Elucidating the diversity of malignant mesenchymal states in glioblastoma by integrative analysis

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Abstract

Background: Multiple glioblastoma studies have described a mesenchymal (MES) state, with each study defining the MES program by distinct sets of genes and highlighting distinct functional associations, including both immune activation and suppression. These variable descriptions complicate our understanding of the MES state and its implications. Here, we hypothesize that there is a range of glioma MES states, possibly reflecting distinct prior states in which a MES program can be induced, and/or distinct mechanisms that induce the MES states in those cells. Methods: We integrated multiple published single-cell and bulk RNA sequencing datasets and MES signatures to define a core MES program that recurs across studies, as well as multiple function-specific MES signatures that vary across MES cells. We then examined the co-occurrence of these signatures and their associations with genetic and microenvironmental features. Results: Based on co-occurrence of MES signatures, we found three main variants of MES states: hypoxia-related (MES-Hyp), astrocyte-related (MES-Ast), and an intermediate state. Notably, the MES states are differentially associated with genetic and microenvironmental features. MES-Hyp is preferentially associated with NF1 deletion, overall macrophage abundance, a high macrophage/microglia ratio, and M2-related macrophages, consistent with previous studies that associated MES with immune suppression. In contrast, MES-Ast is associated with T cell abundance and cytotoxicity, consistent with immune activation through expression of MHC-I/II. Conclusions: Diverse MES states occur in glioblastoma. These states share a subset of core genes but differ primarily in their association with hypoxia vs. astrocytic expression programs, and with immune suppression vs. activation, respectively.

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Chanoch-Myers, R., Wider, A., Suva, M. L., & Tirosh, I. (2022). Elucidating the diversity of malignant mesenchymal states in glioblastoma by integrative analysis. Genome Medicine, 14(1). https://doi.org/10.1186/s13073-022-01109-8

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