Fig 2: Quantitative analysis of ERK phosphorylation in response to RAS mutation ASchematic of a model of the internal factors of the RAS‐ERK pathway, showing parameters associated with each reaction. Shaded regions indicate portions of the model for which parameter values are available from either (yellow) published biochemical assays or (blue) our immunoblot expression data (B–D).BImmunoblot measurement of RAS‐ERK pathway components in each cell line, at baseline (green circles), peak activity (15 min, red triangles), and steady‐state activity (2 h, blue diamonds), four replicates each. Overlaid plots indicate the median (horizontal bars) and 25th–75th percentiles (vertical whiskers) over all conditions. Asterisks indicate statistical significance from the KRASWT cell line, by t‐test (pFDR < 0.05).C, DPhos‐Tag immunoblot measurement of ERK fractional phosphorylation (C) and the relative concentration of dually‐phosphorylated ERK (D), annotated as in (B), but with median and percentile ranges indicated per treatment condition, for 4 replicate cultures. Sample blot imagery shows anti‐ERK1/2 (below C) and anti‐ppERK1/2 (below D) for the same blot replicate. Asterisks indicate significance by t‐test (pFDR < 0.05) from the KRASWT cell line measurement for each condition.E, FComparison of the internal RAS‐ERK model to experimental data. (E) Relative ppERK as predicted by the internal model and measured by immunoblot for the 4 replicates collected, showing the median of the baseline and steady state after EGF treatment (E), and the amplitude of stimulation (F). Error bars show 25th–75th percentiles.G, HPartial least squares regression of both experimental ppERK measurements and predictions via the simple RAS‐ERK model. Regression was based on presence/absence of EGF, and expression levels of RAS, BRAF, CRAF, MEK, and ERK. (G) Percent of variance explained by each PLS model considered, based on how many component terms are allowed. Stim only refers to a PLS model using experimental ppERK data, but only predicting based on the presence/absence of EGF. (H) Weights assigned to each parameter in the PLS models. Gray shaded regions indicate the bounds of statistical significance, determined via bootstrapping with scrambled data. Only values that extend beyond the gray regions are statistically significant from zero (P < 0.05). Source data are available online for this figure.

Fig 3: Inhibition of PLK1 reduces colorectal cancer cell growth by targeting the CRAF-MEK-ERK signaling pathway. (A) Overexpression of PLK1 increases clonogenicity. The PLK1 overexpressing clones of CRC cells were subjected to clonogenicity assay (n = 3). (B) Forced expression of PLK1 activates CRAF-MEK-ERK signaling pathway. The proteins from the PLK1-overexpressing clones were analyzed using immunoblotting. (C,D) Knockdown of PLK1 decreases clonogenicity. CRC cells were transfected with two different shRNA sequences targeting PLK1, and the PLK1 stable knockdown clones of CRC cells were subjected to clonogenicity assay (n = 3). (E) Knockdown of PLK1 leads to a decrease in the phosphorylation levels of CRAF, MEK1/2, and ERK1/2 proteins. * statistically significant in comparison to the control group, with p < 0.05.

Fig 4: Melanomagenic NRAS mutants enhance RAF dimerization.a Schematic representation of the RAF NanoBiT assay in which each RAF isoform is tagged with either LgBiT or SmBiT. Dot plots of normalized luminescence intensity in TN61X/X MEFs infected with adenovirus expressing BRAF-LgBiT and BRAF-SmBiT (b), BRAF-LgBiT and Craf-SmBiT (c), CRAF-LgBiT and CRAF-SmBiT (d), ARAF-LgBiT and BRAF-SmBiT (e), ARAF-LgBiT and ARAF-SmBiT (f), or ARAF-LgBiT and CRAF-SmBiT (g). Luminescence intensity was normalized to crystal violet staining for each well. Dot plot data are presented as mean values +/− SD where each dot represents one biological replicate. The following biologically independent replicates per genotype were examined over five independent experiments (BRAF-BRAF: Q/Q = 5, R/R = 5, H/H = 4; P/P = 4; BRAF-CRAF: Q/Q = 5, R/R = 5, H/H = 4; P/P = 5; CRAF-CRAF: Q/Q = 5, R/R = 5, H/H = 4; P/P = 4; BRAF-ARAF: Q/Q = 4, R/R = 4, H/H = 4; P/P = 4; ARAF-ARAF: Q/Q = 4, R/R = 4, H/H = 4; P/P = 4; ARAF-CRAF: Q/Q = 4, R/R = 4, H/H = 4; P/P = 4). One-way ANOVA with a Tukey’s post-test was used to compare data between each genotype. NRAS mutant samples statistically different from NRAS61R/R samples are indicated in the figure. Adjusted p-values for all comparisons can be found in Supplementary Table 4d. * p < 0.05, ** p < 0.01, † p < 0.001, ‡ p < 0.0001. Source data are provided as a Source Data file.

Fig 5: Oncogenic NRAS mutants mediate differential MAPK activation via a RAF-dependent mechanism.Representative immunoblots of AKT and ERK activation in homozygous MEF cell lines treated with shRNAs targeting Nras, Hras and Kras, or Sos1 (a) or Araf, Braf or Craf (b). Dot plot data are presented as mean values +/− SD where each dot represents one biological replicate. For a the following biologically independent replicates per genotype were examined over five independent experiments (eGFP arm: Q = 5, P = 5, R = 5; NRAS arm: Q = 3, P = 3, R = 3; H/KRAS arm: Q = 3, P = 4, R = 3; SOS1 arm: Q = 5, P = 5, R = 5). For b the following biologically independent replicates per genotype were examined over 8 independent experiments (eGFP arm: Q = 8, P = 8, R = 8; ARAF arm: Q = 6, P = 6, R = 6; BRAF arm: Q = 7, P = 7, R = 6; CRAF arm: Q = 7, P = 7, R = 6). Adjusted p-values were generated using a one-way ANOVA with a Tukey’s multiple comparisons test. Statistics denoted in the figure indicate significant differences between shRNA-treated NRAS mutant MEFs and their respective eGFP control. ** p < 0.01, † p < 0.001. A complete list of adjusted p-values can be found in Supplementary Table 4a, b. Source data are provided as a Source Data file.