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956 Glioma-neuronal circuit remodeling induces regional immunosuppression
  1. Takahide Nejo1,
  2. Saritha Krishna1,
  3. Akane Yamamichi1,
  4. Christian Jimenez1,
  5. Jacob S Young1,
  6. Senthilnath Lakshmanachetty1,
  7. Tiffany Chen1,
  8. Su Phyu1,
  9. Payal Watchmaker1,
  10. Abrar Choudhury1,
  11. David R Raleigh1,
  12. Shawn L Hervey-Jumper1,2 and
  13. Hideho Okada1,3
  1. 1University of California, San Francisco, San Francisco, CA, USA
  2. 2Weill Institute for Neurosciences, San Francisco, CA, USA
  3. 3Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA
  • Journal for ImmunoTherapy of Cancer (JITC) preprint. The copyright holder for this preprint are the authors/funders, who have granted JITC permission to display the preprint. All rights reserved. No reuse allowed without permission.


Background Glioblastomas remodel neuronal circuits.1 Moreover, direct synaptic connections between neurons and glioblastoma cells and glioblastoma- and neuron-derived paracrine growth factors promote glioblastoma growth and invasion.2–4 In converse, glioblastoma cells cause neuronal hyperexcitability and neuronal circuit hypersynchrony through the tumor-derived synaptogenic factor Thrombospondin-1 (TSP-1/Thbs1). Intriguingly, TSP-1 is expressed not only by glioblastoma cells but also by myeloid cells within the tumor. However, the contributions of immune cell components in glioma-neuronal interactions remain unknown. In this study, we test the hypothesis that neuronal activity-dependent glioblastoma proliferation is mediated through the crosstalk between glioblastoma cells, neurons, and immune cells and explore the therapeutic vulnerabilities.

Methods We investigated the differences in transcriptional programs between high- and low-functional connectivity regions (termed HFC and LFC, respectively) through single-cell RNA-sequencing (sc-RNAseq) analysis of patient surgical specimens. We used spatially-resolved RNA-sequencing in a preclinical glioblastoma model SB28. Using bulk RNA-sequencing and flow cytometry, we investigated the significance of TSP-1 through CRISPR-Cas9 knockout in SB28 glioblastoma cells in vitro and in vitro. Furthermore, we evaluated the mechanism of interactions between excitatory neuronal activity and immune regulation using bone-marrow-derived macrophage (BMDM) and cortical neurons in vitro. Finally, we evaluated the effect of neuronal activity-oriented therapy on the tumor-associated macrophages (TAMs) in mice bearing intracerebral SB28 tumors.

Results Through human sc-RNAseq analysis, we discovered a strong association between glioma-neuronal circuit remodeling and regional immunosuppression, in which HFC-derived cells presented remarkable downregulation of several key inflammatory pathways, such as IFNG and TNFa-NFkB (figure 1). Spatial transcriptomics revealed the negative correlations between synaptic activities and inflammatory responses (figure 2). Characterization of TSP-1-WT and KO tumors in vivo demonstrated the significance of TSP-1 in enhancing neuro-synaptic activities but suppressing immune responses, including the differences in TAM polarization patterns and T-cell compositions (figure 3). In vitro assays demonstrated that neuron-secreted factors, but not TSP-1, induced an anti-inflammatory, M2-like phenotype in BMDMs, which was abrogated when the excitatory neuronal activity was pharmacologically suppressed (figure 4). We evaluated perampanel (PER), an FDA-approved non-competitive AMPA-type glutamate receptor inhibitor, to treat the tumor-bearing mice. Flow cytometry revealed that TAMs isolated from PER-treated mice exhibited a more proinflammatory M1-like polarization (p = 0.004), which was accompanied by an improved survival (log-rank p = 0.01) (figure 5).

Conclusions Altogether, our results demonstrate previously unrecognized immunosuppression mechanisms resulting from glioma-neuronal circuit remodeling. Future strategies targeting glioma-neuronal-immune crosstalk may open up new avenues for immunotherapy.


  1. Venkatesh HS, et al. Electrical and synaptic integration of glioma into neural circuits. Nature 2019;573:539–545.

  2. Venkataramani V, et al. Glutamatergic synaptic input to glioma cells drives brain tumour progression. Nature 2019;573:532–538.

  3. Venkataramani V, Tanev DI, Kuner T, Wick W, Winkler F. Synaptic input to brain tumors: clinical implications. Neuro. Oncol. 2021;23:23–33.

  4. Krishna S, et al. Glioblastoma remodelling of human neural circuits decreases survival. Nature 2023:1–9.

Ethics Approval For all human tissue studies, informed consent was obtained, and tissue samples were used in accordance with the University of California, San Francisco (UCSF) institutional review board (IRB) for human research. All patients provided written informed consent. All the experiments and analyses using clinical samples were conducted according to the Declaration of Helsinki. All the mouse studies were performed under a UCSF IACUC-approved protocol.

Abstract 956 Figure 1

scRNA-seq of patient samples. (A-B), Gene set enrichment analyses (GSFA) comparing HFC vs. LFC within tumor cells (A), and myeloid cells (B). The top six upregulated and down-regulated pathways are shown for each comparison. Red and blue indicate upregulanun in HFC and LFC regions, respectively. Normalized enrichment scores (NES) and adjusted p values arc presented in each figure

Abstract 956 Figure 2

Spatial transcriptomics on predinical model. Surface plots show the gene set enrichment signature scores of ‘Post-synaptic Neurotransmitter Receptor Activity’ (GO:MF) and ‘TNFα-Signaling via NFkB’ (Hallmark) within the defined putative glioma-neuronal infiltration area. Scatter plots show the correlations between the scores

Abstract 956 Figure 3

Flow cytometry analysis. a-b, CD45+CD11b+F4/80+ TAMs are charactered as M1-like pro-inflammatory (CD86+CD206-) and M2-like anti-inflammatory (CD86-CD206+) populations (a). Box plot summarizing the Ml-to-M2 ratio (b). (n = 5 mice per group). c-d, CD45+CD3+ brain-infiltrating T-cells are characterized as CD8+ and CD4+ (c) Box plot showing the percentages of CD8+ T-cells (d). (n 4 mice per group). The p value was calculated using the Wilcoxon rank-sum test

Abstract 956 Figure 4

RT-qPCR. a-b, The effects of recombinant TSP-1 (a), and supernatant samples of mouse neuron cultures (b) on the expression levels of Arg1 transcripts in BMDMs were tested. The p values were calculated using Wilcoxon signed rank (pairwise) test

Abstract 956 Figure 5

In-vivo experiment testing the effect of PER. a, The M1-to-M2 ratio of the TAMs isolated from the PER-treated group and the control. b, Kaplan-Meier curves of the tumor-bearing mice treated with PER, or vehicle (n = 10 mice each). The p value was calculated using the Wilcoxon rank-sum test (a) the log-rank test (b)

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