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T cell immunoglobulin and mucin domain-containing protein 3 (TIM3), a member of the TIM family, was originally identified as a receptor expressed on interferon-γ-producing CD4+ and CD8+ T cells. Initial data indicated that TIM3 functioned as a ‘co-inhibitory’ or ‘checkpoint’ receptor, but due to the lack of a definable inhibitory signalling motif, it was also suggested that TIM3 might act as a co-stimulatory receptor. Recent studies have shown that TIM3 is part of a module that contains multiple co-inhibitory receptors (checkpoint receptors), which are co-expressed and co-regulated on dysfunctional or ‘exhausted’ T cells in chronic viral infections and cancer. Furthermore, co-blockade of TIM3 and programmed cell death 1 (PD1) can result in tumour regression in preclinical models and can improve anticancer T cell responses in patients with advanced cancers. Here, we highlight the developments in understanding TIM3 biology, including novel ligand identification and the discovery of loss-of-function mutations associated with human disease. In addition, we summarize emerging data from human clinical trials showing that TIM3 indeed acts as a ‘checkpoint’ receptor and that inhibition of TIM3 enhances the antitumour effect of PD1 blockade.The co-inhibitory receptor TIM3 can serve as a marker of exhausted T cells. Here, the authors investigate the biology of TIM3, discussing its various ligands, signalling pathways and association with human disease. They also provide an overview of emerging clinical data regarding its potential as an anticancer target in combination with PD1 blockade.

Co-inhibitory receptors are important regulators of T-cell function that define the balance between tolerance and autoimmunity. The immune regulatory function of co-inhibitory receptors, including CTLA-4, PD-1, TIM-3, TIGIT, and LAG-3, was first discovered in the setting of autoimmune disease models, in which their blockade or deficiency resulted in induction or exacerbation of the disease. Later on, co-inhibitory receptors on lymphocytes have also been found to influence outcomes in tumor and chronic viral infection settings. These receptors suppress T-cell function in the tumor microenvironment (TME), thereby making the T cells dysfunctional. Based on this observation, blockade of co-inhibitory receptors (also known as checkpoint molecules) has emerged as a successful treatment option for a number of human cancers. However, severe autoimmune-like side effects limit the use of therapeutics that block individual or combinations of co-inhibitory receptors for cancer treatment. In this review we provide an overview of the role of co-inhibitory receptors in autoimmunity and anti-tumor immunity. We then discuss current approaches and future directions to leverage our knowledge of co-inhibitory receptors to target them in tumor immunity without inducing autoimmunity.

The role of B cells in anti-tumour immunity is still debated and, accordingly, immunotherapies have focused on targeting T and natural killer cells to inhibit tumour growth 1 , 2 . Here, using high-throughput flow cytometry as well as bulk and single-cell RNA-sequencing and B-cell-receptor-sequencing analysis of B cells temporally during B16F10 melanoma growth, we identified a subset of B cells that expands specifically in the draining lymph node over time in tumour-bearing mice. The expanding B cell subset expresses the cell surface molecule T cell immunoglobulin and mucin domain 1 (TIM-1, encoded by Havcr1 ) and a unique transcriptional signature, including multiple co-inhibitory molecules such as PD-1, TIM-3, TIGIT and LAG-3. Although conditional deletion of these co-inhibitory molecules on B cells had little or no effect on tumour burden, selective deletion of Havcr1 in B cells both substantially inhibited tumour growth and enhanced effector T cell responses. Loss of TIM-1 enhanced the type 1 interferon response in B cells, which augmented B cell activation and increased antigen presentation and co-stimulation, resulting in increased expansion of tumour-specific effector T cells. Our results demonstrate that manipulation of TIM-1-expressing B cells enables engagement of the second arm of adaptive immunity to promote anti-tumour immunity and inhibit tumour growth. Manipulation of TIM-1-expressing B cells enables engagement of the second arm of adaptive immunity to promote anti-tumour immunity and inhibit tumour growth.

CD4 + effector T cells have been categorized into two subsets: T helper type 1 (T H 1) and T H 2. Another subset of T cells that produce interleukin 17 (IL-17; 'T H -17 cells') has been identified that is highly proinflammatory and induces severe autoimmunity. Whereas IL-23 serves to expand previously differentiated T H -17 cell populations, IL-6 and transforming growth factor-β (TGF-β) induce the differentiation of T H -17 cells from naive precursors. These data suggest a dichotomy between CD4 + regulatory T cells positive for the transcription factor Foxp3 and T H -17 cells: TGF-β induces Foxp3 and generates induced regulatory T cells, whereas IL-6 inhibits TGF-β-driven Foxp3 expression and together with TGF-β induces T H -17 cells. Emerging data regarding T H -17 cells suggest a very important function for this T cell subset in immunity and disease.

T helper 17 cells: Induction and effector functions The recently discovered T H 17 cells, the third subset of effector T helper cells, are the subject of intensive research. They produce the cytokine interleukin-17, coordinate defence against specific pathogens and mediate tissue inflammation. Bettelli et al . review this fast-moving field, focusing on the emergence of the balance between pro-inflammatory TH17 cells and inhibitory T reg cells as key factor in many inflammatory and autoimmune diseases. T helper (T H ) cells constitute an important arm of the adaptive immune system because they coordinate defence against specific pathogens, and their unique cytokines and effector functions mediate different types of tissue inflammation. The recently discovered T H 17 cells, the third subset of effector T helper cells, have been the subject of intense research aimed at understanding their role in immunity and disease. Here we review emerging data suggesting that T H 17 cells have an important role in host defence against specific pathogens and are potent inducers of autoimmunity and tissue inflammation. In addition, the differentiation factors responsible for their generation have revealed an interesting reciprocal relationship with regulatory T (T reg ) cells, which prevent tissue inflammation and mediate self-tolerance.

Cytokines play a critical role in controlling the differentiation of CD4 Th cells into distinct subsets, including IL-17-producing Th17 cells. Unfortunately, the incidence of a number of autoimmune diseases, particularly those in which the IL-23/IL-17 axis has been implicated, has risen in the last several decades, suggesting that environmental factors can promote autoimmunity. Here we review the role of cytokines in Th17 differentiation, particularly the role of IL-23 in promoting the differentiation of a pathogenic subset of Th17 cells that potently induce autoimmune tissue inflammation. Moreover, we highlight emerging data that indicate that environmental factors, including the intestinal microbiota and changes in diet, can alter normal cytokine regulation with potent effects on Th17 differentiation and thus promote autoimmunity, which has strong implications for human disease.

While T cell immunity initially limits Mycobacterium tuberculosis infection, why T cell immunity fails to sterilize the infection and allows recrudescence is not clear. One hypothesis is that T cell exhaustion impairs immunity and is detrimental to the outcome of M. tuberculosis infection. Here we provide functional evidence for the development T cell exhaustion during chronic TB. Second, we evaluate the role of the inhibitory receptor T cell immunoglobulin and mucin domain-containing-3 (TIM3) during chronic M. tuberculosis infection. We find that TIM3 expressing T cells accumulate during chronic infection, co-express other inhibitory receptors including PD1, produce less IL-2 and TNF but more IL-10, and are functionally exhausted. Finally, we show that TIM3 blockade restores T cell function and improves bacterial control, particularly in chronically infected susceptible mice. These data show that T cell immunity is suboptimal during chronic M. tuberculosis infection due to T cell exhaustion. Moreover, in chronically infected mice, treatment with anti-TIM3 mAb is an effective therapeutic strategy against tuberculosis.

Genome-wide association studies have identified loci underlying human diseases, but the causal nucleotide changes and mechanisms remain largely unknown. Here we developed a fine-mapping algorithm to identify candidate causal variants for 21 autoimmune diseases from genotyping data. We integrated these predictions with transcription and cis -regulatory element annotations, derived by mapping RNA and chromatin in primary immune cells, including resting and stimulated CD4 + T-cell subsets, regulatory T cells, CD8 + T cells, B cells, and monocytes. We find that ∼90% of causal variants are non-coding, with ∼60% mapping to immune-cell enhancers, many of which gain histone acetylation and transcribe enhancer-associated RNA upon immune stimulation. Causal variants tend to occur near binding sites for master regulators of immune differentiation and stimulus-dependent gene activation, but only 10–20% directly alter recognizable transcription factor binding motifs. Rather, most non-coding risk variants, including those that alter gene expression, affect non-canonical sequence determinants not well-explained by current gene regulatory models. Genome-wide association studies combined with data from epigenomic maps for immune cells have been used to fine-map causal variants for 21 autoimmune diseases; disease risk tends to be linked to single nucleotide polymorphisms in cell-type-specific enhancers, often in regions adjacent to transcription factor binding motifs. Gene variation in autoimmune diseases Hundreds of risk loci for autoimmunity have been identified previously in genome-wide association studies (GWASs), but the implicated loci comprise multiple variants in linkage disequilibrium and rarely alter protein-coding sequence, which complicates their interpretation. This study adopts a new approach for fine mapping causal genetic variants for 21 autoimmune diseases, applying a novel algorithm to GWAS-based loci and integrating genotypic data with epigenomic maps for specialized immune cells. The results implicate a very specific subset of enhancers involved in T-cell stimulation as causal determinants of autoimmune diseases.

Tr1 cells have potent regulatory effects in vitro and in vivo . Kuchroo and colleagues comprehensively describe the epigenetic, transcriptional and gene regulatory landscape that is essential for Tr1 cell differentiation. Type 1 regulatory T cells (Tr1 cells) are induced by interleukin-27 (IL-27) and have critical roles in the control of autoimmunity and resolution of inflammation. We found that the transcription factors IRF1 and BATF were induced early on after treatment with IL-27 and were required for the differentiation and function of Tr1 cells in vitro and in vivo . Epigenetic and transcriptional analyses revealed that both transcription factors influenced chromatin accessibility and expression of the genes required for Tr1 cell function. IRF1 and BATF deficiencies uniquely altered the chromatin landscape, suggesting that these factors serve a pioneering function during Tr1 cell differentiation.

Single‐cell transcriptomic studies are identifying novel cell populations with exciting functional roles in various in vivo contexts, but identification of succinct gene marker panels for such populations remains a challenge. In this work, we introduce COMET, a computational framework for the identification of candidate marker panels consisting of one or more genes for cell populations of interest identified with single‐cell RNA‐seq data. We show that COMET outperforms other methods for the identification of single‐gene panels and enables, for the first time, prediction of multi‐gene marker panels ranked by relevance. Staining by flow cytometry assay confirmed the accuracy of COMET's predictions in identifying marker panels for cellular subtypes, at both the single‐ and multi‐gene levels, validating COMET's applicability and accuracy in predicting favorable marker panels from transcriptomic input. COMET is a general non‐parametric statistical framework and can be used as‐is on various high‐throughput datasets in addition to single‐cell RNA‐sequencing data. COMET is available for use via a web interface ( http://www.cometsc.com/ ) or a stand‐alone software package ( https://github.com/MSingerLab/COMETSC ). Synopsis COMET is a computational tool for marker‐panel selection from single‐cell RNA‐seq data. It generates ranked predictions of single‐ and multiple‐gene marker panels for a cell population of interest. COMET is a computational tool for combinatorial prediction of marker panels from single‐cell transcriptomic data. COMET's statistical framework enables controlling for specificity and sensitivity in predicted marker panels. Staining by flow‐cytometry validates that COMET identifies novel and favorable single‐ and multi‐gene marker panels for cellular subtypes. COMET is available via a web interface ( http://www.cometsc.com/ ) or downloadable software package ( https://github.com/MSingerLab/COMETSC ). Graphical Abstract COMET is a computational tool for marker‐panel selection from single‐cell RNA‐seq data. It generates ranked predictions of single‐ and multiple‐gene marker panels for a cell population of interest.