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Updated: Jan 20, 2026

Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres
Published on: July 22, 2020
Deep multiomics profiling of brain tumors identifies signaling networks downstream of cancer driver genes
Hong Wang1,2,3, Alexander K Diaz3,4, Timothy I Shaw2,5
1Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA.
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.
Insights
High-throughput omics revealed key molecular drivers in high-grade glioma (HGG). NTRK1 mutations showed greater oncogenic activity than PDGFRA, highlighting novel therapeutic targets like MYC and JUN.
Area of Science:
- Oncology
- Molecular Biology
- Genomics
Background:
- High-throughput omics technologies offer powerful tools for understanding complex cancer biology.
- High-grade glioma (HGG) is an aggressive brain tumor with limited treatment options.
Purpose of the Study:
- To comprehensively profile the molecular landscape of HGG using multi-omics approaches.
- To identify master regulators and potential therapeutic vulnerabilities in HGG mouse models driven by RTK oncogenes.
Main Methods:
- Deep proteome, phosphoproteome, and transcriptome profiling using mass spectrometry.
- Systems biology analysis to identify master regulators (kinases, transcription factors).
- CRISPR-Cas9 screening for functional validation of identified targets.
Main Results:
- Identified 13,860 proteins and 30,431 phosphosites across two HGG models (PDGFRA and NTRK1 driven).
- NTRK1-driven HGG exhibited higher AKT pathway activation (MYC, JUN) and RTK feedback loops, conferring greater oncogenic potency.
- 56% of tested master regulators, including TFs (Myc, Jun) and kinases (AMPKa1, AMPKa2), were essential for NTRK-driven HGG cell viability.
Conclusions:
- Integrative multi-omics analysis successfully identified critical molecular players in HGG.
- NTRK1 mutations represent a more aggressive HGG subtype with distinct vulnerabilities.
- Identified master regulators, particularly TFs and metabolic kinases, represent promising therapeutic targets for HGG.
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