The Immunopeptidome from a Genomic Perspective: Establishing the Noncanonical Landscape of MHC Class I–Associated Peptides

Abstract

Tumor antigens can emerge through multiple mechanisms, including translation of non-coding genomic regions. This non-canonical category of antigens has recently gained attention; however, our understanding of how they recur within and between cancer types is still in its infancy. Therefore, we developed a proteogenomic pipeline based on deep learning de novo mass spectrometry to enable the discovery of non-canonical MHC-associated peptides (ncMAPs) from non-coding regions. Considering that the emergence of tumor antigens can also involve post-translational modifications, we included an open search component in our pipeline. Leveraging the wealth of mass spectrometry-based immunopeptidomics, we analyzed 26 MHC class I immunopeptidomic studies of 9 different cancer types. We validated the de novo identified ncMAPs, along with the most abundant post-translational modifications, using spectral matching and controlled their false discovery rate (FDR) to 1%. Interestingly, the non-canonical presentation appeared to be 5 times enriched for the A03 HLA supertype, with a projected population coverage of 54.85%. Here, we reveal an atlas of 8,601 ncMAPs with varying levels of cancer selectivity and suggest 17 cancer-selective ncMAPs as attractive targets according to a stringent cutoff. In summary, the combination of the open-source pipeline and the atlas of ncMAPs reported herein could facilitate the identification and screening of ncMAPs as targeting agents for T-cell therapies or vaccine development.

Expanding the repertoire reveals recurrent, cryptic, and hematopoietic HLA class I minor histocompatibility antigens

“… 80 Despite this limitation, reverse strategies estimated that up to 7.5% of HLA-I–associated peptides are noncanonical peptides. 77 , 78 , 79 In contrast, we found a higher proportion of 23.3% cryptic MiHAs. Because peptides from cryptic ORFs are similar in peptide length, predicted binding, or hydrophobicity to peptides from canonical ORFs, 77 , 78 , 79 no difference in immunogenicity is expected.…”

“… 77 , 78 , 79 In contrast, we found a higher proportion of 23.3% cryptic MiHAs. Because peptides from cryptic ORFs are similar in peptide length, predicted binding, or hydrophobicity to peptides from canonical ORFs, 77 , 78 , 79 no difference in immunogenicity is expected. We, therefore, speculate that for a proportion of cryptic MiHAs, surface expression of the peptide is sufficient for T-cell recognition, but below the detection limit of mass spectrometry.…”

“…Typically, only nonsynonymous variants leading to AA changes in normal reading frames are included. 69 , 70 , 71 , 72 , 73 To enable identification of cryptic antigens, reference databases need to be enlarged by alternative and long noncoding transcripts and translation of transcripts in all ORFs, 65 , 74 , 75 , 76 , 77 , 78 , 79 which may generate false positives in immunopeptidomics. 80 Despite this limitation, reverse strategies estimated that up to 7.5% of HLA-I–associated peptides are noncanonical peptides.…”