Identification of clinically relevant T cell receptors for personalized T cell therapy using combinatorial algorithms.

A central challenge in developing personalized cancer cell immunotherapy is the identification of tumor-reactive T cell receptors (TCRs). By exploiting the distinct transcriptomic profile of tumor-reactive T cells relative to bystander cells, we build and benchmark TRTpred, an antigen-agnostic in silico predictor of tumor-reactive TCRs. We integrate TRTpred with an avidity predictor to derive a combinatorial algorithm of clinically relevant TCRs for personalized T cell therapy and benchmark it in patient-derived xenografts.

Deep learning predictions of TCR-epitope interactions reveal epitope-specific chains in dual alpha T cells.

T cells have the ability to eliminate infected and cancer cells and play an essential role in cancer immunotherapy. T cell activation is elicited by the binding of the T cell receptor (TCR) to epitopes displayed on MHC molecules, and the TCR specificity is determined by the sequence of its α and ß chains. Here, we collect and curate a dataset of 17,715 αßTCRs interacting with dozens of class I and class II epitopes. We use this curated data to develop MixTCRpred, an epitope-specific TCR-epitope interaction predictor. MixTCRpred accurately predicts TCRs recognizing several viral and cancer epitopes. MixTCRpred further provides a useful quality control tool for multiplexed single-cell TCR sequencing assays of epitope-specific T cells and pinpoints a substantial fraction of putative contaminants in public databases. Analysis of epitope-specific dual α T cells demonstrates that MixTCRpred can identify α chains mediating epitope recognition. Applying MixTCRpred to TCR repertoires from COVID-19 patients reveals enrichment of clonotypes predicted to bind an immunodominant SARS-CoV-2 epitope. Overall, MixTCRpred provides a robust tool to predict TCRs interacting with specific epitopes and interpret TCR-sequencing data from both bulk and epitope-specific T cells.

PGE2 inhibits TIL expansion by disrupting IL-2 signalling and mitochondrial function.

Expansion of antigen-experienced CD8+ T cells is critical for the success of tumour-infiltrating lymphocyte (TIL)-adoptive cell therapy (ACT) in patients with cancer1. Interleukin-2 (IL-2) acts as a key regulator of CD8+ cytotoxic T lymphocyte functions by promoting expansion and cytotoxic capability2,3. Therefore, it is essential to comprehend mechanistic barriers to IL-2 sensing in the tumour microenvironment to implement strategies to reinvigorate IL-2 responsiveness and T cell antitumour responses. Here we report that prostaglandin E2 (PGE2), a known negative regulator of immune response in the tumour microenvironment4,5, is present at high concentrations in tumour tissue from patients and leads to impaired IL-2 sensing in human CD8+ TILs via the PGE2 receptors EP2 and EP4. Mechanistically, PGE2 inhibits IL-2 sensing in TILs by downregulating the IL-2Rγc chain, resulting in defective assembly of IL-2Rß-IL2Rγc membrane dimers. This results in impaired IL-2-mTOR adaptation and PGC1α transcriptional repression, causing oxidative stress and ferroptotic cell death in tumour-reactive TILs. Inhibition of PGE2 signalling to EP2 and EP4 during TIL expansion for ACT resulted in increased IL-2 sensing, leading to enhanced proliferation of tumour-reactive TILs and enhanced tumour control once the cells were transferred in vivo. Our study reveals fundamental features that underlie impairment of human TILs mediated by PGE2 in the tumour microenvironment. These findings have therapeutic implications for cancer immunotherapy and cell therapy, and enable the development of targeted strategies to enhance IL-2 sensing and amplify the IL-2 response in TILs, thereby promoting the expansion of effector T cells with enhanced therapeutic potential.

Response to tumor-infiltrating lymphocyte adoptive therapy is associated with preexisting CD8+ T-myeloid cell networks in melanoma.

Adoptive cell therapy (ACT) using ex vivo-expanded tumor-infiltrating lymphocytes (TILs) can eliminate or shrink metastatic melanoma, but its long-term efficacy remains limited to a fraction of patients. Using longitudinal samples from 13 patients with metastatic melanoma treated with TIL-ACT in a phase 1 clinical study, we interrogated cellular states within the tumor microenvironment (TME) and their interactions. We performed bulk and single-cell RNA sequencing, whole-exome sequencing, and spatial proteomic analyses in pre- and post-ACT tumor tissues, finding that ACT responders exhibited higher basal tumor cell-intrinsic immunogenicity and mutational burden. Compared with nonresponders, CD8+ TILs exhibited increased cytotoxicity, exhaustion, and costimulation, whereas myeloid cells had increased type I interferon signaling in responders. Cell-cell interaction prediction analyses corroborated by spatial neighborhood analyses revealed that responders had rich baseline intratumoral and stromal tumor-reactive T cell networks with activated myeloid populations. Successful TIL-ACT therapy further reprogrammed the myeloid compartment and increased TIL-myeloid networks. Our systematic target discovery study identifies potential T-myeloid cell network-based biomarkers that could improve patient selection and guide the design of ACT clinical trials.

Machine learning methods and harmonized datasets improve immunogenic neoantigen prediction.

The accurate selection of neoantigens that bind to class I human leukocyte antigen (HLA) and are recognized by autologous T cells is a crucial step in many cancer immunotherapy pipelines. We reprocessed whole-exome sequencing and RNA sequencing (RNA-seq) data from 120 cancer patients from two external large-scale neoantigen immunogenicity screening assays combined with an in-house dataset of 11 patients and identified 46,017 somatic single-nucleotide variant mutations and 1,781,445 neo-peptides, of which 212 mutations and 178 neo-peptides were immunogenic. Beyond features commonly used for neoantigen prioritization, factors such as the location of neo-peptides within protein HLA presentation hotspots, binding promiscuity, and the role of the mutated gene in oncogenicity were predictive for immunogenicity. The classifiers accurately predicted neoantigen immunogenicity across datasets and improved their ranking by up to 30%. Besides insights into machine learning methods for neoantigen ranking, we have provided homogenized datasets valuable for developing and benchmarking companion algorithms for neoantigen-based immunotherapies.

A phase 1 trial of adoptive transfer of vaccine-primed autologous circulating T cells in ovarian cancer.

We have previously shown that vaccination with tumor-pulsed dendritic cells amplifies neoantigen recognition in ovarian cancer. Here, in a phase 1 clinical study ( NCT01312376 /UPCC26810) including 19 patients, we show that such responses are further reinvigorated by subsequent adoptive transfer of vaccine-primed, ex vivo-expanded autologous peripheral blood T cells. The treatment is safe, and epitope spreading with novel neopeptide reactivities was observed after cell infusion in patients who experienced clinical benefit, suggesting reinvigoration of tumor-sculpting immunity.

HIV specific Th1 responses are altered in Ugandans with HIV and Schistosoma mansoni coinfection.

BACKGROUND: Fishing communities surrounding Lake Victoria in Uganda have HIV prevalence of 28% and incidence rates of 5 per 100 person years. More than 50% of the local fishermen are infected with Schistosoma mansoni (S. mansoni). We investigated the role of S. mansoni coinfection as a possible modifier of immune responses against HIV. Using polychromatic flow cytometry and Gran-ToxiLux assays, HIV specific responses, T cell phenotypes, antibody-dependent cell-mediated cytotoxic (ADCC) potency and titres were compared between participants with HIV-S. mansoni coinfection and participants with HIV infection alone. RESULTS: S. mansoni coinfection was associated with a modified pattern of anti-HIV responses, including lower frequency of bifunctional (IFNγ + IL-2 - TNF-α+) CD4 T cells, higher overall CD4 T cell activation and lower HIV ADCC antibody titres, compared to participants with HIV alone. CONCLUSIONS: These results support the hypothesis that S. mansoni infection affects T cell and antibody responses to HIV in coinfected individuals.

Neoantigen-specific CD8 T cells with high structural avidity preferentially reside in and eliminate tumors.

The success of cancer immunotherapy depends in part on the strength of antigen recognition by T cells. Here, we characterize the T cell receptor (TCR) functional (antigen sensitivity) and structural (monomeric pMHC-TCR off-rates) avidities of 371 CD8 T cell clones specific for neoantigens, tumor-associated antigens (TAAs) or viral antigens isolated from tumors or blood of patients and healthy donors. T cells from tumors exhibit stronger functional and structural avidity than their blood counterparts. Relative to TAA, neoantigen-specific T cells are of higher structural avidity and, consistently, are preferentially detected in tumors. Effective tumor infiltration in mice models is associated with high structural avidity and CXCR3 expression. Based on TCR biophysicochemical properties, we derive and apply an in silico model predicting TCR structural avidity and validate the enrichment in high avidity T cells in patients' tumors. These observations indicate a direct relationship between neoantigen recognition, T cell functionality and tumor infiltration. These results delineate a rational approach to identify potent T cells for personalized cancer immunotherapy.

Clonal expansion of intra-epithelial T cells in breast cancer revealed by spatial transcriptomics.

The spatial distribution of tumor-infiltrating lymphocytes (TIL) predicts breast cancer outcome and response to systemic therapy, highlighting the importance of an intact tissue structure for characterizing tumors. Here, we present ST-FFPE, a spatial transcriptomics method for the analysis of formalin-fixed paraffin-embedded samples, which opens the possibility of interrogating archival tissue. The method involves extraction, exome capture and sequencing of RNA from different tumor compartments microdissected by laser-capture, and can be used to study the cellular composition of tumor microenvironment. Focusing on triple-negative breast cancer (TNBC), we characterized T cells, B cells, dendritic cells, fibroblasts and endothelial cells in both stromal and intra-epithelial compartments. We found a highly variable spatial distribution of immune cell subsets among tumors. This analysis revealed that the immune repertoires of intra-epithelial T and B cells were consistently less diverse and more clonal than those of stromal T and B cells. T-cell receptor (TCR) sequencing confirmed a reduced diversity and higher clonality of intra-epithelial T cells relative to the corresponding stromal T cells. Analysis of the top 10 dominant clonotypes in the two compartments showed a majority of shared but also some unique clonotypes both in stromal and intra-epithelial T cells. Hyperexpanded clonotypes were more abundant among intra-epithelial than stromal T cells. These findings validate the ST-FFPE method and suggest an accumulation of antigen-specific T cells within tumor core. Because ST-FFPE is applicable for analysis of previously collected tissue samples, it could be useful for rapid assessment of intratumoral cellular heterogeneity in multiple disease and treatment settings.

Intradermal skin test with mRNA vaccines as a surrogate marker of T cell immunity in immunocompromised patients.

OBJECTIVES: Intradermal skin test (IDT) with mRNA vaccines may represent a simple, reliable, and affordable tool to measure T cell response in immunocompromised patients who failed to mount serological responses following vaccination with mRNA covid-19 vaccines. METHODS: We compared anti-SARS-CoV-2 antibodies and cellular responses in vaccinated immunocompromised patients (n = 58), healthy seronegative naive controls (NC, n = 8), and healthy seropositive vaccinated controls (VC, n = 32) by Luminex, spike-induced IFN-γ Elispot and an IDT. A skin biopsy 24 h after IDT and single-cell RNAseq was performed in three vaccinated volunteers. RESULTS: Twenty-five percent of seronegative NC had a positive Elispot (2/8) and IDT (1/4), compared to 95% (20/21) and 93% (28/30) in seropositive VC, respectively. Single-cell RNAseq data in the skin of VC showed a predominant mixed population of effector helper and cytotoxic T cells. The TCR repertoire revealed 18/1064 clonotypes with known specificities against SARS-CoV-2, among which six were spike-specific. Seronegative immunocompromised patients with positive Elispot and IDT were in 83% (5/6) treated with B cell-depleting reagents, while those with negative IDT were all transplant recipients. CONCLUSIONS: Our results indicate that delayed local reaction to IDT reflects vaccine-induced T-cell immunity opening new perspectives to monitor seronegative patients and elderly populations with waning immunity.

Phenotype and Reactivity of Lymphocytes Expanded from Benign Prostate Hyperplasic Tissues and Prostate Cancer.

Benign prostate hyperplasia (BPH) is a frequent condition in aging men, which affects life quality, causing principally lower urinary tract symptoms. Epidemiologic studies suggest that BPH may raise the risk of developing prostate cancer (PCa), most likely promoting a chronic inflammatory environment. Studies aiming at elucidating the link and risk factors that connect BPH and PCa are urgently needed to develop prevention strategies. The BPH microenvironment, similar to the PCa one, increases immune infiltration of the prostate, but, in contrast to PCa, immunosuppression may not be established yet. In this study, we found that prostate-infiltrating lymphocytes (PILs) expanded from hyperplastic prostate tissue recognized tumor-associated antigens (TAA) and autologous tissue, regardless of the presence of tumor cells. PILs expanded from BPH samples of patients with PCa, however, seem to respond more strongly to autologous tissue. Phenotypic characterization of the infiltrating PILs revealed a trend towards better expanding CD4+ T cells in infiltrates derived from PCa, but no significant differences were found. These findings suggest that T cell tolerance is compromised in BPH-affected prostates, likely due to qualitative or quantitative alterations of the antigenic landscape. Our data support the hypothesis that BPH increases the risk of PCa and may pave the way for new personalized preventive vaccine strategies for these patients.

TCR sequencing and cloning methods for repertoire analysis and isolation of tumor-reactive TCRs.

T cell receptor (TCR) technologies, including repertoire analyses and T cell engineering, are increasingly important in the clinical management of cellular immunity in cancer, transplantation, and other immune diseases. However, sensitive and reliable methods for repertoire analyses and TCR cloning are still lacking. Here, we report on SEQTR, a high-throughput approach to analyze human and mouse repertoires that is more sensitive, reproducible, and accurate as compared with commonly used assays, and thus more reliably captures the complexity of blood and tumor TCR repertoires. We also present a TCR cloning strategy to specifically amplify TCRs from T cell populations. Positioned downstream of single-cell or bulk TCR sequencing, it allows time- and cost-effective discovery, cloning, screening, and engineering of tumor-specific TCRs. Together, these methods will accelerate TCR repertoire analyses in discovery, translational, and clinical settings and permit fast TCR engineering for cellular therapies.

Machine learning predictions of MHC-II specificities reveal alternative binding mode of class II epitopes.

CD4+ T cells orchestrate the adaptive immune response against pathogens and cancer by recognizing epitopes presented on class II major histocompatibility complex (MHC-II) molecules. The high polymorphism of MHC-II genes represents an important hurdle toward accurate prediction and identification of CD4+ T cell epitopes. Here we collected and curated a dataset of 627,013 unique MHC-II ligands identified by mass spectrometry. This enabled us to precisely determine the binding motifs of 88 MHC-II alleles across humans, mice, cattle, and chickens. Analysis of these binding specificities combined with X-ray crystallography refined our understanding of the molecular determinants of MHC-II motifs and revealed a widespread reverse-binding mode in HLA-DP ligands. We then developed a machine-learning framework to accurately predict binding specificities and ligands of any MHC-II allele. This tool improves and expands predictions of CD4+ T cell epitopes and enables us to discover viral and bacterial epitopes following the aforementioned reverse-binding mode.

Cancer vaccines based on whole-tumor lysate or neoepitopes with validated HLA binding outperform those with predicted HLA-binding affinity.

Antigen selection and prioritization represent crucial determinants of vaccines' efficacy. Here, we compare two personalized dendritic cell-based vaccination strategies using whole-tumor lysate or neoantigens. Data in mouse and in cancer patients demonstrate that peptide vaccines using neoantigens predicted on the sole basis of in silico peptide-major histocompatibility complex (MHC) binding affinity underperform relative to whole-tumor-lysate vaccines. In contrast, effective in vitro peptide-MHC binding affinity and peptide immunogenicity significantly improve the prioritization of tumor-rejecting neoepitopes and result in more efficacious vaccines.

Longitudinal analysis of DC subsets in patients with ovarian cancer: Implications for immunotherapy.

Background: The use of circulating cDC1 to generate anti-cancer vaccines is among the most promising approaches to overcome the limited immunogenicity and clinical efficacy of monocyte-derived DC. However, the recurrent lymphopenia and the reduction of DC numbers and functionality in patients with cancer may represent an important limitation of such approach. In patients with ovarian cancer (OvC) that had received chemotherapy, we previously showed that cDC1 frequency and function were reduced. Methods: We recruited healthy donors (HD, n=7) and patients with OvC at diagnosis and undergoing interval debulking surgery (IDS, n=6), primary debulking surgery (PDS, n=6) or at relapse (n=8). We characterized longitudinally phenotypic and functional properties of peripheral DC subsets by multiparametric flow cytometry. Results: We show that the frequency of cDC1 and the total CD141+ DC capacity to take up antigen are not reduced at the diagnosis, while their TLR3 responsiveness is partially impaired in comparison with HD. Chemotherapy causes cDC1 depletion and increase in cDC2 frequency, but mainly in patients belonging to the PDS group, while in the IDS group both total lymphocytes and cDC1 are preserved. The capacity of total CD141+ DC and cDC2 to take up antigen is not impacted by chemotherapy, while the activation capacity upon Poly(I:C) (TLR3L) stimulation is further decreased. Conclusions: Our study provides new information about the impact of chemotherapy on the immune system of patients with OvC and sheds a new light on the importance of considering timing with respect to chemotherapy when designing new vaccination strategies that aim at withdrawing or targeting specific DC subsets.

Improved predictions of antigen presentation and TCR recognition with MixMHCpred2.2 and PRIME2.0 reveal potent SARS-CoV-2 CD8+ T-cell epitopes.

The recognition of pathogen or cancer-specific epitopes by CD8+ T cells is crucial for the clearance of infections and the response to cancer immunotherapy. This process requires epitopes to be presented on class I human leukocyte antigen (HLA-I) molecules and recognized by the T-cell receptor (TCR). Machine learning models capturing these two aspects of immune recognition are key to improve epitope predictions. Here, we assembled a high-quality dataset of naturally presented HLA-I ligands and experimentally verified neo-epitopes. We then integrated these data in a refined computational framework to predict antigen presentation (MixMHCpred2.2) and TCR recognition (PRIME2.0). The depth of our training data and the algorithmic developments resulted in improved predictions of HLA-I ligands and neo-epitopes. Prospectively applying our tools to SARS-CoV-2 proteins revealed several epitopes. TCR sequencing identified a monoclonal response in effector/memory CD8+ T cells against one of these epitopes and cross-reactivity with the homologous peptides from other coronaviruses.

Immune pressure sculps tumor cells and trims high-quality mutations.

Immunoediting, the loss of tumor (neo)antigens due to T cell-dependent selection, sculpts tumor immunogenicity. In Nature, Luksza et al. conceive a model to score neoantigens' immunogenicity and predict tumor clonal evolution. With this model, they demonstrate that durable tumor control associates with selective limited acquisition of high-quality mutations.

Microfluidic T Cell Selection by Cellular Avidity.

No T cell receptor (TCR) T cell therapies have obtained clinical approval. The lack of strategies capable of selecting and recovering potent T cell candidates may be a contributor to this. Existing protocols for selecting TCR T cell clones for cell therapies such as peptide multimer methods have provided effective measurements on TCR affinities. However, these methods lack the ability to measure the collective strength of intercellular interactions (i.e., cellular avidity) and markers of T cell activation such as immunological synapse formation. This study describes a novel microfluidic fluid shear stress-based approach to identify and recover highly potent T cell clones based on the cellular avidity between living T cells and tumor cells. This approach is capable of probing approximately up to 10 000 T cell-tumor cell interactions per run and can recover potent T cells with up to 100% purity from mixed populations of T cells within 30 min. Markers of cytotoxicity, activation, and avidity persist when recovered high cellular avidity T cells are subsequently exposed to fresh tumor cells. These results demonstrate how microfluidic probing of cellular avidity may fast track the therapeutic T cell selection process and move the authors closer to precision cancer immunotherapy.

High levels of monocytic myeloid-derived suppressor cells are associated with favorable outcome in patients with pneumonia and sepsis with multi-organ failure.

BACKGROUND: Myeloid-derived suppressor cells (MDSCs) are immature myeloid cells with immunosuppressive functions sub-classified into monocytic and polymorphonuclear MDSCs (M-MDSCs and PMN-MDSCs). Clinical studies reported increased levels of MDSCs that were associated with poor outcome in sepsis patients. Since sepsis patients exhibit signs of inflammation and immunosuppression, MDSCs may provide benefit by dampening deleterious inflammation in some patients. To test this hypothesis, we measured MDSCs in critically ill sepsis patients with pneumonia and multi-organ dysfunctions and a high likelihood of death. METHODS: This was a prospective multicenter observational cohort study performed in eight ICUs in Athens and Thessaloniki, Greece, enrolling critically ill patients with pneumonia and sepsis with multi-organ dysfunctions. A flow cytometry approach using blood collected at study inclusion in tubes containing lyophilized antibodies combined to unsupervised clustering was developed to quantify M-MDSCs and PMN-MDSCs. RESULTS: Forty-eight patients were included, of whom 34 died within 90 days. At study inclusion, M-MDSCs and PMN-MDSCs were increased in sepsis patients when compared to healthy subjects (3.07% vs 0.96% and 22% vs 2.1% of leukocytes, respectively; p < 10-4). Increased PMN-MDSCs were associated with secondary infections (p = 0.024) and new sepsis episodes (p = 0.036). M-MDSCs were more abundant in survivors than in patients who died within 28 days (p = 0.028). Stratification of patients according to M-MDSC levels revealed that high levels of M-MDSC were associated with reduced 90-day mortality (high vs low M-MDSCs: 47% vs 84% mortality, p = 0.003, hazard ratio [HR] = 3.2, 95% CI 1.4-7.2). Combining high M-MDSC levels with low Acute Physiology and Chronic Health Evaluation (APACHE) II score improved patient stratification (M-MDSCshigh/APACHE IIlow vs M-MDSCslow/APACHE IIlow: 20% vs 80% 90-day mortality, p = 0.0096, HR = 7.2, 95% CI 1.6-32). In multivariate analyses high M-MDSCs remained correlated with improved survival in patients with low APACHE II score (p = 0.05, HR = 5.26, 95% CI 1.0-27.8). CONCLUSION: This is the first study to associate high levels of M-MDSCs with improved survival in sepsis patients.