Journal Articles

'Omics analyses

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

Genomic correlates of response to immune checkpoint therapies in clear cell renal cell carcinoma

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Immune checkpoint inhibitors targeting the programmed cell death-1 receptor (PD-1) improve survival in a subset of patients with clear cell renal cell carcinoma (ccRCC). To identify genomic alterations in ccRCC that correlate with response to anti-PD-1 monotherapy, we performed whole exome sequencing of metastatic ccRCC from 35 patients. We found that clinical benefit was associated with loss-of-function mutations in the PBRM1 gene (p=0.012), which encodes a subunit of a SWI/SNF chromatin remodeling complex (the PBAF subtype). We confirmed this finding in an independent validation cohort of 63 ccRCC patients treated with PD-(L)1 blockade therapy alone or in combination with anti-CTLA-4 therapies (p=0.0071). Gene expression analysis of PBAF-deficient ccRCC cell lines and PBRM1-deficient tumors revealed altered transcriptional output in JAK/STAT, hypoxia, and immune signaling pathways. PBRM1 loss in ccRCC may alter global tumor cell expression profiles to influence responsiveness to immune checkpoint therapy.

Author Info: (1) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA 02142

Author Info: (1) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA 02142, USA. (2) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA 02142, USA. (3) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (4) Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA. Weill Cornell Medical College, New York, NY 10065, USA. (5) Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (6) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (7) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (8) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (9) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA 02142, USA. (10) Bristol-Myers Squibb, New York, NY 10154, USA. (11) Bristol-Myers Squibb, New York, NY 10154, USA. (12) Bristol-Myers Squibb, New York, NY 10154, USA. (13) Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA 02142, USA. (14) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA 02142, USA. (15) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (16) Columbia University Medical Center, New York, NY 10032, USA. (17) James Buchanan Brady Urological Institute and Department of Urology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA. (18) James Buchanan Brady Urological Institute and Department of Urology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA. (19) Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA. (20) Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA. Weill Cornell Medical College, New York, NY 10065, USA. (21) Mayo Clinic, Scottsdale, AZ 85259, USA. (22) Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA. Weill Cornell Medical College, New York, NY 10065, USA. (23) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (24) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. Howard Hughes Medical Institute, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (25) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. eliezerm_vanallen@dfci.harvard.edu toni_choueiri@dfci.harvard.edu. (26) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. eliezerm_vanallen@dfci.harvard.edu toni_choueiri@dfci.harvard.edu. Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA 02142, USA.

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A major chromatin regulator determines resistance of tumor cells to T cell-mediated killing

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Many human cancers are resistant to immunotherapy for reasons that are poorly understood. We used a genome-scale CRISPR/Cas9 screen to identify mechanisms of tumor cell resistance to killing by cytotoxic T cells, the central effectors of anti-tumor immunity. Inactivation of >100 genes sensitized mouse B16F10 melanoma cells to killing by T cells, including Pbrm1, Arid2 and Brd7, which encode components of the PBAF form of the SWI/SNF chromatin remodeling complex. Loss of PBAF function increased tumor cell sensitivity to interferon-gamma, resulting in enhanced secretion of chemokines that recruit effector T cells. Treatment-resistant tumors became responsive to immunotherapy when Pbrm1 was inactivated. In many human cancers, expression of PBRM1 and ARID2 inversely correlated with expression of T cell cytotoxicity genes, and Pbrm1-deficient murine melanomas were more strongly infiltrated by cytotoxic T cells.

Author Info: (1) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (2) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston

Author Info: (1) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (2) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (3) Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (4) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (5) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (6) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (7) Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (8) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (9) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (10) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (11) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (12) Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (13) Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. (14) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (15) Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. kai_wucherpfennig@dfci.harvard.edu xsliu@jimmy.harvard.edu. (16) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. kai_wucherpfennig@dfci.harvard.edu xsliu@jimmy.harvard.edu. Department of Microbiology and Immunobiology, Harvard Medical School, Boston, MA 02115, USA.

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Endolysosomal Cation Channels and Cancer-A Link with Great Potential

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The endolysosomal system (ES) consists of lysosomes; early, late, and recycling endosomes; and autophagosomes. It is a key regulator not only of macromolecule degradation and recycling, plasma membrane repair, homeostasis, and lipid storage, but also of antigen presentation, immune defense, cell motility, cell death signaling, tumor growth, and cancer progression. In addition, it plays a critical role in autophagy, and the autophagy-lysosome pathway is intimately associated with the hallmarks of cancer, such as escaping cell death pathways, evading immune surveillance, and deregulating metabolism. The function of endolysosomes is critically dependent on both soluble and endolysosomal membrane proteins such as ion channels and transporters. Cation channels found in the ES include members of the TRP (transient receptor potential) channel superfamily, namely TRPML channels (mucolipins) as well as two-pore channels (TPCs). In recent studies, these channels have been found to play crucial roles in endolysosomal trafficking, lysosomal exocytosis, and autophagy. Mutation or loss of these channel proteins can impact multiple endolysosomal trafficking pathways. A role for TPCs in cancer cell migration and metastasis, linked to distinct defects in endolysosomal trafficking such as integrin trafficking, has been recently established. In this review, we give an overview on the function of lysosomes in cancer with a particular focus on the roles which TPCs and TRPML channels play in the ES and how this can affect cancer cells.

Author Info: (1) Munich Center for Integrated Protein Science CIPSM, 81377 Munchen, Germany. christian.grimm@cup.uni-muenchen.de. Department of Pharmacy, Center for Drug Research, Ludwig-Maximilians-Universitat Munchen, 81377 Munchen, Germany. christian.grimm@cup.uni-muenchen.de

Author Info: (1) Munich Center for Integrated Protein Science CIPSM, 81377 Munchen, Germany. christian.grimm@cup.uni-muenchen.de. Department of Pharmacy, Center for Drug Research, Ludwig-Maximilians-Universitat Munchen, 81377 Munchen, Germany. christian.grimm@cup.uni-muenchen.de. (2) Department of Pharmacy, Center for Drug Research, Ludwig-Maximilians-Universitat Munchen, 81377 Munchen, Germany. karin.bartel@cup.uni-muenchen.de. (3) Department of Pharmacy, Center for Drug Research, Ludwig-Maximilians-Universitat Munchen, 81377 Munchen, Germany. angelika.vollmar@cup.uni-muenchen.de. (4) Munich Center for Integrated Protein Science CIPSM, 81377 Munchen, Germany. martin.biel@cup.uni-muenchen.de. Department of Pharmacy, Center for Drug Research, Ludwig-Maximilians-Universitat Munchen, 81377 Munchen, Germany. martin.biel@cup.uni-muenchen.de.

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Targeting immune checkpoints potentiates immunoediting and changes the dynamics of tumor evolution

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The cancer immunoediting hypothesis postulates a dual role of the immune system: protecting the host by eliminating tumor cells, and shaping the tumor by editing its genome. Here, we elucidate the impact of evolutionary and immune-related forces on editing the tumor in a mouse model for hypermutated and microsatellite-instable colorectal cancer. Analyses of wild-type and immunodeficient RAG1 knockout mice transplanted with MC38 cells reveal that upregulation of checkpoint molecules and infiltration by Tregs are the major tumor escape mechanisms. Our results show that the effects of immunoediting are weak and that neutral accumulation of mutations dominates. Targeting the PD-1/PD-L1 pathway using immune checkpoint blocker effectively potentiates immunoediting. The immunoediting effects are less pronounced in the CT26 cell line, a non-hypermutated/microsatellite-instable model. Our study demonstrates that neutral evolution is another force that contributes to sculpting the tumor and that checkpoint blockade effectively enforces T-cell-dependent immunoselective pressure.

Author Info: (1) Biocenter, Division of Bioinformatics, Medical University of Innsbruck, Innsbruck, Austria. (2) Biocenter, Division of Bioinformatics, Medical University of Innsbruck, Innsbruck, Austria. (3) Division of

Author Info: (1) Biocenter, Division of Bioinformatics, Medical University of Innsbruck, Innsbruck, Austria. (2) Biocenter, Division of Bioinformatics, Medical University of Innsbruck, Innsbruck, Austria. (3) Division of Translational Cell Genetics, Medical University of Innsbruck, Innsbruck, Austria. (4) Biocenter, Division of Bioinformatics, Medical University of Innsbruck, Innsbruck, Austria. (5) Biocenter, Division of Bioinformatics, Medical University of Innsbruck, Innsbruck, Austria. (6) Biocenter, Division of Bioinformatics, Medical University of Innsbruck, Innsbruck, Austria. (7) Division of Translational Cell Genetics, Medical University of Innsbruck, Innsbruck, Austria. (8) TRON -Translational Oncology at the University Medical Center of the Johannes Gutenberg University gGmbH, Mainz, Germany. (9) Division of Translational Cell Genetics, Medical University of Innsbruck, Innsbruck, Austria. (10) Biocenter, Division of Bioinformatics, Medical University of Innsbruck, Innsbruck, Austria. anne.krogsdam@i-med.ac.at. (11) Biocenter, Division of Bioinformatics, Medical University of Innsbruck, Innsbruck, Austria. zlatko.trajanoski@i-med.ac.at.

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The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients

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Anti-PD-1-based immunotherapy has had a major impact on cancer treatment but has only benefited a subset of patients. Among the variables that could contribute to interpatient heterogeneity is differential composition of the patients' microbiome, which has been shown to affect antitumor immunity and immunotherapy efficacy in preclinical mouse models. We analyzed baseline stool samples from metastatic melanoma patients before immunotherapy treatment, through an integration of 16S ribosomal RNA gene sequencing, metagenomic shotgun sequencing, and quantitative polymerase chain reaction for selected bacteria. A significant association was observed between commensal microbial composition and clinical response. Bacterial species more abundant in responders included Bifidobacterium longum, Collinsella aerofaciens, and Enterococcus faecium. Reconstitution of germ-free mice with fecal material from responding patients could lead to improved tumor control, augmented T cell responses, and greater efficacy of anti-PD-L1 therapy. Our results suggest that the commensal microbiome may have a mechanistic impact on antitumor immunity in human cancer patients.

Author Info: (1) Department of Pathology, University of Chicago, Chicago, IL 60637, USA. (2) Department of Pathology, University of Chicago, Chicago, IL 60637, USA. (3) Center for

Author Info: (1) Department of Pathology, University of Chicago, Chicago, IL 60637, USA. (2) Department of Pathology, University of Chicago, Chicago, IL 60637, USA. (3) Center for Research Informatics, University of Chicago, IL 60637, USA. Department of Pediatrics, University of Chicago, IL 60637, USA. (4) Department of Medicine, University of Chicago, Chicago, IL 60637, USA. (5) Department of Medicine, University of Chicago, Chicago, IL 60637, USA. (6) Department of Medicine, University of Chicago, Chicago, IL 60637, USA. (7) Department of Medicine, University of Chicago, Chicago, IL 60637, USA. (8) Department of Pathology, University of Chicago, Chicago, IL 60637, USA. Department of Medicine, University of Chicago, Chicago, IL 60637, USA.

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Immune response-associated gene profiling in Japanese melanoma patients using multi-omics analysis

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Project High-tech Omics-based Patient Evaluation (HOPE), including comprehensive whole-exome sequencing (WES) and gene expression profiling (GEP) using freshly resected tumor specimens, has been in progress since its implementation in 2014. Among a total of 1,685 cancer patients, 13 melanoma patients were registered in the HOPE Project and were characterized using multi-omics analyses. Among the 13 melanoma patients, 4 were deceased, and 9 were alive. The mean overall survival (OS) and relapsefree survival (RFS) times of the melanoma patients were 16.9 and 14.7 months, respectively. Previously, we developed an immune responseassociated gene list, which consisted of 164 genes in Project HOPE, for evaluating the immunological status. In the present study, the association of immune responseassociated gene expression with immunological parameters, such as programmed death-ligand 1 (PD-L1) and CD8 expression levels, single nucleotide variant (SNV) number, and Vogelstein driver gene mutation number, was investigated. With respect to PD-L1 expression, both immuno-suppression and immuno-stimulation-related genes were upregulated in PD-L1-positive melanomas. In contrast, regarding Vogelstein driver mutations, several T-cell activation-related genes were significantly downregulated in the high driver gene mutation group. In addition, many T-cell activation-related genes were upregulated in the CD8-positive melanomas. The correlation of immune response-associated gene expression with the survival time of the melanoma patients was investigated. Eight specific genes were commonly identified as genes that were significantly correlated for both the overall OS and RFS time, which could be possible prognostic factors for melanoma patients. These results revealed that an immune response-associated gene panel could be an informative tool for evaluating the immunological status prior to clinical immunotherapy in the upcoming era of genomic cancer medicine.

Author Info: (1) Division of Immunotherapy, Shizuoka Cancer Center Research Institute, Shizuoka 411-8777, Japan. (2) Division of Dermatology, Shizuoka Cancer Center Hospital, Shizuoka 411-8777, Japan. (3) Division

Author Info: (1) Division of Immunotherapy, Shizuoka Cancer Center Research Institute, Shizuoka 411-8777, Japan. (2) Division of Dermatology, Shizuoka Cancer Center Hospital, Shizuoka 411-8777, Japan. (3) Division of Dermatology, Shizuoka Cancer Center Hospital, Shizuoka 411-8777, Japan. (4) Division of Dermatology, Shizuoka Cancer Center Hospital, Shizuoka 411-8777, Japan. (5) Division of Immunotherapy, Shizuoka Cancer Center Research Institute, Shizuoka 411-8777, Japan. (6) Division of Immunotherapy, Shizuoka Cancer Center Research Institute, Shizuoka 411-8777, Japan. (7) Division of Immunotherapy, Shizuoka Cancer Center Research Institute, Shizuoka 411-8777, Japan. (8) Division of Immunotherapy, Shizuoka Cancer Center Research Institute, Shizuoka 411-8777, Japan. (9) Division of Immunotherapy, Shizuoka Cancer Center Research Institute, Shizuoka 411-8777, Japan. (10) Division of Medical Genetics, Shizuoka Cancer Center Research Institute, Shizuoka 411-8777, Japan. (11) Division of Cancer Diagnostics Research, Shizuoka Cancer Center Research Institute, Shizuoka 411-8777, Japan. (12) SRL Inc., Tokyo 191-0002, Japan. (13) Division of Regional Resources, Shizuoka Cancer Center Research Institute, Shizuoka 411-8777, Japan. (14) Division of Pathology, Shizuoka Cancer Center Hospital, Shizuoka 411-8777, Japan. (15) Office of the President, Shizuoka Cancer Center Hospital, Shizuoka 411-8777, Japan.

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Multi-functional microwell arrays for single cell level functional analysis of lymphocytes

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Functional analysis of lymphocytes is important for development of vaccines and diagnosis/treatment of various immune-related diseases. In this review, we describe multi-functional microwell arrays that enable functional analysis of lymphocytes in single cell level. We first discuss key parameters for microwell array design. Then, we describe how different types of multi-functional microwell arrays was developed for various applications, including live cell imaging of lymphocyte activation, proliferation, and differentiation, and analyses of effector functions such as cytokine secretion and target cell lysis. Incorporation of novel surface chemistries and functional materials into microwell arrays for enhancing sensing capabilities will widen applications of this technology. Multi-functional microwell arrays will be a powerful tool for the development of novel therapeutics against immune-related diseases, in particular for cancer immunotherapy.

Author Info: (1) (2) (3)

Author Info: (1) (2) (3)

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ImmunoMap: A Bioinformatics Tool for T-Cell Repertoire Analysis

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Despite a dramatic increase in T-cell receptor (TCR) sequencing, few approaches biologically parse the data in a fashion that both helps yield new information about immune responses and may guide immunotherapeutic interventions. To address this issue we developed a method, ImmunoMap, that utilizes a sequence analysis approach inspired by phylogenetics to examine TCR repertoire relatedness. ImmunoMap analysis of the CD8 T-cell response to self-antigen (Kb-TRP2) or to a model foreign-antigen (Kb-SIY) in naive and tumor-bearing B6 mice showed differences in the T-cell repertoire of self- versus foreign antigen-specific responses, potentially reflecting immune pressure by the tumor, and also detected lymphoid organ-specific differences in TCR repertoires When ImmunoMap was used to analyze clinical trial data of tumor-infiltrating lymphocytes (TILs) from patients being treated with anti-PD-1, ImmunoMap, but not standard TCR sequence analyses, revealed a clinically predicative signature in pre- and post-therapy samples.

Author Info: (1) Bloomberg-Kimmel Institute for Cancer Immunotherapy, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine. (2) Graduate Program in Immunology, Johns Hopkins University

Author Info: (1) Bloomberg-Kimmel Institute for Cancer Immunotherapy, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine. (2) Graduate Program in Immunology, Johns Hopkins University School of Medicine. (3) Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center. (4) Department of Biomedical Engineering, Johns Hopkins University School of Medicine. (5) Immunogenomics and Precision Oncology Platform, Memorial Sloan Kettering Cancer Center. (6) Institute for Cell Engineering, Johns Hopkins University School of Medicine jschnec1@jhmi.edu.

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Regulatory T cells constrain the TCR repertoire of antigen-stimulated conventional CD4 T cells

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To analyze the potential role of Tregs in controlling the TCR repertoire breadth to a non-self-antigen, a TCRbeta transgenic mouse model (EF4.1) expressing a limited, yet polyclonal naive T-cell repertoire was used. The response of EF4.1 mice to an I-Ab-associated epitope of the F-MuLV envelope protein is dominated by clones expressing a Valpha2 gene segment, thus allowing a comprehensive analysis of the TCRalpha repertoire in a relatively large cohort of mice. Control and Treg-depleted EF4.1 mice were immunized, and the extent of the Valpha2-bearing, antigen-specific TCR repertoire was characterized by high-throughput sequencing and spectratyping analysis. In addition to increased clonal expansion and acquisition of effector functions, Treg depletion led to the expression of a more diverse TCR repertoire comprising several private clonotypes rarely observed in control mice or in the pre-immune repertoire. Injection of anti-CD86 antibodies in vivo led to a strong reduction in TCR diversity, suggesting that Tregs may influence TCR repertoire diversity by modulating costimulatory molecule availability. Collectively, these studies illustrate an additional mechanism whereby Tregs control the immune response to non-self-antigens.

Author Info: (1) Laboratoire d'Immunobiologie, Universite Libre de Bruxelles (ULB), Gosselies, Belgium. (2) Laboratoire d'Immunobiologie, Universite Libre de Bruxelles (ULB), Gosselies, Belgium. (3) DIAPath, Center for Microscopy

Author Info: (1) Laboratoire d'Immunobiologie, Universite Libre de Bruxelles (ULB), Gosselies, Belgium. (2) Laboratoire d'Immunobiologie, Universite Libre de Bruxelles (ULB), Gosselies, Belgium. (3) DIAPath, Center for Microscopy and Molecular Imaging, Universite Libre de Bruxelles (ULB), Gosselies, Belgium. Laboratories of Image, Signal processing & Acoustics Universite Libre de Bruxelles (ULB), Brussels, Belgium. (4) Laboratoire d'Immunobiologie, Universite Libre de Bruxelles (ULB), Gosselies, Belgium. (5) Laboratoire d'Immunobiologie, Universite Libre de Bruxelles (ULB), Gosselies, Belgium. (6) DIAPath, Center for Microscopy and Molecular Imaging, Universite Libre de Bruxelles (ULB), Gosselies, Belgium. Laboratories of Image, Signal processing & Acoustics Universite Libre de Bruxelles (ULB), Brussels, Belgium. (7) Retroviral Immunology, The Francis Crick Institute, London, UK. Department of Medicine Faculty of Medicine, Imperial College London London, UK. (8) Laboratoire d'Immunobiologie, Universite Libre de Bruxelles (ULB), Gosselies, Belgium. (9) Laboratoire d'Immunobiologie, Universite Libre de Bruxelles (ULB), Gosselies, Belgium oleo@ulb.ac.be.

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Single-cell profiling of human gliomas reveals macrophage ontogeny as a basis for regional differences in macrophage activation in the tumor microenvironment

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BACKGROUND: Tumor-associated macrophages (TAMs) are abundant in gliomas and immunosuppressive TAMs are a barrier to emerging immunotherapies. It is unknown to what extent macrophages derived from peripheral blood adopt the phenotype of brain-resident microglia in pre-treatment gliomas. The relative proportions of blood-derived macrophages and microglia have been poorly quantified in clinical samples due to a paucity of markers that distinguish these cell types in malignant tissue. RESULTS: We perform single-cell RNA-sequencing of human gliomas and identify phenotypic differences in TAMs of distinct lineages. We isolate TAMs from patient biopsies and compare them with macrophages from non-malignant human tissue, glioma atlases, and murine glioma models. We present a novel signature that distinguishes TAMs by ontogeny in human gliomas. Blood-derived TAMs upregulate immunosuppressive cytokines and show an altered metabolism compared to microglial TAMs. They are also enriched in perivascular and necrotic regions. The gene signature of blood-derived TAMs, but not microglial TAMs, correlates with significantly inferior survival in low-grade glioma. Surprisingly, TAMs frequently co-express canonical pro-inflammatory (M1) and alternatively activated (M2) genes in individual cells. CONCLUSIONS: We conclude that blood-derived TAMs significantly infiltrate pre-treatment gliomas, to a degree that varies by glioma subtype and tumor compartment. Blood-derived TAMs do not universally conform to the phenotype of microglia, but preferentially express immunosuppressive cytokines and show an altered metabolism. Our results argue against status quo therapeutic strategies that target TAMs indiscriminately and in favor of strategies that specifically target immunosuppressive blood-derived TAMs.

Author Info: (1) Department of Neurological Surgery, University of California, San Francisco, CA, 94143, USA. Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research

Author Info: (1) Department of Neurological Surgery, University of California, San Francisco, CA, 94143, USA. Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA, 94158, USA. University of California, San Francisco, CA, 94158, USA. (2) Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, 15261, USA. Gary.Kohanbash@pitt.edu. (3) Department of Neurological Surgery, University of California, San Francisco, CA, 94143, USA. Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA, 94158, USA. University of California, San Francisco, CA, 94158, USA. (4) Department of Neurological Surgery, University of California, San Francisco, CA, 94143, USA. Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA, 94158, USA. University of California, San Francisco, CA, 94158, USA. (5) Department of Neurological Surgery, University of California, San Francisco, CA, 94143, USA. University of California, San Francisco, CA, 94158, USA. (6) Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA, 94158, USA. Department of Neurology, University of California, San Francisco, CA, 94158, USA. University of California, San Francisco, CA, 94158, USA. (7) Department of Neurological Surgery, University of California, San Francisco, CA, 94143, USA. University of California, San Francisco, CA, 94158, USA. (8) Department of Neurological Surgery, University of California, San Francisco, CA, 94143, USA. University of California, San Francisco, CA, 94158, USA. (9) Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA, 94158, USA. Department of Neurology, University of California, San Francisco, CA, 94158, USA. University of California, San Francisco, CA, 94158, USA. (10) Department of Neurological Surgery, University of California, San Francisco, CA, 94143, USA. Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA, 94158, USA. University of California, San Francisco, CA, 94158, USA. (11) Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, 15261, USA. (12) Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA, 94158, USA. Department of Neurology, University of California, San Francisco, CA, 94158, USA. University of California, San Francisco, CA, 94158, USA. (13) Department of Neurological Surgery, University of California, San Francisco, CA, 94143, USA. Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA, 94158, USA. University of California, San Francisco, CA, 94158, USA. Veterans Affairs Medical Center, San Francisco, CA, 94121, USA. (14) Department of Neurological Surgery, University of California, San Francisco, CA, 94143, USA. manish.aghi@ucsf.edu. University of California, San Francisco, CA, 94158, USA. manish.aghi@ucsf.edu. (15) Department of Neurological Surgery, University of California, San Francisco, CA, 94143, USA. hideho.okada@ucsf.edu. Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA, 94158, USA. hideho.okada@ucsf.edu. University of California, San Francisco, CA, 94158, USA. hideho.okada@ucsf.edu. (16) Department of Neurological Surgery, University of California, San Francisco, CA, 94143, USA. aaron.diaz@ucsf.edu. Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA, 94158, USA. aaron.diaz@ucsf.edu. University of California, San Francisco, CA, 94158, USA. aaron.diaz@ucsf.edu.

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