Large Scale, User-Defined Peptide and Peptide-Human Leukocyte Antigen Library for High Throughput Detection of Immunogenic Antigens

Abstract

Targeted immunotherapies—ranging from personalized cancer vaccines to adoptive T‐cell therapies—have revolutionized oncology by leveraging the specificity of T cells to recognize tumor‐associated peptide-bound Human Leukocyte Antigen complexes (pHLA), leading to a durable and robust T cell response against infected or tumor cells. While the process of profiling the pHLA repertoire through mass spectrometry (MS), also known as immunopeptidomics, excels at identifying abundant peptides, it routinely misses lower‐abundance antigens, noncanonical antigens, and neoantigens—antigens arising from tumor-specific somatic mutations. Conversely, existing computational models—though high‐throughput—are constrained by limited HLA allele coverage and poor incorporation of peptide stability or immunogenicity features. These gaps limit our ability to comprehensively elucidate the tumor immunopeptidome and to discover the most clinically effective targets for next‐generation, personalized immunotherapies. To address the limitations in immunopeptidomics and the biases inherent in contemporary in silico predictors, we have devised two synergistic high-throughput platforms based on the recombinant protein expression system in Escherichia coli (E. coli): (1) Pepyrus: a method for rapid and scalable production of user-defined pure synthetic peptides and peptide spectral libraries, and (2) a method for production of recombinant pHLA from user-defined peptide libraries for targeted screening of HLA-bound peptide. Using Pepyrus, we produced user-defined peptide libraries totalling over 100,000 patient-specific and off-the-shelf shared cancer-specific peptides and acquired extensive reference spectra through high-resolution MS. From the peptide spectral libraries, we demonstrated its ability to improve low-abundance peptide detection when used together with data-independent mass spectrometry (DIA-MS), an acquisition method which provides a comprehensive spectral map of a given sample but requires a reference spectral library for peptide identity deconvolution. Pepyrus significantly increased detection sensitivity for primary tumor samples and patient-derived cell lines, successfully recovering numerous low-abundance neoantigen, endogenous retroviral, and unannotated open-reading-frame peptides that were undetected by conventional MS methods. Subsequently, we combined Pepyrus with recombinant HLA expression in E. coli and generated a recombinant pHLA library encompassing 10,000 peptides across 10 prevalent class I HLA alleles, systematically measuring binding at scale. All HLA alleles tested identified novel bound peptide motifs, thus potentially expanding the space of known allele-specific peptide sequences which could enhance the accuracy of prediction models to predict genuine binders. The design of the pHLA construct also allows for high-throughput screening and heat treatments, potentially allowing for systematic interrogation of features related to peptide stability, which could enhance the accuracy of predicting immunogenic epitopes within patient samples. Collectively, these integrated pipelines amplify the scope and intricacy of immunopeptidome profiling in a user-defined and high throughput manner, facilitating the reliable identification of both shared antigens and patient-specific neoantigens for the development of personalized vaccines and adoptive T-cell therapies. Our approach establishes a robust foundation for next-generation antigen detectors and predictors and paves the way for more efficient and broadly applicable targeted immunotherapies.