MuPeXI: prediction of neo-epitopes from tumor sequencing data.
Bjerregaard, A. M., Nielsen, M., Hadrup, S. R., Szallasi, Z. and Eklund, A. C.
Department of Bio and Health Informatics, Technical University of Denmark, Kemitorvet 208, 2800, Lyngby, Denmark. ambj@cbs.dtu.dk.
Department of Bio and Health Informatics, Technical University of Denmark, Kemitorvet 208, 2800, Lyngby, Denmark.
Instituto de Investigaciones Biotecnologicas, Universidad Nacional de San Martin, Buenos Aires, Argentina.
Section for Immunology and Vaccinology, National Veterinary Institute, Technical University of Denmark, Copenhagen, Denmark.
Computational Health Informatics Program, Boston Children's Hospital, USA, Harvard Medical School, Boston, USA.
Department of Bio and Health Informatics, Technical University of Denmark, Kemitorvet 208, 2800, Lyngby, Denmark. eklund@cbs.dtu.dk.
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 tumors for which predicted MHC-binding peptides had been screened for T cell reactivity, and found that MuPeXI was able to prioritize immunogenic peptides with an area under the curve of 0.63. Compared to other available tools, MuPeXI provides more information and is easier to use. MuPeXI is available as stand-alone software and as a web server at http://www.cbs.dtu.dk/services/MuPeXI .
Cancer Immunology, Immunotherapy : en prensa (2017)