Thunder-DDA-PASEF enables the identification of mRNA splicing-derived immunopeptides in human tumor cell lines

Introduction:

Human leukocyte antigen (HLA, or MHC) peptide ligands, known as immunopeptides, play a crucial role in immune surveillance by triggering immune responses when presented epitopes are recognized by T-cells. This can be exploited to develop immunotherapies targeting immunogenic tumor-specific immunopeptides, termed neoepitopes originating from diverse sources. For instance, somatic mutations can result in single nucleotide variations (SNVs) or RNA processing changes. However, identifying neoepitope candidates by LC-MS is challenging due to the high diversity, large dynamic range, and individual-specificity of the immunopeptidome. To address these challenges, we profiled patient-matched melanoma and normal cell lines with our previously optimized LC-IMS-MS immunopeptidomics method, Thunder-DDA-PASEF. Additionally, we used our R-package splice2neo to detect splice junctions in tumor RNA-sequencing data.

Methods:

Cell pellets of patient-derived cell lines were lysed and HLA class I-peptide complexes were immunoaffinity-enriched using W6/32 anti-HLA-A, -B, -C antibody. Then, peptides were eluted (0.2% TFA), ultrafiltered (10 kDa cutoff), and desalted (HLB Oasis) before LC-MS-IMS analysis in a nanoElute coupled to timsTOF-Pro-2. Peptides were separated within a 47-minute gradient in an Aurora Ultimate RP column, and MS data was acquired using Thunder-DDA-PASEF. Peptides were identified employing PEAKS 11 Online with personalized protein databases including single-nucleotide variants (SNV) and splice junctions obtained by splice2neo.

Results:

LC-MS immunopeptidomics profiling resulted in 5,000 to 15,000 peptides per cell line. Tumor cells with lower HLA transcript expression also resulted in lower immunopeptidome coverage than the corresponding normal cells. Nevertheless, we still detected multiple tumor-specific immunopeptides derived from SNVs, constituting candidate neoepitopes. Furthermore, we identified several immunopeptides derived from RNA splicing as predicted from tumor RNA-seq.

Conclusions:

Thunder-DDA-PASEF provides high-coverage immunopeptidome profiling of cancer cells and enables the validation of neoepitope candidates from SNVs and immunopeptides derived from splice junctions detected in RNA-seq data using splice2neo. This workflow represents a promising strategy to identify tumor-specific targets for personalized cancer immunotherapies.