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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.

Treatment of high-grade serous ovarian cancer (HGSOC) remains challenging. Although HGSOC can potentially be responsive to immunotherapy owing to endogenous immunity at the molecular or T cell level, immunotherapy for this disease has fallen short of expectations to date. This Review proposes a working classification for HGSOC based on the presence or absence of intraepithelial T cells, and elaborates the putative mechanisms that give rise to such immunophenotypes. These differences might explain the failures of existing immunotherapies, and suggest that rational therapeutic approaches tailored to each immunophenotype might meet with improved success. In T cell-inflamed tumours, treatment could focus on mobilizing pre-existing immunity and strengthening the activation of T cells embedded in intraepithelial tumour myeloid niches. Conversely, in immune-excluded and immune-desert tumours, treatment could focus on restoring inflammation by reprogramming myeloid cells, stromal cells and vascular epithelial cells. Poly(ADP-ribose) polymerase (PARP) inhibitors, low-dose radiotherapy, epigenetic drugs and anti-angiogenesis therapy are among the tools available to restore T cell infiltration in HGSOC tumours and could be implemented in combination with vaccines and redirected T cells.Clinical trials of immunotherapies have so far failed to demonstrate efficacy in high-grade serous ovarian cancers. Here, Kandalaft et al. classify high-grade serous ovarian cancers into distinct immunophenotypes that might account for these failures and could also provide a rational basis for tailored immunotherapy in the future.

Single-cell RNA sequencing (scRNA-seq) has revealed an unprecedented degree of immune cell diversity. However, consistent definition of cell subtypes and cell states across studies and diseases remains a major challenge. Here we generate reference T cell atlases for cancer and viral infection by multi-study integration, and develop ProjecTILs, an algorithm for reference atlas projection. In contrast to other methods, ProjecTILs allows not only accurate embedding of new scRNA-seq data into a reference without altering its structure, but also characterizing previously unknown cell states that “deviate” from the reference. ProjecTILs accurately predicts the effects of cell perturbations and identifies gene programs that are altered in different conditions and tissues. A meta-analysis of tumor-infiltrating T cells from several cohorts reveals a strong conservation of T cell subtypes between human and mouse, providing a consistent basis to describe T cell heterogeneity across studies, diseases, and species. One challenge of single cell RNA sequencing analysis is how to consistently identify cell subtypes and states across different datasets. Here the authors propose the use of a reference single-cell atlas as a stable system of coordinates to characterize T cell states across studies, diseases and species.

T cells play a critical role in cancer control, but a range of potent immunosuppressive mechanisms can be upregulated in the tumor microenvironment (TME) to abrogate their activity. While various immunotherapies (IMTs) aiming at re-invigorating the T-cell-mediated anti-tumor response, such as immune checkpoint blockade (ICB), and the adoptive cell transfer (ACT) of natural or gene-engineered expanded tumor-specific T cells, have led to unprecedented clinical responses, only a small proportion of cancer patients benefit from these treatments. Important research efforts are thus underway to identify biomarkers of response, as well as to develop personalized combinatorial approaches that can target other inhibitory mechanisms at play in the TME. In recent years, adenosinergic signaling has emerged as a powerful immuno-metabolic checkpoint in tumors. Like several other barriers in the TME, such as the PD-1/PDL-1 axis, CTLA-4, and indoleamine 2,3-dioxygenase (IDO-1), adenosine plays important physiologic roles, but has been co-opted by tumors to promote their growth and impair immunity. Several agents counteracting the adenosine axis have been developed, and pre-clinical studies have demonstrated important anti-tumor activity, alone and in combination with other IMTs including ICB and ACT. Here we review the regulation of adenosine levels and mechanisms by which it promotes tumor growth and broadly suppresses protective immunity, with extra focus on the attenuation of T cell function. Finally, we present an overview of promising pre-clinical and clinical approaches being explored for blocking the adenosine axis for enhanced control of solid tumors.

Except for its use in palliative care, radiotherapy has been largely abandoned in the management of ovarian cancer because of the recognised efficacy and lower toxicity of systemic chemotherapy compared with radiotherapy. New data have emerged that show synergy of radiotherapy with immunotherapy to control or eradicate cancer. Different doses of hypofractionated radiotherapy have been shown to induce immunogenic cell death and in-situ vaccination in several tumour models. However, doses less than 2 Gy can also reprogramme the tumour microenvironment. This Series paper discusses the past and present use of radiotherapy for ovarian cancer, and the mechanisms by which radiotherapy can mobilise anticancer immunity. We provide emerging preclinical and clinical data for combining immunotherapy with radiotherapy for ovarian cancer treatment and offer a clinical development roadmap to guide the next generation of clinical trials for this combination strategy for this disease.

Predictions of epitopes presented by class II human leukocyte antigen molecules (HLA-II) have limited accuracy, restricting vaccine and therapy design. Here we combined unbiased mass spectrometry with a motif deconvolution algorithm to profile and analyze a total of 99,265 unique peptides eluted from HLA-II molecules. We then trained an epitope prediction algorithm with these data and improved prediction of pathogen and tumor-associated class II neoepitopes.

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.

The precise identification of Human Leukocyte Antigen class I (HLA-I) binding motifs plays a central role in our ability to understand and predict (neo-)antigen presentation in infectious diseases and cancer. Here, by exploiting co-occurrence of HLA-I alleles across ten newly generated as well as forty public HLA peptidomics datasets comprising more than 115,000 unique peptides, we show that we can rapidly and accurately identify many HLA-I binding motifs and map them to their corresponding alleles without any a priori knowledge of HLA-I binding specificity. Our approach recapitulates and refines known motifs for 43 of the most frequent alleles, uncovers new motifs for 9 alleles that up to now had less than five known ligands and provides a scalable framework to incorporate additional HLA peptidomics studies in the future. The refined motifs improve neo-antigen and cancer testis antigen predictions, indicating that unbiased HLA peptidomics data are ideal for in silico predictions of neo-antigens from tumor exome sequencing data. The new motifs further reveal distant modulation of the binding specificity at P2 for some HLA-I alleles by residues in the HLA-I binding site but outside of the B-pocket and we unravel the underlying mechanisms by protein structure analysis, mutagenesis and in vitro binding assays.

Mutation-derived neoantigens are taking central stage as a determinant in eliciting effective antitumor immune responses following adoptive T-cell therapies. These mutations are patient-specific, and their targeting calls for highly personalized pipelines. The promising clinical outcomes of tumor-infiltrating lymphocyte (TIL) therapy have spurred interest in generating T-cell infusion products that have been selectively enriched in neoantigen (or autologous tumor) reactivity. The implementation of an isolation step, prior to T-cell expansion and reinfusion, may provide a way to improve the overall response rates achieved to date by adoptive T-cell therapies in metastatic cancer patients. Here we provide an overview of the main technologies [i.e., peptide major histocompatibility complex (pMHC) multimers, cytokine capture, and activation markers] to enrich infiltrating or circulating T-cells in predefined neoantigen specificities (or tumor reactivity). The unique technical and regulatory challenges faced by such highly specialized and patient-specific manufacturing T-cell platforms are also discussed.

Efforts to precisely identify tumor human leukocyte antigen (HLA) bound peptides capable of mediating T cell-based tumor rejection still face important challenges. Recent studies suggest that non-canonical tumor-specific HLA peptides derived from annotated non-coding regions could elicit anti-tumor immune responses. However, sensitive and accurate mass spectrometry (MS)-based proteogenomics approaches are required to robustly identify these non-canonical peptides. We present an MS-based analytical approach that characterizes the non-canonical tumor HLA peptide repertoire, by incorporating whole exome sequencing, bulk and single-cell transcriptomics, ribosome profiling, and two MS/MS search tools in combination. This approach results in the accurate identification of hundreds of shared and tumor-specific non-canonical HLA peptides, including an immunogenic peptide derived from an open reading frame downstream of the melanoma stem cell marker gene ABCB5 . These findings hold great promise for the discovery of previously unknown tumor antigens for cancer immunotherapy. Non-canonical HLA-bound peptides from presumed non-coding regions are potential targets for cancer immunotherapy, but their discovery remains challenging. Here, the authors integrate exome sequencing, transcriptomics, ribosome profiling, and immunopeptidomics to identify tumor-specific non-canonical HLA-bound peptides.