Stem-like intestinal Th17 cells give rise to pathogenic effector T cells during autoimmunity.

While intestinal Th17 cells are critical for maintaining tissue homeostasis, recent studies have implicated their roles in the development of extra-intestinal autoimmune diseases including multiple sclerosis. However, the mechanisms by which tissue Th17 cells mediate these dichotomous functions remain unknown. Here, we characterized the heterogeneity, plasticity, and migratory phenotypes of tissue Th17 cells in vivo by combined fate mapping with profiling of the transcriptomes and TCR clonotypes of over 84,000 Th17 cells at homeostasis and during CNS autoimmune inflammation. Inter- and intra-organ single-cell analyses revealed a homeostatic, stem-like TCF1+ IL-17+ SLAMF6+ population that traffics to the intestine where it is maintained by the microbiota, providing a ready reservoir for the IL-23-driven generation of encephalitogenic GM-CSF+ IFN-γ+ CXCR6+ T cells. Our study defines a direct in vivo relationship between IL-17+ non-pathogenic and GM-CSF+ and IFN-γ+ pathogenic Th17 populations and provides a mechanism by which homeostatic intestinal Th17 cells direct extra-intestinal autoimmune disease.

Tim-3 adaptor protein Bat3 is a molecular checkpoint of T cell terminal differentiation and exhaustion.

T cell exhaustion has been associated with poor prognosis in persistent viral infection and cancer. Conversely, in the context of autoimmunity, T cell exhaustion has been favorably correlated with long-term clinical outcome. Understanding the development of exhaustion in autoimmune settings may provide underlying principles that can be exploited to quell autoreactive T cells. Here, we demonstrate that the adaptor molecule Bat3 acts as a molecular checkpoint of T cell exhaustion, with deficiency of Bat3 promoting a profound exhaustion phenotype, suppressing autoreactive T cell-mediated neuroinflammation. Mechanistically, Bat3 acts as a critical mTORC2 inhibitor to suppress Akt function. As a result, Bat3 deficiency leads to increased Akt activity and FoxO1 phosphorylation, indirectly promoting Prdm1 expression. Transcriptional analysis of Bat3 -/- T cells revealed up-regulation of dysfunction-associated genes, concomitant with down-regulation of genes associated with T cell effector function, suggesting that absence of Bat3 can trigger T cell dysfunction even under highly proinflammatory autoimmune conditions.

Blockade of IL-22 signaling reverses erythroid dysfunction in stress-induced anemias.

Patients with myelodysplastic syndromes (MDSs) display severe anemia but the mechanisms underlying this phenotype are incompletely understood. Right open-reading-frame kinase 2 (RIOK2) encodes a protein kinase located at 5q15, a region frequently lost in patients with MDS del(5q). Here we show that hematopoietic cell-specific haploinsufficient deletion of Riok2 (Riok2f/+Vav1cre) led to reduced erythroid precursor frequency leading to anemia. Proteomic analysis of Riok2f/+Vav1cre erythroid precursors suggested immune system activation, and transcriptomic analysis revealed an increase in p53-dependent interleukin (IL)-22 in Riok2f/+Vav1cre CD4+ T cells (TH22). Further, we discovered that the IL-22 receptor, IL-22RA1, was unexpectedly present on erythroid precursors. Blockade of IL-22 signaling alleviated anemia not only in Riok2f/+Vav1cre mice but also in wild-type mice. Serum concentrations of IL-22 were increased in the subset of patients with del(5q) MDS as well as patients with anemia secondary to chronic kidney disease. This work reveals a possible therapeutic opportunity for reversing many stress-induced anemias by targeting IL-22 signaling.

Single-cell analyses identify circulating anti-tumor CD8 T cells and markers for their enrichment.

The ability to monitor anti-tumor CD8+ T cell responses in the blood has tremendous therapeutic potential. Here, we used paired single-cell RNA and TCR sequencing to detect and characterize "tumor-matching" (TM) CD8+ T cells in the blood of mice with MC38 tumors or melanoma patients using the TCR as a molecular barcode. TM cells showed increased activation compared with nonmatching T cells in blood and were less exhausted than matching cells in tumors. Importantly, PD-1, which has been used to identify putative circulating anti-tumor CD8+ T cells, showed poor sensitivity for identifying TM cells. By leveraging the transcriptome, we identified candidate cell surface markers for TM cells in mice and patients and validated NKG2D, CD39, and CX3CR1 in mice. These data show that the TCR can be used to identify tumor-relevant cells for characterization, reveal unique transcriptional properties of TM cells, and develop marker panels for tracking and analysis of these cells.

Circulating clonally expanded T cells reflect functions of tumor-infiltrating T cells.

Understanding the relationship between tumor and peripheral immune environments could allow longitudinal immune monitoring in cancer. Here, we examined whether T cells that share the same TCRαß and are found in both tumor and blood can be interrogated to gain insight into the ongoing tumor T cell response. Paired transcriptome and TCRαß repertoire of circulating and tumor-infiltrating T cells were analyzed at the single-cell level from matched tumor and blood from patients with metastatic melanoma. We found that in circulating T cells matching clonally expanded tumor-infiltrating T cells (circulating TILs), gene signatures of effector functions, but not terminal exhaustion, reflect those observed in the tumor. In contrast, features of exhaustion are displayed predominantly by tumor-exclusive T cells. Finally, genes associated with a high degree of blood-tumor TCR sharing were overexpressed in tumor tissue after immunotherapy. These data demonstrate that circulating TILs have unique transcriptional patterns that may have utility for the interrogation of T cell function in cancer immunotherapy.

A bilateral tumor model identifies transcriptional programs associated with patient response to immune checkpoint blockade.

Immune checkpoint blockade (ICB) is efficacious in many diverse cancer types, but not all patients respond. It is important to understand the mechanisms driving resistance to these treatments and to identify predictive biomarkers of response to provide best treatment options for all patients. Here we introduce a resection and response-assessment approach for studying the tumor microenvironment before or shortly after treatment initiation to identify predictive biomarkers differentiating responders from nonresponders. Our approach builds on a bilateral tumor implantation technique in a murine metastatic breast cancer model (E0771) coupled with anti-PD-1 therapy. Using our model, we show that tumors from mice responding to ICB therapy had significantly higher CD8+ T cells and fewer Gr1+CD11b+ myeloid-derived suppressor cells (MDSCs) at early time points following therapy initiation. RNA sequencing on the intratumoral CD8+ T cells identified the presence of T cell exhaustion pathways in nonresponding tumors and T cell activation in responding tumors. Strikingly, we showed that our derived response and resistance signatures significantly segregate patients by survival and associate with patient response to ICB. Furthermore, we identified decreased expression of CXCR3 in nonresponding mice and showed that tumors grown in Cxcr3-/- mice had an elevated resistance rate to anti-PD-1 treatment. Our findings suggest that the resection and response tumor model can be used to identify response and resistance biomarkers to ICB therapy and guide the use of combination therapy to further boost the antitumor efficacy of ICB.

Endogenous Glucocorticoid Signaling Regulates CD8+ T Cell Differentiation and Development of Dysfunction in the Tumor Microenvironment.

Identifying signals in the tumor microenvironment (TME) that shape CD8+ T cell phenotype can inform novel therapeutic approaches for cancer. Here, we identified a gradient of increasing glucocorticoid receptor (GR) expression and signaling from naïve to dysfunctional CD8+ tumor-infiltrating lymphocytes (TILs). Conditional deletion of the GR in CD8+ TILs improved effector differentiation, reduced expression of the transcription factor TCF-1, and inhibited the dysfunctional phenotype, culminating in tumor growth inhibition. GR signaling transactivated the expression of multiple checkpoint receptors and promoted the induction of dysfunction-associated genes upon T cell activation. In the TME, monocyte-macrophage lineage cells produced glucocorticoids and genetic ablation of steroidogenesis in these cells as well as localized pharmacologic inhibition of glucocorticoid biosynthesis improved tumor growth control. Active glucocorticoid signaling associated with failure to respond to checkpoint blockade in both preclinical models and melanoma patients. Thus, endogenous steroid hormone signaling in CD8+ TILs promotes dysfunction, with important implications for cancer immunotherapy.

Layilin augments integrin activation to promote antitumor immunity.

Tumor-infiltrating CD8+ T cells mediate antitumor immune responses. However, the mechanisms by which T cells remain poised to kill cancer cells despite expressing high levels of inhibitory receptors are unknown. Here, we report that layilin, a C-type lectin domain-containing membrane glycoprotein, is selectively expressed on highly activated, clonally expanded, but phenotypically exhausted CD8+ T cells in human melanoma. Lineage-specific deletion of layilin on murine CD8+ T cells reduced their accumulation in tumors and increased tumor growth in vivo. Congruently, gene editing of LAYN in human CD8+ T cells reduced direct tumor cell killing ex vivo. On a molecular level, layilin colocalized with integrin αLß2 (LFA-1) on T cells, and cross-linking layilin promoted the activated state of this integrin. Accordingly, LAYN deletion resulted in attenuated LFA-1-dependent cellular adhesion. Collectively, our results identify layilin as part of a molecular pathway in which exhausted or "dysfunctional" CD8+ T cells enhance cellular adhesiveness to maintain their cytotoxic potential.

Combinatorial prediction of marker panels from single-cell transcriptomic data.

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).

Revolutionizing Cancer Immunology: The Power of Next-Generation Sequencing Technologies.

It has long been appreciated that tumors are diverse, varying in mutational status, composition of cellular infiltrate, and organizational architecture. For the most part, the information embedded in this diversity has gone untapped due to the limited resolution and dimensionality of assays for analyzing nucleic acid expression in cells. The advent of high-throughput, next-generation sequencing (NGS) technologies that measure nucleic acids, particularly at the single-cell level, is fueling the characterization of the many components that comprise the tumor microenvironment (TME), with a strong focus on immune composition. Understanding the immune and nonimmune components of the TME, how they interact, and how this shapes their functional properties requires the development of novel computational methods and, eventually, the application of systems-based approaches. The continued development and application of NGS technologies holds great promise for accelerating discovery in the cancer immunology field.

Induction and transcriptional regulation of the co-inhibitory gene module in T cells.

The expression of co-inhibitory receptors, such as CTLA-4 and PD-1, on effector T cells is a key mechanism for ensuring immune homeostasis. Dysregulated expression of co-inhibitory receptors on CD4+ T cells promotes autoimmunity, whereas sustained overexpression on CD8+ T cells promotes T cell dysfunction or exhaustion, leading to impaired ability to clear chronic viral infections and diseases such as cancer1,2. Here, using RNA and protein expression profiling at single-cell resolution in mouse cells, we identify a module of co-inhibitory receptors that includes not only several known co-inhibitory receptors (PD-1, TIM-3, LAG-3 and TIGIT) but also many new surface receptors. We functionally validated two new co-inhibitory receptors, activated protein C receptor (PROCR) and podoplanin (PDPN). The module of co-inhibitory receptors is co-expressed in both CD4+ and CD8+ T cells and is part of a larger co-inhibitory gene program that is shared by non-responsive T cells in several physiological contexts and is driven by the immunoregulatory cytokine IL-27. Computational analysis identified the transcription factors PRDM1 and c-MAF as cooperative regulators of the co-inhibitory module, and this was validated experimentally. This molecular circuit underlies the co-expression of co-inhibitory receptors in T cells and identifies regulators of T cell function with the potential to control autoimmunity and tumour immunity.

Effect of IL-7 Therapy on Phospho-Ribosomal Protein S6 and TRAF1 Expression in HIV-Specific CD8 T Cells in Patients Receiving Antiretroviral Therapy.

IL-7 therapy has been evaluated in patients who do not regain normal CD4 T cell counts after virologically successful antiretroviral therapy. IL-7 increases total circulating CD4 and CD8 T cell counts; however, its effect on HIV-specific CD8 T cells has not been fully examined. TRAF1, a prosurvival signaling adaptor required for 4-1BB-mediated costimulation, is lost from chronically stimulated virus-specific CD8 T cells with progression of HIV infection in humans and during chronic lymphocytic choriomeningitis infection in mice. Previous results showed that IL-7 can restore TRAF1 expression in virus-specific CD8 T cells in mice, rendering them sensitive to anti-4-1BB agonist therapy. In this article, we show that IL-7 therapy in humans increases the number of circulating HIV-specific CD8 T cells. For a subset of patients, we also observed an increased frequency of TRAF1+ HIV-specific CD8 T cells 10 wk after completion of IL-7 treatment. IL-7 treatment increased levels of phospho-ribosomal protein S6 in HIV-specific CD8 T cells, suggesting increased activation of the metabolic checkpoint kinase mTORC1. Thus, IL-7 therapy in antiretroviral therapy-treated patients induces sustained changes in the number and phenotype of HIV-specific T cells.

Molecular Dissection of CD8+ T-Cell Dysfunction.

Chronic viral infections and cancer often lead to the emergence of dysfunctional or 'exhausted' CD8+ T cells, and the restoration of their functions is currently the focus of therapeutic interventions. In this review, we detail recent advances in the annotation of the gene modules and the epigenetic landscape associated with T-cell dysfunction. Together with analysis of single-cell transcriptomes, these findings have enabled a deeper and more precise understanding of the transcriptional mechanisms that induce and maintain the dysfunctional state and highlight the heterogeneity of CD8+ T-cell phenotypes present in chronically inflamed tissue. We discuss the relevance of these findings for understanding the transcriptional and spatial regulation of dysfunctional T cells and for the design of therapeutics.

Purine synthesis promotes maintenance of brain tumor initiating cells in glioma.

Brain tumor initiating cells (BTICs), also known as cancer stem cells, hijack high-affinity glucose uptake active normally in neurons to maintain energy demands. Here we link metabolic dysregulation in human BTICs to a nexus between MYC and de novo purine synthesis, mediating glucose-sustained anabolic metabolism. Inhibiting purine synthesis abrogated BTIC growth, self-renewal and in vivo tumor formation by depleting intracellular pools of purine nucleotides, supporting purine synthesis as a potential therapeutic point of fragility. In contrast, differentiated glioma cells were unaffected by the targeting of purine biosynthetic enzymes, suggesting selective dependence of BTICs. MYC coordinated the control of purine synthetic enzymes, supporting its role in metabolic reprogramming. Elevated expression of purine synthetic enzymes correlated with poor prognosis in glioblastoma patients. Collectively, our results suggest that stem-like glioma cells reprogram their metabolism to self-renew and fuel the tumor hierarchy, revealing potential BTIC cancer dependencies amenable to targeted therapy.

A Distinct Gene Module for Dysfunction Uncoupled from Activation in Tumor-Infiltrating T Cells.

Reversing the dysfunctional T cell state that arises in cancer and chronic viral infections is the focus of therapeutic interventions; however, current therapies are effective in only some patients and some tumor types. To gain a deeper molecular understanding of the dysfunctional T cell state, we analyzed population and single-cell RNA profiles of CD8(+) tumor-infiltrating lymphocytes (TILs) and used genetic perturbations to identify a distinct gene module for T cell dysfunction that can be uncoupled from T cell activation. This distinct dysfunction module is downstream of intracellular metallothioneins that regulate zinc metabolism and can be identified at single-cell resolution. We further identify Gata-3, a zinc-finger transcription factor in the dysfunctional module, as a regulator of dysfunction, and we use CRISPR-Cas9 genome editing to show that it drives a dysfunctional phenotype in CD8(+) TILs. Our results open novel avenues for targeting dysfunctional T cell states while leaving activation programs intact.

Controlling for conservation in genome-wide DNA methylation studies.

BACKGROUND: A commonplace analysis in high-throughput DNA methylation studies is the comparison of methylation extent between different functional regions, computed by averaging methylation states within region types and then comparing averages between regions. For example, it has been reported that methylation is more prevalent in coding regions as compared to their neighboring introns or UTRs, leading to hypotheses about novel forms of epigenetic regulation. RESULTS: We have identified and characterized a bias present in these seemingly straightforward comparisons that results in the false detection of differences in methylation intensities across region types. This bias arises due to differences in conservation rates, rather than methylation rates, and is broadly present in the published literature. When controlling for conservation at coding start sites the differences in DNA methylation rates disappear. Moreover, a re-evaluation of methylation rates at intronexon junctions reveals that the magnitude of previously reported differences is greatly exaggerated. We introduce two correction methods to address this bias, an inferencebased matrix completion algorithm and an averaging approach, tailored to address different underlying biological questions. We evaluate how analysis using these corrections affects the detection of differences in DNA methylation across functional boundaries. CONCLUSIONS: We report here on a bias in DNA methylation comparative studies that originates in conservation rate differences and manifests itself in the false discovery of differences in DNA methylation intensities and their extents. We have characterized this bias and its broad implications, and show how to control for it so as to enable the study of a variety of biological questions.

A diverse epigenetic landscape at human exons with implication for expression.

DNA methylation is an important epigenetic marker associated with gene expression regulation in eukaryotes. While promoter methylation is relatively well characterized, the role of intragenic DNA methylation remains unclear. Here, we investigated the relationship of DNA methylation at exons and flanking introns with gene expression and histone modifications generated from a human fibroblast cell-line and primary B cells. Consistent with previous work we found that intragenic methylation is positively correlated with gene expression and that exons are more highly methylated than their neighboring intronic environment. Intriguingly, in this study we identified a unique subset of hypomethylated exons that demonstrate significantly lower methylation levels than their surrounding introns. Furthermore, we observed a negative correlation between exon methylation and the density of the majority of histone modifications. Specifically, we demonstrate that hypo-methylated exons at highly expressed genes are associated with open chromatin and have a characteristic histone code comprised of significantly high levels of histone markings. Overall, our comprehensive analysis of the human exome supports the presence of regulatory hypomethylated exons in protein coding genes. In particular our results reveal a previously unrecognized diverse and complex role of the epigenetic landscape within the gene body.

Identification and correction of systematic error in high-throughput sequence data.

BACKGROUND: A feature common to all DNA sequencing technologies is the presence of base-call errors in the sequenced reads. The implications of such errors are application specific, ranging from minor informatics nuisances to major problems affecting biological inferences. Recently developed "next-gen" sequencing technologies have greatly reduced the cost of sequencing, but have been shown to be more error prone than previous technologies. Both position specific (depending on the location in the read) and sequence specific (depending on the sequence in the read) errors have been identified in Illumina and Life Technology sequencing platforms. We describe a new type of systematic error that manifests as statistically unlikely accumulations of errors at specific genome (or transcriptome) locations. RESULTS: We characterize and describe systematic errors using overlapping paired reads from high-coverage data. We show that such errors occur in approximately 1 in 1000 base pairs, and that they are highly replicable across experiments. We identify motifs that are frequent at systematic error sites, and describe a classifier that distinguishes heterozygous sites from systematic error. Our classifier is designed to accommodate data from experiments in which the allele frequencies at heterozygous sites are not necessarily 0.5 (such as in the case of RNA-Seq), and can be used with single-end datasets. CONCLUSIONS: Systematic errors can easily be mistaken for heterozygous sites in individuals, or for SNPs in population analyses. Systematic errors are particularly problematic in low coverage experiments, or in estimates of allele-specific expression from RNA-Seq data. Our characterization of systematic error has allowed us to develop a program, called SysCall, for identifying and correcting such errors. We conclude that correction of systematic errors is important to consider in the design and interpretation of high-throughput sequencing experiments.