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Multi-layered proteomic analyses decode compositional and functional effects of cancer mutations on kinase complexes
Rapidly increasing availability of genomic data and ensuing identification of disease associated mutations allows for an unbiased insight into genetic drivers of disease development. However, determination of molecular mechanisms by which individual genomic changes affect biochemical processes remai...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7366679/ https://www.ncbi.nlm.nih.gov/pubmed/32678104 http://dx.doi.org/10.1038/s41467-020-17387-y |
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author | Mehnert, Martin Ciuffa, Rodolfo Frommelt, Fabian Uliana, Federico van Drogen, Audrey Ruminski, Kilian Gstaiger, Matthias Aebersold, Ruedi |
author_facet | Mehnert, Martin Ciuffa, Rodolfo Frommelt, Fabian Uliana, Federico van Drogen, Audrey Ruminski, Kilian Gstaiger, Matthias Aebersold, Ruedi |
author_sort | Mehnert, Martin |
collection | PubMed |
description | Rapidly increasing availability of genomic data and ensuing identification of disease associated mutations allows for an unbiased insight into genetic drivers of disease development. However, determination of molecular mechanisms by which individual genomic changes affect biochemical processes remains a major challenge. Here, we develop a multilayered proteomic workflow to explore how genetic lesions modulate the proteome and are translated into molecular phenotypes. Using this workflow we determine how expression of a panel of disease-associated mutations in the Dyrk2 protein kinase alter the composition, topology and activity of this kinase complex as well as the phosphoproteomic state of the cell. The data show that altered protein-protein interactions caused by the mutations are associated with topological changes and affected phosphorylation of known cancer driver proteins, thus linking Dyrk2 mutations with cancer-related biochemical processes. Overall, we discover multiple mutation-specific functionally relevant changes, thus highlighting the extensive plasticity of molecular responses to genetic lesions. |
format | Online Article Text |
id | pubmed-7366679 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-73666792020-07-21 Multi-layered proteomic analyses decode compositional and functional effects of cancer mutations on kinase complexes Mehnert, Martin Ciuffa, Rodolfo Frommelt, Fabian Uliana, Federico van Drogen, Audrey Ruminski, Kilian Gstaiger, Matthias Aebersold, Ruedi Nat Commun Article Rapidly increasing availability of genomic data and ensuing identification of disease associated mutations allows for an unbiased insight into genetic drivers of disease development. However, determination of molecular mechanisms by which individual genomic changes affect biochemical processes remains a major challenge. Here, we develop a multilayered proteomic workflow to explore how genetic lesions modulate the proteome and are translated into molecular phenotypes. Using this workflow we determine how expression of a panel of disease-associated mutations in the Dyrk2 protein kinase alter the composition, topology and activity of this kinase complex as well as the phosphoproteomic state of the cell. The data show that altered protein-protein interactions caused by the mutations are associated with topological changes and affected phosphorylation of known cancer driver proteins, thus linking Dyrk2 mutations with cancer-related biochemical processes. Overall, we discover multiple mutation-specific functionally relevant changes, thus highlighting the extensive plasticity of molecular responses to genetic lesions. Nature Publishing Group UK 2020-07-16 /pmc/articles/PMC7366679/ /pubmed/32678104 http://dx.doi.org/10.1038/s41467-020-17387-y Text en © The Author(s) 2020 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 Mehnert, Martin Ciuffa, Rodolfo Frommelt, Fabian Uliana, Federico van Drogen, Audrey Ruminski, Kilian Gstaiger, Matthias Aebersold, Ruedi Multi-layered proteomic analyses decode compositional and functional effects of cancer mutations on kinase complexes |
title | Multi-layered proteomic analyses decode compositional and functional effects of cancer mutations on kinase complexes |
title_full | Multi-layered proteomic analyses decode compositional and functional effects of cancer mutations on kinase complexes |
title_fullStr | Multi-layered proteomic analyses decode compositional and functional effects of cancer mutations on kinase complexes |
title_full_unstemmed | Multi-layered proteomic analyses decode compositional and functional effects of cancer mutations on kinase complexes |
title_short | Multi-layered proteomic analyses decode compositional and functional effects of cancer mutations on kinase complexes |
title_sort | multi-layered proteomic analyses decode compositional and functional effects of cancer mutations on kinase complexes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7366679/ https://www.ncbi.nlm.nih.gov/pubmed/32678104 http://dx.doi.org/10.1038/s41467-020-17387-y |
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