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Identification of recurrent focal copy number variations and their putative targeted driver genes in ovarian cancer
BACKGROUND: Genomic regions with recurrent DNA copy number variations (CNVs) are generally believed to encode oncogenes and tumor suppressor genes (TSGs) that drive cancer growth. However, it remains a challenge to delineate the key cancer driver genes from the regions encoding a large number of gen...
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/PMC4881176/ https://www.ncbi.nlm.nih.gov/pubmed/27230211 http://dx.doi.org/10.1186/s12859-016-1085-7 |
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author | Zhang, Liangcai Yuan, Ying Lu, Karen H. Zhang, Li |
author_facet | Zhang, Liangcai Yuan, Ying Lu, Karen H. Zhang, Li |
author_sort | Zhang, Liangcai |
collection | PubMed |
description | BACKGROUND: Genomic regions with recurrent DNA copy number variations (CNVs) are generally believed to encode oncogenes and tumor suppressor genes (TSGs) that drive cancer growth. However, it remains a challenge to delineate the key cancer driver genes from the regions encoding a large number of genes. RESULTS: In this study, we developed a new approach to CNV analysis based on spectral decomposition of CNV profiles into focal CNVs and broad CNVs. We performed an analysis of CNV data of 587 serous ovarian cancer samples on multiple platforms. We identified a number of novel focal regions, such as focal gain of ESR1, focal loss of LSAMP, prognostic site at 3q26.2 and losses of sub-telomere regions in multiple chromosomes. Furthermore, we performed network modularity analysis to examine the relationships among genes encoded in the focal CNV regions. Our results also showed that the recurrent focal gains were significantly associated with the known oncogenes and recurrent losses associated with TSGs and the CNVs had a greater effect on the mRNA expression of the driver genes than that of the non-driver genes. CONCLUSIONS: Our results demonstrate that spectral decomposition of CNV profiles offers a new way of understanding the role of CNVs in cancer. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1085-7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4881176 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-48811762016-06-07 Identification of recurrent focal copy number variations and their putative targeted driver genes in ovarian cancer Zhang, Liangcai Yuan, Ying Lu, Karen H. Zhang, Li BMC Bioinformatics Methodology Article BACKGROUND: Genomic regions with recurrent DNA copy number variations (CNVs) are generally believed to encode oncogenes and tumor suppressor genes (TSGs) that drive cancer growth. However, it remains a challenge to delineate the key cancer driver genes from the regions encoding a large number of genes. RESULTS: In this study, we developed a new approach to CNV analysis based on spectral decomposition of CNV profiles into focal CNVs and broad CNVs. We performed an analysis of CNV data of 587 serous ovarian cancer samples on multiple platforms. We identified a number of novel focal regions, such as focal gain of ESR1, focal loss of LSAMP, prognostic site at 3q26.2 and losses of sub-telomere regions in multiple chromosomes. Furthermore, we performed network modularity analysis to examine the relationships among genes encoded in the focal CNV regions. Our results also showed that the recurrent focal gains were significantly associated with the known oncogenes and recurrent losses associated with TSGs and the CNVs had a greater effect on the mRNA expression of the driver genes than that of the non-driver genes. CONCLUSIONS: Our results demonstrate that spectral decomposition of CNV profiles offers a new way of understanding the role of CNVs in cancer. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1085-7) contains supplementary material, which is available to authorized users. BioMed Central 2016-05-26 /pmc/articles/PMC4881176/ /pubmed/27230211 http://dx.doi.org/10.1186/s12859-016-1085-7 Text en © Zhang et al. 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 | Methodology Article Zhang, Liangcai Yuan, Ying Lu, Karen H. Zhang, Li Identification of recurrent focal copy number variations and their putative targeted driver genes in ovarian cancer |
title | Identification of recurrent focal copy number variations and their putative targeted driver genes in ovarian cancer |
title_full | Identification of recurrent focal copy number variations and their putative targeted driver genes in ovarian cancer |
title_fullStr | Identification of recurrent focal copy number variations and their putative targeted driver genes in ovarian cancer |
title_full_unstemmed | Identification of recurrent focal copy number variations and their putative targeted driver genes in ovarian cancer |
title_short | Identification of recurrent focal copy number variations and their putative targeted driver genes in ovarian cancer |
title_sort | identification of recurrent focal copy number variations and their putative targeted driver genes in ovarian cancer |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4881176/ https://www.ncbi.nlm.nih.gov/pubmed/27230211 http://dx.doi.org/10.1186/s12859-016-1085-7 |
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