Combined Proteomic and Genetic Interaction Mapping Reveals New RAS Effector Pathways and Susceptibilities

Abstract

Activating mutations in RAS GTPases drive many cancers, but limited understanding of less-studied RAS interactors, and of the specifi c roles of different RAS interactor paralogs, continues to limit target discovery. We developed a multistage discovery and screening process to systematically identify genes conferring RAS-related susceptibilities in lung adenocarcinoma. Using affi nity purifi cation mass spectrometry, we generated a protein-protein interaction map of RAS interactors and pathway components containing hundreds of interactions. From this network, we constructed a CRISPR dual knockout library targeting 119 RAS-related genes that we screened for KRAS -dependent genetic interactions (GI). This approach identifi ed new RAS effectors, including the adhesion controller RADIL and the endocytosis regulator RIN1, and >250 synthetic lethal GIs, including a potent KRAS -dependent interaction between RAP1GDS1 and RHOA. Many GIs link specifi c paralogs within and between gene families. These fi ndings illustrate the power of multiomic approaches to uncover synthetic lethal combinations specifi c for hitherto untreatable cancer genotypes. SIGNIFICANCE:We establish a deep network of protein-protein and genetic interactions in the RAS pathway. Many interactions validated here demonstrate important specifi cities and redundancies among paralogous RAS regulators and effectors. By comparing synthetic lethal interactions across KRAS -dependent and KRAS -independent cell lines, we identify several new combination therapy targets for RAS-driven cancers.

The Ins and Outs of RAS Effector Complexes

“…Expanding the proximal RAS interactomes to also map components further downstream identified a network of interconnected G-proteins in lung cancer cells [151]. In this study, the authors used GDP and GTP locked GST-fusion proteins of HRAS, KRAS and NRAS to identify interactors in cell extracts.…”

Functional interrogation of a SARS-CoV-2 host protein interactome identifies unique and shared coronavirus host factors

“…CRISPR-Cas9 forward genetics and data from IP-MS studies can be combined in a high-coverage hypothesis-driven single guide RNA (sgRNA) screening campaign ( Kelly et al., 2020 ). Focused libraries offer several advantages: (1) increased coverage (smaller libraries allow interrogation of many sgRNAs per gene, thereby lowering the rate of false negatives), (2) increased resolution (smaller libraries ensure higher screen representation at every point of the screen), and (3) a wider range of screening conditions (smaller libraries are more compatible with highly parallel testing of multiple technical and biological conditions) ( DeWeirdt et al., 2020 ; Doench, 2018 ; Parnas et al., 2015 ).…”

Multiplexed identification of RAS paralog imbalance as a driver of lung cancer growth

“…Oncogenic KRAS represents a key node downstream of growth factor-induced signaling, and oncogenic KRAS is sufficient to initiate tumor growth in several different tissues (20,21). Genetic and proteomic mapping have revealed that KRAS interacts with a large network of proteins outside of its canonical effectors and regulators (14,15). To identify putative KRAS-interacting proteins that could affect oncogenic KRAS-driven lung tumor growth in vivo , we integrated proteomics data from AP/MS studies with gene expression data from cancer cells from autochthonous mouse models ( Figure 1a ) .…”