Deep multiomics profiling of brain tumors identifies signaling networks downstream of cancer driver genes.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 31420543.
- Also identified by DOI 10.1038/s41467-019-11661-4 and PMC identifier 6697699.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
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.
Medical subject headings
- Brain Neoplasms
- Gene Expression Profiling
- Glioma
- Proteomics