MassIVE MSV000097797

Partial Public PXD063604

Illuminating oncogenic KRAS signaling by multi-dimensional proteomics

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Description

Mutated KRAS is among the most frequent activating genetic alterations in cancer and drug discovery efforts have led to inhibitors that block its activity. To better understand oncogenic KRAS signaling and the cytostatic effects of drugs that target this system, we performed comprehensive dose-dependent proteome-wide target deconvolution, pathway engagement and protein expression characterization of KRAS, MEK, ERK, SHP2 and SOS1 inhibitors in pancreatic (KRAS G12C, G12D) and lung cancer (KRAS G12C) cells. Analysis of the resulting 715,239 dose-response curves available online established that KRAS inhibitors are very selective. In addition, cross-cell comparisons of phosphoproteomes revealed a core KRAS signaling signature as well as cell line-specific signaling networks. In all cell lines phosphoproteomes were dominated by different degrees of autonomous oncogenic KRAS activity. Comparing the phosphoproteomes of short and long drug exposures allowed the distinction of early KRAS-MEK-ERK signaling from the consequences of cells exiting the cell cycle. This transition to a quiescent state occurred in the absence of substantial proteome re-modelling but broad changes of protein phosphorylation and ubiquitylation. The transition also included the participation of ubiquitylation -mediated inhibition of E1 ubiquitin activating and E2 ubiquitin conjugating enzymes. The collective data provides new views on KRAS signaling, highlights the molecular complexity of this system in cancer, places a large number of new proteins into this functional context and offer a general mechanism of how cancer cells escape death from signaling inhibitors. [doi:10.25345/C5QB9VJ4B] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: KRAS ; Phosphoprotemics ; Ubiquitinome ; Cancer ; PTM ; DatasetType:Proteomics

Contact

Principal Investigators:
(in alphabetical order) 		Bernhard Kuster, Chair of Proteomics and Bioanalytics, Technical University of Munich, Germany
Submitting User: Nkabella
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