Peptide-major Histocompatibility Complex Research Articles

Differential roles of kinetic on- and off-rates in T-cell receptor signal integration revealed with a modified Fab’-DNA ligand

Antibody-derived T-cell receptor (TCR) agonists are commonly used to activate T cells. While antibodies can trigger TCRs regardless of clonotype, they bypass native T cell signal integration mechanisms that rely on monovalent, membrane-associated, and relatively weakly binding ligand in the context of cellular adhesion. Commonly used antibodies and their derivatives bind much more strongly than native peptide major histocompatibility complex (pMHC) ligands bind their cognate TCRs. Because ligand dwell time is a critical parameter that tightly correlates with physiological function of the TCR signaling system, there is a general need, both in research and therapeutics, for universal TCR ligands with controlled kinetic binding parameters. To this end, we have introduced point mutations into recombinantly expressed α-TCRβ H57 Fab to modulate the dwell time of monovalent Fab binding to TCR. When tethered to a supported lipid bilayer via DNA complementation, these monovalent Fab’-DNA ligands activate T cells with potencies well-correlated with their TCR binding dwell time. Single-molecule tracking studies in live T cells reveal that individual binding events between Fab'-DNA ligands and TCRs elicit local signaling responses closely resembling native pMHC. The unique combination of high on- and off-rates of the H57 R97L mutant enables direct observations of cooperative interplay between ligand binding and TCR-proximal condensation of the linker for activation of T cells, which is not readily visualized with pMHC. This work provides insights into how T cells integrate kinetic information from TCR ligands and introduces a method to develop affinity panels for polyclonal T cells, such as cells from a human patient.

Autoregulated splicing of TRA2β programs T cell fate in response to antigen-receptor stimulation.

T cell receptor (TCR) sensitivity to peptide-major histocompatibility complex (MHC) dictates T cell fate. Canonical models of TCR sensitivity cannot be fully explained by transcriptional regulation. In this work, we identify a posttranscriptional regulatory mechanism of TCR sensitivity that guides alternative splicing of TCR signaling transcripts through an evolutionarily ultraconserved poison exon (PE) in the RNA-binding protein (RBP) TRA2β in mouse and human. TRA2β-PE splicing, seen during cancer and infection, was required for TCR-induced effector T cell expansion and function. Tra2β-PE skipping enhanced T cell response to antigen by increasing TCR sensitivity. As antigen levels decreased, Tra2β-PE reinclusion allowed T cell survival. Finally, we found that TRA2β-PE was first included in the genome of jawed vertebrates that were capable of TCR gene rearrangements. We propose that TRA2β-PE splicing acts as a gatekeeper of TCR sensitivity to shape T cell fate.

Transcriptional re-programming of liver-resident iNKT cells into T-regulatory type-1-like liver iNKT cells involves extensive gene de-methylation

Unlike conventional CD4+ T cells, which are phenotypically and functionally plastic, invariant NKT (iNKT) cells generally exist in a terminally differentiated state. Naïve CD4+ T cells can acquire alternative epigenetic states in response to different cues, but it remains unclear whether peripheral iNKT cells are epigenetically stable or malleable. Repetitive encounters of liver-resident iNKT cells (LiNKTs) with alpha-galactosylceramide (αGalCer)/CD1d-coated nanoparticles (NPs) can trigger their differentiation into a LiNKT cell subset expressing a T regulatory type 1 (TR1)-like (LiNKTR1) transcriptional signature. Here we dissect the epigenetic underpinnings of the LiNKT-LiNKTR1 conversion as compared to those underlying the peptide-major histocompatibility complex (pMHC)-NP-induced T-follicular helper (TFH)-to-TR1 transdifferentiation process. We show that gene upregulation during the LINKT-to-LiNKTR1 cell conversion is associated with demethylation of gene bodies, inter-genic regions, promoters and distal gene regulatory elements, in the absence of major changes in chromatin exposure or deposition of expression-promoting histone marks. In contrast, the naïve CD4+ T cell-to-TFH differentiation process involves extensive remodeling of the chromatin and the acquisition of a broad repertoire of epigenetic modifications that are then largely inherited by TFH cell-derived TR1 cell progeny. These observations indicate that LiNKT cells are epigenetically malleable and particularly susceptible to gene de-methylation.

NeoMS: Mass Spectrometry-based Method for Uncovering Mutated MHC-I Neoantigens.

Major Histocompatibility Complex (MHC) molecules play a critical role in the immune system by presenting peptides on the cell surface for recognition by T-cells. Tumor cells often produce MHC peptides with amino acid mutations, known as neoantigens, which evade T-cell recognition, leading to rapid tumor growth. In immunotherapies such as TCR-T and CAR-T, identifying these mutated MHC peptide sequences is crucial. Current mass spectrometry-based peptide identification methods primarily rely on database searching, which fails to detect mutated peptides not present in human databases. In this paper, we propose a novel workflow called NeoMS, designed to efficiently identify both non-mutated and mutated MHC-I peptides from mass spectrometry data. NeoMS utilizes a tagging algorithm to generate an expanded sequence database that includes potential mutated proteins for each sample. Furthermore, it employs a machine learning-based scoring function for each peptide-spectrum match (PSM) to maximize search sensitivity. Finally, a rigorous target-decoy approach is implemented to control the false discovery rates (FDR) of the peptides with and without mutations separately. Experimental results for regular peptides demonstrate that NeoMS outperforms four benchmark methods. For mutated peptides, NeoMS successfully identifies hundreds of high-quality mutated peptides in a melanoma-associated sample, with their validity confirmed by further studies.

A Chemical Approach to Assess the Impact of Post-translational Modification on MHC Peptide Binding and Effector Cell Engagement.

The human major histocompatibility complex (MHC) plays a pivotal role in the presentation of peptidic fragments from proteins, which can originate from self-proteins or from nonhuman antigens, such as those produced by viruses or bacteria. To prevent cytotoxicity against healthy cells, thymocytes expressing T cell receptors (TCRs) that recognize self-peptides are removed from circulation (negative selection), thus leaving T cells that recognize nonself-peptides. Current understanding suggests that post-translationally modified (PTM) proteins and the resulting peptide fragments they generate following proteolysis are largely excluded from negative selection; this feature means that PTMs can generate nonself-peptides that potentially contribute to the development of autoreactive T cells and subsequent autoimmune diseases. Although it is well-established that PTMs are prevalent in peptides present on MHCs, the precise mechanisms by which PTMs influence the antigen presentation machinery remain poorly understood. In the present work, we introduce chemical modifications mimicking PTMs on synthetic peptides. This is the first systematic study isolating the impact of PTMs on MHC binding and also their impact on TCR recognition. Our findings reveal various ways PTMs alter antigen presentation, which could have implications for tumor neoantigen presentation.

Inhibition of glycosphingolipid synthesis with eliglustat in combination with immune checkpoint inhibitors in advanced cancers: preclinical evidence and phase I clinical trial

Glycosphingolipids (GSLs) are abundantly expressed in cancer cells. The effects of GSL-targeted immunotherapies are not fully understood. Here, we show that the inhibition of GSL synthesis with the UDP-glucose ceramide glucosyltransferase inhibitor eliglustat can increase the exposure of the major histocompatibility complex (MHC) and tumour antigen peptides, enhancing the antitumour response of CD8+ T cells in a range of tumour models. We therefore conducted a proof-of-concept phase I trial on the combination of eliglustat and an anti-PD-1 antibody for the treatment of advanced cancers (NCT04944888). The primary endpoints were safety and feasibility, and the secondary endpoint was antitumor activity. All prespecified endpoints were met. Among the 31 enrolled patients, only 1 patient experienced a grade 3 adverse event (AE), and no grade 4 AEs were observed. The objective response rate was 22.6% and the disease control rate reached 71%. Of the 8 patients with proficient mismatch repair/microsatellite stable (pMMR/MSS) colorectal cancer, one achieved complete response and two each had partial response and stable disease. In summary, inhibiting the synthesis of GSLs might represent an effective immunotherapy approach.

Innovations Toward Immunopeptidomics

Over the past 30 years, immunopeptidomics has grown alongside improvements in mass spectrometry technology, genomics, transcriptomics, T cell receptor sequencing, and immunological assays to identify and characterize the targets of activated T cells. Together, multiple research groups with expertise in immunology, biochemistry, chemistry, and peptide mass spectrometry have come together to enable the isolation and sequence identification of endogenous major histocompatibility complex (MHC)-bound peptides. The idea to apply highly sensitive mass spectrometry techniques to study the landscape of peptide antigens presented by cell surface MHCs was innovative and continues to be successfully used and improved upon to deepen our understanding of how peptide antigens are processed and presented to T cells. Multiple research groups were involved in this bringing immunopeptidomics to the forefront of translational research, and we will highlight the contributions of one of the earliest developers, Professor Donald F. Hunt, and his research group at the University of Virginia. The Hunt laboratory applied cutting edge mass spectroscopy–based immunopeptidomics to study cancer, autoimmunity, transplant rejection, and infectious diseases. Across these diverse research areas, the Hunt laboratory and collaborators would characterize previously unknown MHC peptide–binding motifs and identify immunologically active antigens using ultra sensitive mass spectrometry techniques. Amazingly, many of the MHC-bound peptide antigens discovered in collaborations with the Hunt laboratory were sequenced by mass spectrometry before the completion of the human genome using manual de novo sequencing. In this perspective article, we will chronicle the work of the Hunt laboratory and their many collaborators that would be a major part of the foundation for mass spectrometry–based immunopeptidomics and its application to immunology research.

A hidden element governing immunogenicity in tumoral neoepitopes

The search for what characteristics define an epitope as either an immunogenic or a non-responsive target for immunotherapy has eluded researchers for years. Several studies demonstrate that certain positions in the peptide sequences, the major histocompatibility complex (MHC) anchor residues, have a preferential composition of amino acids (allelic motifs), being those epitopes more likely to display a better immunogenic response. First of all, not all MHC ligands are immunogenic, considering that unnumbered self-epitopes are continuously presented on the cell surfaces. In this work, we analyzed data to evaluate an additional element, central to our hypothesis that alterations in tumor protein sequences result in a structural change that shifts the electrostatic surface of the peptide-major histocompatibility complex (pMHC) molecules, pivotal for T-Cell receptor (TCR) recognition and the initiation of an immunogenic response. Firstly, previously neoepitope sequences presenting differential immune responses when compared with their wild-type counterparts were recovered. Even though the sequences were very similar, they triggered responses that were considerably different, and currently, there is no well-established explanation for why they conspicuously differ in immunogenic aspects from each other. The pMHCs structures harboring the epitope sequences were modeled and then used to generate images of their electrostatic surfaces, looking for qualitative differences that indicate the distinct responses. We noticed that no significant alteration occurred between immunogenic tumor peptides and their wild-type non-immunogenic counterparts when comparing their electrostatic surface. An additional comparison was made against structures of pMHCs containing immunogenic epitopes recovered from the Crosstope Database (https://crosstope.com.br/). In this sense, it was also possible to verify if immunogenic tumor epitopes were similar to viral immunogenic ones. Surprisingly, both wild-type (WT) sequences and neoepitopes shared an electrostatic surface distribution with pathogen targets, which could indicate their immunogenic predisposition. So we theorized that a “hidden element” may be responsible for the immunogenicity shift in neoepitopes.

Preparation empty peptide-receptive MHC class I complex for large-scale detection through photolabile peptide ligands

Peptide-major histocompatibility complex (pMHC) multimers are wide recognized as the premier technique for detecting, characterizing, and isolating antigen-specific CD8+ T-cell subsets. These multimers are specifically useful in studying infections, autoimmune conditions, and cancer through single-cell analysis techniques such as flow cytometry and fluorescence microscopy. However, the development of high-throughput assays with commercially available pMHC tetramers can be expensive, while in-house production may pose challenges for most biology research laboratories. In this context, we introduce a cost-friendly and uncomplicated protocol to prepare empty MHC class I tetramers using disulfide-stabilized molecules and photolabile peptide ligands. Our method relies on disulfide bond-stabilized MHC-I molecules, which demonstrated stability when folded into stable monomers in the presence of a photolabile epitope. These monomers, upon ultraviolet irradiation and streptavidin binding, efficiently assemble into tetramers devoid of any peptide. Following a short incubation with the peptide of interest under gentle conditions, the resulting pMHC tetramer effectively detects patient-sourced, neoantigen-specific T cells. Our unique approach streamlines large-scale pMHC generation, thus paving the way for advancements in T cell-based diagnostics and personalized therapies.

Microbiota dictate T cell clonal selection to augment graft-versus-host disease after stem cell transplantation

Allogeneic Tcell expansion is the primary determinant of graft-versus-host disease (GVHD), and current dogma dictates that this is driven by histocompatibility antigen disparities between donor and recipient. This paradigm represents a closed genetic system within which donor Tcells interact with peptide-major histocompatibility complexes (MHCs), though clonal interrogation remains challenging due to the sparseness of the Tcell repertoire. We developed a Bayesian model using donor and recipient Tcell receptor (TCR) frequencies in murine stem cell transplant systems to define limited common expansion of Tcell clones across genetically identical donor-recipient pairs. A subset of donor CD4+ Tcell clonotypes differentially expanded in identical recipients and were microbiota dependent. Microbiota-specific Tcells augmented GVHD lethality and could target microbial antigens presented by gastrointestinal epithelium during an alloreactive response. The microbiota serves as a source of cognate antigens that contribute to clonotypic Tcell expansion and the induction of GVHD independent of donor-recipient genetics.

A Computational Strategy for the Rapid Identification and Ranking of Patient-Specific T Cell Receptors Bound to Neoantigens.

T cell receptor (TCR) recognition of a peptide-major histocompatibility complex (pMHC) is crucial for adaptive immune response. The identification of therapeutically relevant TCR-pMHC protein pairs is a bottleneck in the implementation of TCR-based immunotherapies. The ability to computationally design TCRs to target a specific pMHC requires automated integration of next-generation sequencing, protein-protein structure prediction, molecular dynamics, and TCR ranking. A pipeline to evaluate patient-specific, sequence-based TCRs to a target pMHC is presented. Using the three most frequently expressed TCRs from 16 colorectal cancer patients, the protein-protein structure of the TCRs to the target CEA peptide-MHC is predicted using Modeller and ColabFold. TCR-pMHC structures are compared using automated equilibration and successive analysis. ColabFold generated configurations require an ≈2.5× reduction in equilibration time of TCR-pMHC structures compared to Modeller. The structural differences between Modeller and ColabFold are demonstrated by root mean square deviation (≈0.20nm) between clusters of equilibrated configurations, which impact the number of hydrogen bonds and Lennard-Jones contacts between the TCR and pMHC. TCR ranking criteria that may prioritize TCRs for evaluation of in vitro immunogenicity are identified, and this ranking is validated by comparing to state-of-the-art machine learning-based methods trained to predict the probability of TCR-pMHC binding.

Discovery of a monoclonal, high-affinity CD8+ T-cell clone following natural hepatitis C virus infection.

CD8+ Tcells recognizing their cognate antigen are typically recruited as a polyclonal population consisting of multiple clonotypes with varying T-cell receptor (TCR) affinity to the target peptide-major histocompatibility complex (pMHC) complex. Advances in single-cell sequencing have increased accessibility toward identifying TCRs with matched antigens. Here we present the discovery of a monoclonal CD8+ T-cell population with specificity for a hepatitis C virus (HCV)-derived human leukocyte antigen (HLA) class I epitope (HLA-B*07:02 GPRLGVRAT) which was isolated directly ex vivo from an individual with an episode of acutely resolved HCV infection. This population was absent before infection and underwent expansion and stable maintenance for at least 2 years after infection as measured by HLA-multimer staining. Furthermore, the monoclonal clonotype was characterized by an unusually long dissociation time (half-life = 794 s and koff = 5.73 × 10-4) for its target antigen when compared with previously published results. A comparison with related populations of HCV-specific populations derived fromthe same individual and a second individual suggested that high-affinity TCR-pMHC interactions may be inherent to epitope identity and shape the phenotype of responses which has implications for rational TCR selection and design in the age of personalized immunotherapies.

Development of a Stable Peptide-Major Histocompatibility Complex (MHC) via Sortase and Click Chemistry.

T cells play a crucial role in antitumor immune responses and the clearance of infected cells. They identify their targets through the binding of T-cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules present in cancer cells, infected cells, and antigen-presenting cells. This interaction is often weak, requiring multimeric pMHC molecules to enhance the avidity for identifying antigen-specific T cells. Current exchangeable pMHC-I tetramerization methods may overlook TCRs recognizing less stable yet immunogenic peptides. In vivo applications targeting antigen-specific T cells demand the genetic synthesis of a pMHC fusion for each unique peptide antigen, which poses a significant challenge. To address these challenges, we developed a sortase and click chemistry-mediated approach for generating stable pMHC molecules. Leveraging sortase technology, we introduced an azide click-handle near the N-terminus of β2m, proximal to the MHC-peptide-binding groove. Simultaneously, the peptide was engineered with a multi glycine linker and a C-terminal alkyne click-handle. Azide-alkyne click reactions efficiently immobilized the peptide onto the MHC molecule, providing a versatile and efficient method for pMHC generation. The resulting peptide-clicked-MHC specifically binds to its cognate TCR and remains stable for over 3 months at 4 °C in the absence of any additional free peptide. The stability of the pMHC and its affinity to cognate TCRs are influenced by the linker's nature and length. Multi glycine linkers outperform poly(ethylene glycol) (PEG) linkers in this regard. This technology expands the toolkit for identifying and targeting antigen-specific T cells, enhancing our understanding of cancer-specific immune responses, and has the potential to streamline the development of personalized immunotherapies.

Abstract PO4-16-05: Identification of functional HLA-A*11:01-restricted driver gene PIK3CA mutation specific T-cell receptors

Abstract The adoptive transfer of genetically engineered T-cell receptors (TCR-T) has emerged as a promising therapeutic strategy for the treatment of solid tumors. Recent clinical trials have demonstrated the safety and efficacy of TCR-T cell therapies against certain types of metastatic solid cancers. In our study, we aimed to investigate the potential of TCR-T cell therapies targeting neoantigens, which are exclusively expressed in cancer cells, with a focus on metastatic breast cancer (MBC). Specifically, we identified four driver missense mutations (PIK3CA E542K, E545K, H1047L, and H1047R) frequently observed in MBC patients and utilized computational tools to predict the generation of neoantigens. Utilizing NetMHCpan V.4.1, we performed screening of peptides spanning the mutation region and predicted a neoantigen epitope, PIK3CA_H1047L, to bind with HLA-A*11:01. To validate the presentation and stability of the neoantigen epitope, we employed TAP1-deficient K562 cells and observed stable expression of the mutant peptide-major histocompatibility complex (MHC) complex on the cell membrane. Subsequently, we isolated T cells from healthy donors possessing the HLA-A11:01 genotype, and subjected them to successive stimulations with neopeptide-pulsed dendritic cells. T cells stimulated with neopeptide were examined for neoantigen specificity using an IFN-γ ELISpot assay. Employing pMHC tetramer staining and single-cell sorting via flow cytometry, we successfully isolated five HLA-A11:01-restricted PIK3CA_H1047L-specific TCRs. Through lentivirus transduction of these TCRs into T cells, we achieved the generation of TCR-T cells that exhibited potent and specific activity exclusively against the PIK3CA_H1047L neoantigen. The functionality of the TCR-T cells was confirmed through assessments of CD137 expression, IFN-γ secretion, and cytotoxicity assays. In conclusion, our study demonstrates T cell responses towards neoantigens derived from PIK3CA, a commonly observed driver mutation in MBC. Furthermore, we successfully isolated five distinct neoantigen-specific TCRs that specifically recognized the PIK3CA_H1047L mutation and were restricted to the prevalent HLA-A*11:01 allele. The transfer of these TCRs into T cells resulted in the generation of TCR-T products exhibiting remarkable activity against the PIK3CA_H1047L neoantigen. These findings strongly encourage further investigation into TCRs targeting driver mutations in MBC, with the aim of advancing neoantigen-targeted TCR-T therapies into clinical trials. Additionally, the PIK3CA_H1047L neoantigen holds great promise as a potential candidate for the development of effective cancer vaccines. Citation Format: Meiying Shen, Xiaojian Han, Siyin Chen, Aishun Jin, Shengchun Liu. Identification of functional HLA-A*11:01-restricted driver gene PIK3CA mutation specific T-cell receptors [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-16-05.

Gene network-based and ensemble modeling-based selection of tumor-associated antigens with a predicted low risk of tissue damage for targeted immunotherapy

BackgroundTumor-associated antigens and their derived peptides constitute an opportunity to design off-the-shelf mainline or adjuvant anti-cancer immunotherapies for a broad array of patients. A performant and rational antigen selection pipeline...

IFI30 as a key regulator of PDL1 immunotherapy prognosis in breast cancer

BackgroundIFI30 is a lysosomal thiol reductase involved in antigen presentation and immune regulation in various cancers, including breast cancer. Despite its known involvement, the precise mechanism, function, and relationship with the PD-L1 axis and immune response remain unclear. MethodsWe conducted an extensive investigation into IFI30 mRNA expression in breast cancer utilizing data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. Furthermore, we characterized IFI30 mRNA expression across various cell types using publicly available single-cell RNA sequencing datasets, and assessed protein expression through immunohistochemistry using an in-house breast cancer tissue microarray. Functional experiments were performed to elucidate the effects of IFI30 overexpression on PD-L1 expression and inhibitory efficacy in both macrophages and breast tumor cells. ResultsOur study unveiled a marked upregulation of IFI30 expression in breast cancer tissues compared to their normal counterparts, with notable associations identified with tumor stage and prognosis. Additionally, IFI30 expression demonstrated significant correlations with various immune-related signaling pathways, encompassing peptide antigen binding, cytokine binding, and MHC class II presentation. Notably, breast cancer samples exhibiting high IFI30 expression in tumor cells displayed high PD-L1 expression on corresponding cells, alongside a diminished ratio of CD8 + T cell infiltration within the tumor microenvironment. Furthermore, ectopic knockdown of IFI30 in both tumor cells and macrophages resulted in a reduction of PD-L1 expression, while conversely, overexpression of IFI30 led to an increase in PD-L1 expression. ConclusionsThis study offers new insights into the involvement of IFI30 in breast cancer, elucidating its interplay with the PD-L1 axis and immune response dynamics. Our findings suggest that modulation of the IFI30-PD-L1 axis could serve as a promising strategy for regulating T cells infiltration in breast cancer thus treating breast cancer.

Simultaneous analysis of pMHC binding and reactivity unveils virus-specific CD8 T cell immunity to a concise epitope set.

CD8 T cells provide immunity to virus infection through recognition of epitopes presented by peptide major histocompatibility complexes (pMHCs). To establish a concise panel of widely recognized T cell epitopes from common viruses, we combined analysis of TCR down-regulation upon stimulation with epitope-specific enumeration based on barcode-labeled pMHC multimers. We assess CD8 T cell binding and reactivity for 929 previously reported epitopes in the context of 1 of 25 HLA alleles representing 29 viruses. The prevalence and magnitude of CD8 T cell responses were evaluated in 48 donors and reported along with 137 frequently recognized virus epitopes, many of which were underrepresented in the public domain. Eighty-four percent of epitope-specific CD8 T cell populations demonstrated reactivity to peptide stimulation, which was associated with effector and long-term memory phenotypes. Conversely, nonreactive T cell populations were associated primarily with naive phenotypes. Our analysis provides a reference map of epitopes for characterizing CD8 T cell responses toward common human virus infections.

Abstract LB442: Novel antibodies against a KK-LC-1-derived peptide presented on HLA-A*01 on tumor cells

Abstract The prognostic benefit of immune checkpoint inhibitors (CPIs) is mainly restricted to specific cancers, such as melanoma and lung adenocarcinoma. For patients with cancers which are noninflamed (“cold”), or CPI-resistant, therapeutic options are currently limited. Recently, the US FDA approved the first bispecific molecule targeting a tumor peptide MHC. This highlights the potential of targeting MHC-presented tumor antigens to empower T cells to specifically recognize and eliminate solid tumors. While there is a growing number of agents targeting pMHCs, most of them are restricted to HLA-A*02. There is an urgent need to identify effective pMHC targeted therapies for solid tumors, especially on other alleles to increase the proportion of eligible patients. Kita-Kyushu lung cancer antigen-1 (KK-LC-1/CT83) peptide presented on HLA-A*01 is a promising tumor target as its expression is restricted to tumors and it is broadly expressed in many cancers including gastric, lung, breast, and cervical cancer. However, targeting the KK-LC-1/HLA-A*01 complex is challenging due to the high levels of similar off-target peptides presented in healthy tissues. Through in silico analysis we identified peptides within the human genome that share a high sequence identity to the target. These peptides were found in a database containing >1 million mass spectrometry (MS)-identified peptides presented by healthy tissues, cancer cell lines, and tumor tissue samples. A peptide derived from 6-pyruvoyltetrahydropterin synthase (PTS) was found to be abundantly presented in healthy tissues. MS confirmed that this peptide occurs at extremely high natural levels (620 - 3500 copies per cell) on HLA-A*01 cell lines and healthy tissue. Here, we describe a set of pMHC T-cell engager (TCE) antibodies with high specificity towards HLA-A*01 restricted KK-LC-1 epitope. ScFv phage display libraries were rigorously screened for binding to the pMHC target and counter-screened against predicted off-target peptides including PTS. Specific scFv hits were reformatted into TCEs using an anti-CD3 Fab effector arm. The TCEs showed efficient killing of KK-LC-1/HLA-A*01-positive human cell lines NCI-H1703 and EKVX in co-cultures with human PBMCs, while KK-LC-1-negative/HLA-A*01-positive cell lines SK-MEL-30 and PC-3 (known to present the risk peptides on the surface) were minimally affected. TCE-dependent T cell activation measured by IFNγ was significantly higher in presence of TAP-deficient, (empty) HLA-A*01-expressing T2 cells pulsed with the target peptide compared to the risk peptides. Alanine scans of isolated binders confirmed that at least 6 amino acids of the KK-LC-1 peptide are required for binding. Overall, the data show that these antibodies have promising anti-tumor activity and specificity for KK-LC-1/HLA-A*01 positive tumors. Future activities will focus on lead optimization for therapeutic development. Citation Format: Fabian Scheifele, Stephanie Jungmichel, Nagjie Alijaj, Athanasia Dasargyri, Romina Doerig, Philip Knobel, Hannes Merten, Philipp Richle, Thomas Schleier, Anna Sobieraj, Alessio Vantellini, Tim Fugmann, Rom Leidner, Swethajit Biswas, Leonardo Borras. Novel antibodies against a KK-LC-1-derived peptide presented on HLA-A*01 on tumor cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB442.

Defining T cell receptor repertoires using nanovial-based binding and functional screening

The ability to selectively bind to antigenic peptides and secrete effector molecules can define rare and low-affinity populations of cells with therapeutic potential in emerging T cell receptor (TCR) immunotherapies. We leverage cavity-containing hydrogel microparticles, called nanovials, each coated with peptide-major histocompatibility complex (pMHC) monomers to isolate antigen-reactive T cells. T cells are captured and activated by pMHCs inducing the secretion of effector molecules including IFN-γ and granzyme B that are accumulated on nanovials, allowing sorting based on both binding and function. The TCRs of sorted cells on nanovials are sequenced, recovering paired αβ-chains using microfluidic emulsion-based single-cell sequencing. By labeling nanovials having different pMHCs with unique oligonucleotide-barcodes and secretions with oligo-barcoded detection antibodies, we could accurately link TCR sequences to specific targets and rank each TCR based on the corresponding cell's secretion level. Using the technique, we identified an expanded repertoire of functional TCRs targeting viral antigens with high specificity and found rare TCRs with activity against cancer-specific splicing-enhanced epitopes.

GraphMHC: Neoantigen prediction model applying the graph neural network to molecular structure.

Neoantigens are tumor-derived peptides and are biomarkers that can predict prognosis related to immune checkpoint inhibition by estimating their binding to major histocompatibility complex (MHC) proteins. Although deep neural networks have been primarily used for these prediction models, it is difficult to interpret the models reported thus far as accurately representing the interactions between biomolecules. In this study, we propose the GraphMHC model, which utilizes a graph neural network model applied to molecular structure to simulate the binding between MHC proteins and peptide sequences. Amino acid sequences sourced from the immune epitope database (IEDB) undergo conversion into molecular structures. Subsequently, atomic intrinsic informations and inter-atomic connections are extracted and structured as a graph representation. Stacked graph attention and convolution layers comprise the GraphMHC network which classifies bindings. The prediction results from the test set using the GraphMHC model showed a high performance with an area under the receiver operating characteristic curve of 92.2% (91.9-92.5%), surpassing a baseline model. Moreover, by applying the GraphMHC model to melanoma patient data from The Cancer Genome Atlas project, we found a borderline difference (0.061) in overall survival and a significant difference in stromal score between the high and low neoantigen load groups. This distinction was not present in the baseline model. This study presents the first feature-intrinsic method based on biochemical molecular structure for modeling the binding between MHC protein sequences and neoantigen candidate peptide sequences. This model can provide highly accurate responsibility information that can predict the prognosis of immune checkpoint inhibitors to cancer patients who want to apply it.