Lineage and Spatial Mapping of Glioblastoma-associated Immunity

The diversity of molecular states and cellular plasticity of immune cells in the glioblastoma environment is still poorly understood. Here, we performed scRNA sequencing of the immune compartment and mapped potential cellular interactions leading to an immunosuppressive microenvironment and dysfunction of T cells. Through inferring the dynamic adaptation during T cell activation, we identified three different terminal states with unique transcriptional programs. Modeling of driver genes for terminal T cell fate identified IL-10 signaling alterations in a subpopulation of HAVCR2(+) T cells. To explore in depth cellular interactions, we established an in-silico model by the integration of spatial transcriptomic and scRNA-sequencing, and identified a subset of HMOX1+ myeloid cells defined by IL10 release leading to T cell exhaustion. We found a spatial overlap between HMOX(+) myeloid and HAVCR2(+) T cells, suggesting that myeloid-lymphoid interaction causes immunosuppression present in tumor regions with enriched mesenchymal gene expression. Using human neocortical GBM model, coupled with patient-derived T cells, we confirmed that the functional interaction between myeloid and lymphoid cells, leads to a dysfunctional state of T cells. This IL-10 driven T cell exhaustion was found to be rescued by JAK/STAT inhibition. A comprehensive understanding of the cellular states and plasticity of lymphoid cells in GBM will aid towards successful immunotherapeutic approaches.

[1]  U. Hofmann,et al.  Inferring spatially transient gene expression pattern from spatial transcriptomic studies , 2020, bioRxiv.

[2]  Fabian J. Theis,et al.  CellRank for directed single-cell fate mapping , 2020, Nature Methods.

[3]  Holger Heyn,et al.  Seeded NMF regression to Deconvolute Spatial Transcriptomics Spots with Single-Cell Transcriptomes , 2020 .

[4]  Johannes U. Mayer,et al.  Dissecting cellular crosstalk by sequencing physically interacting cells , 2020, Nature Biotechnology.

[5]  B. Bengsch,et al.  Use of Mass Cytometry to Profile Human T Cell Exhaustion , 2020, Frontiers in Immunology.

[6]  Y. Saeys,et al.  NicheNet: modeling intercellular communication by linking ligands to target genes , 2019, Nature Methods.

[7]  Fabian J Theis,et al.  Generalizing RNA velocity to transient cell states through dynamical modeling , 2019, Nature Biotechnology.

[8]  Sagar,et al.  Mapping microglia states in the human brain through the integration of high-dimensional techniques , 2019, Nature Neuroscience.

[9]  W. Niesen,et al.  Neuroprotection after Hemorrhagic Stroke Depends on Cerebral Heme Oxygenase-1 , 2019, Antioxidants.

[10]  E. Wherry,et al.  Defining ‘T cell exhaustion’ , 2019, Nature Reviews Immunology.

[11]  J. Beck,et al.  Astrogliosis Releases Pro-Oncogenic Chitinase 3-Like 1 Causing MAPK Signaling in Glioblastoma , 2019, Cancers.

[12]  Mariella G. Filbin,et al.  An Integrative Model of Cellular States, Plasticity, and Genetics for Glioblastoma , 2019, Cell.

[13]  Wei Guo,et al.  SCINA: A Semi-Supervised Subtyping Algorithm of Single Cells and Bulk Samples , 2019, Genes.

[14]  U. Hofmann,et al.  Human organotypic brain slice culture: a novel framework for environmental research in neuro-oncology , 2019, Life Science Alliance.

[15]  U. Hofmann,et al.  Tumor-associated reactive astrocytes aid the evolution of immunosuppressive environment in glioblastoma , 2019, Nature Communications.

[16]  Shuigeng Zhou,et al.  Single-cell trajectories reconstruction, exploration and mapping of omics data with STREAM , 2019, Nature Communications.

[17]  I. Amit,et al.  Dysfunctional CD8 T Cells Form a Proliferative, Dynamically Regulated Compartment within Human Melanoma , 2019, Cell.

[18]  Fabian J Theis,et al.  Single-cell RNA-seq denoising using a deep count autoencoder , 2019, Nature Communications.

[19]  A. Butte,et al.  Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage , 2018, Nature Immunology.

[20]  Xueda Hu,et al.  Lineage tracking reveals dynamic relationships of T cells in colorectal cancer , 2018, Nature.

[21]  A. Kalergis,et al.  Heme Oxygenase-1 as a Modulator of Intestinal Inflammation Development and Progression , 2018, Front. Immunol..

[22]  Erik Sundström,et al.  RNA velocity of single cells , 2018, Nature.

[23]  R. Soffietti,et al.  STAT3 labels a subpopulation of reactive astrocytes required for brain metastasis , 2018, Nature Medicine.

[24]  R. Bronson,et al.  A Milieu Molecule for TGF-β Required for Microglia Function in the Nervous System , 2018, Cell.

[25]  Zhihong Chen,et al.  Immune Microenvironment in Glioblastoma Subtypes , 2018, Front. Immunol..

[26]  P. Fecci,et al.  T-cell Dysfunction in Glioblastoma: Applying a New Framework , 2018, Clinical Cancer Research.

[27]  D. Bigner,et al.  T-Cell Exhaustion Signatures Vary with Tumor Type and Are Severe in Glioblastoma , 2018, Clinical Cancer Research.

[28]  Le Cong,et al.  A Distinct Gene Module for Dysfunction Uncoupled from Activation in Tumor-Infiltrating T Cells , 2017, Cell.

[29]  Steven D Chang,et al.  Single-Cell RNAseq analysis of infiltrating neoplastic cells at the migrating front of human glioblastoma , 2017, bioRxiv.

[30]  M. Dey,et al.  Recurrent glioma clinical trial, CheckMate-143: the game is not over yet , 2017, Oncotarget.

[31]  Act Investigators Rindopepimut with temozolomide for patients with newly diagnosed, EGFRvIII-expressing glioblastoma (ACT IV): a randomised, double-blind, international phase 3 trial , 2017 .

[32]  Boxi Kang,et al.  Landscape of Infiltrating T Cells in Liver Cancer Revealed by Single-Cell Sequencing , 2017, Cell.

[33]  Mariella G. Filbin,et al.  Decoupling genetics, lineages, and microenvironment in IDH-mutant gliomas by single-cell RNA-seq , 2017, Science.

[34]  Mariella G. Filbin,et al.  Single-cell RNA-seq supports a developmental hierarchy in human oligodendroglioma , 2016, Nature.

[35]  Rebecka Jörnsten,et al.  Integrative Modeling Reveals Annexin A2-mediated Epigenetic Control of Mesenchymal Glioblastoma , 2016, EBioMedicine.

[36]  Aviv Regev,et al.  A Distinct Gene Module for Dysfunction Uncoupled from Activation in Tumor-Infiltrating T Cells , 2016, Cell.

[37]  Matheus C. Bürger,et al.  Defining CD8+ T cells that provide the proliferative burst after PD-1 therapy , 2016, Nature.

[38]  Ana C Anderson,et al.  Lag-3, Tim-3, and TIGIT: Co-inhibitory Receptors with Specialized Functions in Immune Regulation. , 2016, Immunity.

[39]  Charles H. Yoon,et al.  Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq , 2016, Science.

[40]  B. Zhu,et al.  T-cell exhaustion in the tumor microenvironment , 2015, Cell Death and Disease.

[41]  Y. Naito,et al.  Heme oxygenase-1 and anti-inflammatory M2 macrophages. , 2014, Archives of biochemistry and biophysics.

[42]  Shawn M. Gillespie,et al.  Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma , 2014, Science.

[43]  W. Wick,et al.  Microenvironmental Clues for Glioma Immunotherapy , 2014, Current Neurology and Neuroscience Reports.

[44]  Pedro Romero,et al.  Exhaustion of tumor-specific CD8⁺ T cells in metastases from melanoma patients. , 2011, The Journal of clinical investigation.

[45]  E. Wherry T cell exhaustion , 2011, Nature Immunology.