Fig. 1: CRISPR knockout screen in Ba/F3 lines identifies specific RAS-mutant dependencies.
From: Targeting the SHOC2–RAS interaction in RAS-mutant cancers
a, Schematic describing the Ba/F3 model of oncogene addiction. Ba/F3 relies on IL-3–JAK–STAT signalling for survival unless engineered to express oncogenes such as RAS. Mut, mutation. b, Effect on cell viability for the indicated Ba/F3 isogenic models after treatment for 72 h with the KRAS(G12C) inhibitor adagrasib or the KRAS(G12D) inhibitor MRTX1133. DMSO, dimethyl sulfoxide. c, Genetic screen diagram: Ba/F3 stably engineered to co-express Cas9 and different NRAS and KRAS mutants were transduced with a mouse genome-wide sgRNA library, antibiotic selected, expanded and subjected to genomic DNA isolation and next-generation sequencing (NGS) analysis to identify sensitizer and rescuer genes. d, PCA bi-plot representing PC1 (x axis) and PC2 (y axis) from the 250 most variable genes in the screen. Coloured dots represent PCA scores for each condition. Arrows represent loadings for genes driving the PCA distribution, coloured according to the contribution to the eigenvectors. Selected genes are highlighted with a black dot. e, Scatter plot representing hits from differential representation analysis between screens in Q61 lines and G12 lines. The x axis represents scoring and the y axis represents statistics (see the ‘CRISPR screen analysis’ section in the Methods). Non-significant genes (absolute Q < 2 and RSA > –2) are represented as a density plot to avoid overplotting. f, Dot–plot representing screening results of selected hits. Colours represent Q scoring and dot sizes represent statistical significance (RSA). g, Schematic illustrating the RAS signalling cellular context for the indicated RAS G12 and Q61 hits. h, Effect on cell viability for the indicated Ba/F3 isogenic models following 72 h treatment with inhibitors for SHP2, SOS1 and IGFR. The dotted lines indicate 50% of growth inhibition. i, Effect on cell viability of the indicated Ba/F3 isogenic models following transduction with sgRNAs against SHOC2, sgSHOC2 or non-targeting sgNT. Data in b, h and i are mean ± s.d. of n = 3 biologically independent samples. Images in a, c and g created using BioRender (Galli, G., 2025): a, https://BioRender.com/c48w611; c, https://BioRender.com/m41c915; g, https://BioRender.com/q07k743.
