{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Bjerregaard AM"],"funding":["Breast Cancer Research Foundation","Novo Nordisk","Kræftens Bekæmpelse","Det Frie Forskningsråd"],"pagination":["1123-1130"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11028452"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["66(9)"],"pubmed_abstract":["Personalization of immunotherapies such as cancer vaccines and adoptive T cell therapy depends on identification of patient-specific neo-epitopes that can be specifically targeted. MuPeXI, the mutant peptide extractor and informer, is a program to identify tumor-specific peptides and assess their potential to be neo-epitopes. The program input is a file with somatic mutation calls, a list of HLA types, and optionally a gene expression profile. The output is a table with all tumor-specific peptides derived from nucleotide substitutions, insertions, and deletions, along with comprehensive annotation, including HLA binding and similarity to normal peptides. The peptides are sorted according to a priority score which is intended to roughly predict immunogenicity. We applied MuPeXI to three tum"],"journal":["Cancer immunology, immunotherapy : CII"],"pubmed_title":["MuPeXI: prediction of neo-epitopes from tumor sequencing data."],"pmcid":["PMC11028452"],"funding_grant_id":["R72-A4618","1331-00283","16854"],"pubmed_authors":["Szallasi Z","Hadrup SR","Bjerregaard AM","Nielsen M","Eklund AC"],"additional_accession":[]},"is_claimable":false,"name":"MuPeXI: prediction of neo-epitopes from tumor sequencing data.","description":"Personalization of immunotherapies such as cancer vaccines and adoptive T cell therapy depends on identification of patient-specific neo-epitopes that can be specifically targeted. MuPeXI, the mutant peptide extractor and informer, is a program to identify tumor-specific peptides and assess their potential to be neo-epitopes. The program input is a file with somatic mutation calls, a list of HLA types, and optionally a gene expression profile. The output is a table with all tumor-specific peptides derived from nucleotide substitutions, insertions, and deletions, along with comprehensive annotation, including HLA binding and similarity to normal peptides. The peptides are sorted according to a priority score which is intended to roughly predict immunogenicity. We applied MuPeXI to three tum","dates":{"release":"2017-01-01T00:00:00Z","publication":"2017 Sep","modification":"2025-04-22T20:43:34.939Z","creation":"2025-04-06T03:14:49.999Z"},"accession":"S-EPMC11028452","cross_references":{"pubmed":["28429069"],"doi":["10.1007/s00262-017-2001-3"]}}