MHCquant: Automated and Reproducible Data Analysis for Immunopeptidomics

Abstract

Personalized multipeptide vaccines are currently being discussed intensively for tumor immunotherapy. In order to identify epitopesshort, immunogenic peptidessuitable for eliciting a tumor-specific immune response, human leukocyte antigen-presented peptides are isolated by immunoaffinity purification from cancer tissue samples and analyzed by liquid chromatographycoupled tandem mass spectrometry (LC−MS/MS). Here, we present MHCquant, a fully automated, portable computational pipeline able to process LC−MS/MS data automatically and generate annotated, false discovery rate-controlled lists of (neo-)epitopes with associated relative quantification information. We could show that MHCquant achieves higher sensitivity than established methods. While obtaining the highest number of unique peptides, the rate of predicted MHC binders remains still comparable to other tools. Reprocessing of the data from a previously published study resulted in the identification of several neoepitopes not detected by previously applied methods. MHCquant integrates tailor-made pipeline components with existing open-source software into a coherent processing workflow. Container-based virtualization permits execution of this workflow without complex software installation, execution on cluster/cloud infrastructures, and full reproducibility of the results. Integration with the data analysis workbench KNIME enables easy mining of large-scale immunopeptidomics data sets. MHCquant is available as open-source software along with accompanying documentation on our website at https://www. openms.de/mhcquant/.

Cancer neoantigen prioritization through sensitive and reliable proteogenomics analysis

“…The two somatic variant peptides reported in the original paper but not identified by NeoFlow showed obviously higher absolute RT errors, suggesting the possibility of false positives. Among the four newly identified somatic variant peptides, two have been reported in a recently published reanalysis of the same data set 39 . These results demonstrate the sensitivity and specificity of NeoFlow in analyzing immunopeptidomics data and the value of RT-based validation as an additional filter to reduce false positives.…”

The HLA Ligand Atlas - A resource of natural HLA ligands presented on benign tissues

“…Database search of LC-MS/MS data from the three time series experiments was performed with MHCquant 1.5.1 as previously described (Bichmann et al, 2019). Identifications were matched between runs (Tyanova et al, 2016) based on retention time alignment and targeted feature extraction (Weisser and Choudhary, 2017) to integrate respective MS1 areas for all time points and technical replicates.…”

Mass Spectrometry-Based Identification of MHC-Associated Peptides

“…Other than the MIAPE initiative (minimal information about immunopeptidomics experiment), there is a need for standardized and version-controlled bioinformatics workflows, especially when considering potential clinical applications. One of the examples of such a workflow is MHCQuant [74], which also shows superior identification capabilities compared to other identification engines, as well as support for label-free quantitation. Remarkably, authors showed the identification and confirmation of previously undetected neoantigens in a publicly available dataset.…”