title: In-silico discovery of cancer-specific peptide-HLA complexes for targeted therapy.
abstract: BACKGROUND
  Major Histocompatibility Complex (MHC) or Human Leukocyte Antigen (HLA) Class I molecules bind to peptide fragments of proteins degraded inside the cell and display them on the cell surface. We are interested in peptide-HLA complexes involving peptides that are derived from proteins specifically expressed in cancer cells. Such complexes have been shown to provide an effective means of precisely targeting cancer cells by engineered T-cells and antibodies, which would be an improvement over current chemotherapeutic agents that indiscriminately kill proliferating cells. An important concern with the targeting of peptide-HLA complexes is off-target toxicity that could occur due to the presence of complexes similar to the target complex in cells from essential, normal tissues.
  
  
  RESULTS
  We developed a novel computational strategy for identifying potential peptide-HLA cancer targets and evaluating the likelihood of off-target toxicity associated with these targets. Our strategy combines sequence-based and structure-based approaches in a unique way to predict potential off-targets. The focus of our work is on the complexes involving the most frequent HLA class I allele HLA-A*02:01. Using our strategy, we predicted the off-target toxicity observed in past clinical trials. We employed it to perform a first-ever comprehensive exploration of the human peptidome to identify cancer-specific targets utilizing gene expression data from TCGA (The Cancer Genome Atlas) and GTEx (Gene Tissue Expression), and structural data from PDB (Protein Data Bank). We have thus identified a list of 627 peptide-HLA complexes across various TCGA cancer types.
  
  
  CONCLUSIONS
  Peptide-HLA complexes identified using our novel strategy could enable discovery of cancer-specific targets for engineered T-cells or antibody based therapy with minimal off-target toxicity.
authors.affiliation: Regeneron Pharmaceuticals Inc, Old Saw Mill River Road, Tarrytown, NY, USA. ankur.dhanik@regeneron.com.
authors.forename: Ankur
authors.initials: A
authors.lastname: Dhanik
authors.affiliation: Regeneron Pharmaceuticals Inc, Old Saw Mill River Road, Tarrytown, NY, USA.
authors.forename: Jessica R
authors.initials: JR
authors.lastname: Kirshner
authors.affiliation: Regeneron Pharmaceuticals Inc, Old Saw Mill River Road, Tarrytown, NY, USA.
authors.forename: Douglas
authors.initials: D
authors.lastname: MacDonald
authors.affiliation: Regeneron Pharmaceuticals Inc, Old Saw Mill River Road, Tarrytown, NY, USA.
authors.forename: Gavin
authors.initials: G
authors.lastname: Thurston
authors.affiliation: Regeneron Pharmaceuticals Inc, Old Saw Mill River Road, Tarrytown, NY, USA.
authors.forename: Hsin C
authors.initials: HC
authors.lastname: Lin
authors.affiliation: Regeneron Pharmaceuticals Inc, Old Saw Mill River Road, Tarrytown, NY, USA.
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Murphy
authors.affiliation: Regeneron Pharmaceuticals Inc, Old Saw Mill River Road, Tarrytown, NY, USA.
authors.forename: Wen
authors.initials: W
authors.lastname: Zhang
mesh_terms: D000906:Antibodies / Q000276:immunology; D003198:Computer Simulation; D015395:Histocompatibility Antigens Class I / Q000378:metabolism*; D006801:Humans; D008285:Major Histocompatibility Complex; D058990:Molecular Targeted Therapy; D009369:Neoplasms / Q000145:classification / Q000276:immunology / Q000628:therapy*; D010455:Peptides / Q000276:immunology / Q000378:metabolism*; D013601:T-Lymphocytes / Q000276:immunology
chemical_list: D000906:Antibodies; D015395:Histocompatibility Antigens Class I; D010455:Peptides
keywords: Bioinformatics; Cancer; GTEx; Immunoinformatics; Peptide-HLA; TCGA; Targeted therapy