TScan-II: A genome-scale platform for the de novo identification of CD4+ T cell epitopes.

CD4+ T cells play fundamental roles in orchestrating immune responses and tissue homeostasis. However, our inability to associate peptide human leukocyte antigen class-II (HLA-II) complexes with their cognate T cell receptors (TCRs) in an unbiased manner has hampered our understanding of CD4+ T cell function and role in pathologies. Here, we introduce TScan-II, a highly sensitive genome-scale CD4+ antigen discovery platform. This platform seamlessly integrates the endogenous HLA-II antigen-processing machinery in synthetic antigen-presenting cells and TCR signaling in T cells, enabling the simultaneous screening of multiple HLAs and TCRs. Leveraging genome-scale human, virome, and epitope mutagenesis libraries, TScan-II facilitates de novo antigen discovery and deep exploration of TCR specificity. We demonstrate TScan-II's potential for basic and translational research by identifying a non-canonical antigen for a cancer-reactive CD4+ T cell clone. Additionally, we identified two antigens for clonally expanded CD4+ T cells in Sjögren's disease, which bind distinct HLAs and are expressed in HLA-II-positive ductal cells within affected salivary glands.

T-Scan: A Genome-wide Method for the Systematic Discovery of T Cell Epitopes.

T cell recognition of specific antigens mediates protection from pathogens and controls neoplasias, but can also cause autoimmunity. Our knowledge of T cell antigens and their implications for human health is limited by the technical limitations of T cell profiling technologies. Here, we present T-Scan, a high-throughput platform for identification of antigens productively recognized by T cells. T-Scan uses lentiviral delivery of antigen libraries into cells for endogenous processing and presentation on major histocompatibility complex (MHC) molecules. Target cells functionally recognized by T cells are isolated using a reporter for granzyme B activity, and the antigens mediating recognition are identified by next-generation sequencing. We show T-Scan correctly identifies cognate antigens of T cell receptors (TCRs) from viral and human genome-wide libraries. We apply T-Scan to discover new viral antigens, perform high-resolution mapping of TCR specificity, and characterize the reactivity of a tumor-derived TCR. T-Scan is a powerful approach for studying T cell responses.

High-throughput and multimodal profiling of antigen-specific T cells with a droplet-based cell-cell interaction screening platform.

Identifying antigen-specific T cells from tumor-infiltrating lymphocytes is essential for designing effective T cell immunotherapies. Traditional methods can detect antigen-specific T cells but struggle with high-throughput screening and multimodal profiling simultaneously. To address this issue, we developed DropCCI, a new strategy that transfers antigen information to co-incubated T cells for high-throughput, non-contaminated multimodal profiling. In DropCCI, droplets encapsulated DNA barcodes and antigen-loaded antigen-presenting cells (APCs), while click chemistry-modified T cells were injected into these droplets to capture free barcodes and acquire the corresponding antigen information. Following cell-cell interaction, APCs were removed via streptavidin-biotin conjugation, to prevent contamination. The resulting T cells underwent single-cell omics sequencing for comprehensive profiling of their antigen specificity, transcriptome, and genomics accurately. This click-chemistry method allowed detection of antigen-specific T cells without lysing APCs, avoiding cross-cell contamination and enabling low-noise multimodal profiling of primary T cells. With a completion time within 12 h and no requirement for complex equipment, DropCCI provides unbiased single-cell sequencing results that offer a comprehensive understanding of anti-tumor T cell responses. The concept of DropCCI holds great promise not only for advancing the field of T cell immunotherapy but also for its potential application in studying other cell-cell interactions.

Tumor-Infiltrating T Cells From Clear Cell Renal Cell Carcinoma Patients Recognize Neoepitopes Derived From Point and Frameshift Mutations.

Mutation-derived neoantigens are important targets for T cell-mediated reactivity toward tumors and, due to their unique tumor expression, an attractive target for immunotherapy. Neoepitope-specific T cells have been detected across a number of solid cancers with high mutational burden tumors, but neoepitopes have been mostly selected from single nucleotide variations (SNVs), and little focus has been given to neoepitopes derived from in-frame and frameshift indels, which might be equally important and potentially highly immunogenic. Clear cell renal cell carcinomas (ccRCCs) are medium-range mutational burden tumors with a high pan-cancer proportion of frameshift mutations. In this study, the mutational landscape of tumors from six RCC patients was analyzed by whole-exome sequencing (WES) of DNA from tumor fragments (TFs), autologous tumor cell lines (TCLs), and tumor-infiltrating lymphocytes (TILs, germline reference). Neopeptides were predicted using MuPeXI, and patient-specific peptide-MHC (pMHC) libraries were created for all neopeptides with a rank score < 2 for binding to the patient's HLAs. T cell recognition toward neoepitopes in TILs was evaluated using the high-throughput technology of DNA barcode-labeled pMHC multimers. The patient-specific libraries consisted of, on average, 258 putative neopeptides (range, 103-397, n = 6). In four patients, WES was performed on two different sources (TF and TCL), whereas in two patients, WES was performed only on TF. Most of the peptides were predicted from both sources. However, a fraction was predicted from one source only. Among the total predicted neopeptides, 16% were derived from frameshift indels. T cell recognition of 52 neoepitopes was detected across all patients (range, 4-18, n = 6) and spanning two to five HLA restrictions per patient. On average, 21% of the recognized neoepitopes were derived from frameshift indels (range, 0-43%, n = 6). Thus, frameshift indels are equally represented in the pool of immunogenic neoepitopes as SNV-derived neoepitopes. This suggests the importance of a broad neopeptide prediction strategy covering multiple sources of tumor material, and including different genetic alterations. This study, for the first time, describes the T cell recognition of frameshift-derived neoepitopes in RCC and determines their immunogenic profile.