Sensitive detection of cancer antigens enabled by user-defined peptide libraries

Area of Science:

• Immunology
• Proteomics
• Biotechnology

Background:

• Human leukocyte antigen (HLA)-bound tumor peptides are crucial for cancer immunology and immunotherapy.
• Current mass spectrometry (MS) methods for peptide identification are limited by stochasticity and lack of individual-specific spectral libraries, hindering novel peptide discovery.

Purpose of the Study:

• To introduce Pepyrus, a novel system for generating user-defined, individual-specific or disease-specific peptide libraries in Escherichia coli.
• To enhance the sensitivity and confidence of MS-based peptide identification, particularly for low-abundance neoantigens.

Main Methods:

• Pepyrus generates peptide libraries in E. coli for MS analysis.
• Libraries were used with an HLA-specific data-independent acquisition strategy for peptide identification.
• Application to cell lines from melanoma and renal cell carcinoma patients.

Main Results:

• Achieved >75% recovery of expected sequences per injection for libraries exceeding 10,000 peptides.
• Identified 0.1 fmol of spiked-in peptides within a complex background.
• Facilitated identification of clinically relevant HLA peptides, including novel ones, from cancer cell lines.

Conclusions:

• Pepyrus significantly improves the identification of rare HLA-bound peptides, including neoantigens.
• Enables the creation of personalized peptide libraries for enhanced cancer diagnostics and research.
• Provides large datasets for improving MS data analysis tools, such as spectral, retention time, and ion mobility prediction.