High-throughput, targeted MHC class I immunopeptidomics using a functional genetics screening platform

Immunogenic peptides putatively from intratumor microbes: Opportunities for colorectal cancer treatment

Recent evidence has confirmed the presence of intratumor microbes, yet their impact on the immunopeptidome remains largely unexplored. Here we introduced an integrated strategy to identify the immunopeptidome originated from intratumor microbes. Analyzing 10 colorectal cancer (CRC) patients, we identified 154 putative microbe-derived human leukocyte antigen (HLA)-I ligands. Predominantly bacterial in origin, these peptides were notably abundant in Fusobacterium nucleatum, the most prevalent bacterium differentiating between normal and tumor tissues. We discovered 20 peptides originating from F. nucleatum, thirteen of which, including two peptides shared across multiple patients, were tumor specific. Validation experiments confirmed that the putative microbe-derived peptide could activate CD8+ T cell responses. Our findings indicate that HLA-I molecules are capable of presenting intratumor microbe-derived peptides in CRC, potentially contributing to CD8+ T cell-mediated immunity and suggesting potential strategies for cancer immunotherapy.

Clinical trials, challenges, and changes in TCR-based therapeutics for hematologic malignancies

INTRODUCTION

T cells engineered to express antigen-specific T cell receptors (TCR; TCR-T) are a promising class of immunotherapeutic for patients with hematologic malignancies. Like chimeric antigen receptor-engineered T cells (CAR-T), TCR-T are cell products with defined specificity and composition. Unlike CAR-T, TCR-T can recognize targets arising both from intracellular and cell surface proteins and leverage the sensitivity of natural TCR signaling machinery. A growing number of TCR-T targeting various antigens in different hematologic malignancies are in early-phase clinical trials, and more are in preclinical development.

AREAS COVERED

This review covers results from early-phase TCR-T clinical trials for hematologic malignancies. Challenges in the field are reviewed, including identifying optimal targets, engaging CD4+ help for CD8+ T cells, and overcoming tumor-induced suppression; recent innovations to overcome these challenges are also highlighted.

EXPERT OPINION

In the future, TCR-T's promise for hematologic malignancies will be borne out in later-phase clinical trials and approvals for clinical use. Improved antigen discovery methods will help build the toolbox of targets needed for broadly applicable TCR-T. Rationally designed TCR-T modifications including incorporation of accessory receptors and gene editing will enhance TCR-T function. New hybrid receptors combining features of TCR and CAR will enter the clinic.

Topology surveillance of the lanosterol demethylase CYP51A1 by signal peptide peptidase

Cleavage of transmembrane segments on target proteins by the aspartyl intramembrane protease signal peptide peptidase (SPP, encoded by HM13) has been linked to immunity, viral infection and protein quality control. How SPP recognizes its various substrates and specifies their fate remains elusive. Here, we identify the lanosterol demethylase CYP51A1 as an SPP substrate and show that SPP-catalysed cleavage triggers CYP51A1 clearance by endoplasmic reticulum-associated degradation (ERAD). We observe that SPP targets only a fraction of CYP51A1 molecules, and we identify an amphipathic helix in the CYP51A1 N terminus as a key determinant for SPP recognition. SPP recognition is remarkably specific to CYP51A1 molecules with the amphipathic helix aberrantly inserted in the membrane with a type II orientation. Thus, our data are consistent with a role for SPP in topology surveillance, triggering the clearance of certain potentially non-functional conformers.

A multi-subunit autophagic capture complex facilitates degradation of ER stalled MHC-I in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDA) evades immune detection partly via autophagic capture and lysosomal degradation of major histocompatibility complex class I (MHC-I). Why MHC-I is susceptible to capture via autophagy remains unclear. By synchronizing exit of proteins from the endoplasmic reticulum (ER), we show that PDAC cells display prolonged retention of MHC-I in the ER and fail to efficiently route it to the plasma membrane. A capture-complex composed of NBR1 and the ER-phagy receptor TEX264 facilitates targeting of MHC-I for autophagic degradation, and suppression of either receptor is sufficient to increase total levels and re-route MHC-I to the plasma membrane. Binding of MHC-I to the capture complex is linked to antigen presentation efficiency, as inhibiting antigen loading via knockdown of TAP1 or beta 2-Microglobulin led to increased binding between MHC-I and the TEX264-NBR1 capture complex. Conversely, expression of ER directed high affinity antigenic peptides led to increased MHC-I at the cell surface and reduced lysosomal degradation. A genome-wide CRISPRi screen identified NFXL1, as an ER-resident E3 ligase that binds to MHC-I and mediates its autophagic capture. High levels of NFXL1 are negatively correlated with MHC-I protein expression and predicts poor patient prognosis. These data highlight an ER resident capture complex tasked with sequestration and degradation of non-conformational MHC-I in PDAC cells, and targeting this complex has the potential to increase PDAC immunogenicity.

Major histocompatibility complex and peptide specificity underpin CD8+ T cell direct alloresponse

The direct alloresponse, pivotal in transplant rejection, occurs when recipient T cells recognize intact allogeneic peptide-major histocompatibility complex (pMHC) complexes. Despite extensive research, our understanding of alloreactive CD8+ T cells against an individual MHC allele in humans remains limited, especially their precursor frequency, MHC specificity, and peptide specificity. By using K562 cell-based artificial antigen-presenting cells expressing human leukocyte antigen (HLA)-A∗01:01, HLA-A∗02:01, or HLA-A∗03:01, we determined that the precursor frequency of alloreactive CD8+ T cells against a single MHC allele ranges from 0.1% to 0.5%. Further, these cells exhibited MHC specificity regarding proliferation, activation, interferon gamma secretion, and cytolytic ability, with limited crossreactivity toward nontargeted MHC alleles. Focusing on anti-A2 alloreactive CD8+ T cells, we developed a peptide-exchangeable artificial antigen-presenting cell that displays selected peptides on HLA-A∗02:01. From a set of 95 computationally curated A2-restricted peptides most abundant in renal tubular cells, we identified 2 immunogenic kidney peptides across multiple donors. Overall, our findings significantly enhance the understanding of direct alloresponse and provide a toolkit for future mechanistic studies and reproducible patient monitoring.

Epitope landscape in autoimmune neurological disease and beyond

Autoantibody binding has a central role in autoimmune diseases and has also been linked to cancer, infections, and behavioral disorders. Autoimmune neurological diseases remain misclassified also due to an incomplete understanding of the underlying disease-specific epitopes. Such epitopes are crucial for both pathology and diagnosis, but have historically been overlooked. Recent technological advancements have enabled the exploration of these epitopes, potentially opening novel clinical avenues. The precise identification of novel B and T cell epitopes and their autoreactivity has led to the discovery of autoantigen-specific biomarkers for patients at high risk of autoimmune neurological diseases. In this review, we propose utilizing newly available synthetic and cellular-surface display technologies and guide epitope-focused studies to unlock the potential of disease-specific epitopes for improving diagnosis and treatments. Additionally, we offer recommendations to guide emerging epitope-focused studies to broaden the current landscape.

optiPRM: A Targeted Immunopeptidomics LC-MS Workflow With Ultra-High Sensitivity for the Detection of Mutation-Derived Tumor Neoepitopes From Limited Input Material

Personalized cancer immunotherapies such as therapeutic vaccines and adoptive transfer of T cell receptor-transgenic T cells rely on the presentation of tumor-specific peptides by human leukocyte antigen class I molecules to cytotoxic T cells. Such neoepitopes can for example arise from somatic mutations and their identification is crucial for the rational design of new therapeutic interventions. Liquid chromatography mass spectrometry (LC-MS)-based immunopeptidomics is the only method to directly prove actual peptide presentation and we have developed a parameter optimization workflow to tune targeted assays for maximum detection sensitivity on a per peptide basis, termed optiPRM. Optimization of collision energy using optiPRM allows for the improved detection of low abundant peptides that are very hard to detect using standard parameters. Applying this to immunopeptidomics, we detected a neoepitope in a patient-derived xenograft from as little as 2.5 × 106 cells input. Application of the workflow on small patient tumor samples allowed for the detection of five mutation-derived neoepitopes in three patients. One neoepitope was confirmed to be recognized by patient T cells. In conclusion, optiPRM, a targeted MS workflow reaching ultra-high sensitivity by per peptide parameter optimization, makes the identification of actionable neoepitopes possible from sample sizes usually available in the clinic.

The 2023 Report on the Proteome from the HUPO Human Proteome Project

Since 2010, the Human Proteome Project (HPP), the flagship initiative of the Human Proteome Organization (HUPO), has pursued two goals: (1) to credibly identify the protein parts list and (2) to make proteomics an integral part of multiomics studies of human health and disease. The HPP relies on international collaboration, data sharing, standardized reanalysis of MS data sets by PeptideAtlas and MassIVE-KB using HPP Guidelines for quality assurance, integration and curation of MS and non-MS protein data by neXtProt, plus extensive use of antibody profiling carried out by the Human Protein Atlas. According to the neXtProt release 2023-04-18, protein expression has now been credibly detected (PE1) for 18,397 of the 19,778 neXtProt predicted proteins coded in the human genome (93%). Of these PE1 proteins, 17,453 were detected with mass spectrometry (MS) in accordance with HPP Guidelines and 944 by a variety of non-MS methods. The number of neXtProt PE2, PE3, and PE4 missing proteins now stands at 1381. Achieving the unambiguous identification of 93% of predicted proteins encoded from across all chromosomes represents remarkable experimental progress on the Human Proteome parts list. Meanwhile, there are several categories of predicted proteins that have proved resistant to detection regardless of protein-based methods used. Additionally there are some PE1-4 proteins that probably should be reclassified to PE5, specifically 21 LINC entries and ∼30 HERV entries; these are being addressed in the present year. Applying proteomics in a wide array of biological and clinical studies ensures integration with other omics platforms as reported by the Biology and Disease-driven HPP teams and the antibody and pathology resource pillars. Current progress has positioned the HPP to transition to its Grand Challenge Project focused on determining the primary function(s) of every protein itself and in networks and pathways within the context of human health and disease.

Artificial intelligence in Immuno-genetics

Rapid advancements in the field of artificial intelligence (AI) have opened up unprecedented opportunities to revolutionize various scientific domains, including immunology and genetics. Therefore, it is of interest to explore the emerging applications of AI in immunology and genetics, with the objective of enhancing our understanding of the dynamic intricacies of the immune system, disease etiology, and genetic variations. Hence, the use of AI methodologies in immunological and genetic datasets, thereby facilitating the development of innovative approaches in the realms of diagnosis, treatment, and personalized medicine is reviewed.

TOFIMS mass spectrometry-based immunopeptidomics refines tumor antigen identification

T cell recognition of human leukocyte antigen (HLA)-presented tumor-associated peptides is central for cancer immune surveillance. Mass spectrometry (MS)-based immunopeptidomics represents the only unbiased method for the direct identification and characterization of naturally presented tumor-associated peptides, a key prerequisite for the development of T cell-based immunotherapies. This study reports on the implementation of ion mobility separation-based time-of-flight (TOFIMS) MS for next-generation immunopeptidomics, enabling high-speed and sensitive detection of HLA-presented peptides. Applying TOFIMS-based immunopeptidomics, a novel extensive benignTOFIMS dataset was generated from 94 primary benign samples of solid tissue and hematological origin, which enabled the expansion of benign reference immunopeptidome databases with > 150,000 HLA-presented peptides, the refinement of previously described tumor antigens, as well as the identification of frequently presented self antigens and not yet described tumor antigens comprising low abundant mutation-derived neoepitopes that might serve as targets for future cancer immunotherapy development.

High-throughput characterization of HLA-E-presented CD94/NKG2x ligands reveals peptides which modulate NK cell activation

HLA-E is a non-classical class I MHC protein involved in innate and adaptive immune recognition. While recent studies have shown HLA-E can present diverse peptides to NK cells and T cells, the HLA-E repertoire recognized by CD94/NKG2x has remained poorly defined, with only a limited number of peptide ligands identified. Here we screen a yeast-displayed peptide library in the context of HLA-E to identify 500 high-confidence unique peptides that bind both HLA-E and CD94/NKG2A or CD94/NKG2C. Utilizing the sequences identified via yeast display selections, we train prediction algorithms and identify human and cytomegalovirus (CMV) proteome-derived, HLA-E-presented peptides capable of binding and signaling through both CD94/NKG2A and CD94/NKG2C. In addition, we identify peptides which selectively activate NKG2C+ NK cells. Taken together, characterization of the HLA-E-binding peptide repertoire and identification of NK activity-modulating peptides present opportunities for studies of NK cell regulation in health and disease, in addition to vaccine and therapeutic design.

HLA-II immunopeptidome profiling and deep learning reveal features of antigenicity to inform antigen discovery

CD4+ T cell responses are exquisitely antigen specific and directed toward peptide epitopes displayed by human leukocyte antigen class II (HLA-II) on antigen-presenting cells. Underrepresentation of diverse alleles in ligand databases and an incomplete understanding of factors affecting antigen presentation in vivo have limited progress in defining principles of peptide immunogenicity. Here, we employed monoallelic immunopeptidomics to identify 358,024 HLA-II binders, with a particular focus on HLA-DQ and HLA-DP. We uncovered peptide-binding patterns across a spectrum of binding affinities and enrichment of structural antigen features. These aspects underpinned the development of context-aware predictor of T cell antigens (CAPTAn), a deep learning model that predicts peptide antigens based on their affinity to HLA-II and full sequence of their source proteins. CAPTAn was instrumental in discovering prevalent T cell epitopes from bacteria in the human microbiome and a pan-variant epitope from SARS-CoV-2. Together CAPTAn and associated datasets present a resource for antigen discovery and the unraveling genetic associations of HLA alleles with immunopathologies.