Journal Articles

'Omics analyses

Genome, transcriptome, proteome, etc. studies that help to understand and improve cancer immunotherapy

Current Concepts of Antigen Cross-Presentation

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Dendritic cells have the ability to efficiently present internalized antigens on major histocompatibility complex (MHC) I molecules. This process is termed cross-presentation and is important role in the generation of an immune response against viruses and tumors, after vaccinations or in the induction of immune tolerance. The molecular mechanisms enabling cross-presentation have been topic of intense debate since many years. However, a clear view on these mechanisms remains difficult, partially due to important remaining questions, controversial results and discussions. Here, we give an overview of the current concepts of antigen cross-presentation and focus on a description of the major cross-presentation pathways, the role of retarded antigen degradation for efficient cross-presentation, the dislocation of antigens from endosomal compartment into the cytosol, the reverse transport of proteasome-derived peptides for loading on MHC I and the translocation of the cross-presentation machinery from the ER to endosomes. We try to highlight recent advances, discuss some of the controversial data and point out some of the major open questions in the field.

Author Info: (1) Life and Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany. (2) Life and Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany.

Author Info: (1) Life and Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany. (2) Life and Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany.

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Elucidating T Cell Activation-Dependent Mechanisms for Bifurcation of Regulatory and Effector T Cell Differentiation by Multidimensional and Single-Cell Analysis

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In T cells, T cell receptor (TCR) signaling initiates downstream transcriptional mechanisms for T cell activation and differentiation. Foxp3-expressing regulatory T cells (Treg) require TCR signals for their suppressive function and maintenance in the periphery. It is, however, unclear how TCR signaling controls the transcriptional program of Treg. Since most of studies identified the transcriptional features of Treg in comparison to naive T cells, the relationship between Treg and non-naive T cells including memory-phenotype T cells (Tmem) and effector T cells (Teff) is not well understood. Here, we dissect the transcriptomes of various T cell subsets from independent datasets using the multidimensional analysis method canonical correspondence analysis (CCA). We show that at the cell population level, resting Treg share gene modules for activation with Tmem and Teff. Importantly, Tmem activate the distinct transcriptional modules for T cell activation, which are uniquely repressed in Treg. The activation signature of Treg is dependent on TCR signals and is more actively operating in activated Treg. Furthermore, by using a new CCA-based method, single-cell combinatorial CCA, we analyzed unannotated single-cell RNA-seq data from tumor-infiltrating T cells, and revealed that FOXP3 expression occurs predominantly in activated T cells. Moreover, we identified FOXP3-driven and T follicular helper-like differentiation pathways in tumor microenvironments, and their bifurcation point, which is enriched with recently activated T cells. Collectively, our study reveals the activation mechanisms downstream of TCR signals for the bifurcation of Treg and Teff differentiation and their maturation processes.

Author Info: (1) Faculty of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Japan. (2) Faculty of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Japan. (3)

Author Info: (1) Faculty of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Japan. (2) Faculty of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Japan. (3) Department of Life Sciences, Faculty of Natural Sciences, Imperial College London, London, United Kingdom.

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Isolation of a Structural Mechanism for Uncoupling T Cell Receptor Signaling from Peptide-MHC Binding

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TCR-signaling strength generally correlates with peptide-MHC binding affinity; however, exceptions exist. We find high-affinity, yet non-stimulatory, interactions occur with high frequency in the human T cell repertoire. Here, we studied human TCRs that are refractory to activation by pMHC ligands despite robust binding. Analysis of 3D affinity, 2D dwell time, and crystal structures of stimulatory versus non-stimulatory TCR-pMHC interactions failed to account for their different signaling outcomes. Using yeast pMHC display, we identified peptide agonists of a formerly non-responsive TCR. Single-molecule force measurements demonstrated the emergence of catch bonds in the activating TCR-pMHC interactions, correlating with exclusion of CD45 from the TCR-APC contact site. Molecular dynamics simulations of TCR-pMHC disengagement distinguished agonist from non-agonist ligands based on the acquisition of catch bonds within the TCR-pMHC interface. The isolation of catch bonds as a parameter mediating the coupling of TCR binding and signaling has important implications for TCR and antigen engineering for immunotherapy.

Author Info: (1) Departments of Molecular and Cellular Physiology and Structural Biology, Stanford University School of Medicine, Stanford, CA 94305, USA; Immunology Graduate Program, Stanford University School

Author Info: (1) Departments of Molecular and Cellular Physiology and Structural Biology, Stanford University School of Medicine, Stanford, CA 94305, USA; Immunology Graduate Program, Stanford University School of Medicine, Stanford, CA 94305, USA. (2) Departments of Molecular and Cellular Physiology and Structural Biology, Stanford University School of Medicine, Stanford, CA 94305, USA. (3) Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT 84132, USA. (4) Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94143, USA. (5) Department of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125, USA; Materials and Process Simulation Center, California Institute of Technology, Pasadena, CA 91125, USA; Institute for Systems Biology, Seattle, WA 98109, USA. (6) Department of Chemistry, University of California, Berkeley, Berkeley, CA 94720, USA. (7) Departments of Molecular and Cellular Physiology and Structural Biology, Stanford University School of Medicine, Stanford, CA 94305, USA; Immunology Graduate Program, Stanford University School of Medicine, Stanford, CA 94305, USA. (8) Departments of Molecular and Cellular Physiology and Structural Biology, Stanford University School of Medicine, Stanford, CA 94305, USA. (9) Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA. (10) Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA. (11) Departments of Molecular and Cellular Physiology and Structural Biology, Stanford University School of Medicine, Stanford, CA 94305, USA. (12) Departments of Molecular and Cellular Physiology and Structural Biology, Stanford University School of Medicine, Stanford, CA 94305, USA; Immunology Graduate Program, Stanford University School of Medicine, Stanford, CA 94305, USA. (13) Departments of Molecular and Cellular Physiology and Structural Biology, Stanford University School of Medicine, Stanford, CA 94305, USA. (14) Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA 94305, USA. (15) Department of Chemistry, University of California, Berkeley, Berkeley, CA 94720, USA. (16) Department of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125, USA; Materials and Process Simulation Center, California Institute of Technology, Pasadena, CA 91125, USA. (17) Institute for Systems Biology, Seattle, WA 98109, USA. (18) Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT 84132, USA. (19) Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94143, USA; Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA 94143, USA. (20) Departments of Molecular and Cellular Physiology and Structural Biology, Stanford University School of Medicine, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA 94305, USA. Electronic address: kcgarcia@stanford.edu.

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Bacteria-free minicircle DNA system to generate integration-free CAR-T cells

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BACKGROUND: Chimeric antigen receptor T (CAR-T) cells engineered with lentiviral and retroviral vectors have been successfully applied to treat patients with B cell malignancy. However, viral integration in T cells has the potential risk of mutagenesis, and viral vector production demands effort and is costly. Using non-integrative episomal vector such as minicircle vector to generate integration-free CAR-T cells is an attractive option. METHODS AND RESULTS: We established a novel method to generate minicircle vector within a few hours using simple molecular biology techniques. Since no bacteria is involved, we named these vectors bacteria-free (BF) minicircle. In comparison with plasmids, BF minicircle vector enabled higher transgene expression and improved cell viability in human cell line, stem cells and primary T cells. Using BF minicircle vector, we generated integration-free CAR-T cells, which eliminated cancer cells efficiently both in vitro and in vivo. CONCLUSION: BF minicircle vector will be useful in basic research as well as in clinical applications such as CAR-T and gene therapy. Although the transgene expression of minicircle vector lasts apparently shorter than that of insertional lentivirus, multiple rounds of BF minicircle CAR-T cell infusion could eliminate cancer cells efficiently. On the other hand, a relatively shorter CAR-T cell persistence provides an opportunity to avoid serious side effects such as cytokine storm or on-target off-tumour toxicity.

Author Info: (1) School of Life Sciences, University of Science and Technology of China, Hefei, China. State Key Laboratory of Stem Cell and Reproductive Biology, Institute of

Author Info: (1) School of Life Sciences, University of Science and Technology of China, Hefei, China. State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, The Chinese Academy of Sciences, Beijing, China. (2) State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, The Chinese Academy of Sciences, Beijing, China. (3) Northwest Agriculture and Forestry University, Yangling, China. (4) State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, The Chinese Academy of Sciences, Beijing, China. University of the Chinese Academy of Sciences, Beijing, China. (5) State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, The Chinese Academy of Sciences, Beijing, China. University of the Chinese Academy of Sciences, Beijing, China. (6) Beijing Cord Blood Bank, Beijing, China. (7) State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, The Chinese Academy of Sciences, Beijing, China. University of the Chinese Academy of Sciences, Beijing, China.

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Clonal distribution and intratumor heterogeneity of B cell repertoire in esophageal squamous cell carcinoma

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Recent successes in tumour immunotherapies have highlighted importance of tumour immunity. However, most previous studies to date have focused on T cell immune response, although B cells are key players in the core immune network and are associated with T-cell immune response. Based on our previous study delineating T cell receptor (TCR) repertoire in seven patients with esophageal squamous cell carcinoma (ESCC), this study profiled BCR repertoire of multiple tumour regions, adjacent normal tissue and blood from the same seven patients to reveal characteristics of B cell immunity and relationship to TCR repertoire in ESCC patients. We found that intratumour B cell receptor (BCR) repertoire was significantly more oligoclonal than matched adjacent normal tissue or peripheral blood and moreover clonal amplification of B cells in multiple tumour regions was significantly heterogeneous, although clonal amplification of TCR repertoire across different tissue compartments and regions of the same tumour was similar. However, both BCR and TCR repertoires in tumour microenvironment were distinct from those in adjacent normal tissues and blood, and thus represented a group of B and T cells which were spatially confined to the tumour microenvironment and could react to tumour antigens. Additionally, B and T cell clones varying between different tumour regions showed intratumour heterogeneity of B and T cell immune response. Thus, multiple tumour biopsies could be essential to comprehensively delineate the adaptive immune response to an individual ESCC. These findings expand our understanding of adaptive antitumor immunity and shed more light on ESCC immunotherapy. This study provides insights into intratumour heterogeneity of BCR repertoire as well as difference and relationship between BCR and TCR repertoire in ESCC, expanding our understanding of adaptive antitumor immunity and ESCC immunotherapy. This article is protected by copyright. All rights reserved.

Author Info: (1) Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Laboratory of Biochemistry and Molecular Biology, Peking University Cancer Hospital & Institute, Beijing, 100142

Author Info: (1) Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Laboratory of Biochemistry and Molecular Biology, Peking University Cancer Hospital & Institute, Beijing, 100142, China. (2) New York University Langone Medical Center, Department of Pathology, 560 First Avenue, New York, NY, 10016, United States. (3) MyGenostics Inc, Beijing, China. (4) Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Surgery, Peking University Cancer Hospital & Institute, Beijing, 100142, China. (5) Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Laboratory of Biochemistry and Molecular Biology, Peking University Cancer Hospital & Institute, Beijing, 100142, China.

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A Mechanistic Model for Predicting Cell Surface Presentation of Competing Peptides by MHC Class I Molecules

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Major histocompatibility complex-I (MHC-I) molecules play a central role in the immune response to viruses and cancers. They present peptides on the surface of affected cells, for recognition by cytotoxic T cells. Determining which peptides are presented, and in what proportion, has profound implications for developing effective, medical treatments. However, our ability to predict peptide presentation levels is currently limited. Existing prediction algorithms focus primarily on the binding affinity of peptides to MHC-I, and do not predict the relative abundance of individual peptides on the surface of antigen-presenting cells in situ which is a critical parameter for determining the strength and specificity of the ensuing immune response. Here, we develop and experimentally verify a mechanistic model for predicting cell-surface presentation of competing peptides. Our approach explicitly models key steps in the processing of intracellular peptides, incorporating both peptide binding affinity and intracellular peptide abundance. We use the resulting model to predict how the peptide repertoire is modified by interferon-gamma, an immune modulator well known to enhance expression of antigen processing and presentation proteins.

Author Info: (1) Centre for Cancer Immunology and Institute for Life Sciences, Faculty of Medicine, University of Southampton, Southampton, United Kingdom. (2) Centre for Computational Science, Department

Author Info: (1) Centre for Cancer Immunology and Institute for Life Sciences, Faculty of Medicine, University of Southampton, Southampton, United Kingdom. (2) Centre for Computational Science, Department of Chemistry, University College London, London, United Kingdom. CoMPLEX, University College London, London, United Kingdom. (3) Microsoft Research, Cambridge, United Kingdom. (4) Centre for Computational Science, Department of Chemistry, University College London, London, United Kingdom. CoMPLEX, University College London, London, United Kingdom. (5) Centre for Cancer Immunology and Institute for Life Sciences, Faculty of Medicine, University of Southampton, Southampton, United Kingdom. (6) Microsoft Research, Cambridge, United Kingdom.

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TCR signal strength controls the differentiation of CD4+ effector and memory T cells

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Investigating how early TCR activation events affect the differentiation of CD4+ T cells, Snook et al. utilized a set of in vivo-derived TCRs specific for a viral epitope and found that strong TCR signaling corresponded with early high CD25 expression and these cells gave rise almost exclusively to terminally differentiated effector T helper (TH1) cells. Weaker TCR signaling corresponded with lower CD25 expression and differentiation towards T follicular helper cell and memory phenotypes. Memory T cells derived from CD25hi and CD25lo T cells were equally functional upon restimulation. SHP-1 knockdown favored terminal differentiation.

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Investigating how early TCR activation events affect the differentiation of CD4+ T cells, Snook et al. utilized a set of in vivo-derived TCRs specific for a viral epitope and found that strong TCR signaling corresponded with early high CD25 expression and these cells gave rise almost exclusively to terminally differentiated effector T helper (TH1) cells. Weaker TCR signaling corresponded with lower CD25 expression and differentiation towards T follicular helper cell and memory phenotypes. Memory T cells derived from CD25hi and CD25lo T cells were equally functional upon restimulation. SHP-1 knockdown favored terminal differentiation.

CD4(+) T cell responses are composed of heterogeneous T cell receptor (TCR) signals that influence the acquisition of effector and memory characteristics. We sought to define early TCR-dependent activation events that control T cell differentiation. A polyclonal panel of TCRs specific for the same viral antigen demonstrated substantial variability in TCR signal strength, expression of CD25, and activation of nuclear factor of activated T cells and nuclear factor kappaB. After viral infection, strong TCR signals corresponded to T helper cell (TH1) differentiation, whereas T follicular helper cell and memory T cell differentiation were most efficient when TCR signals were comparatively lower. We observed substantial heterogeneity in TCR-dependent CD25 expression in vivo, and the vast majority of CD4(+) memory T cells were derived from CD25(lo) effector cells that displayed decreased TCR signaling in vivo. Nevertheless, memory T cells derived from either CD25(lo) or CD25(hi) effector cells responded vigorously to rechallenge, indicating that, although early clonal differences in CD25 expression predicted memory T cell numbers, they did not predict memory T cell function on a per cell basis. Gene transcription analysis demonstrated expression clustering based on CD25 expression and enrichment of transcripts associated with enhanced T follicular helper cell and memory development within CD25(lo) effector cells. Direct enhancement of TCR signaling via knockdown of Src homology region 2 domain-containing phosphatase 1, a tyrosine phosphatase that suppresses early TCR signaling events, favored the differentiation of TH1 effector and memory cells. We conclude that strong TCR signals during early T cell activation favor terminal TH1 differentiation over long-term TH1 and T follicular helper cell memory responses.

Author Info: (1) Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT 84112, USA. (2) Department of Medicine, Stanford University School of Medicine

Author Info: (1) Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT 84112, USA. (2) Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA. (3) Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT 84112, USA. matthew.williams@path.utah.edu.

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Chemical and genetic control of IFNgamma-induced MHCII expression

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The cytokine interferon-gamma (IFNgamma) can induce expression of MHC class II (MHCII) on many different cell types, leading to antigen presentation to CD4(+) T cells and immune activation. This has also been linked to anti-tumour immunity and graft-versus-host disease. The extent of MHCII upregulation by IFNgamma is cell type-dependent and under extensive control of epigenetic regulators and signalling pathways. Here, we identify novel genetic and chemical factors that control this form of MHCII expression. Loss of the oxidative stress sensor Keap1, autophagy adaptor p62/SQSTM1, ubiquitin E3-ligase Cullin-3 and chromatin remodeller BPTF impair IFNgamma-mediated MHCII expression. A similar phenotype is observed for arsenite, an oxidative stressor. Effects of the latter can be reversed by the inhibition of HDAC1/2, linking oxidative stress conditions to epigenetic control of MHCII expression. Furthermore, dimethyl fumarate, an antioxidant used for the treatment of several autoimmune diseases, impairs the IFNgamma response by manipulating transcriptional control of MHCII We describe novel pathways and drugs related to oxidative conditions in cells impacting on IFNgamma-mediated MHCII expression, which provide a molecular basis for the understanding of MHCII-associated diseases.

Author Info: (1) Department of Cell and Chemical Biology, LUMC, Leiden, The Netherlands. (2) Department of Immunology, MS Center ErasMS, Erasmus MC, University Medical Center, Rotterdam, The

Author Info: (1) Department of Cell and Chemical Biology, LUMC, Leiden, The Netherlands. (2) Department of Immunology, MS Center ErasMS, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. (3) Department of Immunology, MS Center ErasMS, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. (4) Department of Cell and Chemical Biology, LUMC, Leiden, The Netherlands. (5) Department of Immunohematology and Blood Transfusion, LUMC, Leiden, The Netherlands. (6) Department of Immunology, MS Center ErasMS, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. Department of Neurology, MS Center ErasMS, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. (7) Department of Cell and Chemical Biology, LUMC, Leiden, The Netherlands j.j.neefjes@lumc.nl.

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RNA-sequencing in non-small cell lung cancer shows gene downregulation of therapeutic targets in tumor tissue compared to non-malignant lung tissue

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BACKGROUND: Gene expression of specific therapeutic targets in non-malignant lung tissue might play an important role in optimizing targeted therapies. This study aims to identify different expression patterns of fifteen genes important for targeted therapy in non-small cell lung cancer (NSCLC). METHODS: We prospectively collected tissue of NSCLC and non-malignant lung tissue from 25 primary resected patients. RNA-sequencing and 450 K methylation array profiling was applied to both NSCLC and non-malignant lung tissue and data were analyzed for 14 target genes. We analyzed differential expression and methylation as well as expression according to patient characteristics like smoking status, histology, age, chronic obstructive pulmonary disease, C-reactive protein (CRP) and gender. TCGA data served as a validation set. RESULTS: Nineteen men and 6 women were included. Important targets like PD-L2 (p = 0.035), VEGFR2 (p < 0.001) and VEGFR3 (p < 0.001) were downregulated (respective fold changes = 1.8, 3.1, 2.7, 3.5) in tumor compared to non-malignant lung tissue. The TCGA set confirmed these findings almost universally. PD-L1 (p < 0.001) became also significantly downregulated in the TCGA set. In NSCLC, MUC1 (p = 0.003) showed a higher expression in patients with a CRP < 5 mg/L compared to > 5 mg/L. In the TCGA data but not in our primary data, PD-L1 & 2 were both borderline more expressed in tumors of active smokers vs. tumors of ex-smokers (p = 0.044 and 0.052). CONCLUSIONS: Our results suggest a lower PD-L1 & 2 and VEGFR expression in NSCLC vs. non-malignant lung tissue. Specific patient characteristics did not seem to change the overall expression differences as they were in line with the overall results. This information may contribute to the optimization of targeted treatments.

Author Info: (1) Experimental Radiation Oncology, Department of Oncology, KU Leuven, Leuven, Belgium. kobe.reynders@uzleuven.be. Radiation Oncology Department, University Hospitals Gasthuisberg, KU Leuven, Leuven, Belgium. kobe.reynders@uzleuven.be. Lab of

Author Info: (1) Experimental Radiation Oncology, Department of Oncology, KU Leuven, Leuven, Belgium. kobe.reynders@uzleuven.be. Radiation Oncology Department, University Hospitals Gasthuisberg, KU Leuven, Leuven, Belgium. kobe.reynders@uzleuven.be. Lab of Experimental Radiotherapy, UH-Gasthuisberg, CDG-8th floor-box 815, Herestraat 49 - 3000, Leuven, Belgium. kobe.reynders@uzleuven.be. (2) Respiratory Oncology Department, University Hospitals Gasthuisberg, KU Leuven, Leuven, Belgium. (3) Vesalius Research Center (VRC), VIB, KU Leuven, Leuven, Belgium. Laboratory for Translational Genetics, Department of Oncology, KU Leuven, Leuven, Belgium. (4) Department of Thoracic surgery, University Hospital Gasthuisberg, KU Leuven, Leuven, Belgium. (5) Department of Thoracic surgery, University Hospital Gasthuisberg, KU Leuven, Leuven, Belgium. (6) Department of Radiation Oncology (Maastro Clinic), Maastricht University Medical Center, GROW, Maastricht, The Netherlands. (7) Radiation Oncology Department, University Hospitals Gasthuisberg, KU Leuven, Leuven, Belgium. (8) Respiratory Oncology Department, University Hospitals Gasthuisberg, KU Leuven, Leuven, Belgium. (9) Respiratory Oncology Department, University Hospitals Gasthuisberg, KU Leuven, Leuven, Belgium. (10) Respiratory Division, University Hospital Gasthuisberg, KU Leuven, Leuven, Belgium. (11) Respiratory Oncology Department, University Hospitals Gasthuisberg, KU Leuven, Leuven, Belgium. (12) Vesalius Research Center (VRC), VIB, KU Leuven, Leuven, Belgium. Laboratory for Translational Genetics, Department of Oncology, KU Leuven, Leuven, Belgium. (13) Experimental Radiation Oncology, Department of Oncology, KU Leuven, Leuven, Belgium. Department of Radiation Oncology (Maastro Clinic), Maastricht University Medical Center, GROW, Maastricht, The Netherlands.

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A Universal Live Cell Barcoding-Platform for Multiplexed Human Single Cell Analysis

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Single-cell barcoding enables the combined processing and acquisition of multiple individual samples as one. This maximizes assay efficiency and eliminates technical variability in both sample preparation and analysis. Remaining challenges are the barcoding of live, unprocessed cells to increase downstream assay performance combined with the flexibility of the approach towards a broad range of cell types. To that end, we developed a novel antibody-based platform that allows the robust barcoding of live human cells for mass cytometry (CyTOF). By targeting both the MHC class I complex (beta-2-microglobulin) and a broadly expressed sodium-potassium ATPase-subunit (CD298) with platinum-conjugated antibodies, human immune cells, stem cells as well as tumor cells could be multiplexed in the same single-cell assay. In addition, we present a novel palladium-based covalent viability reagent compatible with this barcoding strategy. Altogether, this platform enables mass cytometry-based, live-cell barcoding across a multitude of human sample types and provides a scheme for multiplexed barcoding of human single-cell assays in general.

Author Info: (1) Department of Pathology, School of Medicine, Stanford University, Palo Alto, CA, USA. (2) Department of Neurology, UCSF, San Francisco, CA, USA. (3) Department of

Author Info: (1) Department of Pathology, School of Medicine, Stanford University, Palo Alto, CA, USA. (2) Department of Neurology, UCSF, San Francisco, CA, USA. (3) Department of Pathology, School of Medicine, Stanford University, Palo Alto, CA, USA. bendall@stanford.edu.

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