Deep multiomics profiling of brain tumors identifies signaling networks downstream of cancer driver genes

脑肿瘤的深度多组学分析确定了癌症驱动基因下游的信号网络

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作者:Hong Wang, Alexander K Diaz, Timothy I Shaw, Yuxin Li, Mingming Niu, Ji-Hoon Cho, Barbara S Paugh, Yang Zhang, Jeffrey Sifford, Bing Bai, Zhiping Wu, Haiyan Tan, Suiping Zhou, Laura D Hover, Heather S Tillman, Abbas Shirinifard, Suresh Thiagarajan, Andras Sablauer, Vishwajeeth Pagala, Anthony A High

Abstract

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.

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