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Proteogenomic Analysis of Protein Sequence Alterations in Breast Cancer Cells
Cancer evolves as a result of an accumulation of mutations and chromosomal aberrations. Developments in sequencing technologies have enabled the discovery and cataloguing of millions of such mutations. The identification of protein-level alterations, typically by using reversed-phase protein arrays...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6637242/ https://www.ncbi.nlm.nih.gov/pubmed/31316139 http://dx.doi.org/10.1038/s41598-019-46897-z |
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author | Lazar, Iulia M. Karcini, Arba Ahuja, Shreya Estrada-Palma, Carly |
author_facet | Lazar, Iulia M. Karcini, Arba Ahuja, Shreya Estrada-Palma, Carly |
author_sort | Lazar, Iulia M. |
collection | PubMed |
description | Cancer evolves as a result of an accumulation of mutations and chromosomal aberrations. Developments in sequencing technologies have enabled the discovery and cataloguing of millions of such mutations. The identification of protein-level alterations, typically by using reversed-phase protein arrays or mass spectrometry, has lagged, however, behind gene and transcript-level observations. In this study, we report the use of mass spectrometry for detecting the presence of mutations-missense, indels and frame shifts-in MCF7 and SKBR3 breast cancer, and non-tumorigenic MCF10A cells. The mutations were identified by expanding the database search process of raw mass spectrometry files by including an in-house built database of mutated peptides (XMAn-v1) that complemented a minimally redundant, canonical database of Homo sapiens proteins. The work resulted in the identification of nearly 300 mutated peptide sequences, of which ~50 were characterized by quality tandem mass spectra. We describe the criteria that were used to select the mutated peptide sequences, evaluate the parameters that characterized these peptides, and assess the artifacts that could have led to false peptide identifications. Further, we discuss the functional domains and biological processes that may be impacted by the observed peptide alterations, and how protein-level detection can support the efforts of identifying cancer driving mutations and genes. Mass spectrometry data are available via ProteomeXchange with identifier PXD014458. |
format | Online Article Text |
id | pubmed-6637242 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-66372422019-07-25 Proteogenomic Analysis of Protein Sequence Alterations in Breast Cancer Cells Lazar, Iulia M. Karcini, Arba Ahuja, Shreya Estrada-Palma, Carly Sci Rep Article Cancer evolves as a result of an accumulation of mutations and chromosomal aberrations. Developments in sequencing technologies have enabled the discovery and cataloguing of millions of such mutations. The identification of protein-level alterations, typically by using reversed-phase protein arrays or mass spectrometry, has lagged, however, behind gene and transcript-level observations. In this study, we report the use of mass spectrometry for detecting the presence of mutations-missense, indels and frame shifts-in MCF7 and SKBR3 breast cancer, and non-tumorigenic MCF10A cells. The mutations were identified by expanding the database search process of raw mass spectrometry files by including an in-house built database of mutated peptides (XMAn-v1) that complemented a minimally redundant, canonical database of Homo sapiens proteins. The work resulted in the identification of nearly 300 mutated peptide sequences, of which ~50 were characterized by quality tandem mass spectra. We describe the criteria that were used to select the mutated peptide sequences, evaluate the parameters that characterized these peptides, and assess the artifacts that could have led to false peptide identifications. Further, we discuss the functional domains and biological processes that may be impacted by the observed peptide alterations, and how protein-level detection can support the efforts of identifying cancer driving mutations and genes. Mass spectrometry data are available via ProteomeXchange with identifier PXD014458. Nature Publishing Group UK 2019-07-17 /pmc/articles/PMC6637242/ /pubmed/31316139 http://dx.doi.org/10.1038/s41598-019-46897-z Text en © The Author(s) 2019 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/. |
spellingShingle | Article Lazar, Iulia M. Karcini, Arba Ahuja, Shreya Estrada-Palma, Carly Proteogenomic Analysis of Protein Sequence Alterations in Breast Cancer Cells |
title | Proteogenomic Analysis of Protein Sequence Alterations in Breast Cancer Cells |
title_full | Proteogenomic Analysis of Protein Sequence Alterations in Breast Cancer Cells |
title_fullStr | Proteogenomic Analysis of Protein Sequence Alterations in Breast Cancer Cells |
title_full_unstemmed | Proteogenomic Analysis of Protein Sequence Alterations in Breast Cancer Cells |
title_short | Proteogenomic Analysis of Protein Sequence Alterations in Breast Cancer Cells |
title_sort | proteogenomic analysis of protein sequence alterations in breast cancer cells |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6637242/ https://www.ncbi.nlm.nih.gov/pubmed/31316139 http://dx.doi.org/10.1038/s41598-019-46897-z |
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