Mutant p53 gain-of-function impact is repressed in the presence of other major oncogenic drivers
Mutant TP53, mutant KRAS and hyperactive CMYC are driver oncogenes with no standard clinical protocols for their direct targeting. To identify interplay of mutant TP53, KRAS and hyperactive CMYC, and exploit them in a therapeutic manner, we performed global proteomics and transcriptomics in a panel of 8 cell lines of colorectal and lung cancers 48h post knock-out of the oncogenes with CRISPR/Cas9. In each cancer type the cell lines containing either all, or one, of each of the activated oncogenes were analyzed. Higher numbers of significant protein and transcript level changes were observed upon CMYC and KRAS disruption compared to mutant TP53 disruption. In contrast to mutant KRAS and CMYC downstream programs the number of mutant p53-dependent proteins and transcripts was reduced several-fold in the presence of mutant KRAS and hyperactive CMYC, compared to cell lines with mutant p53 only. We observed a functional repression of the mutant p53 ability to drive phenotype of cancer cells and transcriptional activity in the presence of mutated KRAS and/or overexpressed CMYC, which in such configuration overtake many of the mutant p53 functions. An overlap of pathways regulated by the transcripts and proteins revealed a molecular program shared by the oncogenes as well as pathways lost or retained in the mutant p53 program, when co-present with the other oncogenes. This allowed to exploit the program common to the oncogenes by experimental, pre-clinical drug targeting.   Oncogene cooperation is known to be important in driving cell transformation, however our observations suggest that mutant KRAS and/or overexpressed CMYC compete with mutant p53 for activation of important oncogenic pathways. While the exact mechanism of this competition is under investigation, we hypothesize that mutant p53 is a context-dependent oncogene – whose gain-of-function range of impact heavily depends on the molecular background of neoplastic cells. Overall design: Cell lines indicated in the file names were 48h post knock-out of the oncogenes with CRISPR/Cas9 techniques in biological triplicates (numbers 1-3). Total RNA was extracted from cells and subjected to mRNA sequencing. We then performed gene expression profiling analysis using data obtained from RNA-seq of lung, colon and pancreatic cancer cell lines.