypes on patient survival using stratified Cox models, would still result in significant association between CNA burden and patients overall survival in both Discovery and Validation data. The same trend was observed in disease specific survival when only PAM50 subtypes were controlled in the stratified Cox models. Our analysis showed that there is a significant association between CNA burden and breast cancer survival. This result is also validated by using TCGA (The Cancer Genome Atlas) data. CNA burden of breast cancer patients has a considerable potential to be used as a novel prognostic biomarker. Frontiers Media S.A. 2018-10-01 /pmc/articles/PMC6178888/ /pubmed/30337938 http://dx.doi.org/10.3389/fgene.2018.00421 Text en Copyright © 2018 Zhang, Feizi, Chi and Hu. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Zhang, Linfan Feizi, Nikta Chi, Chen Hu, Pingzhao Association Analysis of Somatic Copy Number Alteration Burden With Breast Cancer Survival |
title | Association Analysis of Somatic Copy Number Alteration Burden With Breast Cancer Survival |
title_full | Association Analysis of Somatic Copy Number Alteration Burden With Breast Cancer Survival |
title_fullStr | Association Analysis of Somatic Copy Number Alteration Burden With Breast Cancer Survival |
title_full_unstemmed | Association Analysis of Somatic Copy Number Alteration Burden With Breast Cancer Survival |
title_short | Association Analysis of Somatic Copy Number Alteration Burden With Breast Cancer Survival |
title_sort | association analysis of somatic copy number alteration burden with breast cancer survival |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6178888/ https://www.ncbi.nlm.nih.gov/pubmed/30337938 http://dx.doi.org/10.3389/fgene.2018.00421 |
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