Immunopeptidomics and Tumor Antigen Discovery in Oncology

Identifying tumor-specific antigens is essential for developing targeted cancer immunotherapies. Immunopeptidomics, the study of peptides presented by major histocompatibility complex (MHC) molecules, has emerged as a powerful tool in this effort. By analyzing these peptide repertoires, researchers can uncover novel targets for personalized treatments, including cancer vaccines and T-cell therapies.

Advancements in mass spectrometry and bioinformatics have significantly improved the ability to detect and characterize MHC-bound peptides from tumors, driving progress in understanding tumor immune evasion and optimizing therapeutic strategies.

Antigen Processing And Presentation

The generation of tumor-associated antigens begins with antigen processing and presentation, a tightly regulated sequence of intracellular events that dictate which peptides are displayed on the cell surface by MHC molecules. This process determines the immunogenic landscape of a tumor, influencing how effectively the immune system distinguishes malignant cells from healthy tissue. The degradation of intracellular proteins into peptide fragments is the first step, primarily orchestrated by the proteasome. In tumor cells, alterations in proteasomal cleavage preferences can modify the peptide pool, leading to the presentation of unique neoantigens from somatic mutations or aberrant protein expression.

Once peptides are generated, they must be transported into the endoplasmic reticulum (ER) for loading onto MHC molecules. The transporter associated with antigen processing (TAP), a heterodimeric complex, selectively translocates peptides of appropriate length and sequence motifs. Tumor cells often exhibit dysregulation in TAP expression, which can skew the peptide repertoire. Within the ER, chaperone proteins such as tapasin and calreticulin stabilize MHC molecules and ensure high-affinity peptide binding. The efficiency of this process impacts the diversity of tumor-derived peptides on the cell surface, influencing immune recognition.

After peptide loading, MHC-peptide complexes are transported to the plasma membrane, where they become accessible to T cells. The stability and longevity of these complexes are influenced by peptide binding affinity and MHC structural integrity. Tumor cells frequently exploit mechanisms to downregulate MHC expression or alter peptide presentation dynamics, evading immune detection. For example, mutations in β2-microglobulin, a critical component of MHC class I stability, have been observed in various cancers, leading to impaired antigen display. These modifications can create an immunologically “cold” tumor microenvironment, reducing immune surveillance.

MHC Classes And Their Peptide Repertoires

The major histocompatibility complex (MHC) shapes the repertoire of peptides displayed on the cell surface, directly influencing antigen recognition. MHC molecules are classified into class I and class II, each with distinct structural features and peptide-binding preferences. MHC class I molecules primarily present peptides from intracellular proteins, while MHC class II molecules display peptides from extracellular sources. These differences stem from the distinct pathways through which peptides are processed and loaded onto MHC molecules. Tumor cells, which often harbor mutations and aberrant protein expression, generate a unique set of peptides that can be selectively presented, forming the basis for tumor-specific antigen discovery.

MHC class I molecules consist of a heavy chain and β2-microglobulin, with a peptide-binding groove that accommodates peptides typically 8–11 amino acids in length. The selectivity of this groove is dictated by anchor residues within the peptide, which fit into specific pockets of the binding cleft. Tumor cells frequently exhibit alterations in proteasomal processing, generating neoantigens with modified anchor residues that influence MHC binding affinity. The diversity of peptides presented by MHC class I is shaped by the polymorphic nature of human leukocyte antigen (HLA) alleles, which encode different versions of MHC molecules. This genetic variability results in distinct peptide repertoires across individuals, influencing tumor antigen presentation and potential targets for immunotherapy.

MHC class II molecules have a more open-ended binding groove that accommodates longer peptides, typically 13–25 amino acids in length. These peptides are derived from extracellular proteins that are internalized, processed within endosomal compartments, and loaded onto MHC class II molecules via the HLA-DM chaperone. The broader peptide-binding capacity of MHC class II allows for a more diverse antigenic repertoire, including peptides from tumor-associated proteins that are secreted, shed, or phagocytosed by antigen-presenting cells. The binding motifs of MHC class II peptides are less constrained than those of MHC class I, resulting in a more flexible selection of antigenic fragments, influencing immune interactions.

Mass Spectrometry Strategies

Advancements in mass spectrometry have transformed the identification and characterization of MHC-bound peptides. The complexity of these peptide mixtures, combined with their often low abundance, necessitates highly sensitive analytical techniques. Modern approaches rely on high-resolution mass spectrometers with optimized fragmentation methods to accurately sequence peptides and determine their post-translational modifications. The choice of mass spectrometry platform, ionization method, and data acquisition strategy significantly impacts peptide identification.

Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) remains the gold standard for immunopeptidomic analysis, separating complex peptide pools before mass spectrometric detection. Advances in ultra-high-performance liquid chromatography (UHPLC) enhance peptide resolution, reducing co-elution and improving identification confidence. Data-dependent acquisition (DDA) and data-independent acquisition (DIA) strategies refine peptide detection, with DIA offering a more comprehensive sampling of the immunopeptidome. Optimized fragmentation techniques, such as higher-energy collisional dissociation (HCD) and electron-transfer dissociation (ETD), ensure accurate annotation of tumor-derived antigens.

Recent improvements in sample preparation protocols have boosted detection sensitivity. Immunoaffinity purification using MHC-specific antibodies enhances peptide recovery, while chemical derivatization techniques improve ionization efficiency. Isobaric labeling strategies, such as tandem mass tags (TMT), facilitate relative quantification of peptides across multiple samples, enabling comparative immunopeptidomic studies between tumor and normal tissues. These methodological refinements have expanded the detectable peptide repertoire, uncovering previously elusive tumor-associated antigens.

Tumor Antigen Discovery

Identifying tumor-specific antigens is fundamental to developing targeted cancer therapies. Immunopeptidomics enables the systematic discovery of peptides uniquely presented by tumor cells, distinguishing them from those found in healthy tissues.

Peptide Enrichment Steps

The isolation of MHC-bound peptides from tumor samples is a critical step in immunopeptidomic workflows. Given their low abundance, enrichment strategies must be highly selective. Immunoaffinity purification using monoclonal antibodies specific to MHC class I or II molecules is the most widely used approach. These antibodies selectively capture MHC-peptide complexes from tumor lysates, allowing for the subsequent elution of bound peptides. The choice of antibody and purification conditions significantly impacts the yield and diversity of recovered peptides.

Alternative enrichment methods, such as size-exclusion chromatography and ultrafiltration, can further refine peptide isolation. Chemical crosslinking techniques have been explored to stabilize MHC-peptide interactions during purification, preventing peptide loss. Studies comparing different enrichment protocols show that optimized immunoaffinity purification consistently yields a broader and more representative tumor immunopeptidome.

MHC-Bound Peptide Characterization

Once enriched, tumor-derived peptides must be accurately characterized to determine their sequence, post-translational modifications, and binding properties. High-resolution mass spectrometry plays a central role in this process. Fragmentation techniques such as higher-energy collisional dissociation (HCD) and electron-transfer dissociation (ETD) provide complementary insights into peptide backbone structure and modification patterns. These methods are particularly useful for identifying phosphorylated or glycosylated tumor antigens, which may influence peptide stability and MHC binding affinity.

Advancements in de novo sequencing algorithms have further improved the characterization of tumor-specific peptides, particularly those arising from non-canonical translation events or cryptic genomic regions. Tumors frequently present peptides derived from alternative reading frames or noncoding regions, expanding the potential antigenic landscape. Integrating RNA sequencing data with mass spectrometry results allows for a more comprehensive analysis of tumor antigen presentation.

Analytical Data Interpretation

Interpreting immunopeptidomic data requires sophisticated bioinformatics tools capable of distinguishing tumor-specific peptides from those commonly found in normal tissues. Database searching against reference proteomes is a standard approach but may miss novel or mutated peptides unique to tumors. Customized databases incorporating tumor-specific mutations, splice variants, and noncanonical translation products improve peptide identification accuracy.

Machine learning algorithms have been applied to predict MHC binding affinity and peptide immunogenicity, streamlining the selection of promising tumor antigens. Comparative analyses between tumor and adjacent normal tissues help filter out peptides that are ubiquitously expressed, ensuring that selected antigens are truly tumor-specific. These computational advancements are accelerating the discovery of clinically relevant tumor antigens for more precise cancer immunotherapies.

Immunopeptidome Variations In Different Tumor Types

The immunopeptidome of tumors is highly heterogeneous, shaped by genetic, epigenetic, and environmental factors. High-mutation cancers, such as melanoma and lung adenocarcinoma, generate a larger pool of neoantigens due to extensive somatic mutations. In contrast, tumors with low mutational loads, such as certain leukemias and pediatric tumors, often rely on aberrantly expressed self-antigens. These differences influence immunotherapy effectiveness, as tumors with a broader immunopeptidome are more likely to present immunogenic peptides that can be targeted by T cells.