The effects of p53 gene inactivation on mutant proteome expression in a human melanoma cell model.

Background: The identification of mutated proteins in human cancer cells-termed proteogenomics, requires several technologically independent research methodologies including DNA variant identification, RNA sequencing, and mass spectrometry. Any one of these methodologies are not optimized for identifying potential mutated proteins and any one output fails to cover completely a specific landscape. Methods: An isogenic melanoma cell with a p53-null genotype was created by CRISPR/CAS9 system to determine how p53 gene inactivation affects mutant proteome expression. A mutant peptide reference database was developed by comparing two distinct DNA and RNA variant detection platforms using these isogenic cells. Chemically fractionated tryptic peptides from lysates were processed using a TripleTOF 5600+ mass spectrometer and their spectra were identified against this mutant reference database. Results: Approximately 190 mutated peptides were enriched in wt-p53 cells, 187 mutant peptides were enriched in p53-null cells, with an overlap of 147 mutated peptides. STRING analysis highlighted that the wt-p53 cell line was enriched for mutant protein pathways such as CDC5L and POLR1B, whilst the p53-null cell line was enriched for mutated proteins comprising EGF/YES, Ubiquitination, and RPL26/5 nodes. Conclusion: Our study produces a well annotated p53-dependent and p53-independent mutant proteome of a common melanoma cell line model. Coupled to the application of an integrated DNA and RNA variant detection platform (CLCbio) and software for identification of proteins (ProteinPilot), this pipeline can be used to detect high confident mutant proteins in cells. General significance: This pipeline forms a blueprint for identifying mutated proteins in diseased cell systems.