Proteogenomics and de novo sequencing based approach for neoantigen discovery from the immunopeptidomes of patient CRC liver metastases using Mass Spectrometry

Abstract

Abstract Introduction Using High-resolution Mass Spectrometry (MS), we developed a novel immunopeptidomics workflow using de novo sequencing. This method does not rely on a reference database to deduce full-length peptide sequences. As a consequence, peptide discovery is not limited to the reference database and allows for the discovery of novel peptides directly from MS. Goal Identify HLA-associated peptides that appear in high frequency in tumors through de novo sequencing and missed by reference database searches. Method We employed a highly selective anti-HLA Class I monoclonal antibody, W6/32, to enrich HLA-complexes from 21 CRC liver metastases and identified HLA associated peptides using a Thermo Orbitrap Fusion Lumos on-line with a nanoLC 1200. RNA-Seq was also performed on each tumor. MS raw spectra were analyzed by de novo assisted PEAKS-X (BSI) Results Approximately 1600 unique de novo sequenced HLA-associated peptides were identified in a single LC-MS analysis with high confidence (95% ALC cut-off) from each tumor. Approximately 45% of the 1600 unique de novo sequenced peptides matched to reference databases (e.g Uniprot.), leaving a large percentage of peptides with no match. Interestingly, some of these unmatched peptides have been validated as neoantigens that arise from gene mutation, spliced peptides generated by the proteasomes, and non-coding region derived peptides. Conclusion These de novo sequenced peptides without matches in reference databases may provide a unique source of disease-specific HLA class I-presented peptides and trigger specific immune responses. Some of the higher frequency unmatched de novo sequenced peptides may thus serve as tumor-specific targets for next-generation immunotherapies.