Glioblastomas acquire myeloid-affiliated transcriptional programs via epigenetic immunoediting to elicit immune evasion

Abstract

Glioblastoma multiforme (GBM) is an aggressive brain tumor for which current immunotherapy approaches have been unsuccessful. Here, we explore the mechanisms underlying immune evasion in GBM. By serially transplanting GBM stem cells (GSCs) into immunocompetent hosts, we uncover an acquired capability of GSCs to escape immune clearance by establishing an enhanced immunosuppressive tumor microenvironment. Mechanistically, this is not elicited via genetic selection of tumor subclones, but through an epigenetic immunoediting process wherein stable transcriptional and epigenetic changes in GSCs are enforced following immune attack. These changes launch a myeloid-affiliated transcriptional program, which leads to increased recruitment of tumor-associated macrophages. Furthermore, we identify similar epigenetic and transcriptional signatures in human mesenchymal subtype GSCs. We conclude that epigenetic immunoediting may drive an acquired immune evasion program in the most aggressive mesenchymal GBM subtype by reshaping the tumor immune microenvironment.

Keywords: DNA methylation; chemokine; epigenetics; glioblastoma; immune evasion; immunoediting; interferon signaling; macrophage; neural stem cell; syngeneic.

Graphical abstract

Figure 1

Engineered GSCs acquire immune evasion capabilities upon serial transplantation through immunocompetent hosts (A) NSC isolation from BL6 mice and engineering of GBM driver mutations. (B) Immunoblots showing NF1 and PTEN expression in NP cells versus wild-type BL6 NSCs. (C) Immunoblot confirming overexpression of EGFRvIII in NPE cells. (D) Representative stereomicroscope images of GFP⁺ NPE tumors in NSG mice (whole brain live imaging; top, GFP; bottom, GFP/bright field [BF] overlay, n = 15). (E) H&E staining of NPE tumors in NSG (upper panel), scale bar, 50 μm; immunofluorescence of common NSC (GFAP/Nestin) and proliferation (Ki67) markers in NPE tumors (lower panel), scale bar, 20 μm. (F) Reverse-phase protein array (RPPA) analysis of common cancer driver pathways in wild-type BL6 NSCs versus mutant cell lines. (G) Representative bioluminescent imaging of NPE tumor progression in vivo in BL6 recipients. Number of days post-surgery noted above images. (H) Representative stereomicroscope images of GFP⁺ NPE tumors in BL6 hosts (whole brain live imaging; top, GFP; bottom, GFP/bright field [BF] overlay). (I) Experimental design for tumor cell derivation and serial transplantation of NPE cells in NSG and BL6 mice. (J) Survival curves following orthotopic transplantation of: wild-type NSCs into BL6 mice (n = 4, turquoise curve); NPE (n = 15, orange curve), or NPE-IE (n = 12, green curve) into NSG mice; NPE (n = 19, yellow curve), NPE-BL6-TD (n = 27, light purple curve), or NPE-IE (n = 33, dark purple curve) into BL6 mice. See also Figure S1.

Figure S1

Engineering GBM driver mutations in adult mouse neural stem cells to create GBM initiating cell lines, related to Figure 1 and Table S1 (A) Immunoblots of EGFRvIII (left panel) and PDGFRa (right panel) overexpression in NSCs following transfection with the PB-Transposon plasmids. (B) PCR genotyping of clonal Pten Knock-Out (KO) lines to confirm successful gene targeting. (C) Immunoblot of Pten KO NSC lines confirms loss of PTEN protein expression. (D) PCR genotyping of clonal Nf1 KO lines to confirm successful gene targeting. (E) Immunoblot of Nf1 KO NSC lines confirms loss of NF1 protein expression. (F) PCR genotyping of clonal Trp53 KO lines to confirm successful gene targeting. (G) ICC analysis of Trp53 KO clones confirms loss of TRP53 expression, scale bar = 20μm. (H) CRISPR KO of Pten, Nf1 and Trp53 in NSCs does not affect the expression of the common NSC markers Nestin or SOX2, or the ability of NSCs to respond to differentiation cues (growth factor withdrawal and/or BMP addition), scale bar = 20μm. (I) Orthotopic transplantation of NP cells into NOD-scid-gamma (NSG) mice provides a premalignant model (whole brain live imaging shown; top, GFP; bottom, overlay of GFP and brightfield (BF), representative images of n = 5 mice). (J) Immunoblots of the GBM driver mutations (NF1, PTEN and EGFRvIII) in engineered NPE-Mx (multiplex) NSCs. (K) Top: Orthotopic transplantation of NPE-Mx cells leads to tumour formation in NSG mice (whole brain live imaging shown; top, GFP; bottom, overlay of GFP and brightfield (BF)). Bottom: Survival curve of NSG mice orthotopically transplanted with NPE-Mx cells (n = 3 mice). (L) Immunoblots of NF1, PTEN, and EGFR expression in NPE-Mx-TD (tumour-derived) polyclonal and clonal lines versus parental NSCs. (M) Immunoblot of PDGFRa and PTEN in PPP NSCs. (N) ICC confirming reduction of TRP53 expression in PPP cells versus parental NSCs (left panel) and quantification of Trp53-expressing cells by ICC (right panel; student’s t-test ^∗∗∗ p≤0.001, error bars represent SEM), scale bar = 20μm. (O) ICC of PPP mutant NSC lines for NSC markers (Sox2, Nestin) in self-renewing, EGF/FGF containing media and differentiation markers (GFAP, Tuj1) in differentiation conditions (BMP or -EGF/-FGF), scale bar = 20μm. (P) Bioluminescent IVIS imaging of PPP tumour progression in vivo in NSG and BL6 recipients. Number of days post-surgery is noted above each image. (Q) Survival curve of NSG (n = 4) and BL6 (n = 15) mice transplanted with PPP cells (R) Flow cytometric analysis of the NPE-BL6-TD cells confirms that no CD45+ cells are detectable in vitro as compared to unstained NPE-BL6-TD and bone marrow-derived cells. (S) Quantification of tumour incidence in NSG and BL6 mice transplanted with NPE, NPE-BL6-TD and NPE-IE cell lines. Numbers above bars denote actual tumour occurrence in all transplants. (T) Confluence analysis of NPE and NPE-IE cells indicates no significant difference in proliferation rates (p = 0.2888). (U) Karyotyping of parental subsequently engineered NSCs (>10 cell spreads counted per cell line, bars represent the mean value, error bars represent SEM, dots represent individual counts).

Figure S2

Immune profiling of NPE and NPE-IE tumors reveals recapitulation of human disease and dynamic immune populations, related to Figure 2 (A) Survival analysis of BL6 mice orthotopically injected with NPE (left), NPE-BL6-TD (center) or NPE-IE (right) cells and subjected to IP injection of anti-CD8 or isotype matched control (IgG2b). NPE: n = 6 mice + ɑCD8, n = 5 mice + ɑIgG2b; p = 0.1002. NPE-BL6-TD: n = 6 mice + ɑCD8, n = 4 mice + ɑIgG2b; p = 0.1705. NPE-IE: n = 12 + ɑCD8, n = 10 + ɑIgG2b; p = 0.0171). (B) Example gating strategy to determine immune cell populations in normal and tumor-burdened whole brains. (C) Quantification of the proportions of major immune cell populations in normal whole brains and tumor-burdened brains. (D) Quantification of PD1⁺ TIM3⁺ CD4 and CD8 T cells in whole brains of non-transplanted BL6 mice versus those with tumors from transplanted NPE or NPE-IE cells; n = 4 brains analyzed for each condition. (E) Representative images of cell classification training used for macrophage quantification in NPE/NPE-IE fluorescent IHC images. (F) Quantification of Iba1+ F4/80+ macrophage populations as fraction of the total cell population (right). p values calculated with one-way ANOVA, n = 3 – 5 brains from each condition analyzed.

Figure 2

Whole brain immune population profiling reveals recapitulation of human GBM (A) Multi-parametric flow cytometry uniform manifold approximation and projection (UMAP) of immune cell populations (CD45⁺) in whole brains of non-transplanted BL6 mice versus those with NPE or NPE-IE tumors; n = 4 brains per condition. (B) Quantification of macrophage (left) and microglia (right) populations in (A). (C) Quantification of CD8 T cell (left), CD4 T^reg (center), and FOXP3⁻ CD4 T cell populations in (A). (D) Multi-parametric flow cytometry UMAP of myeloid populations (CD45⁺/CD11b⁺) in whole brains of non-transplanted BL6 mice versus those with NPE or NPE-IE tumors; n = 4 per condition. (E) Representative fluorescent IHC of macrophage populations (F4/80⁺, Iba1⁺) in NPE or NPE-IE tumors/adjacent tissue; (n = 3–5 per condition), scale bar, 200 μm. (F) Quantification of Iba1⁺ F4/80⁺ populations in (E) shown as frequency per mm². One-way ANOVA, n = 3–5 brains from each condition analyzed. See also Figure S2.

Figure 3

Immune evasive NPE-IE tumors possess a highly immunosuppressive microenvironment (A) Fast interpolation-based t-distributed stochastic neighborhood embedding (FIt-SNE) maps of cell populations in NPE and NPE-IE tumors. (B) Quantification of cell population frequencies in (A) as proportion of total live cell population (n = 4 per condition). (C) Flt-SNE maps of myeloid (CD11b⁺) cells in NPE and NPE-IE tumors. (D) Quantification of macrophage, M-MDSCs, and microglia frequency in (C) as proportion of total live cell population (n = 4 per condition). (E) PD-L1 median fluorescent intensity (MFI) quantification on microglia and macrophages in NPE and NPE-IE tumors (n = 4 per condition). (F) Bioluminescent imaging of NPE-IE tumor progression in BL6 in vivo following intraperitoneal (i.p.) injection of aCSF-1R or PBS. (G) Survival analysis of BL6 mice orthotopically injected with NPE-IE cells and subjected to i.p. injection of αCSF-1R (n = 17) or PBS (n = 11). (H) Quantification of CD8⁺/CD4⁺ T cell population frequencies in NPE and NPE-IE tumors as a proportion of total live cell population in (A) (n = 6 per condition). (I) Phenotypic marker expression of CD8⁺/CD4⁺ T cell subsets from (A) (n = 6 per condition). For Flt-SNE plots, data were generated from 150,000 live cells randomly sampled from 3 tumors per condition (50,000 live events shown per tumor). See also Figure S3.

Figure S3

Immune evasive NPE-IE tumors possess a highly immunosuppressive TME, related to Figure 3 (A) & (B) Gating strategy to define myeloid (A) and lymphoid (B) populations in NPE and NPE-IE tumors. (C) Representative histograms of PD-L1 expression on microglia and macrophages in NPE-IE tumors (linked to Figure 3E). Control represents fully stained sample minus anti-PD-L1 antibody. (D) Representative histograms of CD206, CD86 and CD11c expression on macrophages from NPE and NPE-IE tumors. Data derived from 3 tumors randomly down sampled for 50,000 live cells each. Control represents fully stained sample minus either anti-CD206, anti-CD86 or anti-CD11c antibodies. (E) Flow cytometry quantification of the frequency of macrophages, M-MDSC and microglia positive for expression of PD-L1 (F) Flow cytometry quantification of the frequency of NK cells as a percentage of live cells. (G) Flow cytometry quantification of the frequency of CD11b⁺ DCs as a percentage of live cells. (H) Flow cytometry quantification of CD11b⁺ DCs positive for expression of PD-L1. (I) Survival analysis of NSG mice orthotopically injected with NPE-IE cells subjected to IP injection of aCSF-1R or PBS (n = 5 mice + ɑCSF-1R; n = 3 mice +PBS; p = 0.2367).

Figure S4

Transcriptional and epigenetic reconfiguration occurs across mouse samples, with DNA hypomethylation occurring at key immune-associated genes, related to Figures 4 and 5 (A) WGS copy number heatmap of log₂ ratios of coverage for NPE and NPE-IE lines demonstrates genetic stability of mouse lines (gain of chrX evident as CNVs were called against male reference). (B) Principal Component Analysis (PCA) of RNA-seq data (top 500 most variable genes) for all cell line samples. (C) Heatmap of Z-scaled normalized counts for genes specific to all cell lines engineered with Nf1 loss ordered by log₂ fold change (NF1 KO samples Vs. all others) (top). Z-scaled normalized counts of specific genes shown in heatmap across all mutants (Red trend line indicates mean Z-scaled expression) (bottom). (D) Pairwise comparisons of CpG methylation changes between lines (excluding NP double mutant) as density scatterplots, and DMR bar plots – highlighting the predominant hypomethylation within tumor derived samples. (E) Rank plots of promoter DMRs (+/− 2kb TSS) displaying hypomethylation in NPE-NSG-TD lines versus NPE samples (DMRs with > 50% methylation loss, overlapping genes within immune and interferon GO terms are highlighted in blue). (F) Promoter DMR methylation (%) across lines for Irf8, Nt5e and Cd274, genes (top), and correlation with RNA-seq normalized counts (bottom) (SCC, and p value reported). (G) RNA-seq normalized counts of Nt5e across analyzed lines.

Figure 4

Immune evasive cells undergo significant transcriptional reconfiguration following immune attack (A) PCA (principal component analysis) of mRNA-seq data (top 500 most variable genes) from NPE cells and derivative lines (B) Heatmap of Z scaled normalized counts for genes specific to NPE-BL6-TD and NPE-IE lines ordered by log₂ fold change (NPE-BL6-TD and NPE-IE versus all others) (top). Z scaled normalized counts of specific genes shown in (B) across all mutants (red trend line indicates mean Z scaled expression) (bottom). (C) Heatmap of ssGSEA enrichment for select immune associated GO signatures across cell lines (top panel) and ssGSEA enrichment for Verhaak subtypes (proneural [PN], classical [CL], mesenchymal [MES]) (bottom) (-log₁₀ p values (red/blue), simplicity scores (white/gray), and ssGSEA enrichment (red/yellow/blue) reported). (D) Gene set enrichment analysis (GSEA) plot of chemokine-mediated signaling pathway for genes differentially expressed between NPE-IE and NPE-BL6-TD samples (enrichment score [ES] and false discovery rate [FDR] reported). (E) Volcano plot of differentially expressed genes between NPE-BL6-TD and NPE-IE. Ccl9 highlighted as gene with highest log₂ fold change. (F) Normalized read counts of selected chemokines (Ccl9, Ccl6, and Ccl2). (G) Forward phase protein array analysis of selected chemokines (CCL9, CCL6, and CCL2). See also Figure S4 and Tables S2 and S3.

Figure 5

Immune evasion in NPE-IE lines is underpinned by epigenetic immunoediting (A) PCA of RRBS CpG methylation (top 25% most variable CpG sites). (B) Density heatmap of CpG methylation (%) across lines. (C) Density scatterplots of CpG methylation (%) (left) and differentially methylated region (DMR) bar plots (right) (red, hypermethylated DMRs; blue, hypomethylated DMRs) in NPE-BL6-TD and NPE-IE lines versus NPE (% DMR methylation change reported). (D) Rank plots of promoter DMRs (±2 kb TSS) displaying hypomethylation in NPE-BL6-TD (top) and NPE-IE (bottom) versus NPE samples (DMRs with >50% methylation loss, overlapping genes within immune and interferon GO terms are highlighted in blue). (E) Mean CpG methylation (%) tracks for profiled samples around Irf8 transcriptional start site. See also Figure S4.

Figure 6

Irf8 is responsive to IFNγ and TAMs in NPE cells in vitro and is important for immune evasion (A) GSEA of IFNγ response signature in NPE-IE cells (enrichment score [ES] and FDR reported). (B) RT-qPCR analysis of Irf8 expression in NPE, NPE-BL6-TD and NPE-IE cells in vitro ± IFNγ treatment. (C) Representative immunoblot of IRF8 expression in NPE cell panel ± IFNγ time series treatment in vitro (n = 3). (D) Representative immunoblot of IRF8 and pSTAT1 expression in NPE cell panel with IFNγ/Tofacitinib treatment in vitro (n = 3). (E) qRT-PCR analysis of Irf8 expression in NPE cells in vitro versus GFP⁺ cells derived directly from NPE tumors in NSG/BL6 hosts. Points represent technical duplicates of cells isolated from individual animals. (F) Schematic of NPE cells co-culture with immune populations derived from NPE tumors. (G) RT-qPCR analysis of Irf8 expression in NPE cells co-cultured as in (F) (paired t test). (H) Representative bioluminescent imaging of NPE-IE/NPE-IE-Irf8^KO tumor progression in BL6 in vivo (Irf8^KO clone G4 shown). (I) Survival of BL6 mice orthotopically transplanted with NPE-IE cells versus clonally derived NPE-IE-Irf8^KO lines (NPE-IE, n = 12; NPE-IE Irf8^KO G4, n = 15; NPE-IE Irf8^KO K6, n = 10; NPE-IE Irf8^KO E6, n = 6). p values for survival of each Irf8^KO line versus parental NPE-IE: ^∗∗parental versus Irf8^KO G4, p = 0.0047; ^∗parental versus Irf8^KO K6, p = 0.0323; parental versus Irf8^KO E6, p = 0.0857. RT-qPCR data representative of at least 3 biological replicates performed in technical duplicates; relative quantification (RQ) to NPE untreated sample. See also Figure S5.

Figure S5

Irf8 is responsive to IFNγ and TAMs in NPE and PPP cells in vitro and is important for immune evasion, related to Figure 6 (A) Immunoblot analysis of Irf8 expression in NPE cells and subsequently tumor-derived lines with and without in vitro IFNγ treatment (representative of n = 3 experiments). (B) RT-qPCR analysis of Irf8 (left) and Ifih1 (right, confirms stimulation of IFN signaling) expression in untreated (UT) NPE, NPE-BL6-TD and NPE-IE cells versus in vitro treatment with IFNα/β (a, b, respectively). Error bars represent SEM, RQ (relative quantification) relative to NPE untreated conditions. (C) Schematic of Irf8-mCherry reporter design. (D) Flow cytometric analysis of mCherry expression in NPE-Irf8-mCherry reporter lines ± IFNγ treatment versus Parental NPE lines with adjunct histograms showing population distributions. (E) Gating strategy employed to isolate GFP⁺ tumor cells, CD45⁺CD3⁺ T cells and CD45^hi/lo F4/80⁺ myeloid cells from NPE tumors in NSG or BL6 host mice. Related to Figure 6E. (F) RT-qPCR analysis of selected target gene expression (H2-Ab1, H2-Q7 and Ifi47) in ‘immune naive’ NPE cells in vitro compared with cells derived directly from NPE tumors in NSG and BL6 hosts. Each point represents technical duplicates of cells isolated from individual animals. Related to Figure 6E (G) Heatmap illustrating expression levels of selected target gene expression (Irf8, H2-Q10, H2-Ab1, H2-Q7 and Ifi47) in untreated NPE cells versus those co-cultured with NPE tumor-derived immune populations in vitro. Gene expression was determined by RT-qPCR and is displayed as normalized expression values from technical duplicates of n = 3 biological replicates, related to Figure 6G. (H) Heatmap illustrating expression levels of selected target gene expression (Irf8, H2-Q10 and H2-Ab1) in untreated PPP cells versus those co-cultured with NPE tumor-derived immune populations in vitro. Gene expression was determined by RT-qPCR and is displayed as normalized expression values from technical duplicates of n = 3 biological replicates. (I) PCR genotyping of Irf8 locus in NPE-IE lines versus clonally derived NPE-IE Irf8 KO lines confirms successful gene targeting. (J) Immunoblot of IRF8 expression in NPE-IE lines in the presence or absence of IFNγ treatment in vitro.

Figure S6

Non-negative matrix factorization (NMF) of bulk RNA-seq in patient-derived GSCs identifies two distinct subtypes, related to Figure 7 (A) NMF of bulk RNA-seq highlights two predominant subgroups within patient-derived GBM GSCs. Consensus matrices for each NMF model across different ranks, or number of considered meta-gene modules (Metagenes, Consensus cluster assignment, Silhouette score to assess cluster quality, -log10 p values for Verhaak subtypes, and average connectivity across runs, are reported). (B) Consensus matrices for different algorithms of rank 2 highlight stability across approaches (left). Cophenetic score computed for each number of considered meta-genes (dotted line represents random data), highlight two subgroups as optimal (right). (C) Heatmap of ssGSEA enrichment for MES^Imm signature across engineered mouse cell lines (-log₁₀ p values (Red/Blue), and ssGSEA enrichment (red/yellow/blue) are reported). (D) PCA of publicly available scRNA-seq data of adult GBM cells (Neftel et al., 2019). Separation along PC2 is associated with IFN signaling genes (highlighted in black), and mesenchymal subtype genes (CD44, CHI3L1, and VIM highlighted in red). (E) scRNA-seq ssGSEA enrichment for select immune GO terms across adult GBM cells ordered by MES^Imm subtype p value. (F) Heatmap of Z-score TPM scRNA-seq of adult GBM cells for IFN genes highlighted in Figure 7B (top), and IRF family members (bottom), ordered by MES^Imm subtype p value. Differential expression between MES^Imm and Non-MES^Imm samples log₂ fold change, percentile of effect size, and adjusted p values are reported. (G) Heatmap of Spearman’s rank correlation coefficient for gene sets from (S6F) with previously published subtypes (Non-MES^Imm, MES^Imm highlighted in red).

Figure 7

Human GSCs display two predominant major transcriptional subtypes, one of which is defined by IFN signaling and hypomethylation and is similar to the mesenchymal subtype from Verhaak et al., 2010 (A) Metagene (S1 Non-MES^Imm and S2 MES^Imm) enrichment and Verhaak subtype classification (PN/CL/MES, ssGSEA -log₁₀ p values reported) across human GSCs. (B) Heatmap of Z-scaled normalized counts for genes specific to metagene modules (S1 Non-MES^Imm/S2 MES^Imm). IFN associated genes specific to S2 MES^Imm module highlighted. (C) Pathways enriched within S1 Non-MES^Imm/S2 MES^Imm signatures (^∗terms of interest). (D) Expression of candidate genes of interest (CCL2, IRF1, IRF7, and IRF8) in human Non-MES^Imm versus MES^Imm GSCs. (E) Density heatmap of CpG methylation levels (beta values) in human GSCs. (F) Empirical cumulative distribution function (ECDF) for DNA methylation levels (beta values) across GSCs (red, MES^Imm; blue, Non- MES^Imm). (G) Bar plot of DMRs between MES^Imm and Non-MES^Imm GSCs (red, hypermethylated DMRs; blue, hypomethylated DMRs, DMR methylation % change reported). (H) Density scatterplot of CpG methylation (beta values) between MES^Imm and Non-MES^Imm GSCs. See also Figures S6 and S7 and Table S4.

Figure S7

Comparison of the MES^Imm subtype with published subtypes across single cell data—with hypomethylation evident in MES^Imm samples, related to Figure 7 (A) Heatmap of -log₁₀ ssGSEA p values for subtypes across single cell RNA-seq cohort (Neftel et al., 2019). (B) Scatterplot of ssGSEA enrichment scores and mean methylation (beta-values) for each sample (red: MES^Imm, blue: Non- MES^Imm), with correlation coefficients reported. (C) Genome tracks of key DMRs for IRF1, CCL2, and IRF8 (red: MES^Imm, blue: Non- MES^Imm). (D) Methylation (beta-value) at each CpG site within each corresponding DMR (trend lines denote LOESS curves).