Merkel cell polyomavirus-specific and CD39+CLA+ CD8 T cells as blood-based predictive biomarkers for PD-1 blockade in Merkel cell carcinoma.

Merkel cell carcinoma is a skin cancer often driven by Merkel cell polyomavirus (MCPyV) with high rates of response to anti-PD-1 therapy despite low mutational burden. MCPyV-specific CD8 T cells are implicated in anti-PD-1-associated immune responses and provide a means to directly study tumor-specific T cell responses to treatment. Using mass cytometry and combinatorial tetramer staining, we find that baseline frequencies of blood MCPyV-specific cells correlated with response and survival. Frequencies of these cells decrease markedly during response to therapy. Phenotypes of MCPyV-specific CD8 T cells have distinct expression patterns of CD39, cutaneous lymphocyte-associated antigen (CLA), and CD103. Correspondingly, overall bulk CD39+CLA+ CD8 T cell frequencies in blood correlate with MCPyV-specific cell frequencies and similarly predicted favorable clinical outcomes. Conversely, frequencies of CD39+CD103+ CD8 T cells are associated with tumor burden and worse outcomes. These cell subsets can be useful as biomarkers and to isolate blood-derived tumor-specific T cells.

Interferon-α promotes neo-antigen formation and preferential HLA-B-restricted antigen presentation in pancreatic ß-cells.

Interferon (IFN)-α is the earliest cytokine signature observed in individuals at risk for type 1 diabetes (T1D), but its effect on the repertoire of HLA Class I (HLA-I)-bound peptides presented by pancreatic ß-cells is unknown. Using immunopeptidomics, we characterized the peptide/HLA-I presentation in in-vitro resting and IFN-α-exposed ß-cells. IFN-α increased HLA-I expression and peptide presentation, including neo-sequences derived from alternative mRNA splicing, post-translational modifications - notably glutathionylation - and protein cis-splicing. This antigenic landscape relied on processing by both the constitutive and immune proteasome. The resting ß-cell immunopeptidome was dominated by HLA-A-restricted ligands. However, IFN-α only marginally upregulated HLA-A and largely favored HLA-B, translating into a major increase in HLA-B-restricted peptides and into an increased activation of HLA-B-restricted vs. HLA-A-restricted CD8+ T-cells. A preferential HLA-B hyper-expression was also observed in the islets of T1D vs. non-diabetic donors, and we identified islet-infiltrating CD8+ T-cells from T1D donors reactive to HLA-B-restricted granule peptides. Thus, the inflammatory milieu of insulitis may skew the autoimmune response toward epitopes presented by HLA-B, hence recruiting a distinct T-cell repertoire that may be relevant to T1D pathogenesis.

Fundamental immune-oncogenicity trade-offs define driver mutation fitness.

Missense driver mutations in cancer are concentrated in a few hotspots1. Various mechanisms have been proposed to explain this skew, including biased mutational processes2, phenotypic differences3-6 and immunoediting of neoantigens7,8; however, to our knowledge, no existing model weighs the relative contribution of these features to tumour evolution. We propose a unified theoretical 'free fitness' framework that parsimoniously integrates multimodal genomic, epigenetic, transcriptomic and proteomic data into a biophysical model of the rate-limiting processes underlying the fitness advantage conferred on cancer cells by driver gene mutations. Focusing on TP53, the most mutated gene in cancer1, we present an inference of mutant p53 concentration and demonstrate that TP53 hotspot mutations optimally solve an evolutionary trade-off between oncogenic potential and neoantigen immunogenicity. Our model anticipates patient survival in The Cancer Genome Atlas and patients with lung cancer treated with immunotherapy as well as the age of tumour onset in germline carriers of TP53 variants. The predicted differential immunogenicity between hotspot mutations was validated experimentally in patients with cancer and in a unique large dataset of healthy individuals. Our data indicate that immune selective pressure on TP53 mutations has a smaller role in non-cancerous lesions than in tumours, suggesting that targeted immunotherapy may offer an early prophylactic opportunity for the former. Determining the relative contribution of immunogenicity and oncogenic function to the selective advantage of hotspot mutations thus has important implications for both precision immunotherapies and our understanding of tumour evolution.

Engineering T-cells with chimeric antigen receptors to combat hematological cancers: an update on clinical trials.

Chimeric antigen receptor (CAR) redirected T-cells has shown efficacy in the treatment of B-cell leukemia/lymphoma, however, high numbers of relapses occur due to loss of targeted antigen or intrinsic failure of the CAR T-cells. In this situation modifications of the basic strategy are envisaged to reduce the risk of relapse, some of them are in early clinical exploration. These include simultaneous targeting of multiple antigens or combination of CAR T-cell therapy with other treatment modalities such as checkpoint inhibitors. The review evaluates and discusses these modified advanced therapies and pre-clinical approaches with respect to their potential to control leukemia and lymphoma in the long-term.

NetTCR-2.0 enables accurate prediction of TCR-peptide binding by using paired TCRα and ß sequence data.

Prediction of T-cell receptor (TCR) interactions with MHC-peptide complexes remains highly challenging. This challenge is primarily due to three dominant factors: data accuracy, data scarceness, and problem complexity. Here, we showcase that "shallow" convolutional neural network (CNN) architectures are adequate to deal with the problem complexity imposed by the length variations of TCRs. We demonstrate that current public bulk CDR3ß-pMHC binding data overall is of low quality and that the development of accurate prediction models is contingent on paired α/ß TCR sequence data corresponding to at least 150 distinct pairs for each investigated pMHC. In comparison, models trained on CDR3α or CDR3ß data alone demonstrated a variable and pMHC specific relative performance drop. Together these findings support that T-cell specificity is predictable given the availability of accurate and sufficient paired TCR sequence data. NetTCR-2.0 is publicly available at https://services.healthtech.dtu.dk/service.php?NetTCR-2.0 .

Meta-analysis of tumor- and T cell-intrinsic mechanisms of sensitization to checkpoint inhibition.

Checkpoint inhibitors (CPIs) augment adaptive immunity. Systematic pan-tumor analyses may reveal the relative importance of tumor-cell-intrinsic and microenvironmental features underpinning CPI sensitization. Here, we collated whole-exome and transcriptomic data for >1,000 CPI-treated patients across seven tumor types, utilizing standardized bioinformatics workflows and clinical outcome criteria to validate multivariable predictors of CPI sensitization. Clonal tumor mutation burden (TMB) was the strongest predictor of CPI response, followed by total TMB and CXCL9 expression. Subclonal TMB, somatic copy alteration burden, and histocompatibility leukocyte antigen (HLA) evolutionary divergence failed to attain pan-cancer significance. Dinucleotide variants were identified as a source of immunogenic epitopes associated with radical amino acid substitutions and enhanced peptide hydrophobicity/immunogenicity. Copy-number analysis revealed two additional determinants of CPI outcome supported by prior functional evidence: 9q34 (TRAF2) loss associated with response and CCND1 amplification associated with resistance. Finally, single-cell RNA sequencing (RNA-seq) of clonal neoantigen-reactive CD8 tumor-infiltrating lymphocytes (TILs), combined with bulk RNA-seq analysis of CPI-responding tumors, identified CCR5 and CXCL13 as T-cell-intrinsic markers of CPI sensitivity.

The T cell differentiation landscape is shaped by tumour mutations in lung cancer.

Tumour mutational burden (TMB) predicts immunotherapy outcome in non-small cell lung cancer (NSCLC), consistent with immune recognition of tumour neoantigens. However, persistent antigen exposure is detrimental for T cell function. How TMB affects CD4 and CD8 T cell differentiation in untreated tumours, and whether this affects patient outcomes is unknown. Here we paired high-dimensional flow cytometry, exome, single-cell and bulk RNA sequencing from patients with resected, untreated NSCLC to examine these relationships. TMB was associated with compartment-wide T cell differentiation skewing, characterized by loss of TCF7-expressing progenitor-like CD4 T cells, and an increased abundance of dysfunctional CD8 and CD4 T cell subsets, with significant phenotypic and transcriptional similarity to neoantigen-reactive CD8 T cells. A gene signature of redistribution from progenitor-like to dysfunctional states associated with poor survival in lung and other cancer cohorts. Single-cell characterization of these populations informs potential strategies for therapeutic manipulation in NSCLC.

Publisher Correction: Spatial heterogeneity of the T cell receptor repertoire reflects the mutational landscape in lung cancer.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Stereotactic ablative body radiotherapy (SABR) combined with immunotherapy (L19-IL2) versus standard of care in stage IV NSCLC patients, ImmunoSABR: a multicentre, randomised controlled open-label phase II trial.

BACKGROUND: About 50% of non-small cell lung cancer (NSCLC) patients have metastatic disease at initial diagnosis, which limits their treatment options and, consequently, the 5-year survival rate (15%). Immune checkpoint inhibitors (ICI), either alone or in combination with chemotherapy, have become standard of care (SOC) for most good performance status patients. However, most patients will not obtain long-term benefit and new treatment strategies are therefore needed. We previously demonstrated clinical safety of the tumour-selective immunocytokine L19-IL2, consisting of the anti-ED-B scFv L19 antibody coupled to IL2, combined with stereotactic ablative radiotherapy (SABR). METHODS: This investigator-initiated, multicentric, randomised controlled open-label phase II clinical trial will test the hypothesis that the combination of SABR and L19-IL2 increases progression free survival (PFS) in patients with limited metastatic NSCLC. One hundred twenty-six patients will be stratified according to their metastatic load (oligo-metastatic: ≤5 or poly-metastatic: 6 to 10) and randomised to the experimental-arm (E-arm) or the control-arm (C-arm). The C-arm will receive SOC, according to the local protocol. E-arm oligo-metastatic patients will receive SABR to all lesions followed by L19-IL2 therapy; radiotherapy for poly-metastatic patients consists of irradiation of one (symptomatic) to a maximum of 5 lesions (including ICI in both arms if this is the SOC). The accrual period will be 2.5-years, starting after the first centre is initiated and active. Primary endpoint is PFS at 1.5-years based on blinded radiological review, and secondary endpoints are overall survival, toxicity, quality of life and abscopal response. Associative biomarker studies, immune monitoring, CT-based radiomics, stool collection, iRECIST and tumour growth rate will be performed. DISCUSSION: The combination of SABR with or without ICI and the immunocytokine L19-IL2 will be tested as 1st, 2nd or 3rd line treatment in stage IV NSCLC patients in 14 centres located in 6 countries. This bimodal and trimodal treatment approach is based on the direct cytotoxic effect of radiotherapy, the tumour selective immunocytokine L19-IL2, the abscopal effect observed distant from the irradiated metastatic site(s) and the memory effect. The first results are expected end 2023. TRIAL REGISTRATION: ImmunoSABR Protocol Code: NL67629.068.18; EudraCT: 2018-002583-11; Clinicaltrials.gov: NCT03705403; ISRCTN ID: ISRCTN49817477; Date of registration: 03-April-2019.

Spatial heterogeneity of the T cell receptor repertoire reflects the mutational landscape in lung cancer.

Somatic mutations together with immunoediting drive extensive heterogeneity within non-small-cell lung cancer (NSCLC). Herein we examine heterogeneity of the T cell antigen receptor (TCR) repertoire. The number of TCR sequences selectively expanded in tumors varies within and between tumors and correlates with the number of nonsynonymous mutations. Expanded TCRs can be subdivided into TCRs found in all tumor regions (ubiquitous) and those present in a subset of regions (regional). The number of ubiquitous and regional TCRs correlates with the number of ubiquitous and regional nonsynonymous mutations, respectively. Expanded TCRs form part of clusters of TCRs of similar sequence, suggestive of a spatially constrained antigen-driven process. CD8+ tumor-infiltrating lymphocytes harboring ubiquitous TCRs display a dysfunctional tissue-resident phenotype. Ubiquitous TCRs are preferentially detected in the blood at the time of tumor resection as compared to routine follow-up. These findings highlight a noninvasive method to identify and track relevant tumor-reactive TCRs for use in adoptive T cell immunotherapy.

Lipid Nanoparticles for Delivery of Therapeutic RNA Oligonucleotides.

Gene therapy is an exciting field that has the potential to address emerging scientific and therapeutic tasks. RNA-based gene therapy has made remarkable progress in recent decades. Nevertheless, efficient targeted delivery of RNA therapeutics is still a prerequisite for entering the clinics. In this review, we introduce current delivery methods for RNA gene therapeutics based on lipid nanoparticles (LNPs). We focus on the clinical appeal of recent RNA NPs and discuss existing challenges of fabrication and screening LNP candidates for effective translation into drugs of human metabolic diseases and cancer.

T cell receptor fingerprinting enables in-depth characterization of the interactions governing recognition of peptide-MHC complexes.

The promiscuous nature of T-cell receptors (TCRs) allows T cells to recognize a large variety of pathogens, but makes it challenging to understand and control T-cell recognition. Existing technologies provide limited information about the key requirements for T-cell recognition and the ability of TCRs to cross-recognize structurally related elements. Here we present a 'one-pot' strategy for determining the interactions that govern TCR recognition of peptide-major histocompatibility complex (pMHC). We measured the relative affinities of TCRs to libraries of barcoded peptide-MHC variants and applied this knowledge to understand the recognition motif, here termed the TCR fingerprint. The TCR fingerprints of 16 different TCRs were identified and used to predict and validate cross-recognized peptides from the human proteome. The identified fingerprints differed among TCRs recognizing the same epitope, demonstrating the value of this strategy for understanding T-cell interactions and assessing potential cross-recognition before selection of TCRs for clinical development.

Preclinical evaluation of NF-κB-triggered dendritic cells expressing the viral oncogenic driver of Merkel cell carcinoma for therapeutic vaccination.

BACKGROUND: Merkel cell carcinoma (MCC) is a rare but very aggressive skin tumor that develops after integration of a truncated form of the large T-antigen (truncLT) of the Merkel cell polyomavirus (MCV) into the host's genome. Therapeutic vaccination with dendritic cells (DCs) loaded with tumor antigens is an active form of immunotherapy, which intends to direct the immune system towards tumors which express the respective vaccination antigens. METHODS: Cytokine-matured monocyte-derived DCs of healthy donors and MCC patients were electroporated with mRNA encoding the truncLT. To permit major histocompatibility complex (MHC) class II next to class I presentation, we used an RNA construct in which the antigen was fused to a DCLamp sequence in addition to the unmodified antigen. To further improve their immunogenicity, the DCs were additionally activated by co-transfection with the constitutively active nuclear factor (NF)-κB activator caIKK. These DCs were used to stimulate autologous CD8+ T-cells or a mixture of CD4+ and CD8+ T-cells. Then the percentage of T-cells, specific for the truncLT, was quantified by interferon (IFN)γ ELISpot assays. RESULTS: Both the truncLT and its DCLamp-fusion were detected within the DCs by flow cytometry, albeit the latter required blocking of the proteasome. The transfection with caIKK upregulated maturation markers and induced cytokine production. After 2-3 rounds of stimulation, the T-cells from 11 out of 13 healthy donors recognized the antigen. DCs without caIKK appeared in comparison less potent in inducing such responses. When using cells derived from MCC patients, we could induce responses for 3 out of 5 patients; however, here the caIKK-transfected DCs did not display their superiority. CONCLUSION: These results show that optimized DCs are able to induce MCV-antigen-specific T-cell responses. Therapeutic vaccination with such transfected DCs could direct the immune system against MCC.

Neoantigen landscape dynamics during human melanoma-T cell interactions.

Recognition of neoantigens that are formed as a consequence of DNA damage is likely to form a major driving force behind the clinical activity of cancer immunotherapies such as T-cell checkpoint blockade and adoptive T-cell therapy. Therefore, strategies to selectively enhance T-cell reactivity against genetically defined neoantigens are currently under development. In mouse models, T-cell pressure can sculpt the antigenicity of tumours, resulting in the emergence of tumours that lack defined mutant antigens. However, whether the T-cell-recognized neoantigen repertoire in human cancers is constant over time is unclear. Here we analyse the stability of neoantigen-specific T-cell responses and the antigens they recognize in two patients with stage IV melanoma treated by adoptive T-cell transfer. The T-cell-recognized neoantigens can be selectively lost from the tumour cell population, either by overall reduced expression of the genes or loss of the mutant alleles. Notably, loss of expression of T-cell-recognized neoantigens was accompanied by development of neoantigen-specific T-cell reactivity in tumour-infiltrating lymphocytes. These data demonstrate the dynamic interactions between cancer cells and T cells, which suggest that T cells mediate neoantigen immunoediting, and indicate that the therapeutic induction of broad neoantigen-specific T-cell responses should be used to avoid tumour resistance.

Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade.

As tumors grow, they acquire mutations, some of which create neoantigens that influence the response of patients to immune checkpoint inhibitors. We explored the impact of neoantigen intratumor heterogeneity (ITH) on antitumor immunity. Through integrated analysis of ITH and neoantigen burden, we demonstrate a relationship between clonal neoantigen burden and overall survival in primary lung adenocarcinomas. CD8(+)tumor-infiltrating lymphocytes reactive to clonal neoantigens were identified in early-stage non-small cell lung cancer and expressed high levels of PD-1. Sensitivity to PD-1 and CTLA-4 blockade in patients with advanced NSCLC and melanoma was enhanced in tumors enriched for clonal neoantigens. T cells recognizing clonal neoantigens were detectable in patients with durable clinical benefit. Cytotoxic chemotherapy-induced subclonal neoantigens, contributing to an increased mutational load, were enriched in certain poor responders. These data suggest that neoantigen heterogeneity may influence immune surveillance and support therapeutic developments targeting clonal neoantigens.

Hierarchical Bayesian mixture modelling for antigen-specific T-cell subtyping in combinatorially encoded flow cytometry studies.

Novel uses of automated flow cytometry technology for measuring levels of protein markers on thousands to millions of cells are promoting increasing need for relevant, customized Bayesian mixture modelling approaches in many areas of biomedical research and application. In studies of immune profiling in many biological areas, traditional flow cytometry measures relative levels of abundance of marker proteins using fluorescently labeled tags that identify specific markers by a single-color. One specific and important recent development in this area is the use of combinatorial marker assays in which each marker is targeted with a probe that is labeled with two or more fluorescent tags. The use of several colors enables the identification of, in principle, combinatorially increasingly numbers of subtypes of cells, each identified by a subset of colors. This represents a major advance in the ability to characterize variation in immune responses involving larger numbers of functionally differentiated cell subtypes. We describe novel classes of Markov chain Monte Carlo methods for model fitting that exploit distributed GPU (graphics processing unit) implementation. We discuss issues of cellular subtype identification in this novel, general model framework, and provide a detailed example using simulated data. We then describe application to a data set from an experimental study of antigen-specific T-cell subtyping using combinatorially encoded assays in human blood samples. Summary comments discuss broader questions in applications in immunology, and aspects of statistical computation.

Discovering naturally processed antigenic determinants that confer protective T cell immunity.

CD8+ T cells (TCD8) confer protective immunity against many infectious diseases, suggesting that microbial TCD8 determinants are promising vaccine targets. Nevertheless, current T cell antigen identification approaches do not discern which epitopes drive protective immunity during active infection - information that is critical for the rational design of TCD8-targeted vaccines. We employed a proteomics-based approach for large-scale discovery of naturally processed determinants derived from a complex pathogen, vaccinia virus (VACV), that are presented by the most frequent representatives of four major HLA class I supertypes. Immunologic characterization revealed that many previously unidentified VACV determinants were recognized by smallpox-vaccinated human peripheral blood cells in a variegated manner. Many such determinants were recognized by HLA class I-transgenic mouse immune TCD8 too and elicited protective TCD8 immunity against lethal intranasal VACV infection. Notably, efficient processing and stable presentation of immune determinants as well as the availability of naive TCD8 precursors were sufficient to drive a multifunctional, protective TCD8 response. Our approach uses fundamental insights into T cell epitope processing and presentation to define targets of protective TCD8 immunity within human pathogens that have complex proteomes, suggesting that this approach has general applicability in vaccine sciences.

Conditional ligands for Asian HLA variants facilitate the definition of CD8+ T-cell responses in acute and chronic viral diseases.

Conditional ligands have enabled the high-throughput production of human leukocyte antigen (HLA) libraries that present defined peptides. Immunomonitoring platforms typically concentrate on restriction elements associated with European ancestry, and such tools are scarce for Asian HLA variants. We report 30 novel irradiation-sensitive ligands, specifically targeting South East Asian populations, which provide 93, 63, and 79% coverage for HLA-A, -B, and -C, respectively. Unique ligands for all 16 HLA types were constructed to provide the desired soluble HLA product in sufficient yield. Peptide exchange was accomplished for all variants as demonstrated by an ELISA-based MHC stability assay. HLA tetramers with redirected specificity could detect antigen-specific CD8(+) T-cell responses against human cytomegalovirus, hepatitis B (HBV), dengue virus (DENV), and Epstein-Barr virus (EBV) infections. The potential of this population-centric HLA library was demonstrated with the characterization of seven novel T-cell epitopes from severe acute respiratory syndrome coronavirus, HBV, and DENV. Posthoc analysis revealed that the majority of responses would be more readily identified by our unbiased discovery approach than through the application of state-of-the-art epitope prediction. This flow cytometry-based technology therefore holds considerable promise for monitoring clinically relevant antigen-specific T-cell responses in populations of distinct ethnicity.

High-throughput identification of potential minor histocompatibility antigens by MHC tetramer-based screening: feasibility and limitations.

T-cell recognition of minor histocompatibility antigens (MiHA) plays an important role in the graft-versus-tumor (GVT) effect of allogeneic stem cell transplantation (allo-SCT). However, the number of MiHA identified to date remains limited, making clinical application of MiHA reactive T-cell infusion difficult. This study represents the first attempt of genome-wide prediction of MiHA, coupled to the isolation of T-cell populations that react with these antigens. In this unbiased high-throughput MiHA screen, both the possibilities and pitfalls of this approach were investigated. First, 973 polymorphic peptides expressed by hematopoietic stem cells were predicted and screened for HLA-A2 binding. Subsequently a set of 333 high affinity HLA-A2 ligands was identified and post transplantation samples from allo-SCT patients were screened for T-cell reactivity by a combination of pMHC-tetramer-based enrichment and multi-color flow cytometry. Using this approach, 71 peptide-reactive T-cell populations were generated. The isolation of a T-cell line specifically recognizing target cells expressing the MAP4K1(IMA) antigen demonstrates that identification of MiHA through this approach is in principle feasible. However, with the exception of the known MiHA HMHA1, none of the other T-cell populations that were generated demonstrated recognition of endogenously MiHA expressing target cells, even though recognition of peptide-loaded targets was often apparent. Collectively these results demonstrate the technical feasibility of high-throughput analysis of antigen-specific T-cell responses in small patient samples. However, the high-sensitivity of this approach requires the use of potential epitope sets that are not solely based on MHC binding, to prevent the frequent detection of T-cell responses that lack biological relevance.