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Pan-cancer proteogenomic investigations identify post-transcriptional kinase targets

Identifying genomic alterations of cancer proteins has guided the development of targeted therapies, but proteomic analyses are required to validate and reveal new treatment opportunities. Herein, we develop a new algorithm, OPPTI, to discover overexpressed kinase proteins across 10 cancer types usi...

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Autores principales: Elmas, Abdulkadir, Tharakan, Serena, Jaladanki, Suraj, Galsky, Matthew D., Liu, Tao, Huang, Kuan-lin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8458405/
https://www.ncbi.nlm.nih.gov/pubmed/34552204
http://dx.doi.org/10.1038/s42003-021-02636-7
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author Elmas, Abdulkadir
Tharakan, Serena
Jaladanki, Suraj
Galsky, Matthew D.
Liu, Tao
Huang, Kuan-lin
author_facet Elmas, Abdulkadir
Tharakan, Serena
Jaladanki, Suraj
Galsky, Matthew D.
Liu, Tao
Huang, Kuan-lin
author_sort Elmas, Abdulkadir
collection PubMed
description Identifying genomic alterations of cancer proteins has guided the development of targeted therapies, but proteomic analyses are required to validate and reveal new treatment opportunities. Herein, we develop a new algorithm, OPPTI, to discover overexpressed kinase proteins across 10 cancer types using global mass spectrometry proteomics data of 1,071 cases. OPPTI outperforms existing methods by leveraging multiple co-expressed markers to identify targets overexpressed in a subset of tumors. OPPTI-identified overexpression of ERBB2 and EGFR proteins correlates with genomic amplifications, while CDK4/6, PDK1, and MET protein overexpression frequently occur without corresponding DNA- and RNA-level alterations. Analyzing CRISPR screen data, we confirm expression-driven dependencies of multiple currently-druggable and new target kinases whose expressions are validated by immunochemistry. Identified kinases are further associated with up-regulated phosphorylation levels of corresponding signaling pathways. Collectively, our results reveal protein-level aberrations—sometimes not observed by genomics—represent cancer vulnerabilities that may be targeted in precision oncology.
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spelling pubmed-84584052021-10-07 Pan-cancer proteogenomic investigations identify post-transcriptional kinase targets Elmas, Abdulkadir Tharakan, Serena Jaladanki, Suraj Galsky, Matthew D. Liu, Tao Huang, Kuan-lin Commun Biol Article Identifying genomic alterations of cancer proteins has guided the development of targeted therapies, but proteomic analyses are required to validate and reveal new treatment opportunities. Herein, we develop a new algorithm, OPPTI, to discover overexpressed kinase proteins across 10 cancer types using global mass spectrometry proteomics data of 1,071 cases. OPPTI outperforms existing methods by leveraging multiple co-expressed markers to identify targets overexpressed in a subset of tumors. OPPTI-identified overexpression of ERBB2 and EGFR proteins correlates with genomic amplifications, while CDK4/6, PDK1, and MET protein overexpression frequently occur without corresponding DNA- and RNA-level alterations. Analyzing CRISPR screen data, we confirm expression-driven dependencies of multiple currently-druggable and new target kinases whose expressions are validated by immunochemistry. Identified kinases are further associated with up-regulated phosphorylation levels of corresponding signaling pathways. Collectively, our results reveal protein-level aberrations—sometimes not observed by genomics—represent cancer vulnerabilities that may be targeted in precision oncology. Nature Publishing Group UK 2021-09-22 /pmc/articles/PMC8458405/ /pubmed/34552204 http://dx.doi.org/10.1038/s42003-021-02636-7 Text en © The Author(s) 2021 https://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/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Elmas, Abdulkadir
Tharakan, Serena
Jaladanki, Suraj
Galsky, Matthew D.
Liu, Tao
Huang, Kuan-lin
Pan-cancer proteogenomic investigations identify post-transcriptional kinase targets
title Pan-cancer proteogenomic investigations identify post-transcriptional kinase targets
title_full Pan-cancer proteogenomic investigations identify post-transcriptional kinase targets
title_fullStr Pan-cancer proteogenomic investigations identify post-transcriptional kinase targets
title_full_unstemmed Pan-cancer proteogenomic investigations identify post-transcriptional kinase targets
title_short Pan-cancer proteogenomic investigations identify post-transcriptional kinase targets
title_sort pan-cancer proteogenomic investigations identify post-transcriptional kinase targets
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8458405/
https://www.ncbi.nlm.nih.gov/pubmed/34552204
http://dx.doi.org/10.1038/s42003-021-02636-7
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