diffcyt: Differential discovery in high-dimensional cytometry via high-resolution clustering

CD37 is a safe chimeric antigen receptor target to treat acute myeloid leukemia

Acute myeloid leukemia (AML) is characterized by the accumulation of immature myeloid cells in the bone marrow and the peripheral blood. Nearly half of the AML patients relapse after standard induction therapy, and new forms of therapy are urgently needed. Chimeric antigen receptor (CAR) T therapy has so far not been successful in AML due to lack of efficacy and safety. Indeed, the most attractive antigen targets are stem cell markers such as CD33 or CD123. We demonstrate that CD37, a mature B cell marker, is expressed in AML samples, and its presence correlates with the European LeukemiaNet (ELN) 2017 risk stratification. We repurpose the anti-lymphoma CD37CAR for the treatment of AML and show that CD37CAR T cells specifically kill AML cells, secrete proinflammatory cytokines, and control cancer progression in vivo. Importantly, CD37CAR T cells display no toxicity toward hematopoietic stem cells. Thus, CD37 is a promising and safe CAR T cell AML target.

A temporal developmental map separates human NK cells from noncytotoxic ILCs through clonal and single-cell analysis

ABSTRACT

Natural killer (NK) cells represent the cytotoxic member within the innate lymphoid cell (ILC) family that are important against viral infections and cancer. Although the NK cell emergence from hematopoietic stem and progenitor cells through multiple intermediate stages and the underlying regulatory gene network has been extensively studied in mice, this process is not well characterized in humans. Here, using a temporal in vitro model to reconstruct the developmental trajectory of NK lineage, we identified an ILC-restricted oligopotent stage 3a CD34-CD117+CD161+CD45RA+CD56- progenitor population, that exclusively gave rise to CD56-expressing ILCs in vitro. We also further investigated a previously nonappreciated heterogeneity within the CD56+CD94-NKp44+ subset, phenotypically equivalent to stage 3b population containing both group-1 ILC and RORγt+ ILC3 cells, that could be further separated based on their differential expression of DNAM-1 and CD161 receptors. We confirmed that DNAM-1hi S3b and CD161hiCD117hi ILC3 populations distinctively differed in their expression of effector molecules, cytokine secretion, and cytotoxic activity. Furthermore, analysis of lineage output using DNA-barcode tracing across these stages supported a close developmental relationship between S3b-NK and S4-NK (CD56+CD94+) cells, whereas distant to the ILC3 subset. Cross-referencing gene signatures of culture-derived NK cells and other noncytotoxic ILCs with publicly available data sets validated that these in vitro stages highly resemble transcriptional profiles of respective in vivo ILC counterparts. Finally, by integrating RNA velocity and gene network analysis through single-cell regulatory network inference and clustering we unravel a network of coordinated and highly dynamic regulons driving the cytotoxic NK cell program, as a guide map for future studies on NK cell regulation.

spillR: spillover compensation in mass cytometry data

MOTIVATION

Channel interference in mass cytometry can cause spillover and may result in miscounting of protein markers. Chevrier et al. introduce an experimental and computational procedure to estimate and compensate for spillover implemented in their R package CATALYST. They assume spillover can be described by a spillover matrix that encodes the ratio between the signal in the unstained spillover receiving and stained spillover emitting channel. They estimate the spillover matrix from experiments with beads. We propose to skip the matrix estimation step and work directly with the full bead distributions. We develop a nonparametric finite mixture model and use the mixture components to estimate the probability of spillover. Spillover correction is often a pre-processing step followed by downstream analyses, and choosing a flexible model reduces the chance of introducing biases that can propagate downstream.

RESULTS

We implement our method in an R package spillR using expectation-maximization to fit the mixture model. We test our method on simulated, semi-simulated, and real data from CATALYST. We find that our method compensates low counts accurately, does not introduce negative counts, avoids overcompensating high counts, and preserves correlations between markers that may be biologically meaningful.

AVAILABILITY AND IMPLEMENTATION

Our new R package spillR is on bioconductor at bioconductor.org/packages/spillR. All experiments and plots can be reproduced by compiling the R markdown file spillR_paper.Rmd at github.com/ChristofSeiler/spillR_paper.

PPARγ attenuates cellular senescence of alveolar macrophages in asthma-COPD overlap

BACKGROUND

Asthma-chronic obstructive pulmonary disease (COPD) overlap (ACO) represents a complex condition characterized by shared clinical and pathophysiological features of asthma and COPD in older individuals. However, the pathophysiology of ACO remains unexplored. We aimed to identify the major inflammatory cells in ACO, examine senescence within these cells, and elucidate the genes responsible for regulating senescence.

METHODS

Bioinformatic analyses were performed to investigate major cell types and cellular senescence signatures in a public single-cell RNA sequencing (scRNA-Seq) dataset derived from the lung tissues of patients with ACO. Similar analyses were carried out in an independent cohort study Immune Mechanisms Severe Asthma (IMSA), which included bulk RNA-Seq and CyTOF data from bronchoalveolar lavage fluid (BALF) samples.

RESULTS

The analysis of the scRNA-Seq data revealed that monocytes/ macrophages were the predominant cell type in the lung tissues of ACO patients, constituting more than 50% of the cells analyzed. Lung monocytes/macrophages from patients with ACO exhibited a lower prevalence of senescence as defined by lower enrichment scores of SenMayo and expression levels of cellular senescence markers. Intriguingly, analysis of the IMSA dataset showed similar results in patients with severe asthma. They also exhibited a lower prevalence of senescence, particularly in airway CD206 + macrophages, along with increased cytokine expression (e.g., IL-4, IL-13, and IL-22). Further exploration identified alveolar macrophages as a major subtype of monocytes/macrophages driving cellular senescence in ACO. Differentially expressed genes related to oxidation-reduction, cytokines, and growth factors were implicated in regulating senescence in alveolar macrophages. PPARγ (Peroxisome Proliferator-Activated Receptor Gamma) emerged as one of the predominant regulators modulating the senescent signature of alveolar macrophages in ACO.

CONCLUSION

The findings suggest that senescence in macrophages, particularly alveolar macrophages, plays a crucial role in the pathophysiology of ACO. Furthermore, PPARγ may represent a potential therapeutic target for interventions aimed at modulating senescence-associated processes in ACO.Key words ACO, Asthma, COPD, Macrophages, Senescence, PPARγ.

SuperCellCyto: enabling efficient analysis of large scale cytometry datasets

Advancements in cytometry technologies have enabled quantification of up to 50 proteins across millions of cells at single cell resolution. Analysis of cytometry data routinely involves tasks such as data integration, clustering, and dimensionality reduction. While numerous tools exist, many require extensive run times when processing large cytometry data containing millions of cells. Existing solutions, such as random subsampling, are inadequate as they risk excluding rare cell subsets. To address this, we propose SuperCellCyto, an R package that builds on the SuperCell tool which groups highly similar cells into supercells. SuperCellCyto is available on GitHub ( https://github.com/phipsonlab/SuperCellCyto ) and Zenodo ( https://doi.org/10.5281/zenodo.10521294 ).

Phase II Study of Eribulin plus Pembrolizumab in Metastatic Soft-tissue Sarcomas: Clinical Outcomes and Biological Correlates

PURPOSE

Eribulin modulates the tumor-immune microenvironment via cGAS-STING signaling in preclinical models. This non-randomized phase II trial evaluated the combination of eribulin and pembrolizumab in patients with soft-tissue sarcomas (STS).

PATIENTS AND METHODS

Patients enrolled in one of three cohorts: leiomyosarcoma (LMS), liposarcomas (LPS), or other STS that may benefit from PD-1 inhibitors, including undifferentiated pleomorphic sarcoma (UPS). Eribulin was administered at 1.4 mg/m2 i.v. (days 1 and 8) with fixed-dose pembrolizumab 200 mg i.v. (day 1) of each 21-day cycle, until progression, unacceptable toxicity, or completion of 2 years of treatment. The primary endpoint was the 12-week progression-free survival rate (PFS-12) in each cohort. Secondary endpoints included the objective response rate, median PFS, safety profile, and overall survival (OS). Pretreatment and on-treatment blood specimens were evaluated in patients who achieved durable disease control (DDC) or progression within 12 weeks [early progression (EP)]. Multiplexed immunofluorescence was performed on archival LPS samples from patients with DDC or EP.

RESULTS

Fifty-seven patients enrolled (LMS, n = 19; LPS, n = 20; UPS/Other, n = 18). The PFS-12 was 36.8% (90% confidence interval: 22.5-60.4) for LMS, 69.6% (54.5-89.0) for LPS, and 52.6% (36.8-75.3) for UPS/Other cohorts. All 3 patients in the UPS/Other cohort with angiosarcoma achieved RECIST responses. Toxicity was manageable. Higher IFNα and IL4 serum levels were associated with clinical benefit. Immune aggregates expressing PD-1 and PD-L1 were observed in a patient that completed 2 years of treatment.

CONCLUSIONS

The combination of eribulin and pembrolizumab demonstrated promising activity in LPS and angiosarcoma.

Cancer-associated fibroblast phenotypes are associated with patient outcome in non-small cell lung cancer

Despite advances in treatment, lung cancer survival rates remain low. A better understanding of the cellular heterogeneity and interplay of cancer-associated fibroblasts (CAFs) within the tumor microenvironment will support the development of personalized therapies. We report a spatially resolved single-cell imaging mass cytometry (IMC) analysis of CAFs in a non-small cell lung cancer cohort of 1,070 patients. We identify four prognostic patient groups based on 11 CAF phenotypes with distinct spatial distributions and show that CAFs are independent prognostic factors for patient survival. The presence of tumor-like CAFs is strongly correlated with poor prognosis. In contrast, inflammatory CAFs and interferon-response CAFs are associated with inflamed tumor microenvironments and higher patient survival. High density of matrix CAFs is correlated with low immune infiltration and is negatively correlated with patient survival. In summary, our data identify phenotypic and spatial features of CAFs that are associated with patient outcome in NSCLC.

Blood immunophenotyping identifies distinct kidney histopathology and outcomes in patients with lupus nephritis

Lupus nephritis (LN) is a frequent manifestation of systemic lupus erythematosus, and fewer than half of patients achieve complete renal response with standard immunosuppressants. Identifying non-invasive, blood-based pathologic immune alterations associated with renal injury could aid therapeutic decisions. Here, we used mass cytometry immunophenotyping of peripheral blood mononuclear cells in 145 patients with biopsy-proven LN and 40 healthy controls to evaluate the heterogeneity of immune activation in patients with LN and to identify correlates of renal parameters and treatment response. Unbiased analysis identified 3 immunologically distinct groups of patients with LN that were associated with different patterns of histopathology, renal cell infiltrates, urine proteomic profiles, and treatment response at one year. Patients with enriched circulating granzyme B+ T cells at baseline showed more severe disease and increased numbers of activated CD8 T cells in the kidney, yet they had the highest likelihood of treatment response. A second group characterized primarily by a high type I interferon signature had a lower likelihood of response to therapy, while a third group appeared immunologically inactive by immunophenotyping at enrollment but with chronic renal injuries. Main immune profiles could be distilled down to 5 simple cytometric parameters that recapitulate several of the associations, highlighting the potential for blood immune profiling to translate to clinically useful non-invasive metrics to assess immune-mediated disease in LN.

PPARγ Attenuates Cellular Senescence of Alveolar Macrophages in Asthma- COPD Overlap

Asthma-chronic obstructive pulmonary disease (COPD) overlap (ACO) represents a complex condition characterized by shared clinical and pathophysiological features of asthma and COPD in older individuals. However, the pathophysiology of ACO remains unexplored. We aimed to identify the major inflammatory cells in ACO, examine senescence within these cells, and elucidate the genes responsible for regulating senescence. Bioinformatic analyses were performed to investigate major cell types and cellular senescence signatures in a public single-cell RNA sequencing (scRNA-Seq) dataset derived from the lung tissues of patients with ACO. Similar analyses were carried out in an independent cohort study Immune Mechanisms Severe Asthma (IMSA), which included bulk RNA-Seq and CyTOF data from bronchoalveolar lavage fluid (BALF) samples. The analysis of the scRNA-Seq data revealed that monocytes/ macrophages were the predominant cell type in the lung tissues of ACO patients, constituting more than 50% of the cells analyzed. Lung monocytes/macrophages from patients with ACO exhibited a lower prevalence of senescence as defined by lower enrichment scores of SenMayo and expression levels of cellular senescence markers. Intriguingly, analysis of the IMSA dataset showed similar results in patients with severe asthma. They also exhibited a lower prevalence of senescence, particularly in airway CD206 + macrophages, along with increased cytokine expression (e.g., IL-4, IL-13, and IL-22). Further exploration identified alveolar macrophages as a major subtype of monocytes/macrophages driving cellular senescence in ACO. Differentially expressed genes related to oxidation-reduction, cytokines, and growth factors were implicated in regulating senescence in alveolar macrophages. PPARγ (Peroxisome Proliferator-Activated Receptor Gamma) emerged as one of the predominant regulators modulating the senescent signature of alveolar macrophages in ACO. Collectively, the findings suggest that senescence in macrophages, particularly alveolar macrophages, plays a crucial role in the pathophysiology of ACO. Furthermore, PPARγ may represent a potential therapeutic target for interventions aimed at modulating senescence-associated processes in ACO.

Interferon-stimulated neutrophils as a predictor of immunotherapy response

Despite the remarkable success of anti-cancer immunotherapy, its effectiveness remains confined to a subset of patients-emphasizing the importance of predictive biomarkers in clinical decision-making and further mechanistic understanding of treatment response. Current biomarkers, however, lack the power required to accurately stratify patients. Here, we identify interferon-stimulated, Ly6Ehi neutrophils as a blood-borne biomarker of anti-PD1 response in mice at baseline. Ly6Ehi neutrophils are induced by tumor-intrinsic activation of the STING (stimulator of interferon genes) signaling pathway and possess the ability to directly sensitize otherwise non-responsive tumors to anti-PD1 therapy, in part through IL12b-dependent activation of cytotoxic T cells. By translating our pre-clinical findings to a cohort of patients with non-small cell lung cancer and melanoma (n = 109), and to public data (n = 1440), we demonstrate the ability of Ly6Ehi neutrophils to predict immunotherapy response in humans with high accuracy (average AUC ≈ 0.9). Overall, our study identifies a functionally active biomarker for use in both mice and humans.

Benchmarking differential abundance methods for finding condition-specific prototypical cells in multi-sample single-cell datasets

BACKGROUND

To analyze the large volume of data generated by single-cell technologies and to identify cellular correlates of particular clinical or experimental outcomes, differential abundance analyses are often applied. These algorithms identify subgroups of cells whose abundances change significantly in response to disease progression, or to an experimental perturbation. Despite the effectiveness of differential abundance analyses in identifying critical cell-states, there is currently no systematic benchmarking study to compare their applicability, usefulness, and accuracy in practice across single-cell modalities.

RESULTS

Here, we perform a comprehensive benchmarking study to objectively evaluate and compare the benefits and potential downsides of current state-of-the-art differential abundance testing methods. We benchmarked six single-cell testing methods on several practical tasks, using both synthetic and real single-cell datasets. The tasks evaluated include effectiveness in identifying true differentially abundant subpopulations, accuracy in the adequate handling of batch effects, runtime efficiency, and hyperparameter usability and robustness. Based on various evaluation results, this paper gives dataset-specific suggestions for the practical use of differential abundance testing approaches.

CONCLUSIONS

Based on our benchmarking study, we provide a set of recommendations for the optimal usage of single-cell DA testing methods in practice, particularly with respect to factors such as the presence of technical noise (for example batch effects), dataset size, and hyperparameter sensitivity.

Approaching Mass Cytometry Translational Studies by Experimental and Data Curation Settings

Clinical studies are conducted to better understand the pathological mechanism of diseases and to find biomarkers associated with disease activity, drug response, or outcome prediction. Mass cytometry (MC) is a high-throughput single-cell technology that measures hundreds of cells per second with more than 40 markers per cell. Thus, it is a suitable tool for immune monitoring and biomarker discovery studies. Working in translational and clinical settings requires a careful experimental design to minimize, monitor, and correct the variations introduced during sample collection, preparation, acquisition, and analysis. In this review, we will focus on these important aspects of MC-related experiments and data curation in the context of translational clinical research projects.

Single-cell characterization of human GBM reveals regional differences in tumor-infiltrating leukocyte activation

Glioblastoma (GBM) harbors a highly immunosuppressive tumor microenvironment (TME) which influences glioma growth. Major efforts have been undertaken to describe the TME on a single-cell level. However, human data on regional differences within the TME remain scarce. Here, we performed high-depth single-cell RNA sequencing (scRNAseq) on paired biopsies from the tumor center, peripheral infiltration zone and blood of five primary GBM patients. Through analysis of >45,000 cells, we revealed a regionally distinct transcription profile of microglia (MG) and monocyte-derived macrophages (MdMs) and an impaired activation signature in the tumor-peripheral cytotoxic-cell compartment. Comparing tumor-infiltrating CD8+ T cells with circulating cells identified CX3CR1high and CX3CR1int CD8+ T cells with effector and memory phenotype, respectively, enriched in blood but absent in the TME. Tumor CD8+ T cells displayed a tissue-resident memory phenotype with dysfunctional features. Our analysis provides a regionally resolved mapping of transcriptional states in GBM-associated leukocytes, serving as an additional asset in the effort towards novel therapeutic strategies to combat this fatal disease.

A systematic analysis of the human immune response to Plasmodium vivax

BACKGROUNDThe biology of Plasmodium vivax is markedly different from that of P. falciparum; how this shapes the immune response to infection remains unclear. To address this shortfall, we inoculated human volunteers with a clonal field isolate of P. vivax and tracked their response through infection and convalescence.METHODSParticipants were injected intravenously with blood-stage parasites and infection dynamics were tracked in real time by quantitative PCR. Whole blood samples were used for high dimensional protein analysis, RNA sequencing, and cytometry by time of flight, and temporal changes in the host response to P. vivax were quantified by linear regression. Comparative analyses with P. falciparum were then undertaken using analogous data sets derived from prior controlled human malaria infection studies.RESULTSP. vivax rapidly induced a type I inflammatory response that coincided with hallmark features of clinical malaria. This acute-phase response shared remarkable overlap with that induced by P. falciparum but was significantly elevated (at RNA and protein levels), leading to an increased incidence of pyrexia. In contrast, T cell activation and terminal differentiation were significantly increased in volunteers infected with P. falciparum. Heterogeneous CD4+ T cells were found to dominate this adaptive response and phenotypic analysis revealed unexpected features normally associated with cytotoxicity and autoinflammatory disease.CONCLUSIONP. vivax triggers increased systemic interferon signaling (cf P. falciparum), which likely explains its reduced pyrogenic threshold. In contrast, P. falciparum drives T cell activation far in excess of P. vivax, which may partially explain why falciparum malaria more frequently causes severe disease.TRIAL REGISTRATIONClinicalTrials.gov NCT03797989.FUNDINGThe European Union's Horizon 2020 Research and Innovation programme, the Wellcome Trust, and the Royal Society.

A cell-level discriminative neural network model for diagnosis of blood cancers

MOTIVATION

Precise identification of cancer cells in patient samples is essential for accurate diagnosis and clinical monitoring but has been a significant challenge in machine learning approaches for cancer precision medicine. In most scenarios, training data are only available with disease annotation at the subject or sample level. Traditional approaches separate the classification process into multiple steps that are optimized independently. Recent methods either focus on predicting sample-level diagnosis without identifying individual pathologic cells or are less effective for identifying heterogeneous cancer cell phenotypes.

RESULTS

We developed a generalized end-to-end differentiable model, the Cell Scoring Neural Network (CSNN), which takes sample-level training data and predicts the diagnosis of the testing samples and the identity of the diagnostic cells in the sample, simultaneously. The cell-level density differences between samples are linked to the sample diagnosis, which allows the probabilities of individual cells being diagnostic to be calculated using backpropagation. We applied CSNN to two independent clinical flow cytometry datasets for leukemia diagnosis. In both qualitative and quantitative assessments, CSNN outperformed preexisting neural network modeling approaches for both cancer diagnosis and cell-level classification. Post hoc decision trees and 2D dot plots were generated for interpretation of the identified cancer cells, showing that the identified cell phenotypes match the cancer endotypes observed clinically in patient cohorts. Independent data clustering analysis confirmed the identified cancer cell populations.

AVAILABILITY AND IMPLEMENTATION

The source code of CSNN and datasets used in the experiments are publicly available on GitHub (http://github.com/erobl/csnn). Raw FCS files can be downloaded from FlowRepository (ID: FR-FCM-Z6YK).

Molecular, metabolic, and functional CD4 T cell paralysis in the lymph node impedes tumor control

CD4 T cells are central effectors of anti-cancer immunity and immunotherapy, yet the regulation of CD4 tumor-specific T (TTS) cells is unclear. We demonstrate that CD4 TTS cells are quickly primed and begin to divide following tumor initiation. However, unlike CD8 TTS cells or exhaustion programming, CD4 TTS cell proliferation is rapidly frozen in place by a functional interplay of regulatory T cells and CTLA4. Together these mechanisms paralyze CD4 TTS cell differentiation, redirecting metabolic circuits, and reducing their accumulation in the tumor. The paralyzed state is actively maintained throughout cancer progression and CD4 TTS cells rapidly resume proliferation and functional differentiation when the suppressive constraints are alleviated. Overcoming their paralysis established long-term tumor control, demonstrating the importance of rapidly crippling CD4 TTS cells for tumor progression and their potential restoration as therapeutic targets.

sccomp: Robust differential composition and variability analysis for single-cell data

Cellular omics such as single-cell genomics, proteomics, and microbiomics allow the characterization of tissue and microbial community composition, which can be compared between conditions to identify biological drivers. This strategy has been critical to revealing markers of disease progression, such as cancer and pathogen infection. A dedicated statistical method for differential variability analysis is lacking for cellular omics data, and existing methods for differential composition analysis do not model some compositional data properties, suggesting there is room to improve model performance. Here, we introduce sccomp, a method for differential composition and variability analyses that jointly models data count distribution, compositionality, group-specific variability, and proportion mean-variability association, being aware of outliers. sccomp provides a comprehensive analysis framework that offers realistic data simulation and cross-study knowledge transfer. Here, we demonstrate that mean-variability association is ubiquitous across technologies, highlighting the inadequacy of the very popular Dirichlet-multinomial distribution. We show that sccomp accurately fits experimental data, significantly improving performance over state-of-the-art algorithms. Using sccomp, we identified differential constraints and composition in the microenvironment of primary breast cancer.

Infectious neutrophil deployment is regulated by resolvin D4

Neutrophils reside in the bone marrow (BM), ready for deployment to sites of injury/infection, initiating inflammation and its resolution. Here, we report that distal infections signal to the BM via resolvins to regulate granulopoiesis and BM neutrophil deployment. Emergency granulopoiesis during peritonitis evoked changes in BM resolvin D1 (RvD1) and BM RvD4. We found that leukotriene B4 stimulates neutrophil deployment. RvD1 and RvD4 each limited neutrophilic infiltration to infections, and differently regulated BM myeloid populations: RvD1 increased reparative monocytes, and RvD4 regulated granulocytes. RvD4 disengaged emergency granulopoiesis, prevented excess BM neutrophil deployment, and acted on granulocyte progenitors. RvD4 also stimulated exudate neutrophil, monocyte, and macrophage phagocytosis, and enhanced bacterial clearance. This mediator accelerated both neutrophil apoptosis and clearance by macrophages, thus expediting the resolution phase of inflammation. RvD4 stimulated phosphorylation of ERK1/2 and STAT3 in human BM-aspirate-derived granulocytes. RvD4 in the 1 to 100 nM range stimulated whole-blood neutrophil phagocytosis of Escherichia coli. RvD4 increased BM macrophage efferocytosis of neutrophils. Together, these results demonstrate the novel functions of resolvins in granulopoiesis and neutrophil deployment, contributing to the resolution of infectious inflammation.

Computational Methods for Single-Cell Proteomics

Advances in single-cell proteomics technologies have resulted in high-dimensional datasets comprising millions of cells that are capable of answering key questions about biology and disease. The advent of these technologies has prompted the development of computational tools to process and visualize the complex data. In this review, we outline the steps of single-cell and spatial proteomics analysis pipelines. In addition to describing available methods, we highlight benchmarking studies that have identified advantages and pitfalls of the currently available computational toolkits. As these technologies continue to advance, robust analysis tools should be developed in tandem to take full advantage of the potential biological insights provided by these data.

Treatment of adult ALL patients with third-generation CD19-directed CAR T cells: results of a pivotal trial

BACKGROUND

Third-generation chimeric antigen receptor (CAR)-engineered T cells (CARTs) might improve clinical outcome of patients with B cell malignancies. This is the first report on a third-generation CART dose-escalating, phase-1/2 investigator-initiated trial treating adult patients with refractory and/or relapsed (r/r) acute lymphoblastic leukemia (ALL).

METHODS

Thirteen patients were treated with escalating doses of CD19-directed CARTs between 1 × 10⁶ and 50 × 10⁶ CARTs/m². Leukapheresis, manufacturing and administration of CARTs were performed in-house.

RESULTS

For all patients, CART manufacturing was feasible. None of the patients developed any grade of Immune effector cell-associated neurotoxicity syndrome (ICANS) or a higher-grade (≥ grade III) catokine release syndrome (CRS). CART expansion and long-term CART persistence were evident in the peripheral blood (PB) of evaluable patients. At end of study on day 90 after CARTs, ten patients were evaluable for response: Eight patients (80%) achieved a complete remission (CR), including five patients (50%) with minimal residual disease (MRD)-negative CR. Response and outcome were associated with the administered CART dose. At 1-year follow-up, median overall survival was not reached and progression-free survival (PFS) was 38%. Median PFS was reached on day 120. Lack of CD39-expression on memory-like T cells was more frequent in CART products of responders when compared to CART products of non-responders. After CART administration, higher CD8 + and γδ-T cell frequencies, a physiological pattern of immune cells and lower monocyte counts in the PB were associated with response.

CONCLUSION

In conclusion, third-generation CARTs were associated with promising clinical efficacy and remarkably low procedure-specific toxicity, thereby opening new therapeutic perspectives for patients with r/r ALL. Trial registration This trial was registered at www.

CLINICALTRIALS

gov as NCT03676504.

LPS binding protein and activation signatures are upregulated during asthma exacerbations in children

Asthma exacerbations in children are associated with respiratory viral infection and atopy, resulting in systemic immune activation and infiltration of immune cells into the airways. The gene networks driving the immune activation and subsequent migration of immune cells into the airways remains incompletely understood. Cellular and molecular profiling of PBMC was employed on paired samples obtained from atopic asthmatic children (n = 19) during acute virus-associated exacerbations and later during convalescence. Systems level analyses were employed to identify coexpression networks and infer the drivers of these networks, and validation was subsequently obtained via independent samples from asthmatic children. During exacerbations, PBMC exhibited significant changes in immune cell abundance and upregulation of complex interlinked networks of coexpressed genes. These were associated with priming of innate immunity, inflammatory and remodelling functions. We identified activation signatures downstream of bacterial LPS, glucocorticoids and TGFB1. We also confirmed that LPS binding protein was upregulated at the protein-level in plasma. Multiple gene networks known to be involved positively or negatively in asthma pathogenesis, are upregulated in circulating PBMC during acute exacerbations, supporting the hypothesis that systemic pre-programming of potentially pathogenic as well as protective functions of circulating immune cells preceeds migration into the airways. Enhanced sensitivity to LPS is likely to modulate the severity of acute asthma exacerbations through exposure to environmental LPS.

Immunogenomic profile at baseline predicts host susceptibility to clinical malaria

Introduction

Host gene and protein expression impact susceptibility to clinical malaria, but the balance of immune cell populations, cytokines and genes that contributes to protection, remains incompletely understood. Little is known about the determinants of host susceptibility to clinical malaria at a time when acquired immunity is developing.

Methods

We analyzed peripheral blood mononuclear cells (PBMCs) collected from children who differed in susceptibility to clinical malaria, all from a small town in Mali. PBMCs were collected from children aged 4-6 years at the start, peak and end of the malaria season. We characterized the immune cell composition and cytokine secretion for a subset of 20 children per timepoint (10 children with no symptomatic malaria age-matched to 10 children with >2 symptomatic malarial illnesses), and gene expression patterns for six children (three per cohort) per timepoint.

Results

We observed differences between the two groups of children in the expression of genes related to cell death and inflammation; in particular, inflammatory genes such as CXCL10 and STAT1 and apoptotic genes such as XAF1 were upregulated in susceptible children before the transmission season began. We also noted higher frequency of HLA-DR+ CD4 T cells in protected children during the peak of the malaria season and comparable levels cytokine secretion after stimulation with malaria schizonts across all three time points.

Conclusion

This study highlights the importance of baseline immune signatures in determining disease outcome. Our data suggests that differences in apoptotic and inflammatory gene expression patterns can serve as predictive markers of susceptibility to clinical malaria.

DCATS: differential composition analysis for flexible single-cell experimental designs

Differential composition analysis - the identification of cell types that have statistically significant changes in abundance between multiple experimental conditions - is one of the most common tasks in single cell omic data analysis. However, it remains challenging to perform differential composition analysis in the presence of flexible experimental designs and uncertainty in cell type assignment. Here, we introduce a statistical model and an open source R package, DCATS, for differential composition analysis based on a beta-binomial regression framework that addresses these challenges. Our empirical evaluation shows that DCATS consistently maintains high sensitivity and specificity compared to state-of-the-art methods.

Deep immune B and plasma cell repertoire in non-small cell lung cancer

Introduction

B cells, which have long been thought to be minor players in the development of anti-tumor responses, have been implicated as key players in lung cancer pathogenesis and response to checkpoint blockade in patients with lung cancer. Enrichment of late-stage plasma and memory cells in the tumor microenvironment has been shown in lung cancer, with the plasma cell repertoire existing on a functional spectrum with suppressive phenotypes correlating with outcome. B cell dynamics may be influenced by the inflammatory microenvironment observed in smokers and between LUAD and LUSC.

Methods

Here, we show through high-dimensional deep phenotyping using mass cytometry (CyTOF), next generation RNA sequencing and multispectral immunofluorescence imaging (VECTRA Polaris) that key differences exist in the B cell repertoire between tumor and circulation in paired specimens from lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC).

Results

In addition to the current literature, this study provides insight into the in-depth description of the B cell contexture in Non-Small Cell Lung Cancer (NSCLC) with reference to broad clinico-pathological parameters based on our analysis of 56 patients. Our findings reinforce the phenomenon of B-cell trafficking from distant circulatory compartments into the tumour microenvironment (TME). The circulatory repertoire shows a predilection toward plasma and memory phenotypes in LUAD however no major differences exist between LUAD and LUSC at the level of the TME. B cell repertoire, amongst other factors, may be influenced by the inflammatory burden in the TME and circulation, that is, smokers and non-smokers. We have further clearly demonstrated that the plasma cell repertoire exists on a functional spectrum in lung cancer, and that the suppressive regulatory arm of this axis may play a significant role in determining postoperative outcomes as well as following checkpoint blockade. This will require further long-term functional correlation.

Conclusion

B and Plasma cell repertoire is very diverse and heterogeneous across different tissue compartments in lung cancer. Smoking status associates with key differences in the immune milieu and the consequent inflammatory microenvironment is likely responsible for the functional and phenotypic spectrum we have seen in the plasma cell and B cell repertoire in this condition.

Stromal and therapy-induced macrophage proliferation promotes PDAC progression and susceptibility to innate immunotherapy

Tumor-associated macrophages (TAMs) are abundant in pancreatic ductal adenocarcinomas (PDACs). While TAMs are known to proliferate in cancer tissues, the impact of this on macrophage phenotype and disease progression is poorly understood. We showed that in PDAC, proliferation of TAMs could be driven by colony stimulating factor-1 (CSF1) produced by cancer-associated fibroblasts. CSF1 induced high levels of p21 in macrophages, which regulated both TAM proliferation and phenotype. TAMs in human and mouse PDACs with high levels of p21 had more inflammatory and immunosuppressive phenotypes. p21 expression in TAMs was induced by both stromal interaction and/or chemotherapy treatment. Finally, by modeling p21 expression levels in TAMs, we found that p21-driven macrophage immunosuppression in vivo drove tumor progression. Serendipitously, the same p21-driven pathways that drive tumor progression also drove response to CD40 agonist. These data suggest that stromal or therapy-induced regulation of cell cycle machinery can regulate both macrophage-mediated immune suppression and susceptibility to innate immunotherapy.

Single-cell immune profiling of Meniere Disease patients

BACKGROUND

Meniere Disease (MD) is an inner ear syndrome, characterized by episodes of vertigo, tinnitus and fluctuating sensorineural hearing loss. The pathological mechanism leading to sporadic MD is still poorly understood, however an allergic inflammatory response seems to be involved in some patients with MD.

OBJECTIVE

Decipher an immune signature associated with the syndrome.

METHODS

We performed mass cytometry immune profiling on peripheral blood from MD patients and controls. We analyzed differences in state and differences in abundance of the different cellular subsets. IgE levels were quantified through ELISA on supernatant of cultured whole blood.

RESULTS

We have identified two clusters of individuals according to the single cell cytokine profile. These clusters presented differences in IgE levels, immune cell population abundance, including a reduction of CD56^dim NK-cells, and changes in cytokine expression with a different response to bacterial and fungal antigens.

CONCLUSION

Our results support a systemic inflammatory response in some MD patients that show a type 2 response with allergic phenotype, which could benefit from personalized IL-4 blockers.

HIF prolyl hydroxylase 2/3 deletion disrupts astrocytic integrity and exacerbates neuroinflammation

Astrocytes constitute the parenchymal border of the blood-brain barrier (BBB), modulate the exchange of soluble and cellular elements, and are essential for neuronal metabolic support. Thus, astrocytes critically influence neuronal network integrity. In hypoxia, astrocytes upregulate a transcriptional program that has been shown to boost neuroprotection in several models of neurological diseases. We investigated transgenic mice with astrocyte-specific activation of the hypoxia-response program by deleting the oxygen sensors, HIF prolyl-hydroxylase domains 2 and 3 (Phd2/3). We induced astrocytic Phd2/3 deletion after onset of clinical signs in experimental autoimmune encephalomyelitis (EAE) that led to an exacerbation of the disease mediated by massive immune cell infiltration. We found that Phd2/3-ko astrocytes, though expressing a neuroprotective signature, exhibited a gradual loss of gap-junctional Connexin-43 (Cx43), which was induced by vascular endothelial growth factor-alpha (Vegf-a) expression. These results provide mechanistic insights into astrocyte biology, their critical role in hypoxic states, and in chronic inflammatory CNS diseases.

Profiling of syngeneic mouse HCC tumor models as a framework to understand anti-PD-1 sensitive tumor microenvironments

BACKGROUND AND AIMS

The treatment of hepatocellular carcinoma (HCC) has been transformed by the use of immune checkpoint inhibitors. However, most patients with HCC do not benefit from treatment with immunotherapy. There is an urgent need to understand the mechanisms that underlie response or resistance to immunotherapy for patients with HCC. The use of syngeneic mouse models that closely recapitulate the heterogeneity of human HCC will provide opportunities to examine the complex interactions between cancer cells and nonmalignant cells in the tumor microenvironment.

APPROACH AND RESULTS

We leverage a multifaceted approach that includes imaging mass cytometry and suspension cytometry by time of flight to profile the tumor microenvironments of the Hep53.4, Hepa 1-6, RIL-175, and TIBx (derivative of TIB-75) syngeneic mouse HCC models. The immune tumor microenvironments vary across these four models, and various immunosuppressive pathways exist at baseline in orthotopic liver tumors derived from these models. For instance, TIBx, which is resistant to anti-programmed cell death protein 1 therapy, contains a high proportion of "M2-like" tumor-associated macrophages with the potential to diminish antitumor immunity. Investigation of The Cancer Genome Atlas reveals that the baseline immunologic profiles of Hep53.4, RIL-175, and TIBx are broadly representative of human HCCs; however, Hepa 1-6 does not recapitulate the immune tumor microenvironment of the vast majority of human HCCs.

CONCLUSIONS

There is a wide diversity in the immune tumor microenvironments in preclinical models and in human HCC, highlighting the need to use multiple syngeneic HCC models to improve the understanding of how to treat HCC through immune modulation.

ANPELA: Significantly Enhanced Quantification Tool for Cytometry-Based Single-Cell Proteomics

ANPELA is widely used for quantifying traditional bulk proteomic data. Recently, there is a clear shift from bulk proteomics to the single-cell ones (SCP), for which powerful cytometry techniques demonstrate the fantastic capacity of capturing cellular heterogeneity that is completely overlooked by traditional bulk profiling. However, the in-depth and high-quality quantification of SCP data is still challenging and severely affected by the large numbers of quantification workflows and extreme performance dependence on the studied datasets. In other words, the proper selection of well-performing workflow(s) for any studied dataset is elusory, and it is urgently needed to have a significantly enhanced and accelerated tool to address this issue. However, no such tool is developed yet. Herein, ANPELA is therefore updated to its 2.0 version (https://idrblab.org/anpela/), which is unique in providing the most comprehensive set of quantification alternatives (>1000 workflows) among all existing tools, enabling systematic performance evaluation from multiple perspectives based on machine learning, and identifying the optimal workflow(s) using overall performance ranking together with the parallel computation. Extensive validation on different benchmark datasets and representative application scenarios suggest the great application potential of ANPELA in current SCP research for gaining more accurate and reliable biological insights.

Molecular, metabolic and functional CD4 T cell paralysis impedes tumor control

CD4 T cells are important effectors of anti-tumor immunity, yet the regulation of CD4 tumor-specific T (T TS ) cells during cancer development is still unclear. We demonstrate that CD4 T TS cells are initially primed in the tumor draining lymph node and begin to divide following tumor initiation. Distinct from CD8 T TS cells and previously defined exhaustion programs, CD4 T TS cell proliferation is rapidly frozen in place and differentiation stunted by a functional interplay of T regulatory cells and both intrinsic and extrinsic CTLA4 signaling. Together these mechanisms paralyze CD4 T TS cell differentiation, redirecting metabolic and cytokine production circuits, and reducing CD4 T TS cell accumulation in the tumor. Paralysis is actively maintained throughout cancer progression and CD4 T TS cells rapidly resume proliferation and functional differentiation when both suppressive reactions are alleviated. Strikingly, Treg depletion alone reciprocally induced CD4 T TS cells to themselves become tumor-specific Tregs, whereas CTLA4 blockade alone failed to promote T helper differentiation. Overcoming their paralysis established long-term tumor control, demonstrating a novel immune evasion mechanism that specifically cripples CD4 T TS cells to favor tumor progression.

CyTOF protocol for immune monitoring of solid tumors from mouse models

Techniques for robust immune profiling of mouse tumor and blood are key to understanding immunological responses in mouse models of cancer. Here, we describe mass cytometry (cytometry by time-of-flight) procedures to facilitate high-parameter profiling of low-volume survival blood samples and end-of-study tumor samples. We employ live-cell barcoding systems to mark all cells from each tumor and blood to improve cost-effectiveness and minimize batch effects. For complete details on the use and execution of this protocol, please refer to Charmsaz et al. (2021).1.

Dynamic CD8+ T cell responses to cancer immunotherapy in human regional lymph nodes are disrupted in metastatic lymph nodes

CD8+ T cell responses are critical for anti-tumor immunity. While extensively profiled in the tumor microenvironment, recent studies in mice identified responses in lymph nodes (LNs) as essential; however, the role of LNs in human cancer patients remains unknown. We examined CD8+ T cells in human head and neck squamous cell carcinomas, regional LNs, and blood using mass cytometry, single-cell genomics, and multiplexed ion beam imaging. We identified progenitor exhausted CD8+ T cells (Tpex) that were abundant in uninvolved LN and clonally related to terminally exhausted cells in the tumor. After anti-PD-L1 immunotherapy, Tpex in uninvolved LNs reduced in frequency but localized near dendritic cells and proliferating intermediate-exhausted CD8+ T cells (Tex-int), consistent with activation and differentiation. LN responses coincided with increased circulating Tex-int. In metastatic LNs, these response hallmarks were impaired, with immunosuppressive cellular niches. Our results identify important roles for LNs in anti-tumor immune responses in humans.

Immunological signature in human cases of monkeypox infection in 2022 outbreak: an observational study

BACKGROUND

An unprecedented global monkeypox outbreak started in May, 2022. No data are yet available about the dynamics of the immune response against monkeypox virus. The aim of this study was to describe kinetics of T-cell response, inflammatory profile, and pox-specific T-cell induction in patients with laboratory-confirmed monkeypox.

METHODS

17 patients with laboratory-confirmed monkeypox admitted at the Lazzaro Spallanzani National Institute for Infectious Diseases (Rome, Italy), from May 19, to July 7, 2022, were tested for differentiation and activation profile of CD4 and CD8 T (expression of CD38, PD-1, and CD57 assessed by flow cytometry), frequency of pox-specific T cells (by standard interferon-γ ELISpot), and release of interleukin (IL)-1β, IL-6, IL-8, and tumour necrosis factor (TNF) in plasma (by ELISA). All patients were tested 10-12 days after symptoms onset. In a subgroup of nine patients with a laboratory-confirmed monkeypox, the kinetics of the immune response were analysed longitudinally according to timing from symptoms onset and compared with ten healthy donors (ie, health-care workers recruited from the same institution).

FINDINGS

Among the 17 patients, ten were HIV negative and seven HIV positive, all with good viro-immunological status. On days 0-3 from symptom onset, patients with laboratory-confirmed monkeypox were characterised by a statistically significant reduction in CD4+ T cells (p=0·0011) and a concurrent increase of CD8+ T cells (p=0·0057) compared with healthy donors. A lower proportion of naive (CD45RA+CD27+) CD4+ T cells was observed in six (67%) of nine patients and a concomitant higher proportion of effector memory (CD45RA-CD27-) CD4+ T cells in all patients; this skewed immune profile tended to normalise over time. A similar differentiated profile was also observed in CD8+ T cells with a consistent expansion of terminally differentiated CD8+ T cells. Patients with monkeypox had a higher proportion of CD4+CD38+ and CD38+CD8+ T-cells than healthy donors, which normalised after 12-20 days from symptom onset. The expression of PD-1 and CD57 on CD4+ and CD8+ T-cells showed kinetics similar to that observed for CD38. Furthermore, the inflammatory cytokines (IL-1β, IL-6, IL-8, and TNF) were higher in patients with monkeypox than in healthy donors and, although they decreased over time, they remained elevated after recovery. Almost all patients (15 [94%] of 16) developed a pox-specific Th1 response. No differences in immune cells profile were observed between patients with and without HIV, whereas paucysimptomatic patients (without systemic symptoms, with less than five skin lesions, and no other mucosal localisation of monkeypox) showed a less perturbed immune profile early after symptom onset.

INTERPRETATION

Our data showed the immunological signature of monkeypox virus infection, characterised by an early expansion of activated effector CD4+ and CD8+ T cells that persisted over time. Almost all patients, even regardless of HIV infection, developed a poxvirus-specific Th1 cell response. These results might have implications on the expected immunogenicity of monkeypox vaccination, suggesting that it might not be necessary to vaccinate people who have already been infected.

FUNDING

Italian Ministry of Health.

TRANSLATION

For the Italian translation of the abstract see Supplementary Materials section.

A cell-level discriminative neural network model for diagnosis of blood cancers

Motivation

Precise identification of cancer cells in patient samples is essential for accurate diagnosis and clinical monitoring but has been a significant challenge in machine learning approaches for cancer precision medicine. In most scenarios, training data are only available with disease annotation at the subject or sample level. Traditional approaches separate the classification process into multiple steps that are optimized independently. Recent methods either focus on predicting sample-level diagnosis without identifying individual pathologic cells or are less effective for identifying heterogeneous cancer cell phenotypes.

Results

We developed a generalized end-to-end differentiable model, the Cell Scoring Neural Network (CSNN), which takes the available sample-level training data and predicts both the diagnosis of the testing samples and the identity of the diagnostic cells in the sample, simultaneously. The cell-level density differences between samples are linked to the sample diagnosis, which allows the probabilities of individual cells being diagnostic to be calculated using backpropagation. We applied CSNN to two independent clinical flow cytometry datasets for leukemia diagnosis. In both qualitative and quantitative assessments, CSNN outperformed preexisting neural network modeling approaches for both cancer diagnosis and cell-level classification. Post hoc decision trees and 2D dot plots were generated for interpretation of the identified cancer cells, showing that the identified cell phenotypes match the cancer endotypes observed clinically in patient cohorts. Independent data clustering analysis confirmed the identified cancer cell populations.

Availability

The source code of CSNN and datasets used in the experiments are publicly available on GitHub and FlowRepository.

Contact

Edgar E. Robles: roblesee@uci.edu and Yu Qian: mqian@jcvi.org.

Supplementary information

Supplementary data are available on GitHub and at Bioinformatics online.

Detailed characterization of SARS-CoV-2-specific T and B cells after infection or heterologous vaccination

The formation of a robust long-term antigen (Ag)-specific memory, both humoral and cell-mediated, is created following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or vaccination. Here, by using polychromatic flow cytometry and complex data analyses, we deeply investigated the magnitude, phenotype, and functionality of SARS-CoV-2-specific immune memory in two groups of healthy subjects after heterologous vaccination compared to a group of subjects who recovered from SARS-CoV-2 infection. We find that coronavirus disease 2019 (COVID-19) recovered patients show different long-term immunological profiles compared to those of donors who had been vaccinated with three doses. Vaccinated individuals display a skewed T helper (Th)1 Ag-specific T cell polarization and a higher percentage of Ag-specific and activated memory B cells expressing immunoglobulin (Ig)G compared to those of patients who recovered from severe COVID-19. Different polyfunctional properties characterize the two groups: recovered individuals show higher percentages of CD4+ T cells producing one or two cytokines simultaneously, while the vaccinated are distinguished by highly polyfunctional populations able to release four molecules, namely, CD107a, interferon (IFN)-γ, tumor necrosis factor (TNF), and interleukin (IL)-2. These data suggest that functional and phenotypic properties of SARS-CoV-2 adaptive immunity differ in recovered COVID-19 individuals and vaccinated ones.

A sex-biased imbalance between Tfr, Tph, and atypical B cells determines antibody responses in COVID-19 patients

Sex-biased humoral immune responses to COVID-19 patients have been observed, but the cellular basis for this is not understood. Using single-cell proteomics by mass cytometry, we find disrupted regulation of humoral immunity in COVID-19 patients, with a sex-biased loss of circulating follicular regulatory T cells (cTfr) at a significantly greater rate in male patients. In addition, a male sex-associated cellular network of T-peripheral helper, plasma blasts, proliferating and extrafollicular/atypical CD11c⁺ memory B cells was strongly positively correlated with neutralizing antibody concentrations and negatively correlated with cTfr frequency. These results suggest that sex-specific differences to the balance of cTfr and a network of extrafollicular antibody production-associated cell types may be a key factor in the altered humoral immune responses between male and female COVID-19 patients.

Differential compartmentalization of myeloid cell phenotypes and responses towards the CNS in Alzheimer's disease

Myeloid cells are suggested as an important player in Alzheimer´s disease (AD). However, its continuum of phenotypic and functional changes across different body compartments and their use as a biomarker in AD remains elusive. Here, we perform multiple state-of-the-art analyses to phenotypically and metabolically characterize immune cells between peripheral blood (n = 117), cerebrospinal fluid (CSF, n = 117), choroid plexus (CP, n = 13) and brain parenchyma (n = 13). We find that CSF cells increase expression of markers involved in inflammation, phagocytosis, and metabolism. Changes in phenotype of myeloid cells from AD patients are more pronounced in CP and brain parenchyma and upon in vitro stimulation, suggesting that AD-myeloid cells are more vulnerable to environmental changes. Our findings underscore the importance of myeloid cells in AD and the detailed characterization across body compartments may serve as a resource for future studies focusing on the assessment of these cells as biomarkers in AD.

Single-cell phenotypes of peripheral blood immune cells in early and late stages of non-alcoholic fatty liver disease

Background

Immune and inflammatory cells respond to multiple pathological hits in the development of non-alcoholic steatohepatitis (NASH) and fibrosis. Relatively little is known about how their type and function change through the non-alcoholic fatty liver disease (NAFLD) spectrum. We used multi-dimensional mass cytometry and a tailored bioinformatic approach to study circulating immune cells sampled from healthy individuals and people with NAFLD.

Methods

Cytometry by time of flight (CyTOF) using 36 metal-conjugated antibodies was applied to peripheral blood mononuclear cells (PBMCs) from biopsy-proven NASH fibrosis (late disease), steatosis (early disease) and healthy patients. Supervised and unsupervised analyses were used, findings confirmed and mechanisms assessed using independent healthy and disease PBMC samples.

Results

Of 36 PBMC clusters, 21 changed between controls and disease samples. Significant differences between diseases stages with changes in T cells and myeloid cells throughout disease and B cell changes in late stages. Semi-supervised gating and re-clustering showed that disease stages were associated with fewer monocytes with active signalling and more inactive NK cells, while B and T cells bearing activation markers reduced in late stages, B cells bearing co-stimulatory molecules increased. Functionally, disease states were associated with fewer activated MAIT cells and reduced TLR-mediated cytokine production in late disease.

Conclusions

A range of innate and adaptive immune changes begin early in NAFLD and disease stages are associated with a functionally less active phenotype compared to controls. Further study of the immune response in NAFLD spectrum may give insight into mechanisms of disease with potential clinical application.

INFLECT: an R-package for cytometry cluster evaluation using marker modality

Background

Current methods of high-dimensional unsupervised clustering of mass cytometry data lack means to monitor and evaluate clustering results. Whether unsupervised clustering is correct is typically evaluated by agreement with dimensionality reduction techniques or based on benchmarking with manually classified cells. The ambiguity and lack of reproducibility of sequential gating has been replaced with ambiguity in interpretation of clustering results. On the other hand, spurious overclustering of data leads to loss of statistical power. We have developed INFLECT, an R-package designed to give insight in clustering results and provide an optimal number of clusters. In our approach, a mass cytometry dataset is overclustered intentionally to ensure the smallest phenotypically different subsets are captured using FlowSOM. A range of metacluster number endpoints are generated and evaluated using marker interquartile range and distribution unimodality checks. The fraction of marker distributions that pass these checks is taken as a measure of clustering success. The fraction of unimodal distributions within metaclusters is plotted against the number of generated metaclusters and reaches a plateau of diminishing returns. The inflection point at which this occurs gives an optimal point of capturing cellular heterogeneity versus statistical power.

Results

We applied INFLECT to four publically available mass cytometry datasets of different size and number of markers. The unimodality score consistently reached a plateau, with an inflection point dependent on dataset size and number of dimensions. We tested both ConsenusClusterPlus metaclustering and hierarchical clustering. While hierarchical clustering is less computationally expensive and thus faster, it achieved similar results to ConsensusClusterPlus. The four datasets consisted of labeled data and we compared INFLECT metaclustering to published results. INFLECT identified a higher optimal number of metaclusters for all datasets. We illustrated the underlying heterogeneity within labels, showing that these labels encompass distinct types of cells.

Conclusion

INFLECT addresses a knowledge gap in high-dimensional cytometry analysis, namely assessing clustering results. This is done through monitoring marker distributions for interquartile range and unimodality across a range of metacluster numbers. The inflection point is the optimal trade-off between cellular heterogeneity and statistical power, applied in this work for FlowSOM clustering on mass cytometry datasets.

Radiation therapy induces immunosenescence mediated by p90RSK

Radiation therapy (RT) to the chest increases the patients' risk of cardiovascular disease (CVD). A complete understanding of the mechanisms by which RT induces CVD could lead to specific preventive, therapeutic approaches. It is becoming evident that both genotoxic chemotherapy agents and radiation induce mitochondrial dysfunction and cellular senescence. Notably, one of the common phenotypes observed in cancer survivors is accelerated senescence, and immunosenescence is closely related to both cancer risk and CVD development. Therefore, suppression of immunosenescence can be an ideal target to prevent cancer treatment-induced CVD. However, the mechanism(s) by which cancer treatments induce immunosenescence are incompletely characterized. We isolated peripheral blood mononuclear cells (PBMCs) before and 3 months after RT from 16 thoracic cancer patients. We characterized human immune cell lineages and markers of senescence, DNA damage response (DDR), efferocytosis, and determinants of clonal hematopoiesis of indeterminant potential (CHIP), using mass cytometry (CyTOF). We found that the frequency of the B cell subtype was decreased after RT. Unsupervised clustering of the CyTOF data identified 138 functional subsets of PBMCs. Compared with baseline, RT increased TBX21 (T-bet) expression in the largest B cell subset of Ki67-/DNMT3a+naïve B cells, and T-bet expression was correlated with phosphorylation of p90RSK expression. CD38 expression was also increased in naïve B cells (CD27-) and CD8+ effector memory CD45RA T cells (TEMRA). In vitro, we found the critical role of p90RSK activation in upregulating (1) CD38+/T-bet+ memory and naïve B, and myeloid cells, (2) senescence-associated β-gal staining, and (3) mitochondrial reactive oxygen species (ROS) after ionizing radiation (IR). These data suggest the crucial role of p90RSK activation in immunosenescence. The critical role of p90RSK activation in immune cells and T-bet induction in upregulating atherosclerosis formation has been reported. Furthermore, T-bet directly binds to the CD38 promoter region and upregulates CD38 expression. Since both T-bet and CD38 play a significant role in the process of immunosenescence, our data provide a cellular and molecular mechanism that links RT-induced p90RSK activation and the immunosenescence with T-bet and CD38 induction observed in thoracic cancer patients treated by RT and suggests that targeting the p90RSK/T-bet/CD38 pathway could play a role in preventing the radiation-associated CVD and improving cancer prognosis by inhibiting immunosenescence.

Deciphering molecular and cellular ex vivo responses to bispecific antibodies PD1-TIM3 and PD1-LAG3 in human tumors

BACKGROUND

Next-generation cancer immunotherapies are designed to broaden the therapeutic repertoire by targeting new immune checkpoints including lymphocyte-activation gene 3 (LAG-3) and T cell immunoglobulin and mucin-domain containing-3 (TIM-3). Yet, the molecular and cellular mechanisms by which either receptor functions to mediate its inhibitory effects are still poorly understood. Similarly, little is known on the differential effects of dual, compared with single, checkpoint inhibition.

METHODS

We here performed in-depth characterization, including multicolor flow cytometry, single cell RNA sequencing and multiplex supernatant analysis, using tumor single cell suspensions from patients with cancer treated ex vivo with novel bispecific antibodies targeting programmed cell death protein 1 (PD-1) and TIM-3 (PD1-TIM3), PD-1 and LAG-3 (PD1-LAG3), or with anti-PD-1.

RESULTS

We identified patient samples which were responsive to PD1-TIM3, PD1-LAG3 or anti-PD-1 using an in vitro approach, validated by the analysis of 659 soluble proteins and enrichment for an anti-PD-1 responder signature. We found increased abundance of an activated (HLA-DR⁺CD25⁺GranzymeB⁺) CD8⁺ T cell subset and of proliferating CD8⁺ T cells, in response to bispecific antibody or anti-PD-1 treatment. Bispecific antibodies, but not anti-PD-1, significantly increased the abundance of a proliferating natural killer cell subset, which exhibited enrichment for a tissue-residency signature. Key phenotypic and transcriptional changes occurred in a PD-1⁺CXCL13⁺CD4⁺ T cell subset, in response to all treatments, including increased interleukin-17 secretion and signaling toward plasma cells. Interestingly, LAG-3 protein upregulation was detected as a unique pharmacodynamic effect mediated by PD1-LAG3, but not by PD1-TIM3 or anti-PD-1.

CONCLUSIONS

Our in vitro system reliably assessed responses to bispecific antibodies co-targeting PD-1 together with LAG-3 or TIM-3 using patients' tumor infiltrating immune cells and revealed transcriptional and phenotypic imprinting by bispecific antibody formats currently tested in early clinical trials.

SLAMF7 modulates B cells and adaptive immunity to regulate susceptibility to CNS autoimmunity

Background

Multiple sclerosis (MS) is a chronic, debilitating condition characterized by CNS autoimmunity stemming from a complex etiology involving both environmental and genetic factors. Our current understanding of MS points to dysregulation of the immune system as the pathogenic culprit, however, it remains unknown as to how the many genes associated with increased susceptibility to MS are involved. One such gene linked to MS susceptibility and known to regulate immune function is the self-ligand immune cell receptor SLAMF7.

Methods

We subjected WT and SLAMF7^−/− mice to multiple EAE models, compared disease severity, and comprehensively profiled the CNS immune landscape of these mice. We identified all SLAMF7-expressing CNS immune cells and compared the entire CNS immune niche between genotypes. We performed deep phenotyping and in vitro functional studies of B and T cells via spectral cytometry and BioPlex assays. Adoptive transfer studies involving the transfer of WT and SLAMF7^−/− B cells into B cell-deficient mice (μMT) were also performed. Finally, B–T cell co-culture studies were performed, and a comparative cell–cell interaction network derived from scRNA-seq data of SLAMF7⁺ vs. SLAMF7⁻ human CSF immune cells was constructed.

Results

We found SLAMF7^−/− mice to be more susceptible to EAE compared to WT mice and found SLAMF7 to be expressed on numerous CNS immune cell subsets. Absence of SLAMF7 did not grossly alter the CNS immune landscape, but allowed for altered immune cell subset infiltration during EAE in a model-dependent manner. Global lack of SLAMF7 expression increased myeloid cell activation states along with augmented T cell anti-MOG immunity. B cell profiling studies revealed increased activation states of specific plasma and B cell subsets in SLAMF7^−/− mice during EAE, and functional co-culture studies determined that SLAMF7^−/− B cells induce exaggerated T cell activation. Adoptive transfer studies revealed that the increased susceptibility of SLAMF7^−/− mice to EAE is partly B cell dependent and reconstruction of the human CSF SLAMF7-interactome found B cells to be critical to cell–cell communication between SLAMF7-expressing cells.

Conclusions

Our studies have identified novel roles for SLAMF7 in CNS immune regulation and B cell function, and illuminate underpinnings of the genetic association between SLAMF7 and MS.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12974-022-02594-9.

Challenges in translational machine learning

Machine learning (ML) algorithms are increasingly being used to help implement clinical decision support systems. In this new field, we define as "translational machine learning", joint efforts and strong communication between data scientists and clinicians help to span the gap between ML and its adoption in the clinic. These collaborations also improve interpretability and trust in translational ML methods and ultimately aim to result in generalizable and reproducible models. To help clinicians and bioinformaticians refine their translational ML pipelines, we review the steps from model building to the use of ML in the clinic. We discuss experimental setup, computational analysis, interpretability and reproducibility, and emphasize the challenges involved. We highly advise collaboration and data sharing between consortia and institutes to build multi-centric cohorts that facilitate ML methodologies that generalize across centers. In the end, we hope that this review provides a way to streamline translational ML and helps to tackle the challenges that come with it.

Aberrant signaling of immune cells in Sjögren’s syndrome patient subgroups upon interferon stimulation

Background

Primary Sjögren’s syndrome (pSS) is a systemic autoimmune disease, characterized by mononuclear cell infiltrates in the salivary and lacrimal glands, leading to glandular atrophy and dryness. Patient heterogeneity and lack of knowledge regarding its pathogenesis makes pSS a difficult disease to manage.

Methods

An exploratory analysis using mass cytometry was conducted of MAPK/ERK and JAK/STAT signaling pathways in peripheral blood mononuclear cells (PBMC) from 16 female medication free pSS patients (8 anti-Sjögren’s syndrome-related antigen A negative/SSA- and 8 SSA+) and 8 female age-matched healthy donors after stimulation with interferons (IFNs).

Results

We found significant differences in the frequencies of memory B cells, CD8+ T central and effector memory cells and terminally differentiated CD4+ T cells among the healthy donors and patient subgroups. In addition, we observed an upregulation of HLA-DR and CD38 in many cell subsets in the patients. Upon IFNα2b stimulation, slightly increased signaling through pSTAT1 Y701 was observed in most cell types in pSS patients compared to controls, while phosphorylation of STAT3 Y705 and STAT5 Y694 were slightly reduced. IFNγ stimulation resulted in significantly increased pSTAT1 Y701 induction in conventional dendritic cells (cDCs) and classical and non-classical monocytes in the patients. Most of the observed differences were more prominent in the SSA+ subgroup, indicating greater disease severity in them.

Conclusions

Augmented activation status of certain cell types along with potentiated pSTAT1 Y701 signaling and reduced pSTAT3 Y705 and pSTAT5 Y694 induction may predispose pSS patients, especially the SSA+ subgroup, to upregulated expression of IFN-induced genes and production of autoantibodies. These patients may benefit from therapies targeting these pathways.

An R-based reproducible and user-friendly preprocessing pipeline for CyTOF data

Mass cytometry (CyTOF) has become a method of choice for in-depth characterization of tissue heterogeneity in health and disease, and is currently implemented in multiple clinical trials, where higher quality standards must be met. Currently, preprocessing of raw files is commonly performed in independent standalone tools, which makes it difficult to reproduce. Here, we present an R pipeline based on an updated version of CATALYST that covers all preprocessing steps required for downstream mass cytometry analysis in a fully reproducible way. This new version of CATALYST is based on Bioconductor’s SingleCellExperiment class and fully unit tested. The R-based pipeline includes file concatenation, bead-based normalization, single-cell deconvolution, spillover compensation and live cell gating after debris and doublet removal. Importantly, this pipeline also includes different quality checks to assess machine sensitivity and staining performance while allowing also for batch correction. This pipeline is based on open source R packages and can be easily be adapted to different study designs. It therefore has the potential to significantly facilitate the work of CyTOF users while increasing the quality and reproducibility of data generated with this technology.

Effective Treatment of Patients Experiencing Primary, Acute HIV Infection Decreases Exhausted/Activated CD4+ T Cells and CD8+ T Memory Stem Cells

Several studies have identified main changes in T- and B-lymphocyte subsets during chronic HIV infection, but few data exist on how these subsets behave during the initial phase of HIV infection. We enrolled 22 HIV-infected patients during the acute stage of infection before the initiation of antiretroviral therapy (ART). Patients had blood samples drawn previous to ART initiation (T0), and at 2 (T1) and 12 (T2) months after ART initiation. We quantified cellular HIV-DNA content in sorted naïve and effector memory CD4 T cells and identified the main subsets of T- and B-lymphocytes using an 18-parameter flow cytometry panel. We identified correlations between the patients’ clinical and immunological data using PCA. Effective HIV treatment reduces integrated HIV DNA in effector memory T cells after 12 months (T2) of ART. The main changes in CD4+ T cells occurred at T2, with a reduction of activated memory, cytolytic and activated/exhausted stem cell memory T (T_SCM) cells. Changes were present among CD8+ T cells since T1, with a reduction of several activated subsets, including activated/exhausted T_SCM. At T2 a reduction of plasmablasts and exhausted B cells was also observed. A negative correlation was found between the total CD4+ T-cell count and IgM-negative plasmablasts. In patients initiating ART immediately following acute/early HIV infection, the fine analysis of T- and B-cell subsets has allowed us to identify and follow main modifications due to effective treatment, and to identify significant changes in CD4+ and CD8+ T memory stem cells.

Circulating L-Arginine predicts the survival of cancer patients treated with immune checkpoint inhibitors

BACKGROUND

The discovery of immune checkpoint inhibitors (ICIs) has revolutionized the systemic approach to cancer treatment. However, most patients receiving ICIs do not derive benefits. Therefore, it is crucial to identify reliable predictive biomarkers of response to ICIs. One important pathway in regulating immune cell reactivity is L-arginine (ARG) metabolism, essential to T-cell activation. We therefore aimed to evaluate the association between baseline plasma ARG levels and the clinical benefit of ICIs.

PATIENTS AND METHODS

The correlation between ARG levels and clinical ICI activity was assessed by analyzing plasma samples obtained before treatment onset in two independent cohorts of patients with advanced cancer included in two institutional molecular profiling programs (BIP, NCT02534649, n = 77; PREMIS, NCT03984318, n = 296) and from patients in a phase 1 first-in-human study of budigalimab monotherapy (NCT03000257). Additionally, the correlation between ARG levels and ICI efficacy in preclinical settings was evaluated using a syngeneic mouse model of colorectal cancer responsive to ICIs. Using matched PBMC plasma samples, we analyzed the correlation between ARG levels and PBMC features through multiplexed flow cytometry analysis.

RESULTS

In both discovery and validation cohorts, low ARG levels at baseline (<42 μM) were significantly and independently associated with a worse clinical benefit rate, progression-free survival, and overall survival. Moreover, at the preclinical level, the tumor rejection rate was significantly higher in mice with high baseline ARG levels than in those with low ARG levels (85.7% versus 23.8%; P = 0.004). Finally, PBMC immunophenotyping showed that low ARG levels were significantly associated with increased PD-L1 expression in several immune cell subsets from the myeloid lineage.

CONCLUSION

We demonstrate that baseline ARG levels predict ICI response. Plasma ARG quantification may therefore represent an attractive biomarker to tailor novel therapeutic regimens targeting the ARG pathway in combination with ICIs.

Molecular and cellular immune features of aged patients with severe COVID-19 pneumonia

Aging is a major risk factor for developing severe COVID-19, but few detailed data are available concerning immunological changes after infection in aged individuals. Here we describe main immune characteristics in 31 patients with severe SARS-CoV-2 infection who were >70 years old, compared to 33 subjects <60 years of age. Differences in plasma levels of 62 cytokines, landscape of peripheral blood mononuclear cells, T cell repertoire, transcriptome of central memory CD4⁺ T cells, specific antibodies are reported along with features of lung macrophages. Elderly subjects have higher levels of pro-inflammatory cytokines, more circulating plasmablasts, reduced plasmatic level of anti-S and anti-RBD IgG3 antibodies, lower proportions of central memory CD4⁺ T cells, more immature monocytes and CD56⁺ pro-inflammatory monocytes, lower percentages of circulating follicular helper T cells (cTfh), antigen-specific cTfh cells with a less activated transcriptomic profile, lung resident activated macrophages that promote collagen deposition and fibrosis. Our study underlines the importance of inflammation in the response to SARS-CoV-2 and suggests that inflammaging, coupled with the inability to mount a proper anti-viral response, could exacerbate disease severity and the worst clinical outcome in old patients.

Patients over the age of 70 show inflammaging and a weaker anti-viral response to SARS-CoV-2, pointing at the immunological changes associated with COVID-19 severity and outcome for aged patients.

Brain Cell Type-Specific Nuclear Proteomics Is Imperative to Resolve Neurodegenerative Disease Mechanisms

Neurodegenerative diseases (NDs) involve complex cellular mechanisms that are incompletely understood. Emerging findings have revealed that disruption of nuclear processes play key roles in ND pathogenesis. The nucleus is a nexus for gene regulation and cellular processes that together, may underlie pathomechanisms of NDs. Furthermore, many genetic risk factors for NDs encode proteins that are either present in the nucleus or are involved in nuclear processes (for example, RNA binding proteins, epigenetic regulators, or nuclear-cytoplasmic transport proteins). While recent advances in nuclear transcriptomics have been significant, studies of the nuclear proteome in brain have been relatively limited. We propose that a comprehensive analysis of nuclear proteomic alterations of various brain cell types in NDs may provide novel biological and therapeutic insights. This may be feasible because emerging technical advances allow isolation and investigation of intact nuclei from post-mortem frozen human brain tissue with cell type-specific and single-cell resolution. Accordingly, nuclei of various brain cell types harbor unique protein markers which can be used to isolate cell-type specific nuclei followed by down-stream proteomics by mass spectrometry. Here we review the literature providing a rationale for investigating proteomic changes occurring in nuclei in NDs and then highlight the potential for brain cell type-specific nuclear proteomics to enhance our understanding of distinct cellular mechanisms that drive ND pathogenesis.

Single-cell spatial analysis of tumor immune architecture in diffuse large B-cell lymphoma

Multiplexed immune cell profiling of the tumor microenvironment (TME) in cancer has improved our understanding of cancer immunology, but complex spatial analyses of tumor-immune interactions in lymphoma are lacking. Here we used imaging mass cytometry (IMC) on 33 cases of diffuse large B cell lymphoma (DLBCL) to characterize tumor and immune cell architecture and correlate it to clinicopathological features such as cell of origin, gene mutations, and responsiveness to chemotherapy. To understand the poor response of DLBCL to immune checkpoint inhibitors (ICI), we compared our results to IMC data from Hodgkin lymphoma (HL), a cancer highly responsive to ICI, and observed differences in the expression of PD-L1, PD-1, and TIM-3. We created a spatial classification of tumor cells and identified tumor-centric sub-regions of immune activation, immune suppression, and immune exclusion within the topology of DLBCL. Finally, the spatial analysis allowed us to identify markers such as CXCR3, which are associated with penetration of immune cells into immune desert regions, with important implications for engineered cellular therapies. This is the first study to integrate tumor mutational profiling, cell of origin classification, and multiplexed immuno-phenotyping of the TME into a spatial analysis of DLBCL at the single cell level. We demonstrate that, far from being histo-pathologically monotonous, DLBCL has a complex tumor architecture, and that changes in tumor topology can be correlated with clinically relevant features. This analysis identifies candidate biomarkers and therapeutic targets such as TIM-3, CCR4, and CXCR3 that are relevant for combination treatment strategies in immuno-oncology and cellular therapies.