Orthogonal cytokine engineering enables novel synthetic effector states escaping canonical exhaustion in tumor-rejecting CD8+ T cells.

To date, no immunotherapy approaches have managed to fully overcome T-cell exhaustion, which remains a mandatory fate for chronically activated effector cells and a major therapeutic challenge. Understanding how to reprogram CD8+ tumor-infiltrating lymphocytes away from exhausted effector states remains an elusive goal. Our work provides evidence that orthogonal gene engineering of T cells to secrete an interleukin (IL)-2 variant binding the IL-2Rßγ receptor and the alarmin IL-33 reprogrammed adoptively transferred T cells to acquire a novel, synthetic effector state, which deviated from canonical exhaustion and displayed superior effector functions. These cells successfully overcame homeostatic barriers in the host and led-in the absence of lymphodepletion or exogenous cytokine support-to high levels of engraftment and tumor regression. Our work unlocks a new opportunity of rationally engineering synthetic CD8+ T-cell states endowed with the ability to avoid exhaustion and control advanced solid tumors.

Activation of the transcription factor NFAT5 in the tumor microenvironment enforces CD8+ T cell exhaustion.

Persistent exposure to antigen during chronic infection or cancer renders T cells dysfunctional. The molecular mechanisms regulating this state of exhaustion are thought to be common in infection and cancer, despite obvious differences in their microenvironments. Here we found that NFAT5, an NFAT family transcription factor that lacks an AP-1 docking site, was highly expressed in exhausted CD8+ T cells in the context of chronic infections and tumors but was selectively required in tumor-induced CD8+ T cell exhaustion. Overexpression of NFAT5 in CD8+ T cells reduced tumor control, while deletion of NFAT5 improved tumor control by promoting the accumulation of tumor-specific CD8+ T cells that had reduced expression of the exhaustion-associated proteins TOX and PD-1 and produced more cytokines, such as IFNÉ£ and TNF, than cells with wild-type levels of NFAT5, specifically in the precursor exhausted PD-1+TCF1+TIM-3-CD8+ T cell population. NFAT5 did not promote T cell exhaustion during chronic infection with clone 13 of lymphocytic choriomeningitis virus. Expression of NFAT5 was induced by TCR triggering, but its transcriptional activity was specific to the tumor microenvironment and required hyperosmolarity. Thus, NFAT5 promoted the exhaustion of CD8+ T cells in a tumor-selective fashion.

Tumor-reactive T cell clonotype dynamics underlying clinical response to TIL therapy in melanoma.

Adoptive cell therapy (ACT) using in vitro expanded tumor-infiltrating lymphocytes (TILs) has inconsistent clinical responses. To better understand determinants of therapeutic success, we tracked TIL clonotypes from baseline tumors to ACT products and post-ACT blood and tumor samples in melanoma patients using single-cell RNA and T cell receptor (TCR) sequencing. Patients with clinical responses had baseline tumors enriched in tumor-reactive TILs, and these were more effectively mobilized upon in vitro expansion, yielding products enriched in tumor-specific CD8+ cells that preferentially infiltrated tumors post-ACT. Conversely, lack of clinical responses was associated with tumors devoid of tumor-reactive resident clonotypes and with cell products mostly composed of blood-borne clonotypes that persisted in blood but not in tumors post-ACT. Upon expansion, tumor-specific TILs lost tumor-associated transcriptional signatures, including exhaustion, and responders exhibited an intermediate exhausted effector state after TIL engraftment in the tumor, suggesting functional reinvigoration. Our findings provide insight into the nature and dynamics of tumor-specific clonotypes associated with clinical response to TIL-ACT, with implications for treatment optimization.

Disturbed mitochondrial dynamics in CD8+ TILs reinforce T cell exhaustion.

The metabolic challenges present in tumors attenuate the metabolic fitness and antitumor activity of tumor-infiltrating T lymphocytes (TILs). However, it remains unclear whether persistent metabolic insufficiency can imprint permanent T cell dysfunction. We found that TILs accumulated depolarized mitochondria as a result of decreased mitophagy activity and displayed functional, transcriptomic and epigenetic characteristics of terminally exhausted T cells. Mechanistically, reduced mitochondrial fitness in TILs was induced by the coordination of T cell receptor stimulation, microenvironmental stressors and PD-1 signaling. Enforced accumulation of depolarized mitochondria with pharmacological inhibitors induced epigenetic reprogramming toward terminal exhaustion, indicating that mitochondrial deregulation caused T cell exhaustion. Furthermore, supplementation with nicotinamide riboside enhanced T cell mitochondrial fitness and improved responsiveness to anti-PD-1 treatment. Together, our results reveal insights into how mitochondrial dynamics and quality orchestrate T cell antitumor responses and commitment to the exhaustion program.

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.

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.

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.

Lighting up the tumor fire with low-dose irradiation.

Current efforts combining immunotherapy and radiation have focused on high-dose radiation delivered to few tumor lesions, aiming to generate diffuse abscopal effects; however, these effects are uncommon in patients. Three recent studies in mouse tumor models and human cancer patients show that low-dose radiation (LDRT) delivered to all tumor lesions effectively mobilizes innate and adaptive immunity and synergizes with immunotherapy. These new findings suggest LDRT's potential as an immune amplifier capable of reprogramming the tumor microenvironment, instigating inflammation, and sensitizing 'cold' tumors to immune checkpoint blockade responsiveness.

Radiotherapy combination opportunities leveraging immunity for the next oncology practice.

Approximately one-half of patients with newly diagnosed cancer and many patients with persistent or recurrent tumors receive radiotherapy (RT), with the explicit goal of eliminating tumors through direct killing. The current RT dose and schedule regimens have been empirically developed. Although early clinical studies revealed that RT could provoke important responses not only at the site of treatment but also on remote, nonirradiated tumor deposits-the so-called "abscopal effect"- the underlying mechanisms were poorly understood and were not therapeutically exploited. Recent work has elucidated the immune mechanisms underlying these effects and has paved the way for developing combinations of RT with immune therapy. In the wake of recent therapeutic breakthroughs in the field of immunotherapy, rational combinations of immunotherapy with RT could profoundly change the standard of care for many tumor types in the next decade. Thus, a deep understanding of the immunologic effects of RT is urgently needed to design the next generation of therapeutic combinations. Here, the authors review the immune mechanisms of tumor radiation and summarize the preclinical and clinical evidence on immunotherapy-RT combinations. Furthermore, a framework is provided for the practicing clinician and the clinician investigator to guide the development of novel combinations to more rapidly advance this important field. CA Cancer J Clin 2017;67:65-85. © 2016 American Cancer Society.

Reflections on the opportunities and challenges of applying experience-based co-design (EBCD) to phase 1 clinical trials in oncology.

BACKGROUND: Experience-Based Co-Design (EBCD) is a multi-stage participatory action research process which was developed originally to increase patient involvement in service improvement initiatives. This viewpoint article serves as a reflection on the researchers' experiences, focusing on the application and feasibility of participatory approaches, particularly co-design, in the specific context of early-phase clinical trials. METHODS: We reflect on the opportunities and challenges of applying EBCD in a new context of early-phase clinical trials in oncology where experimental treatments are increasingly perceived as a therapeutic option and, in certain instances, their efficacy may lead to accelerated approval facilitating a swifter integration into standard care. RESULTS: We propose that the opportunity of applying EBCD in such trials lies in improving the delivery of person-centered care, care coordination, and support during the transition from experimental to standard care. Three potential challenges when applying EBCD in early-phase clinical trials are discussed related to: the need for standardization in trial processes; planning EBCD in a context of high uncertainty; and vulnerability of patient populations. CONCLUSION: Integrating EBCD into early-phase oncology trials presents an opportunity to enhance person-centered care and can lead to simultaneous improvements in care processes and therapeutic development. PATIENT OR PUBLIC CONTRIBUTION: This article has been developed with the collaboration of a patient partner who serves on the advisory board of our ongoing EBCD study in early clinical trials.

Sensitive Immunopeptidomics by Leveraging Available Large-Scale Multi-HLA Spectral Libraries, Data-Independent Acquisition, and MS/MS Prediction.

Mass spectrometry (MS) is the state-of-the-art methodology for capturing the breadth and depth of the immunopeptidome across human leukocyte antigen (HLA) allotypes and cell types. The majority of studies in the immunopeptidomics field are discovery driven. Hence, data-dependent tandem MS (MS/MS) acquisition (DDA) is widely used, as it generates high-quality references of peptide fingerprints. However, DDA suffers from the stochastic selection of abundant ions that impairs sensitivity and reproducibility. In contrast, in data-independent acquisition (DIA), the systematic fragmentation and acquisition of all fragment ions within given isolation m/z windows yield a comprehensive map for a given sample. However, many DIA approaches commonly require generating comprehensive DDA-based spectrum libraries, which can become impractical for studying noncanonical and personalized neoantigens. Because the amount of HLA peptides eluted from biological samples such as small tissue biopsies is typically not sufficient for acquiring both meaningful DDA data necessary for generating comprehensive spectral libraries and DIA MS measurements, the implementation of DIA in the immunopeptidomics translational research domain has remained limited. We implemented a DIA immunopeptidomics workflow and assessed its sensitivity and accuracy by matching DIA data against libraries with growing complexity-from sample-specific libraries to libraries combining 2 to 40 different immunopeptidomics samples. Analyzing DIA immunopeptidomics data against a complex multi-HLA spectral library resulted in a two-fold increase in peptide identification compared with sample-specific library and in a three-fold increase compared with DDA measurements, yet with no detrimental effect on the specificity. Furthermore, we demonstrated the implementation of DIA for sensitive personalized neoantigen discovery through the analysis of DIA data with predicted MS/MS spectra of clinically relevant HLA ligands. We conclude that a comprehensive multi-HLA library for DIA approach in combination with MS/MS prediction is highly advantageous for clinical immunopeptidomics, especially when low amounts of biological samples are available.

Structural dissimilarity from self drives neoepitope escape from immune tolerance.

T-cell recognition of peptides incorporating nonsynonymous mutations, or neoepitopes, is a cornerstone of tumor immunity and forms the basis of new immunotherapy approaches including personalized cancer vaccines. Yet as they are derived from self-peptides, the means through which immunogenic neoepitopes overcome immune self-tolerance are often unclear. Here we show that a point mutation in a non-major histocompatibility complex anchor position induces structural and dynamic changes in an immunologically active ovarian cancer neoepitope. The changes pre-organize the peptide into a conformation optimal for recognition by a neoepitope-specific T-cell receptor, allowing the receptor to bind the neoepitope with high affinity and deliver potent T-cell signals. Our results emphasize the importance of structural and physical changes relative to self in neoepitope immunogenicity. Considered broadly, these findings can help explain some of the difficulties in identifying immunogenic neoepitopes from sequence alone and provide guidance for developing novel, neoepitope-based personalized therapies.

Deciphering and reversing tumor immune suppression.

Generating an anti-tumor immune response is a multi-step process that is executed by effector T cells that can recognize and kill tumor targets. However, tumors employ multiple strategies to attenuate the effectiveness of T-cell-mediated attack. They achieve this by interfering with nearly every step required for effective immunity, from deregulation of antigen-presenting cells to establishment of a physical barrier at the vasculature that prevents homing of effector tumor-rejecting cells and the suppression of effector lymphocytes through the recruitment and activation of immunosuppressive cells such as myeloid-derived suppressor cells, tolerogenic monocytes, and T regulatory cells. Here, we review the ways in which tumors exert immune suppression and highlight the new therapies that seek to reverse this phenomenon and promote anti-tumor immunity. Understanding anti-tumor immunity, and how it becomes disabled by tumors, will ultimately lead to improved immune therapies and prolonged survival of patients.

Mass Spectrometry Based Immunopeptidomics Leads to Robust Predictions of Phosphorylated HLA Class I Ligands.

The presentation of peptides on class I human leukocyte antigen (HLA-I) molecules plays a central role in immune recognition of infected or malignant cells. In cancer, non-self HLA-I ligands can arise from many different alterations, including non-synonymous mutations, gene fusion, cancer-specific alternative mRNA splicing or aberrant post-translational modifications. Identifying HLA-I ligands remains a challenging task that requires either heavy experimental work for in vivo identification or optimized bioinformatics tools for accurate predictions. To date, no HLA-I ligand predictor includes post-translational modifications. To fill this gap, we curated phosphorylated HLA-I ligands from several immunopeptidomics studies (including six newly measured samples) covering 72 HLA-I alleles and retrieved a total of 2,066 unique phosphorylated peptides. We then expanded our motif deconvolution tool to identify precise binding motifs of phosphorylated HLA-I ligands. Our results reveal a clear enrichment of phosphorylated peptides among HLA-C ligands and demonstrate a prevalent role of both HLA-I motifs and kinase motifs on the presentation of phosphorylated peptides. These data further enabled us to develop and validate the first predictor of interactions between HLA-I molecules and phosphorylated peptides.

Structure-based optimization of type III indoleamine 2,3-dioxygenase 1 (IDO1) inhibitors.

The haem enzyme indoleamine 2,3-dioxygenase 1 (IDO1) catalyses the rate-limiting step in the kynurenine pathway of tryptophan metabolism and plays an essential role in immunity, neuronal function, and ageing. Expression of IDO1 in cancer cells results in the suppression of an immune response, and therefore IDO1 inhibitors have been developed for use in anti-cancer immunotherapy. Here, we report an extension of our previously described highly efficient haem-binding 1,2,3-triazole and 1,2,4-triazole inhibitor series, the best compound having both enzymatic and cellular IC50 values of 34 nM. We provide enzymatic inhibition data for almost 100 new compounds and X-ray diffraction data for one compound in complex with IDO1. Structural and computational studies explain the dramatic drop in activity upon extension to pocket B, which has been observed in diverse haem-binding inhibitor scaffolds. Our data provides important insights for future IDO1 inhibitor design.

The C-terminal extension landscape of naturally presented HLA-I ligands.

HLA-I molecules play a central role in antigen presentation. They typically bind 9- to 12-mer peptides, and their canonical binding mode involves anchor residues at the second and last positions of their ligands. To investigate potential noncanonical binding modes, we collected in-depth and accurate HLA peptidomics datasets covering 54 HLA-I alleles and developed algorithms to analyze these data. Our results reveal frequent (442 unique peptides) and statistically significant C-terminal extensions for at least eight alleles, including the common HLA-A03:01, HLA-A31:01, and HLA-A68:01. High resolution crystal structure of HLA-A68:01 with such a ligand uncovers structural changes taking place to accommodate C-terminal extensions and helps unraveling sequence and structural properties predictive of the presence of these extensions. Scanning viral proteomes with the C-terminal extension motifs identifies many putative epitopes and we demonstrate direct recognition by human CD8+ T cells of a 10-mer epitope from cytomegalovirus predicted to follow the C-terminal extension binding mode.

Turning up the heat on non-immunoreactive tumours: opportunities for clinical development.

Notable advances have been achieved in the treatment of cancer since the advent of immunotherapy, and immune checkpoint inhibitors have shown clinical benefit across a wide variety of tumour types. Nevertheless, most patients still progress on these treatments, highlighting the importance of unravelling the underlying mechanisms of primary resistance to immunotherapy. A well described biomarker of non-responsiveness to immune checkpoint inhibitors is the absence or low presence of lymphocytes in the tumour microenvironment, so-called cold tumours. There are five mechanisms of action that have the potential to turn cold tumours into so-called hot and inflamed tumours, hence increasing the tumour's responsiveness to immunotherapy-increasing local inflammation, neutralising immunosuppression at the tumour site, modifying the tumour vasculature, targeting the tumour cells themselves, or increasing the frequency of tumour-specific T cells. In this Review, we discuss preclinical data that serves as the basis for ongoing immunotherapy clinical trials for the treatment of non-immunoreactive tumours, as well as reviewing clinical and translational data where available. We explain how improving our understanding of the underlying mechanisms of primary resistance to immunotherapy will help elucidate an increasingly granular view of the tumour microenvironment cellular composition, functional status, and cellular localisation, with the goal of further therapy refinement.

Multielemental Analysis of Low-Volume Samples Reveals Cancer-Specific Profile in Serum and Sorted Immune Cells.

We developed and validated a reliable, robust, and easy-to-implement quantitative method for multielemental analysis of low-volume samples. Our ICP-MS-based method comprises the analysis of 20 elements (Mg, P, S, K, Ca, V, Cr, Mn, Fe, Co, Cu, Zn, Se, Br, Rb, Sr, Mo, I, Cs, and Ba) in 10 µL of serum and 12 elements (Mg, S, Mn, Fe, Co, Cu, Zn Se, Br, Rb, Mo, and Cs) in less than 250 000 cells. As a proof-of-concept, we analyzed the elemental profiles of serum and sorted immune T cells derived from naïve and tumor-bearing mice. The results indicate a tumor systemic effect on the elemental profiles of both serum and T cells. Our approach highlights promising applications of multielemental analysis in precious samples such as rare cell populations or limited volumes of biofluids that could provide a deeper understanding of the essential role of elements as cofactors in biological and pathological processes.