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Updated: Dec 10, 2025
Yeast As a Chassis for Developing Functional Assays to Study Human P53
Published on: August 4, 2019
The effects of p53 gene inactivation on mutant proteome expression in a human melanoma cell model
Jakub Faktor1, Giuseppa Grasso2, Filip Zavadil Kokas1
1Research Centre for Applied Molecular Oncology (RECAMO), Masaryk Memorial Cancer Institute, 656 53 Brno, Czech Republic.
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.
Insights
This study developed a proteogenomic pipeline to identify mutated proteins in cancer cells, revealing p53-dependent and independent pathways in melanoma. This method enhances the detection of high-confidence mutant proteins for cancer research.
Area of Science:
- Oncology
- Proteomics
- Genomics
Background:
- Proteogenomics, the identification of mutated proteins in human cancer cells, relies on multiple independent technologies like DNA variant identification, RNA sequencing, and mass spectrometry.
- Each methodology has limitations, and no single approach completely captures the landscape of potential mutated proteins.
Purpose of the Study:
- To investigate the impact of p53 gene inactivation on mutant proteome expression in melanoma.
- To establish a robust pipeline for identifying high-confidence mutated proteins in cancer cells.
Main Methods:
- Created an isogenic melanoma cell line with a p53-null genotype using CRISPR/Cas9.
- Developed a mutant peptide reference database by integrating DNA and RNA variant data from two detection platforms.
- Utilized mass spectrometry (TripleTOF 5600+) for peptide identification against the curated database.
Main Results:
- Identified approximately 190 mutated peptides in wild-type p53 cells and 187 in p53-null cells, with 147 common mutated peptides.
- STRING analysis revealed distinct enriched mutant protein pathways, including CDC5L and POLR1B in wt-p53 cells, and EGF/YES, Ubiquitination, and RPL26/5 nodes in p53-null cells.
Conclusions:
- Generated a well-annotated p53-dependent and p53-independent mutant proteome for a melanoma cell line model.
- The integrated DNA/RNA variant detection and protein identification pipeline enables high-confidence detection of mutant proteins.
- This pipeline serves as a foundational blueprint for identifying mutated proteins in various diseased cell systems.
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