Immune checkpoint therapy (ICT) has the power to eradicate cancer, but the mechanisms that determine effective therapy-induced immune responses are not fully understood. Here, using high-dimensional single-cell profiling, we interrogate whether the landscape of T cell states in the peripheral blood predict responses to combinatorial targeting of the OX40 costimulatory and PD-1 inhibitory pathways. Single-cell RNA sequencing and mass cytometry expose systemic and dynamic activation states of therapy-responsive CD4⁺ and CD8⁺ T cells in tumor-bearing mice with expression of distinct natural killer (NK) cell receptors, granzymes, and chemokines/chemokine receptors. Moreover, similar NK cell receptor-expressing CD8⁺ T cells are also detected in the blood of immunotherapy-responsive cancer patients. Targeting the NK cell and chemokine receptors in tumor-bearing mice shows the functional importance of these receptors for therapy-induced anti-tumor immunity. These findings provide a better understanding of ICT and highlight the use and targeting of dynamic biomarkers on T cells to improve cancer immunotherapy.

Objective: Mass cytometry (MC) immunoprofiling allows high-parameter phenotyping of immune cells. We set to investigate the potential of MC immuno-monitoring of axial spondyloarthritis (axSpA) patients enrolled in the Tight Control SpondyloArthritis (TiCoSpA) trial. Methods: Fresh, longitudinal PBMCs samples (baseline, 24, and 48 weeks) from 9 early, untreated axSpA patients and 7 HLA-B27⁺ controls were analyzed using a 35-marker panel. Data were subjected to HSNE dimension reduction and Gaussian mean shift clustering (Cytosplore), followed by Cytofast analysis. Linear discriminant analyzer (LDA), based on initial HSNE clustering, was applied onto week 24 and 48 samples. Results: Unsupervised analysis yielded a clear separation of baseline patients and controls including a significant difference in 9 T cell, B cell, and monocyte clusters (cl), indicating disrupted immune homeostasis. Decrease in disease activity (ASDAS score; median 1.7, range 0.6–3.2) from baseline to week 48 matched significant changes over time in five clusters: cl10 CD4 T_nai cells median 4.7 to 0.02%, cl37 CD4 T_em cells median 0.13 to 8.28%, cl8 CD4 T_cm cells median 3.2 to 0.02%, cl39 B cells median 0.12 to 2.56%, and cl5 CD38⁺ B cells median 2.52 to 0.64% (all p<0.05). Conclusions: Our results showed that a decrease in disease activity in axSpA coincided with normalization of peripheral T- and B-cell frequency abnormalities. This proof of concept study shows the value of MC immuno-monitoring in clinical trials and longitudinal studies in axSpA. MC immunophenotyping on a larger, multi-center scale is likely to provide crucial new insights in the effect of anti-inflammatory treatment and thereby the pathogenesis of inflammatory rheumatic diseases. Key Points • Longitudinal immuno-monitoring of axSpA patients through mass cytometry indicates that normalization of immune cell compartments coincides with decrease in disease activity. • Our proof of concept study confirms the value of immune-monitoring utilizing mass cytometry.

Understanding the mechanisms and impact of booster vaccinations are essential in the design and delivery of vaccination programs. Here we show that a three dose regimen of a synthetic peptide vaccine elicits an accruing CD8⁺ T cell response against one SARS-CoV-2 Spike epitope. We see protection against lethal SARS-CoV-2 infection in the K18-hACE2 transgenic mouse model in the absence of neutralizing antibodies, but two dose approaches are insufficient to confer protection. The third vaccine dose of the single T cell epitope peptide results in superior generation of effector-memory T cells and tissue-resident memory T cells, and these tertiary vaccine-specific CD8⁺ T cells are characterized by enhanced polyfunctional cytokine production. Moreover, fate mapping shows that a substantial fraction of the tertiary CD8⁺ effector-memory T cells develop from re-migrated tissue-resident memory T cells. Thus, repeated booster vaccinations quantitatively and qualitatively improve the CD8⁺ T cell response leading to protection against otherwise lethal SARS-CoV-2 infection.

Chronic intestinal inflammation underlies inflammatory bowel disease (IBD). Previous studies indicated alterations in the cellular immune system; however, it has been challenging to interrogate the role of all immune cell subsets simultaneously. Therefore, we aimed to identify immune cell types associated with inflammation in IBD using high-dimensional mass cytometry. We analyzed 188 intestinal biopsies and paired blood samples of newly-diagnosed, treatment-naive patients (n=42) and controls (n=26) in two independent cohorts. We applied mass cytometry (36-antibody panel) to resolve single cells and analyzed the data with unbiased Hierarchical-SNE. In addition, imaging-mass cytometry (IMC) was performed to reveal the spatial distribution of the immune subsets in the tissue. We identified 44 distinct immune subsets. Correlation network analysis identified a network of inflammation-associated subsets, including HLA-DR⁺CD38⁺ EM CD4⁺ T cells, T regulatory-like cells, PD1⁺ EM CD8⁺ T cells, neutrophils, CD27⁺ TCRγδ cells and NK cells. All disease-associated subsets were validated in a second cohort. This network was abundant in a subset of patients, independent of IBD subtype, severity or intestinal location. Putative disease-associated CD4⁺ T cells were detectable in blood. Finally, imaging-mass cytometry revealed the spatial colocalization of neutrophils, memory CD4⁺ T cells and myeloid cells in the inflamed intestine. Our study indicates that a cellular network of both innate and adaptive immune cells colocalizes in inflamed biopsies from a subset of patients. These results contribute to dissecting disease heterogeneity and may guide the development of targeted therapeutics in IBD.

SummaryFactors that govern the complex formation of memory T cells are not completelyunderstood. A better understanding of thedevelopment of memory Tcell hetero-geneity is however required to enhance vaccination and immunotherapy ap-proaches. Here we examined the impact of pathogen- and tissue-specific cueson memory CD8+T cell heterogeneity using high-dimensional single-cell mass cy-tometry and a tailored bioinformatics pipeline. We identified distinct populationsof pathogen-specific CD8+T cells that uniquely connected to a specific pathogenor associated to multiple types of acute and persistent infections. In addition, thetissue environment shaped the memory CD8+T cell heterogeneity, albeit to alesser extent than infection. The programming of memory CD8+T cell differenti-ation during acute infection is eventually superseded by persistent infection.Thus, the plethora of distinct memory CD8+T cell subsets that arise upon infec-tion is dominantly sculpted by the pathogen-specific cues and further shaped by the tissue environment.

During healthy pregnancy, a balanced microenvironment at the maternal-fetal interface with coordinated interaction between various immune cells is necessary to maintain immunological tolerance. While specific decidual immune cell subsets have been investigated, a system-wide unbiased approach is lacking. Here, mass cytometry was applied for data-driven, in-depth immune profiling of the total leukocyte population isolated from first, second, and third trimester decidua, as well as maternal peripheral blood at time of delivery. The maternal-fetal interface showed a unique composition of immune cells, different from peripheral blood, with significant differences between early and term pregnancy samples. Profiling revealed substantial heterogeneity in the decidual lymphoid and myeloid cell lineages that shape gestational-specific immune networks and putative differentiation trajectories over time during gestation. Uncovering the overall complexity at the maternal-fetal interface throughout pregnancy resulted in a human atlas that may serve as a foundation upon which comprehension of the immune microenvironment and alterations thereof in pregnancy complications can be built.

Background: The clinical benefit of immunotherapeutic approaches against cancer has been well established although complete responses are only observed in a minority of patients. Combination immunotherapy offers an attractive avenue to develop more effective cancer therapies by improving the efficacy and duration of the tumor-specific T-cell response. Here, we aimed at deciphering the mechanisms governing the response to PD-1/PD-L1 checkpoint blockade to support the rational design of combination immunotherapy. Methods: Mice bearing subcutaneous MC-38 tumors were treated with blocking PD-L1 antibodies. To establish high-dimensional immune signatures of immunotherapy-specific responses, the tumor microenvironment was analyzed by CyTOF mass cytometry using 38 cellular markers. Findings were further examined and validated by flow cytometry and by functional in vivo experiments. Immune profiling was extended to the tumor microenvironment of colorectal cancer patients. Results: PD-L1 blockade induced selectively the expansion of tumor-infiltrating CD4⁺ and CD8⁺ T-cell subsets, co-expressing both activating (ICOS) and inhibitory (LAG-3, PD-1) molecules. By therapeutically co-targeting these molecules on the T_AI cell subsets in vivo by agonistic and antagonist antibodies, we were able to enhance PD-L1 blockade therapy as evidenced by an increased number of T_AI cells within the tumor micro-environment and improved tumor protection. Moreover, T_AI cells were also found in the tumor-microenvironment of colorectal cancer patients. Conclusions: This study shows the presence of T cell subsets in the tumor micro-environment expressing both activating and inhibitory receptors. These T_AI cells can be targeted by combined immunotherapy leading to improved survival.

Multi-parametric flow and mass cytometry allows exceptional high-resolution exploration of the cellular composition of the immune system. A large panel of computational tools have been developed to analyze the high-dimensional landscape of the data generated. Analysis frameworks such as FlowSOM or Cytosplore incorporate clustering and dimensionality reduction techniques and include algorithms allowing visualization of multi-parametric cytometric analysis. To additionally provide means to quantify specific cell clusters and correlations between samples, we developed an R-package, called cytofast, for further downstream analysis. Specifically, cytofast enables the visualization and quantification of cell clusters for an efficient discovery of cell populations associated with diseases or physiology. We used cytofast on mass and flow cytometry datasets based on the modulation of the immune system upon immunotherapy. With cytofast, we rapidly generated visual representations of group-related immune cell clusters and showed correlations with the immune system composition. We discovered macrophage subsets that significantly decrease upon cancer immunotherapy and distinct prime-boost effects of prophylactic vaccines on the myeloid compartment. Cytofast is a time-efficient tool for comprehensive cytometric analysis to reveal immune signatures and correlations. Cytofast is available at Bioconductor.