Deciphering the MHC-I/II Immunopeptidome landscape of murine tumor with normal tissues for neoantigen discovery

The Major Histocompatibility Complex (MHC) displays numerous peptides on the surface of cells, particularly neoplastic cells. These MHC-associated peptides are crucial not only for functional research on adaptive immunity but also for defining neoantigens that can be harnessed for cancer immunotherapy through vaccines or cell therapies. Mass Spectrometry (MS) has emerged as a powerful tool for identifying MHC-presented peptides (MIPs) from tumor cells, offering a direct method to detect peptides exactly presented by MHC molecules, a capability that is distinct from Next-Generation Sequencing (NGS).

Despite the advantages of MS, there have been relatively few reports on the direct identification of neoantigens just by MS. We have developed a highly sensitive and reproducible immune-precipitation procedure that enables the direct identification of neoantigens through MS denovo sequencing algorithm—DeepNovo.

Considering the widespread prevalence of cancer types, we designed an experiment involving seven tumor cell lines implanted into C57/Bl6 mice, including MC-38, Hepa 1-6, LLC1, B16-F10, Panc02, MFC, and Renca. The subcutaneous tumor tissues were subjected to immunoprecipitation to capture MHCI/II-associated peptides to discover neoantigens using an in-house developed integrated platform named DeepImmu.2000-10000 MHC I binders have been identified from these tumor/benign tissues. And 60 neoantigens were selected from around 10000 of the CRC tumor tissues according to the immunogenicity prediction by DeepSelf. 12 peptide pools were generated by 60 synthetic peptides to assess their immunogenicity by Elispot assay. 4 out of 12 peptide pools were confirmed to be positive for immunogenicity.

In summary, the discovery of neoantigens can be achieved solely by MS data, relying on accurate peptide denovo-sequencing. This method has the potential to significantly accelerate the neoantigen discovery process in less than one week, indicating promising clinical applications. Using DeepImmu Platform, we also constructed a landscape of a pan-tissue immunopeptidomics library from both tumor and benign tissues, which could be a good resource for future neoantigen discovery.