{
  "abstract": "Background Identifying and prioritizing neoantigenic, immuno-targetable peptides from cancer patient tissue are crucial for advancing personalized cancer immunotherapies. Currently, next generation sequencing (NGS) of tumor tissue and prioritization software are used to identify candidate neoantigens that harbor mutations in coding exons and confirm transcriptional expression for immuno-targeting with cancer vaccines. However, genomic methods cannot provide definitive peptide expression nor identify peptides untraceable to a genomic origin. Directly identifying and prioritizing neoantigenic peptides in clinical patient tissue enables definitive identification of a broader spectrum of neoantigenic peptides potentially leading to significant advancements in cancer immunotherapy.Methods A novel, proprietary mass spectrometry-based proteomic platform was developed, using a GBM CT2A mouse tumor model, to identify neoantigenic peptides directly from formalin fixed paraffin embedded (FFPE) tumor tissue. Proteomic analysis of cellular lysates prepared from formalin fixed CT2A cell line preparations and CT2A xenograft FFPE tumor tissue was first performed and candidate neoantigen peptides were identified using the netMHCpan4.1 webserver. Subsequently, genomic lysates from multiple colon cancer patient tissues were analyzed by NGS for DNA mutations and total RNA transcription expression and by mass spectrometry to search for candidate neoantigenic peptides using the netMHCpan4.1 webserver for prioritization. Bioinformatics analysis was performed on both genomic and proteomic datasets.Results Proteomic analysis of formalin fixed samples from the GBM CT2A mouse tumor model system demonstrates a novel platform that routinely identified >2000 peptides from each FFPE xenograft tumor tissue preparation. Peptides demonstrating strong MHC binding prediction (8-12 amino acids in length) were identified and characterized as canonical neoantigens because they harbor exon coding mutations or derive from the integrated cytomegalovirus, or are characterized as noncanonical peptides because they are of untraceable genomic origin and likely derive from ncORFs, dysregulated proteasome splicing, and/or dysregulated RNA splicing. Similarly, multiple canonical and noncanonical candidate cancer neoantigens have been identified across each colon cancer patient tissue and bioinformatics efforts are underway to evaluate and contrast individual datasets and combined datasets.Conclusions A novel, proprietary platform for identification of cancer neoantigen peptides directly from FFPE cancer patient tissue was developed. The platform can advance personal vaccine therapeutics by validating suspected canonical neoantigens and by identifying additional noncanonical immunotherapy targets. Beyond producing a broader spectrum of neoantigenic targets, the platform may extend clinical benefit to patients with low tumor mutational burden by virtue of uniquely identifying additional immunotherapy targets not accessible by current genomic methods.",
  "authors": [
    {
      "affiliations": [
        "InAntigen Therapeutics, Gaithersburg, MD, USA"
      ],
      "name": "David Krizman"
    },
    {
      "affiliations": [
        "InAntigen Therapeutics, Gaithersburg, MD, USA"
      ],
      "name": "Marlene Darfler"
    }
  ],
  "title": "121 Unlocking the antigenic proteome in clinical cancer tissue to enable personalized cancer immunotherapy",
  "uid": "2f868a9d-1c51-59a1-8869-7da40c7bea52"
}