MHCquant: Automated and reproducible data analysis for immunopeptidomics

ABSTRACT: Personalized multi-peptide vaccines are currently being discussed intensively for tumor immunotherapy. In order to find epitopes - short, immunogenic peptides - suitable to elicit an immune response, human leukocyte antigen-presented peptides from cancer tissue samples are purified using immunoaffinity purification and analyzed by high performance liquid chromatography coupled to mass spectrometry. Here we report on a novel computational pipeline to identify peptides from large-scale immunopeptidomics raw data sets. In the conducted experiments we benchmarked our workflow to other existing mass spectrometry analysis software and achieved higher sensitivity. A dataset of 38 HLA immunopeptidomics raw files of peripheral blood mononuclear cells (PBMCs) from 10 healthy volunteers and 4 JY cell lines was used to assess the performance of the pipeline at each processing step. In addition, 66 isotope labeled known HLA-presented peptides were spiked into the JY cell extracts decreasing in concentration by log10 steps from 100 fmol to 0.1 fmol.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): B Cell, Blood Plasma, Peripheral Blood Mononuclear Cell, Blood

SUBMITTER: Leon Bichmann  

LAB HEAD: Professor Oliver Kohlbacher

PROVIDER: PXD011628 | Pride | 2019-10-14

REPOSITORIES: Pride