Explore the vast range of titles available.

Anti-PD-1 therapy yields objective clinical responses in 30–40% of advanced melanoma patients. Since most patients do not respond, predictive biomarkers to guide treatment selection are needed. We hypothesize that MHC-I/II expression is required for tumour antigen presentation and may predict anti-PD-1 therapy response. In this study, across 60 melanoma cell lines, we find bimodal expression patterns of MHC-II, while MHC-I expression was ubiquitous. A unique subset of melanomas are capable of expressing MHC-II under basal or IFNγ-stimulated conditions. Using pathway analysis, we show that MHC-II(+) cell lines demonstrate signatures of ‘PD-1 signalling’, ‘allograft rejection’ and ‘T-cell receptor signalling’, among others. In two independent cohorts of anti-PD-1-treated melanoma patients, MHC-II positivity on tumour cells is associated with therapeutic response, progression-free and overall survival, as well as CD4 + and CD8 + tumour infiltrate. MHC-II + tumours can be identified by melanoma-specific immunohistochemistry using commercially available antibodies for HLA-DR to improve anti-PD-1 patient selection. Immunotherapy is used to treat melanoma, however patient responses vary widely highlighting the need for factors that can predict therapeutic success. Here, the authors show that MHC-II molecules expressed by tumour cells are positively correlated with a good response to therapy and overall patient survival.

Marker enrichment modeling (MEM) provides an objective metric for characterizing cell populations from high-content single-cell analysis. The MEM score outperforms standard metrics and provides a machine-readeable label for cell subsets. Learning cell identity from high-content single-cell data presently relies on human experts. We present marker enrichment modeling (MEM), an algorithm that objectively describes cells by quantifying contextual feature enrichment and reporting a human- and machine-readable text label. MEM outperforms traditional metrics in describing immune and cancer cell subsets from fluorescence and mass cytometry. MEM provides a quantitative language to communicate characteristics of new and established cytotypes observed in complex tissues.

Recent advances in cytometry have enabled high-throughput data collection with multiple single-cell protein expression measurements. The significant biological and technical variance in cytometry has posed a formidable challenge during the gating process, especially for the initial pre-gates which deal with unpredictable events, such as debris and technical artifacts. To mitigate the labor-intensive manual gating process, we propose UNITO, a framework to rigorously identify the hierarchical cytometric subpopulations. UNITO transforms a cell-level classification task into an image-based segmentation problem. The framework is validated on three independent cohorts (two mass cytometry and one flow cytometry datasets). We compare its results with previous automated methods using the consensus of at least four experienced immunologists. UNITO outperforms existing methods and deviates from human consensus by no more than any individual does. UNITO can reproduce a similar contour compared to manual gating for post-hoc inspection, and it also allows parallelization of samples for faster processing. High-throughput cytometry generates complex single-cell data with challenging manual gating process. Here, authors introduce UNITO, a framework that transforms cell classification into image segmentation, outperforming existing methods in identifying cytometric subpopulations across diverse datasets.

A goal of cancer research is to reveal cell subsets linked to continuous clinical outcomes to generate new therapeutic and biomarker hypotheses. We introduce a machine learning algorithm, Risk Assessment Population IDentification (RAPID), that is unsupervised and automated, identifies phenotypically distinct cell populations, and determines whether these populations stratify patient survival. With a pilot mass cytometry dataset of 2 million cells from 28 glioblastomas, RAPID identified tumor cells whose abundance independently and continuously stratified patient survival. Statistical validation within the workflow included repeated runs of stochastic steps and cell subsampling. Biological validation used an orthogonal platform, immunohistochemistry, and a larger cohort of 73 glioblastoma patients to confirm the findings from the pilot cohort. RAPID was also validated to find known risk stratifying cells and features using published data from blood cancer. Thus, RAPID provides an automated, unsupervised approach for finding statistically and biologically significant cells using cytometry data from patient samples.

SARS-CoV-2 messenger RNA vaccination in healthy individuals generates immune protection against COVID-19. However, little is known about SARS-CoV-2 mRNA vaccine-induced responses in immunosuppressed patients. We investigated induction of antigen-specific antibody, B cell and T cell responses longitudinally in patients with multiple sclerosis (MS) on anti-CD20 antibody monotherapy ( n  = 20) compared with healthy controls ( n  = 10) after BNT162b2 or mRNA-1273 mRNA vaccination. Treatment with anti-CD20 monoclonal antibody (aCD20) significantly reduced spike-specific and receptor-binding domain (RBD)-specific antibody and memory B cell responses in most patients, an effect ameliorated with longer duration from last aCD20 treatment and extent of B cell reconstitution. By contrast, all patients with MS treated with aCD20 generated antigen-specific CD4 and CD8 T cell responses after vaccination. Treatment with aCD20 skewed responses, compromising circulating follicular helper T (T FH ) cell responses and augmenting CD8 T cell induction, while preserving type 1 helper T (T H 1) cell priming. Patients with MS treated with aCD20 lacking anti-RBD IgG had the most severe defect in circulating T FH responses and more robust CD8 T cell responses. These data define the nature of the SARS-CoV-2 vaccine-induced immune landscape in aCD20-treated patients and provide insights into coordinated mRNA vaccine-induced immune responses in humans. Our findings have implications for clinical decision-making and public health policy for immunosuppressed patients including those treated with aCD20. SARS-CoV-2-specific antibodies and memory B cells are significantly reduced, but CD4 + and CD8 + T cells are robustly activated, in patients with multiple sclerosis on anti-CD20 monotherapy versus healthy controls after BNT162b2 or mRNA-1273 mRNA vaccination.

Exhausted CD8 T cells (T EX ) are a distinct state of T cell differentiation associated with failure to clear chronic viruses and cancer. Immunotherapies such as PD-1 blockade can reinvigorate T EX cells, but reinvigoration is not durable. A major unanswered question is whether T EX cells differentiate into functional durable memory T cells (T MEM ) upon antigen clearance. Here, using a mouse model, we found that upon eliminating chronic antigenic stimulation, T EX cells partially (re)acquire phenotypic and transcriptional features of T MEM cells. These ‘recovering’ T EX cells originated from the T cell factor (TCF-1 + ) T EX progenitor subset. Nevertheless, the recall capacity of these recovering T EX cells remained compromised as compared to T MEM cells. Chromatin-accessibility profiling revealed a failure to recover core memory epigenetic circuits and maintenance of a largely exhausted open chromatin landscape. Thus, despite some phenotypic and transcriptional recovery upon antigen clearance, exhaustion leaves durable epigenetic scars constraining future immune responses. These results support epigenetic remodeling interventions for T EX cell–targeted immunotherapies. Wherry and colleagues examine whether exhausted T cells (T EX ) can differentiate into functional memory T cells (T MEM ) when chronic antigen is withdrawn. Using the chronic LCMV infection mouse model, they show that ‘recovering’ T EX cells (REC-T EX ) only partially recover immunophenotypic and functional characteristics of T MEM cells. The epigenomic status of REC-T EX cells more closely resembles that of T EX cells, and, upon rechallenge, the REC-T EX cells were still compromised in their ability to respond to virus.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection of vaccinated individuals is increasingly common but rarely results in severe disease, likely due to the enhanced potency and accelerated kinetics of memory immune responses. However, there have been few opportunities to rigorously study early recall responses during human viral infection. To better understand human immune memory and identify potential mediators of lasting vaccine efficacy, we used high-dimensional flow cytometry and SARS-CoV-2 antigen probes to examine immune responses in longitudinal samples from vaccinated individuals infected during the Omicron wave. These studies revealed heightened spike-specific responses during infection of vaccinated compared to unvaccinated individuals. Spike-specific cluster of differentiation (CD)4 T cells and plasmablasts expanded and CD8 T cells were robustly activated during the first week. In contrast, memory B cell activation, neutralizing antibody production and primary responses to nonspike antigens occurred during the second week. Collectively, these data demonstrate the functionality of vaccine-primed immune memory and highlight memory T cells as rapid responders during SARS-CoV-2 infection. Wherry and colleagues define the kinetics of vaccine-primed recall immune responses during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) breakthrough infection, highlighting rapid activation of memory T cells and broadly enhanced immune responses in previously vaccinated individuals.

Age-associated changes in the T cell compartment are well described. However, limitations of current single-modal or bimodal single-cell assays, including flow cytometry, RNA-seq (RNA sequencing) and CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing), have restricted our ability to deconvolve more complex cellular and molecular changes. Here, we profile >300,000 single T cells from healthy children (aged 11–13 years) and older adults (aged 55–65 years) by using the trimodal assay TEA-seq (single-cell analysis of mRNA transcripts, surface protein epitopes and chromatin accessibility), which revealed that molecular programming of T cell subsets shifts toward a more activated basal state with age. Naive CD4 + T cells, considered relatively resistant to aging, exhibited pronounced transcriptional and epigenetic reprogramming. Moreover, we discovered a novel CD8αα + T cell subset lost with age that is epigenetically poised for rapid effector responses and has distinct inhibitory, costimulatory and tissue-homing properties. Together, these data reveal new insights into age-associated changes in the T cell compartment that may contribute to differential immune responses. Using TEA-seq, Thomson et al. detail transcriptional and epigenetic alterations in the T cell compartment between healthy children and older adults, leading to the discovery of a novel pediatric CD8αα + population poised for rapid effector responses.