Abstract
The tumour microenvironment plays an essential role in malignancy, and neurons have emerged as a key component of the tumour microenvironment that promotes tumourigenesis across a host of cancers1,2. Recent studies on glioblastoma (GBM) highlight bidirectional signalling between tumours and neurons that propagates a vicious cycle of proliferation, synaptic integration and brain hyperactivity3,4,5,6,7,8; however, the identity of neuronal subtypes and tumour subpopulations driving this phenomenon is incompletely understood. Here we show that callosal projection neurons located in the hemisphere contralateral to primary GBM tumours promote progression and widespread infiltration. Using this platform to examine GBM infiltration, we identified an activity-dependent infiltrating population present at the leading edge of mouse and human tumours that is enriched for axon guidance genes. High-throughput, in vivo screening of these genes identified SEMA4F as a key regulator of tumourigenesis and activity-dependent progression. Furthermore, SEMA4F promotes the activity-dependent infiltrating population and propagates bidirectional signalling with neurons by remodelling tumour-adjacent synapses towards brain network hyperactivity. Collectively our studies demonstrate that subsets of neurons in locations remote to primary GBM promote malignant progression, and also show new mechanisms of glioma progression that are regulated by neuronal activity.
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Data availability
scRNA-seq and bulk RNA-seq data from activity-driven tumours and SEMA4F GOF tumours have been deposited in the NCBI Gene Expression Omnibus under accession no. GSE231800. Source data are provided with this paper. All other data in this article are available from the corresponding author on reasonable request.
Code availability
No custom code was used in this study. The R package limma eBayes function was used to define DEGs. The Bioconductor SVA/Combat package was used for batch correction.
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Acknowledgements
This work was supported by US National Institutes of Health (grant nos. NS124093, NS071153 and CA223388 to B.D.). It was also supported by the National Cancer Institute–Cancer Target Discovery and Development (nos. U01-CA217842 to B.D., F31-CA243382 to E.H.-H., 1F31CA265156 to R.C. and T32-5T32HL092332-19 to B.L.; and by National Institutes of Health (NIH) Director’s Pioneer Award (no. DP1NS111132 to M.M.). We are thankful for support from the David and Eula Wintermann Foundation. scRNA-seq studies were performed at the Single Cell Genomics Core at BCM, partially supported by NIH shared instrument grants (nos. S10OD023469 and S10OD025240) and no. P30EY002520. Human tumour tissue samples were obtained from the Dan L. Duncan Cancer Center Pathology and Histology Core core at BCM (IRB no. H-35355), supported by P30 Cancer Center Support Grant no. NCI-CA125123. We acknowledge the Optogenetics and Viral Vectors Core at the Jan and Dan Duncan Neurological Research Institute. Research reported in this publication was supported by the Eunice Kennedy Shriver National Institute of Child Health & Human Development of NIH under award no. P50HD103555 for use of the Microscopy Core facilities and the Animal Phenotyping & Preclinical Endpoints Core facilities. Images in schematics were created using BioRender.com.
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E.H.-H. and B.D. conceived the project and designed experiments. E.H.-H., Y.-T.C. and Y.Y. performed mouse tumour experiments. E.H.-H. performed the barcoded screen. P.H. generated glioma cell lines. E.H.-H., Y.K. and E.L.-F. performed scRNA-seq experiments. E.H.-H. and E.L.-F. performed synaptic staining. H.-C.C., E.M., Z.-F.L., S.M., M.R.W. and D.C. assisted in sectioning and analysis of tumour samples. J.W. and M. McDonald executed electrophysiology studies. R.C., M. Monje, A.J., J.L.N. and G.R. provided essential reagents. E.H.-H., B.L., A.S.H. and J.B. designed and executed bioinformatics analyses. K.R.T. and M.M. designed and performed in vitro glioma migration experiments. E.H.-H. and B.D. wrote the manuscript, with input from M. Monje, Y.-T.C. and A.S.H.
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Extended data figures and tables
Extended Data Fig. 1 Contralateral activity drives glioma progression and infiltration.
a. Kaplan-Meier survival analysis of RCAS-Ntva tumors treated with saline (medianSaline = 95 days, n = 11) or CNO (medianCNO = 51 days, n = 9) showing significantly faster morbidity in CNO treated RCAS tumors (Log-rank (Mantel-Cox) test, Chisq = 6.456, df = 1, p-value = 0.0111, CNO/Saline HRlog-rank = 2.768, 95% CI = 0.9770 to 7.945). b. H&E staining of RCAS-Ntva tumors samples revealed high grade characteristics in CNO treated tumor groups (red arrows). Ki67 staining proliferation in CNO treated mice versus saline treated mice. Quantification is derived from n = 5 mice from CNO (mean = 14.51%, SD = 7.076%) and Saline (mean = 4.017%, SD = 2.179%) groups and determined by Welch’s unpaired t-test (P-value = 0.0276, t = 3.228, df = 4.441). c. Mathematical modeling of glioma infiltration as a function of tumor mass. Blue line is the smoothed data points using piecewise-cubic splines; red horizontal dashed lines are the 0.8 pmax and 0.02 pmax glioma cell density of the maximum smoothed cellular density (pmax). Red vertical lines are the intersecting distance points of the red horizontal lines with smoothed blue line, which is used in calculating infiltrating width (IW). Black arrow shows the IW. Log-log plot shows the dependence of IW and tumor mass (TM). Analysis was performed at the p30 timepoint on CTL n = 3, Saline n = 3, CNO n = 3; samples from individual biological replicates are color coded. d. Glioma 3D spheroid migration assay, measuring glioma infiltration after treatment with growth factor media, conditioned media (CM) from spontaneously active cortical explants, spontaneously active cortical explants silenced with TTX (10 μm) or optogenetically stimulated cortical explants (channelrhodopsin-2 (ChR2)-expressing deep layer cortical projection neurons), in comparison to ACSF control. Data are plotted as median (center line), IQR (box limits) and minimum and maximum values (whiskers) (b).
Extended Data Fig. 2 Contralateral cortical stimulation accelerates tumor progression.
a. Schematic depicting injection of AAV into the contralateral cortex. b. Electrophysiology measuring neural activity in response to CNO treatment on mouse brain sections to confirm DREADD activity. c. Schematic of intra-uterine electroporation (IUE) model of high-grade glioma (HGG). Representative images of tumor brains from 20 day old mice versus 60 days old. Tumor brain slices were stained with Hoechst, and native GFP fluorescence was utilized to visualize tumor. Time course of contralateral cortical infiltration. Log-regression of 3xCr tumors demonstrated that infiltration correlates strongly with time (two-sided log-regression, Chi-square = 23.38, df = 1, p-value < 0.0001, n30 = 22, n50 = 19, n70 = 21, n90 = 10). 72 IUE-HGG bearing mice were generated from 10 separate litters of mice and sampled across P30, P50, P70, P90 to ensure accurate representation of infiltration. d. Representative images of infiltrating tumor across the midline at each respective timepoint. e. Representative Ki67 staining of CNO-treated versus Saline-treated versus untreated IUE-HGG sections taken from P30 tumor brains. f. Representative Ki67 staining of CNO-only control, without hM3Dq, Saline, and IUE-HGG sections taken from P30 tumor brains, g–h. Representative images of infiltrating tumor across the midline at each respective timepoint from the CNO-only control experiments (g) and saline only control (h). Tumor sections were imaged and quantified for each condition from at least five mice to ensure reproducibility (d–h).
Extended Data Fig. 3 Ipsilateral stimulation does not promote early tumor progression.
a. Representative Ki67 staining of CNO versus Saline versus untreated IUE-HGG sections taken from P30 tumor brains after ipsilateral stimulation. b. Representative images of corpus callosum cut tumors stained for Ki67 (quantification in main figure). Tumor samples were prepared as described above, using native GFP to image tumor. c. Representative images of Rasgrf2-dCre tumors stained for Ki67 (quantification in main figure). Tumor samples were prepared as described above, using native GFP to image tumor). Tumor sections were imaged and quantified for each condition from at least five mice to ensure reproducibility (a–c). Graphics in a created with BioRender.com.
Extended Data Fig. 4 Activation of contralateral inhibitory neurons does not promote tumor progression.
a. Representative image of Rosa-LSL-TdTom + Rasgrf2-dCre mouse brain harvested 2 days post Trimethoprim treatment. Cells from layer 2/3 of the cortex show TdTom labelling. b. Representative images from IUE-HGG tumors at P30 demonstrating infiltration and Ki67 expression after activation of inhibitory neurons with AAV-Dlx5/6-hM3Dq in the cortex contralateral. c. Quantification of tumor infiltration and Ki67 expression at P30. Infiltration analyzed one-way ANOVA. Data derived from 3xCr CTL (n = 7), 3xCr + DLX-hM3Dq-mCh + Saline (n = 6), 3xCr + DLX-hM3Dq-mCh + CNO (n = 7) tumors with 18 coronal slices analyzed per tumor. Coronal sections with infiltrating tumor showed no difference in proliferation compared to saline treated (p-value = 0.1823) or control tumors (p-value = 0.5328) or infiltration at P30 compared to Saline (p-value = 0.8880) or control tumors (p-value = 0.9981). d. Stacked bar chart of SingleR labeled populations percent representation in CNO and Saline single cell sequencing datasets. e. Feature plot of cluster of interest marker genes. Color represents a score assigned based on overall expression of marker genes. Seurat’s AddModuleScore function was used to calculate these scores. Red Arrow denotes population of interest featured in Fig. 3b. f. GO terms of genes enriched in the spatial transcriptomics analysis of the leading edge of P50 mouse tumors (R6-R8), (Cutoff for DEG via DESeq2, with p-value < 0.05). Data are plotted as median (center line), IQR (box limits) and minimum and maximum values (whiskers) (c).
Extended Data Fig. 5 Expression characteristics of EphA6, EphA7, and Sema4F.
a. Heatmap of IVY-GAP expression data of all axon guidance genes included in the bar coded screen described in main Fig. 4a. b. Heatmap of IVY-GAP expression data for Sema4f, EphA6, EphA7. c. KM curve of GEPIA survival data. GBM patient cohort data were split based on high and low Sema4F expression. d. Western blots of wild type, GOF, and LOF tumors. (pBSema4F is GOF; sgSema4F is LOF). Antibodies and concentrations used are described in methods. Western blots were quantified in ImageJ. Western blots were performed on biological replicates (2 additional tumor sample) to ensure reproducibility.
Extended Data Fig. 6 Analysis of EphA6, EphA7, and Sema4F GOF/LOF tumors.
a. Kaplan-Meier survival curve of individual gain-of-function and loss-of-function validation studies for EphA6 and EphA7. EphA6-GOF (medianA6GOF = 105 days, Chisq = 0.7, df = 1, p-value = 0.4, n = 11), EphA6-LOF (medianA6LOF = 133days, Chis = 7.2, df = 1, p-value = 0.007, n = 7), EphA7-GOF (medianA7GOF = 97 days, Chisq = 0, df = 1 p-value = 0.9, n = 15), EphA7-LOF (medianA7LOF = 97.5 days, Chisq = 1.3, df = 1, p-value = 0.3). b. Representative immunostainings of EphA6, EphA7, and Sema4F human tumor micro-array. c. Quantification of infiltration from these tumors across the P30-P70 timecourse. Infiltration was quantified based on the presence of tumor cells in contralateral cortex and analyzed via two-way analysis of variance (ANOVA). Error bars represent standard deviation, data derived from EphA6-GOF p30 n = 7, EphA6-GOF p50 n = 13, EphA6-GOF p70 n = 11, EphA6 CTL p30 n = 8, EphA6 CTL p50 n = 6, EphA6 CTL p70 n = 11, EphA6-LOF p30 n = 8, EphA6-LOF p50 n = 6, EphA6-LOF p70 n = 11, EphA7-GOF p30 n = 9, EphA7-GOF p50 n = 12, EphA7-GOF p70 n = 12, EphA7 CTL p30 n = 5, EphA7 CTL p50 n = 5, EphA7 CTL p70 n = 7, EphA7-LOF p30 n = 6, EphA7-LOF p50 n = 6, EphA7-LOF p70 n = 9. d. Quantification of transwell migration of human glioma cell lines; infiltrating cells were counted after 48 h incubation (n = 3 wells per condition). e. Kaplan-Meier survival curve for human glioma cell lines transplanted into mouse brain. Samples were analyzed via log-rank (Mantel-Cox) test. WT median survival = 66 days, n = 11; GFP median = 62 days n = 7; Sema4f-GOF median = 74 days, n = 10, Chi = 0.4120, p-value = 0.5209; shSCR median = 69 days, n = 9; shSema4F median = undefined after 100 days, n = 8, Chi = 14.08 p-value = 0.0002. *P < 0.05, **P < 0.01, ***P < 0.001, **** P < 0.0001, two-way analysis of variance (ANOVA) (c), one-way analysis of variance (ANOVA) (f), Log-rank (Mantel-Cox) test (a,d). Data are plotted as median (center line), IQR (box limits) and minimum and maximum values (whiskers) (c–d).
Extended Data Fig. 7 Infiltrating glioma from EphA6 and EphA7 GOF/LOF tumors.
a. Representative images of IUE-HGG GOF/LOF/CTL of EphA6 in P50 mice. Frozen sections were stained with Hoechst and native GFP was assessed for infiltration status into the contralateral cortex. b. Representative images of IUE-HGG GOF/LOF/CTL of Epha7 in P50 mice. Samples assessed as outlined above (EphA6-GOF p50 n = 13, EphA6 CTL p50 n = 6, EphA6-LOF p50 n = 6, EphA7-GOF p50 n = 12, EphA7 CTL p50 n = 5, EphA7-LOF p50 n = 6) (a,b). c. Representative H&E staining of IUE-HGG tumors containing GOF and LOF of EphA6, EphA7, and Sema 4F. All tumors demonstrated high-grade characteristics such as microvascular proliferation or necrosis regardless of GOF or LOF. H&E staining repeated on n = 4 tumor samples per condition d. qRT-PCR validation of Sema4F-GOF (S4F-GOF) overexpression and shRNAi knockdown in human glioma cell lines. Data are derived from n = 3 biological replicates per condition. Results are plotted as mean +/- SD. Values were analyzed by Brown-Forsythe and Welch two-way ANOVA. S4F-GOF showed significant upregulation compared to uninfected control (**P = 0.0082). shS4F #4 showed significant downregulation compared to shScramble cells (*P = 0.0167).
Extended Data Fig. 8 Representative Ki67 images from Sema4F manipulated tumors.
a. Representative images of Sema4F GOF/LOF and control tumors stained for Ki67 in P30 mice. Tumor samples were using native GFP to image tumor. b. Representative images of Sema4F-LOF and control tumors treated with CNO or Saline and stained for Ki67 in P30 mice. c. Representative images from IUE-HGG tumors at P30 demonstrating the extent of infiltration with Sema4F-ectodomain and Sema4F-ectodomain + Sema4F-LOF. d. Quantification of tumor infiltration and Ki67 expression at P30. Infiltration analyzed one-way ANOVA. Data derived from n = 6 CTL, n = 7 S4F-Ecto, and n = 5 S4F Ecto+LOF tumors, *P = 0.0483, **Pinfil = 0.0025, **PKi67 = 0.0023 ****P = <0.0001. e. Representative images of Sema4F-ectodomain and Sema4F-ectodomain + Sema4F-LOF and control tumors stained for Ki67 in 30 day old mice. f. Representative images of infiltrating tumor across the midline from Sema4Fectodomain and Sema4F-ectodomain + Sema4F-LOF tumors in 30 day old mice. Data are plotted as median (center line), IQR (box limits) and minimum and maximum values (whiskers) (d).
Extended Data Fig. 9 Single Cell RNA-Seq analysis.
a. Single Cell RNA-Seq DimPlots of P50 IUE-HGG from CNO, Sema4F, and saline controls UMAP plot of full single cell datasets from CNO and Saline treated and Sema4F GOF tumors. Tumors were isolated and sequenced as outlined above. All clusters were represented in all datasets, though their relative abundance varied. b. Single cell RNASeq analysis of from IUE-glioma model, sub-clustering on non-tumor, GFP-negative cells. Red circle denotes neuronal populations, marked by Map2, Tubb3, and Ncam. Note that Plexin B1 and B2 expression is enriched in neuronal populations, denoted by purple dots. c. Volcano plot depicting the differentially expressed genes (DEGs) between human glioma cell lines overexpressing Sema4F (Sema4F-GOF) and controls. For downregulated genes with blue color: padj < 0.001 & log2FoldChange < (−0.75); for upregulated genes in red: padj < 0.001 & log2FoldChange > 0.75) d. GO analysis of DEGs upregulated in the Sema4F-GOF glioma cell lines. DEGs from padj < 0.001 & log2FoldChange > 0.75).
Extended Data Fig. 10 Staining for synaptic markers in mice bearing PDXSema4F-GOF tumors.
a. Antibody staining of inhibitory synapses (VGAT-Gephryin) and b. excitatory (Vglut2PSD95) synapse from P50 mouse brains at peritumoral margins from PDX tumors ovexpressing Sema4F and control. Box denotes zoomed in region in adjacent panel (20X, 63X, and 200X magnification left to right; scale bar left to right: 50 um, 20 um and 10 um). Quantification of synaptic staining via unpaired two-tailed t-test is derived from PDX-Con n = 3 and PDX-S4F-GOF n = 3, utilizing a total of 13 fields of view from these sections for each experimental condition, (***P = 0.0001, ****P < 0.0001), data are presented as mean values +/− SE.
Supplementary information
Supplementary Fig. 1
Uncropped immunoblots associated with Extended Data Fig. 5d.
Supplementary Table 1
GO-term analysis of upregulated genes in CNO-treated mouse dataset versus saline-treated mouse dataset. Positive markers were found for CNO-treated samples, and these were analysed via Enrichr using the KEGG 2021 Human gene set.
Supplementary Table 2
Metadata for the final Seurat object containing CNO, saline and SEMA4F GOF scRNA-seq.
Supplementary Table 3
GO-term analysis of upregulated genes in subcluster of interest (Fig. 3) in CNO-treated mouse dataset versus saline-treated mouse dataset. Positive markers were found for CNO-treated samples, and these were analysed via Enrichr using the KEGG 2021 Human gene set.
Supplementary Table 4
GO-term analysis of upregulated genes found in the leading edge (R6–R8) of the spatial transcriptomics analysis from Fig. 3. GO terms derived from Enrichr using the KEGG 2021 Human gene set.
Supplementary Table 5
GO-term analysis of upregulated genes in sub-subcluster of interest (Fig. 5) in CNO-treated and SEMA4F GOF mouse dataset versus saline-treated mouse dataset. Positive markers were found for the cluster of interest, and these markers were analysed via Enrichr using the KEGG 2021 Human gene set.
Supplementary Table 6
List of GO terms from human cell lines overexpressing SEMA4F compared with controls. Analysis was performed with Enrichr using the KEGG 2021 Human gene set.
Supplementary Table 7
List of DEGs from human cell lines overexpressing SEMA4F compared with controls. Analysis was performed with Enrichr using the KEGG 2021 Human gene set.
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Huang-Hobbs, E., Cheng, YT., Ko, Y. et al. Remote neuronal activity drives glioma progression through SEMA4F. Nature 619, 844–850 (2023). https://doi.org/10.1038/s41586-023-06267-2
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DOI: https://doi.org/10.1038/s41586-023-06267-2
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