COSMIC-based mutation database enhances identification efficiency of HLA-I immunopeptidome

Area of Science:

• Immunology
• Genomics
• Proteomics

Background:

• Neoantigens are crucial targets in tumor immunotherapy.
• Human Leukocyte Antigen class I (HLA-I) molecules present immunopeptides for T-cell recognition.
• Whole exome sequencing (WES) based mutation databases have limitations in identifying all potential neoantigens.

Purpose of the Study:

• To evaluate an extended mutation database for enhanced neoantigen identification.
• To compare the efficacy of a COSMIC-based database against a WES-based database for identifying HLA-I immunopeptides.
• To validate the potential of identified mutant peptides as neoantigens.

Main Methods:

• Proteogenomic profiling using mass spectrometry to analyze the HLA-I immunopeptidome.
• Construction of HepG2 WES-based and COSMIC-based mutation databases.
• Identification of HepG2-specific mutant immunopeptides using both databases.
• Evaluation of HLA-I binding affinity using NetMHCpan and peptide-docking modeling.

Main Results:

• The COSMIC-based database identified 5 mutant immunopeptides, while the HepG2 WES-based database identified only 1.
• The identified mutant peptides demonstrated potential as neoantigens through HLA-I affinity validation.
• The COSMIC-based approach proved more effective in uncovering mutant peptides.

Conclusions:

• An extended COSMIC mutation database is a more efficient strategy for identifying mutant peptides from HLA-I immunopeptidomes.
• WES-based databases may miss potential neoantigens due to sequencing depth or sample quality.
• The COSMIC-based database effectively uncovers potential neoantigens within HLA-I immunopeptidomes, advancing cancer immunotherapy.