MHCquant: Automated and reproducible data analysis for immunopeptidomics

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.

个性化多肽疫苗目前正被广泛研究用于肿瘤免疫治疗。为筛选可诱发免疫应答的表位（epitope）——即短小的免疫原性肽段——研究人员通过免疫亲和纯化法从癌组织样本中提取人类白细胞抗原（human leukocyte antigen, HLA）呈递的肽段，并借助高效液相色谱-质谱联用技术对其进行分析。本研究报道了一款可从大规模免疫肽组学原始数据集中鉴定肽段的新型计算流程。在本实验中，我们将自研分析流程与现有质谱分析软件开展基准对比测试，结果表明本流程具有更高的检测灵敏度。本研究使用了包含38份HLA免疫肽组学原始文件的数据集，这些文件取自10名健康志愿者以及4株JY细胞系的外周血单个核细胞（peripheral blood mononuclear cells, PBMCs），用于评估该计算流程在各处理步骤中的性能表现。此外，我们将66份经同位素标记的已知HLA呈递肽段掺入JY细胞提取物中，其浓度从100飞摩尔（fmol）以10为底的对数梯度递减至0.1飞摩尔。