Spatial maps of T cell receptors and transcriptomes reveal distinct immune niches and interactions in the adaptive immune response.

T cells mediate antigen-specific immune responses to disease through the specificity and diversity of their clonotypic T cell receptors (TCRs). Determining the spatial distributions of T cell clonotypes in tissues is essential to understanding T cell behavior, but spatial sequencing methods remain unable to profile the TCR repertoire. Here, we developed Slide-TCR-seq, a 10-µm-resolution method, to sequence whole transcriptomes and TCRs within intact tissues. We confirmed the ability of Slide-TCR-seq to map the characteristic locations of T cells and their receptors in mouse spleen. In human lymphoid germinal centers, we identified spatially distinct TCR repertoires. Profiling T cells in renal cell carcinoma and melanoma specimens revealed heterogeneous immune responses: T cell states and infiltration differed intra- and inter-clonally, and adjacent tumor and immune cells exhibited distinct gene expression. Altogether, our method yields insights into the spatial relationships between clonality, neighboring cell types, and gene expression that drive T cell responses.

Landscape of helper and regulatory antitumour CD4+ T cells in melanoma.

Within the tumour microenvironment, CD4+ T cells can promote or suppress antitumour responses through the recognition of antigens presented by human leukocyte antigen (HLA) class II molecules1,2, but how cancers co-opt these physiologic processes to achieve immune evasion remains incompletely understood. Here we performed in-depth analysis of the phenotype and tumour specificity of CD4+ T cells infiltrating human melanoma specimens, finding that exhausted cytotoxic CD4+ T cells could be directly induced by melanoma cells through recognition of HLA class II-restricted neoantigens, and also HLA class I-restricted tumour-associated antigens. CD4+ T regulatory (TReg) cells could be indirectly elicited through presentation of tumour antigens via antigen-presenting cells. Notably, numerous tumour-reactive CD4+ TReg clones were stimulated directly by HLA class II-positive melanoma and demonstrated specificity for melanoma neoantigens. This phenomenon was observed in the presence of an extremely high tumour neoantigen load, which we confirmed to be associated with HLA class II positivity through the analysis of 116 melanoma specimens. Our data reveal the landscape of infiltrating CD4+ T cells in melanoma and point to the presentation of HLA class II-restricted neoantigens and direct engagement of immunosuppressive CD4+ TReg cells as a mechanism of immune evasion that is favoured in HLA class II-positive melanoma.

A Pooled Analysis of 3 Phase II Trials of Salvage Nivolumab/Ipilimumab After Nivolumab in Renal Cell Carcinoma.

BACKGROUND: Nivolumab plus ipilimumab has demonstrated improved survival for treatment-naïve advanced clear cell renal cell carcinoma (RCC). A series of clinical trials evaluated the effect of salvage nivolumab plus ipilimumab in patients without an objective response to nivolumab. Given the size and heterogeneity of these studies, we performed a pooled analysis to better inform the activity of nivolumab plus ipilimumab after nivolumab. PATIENTS AND METHODS: Eligible patients included those with advanced clear cell RCC having received no prior immunotherapy. The primary objective was confirmed objective response rate (ORR) by investigator-assessment. Secondary objectives included progression-free survival (PFS) and overall survival (OS). RESULTS: The analysis included 410 patients with clear cell RCC, of whom 340 (82.9%) had IMDC intermediate/poor risk disease, and 137 (33.4%) had prior treatment. The 16-18-week ORR to nivolumab prior to nivolumab plus ipilimumab was 22.7% (n = 93), and best ORR to nivolumab was 25.1% (n = 103). Two hundred and thirty (56.1%) patients treated with nivolumab received nivolumab plus ipilimumab at a median of 16 weeks (IQR 9-19) after initiation of nivolumab [27.0% (n = 62) with stable disease and 73.0% (n = 168) with progressive disease to nivolumab]. The ORR to nivolumab plus ipilimumab was 12.6% (n = 29). Six-month PFS on nivolumab plus ipilimumab was 37% (95% CI, 27-47). Median follow-up was 34.3 months and 3-year OS was 59% (95% CI, 53-64) from nivolumab start. CONCLUSION: A small subset of patients lacking a response to nivolumab derive benefit from salvage nivolumab plus ipilimumab. When possible, both drugs should be given in concomitantly, rather in an adaptive fashion.

TIGIT expression in renal cell carcinoma infiltrating T cells is variable and inversely correlated with PD-1 and LAG3.

PURPOSE: Immune checkpoint inhibitors have revolutionized the treatment of renal cell carcinoma (RCC), but many patients do not respond to therapy and the majority develop resistant disease over time. Thus, there is increasing need for alternative immunomodulating agents. The co-inhibitory molecule T-cell immunoglobulin and ITIM domain (TIGIT) may play a role in resistance to approved immune checkpoint inhibitors and is being investigated as a potential therapeutic target. The purpose of this study was to quantify TIGIT positivity in tumor-infiltrating T cells in RCC. METHODS: We employed tissue microarrays containing specimens from primary RCC tumors, adjacent normal renal tissue, and RCC metastases to quantify TIGIT within tumor-infiltrating CD3+ T cells using quantitative immunofluorescent analysis. We also compared these results to TIGIT+ CD3+ levels in four other tumor types (melanoma, non-small cell lung, cervical, and head and neck cancers). RESULTS: We did not observe significant differences in TIGIT positivity between primary RCC tumors and patient-matched metastatic samples. We found that the degree of TIGIT positivity in RCC is comparable to that in lung cancer but lower than that in melanoma, cervical, and head and neck cancers. Correlation analysis comparing TIGIT positivity to previously published, patient-matched spatial proteomic data by our group revealed a negative association between TIGIT and the checkpoint proteins PD-1 and LAG3. CONCLUSION: Our findings support careful evaluation of TIGIT expression on T cells in primary or metastatic RCC specimens for patients who may be treated with TIGIT-targeting antibodies, as increased TIGIT positivity might be associated with a greater likelihood of response to therapy.

Reactive and proactive control processes in voluntary task choice.

Deciding which task to perform when multiple tasks are available can be influenced by external influences in the environment. In the present study, we demonstrate that such external biases on task-choice behavior reflect reactive control adjustments instead of a failure in control to internally select a task goal. Specifically, in two experiments we delayed the onset of one of two task stimuli by a short (50 ms), medium (300 ms), or long (1,000 ms) stimulus-onset asynchrony (SOA) within blocks while also varying the relative frequencies of short versus long SOAs across blocks (i.e., short SOA frequent vs. long SOA frequent). Participants' task choices were increasingly biased towards selecting the task associated with the first stimulus with increasing SOAs. Critically, both experiments also revealed that the short-to-medium SOA bias was larger in blocks with more frequent long SOAs when participants had limited time to prepare for an upcoming trial. When time to select an upcoming task was extended in Experiment 2, this interaction was not significant, suggesting that the extent to which people rely on reactive control adjustments is additionally modulated by proactive control processes. Thus, the present findings also suggest that voluntary task choices are jointly guided by both proactive and reactive processes, which are likely to adjust the relative activation of different task goals in working memory.

Optimized Liquid and Gas Phase Fractionation Increases HLA-Peptidome Coverage for Primary Cell and Tissue Samples.

MS is the most effective method to directly identify peptides presented on human leukocyte antigen (HLA) molecules. However, current standard approaches often use 500 million or more cells as input to achieve high coverage of the immunopeptidome, and therefore, these methods are not compatible with the often limited amounts of tissue available from clinical tumor samples. Here, we evaluated microscaled basic reversed-phase fractionation to separate HLA peptide samples offline followed by ion mobility coupled to LC-MS/MS for analysis. The combination of these two separation methods enabled identification of 20% to 50% more peptides compared with samples analyzed without either prior fractionation or use of ion mobility alone. We demonstrate coverage of HLA immunopeptidomes with up to 8107 distinct peptides starting with as few as 100 million cells. The increased sensitivity obtained using our methods can provide data useful to improve HLA-binding prediction algorithms as well as to enable detection of clinically relevant epitopes such as neoantigens.

HLA-A*03 and response to immune checkpoint blockade in cancer: an epidemiological biomarker study.

BACKGROUND: Predictive biomarkers could allow more precise use of immune checkpoint inhibitors (ICIs) in treating advanced cancers. Given the central role of HLA molecules in immunity, variation at the HLA loci could differentially affect the response to ICIs. The aim of this epidemiological study was to determine the effect of HLA-A*03 as a biomarker for predicting response to immunotherapy. METHODS: In this epidemiological study, we investigated the clinical outcomes (overall survival, progression free survival, and objective response rate) after treatment for advanced cancer in eight cohorts of patients: three observational cohorts of patients with various types of advanced tumours (the Memorial Sloan Kettering Integrated Mutation Profiling of Actionable Cancer Targets [MSK-IMPACT] cohort, the Dana-Farber Cancer Institute [DFCI] Profile cohort, and The Cancer Genome Atlas) and five clinical trials of patients with advanced bladder cancer (JAVELIN Solid Tumour) or renal cell carcinoma (CheckMate-009, CheckMate-010, CheckMate-025, and JAVELIN Renal 101). In total, these cohorts included 3335 patients treated with various ICI agents (anti-PD-1, anti-PD-L1, and anti-CTLA-4 inhibitors) and 10 917 patients treated with non-ICI cancer-directed therapeutic approaches. We initially modelled the association of HLA amino-acid variation with overall survival in the MSK-IMPACT discovery cohort, followed by a detailed analysis of the association between HLA-A*03 and clinical outcomes in MSK-IMPACT, with replication in the additional cohorts (two further observational cohorts and five clinical trials). FINDINGS: HLA-A*03 was associated in an additive manner with reduced overall survival after ICI treatment in the MSK-IMPACT cohort (HR 1·48 per HLA-A*03 allele [95% CI 1·20-1·82], p=0·00022), the validation DFCI Profile cohort (HR 1·22 per HLA-A*03 allele, 1·05-1·42; p=0·0097), and in the JAVELIN Solid Tumour clinical trial for bladder cancer (HR 1·36 per HLA-A*03 allele, 1·01-1·85; p=0·047). The HLA-A*03 effect was observed across ICI agents and tumour types, but not in patients treated with alternative therapies. Patients with HLA-A*03 had shorter progression-free survival in the pooled patient population from the three CheckMate clinical trials of nivolumab for renal cell carcinoma (HR 1·31, 1·01-1·71; p=0·044), but not in those receiving control (everolimus) therapies. Objective responses were observed in none of eight HLA-A*03 homozygotes in the ICI group (compared with 59 [26·6%] of 222 HLA-A*03 non-carriers and 13 (17·1%) of 76 HLA-A*03 heterozygotes). HLA-A*03 was associated with shorter progression-free survival in patients receiving ICI in the JAVELIN Renal 101 randomised clinical trial for renal cell carcinoma (avelumab plus axitinib; HR 1·59 per HLA-A*03 allele, 1·16-2·16; p=0·0036), but not in those receiving control (sunitinib) therapy. Objective responses were recorded in one (12·5%) of eight HLA-A*03 homozygotes in the ICI group (compared with 162 [63·8%] of 254 HLA-A*03 non-carriers and 40 [55·6%] of 72 HLA-A*03 heterozygotes). HLA-A*03 was associated with impaired outcome in meta-analysis of all 3335 patients treated with ICI at genome-wide significance (p=2·01 × 10-8) with no evidence of heterogeneity in effect (I2 0%, 95% CI 0-0·76) INTERPRETATION: HLA-A*03 is a predictive biomarker of poor response to ICI. Further evaluation of HLA-A*03 is warranted in randomised trials. HLA-A*03 carriage could be considered in decisions to initiate ICI in patients with cancer. FUNDING: National Institutes of Health, Merck KGaA, and Pfizer.

Plasma cell-free DNA variant analysis compared with methylated DNA analysis in renal cell carcinoma.

PURPOSE: Plasma cell-free DNA (cfDNA) variant analysis is commonly used in many cancer subtypes. Cell-free methylated DNA immunoprecipitation sequencing (cfMeDIP-seq) has shown high sensitivity for cancer detection. To date, studies have not compared the sensitivity of both methods in a single cancer subtype. METHODS: cfDNA from 40 metastatic RCC (mRCC) patients was subjected to targeted panel variant analysis. For 34 of 40, cfMeDIP-seq was also performed. A separate cohort of 38 mRCC patients were used in cfMeDIP-seq analysis to train an RCC classifier. RESULTS: cfDNA variant analysis detected 21 candidate variants in 11 of 40 mRCC patients (28%), after exclusion of 2 germline variants and 6 variants reflecting clonal hematopoiesis. Among 23 patients with parallel tumor sequencing, cfDNA analysis alone identified variants in 9 patients (39%), while cfDNA analysis focused on tumor sequencing variant findings improved the sensitivity to 52%. In 34 mRCC patients undergoing cfMeDIP-seq, cfDNA variant analysis identified variants in 7 (21%), while cfMeDIP-seq detected all mRCC cases (100% sensitivity) with 88% specificity in 34 control subjects. In 5 patients with cfDNA variants and serial samples, variant frequency correlated with response to therapy. CONCLUSION: cfMeDIP-seq is significantly more sensitive for mRCC detection than cfDNA variant analysis. However, cfDNA variant analysis may be useful for monitoring response to therapy.

The Transcriptional Activator Krüppel-like Factor-6 Is Required for CNS Myelination.

Growth factors of the gp130 family promote oligodendrocyte differentiation, and viability, and myelination, but their mechanisms of action are incompletely understood. Here, we show that these effects are coordinated, in part, by the transcriptional activator Krüppel-like factor-6 (Klf6). Klf6 is rapidly induced in oligodendrocyte progenitors (OLP) by gp130 factors, and promotes differentiation. Conversely, in mice with lineage-selective Klf6 inactivation, OLP undergo maturation arrest followed by apoptosis, and CNS myelination fails. Overlapping transcriptional and chromatin occupancy analyses place Klf6 at the nexus of a novel gp130-Klf-importin axis, which promotes differentiation and viability in part via control of nuclear trafficking. Klf6 acts as a gp130-sensitive transactivator of the nuclear import factor importin-α5 (Impα5), and interfering with this mechanism interrupts step-wise differentiation. Underscoring the significance of this axis in vivo, mice with conditional inactivation of gp130 signaling display defective Klf6 and Impα5 expression, OLP maturation arrest and apoptosis, and failure of CNS myelination.

Assessing the role of reward in task selection using a reward-based voluntary task switching paradigm.

People exhibit a remarkable ability to both maintain controlled focus on executing a single task and flexibly shift between executing several tasks. Researchers studying human multitasking have traditionally focused on the cognitive control mechanisms that allow for such stable and flexible task execution, but there has been a recent interest in how cognitive control mechanisms drive the decision of task selection. The present research operationalizes a foraging analogy to investigate what factors drive the decision to either exploit task repetitions or explore task switches. A novel paradigm-reward-based voluntary task switching-ascribes point values to tasks where the overall goal is to accumulate points as quickly as possible. The reward structure generally rewards switching tasks, thereby juxtaposing the motivation to gain increased reward (by exploring task switches) against the motivation to perform quickly (by exploiting task repetitions). Results suggest that people are highly sensitive to changes in both reward and effort demands when making task selections, and that the task selection process is efficient and flexible. We argue that a cost-benefit mechanism might underlie decisions in multitasking contexts, whereby people compute task selections based on both the reward available for selecting a task and the effort necessary to execute a task.

A multicenter, retrospective, case-cohort study of the epidemiology and risk factors for Clostridium difficile infection among cord blood transplant recipients.

BACKGROUND: Clostridium difficile infection (CDI) is the leading cause of health-care associated infectious diarrhea. The aim of this study was to evaluate the epidemiology and risk factors for CDI in the 100 days following umbilical cord blood transplantation (UCBT) at three Boston hospitals. METHODS: We performed a multicenter, retrospective, case-cohort study of 226 UCBT recipients at Beth Israel Deaconess Medical Center, Massachusetts General Hospital, and Dana Farber/Brigham and Women's Cancer Center from 2003 to 2012. CDI was defined as diarrhea (≥3 unformed bowel movements for at least 2 days) plus a positive stool test for toxinogenic C. difficile and not attributed to any other cause. RESULTS: Among 226 UCBT recipients, 22 patients (9.7%) developed CDI within the first 100 days of transplant (corresponding to an infection rate of 10.8 cases per 10 000 person-days). The 100-day and 1-year rates were stable across the time period and between institutions. UCBT recipients with CDI were more likely than non-CDI patients to be older, with higher body mass indices, and to have received an antipseudomonal penicillin agent. In a time-dependent case-cohort analysis of the risk factors associated with CDI in the first 100 days after UCBT, bacterial infection after UCBT was the strongest risk factor for CDI (hazard ratio 2.8; 95% confidence interval 1.08-7.24; P=.03), after adjustment for transplant variables including antibiotic exposure. CONCLUSION: This study verifies the previously reported risk factors for CDI including older age and antibiotic exposure and identifies a novel association between bacterial infections and risk for CDI.

Cytokine response is determined by duration of receptor and signal transducers and activators of transcription 3 (STAT3) activation.

Paradoxically, the pro-inflammatory cytokine IL-6 and the anti-inflammatory cytokine IL-10 both activate STAT3, yet generate nearly opposing cellular responses. Here, we show that the temporal pattern of STAT3 activation codes for the specific cytokine response. A computational model of IL-6 and IL-10 signaling predicted that IL-6 stimulation results in transient activation of STAT3, with a rapid decline in phosphorylation and nuclear localization. In contrast, simulated IL-10 signaling resulted in sustained STAT3 activation. The predicted STAT3 patterns produced by each cytokine were confirmed experimentally in human dendritic cells. Time course microarray studies further showed that the dynamic genome-wide transcriptional responses were nearly identical at early time points following stimulation (when STAT3 is active in response to both IL-6 and IL-10) but divergent at later times (when STAT3 is active only in response to IL-10). Truncating STAT3 activation after IL-10 stimulation caused IL-10 to elicit an IL-6-like transcriptional and secretory response. That the duration of IL-10 receptor and STAT3 activation can direct distinct responses reveals a complex cellular information-coding mechanism that may be relevant to improving the prediction of the effects of drug candidates using this mechanism.

Update on Biomarkers in Renal Cell Carcinoma.

Immune checkpoint inhibitors have significantly transformed the treatment paradigm for metastatic renal cell carcinoma (RCC), offering prolonged overall survival and achieving remarkable deep and durable responses. However, given the multiple ICI-containing, standard-of-care regimens approved for RCC, identifying biomarkers that predict therapeutic response and resistance is of critical importance. Although tumor-intrinsic features such as pathological characteristics, genomic alterations, and transcriptional signatures have been extensively investigated, they have yet to provide definitive, robust predictive biomarkers. Current research is exploring host factors through in-depth characterization of the immune system. Additionally, innovative technological approaches are being developed to overcome challenges presented by existing techniques, such as tumor heterogeneity. Promising avenues in biomarker discovery include the study of the microbiome, radiomics, and spatial transcriptomics.

Emerging Novel Functional Imaging and Immunotherapy in Renal Cell Carcinoma and Current Treatment Sequencing Strategies After Immunotherapy.

The management of renal cell carcinoma (RCC) has advanced significantly in the past two decades. Many promising functional imaging modalities such as radiolabeled tracer targeting carbonic anhydrase IX and prostate-specific membrane antigen are under development to detect primary kidney tumors, stage systemic disease, and assess treatment response in RCC. Immune checkpoint inhibitors targeting PD-1 and cytotoxic T-cell lymphocyte-4 have changed the treatment paradigm in advanced RCC. Trials investigating novel mechanisms such as LAG-3 immune checkpoint inhibition, chimeric antigen receptor T-cell therapies, and T-cell engagers targeting RCC-associated antigens are currently ongoing. With the rapidly changing treatment landscape of RCC, the treatment sequence strategies will continue to evolve. Familiarity with the toxicities associated with the therapeutic agents and how to manage them are essential to achieve optimal patient outcomes. This review summarizes the recent developments of functional imaging and immunotherapy strategies in RCC, and the evidence supports treatment sequencing.

Clinical Implications of Basic Research: Exploring the Transformative Potential of Spatial 'Omics in Uro-oncology.

New spatial molecular technologies are poised to transform our understanding and treatment of urological cancers. By mapping the spatial molecular architecture of tumours, these platforms uncover the complex heterogeneity within and around individual malignancies, offering novel insights into disease development, progression, diagnosis, and treatment. They enable tracking of clonal phylogenetics in situ and immune-cell interactions in the tumour microenvironment. A whole transcriptome/genome/proteome-level spatial analysis is hypothesis generating, particularly in the areas of risk stratification and precision medicine. Current challenges include reagent costs, harmonisation of protocols, and computational demands. Nonetheless, the evolving landscape of the technology and evolving machine learning applications have the potential to overcome these barriers, pushing towards a future of personalised cancer therapy, leveraging detailed spatial cellular and molecular data. PATIENT SUMMARY: Tumours are complex and contain many different components. Although we have been able to observe some of these differences visually under the microscope, until recently, we have not been able to observe the genetic changes that underpin cancer development. Scientists are now able to explore molecular/genetic differences using approaches such as "spatial transcriptomics" and "spatial proteomics", which allow them to see genetic and cellular variation across a region of normal and cancerous tissue without destroying the tissue architecture. Currently, these technologies are limited by high associated costs, and a need for powerful and complex computational analysis workflows. Future advancements and results through these new technologies may assist patients and their doctors as they make decisions about treating their cancer.