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Deep multiomics profiling of brain tumors identifies signaling networks downstream of cancer driver genes
High throughput omics approaches provide an unprecedented opportunity for dissecting molecular mechanisms in cancer biology. Here we present deep profiling of whole proteome, phosphoproteome and transcriptome in two high-grade glioma (HGG) mouse models driven by mutated RTK oncogenes, PDGFRA and NTR...
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/PMC6697699/ https://www.ncbi.nlm.nih.gov/pubmed/31420543 http://dx.doi.org/10.1038/s41467-019-11661-4 |
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author | Wang, Hong Diaz, Alexander K. Shaw, Timothy I. Li, Yuxin Niu, Mingming Cho, Ji-Hoon Paugh, Barbara S. Zhang, Yang Sifford, Jeffrey Bai, Bing Wu, Zhiping Tan, Haiyan Zhou, Suiping Hover, Laura D. Tillman, Heather S. Shirinifard, Abbas Thiagarajan, Suresh Sablauer, Andras Pagala, Vishwajeeth High, Anthony A. Wang, Xusheng Li, Chunliang Baker, Suzanne J. Peng, Junmin |
author_facet | Wang, Hong Diaz, Alexander K. Shaw, Timothy I. Li, Yuxin Niu, Mingming Cho, Ji-Hoon Paugh, Barbara S. Zhang, Yang Sifford, Jeffrey Bai, Bing Wu, Zhiping Tan, Haiyan Zhou, Suiping Hover, Laura D. Tillman, Heather S. Shirinifard, Abbas Thiagarajan, Suresh Sablauer, Andras Pagala, Vishwajeeth High, Anthony A. Wang, Xusheng Li, Chunliang Baker, Suzanne J. Peng, Junmin |
author_sort | Wang, Hong |
collection | PubMed |
description | High throughput omics approaches provide an unprecedented opportunity for dissecting molecular mechanisms in cancer biology. Here we present deep profiling of whole proteome, phosphoproteome and transcriptome in two high-grade glioma (HGG) mouse models driven by mutated RTK oncogenes, PDGFRA and NTRK1, analyzing 13,860 proteins and 30,431 phosphosites by mass spectrometry. Systems biology approaches identify numerous master regulators, including 41 kinases and 23 transcription factors. Pathway activity computation and mouse survival indicate the NTRK1 mutation induces a higher activation of AKT downstream targets including MYC and JUN, drives a positive feedback loop to up-regulate multiple other RTKs, and confers higher oncogenic potency than the PDGFRA mutation. A mini-gRNA library CRISPR-Cas9 validation screening shows 56% of tested master regulators are important for the viability of NTRK-driven HGG cells, including TFs (Myc and Jun) and metabolic kinases (AMPKa1 and AMPKa2), confirming the validity of the multiomics integrative approaches, and providing novel tumor vulnerabilities. |
format | Online Article Text |
id | pubmed-6697699 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-66976992019-08-19 Deep multiomics profiling of brain tumors identifies signaling networks downstream of cancer driver genes Wang, Hong Diaz, Alexander K. Shaw, Timothy I. Li, Yuxin Niu, Mingming Cho, Ji-Hoon Paugh, Barbara S. Zhang, Yang Sifford, Jeffrey Bai, Bing Wu, Zhiping Tan, Haiyan Zhou, Suiping Hover, Laura D. Tillman, Heather S. Shirinifard, Abbas Thiagarajan, Suresh Sablauer, Andras Pagala, Vishwajeeth High, Anthony A. Wang, Xusheng Li, Chunliang Baker, Suzanne J. Peng, Junmin Nat Commun Article High throughput omics approaches provide an unprecedented opportunity for dissecting molecular mechanisms in cancer biology. Here we present deep profiling of whole proteome, phosphoproteome and transcriptome in two high-grade glioma (HGG) mouse models driven by mutated RTK oncogenes, PDGFRA and NTRK1, analyzing 13,860 proteins and 30,431 phosphosites by mass spectrometry. Systems biology approaches identify numerous master regulators, including 41 kinases and 23 transcription factors. Pathway activity computation and mouse survival indicate the NTRK1 mutation induces a higher activation of AKT downstream targets including MYC and JUN, drives a positive feedback loop to up-regulate multiple other RTKs, and confers higher oncogenic potency than the PDGFRA mutation. A mini-gRNA library CRISPR-Cas9 validation screening shows 56% of tested master regulators are important for the viability of NTRK-driven HGG cells, including TFs (Myc and Jun) and metabolic kinases (AMPKa1 and AMPKa2), confirming the validity of the multiomics integrative approaches, and providing novel tumor vulnerabilities. Nature Publishing Group UK 2019-08-16 /pmc/articles/PMC6697699/ /pubmed/31420543 http://dx.doi.org/10.1038/s41467-019-11661-4 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 Wang, Hong Diaz, Alexander K. Shaw, Timothy I. Li, Yuxin Niu, Mingming Cho, Ji-Hoon Paugh, Barbara S. Zhang, Yang Sifford, Jeffrey Bai, Bing Wu, Zhiping Tan, Haiyan Zhou, Suiping Hover, Laura D. Tillman, Heather S. Shirinifard, Abbas Thiagarajan, Suresh Sablauer, Andras Pagala, Vishwajeeth High, Anthony A. Wang, Xusheng Li, Chunliang Baker, Suzanne J. Peng, Junmin Deep multiomics profiling of brain tumors identifies signaling networks downstream of cancer driver genes |
title | Deep multiomics profiling of brain tumors identifies signaling networks downstream of cancer driver genes |
title_full | Deep multiomics profiling of brain tumors identifies signaling networks downstream of cancer driver genes |
title_fullStr | Deep multiomics profiling of brain tumors identifies signaling networks downstream of cancer driver genes |
title_full_unstemmed | Deep multiomics profiling of brain tumors identifies signaling networks downstream of cancer driver genes |
title_short | Deep multiomics profiling of brain tumors identifies signaling networks downstream of cancer driver genes |
title_sort | deep multiomics profiling of brain tumors identifies signaling networks downstream of cancer driver genes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6697699/ https://www.ncbi.nlm.nih.gov/pubmed/31420543 http://dx.doi.org/10.1038/s41467-019-11661-4 |
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