370 Single-Cell Analysis of Human Glioma and Immune Cells Identifies S100A4 as an Immunotherapy Target. (April 2023)

• Record Type: Journal Article
• Authors: Huntoon, Kristin; Abdelfattah, Nourhan; Wang, Caiyi; Kumar, Parveen; Jiang, Wen; Kim, Betty Y. S.; George, Joshy; Yun, Kyuson
• Is Part Of: Neurosurgery. Volume 69(2023)Supplement 1
• Page Start: 63
• Page End: 63
• Publication Date: 2023-04
• Subjects: Nervous system -- Surgery -- Periodicals; 617.48005
• DOI: 10.1227/neu.0000000000002375_370
• Languages: English
• ISSNs: 0148-396X

Abstract

Abstract : INTRODUCTION: Tumor-associated myeloid cells are critical regulators of tumor progression, metastasis, and immune evasion and are promising therapeutic targets. However, elucidating their functional and molecular heterogeneity in human cancers has been challenging given a lack of lineage-specific markers and their highly plastic nature, which precludes faithful modeling and analysis in vitro. Therefore a major rate-limiting step in developing more effective immunotherapies for glioblastoma (GBM) is our inadequate understanding of the cellular complexity and the molecular heterogeneity of immune infiltrates in gliomas. METHODS: Via RNAseq we integrated analysis of 201, 986 human glioma, immune, and other stromal cells at the single cell level generating multi-regional and -dimensional analyses of human gliomas and in doing so map GBM cellular heterotypia and spatial, molecular, and functional heterogeneity of glioma and associated stromal cells, including immune cells. RESULTS: We discovered extensive spatial and molecular heterogeneity in immune infiltrates. We identify molecular signatures for nine distinct myeloid cell subtypes, of which five are independent prognostic indicators of glioma patient survival. Furthermore, we identify S100A4 as a regulator of immune suppressive T and myeloid cells in GBM and demonstrate that deleting S100A4 in non-cancer cells is sufficient to reprogram the immune landscape and significantly improve survival. CONCLUSIONS: This study provides insights into spatial, molecular, and functional heterogeneity of glioma and glioma-associated immune cells and demonstrates the utility of this dataset for discovering therapeutic targets for this poorly immunogenic cancer.