Consensus gene modules strategy identifies candidate blood-based biomarkers for primary Sjögren's disease.

Primary Sjögren disease (pSD) is an autoimmune disease characterized by lymphoid infiltration of exocrine glands leading to dryness of the mucosal surfaces and by the production of autoantibodies. The pathophysiology of pSD remains elusive and no treatment with demonstrated efficacy is available yet. To better understand the biology underlying pSD heterogeneity, we aimed at identifying Consensus gene Modules (CMs) that summarize the high-dimensional transcriptomic data of whole blood samples in pSD patients. We performed unsupervised gene classification on four data sets and identified thirteen CMs. We annotated and interpreted each of these CMs as corresponding to cell type abundances or biological functions by using gene set enrichment analyses and transcriptomic profiles of sorted blood cell subsets. Correlation with independently measured cell type abundances by flow cytometry confirmed these annotations. We used these CMs to reconcile previously proposed patient stratifications of pSD. Importantly, we showed that the expression of modules representing lymphocytes and erythrocytes before treatment initiation is associated with response to hydroxychloroquine and leflunomide combination therapy in a clinical trial. These consensus modules will help the identification and translation of blood-based predictive biomarkers for the treatment of pSD.

Crosstalk between CD64+MHCII+ macrophages and CD4+ T cells drives joint pathology during chikungunya.

Communications between immune cells are essential to ensure appropriate coordination of their activities. Here, we observed the infiltration of activated macrophages into the joint-footpads of chikungunya virus (CHIKV)-infected animals. Large numbers of CD64+MHCII+ and CD64+MHCII- macrophages were present in the joint-footpad, preceded by the recruitment of their CD11b+Ly6C+ inflammatory monocyte precursors. Recruitment and differentiation of these myeloid subsets were dependent on CD4+ T cells and GM-CSF. Transcriptomic and gene ontology analyses of CD64+MHCII+ and CD64+MHCII- macrophages revealed 89 differentially expressed genes, including genes involved in T cell proliferation and differentiation pathways. Depletion of phagocytes, including CD64+MHCII+ macrophages, from CHIKV-infected mice reduced disease pathology, demonstrating that these cells play a pro-inflammatory role in CHIKV infection. Together, these results highlight the synergistic dynamics of immune cell crosstalk in driving CHIKV immunopathogenesis. This study provides new insights in the disease mechanism and offers opportunities for development of novel anti-CHIKV therapeutics.

Single-cell protein expression profiling resolves circulating and resident memory T cell diversity across tissues and infection contexts.

Memory CD8+ T cells can be broadly divided into circulating (TCIRCM) and tissue-resident memory T (TRM) populations. Despite well-defined migratory and transcriptional differences, the phenotypic and functional delineation of TCIRCM and TRM cells, particularly across tissues, remains elusive. Here, we utilized an antibody screening platform and machine learning prediction pipeline (InfinityFlow) to profile >200 proteins in TCIRCM and TRM cells in solid organs and barrier locations. High-dimensional analyses revealed unappreciated heterogeneity within TCIRCM and TRM cell lineages across nine different organs after either local or systemic murine infection models. Additionally, we demonstrated the relative effectiveness of strategies allowing for the selective ablation of TCIRCM or TRM populations across organs and identified CD55, KLRG1, CXCR6, and CD38 as stable markers for characterizing memory T cell function during inflammation. Together, these data and analytical framework provide an in-depth resource for memory T cell classification in both steady-state and inflammatory conditions.

Characterization of CD4+ and CD8+ T cells responses in the mixed lymphocyte reaction by flow cytometry and single cell RNA sequencing.

Background: The Mixed Lymphocyte Reaction (MLR) consists in the allogeneic co-culture of monocytes derived dendritic cells (MoDCs) with T cells from another donor. This in vitro assay is largely used for the assessment of immunotherapy compounds. Nevertheless, the phenotypic changes associated with lymphocyte responsiveness under MLR have never been thoroughly evaluated. Methods: Here, we used multiplex cytokine and chemokine assays, multiparametric flow cytometry and single cell RNA sequencing to deeply characterize T cells activation and function in the context of CD4+- and CD8+-specific MLR kinetics. Results: We showed that CD4+ and CD8+ T cells in MLR share common classical markers of response such as polyfunctionality, increased proliferation and CD25 expression but differ in their kinetics and amplitude of activation as well as their patterns of cytokines secretion and immune checkpoints expression. The analysis of immunoreactive Ki-67+CD25+ T cells identified PBK, LRR1 and MYO1G as new potential markers of MLR response. Using cell-cell communication network inference and pathway analysis on single cell RNA sequencing data, we also highlighted key components of the immunological synapse occurring between T cells and the stimulatory MoDCs together with downstream signaling pathways involved in CD4+ and CD8+ T cells activation. Conclusion: These results provide a deep understanding of the kinetics of the MLR assay for CD4+ or CD8+ T cells and may allow to better characterize compounds impacting MLR and eventually identify new strategies for immunotherapy in cancer.

Tertiary lymphoid structures generate and propagate anti-tumor antibody-producing plasma cells in renal cell cancer.

The presence of intratumoral tertiary lymphoid structures (TLS) is associated with positive clinical outcomes and responses to immunotherapy in cancer. Here, we used spatial transcriptomics to examine the nature of B cell responses within TLS in renal cell carcinoma (RCC). B cells were enriched in TLS, and therein, we could identify all B cell maturation stages toward plasma cell (PC) formation. B cell repertoire analysis revealed clonal diversification, selection, expansion in TLS, and the presence of fully mature clonotypes at distance. In TLS+ tumors, IgG- and IgA-producing PCs disseminated into the tumor beds along fibroblastic tracks. TLS+ tumors exhibited high frequencies of IgG-producing PCs and IgG-stained and apoptotic malignant cells, suggestive of anti-tumor effector activity. Therapeutic responses and progression-free survival correlated with IgG-stained tumor cells in RCC patients treated with immune checkpoint inhibitors. Thus, intratumoral TLS sustains B cell maturation and antibody production that is associated with response to immunotherapy, potentially via direct anti-tumor effects.

High-throughput single-cell quantification of hundreds of proteins using conventional flow cytometry and machine learning.

Modern immunologic research increasingly requires high-dimensional analyses to understand the complex milieu of cell types that comprise the tissue microenvironments of disease. To achieve this, we developed Infinity Flow combining hundreds of overlapping flow cytometry panels using machine learning to enable the simultaneous analysis of the coexpression patterns of hundreds of surface-expressed proteins across millions of individual cells. In this study, we demonstrate that this approach allows the comprehensive analysis of the cellular constituency of the steady-state murine lung and the identification of previously unknown cellular heterogeneity in the lungs of melanoma metastasis­bearing mice. We show that by using supervised machine learning, Infinity Flow enhances the accuracy and depth of clustering or dimensionality reduction algorithms. Infinity Flow is a highly scalable, low-cost, and accessible solution to single-cell proteomics in complex tissues.

Spatial UMAP and Image Cytometry for Topographic Immuno-oncology Biomarker Discovery.

Multiplex immunofluorescence (mIF) can detail spatial relationships and complex cell phenotypes in the tumor microenvironment (TME). However, the analysis and visualization of mIF data can be complex and time-consuming. Here, we used tumor specimens from 93 patients with metastatic melanoma to develop and validate a mIF data analysis pipeline using established flow cytometry workflows (image cytometry). Unlike flow cytometry, spatial information from the TME was conserved at single-cell resolution. A spatial uniform manifold approximation and projection (UMAP) was constructed using the image cytometry output. Spatial UMAP subtraction analysis (survivors vs. nonsurvivors at 5 years) was used to identify topographic and coexpression signatures with positive or negative prognostic impact. Cell densities and proportions identified by image cytometry showed strong correlations when compared with those obtained using gold-standard, digital pathology software (R2 > 0.8). The associated spatial UMAP highlighted "immune neighborhoods" and associated topographic immunoactive protein expression patterns. We found that PD-L1 and PD-1 expression intensity was spatially encoded-the highest PD-L1 expression intensity was observed on CD163+ cells in neighborhoods with high CD8+ cell density, and the highest PD-1 expression intensity was observed on CD8+ cells in neighborhoods with dense arrangements of tumor cells. Spatial UMAP subtraction analysis revealed numerous spatial clusters associated with clinical outcome. The variables represented in the key clusters from the unsupervised UMAP analysis were validated using established, supervised approaches. In conclusion, image cytometry and the spatial UMAPs presented herein are powerful tools for the visualization and interpretation of single-cell, spatially resolved mIF data and associated topographic biomarker development.

Non-terminally exhausted tumor-resident memory HBV-specific T cell responses correlate with relapse-free survival in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) often develops following chronic hepatitis B virus (HBV) infection and responds poorly to immune checkpoint blockade. Here, we examined the antigen specificities of HCC-infiltrating T cells and their relevance to tumor control. Using highly multiplexed peptide-MHC tetramer staining of unexpanded cells from blood, liver, and tumor tissues from 46 HCC patients, we detected 91 different antigen-specific CD8+ T cell populations targeting HBV, neoantigen, tumor-associated, and disease-unrelated antigens. Parallel high-dimensional analysis delineated five distinct antigen-specific tissue-resident memory T (Trm) cell populations. Intratumoral and intrahepatic HBV-specific T cells were enriched for two Trm cell subsets that were PD-1loTOXlo, despite being clonally expanded. High frequencies of intratumoral terminally exhausted T cells were uncommon. Patients with tumor-infiltrating HBV-specific CD8+ Trm cells exhibited longer-term relapse-free survival. Thus, non-terminally exhausted HBV-specific CD8+ Trm cells show hallmarks of active involvement and effective antitumor response, implying that these cells could be harnessed for therapeutic purposes.

Human Tumor-Infiltrating MAIT Cells Display Hallmarks of Bacterial Antigen Recognition in Colorectal Cancer.

Growing evidence indicates a role for the gut microbiota in modulating anti-tumor treatment efficacy in human cancer. Here we study mucosa-associated invariant T (MAIT) cells to look for evidence of bacterial antigen recognition in human colon, lung, and kidney carcinomas. Using mass cytometry and single-cell mRNA sequencing, we identify a tumor-infiltrating MAIT cell subset expressing CD4 and Foxp3 and observe high expression of CD39 on MAIT cells from colorectal cancer (CRC) only, which we show in vitro to be expressed specifically after TCR stimulation. We further reveal that these cells are phenotypically and functionally exhausted. Sequencing data show high bacterial infiltration in CRC tumors and highlight an enriched species, Fusobacteria nucleatum, with capability to activate MAIT cells in a TCR-dependent way. Our results provide evidence of a MAIT cell response to microbial antigens in CRC and could pave the way for manipulating MAIT cells or the microbiome for cancer therapy.

The murine Microenvironment Cell Population counter method to estimate abundance of tissue-infiltrating immune and stromal cell populations in murine samples using gene expression.

Quantifying tissue-infiltrating immune and stromal cells provides clinically relevant information for various diseases. While numerous methods can quantify immune or stromal cells in human tissue samples from transcriptomic data, few are available for mouse studies. We introduce murine Microenvironment Cell Population counter (mMCP-counter), a method based on highly specific transcriptomic markers that accurately quantify 16 immune and stromal murine cell populations. We validated mMCP-counter with flow cytometry data and showed that mMCP-counter outperforms existing methods. We showed that mMCP-counter scores are predictive of response to immune checkpoint blockade in cancer mouse models and identify early immune impacts of Alzheimer's disease.

Partial absence of PD-1 expression by tumor-infiltrating EBV-specific CD8+ T cells in EBV-driven lymphoepithelioma-like carcinoma.

OBJECTIVES: Lymphoepithelioma-like carcinoma (LELC) is an uncommon lung cancer, typically observed in young, non-smoking Asian populations. LELC is associated with Epstein-Barr virus (EBV) infection of lung tumor cells of epithelial origin, suggesting a carcinogenic role of EBV as observed in nasopharyngeal carcinoma (NPC). Here, we studied the antigen specificity and phenotype of EBV-specific CD8+ T cells in blood and tumor of one LELC patient positive for EBV infection in lung tumor cells. METHODS: Using multiplex MHC class I tetramers, mass cytometry and mRNA sequencing, we studied EBV-specific CD8+ T cells at the transcriptomic and phenotypic levels in blood and tumor tissues of the LELC patient. RESULTS: Lymphoepithelioma-like carcinoma lung tumor cells were positive for EBV infection. In both blood and tumor tissues, we detected two populations of EBV-specific CD8+ T cells targeting the EBV lytic cycle proteins: BRLF1 and BMLF1. Transcriptomic analyses of these two populations in the tumor, which can be considered as tumor-specific, revealed their distinct exhausted profile and polyclonal TCR repertoire. High-dimensional phenotypical analysis revealed the distinct phenotype of these cells between blood and tumor tissues. In tumor tissue, EBV-specific CD8+ TILs were phenotypically heterogeneous, but consistently expressed CD39. Unexpectedly, although the LELC tumor cells expressed abundant PD-L1, these tumor-specific CD8+ tumor-infiltrating lymphocytes (TILs) mostly did not express PD-1. CONCLUSION: Epstein-Barr virus-specific CD8+ TILs in EBV-driven tumor are heterogeneous and partially lack PD-1 expression, suggesting that anti-PD1/PD-L1 immunotherapy may not be an appropriate strategy for disinhibiting EBV-specific cells in the treatment of LELC patients.

Combinatorial Single-Cell Analyses of Granulocyte-Monocyte Progenitor Heterogeneity Reveals an Early Uni-potent Neutrophil Progenitor.

Granulocyte-monocyte progenitors (GMPs) have been previously defined for their potential to generate various myeloid progenies such as neutrophils and monocytes. Although studies have proposed lineage heterogeneity within GMPs, it is unclear if committed progenitors already exist among these progenitors and how they may behave differently during inflammation. By combining single-cell transcriptomic and proteomic analyses, we identified the early committed progenitor within the GMPs responsible for the strict production of neutrophils, which we designate as proNeu1. Our dissection of the GMP hierarchy led us to further identify a previously unknown intermediate proNeu2 population. Similar populations could be detected in human samples. proNeu1s, but not proNeu2s, selectively expanded during the early phase of sepsis at the expense of monocytes. Collectively, our findings help shape the neutrophil maturation trajectory roadmap and challenge the current definition of GMPs.

Publisher Correction: Orchestrating single-cell analysis with Bioconductor.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Orchestrating single-cell analysis with Bioconductor.

Recent technological advancements have enabled the profiling of a large number of genome-wide features in individual cells. However, single-cell data present unique challenges that require the development of specialized methods and software infrastructure to successfully derive biological insights. The Bioconductor project has rapidly grown to meet these demands, hosting community-developed open-source software distributed as R packages. Featuring state-of-the-art computational methods, standardized data infrastructure and interactive data visualization tools, we present an overview and online book (https://osca.bioconductor.org) of single-cell methods for prospective users.

Large-Scale HLA Tetramer Tracking of T Cells during Dengue Infection Reveals Broad Acute Activation and Differentiation into Two Memory Cell Fates.

T cells play important multifaceted roles during dengue infection, and understanding their responses is important for defining correlates of protective immunity and identifying effective vaccine antigens. Using mass cytometry and a highly multiplexed peptide-HLA (human leukocyte antigen) tetramer staining strategy, we probed T cells from dengue patients-a total of 430 dengue and control candidate epitopes-together with key markers of activation, trafficking, and differentiation. During acute disease, dengue-specific CD8+ T cells expressed a distinct profile of activation and trafficking receptors that distinguished them from non-dengue-specific T cells. During convalescence, dengue-specific T cells differentiated into two major cell fates, CD57+ CD127--resembling terminally differentiated senescent memory cells and CD127+ CD57--resembling proliferation-capable memory cells. Validation in an independent cohort showed that these subsets remained at elevated frequencies up to one year after infection. These analyses aid our understanding of the generation of T cell memory in dengue infection or vaccination.

Author Correction: Lung endothelial cell antigen cross-presentation to CD8+T cells drives malaria-associated lung injury.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Lung endothelial cell antigen cross-presentation to CD8+T cells drives malaria-associated lung injury.

Malaria-associated acute respiratory distress syndrome (ARDS) and acute lung injury (ALI) are life-threatening manifestations of severe malaria infections. The pathogenic mechanisms that lead to respiratory complications, such as vascular leakage, remain unclear. Here, we confirm that depleting CD8+T cells with anti-CD8ß antibodies in C57BL/6 mice infected with P. berghei ANKA (PbA) prevent pulmonary vascular leakage. When we transfer activated parasite-specific CD8+T cells into PbA-infected TCRß-/- mice (devoid of all T-cell populations), pulmonary vascular leakage recapitulates. Additionally, we demonstrate that PbA-infected erythrocyte accumulation leads to lung endothelial cell cross-presentation of parasite antigen to CD8+T cells in an IFNγ-dependent manner. In conclusion, pulmonary vascular damage in ALI is a consequence of IFNγ-activated lung endothelial cells capturing, processing, and cross-presenting malaria parasite antigen to specific CD8+T cells induced during infection. The mechanistic understanding of the immunopathogenesis in malaria-associated ARDS and ALI provide the basis for development of adjunct treatments.

Single-Cell Analysis of Human Mononuclear Phagocytes Reveals Subset-Defining Markers and Identifies Circulating Inflammatory Dendritic Cells.

Human mononuclear phagocytes comprise phenotypically and functionally overlapping subsets of dendritic cells (DCs) and monocytes, but the extent of their heterogeneity and distinct markers for subset identification remains elusive. By integrating high-dimensional single-cell protein and RNA expression data, we identified distinct markers to delineate monocytes from conventional DC2 (cDC2s). Using CD88 and CD89 for monocytes and HLA-DQ and FcεRIα for cDC2s allowed for their specific identification in blood and tissues. We also showed that cDC2s could be subdivided into phenotypically and functionally distinct subsets based on CD5, CD163, and CD14 expression, including a distinct subset of circulating inflammatory CD5-CD163+CD14+ cells related to previously defined DC3s. These inflammatory DC3s were expanded in systemic lupus erythematosus patients and correlated with disease activity. These findings further unravel the heterogeneity of DC subpopulations in health and disease and may pave the way for the identification of specific DC subset-targeting therapies.

Late-differentiated effector neoantigen-specific CD8+ T cells are enriched in peripheral blood of non-small cell lung carcinoma patients responding to atezolizumab treatment.

BACKGROUND: There is strong evidence that immunotherapy-mediated tumor rejection can be driven by tumor-specific CD8+ T cells reinvigorated to recognize neoantigens derived from tumor somatic mutations. Thus, the frequencies or characteristics of tumor-reactive, mutation-specific CD8+ T cells could be used as biomarkers of an anti-tumor response. However, such neoantigen-specific T cells are difficult to reliably identify due to their low frequency in peripheral blood and wide range of potential epitope specificities. METHODS: Peripheral blood mononuclear cells (PBMC) from 14 non-small cell lung cancer (NSCLC) patients were collected pre- and post-treatment with the anti-PD-L1 antibody atezolizumab. Using whole exome sequencing and RNA sequencing we identified tumor neoantigens that are predicted to bind to major histocompatibility complex class I (MHC-I) and utilized mass cytometry, together with cellular 'barcoding', to profile immune cells from patients with objective response to therapy (n = 8) and those with progressive disease (n = 6). In parallel, a highly-multiplexed combinatorial tetramer staining was used to screen antigen-specific CD8+ T cells in peripheral blood for 782 candidate tumor neoantigens and 71 known viral-derived control peptide epitopes across all patient samples. RESULTS: No significant treatment- or response associated phenotypic difference were measured in bulk CD8+ T cells. Multiplexed peptide-MHC multimer staining detected 20 different neoantigen-specific T cell populations, as well as T cells specific for viral control antigens. Not only were neoantigen-specific T cells more frequently detected in responding patients, their phenotypes were also almost entirely distinct. Neoantigen-specific T cells from responder patients typically showed a differentiated effector phenotype, most like Cytomegalovirus (CMV) and some types of Epstein-Barr virus (EBV)-specific CD8+ T cells. In contrast, more memory-like phenotypic profiles were observed for neoantigen-specific CD8+ T cells from patients with progressive disease. CONCLUSION: This study demonstrates that neoantigen-specific T cells can be detected in peripheral blood in non-small cell lung cancer (NSCLC) patients during anti-PD-L1 therapy. Patients with an objective response had an enrichment of neoantigen-reactive T cells and these cells showed a phenotype that differed from patients without a response. These findings suggest the ex vivo identification, characterization, and longitudinal follow-up of rare tumor-specific differentiated effector neoantigen-specific T cells may be useful in predicting response to checkpoint blockade. TRIAL REGISTRATION: POPLAR trial NCT01903993 .