Translating Immunopeptidomics to Immunotherapy-Decision-Making for Patient and Personalized Target Selection

Abstract

Immunotherapy is revolutionizing cancer treatment and has shown success in particular for tumors with a high mutational load. These effects have been linked to neoantigens derived from patient-specific mutations. To expand efficacious immunotherapy approaches to the vast majority of tumor types and patient populations carrying only a few mutations and maybe not a single presented neoepitope, it is necessary to expand the target space to non-mutated cancer-associated antigens. Mass spectrometry enables the direct and unbiased discovery and selection of tumor-specific human leukocyte antigen (HLA) peptides that can be used to define targets for immunotherapy. Combining these targets into a warehouse allows for multi-target therapy and accelerated clinical application. For precise personalization aimed at optimally ensuring treatment efficacy and safety, it is necessary to assess the presence of the target on each individual patient's tumor. Here we show how LC-MS paired with gene expression data was used to define mRNA biomarkers currently being used as diagnostic test IMADETECT™ for patient inclusion and personalized target selection within two clinical trials (NCT02876510, NCT03247309). Thus, we present a way how to translate HLA peptide presentation into gene expression thresholds for companion diagnostics in immunotherapy considering the peptide-specific correlation to its encoding mRNA.

Keywords: Human leukocyte antigen; Immunopeptidome; Immunotherapy; Label-free quantitation; Precision medicine.