High-dimensional Single-cell Analysis Research Articles

High-dimensional single-cell analysis of human natural killer cell heterogeneity

Natural killer (NK) cells are innate lymphoid cells (ILCs) contributing to immune responses to microbes and tumors. Historically, their classification hinged on a limited array of surface protein markers. Here, we used single-cell RNA sequencing (scRNA-seq) and cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) to dissect the heterogeneity of NK cells. We identified three prominent NK cell subsets in healthy human blood: NK1, NK2 and NK3, further differentiated into six distinct subgroups. Our findings delineate the molecular characteristics, key transcription factors, biological functions, metabolic traits and cytokine responses of each subgroup. These data also suggest two separate ontogenetic origins for NK cells, leading to divergent transcriptional trajectories. Furthermore, we analyzed the distribution of NK cell subsets in the lung, tonsils and intraepithelial lymphocytes isolated from healthy individuals and in 22 tumor types. This standardized terminology aims at fostering clarity and consistency in future research, thereby improving cross-study comparisons.

Immune cell profiles associated with human exposure to perfluorinated compounds (PFAS) suggest changes in natural killer, T helper, and T cytotoxic cell subpopulations

Per- and polyfluoroalkyl substances (PFAS) constitutes a group of highly persistent man-made substances. Recent evidence indicates that PFAS negatively impact the immune system. However, it remains unclear how different PFAS are associated with alterations in circulating leukocyte subpopulations. More detailed knowledge of such potential associations can provide better understanding into mechanisms of PFAS immunotoxicity in humans. In this exploratory study, associations of serum levels of common PFAS (perfluorooctanoic acid (PFOA), perfluorooctane sulfonic acid (PFOS), perfluorononanoic acid (PFNA), and perfluorohexane sulfonic acid (PFHxS)) and immune cell profiles of peripheral blood mononuclear cells, both with and without immunostimulation, were investigated. High-dimensional single cell analysis by mass cytometry was done on blood leukocytes from fifty participants in the Norwegian human biomonitoring EuroMix study.Different PFAS were associated with changes in various subpopulations of natural killer (NK), T helper (Th), and cytotoxic T (Tc) cells. Broadly, PFAS concentrations were related to increased frequencies of NK cells and activated subpopulations of NK cells. Additionally, increased levels of activated T helper memory cell subpopulations point to Th2/Th17 and Treg-like skewed profiles. Finally, PFAS concentrations were associated with decreased frequencies of T cytotoxic cell subpopulations with CXCR3+ effector memory (EM) phenotypes. Several of these observations point to biologically plausible mechanisms that may contribute to explaining the epidemiological reports of immunosuppression by PFAS. Our results suggest that PFAS exposures even at relatively low levels are associated with changes in immune cell subpopulations, a finding which should be explored more thoroughly in a larger cohort. Additionally, causal relationships should be confirmed in experimental studies. Overall, this study demonstrates the strength of profiling by mass cytometry in revealing detailed changes in immune cells at a single cell level.

Abstract 124: IRG1-Itaconate Axis Protects From Cholesterol-Induced Inflammation And Atherosclerosis

Atherosclerosis, the major underlying cause of cardiovascular disease (CVD) mortality, is fueled by a failure to resolve lipid-driven inflammation within the vessel wall. Understanding the immunometabolic mechanisms underpinning sustained inflammation within this microenvironment is needed for the development of novel targeted therapies. Immune responsive gene 1 (IRG) is an enzyme that diverts the TCA cycle intermediate, cis-aconitate, to produce itaconate, a metabolite with anti-microbial and anti-inflammatory functions. We used a translational approach to investigate the therapeutic potential of the Irg1-itaconate axis for human atherosclerosis. Using single cell RNA-sequencing, we found that IRG1 is upregulated in human coronary atherosclerotic lesions compared to patient-matched healthy vasculature, and is primarily expressed by plaque monocytes and macrophages. In mouse models of atherosclerosis, Irg1 was expressed by plaque monocytes, macrophage and neutrophils, but declined with disease progression. Global or hematopoietic Irg1 -deficiency increased atherosclerosis burden, plaque lipid content, and expression of interleukin (IL)-1b. Mechanistically, absence of Irg1 potentiates lipid accumulation and lipid-mediated inflammation via a feed-forward cycle involving increased neutrophil extracellular trap (NET) formation, NET-induced NLRP3 inflammasome priming in macrophages, and subsequent IL-1b release. Conversely, supplementation of the Irg1 pathway using the derivative 4-octyl itaconate (4-OI) reduced atherosclerotic inflammation and promoted beneficial plaque remodeling in mice. To assess the therapeutic potential of 4-OI in humans, we leveraged a validated systems-immunology approach to investigate CVD-related inflammation ex vivo . Using high dimensional single cell analyses, we showed that 4-OI supplementation attenuated pro-inflammatory phospho-signaling in human peripheral blood mononuclear cells treated with plasma from CVD patients, and caused an anti-inflammatory rewiring of macrophage populations. Our data highlight the relevance of pursuing Irg1 -itaconate axis supplementation as a therapeutic approach to treat atherosclerosis in humans.

Single-Cell Informatics for Tumor Microenvironment and Immunotherapy.

Cancer comprises malignant cells surrounded by the tumor microenvironment (TME), a dynamic ecosystem composed of heterogeneous cell populations that exert unique influences on tumor development. The immune community within the TME plays a substantial role in tumorigenesis and tumor evolution. The innate and adaptive immune cells "talk" to the tumor through ligand-receptor interactions and signaling molecules, forming a complex communication network to influence the cellular and molecular basis of cancer. Such intricate intratumoral immune composition and interactions foster the application of immunotherapies, which empower the immune system against cancer to elicit durable long-term responses in cancer patients. Single-cell technologies have allowed for the dissection and characterization of the TME to an unprecedented level, while recent advancements in bioinformatics tools have expanded the horizon and depth of high-dimensional single-cell data analysis. This review will unravel the intertwined networks between malignancy and immunity, explore the utilization of computational tools for a deeper understanding of tumor-immune communications, and discuss the application of these approaches to aid in diagnosis or treatment decision making in the clinical setting, as well as the current challenges faced by the researchers with their potential future improvements.

Abstract C029: Multiple non-redundant immune checkpoints direct therapeutic resistance to chemotherapy and anti-CSF1R in pancreatic ductal adenocarcinoma

Abstract A hallmark of pancreatic ductal adenocarcinoma (PDA) is the formation of a myeloid rich immunosuppressive microenvironment which acts as a barrier to treatment. Therapeutic blockade/depletion of immunosuppressive myeloid cells in combination with chemotherapy or anti-PD-1 checkpoint blockade is under investigation in PDA but has yet to demonstrate broad clinical success. Here, we studied mechanisms of resistance to myeloid-targeted therapy to inform rational combination strategies. Spatial and molecular profiling of the tumor microenvironment in mouse and human PDA revealed vast intra-tumoral myeloid heterogeneity. Depletion of distinct myeloid cell populations triggered T cell infiltration into tumors but also provoked compensatory remodeling of the myeloid compartment. However, concurrent depletion of multiple myeloid subsets using drugs targeting CSF1R, CCR2/5, and CXCR2 was unexpectedly insufficient to overcome treatment resistance and failed to restore productive T cell surveillance in murine models of PDA. Therefore, we next investigated the role of the lymphoid compartment. High-dimensional single cell analyses of T cell infiltrates in PDA revealed an upregulation of multiple checkpoint molecules, including PD-1, LAG3 and CTLA-4, in both mice and humans, suggesting potential resistance mechanisms. In contrast to combinatory myeloid cell depletion, combined blockade of PD-1, LAG3, and CTLA-4 with gemcitabine and anti-CSF1R triggered peripheral CD4+ and CD8+ T cell activation and produced deep and durable tumor responses with a nearly 3-fold increase in median survival and in some cases, tumor cures. Taken together, these studies highlight the contribution of multiple immune checkpoints to cancer immune evasion and reveal a novel role for LAG3 in treatment resistance in PDA. Together, these findings suggest that a multipronged approach to disrupting negative regulatory signals controlling T cell function may be needed to realize the potential of immunotherapy in PDA. Citation Format: Meredith L. Stone, Veronica M. Herrera, Yan Li, Heather Coho, Yuqing Yue, Kathleen Graham, Devora Delman, Shaun O'Brien, Gregory L. Beatty. Multiple non-redundant immune checkpoints direct therapeutic resistance to chemotherapy and anti-CSF1R in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr C029.

EXTH-64. ESTABLISHING A CLINICALLY RELEVANT MOUSE MODEL OF MESENCHYMAL GLIOBLASTOMA FOR STUDYING TME TARGETING TREATMENTS

Abstract Historically, pre-clinical GBM models have largely failed to predict response in the clinical setting. Here, we establish a more clinically faithful model using the syngeneic NFpp10a-Luc2 mesenchymal-GBM cell line to study response to resection and temozolomide (TMZ), adjuvant/neo-adjuvant anti-PD1 and Regorafenib (REGO) therapy. Cells were orthotopically implanted in C57BL/6-mice. Response to surgical and therapeutic interventions was assessed using bioluminescence imaging (BLI). Murine Microenvironment cell-population (mMCP)-counter, GSEA and multiple iteractive labelling by antibody neodeposition (MILAN, high-dimensional single-cell multiplex analysis) were employed to characterise treatment-related TME effects. We observed survival advantage in aged mice undergoing resection (resection:33.5 days vs non-resection:18 days; p = 0.0166). TMZ/anti-PD1 had no impact on tumour growth (TMZ: p = 0.9001, anti-PD1: p = 0.7933) or survival (TMZ:p = 0.3035, anti-PD1-:p = 0.6328). Neo-adjuvant anti-PD1 also conferred no survival advantage in young mice (33 vs 35 days; p = 0.9429). REGO/REGO+TMZ treatment conferred no survival benefit in young mice (REGO:p = 0.0735 and REGO+TMZ:p = 0.3945). mMCP-counter (which estimates the abundance of TME-cell populations from gene-expression data) showed resection upregulated B-cells and mast-cells, whereas TMZ caused a decreased abundance of vessels. Anti-PD1 treatment caused an enrichment of B-cells, mast-cells, and CXCR3 expression (p = 0.0045). REGO/TMZ+REGO treatment upregulated cytotoxic-lymphocyte populations. MILAN analysis showed resection increased cytotoxic-T-cells (20.3% vs pre-resection:7%). In contrast, TMZ/REGO monotherapy increased tumour-cells and decreased cytotoxic-T-cells. Anti-PD1 decreased macrophage abundance (39.8% vs control:14.5%). Likewise, TMZ+REGO decreased macrophages (11.3% vs control:35.3%) but upregulated B-cells and vessels. Overall, we have characterised response of the NFpp10a mouse model to resection, TMZ, anti-PD1 and REGO. We have shown that the model is insensitive to chemotherapy and TME-targeting therapies, mirroring patient-response patterns. Nevertheless, we observe transcriptomic and proteomic changes following TME-targeting treatments. Further analyses of these TME-associated resistance properties may help guide novel combinatorial treatment regimens. Overall, the NFpp10a model of mesenchymal GBM may be employed in future pre-clinical studies to accurately guide future clinical trials.

High-dimensional single-cell proteomics analysis of esophageal squamous cell carcinoma reveals dynamic alterations of the tumor immune microenvironment after neoadjuvant therapy

BackgroundDynamic alterations of the tumor immune microenvironment in esophageal squamous cell carcinoma (ESCC) after different neoadjuvant therapies were understudied.MethodsWe used mass cytometry with a 42-antibody panel for 6 adjacent normal...

Platinum-Chimeric Carrier Cells for Ultratrace Cell Analysis in Mass Cytometry.

Mass cytometry by time-of-flight (CyTOF), a high-dimensional single-cell analysis platform, detects up to 50 biomarkers at single-cell resolution. However, CyTOF analysis of biological samples with a minimal number of available cells or rare cell subsets remains a major technical challenge due to the extensive loss of cells during cell recovery, staining, and acquisition. Here, we introduce a platinum-chimeric carrier cell strategy for mass cytometry profiling of ultratrace cell samples. Cisplatin can rapidly enter broken plasma membranes of dead cells and form a chimeric interaction with cellular proteins, peptides, and amino acids. Thus, 198Pt-cisplatin is adopted to tag carrier cells in the pretreatment stage. We investigated 8 cell lines that are commonly accessible in laboratories for their potential as carrier cells to preserve rare target cells for CyTOF analysis. We designed a panel of 35 protein biomarkers to evaluate the comprehensive single-cell subtype classification capability with or without the carrier cell strategy. We further demonstrated the detection and analysis of as few as 1 × 104 immune cells using our method. The proposed method thus allows CyTOF analysis on precious clinical samples with less abundant cells.

Feasibility of mass cytometry proteomic characterisation of circulating tumour cells in head and neck squamous cell carcinoma for deep phenotyping

BackgroundCirculating tumour cells (CTCs) are a potential cancer biomarker, but current methods of CTC analysis at single-cell resolution are limited. Here, we describe high-dimensional single-cell mass cytometry proteomic analysis of CTCs in HNSCC.MethodsParsortix microfluidic-enriched CTCs from 14 treatment-naïve HNSCC patients were analysed by mass cytometry analysis using 41 antibodies. Immune cell lineage, epithelial-mesenchymal transition (EMT), stemness, proliferation and immune checkpoint expression was assessed alongside phosphorylation status of multiple signalling proteins. Patient-matched tumour gene expression and CTC EMT profiles were compared. Standard bulk CTC RNAseq was performed as a baseline comparator to assess mass cytometry data.ResultsCTCs were detected in 13/14 patients with CTC counts of 2–24 CTCs/ml blood. Unsupervised clustering separated CTCs into epithelial, early EMT and advanced EMT groups that differed in signalling pathway activation state. Patient-specific CTC cluster patterns separated into immune checkpoint low and high groups. Patient tumour and CTC EMT profiles differed. Mass cytometry outperformed bulk RNAseq to detect CTCs and characterise cell phenotype.DiscussionWe demonstrate mass cytometry allows high-plex proteomic characterisation of CTCs at single-cell resolution and identify common CTC sub-groups with potential for novel biomarker development and immune checkpoint inhibitor treatment stratification.

Single-cell mapping reveals several immune subsets associated with liver metastasis of pancreatic ductal adenocarcinoma

Identifying a metastasis-correlated immune cell composition within the tumor microenvironment (TME) of pancreatic ductal adenocarcinoma (PDAC) will help to develop promising and innovative therapeutic strategies. However, the dynamics of immune cell lineages in the TME of advanced PDAC remains elusive. Twenty-six samples from 11 patients (including 11 primary tumor tissues, 10 blood, and 5 lymph nodes) with different stages were used to develop a multiscale immune profile. High-dimensional single-cell analysis with mass cytometry was performed to search for metastasis-correlated immune changes in the microenvironment. The findings were further validated by published single-cell RNA sequencing (scRNA-seq) data and multiplex fluorescent immunohistochemistry. High-dimensional single-cell profiling revealed that the three immune-relevant sites formed a distinct immune atlas. Interestingly, thePDAC microenvironment with the potential for metastatic spread to the liver was characterized by a decreased proportion of CD103+PD-1+CD39+ Tcells with cytotoxic and exhausted functional status and an increased proportion of CD73+ macrophages. Analysis of scRNA-seq data of PDAC further confirmed the identified subsets and revealed strong potential interactions via various ligand-receptor pairs between the identified T subsets and the macrophages. Moreover, stratified patients with different immune compositions correlated with clinical outcomes of PDAC. Our study uncovered metastasis-correlated immune changes, suggesting that ecosystem-based patient classification in PDAC will facilitate the identification of candidates likely to benefit from immunotherapy. This work was supported by the National Key Research and Development Program of China, the Shanghai International Science and Technology Collaboration Program, the Shanghai Sailing Program, and the Key Laboratory of diagnosis and treatment of severe hepato-pancreatic diseases of Zhejiang Province.

High-dimensional single-cell analysis unveils distinct immune signatures of peripheral blood in patients with pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies with poor response to immune checkpoint inhibitors. The mechanism of such poor response is not completely understood. We assessed T-cell receptor (TCR) repertoire and RNA expression at the single-cell level using high-dimensional sequencing of peripheral blood immune cells isolated from PDAC patients and from healthy human controls. We validated RNA-sequencing data by performing mass cytometry (CyTOF) and by measuring serum levels of multiple immune checkpoint proteins. We found that proportions of T cells (CD45+CD3+) were decreased in PDAC patients compared to healthy controls, while proportion of myeloid cells was increased. The proportion of cytotoxic CD8+ T cells and the level of cytotoxicity per cell were increased in PDAC patients, with reduced TCR clonal diversity. We also found a significantly enriched S100A9+ monocyte population and an increased level of TIM-3 expression in immune cells of peripheral blood in PDAC patients. In addition, the serum level of soluble TIM-3 (sTIM-3) was significantly higher in PDAC patients compared to the non-PDAC participants and correlated with worse survival in two independent PDAC cohorts. Moreover, sTIM-3 exhibited a valuable role in diagnosis of PDAC, with sensitivity and specificity of about 80% in the training and validation groups, respectively. We further established an integrated model by combining sTIM-3 and carbohydrate antigen 19- 9 (CA19-9), which had an area under the curve of 0.974 and 0.992 in training and validation cohorts, respectively. Our RNA-seq and proteomic results provide valuable insight for understanding the immune cell composition of peripheral blood of patients with PDAC.

CosTaL: an accurate and scalable graph-based clustering algorithm for high-dimensional single-cell data analysis.

With the aim of analyzing large-sized multidimensional single-cell datasets, we are describing a method for Cosine-based Tanimoto similarity-refined graph for community detection using Leiden's algorithm (CosTaL). As a graph-based clustering method, CosTaL transforms the cells with high-dimensional features into a weighted k-nearest-neighbor (kNN) graph. The cells are represented by the vertices of the graph, while an edge between two vertices in the graph represents the close relatedness between the two cells. Specifically, CosTaL builds an exact kNN graph using cosine similarity and uses the Tanimoto coefficient as the refining strategy to re-weight the edges in order to improve the effectiveness of clustering. We demonstrate that CosTaL generally achieves equivalent or higher effectiveness scores on seven benchmark cytometry datasets and six single-cell RNA-sequencing datasets using six different evaluation metrics, compared with other state-of-the-art graph-based clustering methods, including PhenoGraph, Scanpy and PARC. As indicated by the combined evaluation metrics, Costal has high efficiency with small datasets and acceptable scalability for large datasets, which is beneficial for large-scale analysis.

MP14-11 SINGLE CELL-BASED IMMUNE PROFILING OF THE TUMOR AND ITS IMMUNE MICROENVIRONMENT REVEALED DIFFERENCES BETWEEN NMIBC AND MIBC: IMPLICATION FOR IMMUNO-THERAPY

You have accessJournal of UrologyCME1 Apr 2023MP14-11 SINGLE CELL-BASED IMMUNE PROFILING OF THE TUMOR AND ITS IMMUNE MICROENVIRONMENT REVEALED DIFFERENCES BETWEEN NMIBC AND MIBC: IMPLICATION FOR IMMUNO-THERAPY Massimo Lazzeri, NicolòMaria Buffi, Giovanni Lughezzani, Paolo Casale, Roberto Hurle, Alberto Saita, Vittorio Fasulo, Marco Paciotti, Marta Pandini, Roberta Carriero, Mattia Carvetta, Marta Iovino, Piergiuseppe Colombo, Grazia Elefante, Gianluca Basso, Sergio Marchini, Paolo Kunderfranco, and Diletta Di Mitri Massimo LazzeriMassimo Lazzeri More articles by this author , NicolòMaria BuffiNicolòMaria Buffi More articles by this author , Giovanni LughezzaniGiovanni Lughezzani More articles by this author , Paolo CasalePaolo Casale More articles by this author , Roberto HurleRoberto Hurle More articles by this author , Alberto SaitaAlberto Saita More articles by this author , Vittorio FasuloVittorio Fasulo More articles by this author , Marco PaciottiMarco Paciotti More articles by this author , Marta PandiniMarta Pandini More articles by this author , Roberta CarrieroRoberta Carriero More articles by this author , Mattia CarvettaMattia Carvetta More articles by this author , Marta IovinoMarta Iovino More articles by this author , Piergiuseppe ColomboPiergiuseppe Colombo More articles by this author , Grazia ElefanteGrazia Elefante More articles by this author , Gianluca BassoGianluca Basso More articles by this author , Sergio MarchiniSergio Marchini More articles by this author , Paolo KunderfrancoPaolo Kunderfranco More articles by this author , and Diletta Di MitriDiletta Di Mitri More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003234.11AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Novel predictive tools to guide treatment decision are required and novel therapies are needed. Immunotherapies are under investigation and hold strong promise, however efficacy is still limited. On this line, a comprehensive analysis of the immune infiltrate in BC would reveal mechanisms of resistance and unveil novel targets. METHODS: Here we investigated the profile of the immune microenvironment in NMBC and MIBC patients by high dimensional single cell analysis, including scRNAseq and Imaging Mass Cytometry. For the scRNAseq analysis, we enrolled NMBC and MIBC patients and we FACS sorted CD45+ immune cells and CD45- epithelia and stromal cells. Cells were then processed by 3’-based scRNA-seq strategy (10X Genomics) that revealed the transcriptional landscape of sorted populations. Additional patients were enrolled for the Cytomass analysis. Tissue sections were snap frozen, stained and acquired by Hyperion system. The primary endpoint was to unveil differences in the composition and tumor and immune cells in NMIBC and MIBC tumors. RESULTS: The entire cohort consisted of 14 patients with clinically significant bladder cancer who underwent radical cystectomy and TURBT. Our analysis identified differences in immune cells abundance and activation state when comparing NMBC and MIBC samples. Modulations were particularly evident for a subset of PLIN2+ Tumor associated macrophages (TAMs) that was enriched in invasive tumors (Fold change=8.37). In the lymphoid compartment, T regulatory cells (Tregs) showed strong transcriptional changes between NMBC and MIBC samples, that suggest a higher fitness and suppressive function in Tregs that infiltrate MIBC. In addition, our analysis revealed a high heterogeneity in the composition of tumor cells in both cohorts (Figure 1). Finally, Cytomass analysis unveiled modulations in immune cells activation and spatial localization when comparing NMBC and MIBC that will be further investigated. CONCLUSIONS: Our study supports the effectiveness of single cell RNA sequencing in the dissection of the immune landscape in BC and identified immune changes when comparing neoplastic tissue from MIBC with NMBC patients. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e186 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Massimo Lazzeri More articles by this author NicolòMaria Buffi More articles by this author Giovanni Lughezzani More articles by this author Paolo Casale More articles by this author Roberto Hurle More articles by this author Alberto Saita More articles by this author Vittorio Fasulo More articles by this author Marco Paciotti More articles by this author Marta Pandini More articles by this author Roberta Carriero More articles by this author Mattia Carvetta More articles by this author Marta Iovino More articles by this author Piergiuseppe Colombo More articles by this author Grazia Elefante More articles by this author Gianluca Basso More articles by this author Sergio Marchini More articles by this author Paolo Kunderfranco More articles by this author Diletta Di Mitri More articles by this author Expand All Advertisement PDF downloadLoading ...

Applying single-cell highly multiplexed secretome proteomics to characterize immunotherapeutic products and predict clinical responses.

Genetically and phenotypically identical immune cell populations can be highly heterogenous in terms of their immune functions and protein secretion profiles. The microfluidic chip-based single-cell highly multiplexed secretome proteomics enables characterization of cellular heterogeneity of immune responses at different cellular and molecular layers. Increasing evidence has demonstrated that polyfunctional T cells that simultaneously produce 2+ proteins per cell at the single-cell level are key effector cells that contribute to the development of potent and durable cellular immunity against pathogens and cancers. The functional proteomic technology offers a wide spectrum of cellular function assessment and can uniquely define highly polyfunctional cell subsets with cytokine signatures from live individual cells. This high-dimensional single-cell analysis provides deep dissection into functional heterogeneity and helps identify predictive biomarkers and potential correlates that are crucial for immunotherapeutic product design optimization and personalized immunotherapy development to achieve better clinical outcomes.

OP05 High-dimensional single-cell analysis identifies cellular signatures associated with response to vedolizumab therapy in ulcerative colitis

Abstract Background The unpredictability of response to biological therapy in ulcerative colitis (UC) patients, including vedolizumab (VDZ), an anti-α4β7 integrin antibody, poses a serious challenge for medical care. This study aims to identify the relevant cellular and molecular signatures that mark response to VDZ by combining single-cell transcriptomics (scRNAseq) and high-dimensional flow cytometry (Cytek). Methods Gut biopsies and peripheral blood mononuclear cells (PBMCs) from patients with active UC were collected 2 weeks prior and 14 weeks after starting VDZ therapy. Response was evaluated at week 14 based on endoscopy and Physician Global Assessment. Transcriptome profiles of 159.188 and 95.057 high-quality single cells were generated from biopsies and PBMCs, respectively. Additional 797.670 CD45+ mucosal cells and 900.000 PBMCs were processed for validating scRNAseq results by Cytek. Results From a total of 25 UC patients (mean age 41±12.7 years, 52% female, 36% anti-TNFα naive), 15 patients (60%) reached response at week 14. Patients with no prior use of anti-TNFα were more likely to achieve remission with VDZ compared to anti-TNFα exposed patients (89% vs 44% response rate, respectively). Analysis of cell abundances revealed a partial recovery of the epithelial and stromal cell mucosal compartments in responders at week 14. Both scRNAseq and Cytek show that in responders VDZ prevented T cells (CD8+IL17+ and CD4+PD1+ subsets) and innate immune cells (NKs, DCs and inflammatory monocytes) from entering mucosa, resulting in their enrichment in PBMCs. In contrast, non-response to VDZ was marked by an expansion of inflammatory fibroblasts and activated endothelial cells, and depletion of most epithelial subsets. VDZ retained CD4 T cells in PBMCs in non-responders, but failed to halt active mucosal inflammation at week 14. Strikingly, involvement of the innate immune cells in UC inflammation prior to VDZ treatment was much more prominent in non-responders who showed higher baseline abundance of NKs, ILCs, γδ-T cells, DCs and inflammatory monocytes in their peripheral blood and mucosa compared to responders. While VDZ inhibited integrin β7 expression on circulating T cells in all patients, only in responders it coincided with the lower mucosal abundance of lymphocytes, suggesting that T cells in non-responders might employ alternative, β7-independent trafficking routes. Conclusion This is the largest prospective scRNAseq study addressing the response to biological therapy in UC. We showed that active, innate immune cell-mediated inflammation marks the primary non-response to VDZ that persists prior to and throughout the treatment, accompanied by β7-independent lymphocyte migration.

Machine learning empowered multi-stress level electromechanical phenotyping for high-dimensional single cell analysis

Microfluidics provides a powerful platform for biological analysis by harnessing the ability to precisely manipulate fluids and microparticles with integrated microsensors. Here, we introduce an imaging and impedance cell analyzer (IM2Cell), which implements single cell level impedance analysis and hydrodynamic mechanical phenotyping simultaneously. For the first time, IM2Cell demonstrates the capability of multi-stress level mechanical phenotyping. Specifically, IM2Cell is capable of characterizing cell diameter, three deformability responses, and four electrical properties. It presents high-dimensional information to give insight into subcellular components such as cell membrane, cytoplasm, cytoskeleton, and nucleus. In this work, we first validate imaging and impedance-based cell analyses separately. Then, the two techniques are combined to obtain both imaging and impedance data analyzed by machine learning method, exhibiting an improved prediction accuracy from 83.1% to 95.4% between fixed and living MDA-MB-231 breast cancer cells. Next, IM2Cell demonstrates 91.2% classification accuracy in a mixture of unlabeled MCF-10A, MCF-7, and MDA-MB-231 cell lines. Finally, an application demonstrates the potential of IM2Cell for the deformability studies of peripheral blood mononuclear cells (PBMCs) subpopulations without cumbersome isolation or labeling steps.

A 31-plex panel for high-dimensional single-cell analysis of murine preclinical models of solid tumors by imaging mass cytometry.

Currently, the study of resistance mechanisms and disease progression in cancer relies on the capacity to analyze tumors as a complex ecosystem of healthy and malignant cells. Therefore, one of the current challenges is to decipher the intra-tumor heterogeneity and especially the spatial distribution and interactions of the different cellular actors within the tumor. Preclinical mouse models are widely used to extend our understanding of the tumor microenvironment (TME). Such models are becoming more sophisticated and allow investigating questions that cannot be addressed in clinical studies. Indeed, besides studying the tumor cell interactions within their environment, mouse models allow evaluating the efficacy of new drugs and delivery approaches, treatment posology, and toxicity. Spatially resolved analyses of the intra-tumor heterogeneity require global approaches to identify and localize a large number of different cell types. For this purpose, imaging mass cytometry (IMC) is a major asset in the field of human immuno-oncology. However, the paucity of validated IMC panels to study TME in pre-clinical mouse models remains a critical obstacle to translational or basic research in oncology. Here, we validated a panel of 31 markers for studying at the single-cell level the TME and the immune landscape for discovering/characterizing cells with complex phenotypes and the interactions shaping the tumor ecosystem in mouse models.

Glucocorticoids target the CXCL9/CXCL10-CXCR3 axis and confer protection against immune-mediated kidney injury.

Glucocorticoids remain a cornerstone of therapeutic regimes for autoimmune and chronic inflammatory diseases - for example, in different forms of crescentic glomerulonephritis - because of their rapid antiinflammatory effects, low cost, and wide availability. Despite their routine use for decades, the underlying cellular mechanisms by which steroids exert their therapeutic effects need to be fully elucidated. Here, we demonstrate that high-dose steroid treatment rapidly reduced the number of proinflammatory CXCR3+CD4+ T cells in the kidney by combining high-dimensional single-cell and morphological analyses of kidney biopsies from patients with antineutrophil cytoplasmic antibody-associated (ANCA-associated) crescentic glomerulonephritis. Using an experimental model of crescentic glomerulonephritis, we show that the steroid-induced decrease in renal CD4+ T cells is a consequence of reduced T cell recruitment, which is associated with an ameliorated disease course. Mechanistic in vivo and in vitro studies revealed that steroids act directly on renal tissue cells, such as tubular epithelial cells, but not on T cells, which resulted in an abolished renal expression of CXCL9 and CXCL10 as well as in the prevention of CXCR3+CD4+ T cell recruitment to the inflamed kidneys. Thus, we identified the CXCL9/CXCL10-CXCR3 axis as a previously unrecognized cellular and molecular target of glucocorticoids providing protection from immune-mediated pathology.

A 16-color full spectrum flow cytometric analysis for comprehensive evaluation of T-cell reconstitution in SIV-infected rhesus macaques

T-cell reconstitution is central in human immunodeficiency virus (HIV) infection/disease progression. Simian immunodeficiency virus (SIV)-infected rhesus macaques (Macaca mulatta) have been the most widely used animal model for HIV research so far. An effective flow cytometry panel is crucial for monitoring the T cell reconstitution in SIV infection progression. We developed this sixteen-color flow cytometry-based panel for a T cell subsets analysis by manual gating and, once successfully gated, to characterize T cells function in-depth in rhesus macaques. This panel included markers to characterize CD4+ T cells and CD8+ T cells, T regulatory cells (Tregs), and T cell differentiation status (CD45RA and CCR7). Additionally, we included antibodies that measure T cell activation and proliferation molecules (CD69, HLA-DR, CD38 and Ki67), antibodies that examine the expressions of key PD-1 pathway molecule (PD-1), SIV potential target (CD32) and the primary SIV co-receptor CCR5 (CD195). High-dimensional single cell analysis was also performed to identify CD3+ T cells immunophenotypes of SIV-infected rhesus macaques. We designed this panel to evaluate the responses of different T cell subsets to SIV in whole blood from SIV-infected rhesus macaques.

Tellurium-containing polymer for mass cytometry

Mass cytometry is a powerful analytical technique for high-dimensional single-cell analysis. In this technique, cells are stained with heavy isotope-tagged antibodies and are analyzed by an inductively coupled plasma time-of-flight mass spectrometer. While the current mass cytometer has more than 100 mass channels, only about 50 are used because reagents are only available for a fraction of the useful elements. Here we describe the synthesis of a tellurium-containing polymer based on poly-l-lysine and sulfated tellurophene. The polymer carried ca. 48 tellurophene units per chain and had a terminal azide group for antibody conjugation. While the polymer could be conjugated to antibodies, the resulting conjugates gave mixed results in mass cytometry immunoassays. For example, a goat anti-mouse (secondary) antibody and an anti-CD19 primary Ab labeled with polymers gave promising results in antibody titration experiments. However, an anti-CD20 Ab labeled with a 126Te-enriched polymer no longer recognized the antigen and showed significant non-specific binding in a 7-plex assay with human PBMCs.