MuPeXI: prediction of neo-epitopes from tumor sequencing data

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 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 .

Keywords: Immunotherapy; Mutation; Neo-antigens; Neo-epitopes; Prediction; Sequencing.

Fig. 1

MuPeXI flow chart. Pre-processing: Raw sequencing data (WXS/WGS and RNA-seq) is analyzed, leading to variant calls (VCF file) and expression values. HLA alleles are determined, either from the NGS data or by other methods. a Effect: The first step of the MuPeXI algorithm is to determine the effect of the mutation on protein sequence using Ensembls Variant Effect Predictor (VEP). b Extraction: Peptides are extracted from mutated and normal proteome sequences and chopped up to the user-defined length. For in-frame mutations, amino acid changes are applied directly to the proteome reference. For frameshift mutations, nucleotide changes are applied to the cDNA reference and translated. c Similarity: To search for self-similarity, the entire proteome reference is chopped up (unless provided) into the user-defined lengths and searched for identical matches with the mutated peptides, which are penalized in the final peptide ranking. This peptide panel is also used to find the most similar normal peptide for peptides originating from indels and frameshifts. d MHC binding: Peptide binding affinities are determined by NetMHCpan 3.0 for both mutated and normal peptides. e Expression: if an expression file is provided the relevant expression value is given for the corresponding gene or the sum of the transcripts which contain the peptide. f Annotations: All relevant information for each mutated, normal peptide pair are annotated. g Ranking: Finally, the peptides are ranked according to the priority score

Fig. 2

MuPeXI and pVac-Seq performance comparison. The MuPeXI performance is plotted as a ROC curve based on the priority score. pVac-Seq performance is plotted as individual calculations of sensitivity and specificity according to various filtering combinations. The red triangle indicates pVac-Seq performance using default filtering criteria