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Authors:
Dr Campbell Bunce, Chief Scientific Officer
Edward Cloake, Director of Immunology
Immunogenicity assessment is essential in any therapeutic protein development. But there’s a key step in this process that’s both powerful and versatile: major histocompatibility complex (MHC)-associated peptide proteomics (MAPPs), a complex yet informative assay that gives detailed insights into the immunogenic potential of a biologic. The real power of MAPPS, however, lies in its versatility in being applicable to other areas of drug development like vaccine design. This article looks at how the MAPPs assay works, how it integrates with other immunogenicity assays, and just how it can be flipped to help in vaccine design.
At its core, MAPPs is a method to identify peptides that bind major histocompatibility complex (MHC) molecules on antigen-presenting cells (APCs). The MAPPs assay can be broken into four main steps:
MAPPs works alongside other immunogenicity testing methods by offering a deeper look at peptide presentation and T-cell epitope identification (1).
MAPPs and T-cell assays. MAPPs identifies peptides that APCs present, meaning you can then use traditional T-cell assays to measure the T-cell responses to these peptides. MAPPs gives a map of naturally presented peptides, which affords us a good deal of confidence that the peptides tested in our T-cell assays are relevant in vivo.
MAPPs versus HLA-peptide binding assays. Human leukocyte antigen (HLA)-peptide binding assays predict potential T-cell epitopes based on binding affinity to HLA molecules but can miss naturally processed peptides. MAPPs identifies these naturally processed peptides and provides more accurate in vivo representation. This confirms which peptides are naturally presented and potentially immunogenic, complementing HLA binding assays.
MAPPs and in silico algorithms. In silico algorithms can predict peptide binding to HLA molecules based on known binding motifs. MAPPs can then move to validate these predictions by showing which peptides APCs present. However, many in silico algorithms are trained on datasets that only represent a small fraction of the naturally occurring peptidome,(1) leading them to overestimate risk as they include peptides that may never be processed by APCs. MAPPs circumvents this limitation by focusing on peptides actually processed and presented by human cells, which gives us a more accurate immunogenicity profile. Thankfully, MAPPs data has the potential to refine these algorithms to improve the predictive power.
Rather than being a standalone assay, MAPPs integrates with and enhances traditional immunogenicity assays, providing a comprehensive view of a biotherapeutic’s immunogenicity potential. This leads to better-informed drug development decisions and effective strategies to reduce unwanted immune responses.