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Comprehensive analyses of somatic TP53 mutation in tumors with variable mutant allele frequency
Somatic mutation of the tumor suppressor gene TP53 is reported in at least 50% of human malignancies. Most high-grade serous ovarian cancers (HGSC) have a mutant TP53 allele. Accurate detection of these mutants in heterogeneous tumor tissue is paramount as therapies emerge to target mutant p53. We u...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5584393/ https://www.ncbi.nlm.nih.gov/pubmed/28872635 http://dx.doi.org/10.1038/sdata.2017.120 |
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author | Cole, Alexander J. Zhu, Ying Dwight, Trisha Yu, Bing Dickson, Kristie-Ann Gard, Gregory B. Maidens, Jayne Valmadre, Susan Gill, Anthony J. Clifton-Bligh, Roderick Marsh, Deborah J. |
author_facet | Cole, Alexander J. Zhu, Ying Dwight, Trisha Yu, Bing Dickson, Kristie-Ann Gard, Gregory B. Maidens, Jayne Valmadre, Susan Gill, Anthony J. Clifton-Bligh, Roderick Marsh, Deborah J. |
author_sort | Cole, Alexander J. |
collection | PubMed |
description | Somatic mutation of the tumor suppressor gene TP53 is reported in at least 50% of human malignancies. Most high-grade serous ovarian cancers (HGSC) have a mutant TP53 allele. Accurate detection of these mutants in heterogeneous tumor tissue is paramount as therapies emerge to target mutant p53. We used a Fluidigm Access Array™ System with Massively Parallel Sequencing (MPS) to analyze DNA extracted from 76 serous ovarian tumors. This dataset has been made available to researchers through the European Genome-phenome Archive (EGA; EGAS00001002200). Herein, we present analyses of this dataset using HaplotypeCaller and MuTect2 through the Broad Institute’s Genome Analysis Toolkit (GATK). We anticipate that this TP53 mutation dataset will be useful to researchers developing and testing new software to accurately determine high and low frequency variant alleles in heterogeneous aneuploid tumor tissue. Furthermore, the analysis pipeline we present provides a valuable framework for determining somatic variants more broadly in tumor tissue. |
format | Online Article Text |
id | pubmed-5584393 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-55843932017-09-12 Comprehensive analyses of somatic TP53 mutation in tumors with variable mutant allele frequency Cole, Alexander J. Zhu, Ying Dwight, Trisha Yu, Bing Dickson, Kristie-Ann Gard, Gregory B. Maidens, Jayne Valmadre, Susan Gill, Anthony J. Clifton-Bligh, Roderick Marsh, Deborah J. Sci Data Data Descriptor Somatic mutation of the tumor suppressor gene TP53 is reported in at least 50% of human malignancies. Most high-grade serous ovarian cancers (HGSC) have a mutant TP53 allele. Accurate detection of these mutants in heterogeneous tumor tissue is paramount as therapies emerge to target mutant p53. We used a Fluidigm Access Array™ System with Massively Parallel Sequencing (MPS) to analyze DNA extracted from 76 serous ovarian tumors. This dataset has been made available to researchers through the European Genome-phenome Archive (EGA; EGAS00001002200). Herein, we present analyses of this dataset using HaplotypeCaller and MuTect2 through the Broad Institute’s Genome Analysis Toolkit (GATK). We anticipate that this TP53 mutation dataset will be useful to researchers developing and testing new software to accurately determine high and low frequency variant alleles in heterogeneous aneuploid tumor tissue. Furthermore, the analysis pipeline we present provides a valuable framework for determining somatic variants more broadly in tumor tissue. Nature Publishing Group 2017-09-05 /pmc/articles/PMC5584393/ /pubmed/28872635 http://dx.doi.org/10.1038/sdata.2017.120 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article. |
spellingShingle | Data Descriptor Cole, Alexander J. Zhu, Ying Dwight, Trisha Yu, Bing Dickson, Kristie-Ann Gard, Gregory B. Maidens, Jayne Valmadre, Susan Gill, Anthony J. Clifton-Bligh, Roderick Marsh, Deborah J. Comprehensive analyses of somatic TP53 mutation in tumors with variable mutant allele frequency |
title | Comprehensive analyses of somatic TP53 mutation in tumors with variable mutant allele frequency |
title_full | Comprehensive analyses of somatic TP53 mutation in tumors with variable mutant allele frequency |
title_fullStr | Comprehensive analyses of somatic TP53 mutation in tumors with variable mutant allele frequency |
title_full_unstemmed | Comprehensive analyses of somatic TP53 mutation in tumors with variable mutant allele frequency |
title_short | Comprehensive analyses of somatic TP53 mutation in tumors with variable mutant allele frequency |
title_sort | comprehensive analyses of somatic tp53 mutation in tumors with variable mutant allele frequency |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5584393/ https://www.ncbi.nlm.nih.gov/pubmed/28872635 http://dx.doi.org/10.1038/sdata.2017.120 |
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