CD97 maintains tumorigenicity of glioblastoma stem cells via mTORC2 signaling and is targeted by CAR Th9 cells

Abstract

Glioblastoma (GBM) stem cells (GSCs) contribute to poor prognosis in patients with GBM. Identifying molecular markers is crucial for developing targeted therapies. Here, we identify cluster of differentiation 97 (CD97) as an optimal GSC surface antigen for potential targeting by chimeric antigen receptor (CAR) T cell therapy through in vitro antibody screening. CD97 is consistently expressed in all validated patient-derived GSCs and positively correlated with known intracellular GSC markers. Silencing CD97 reduces GSC tumorigenicity-related activities, including self-renewal, proliferation, and tumor progression. Transcriptome analysis reveals that CD97 activates mTORC2, leading to AKT S473 phosphorylation and enhanced expression of the downstream genes ARHGAP1, BZW1, and BZW2. Inhibiting mTORC2 with JR-AB2-011 suppresses GSC tumorigenicity and downstream gene expression. We develop CD97-CAR T helper (Th) 9 cells, which exhibit potent cytotoxic effects in vitro and extend survival in mice. These findings suggest that CD97 is a promising GSC-enriched antigen and that targeting it with CAR Th9 cells offers a potential therapeutic strategy for GBM.

Keywords: CAR T; CD97; Th9 cell; glioblastoma; glioblastoma stem cell; mTORC2; self-renewal; tumorigenicity.

Graphical abstract

Figure 1

Identification of surface antigens for GSCs (A) Schematic illustrating the experimental design. Human astrocytes and GSCs (83 and X01) were profiled using multiple antibody libraries. (B) Heatmap showing the top 32 genes of human cell surface antigens, ranked based on the fold change values of fluorescence intensity compared to normal astrocytes or differentiated GSCs. (C and D) High-throughput confocal immunofluorescence (IF) staining images showing staining with the anti-CD97 antibody (C) and quantification of fluorescence in the antibody array (values normalized to those of astrocytes) (D). Scale bar, 50 μm. All error bars represent the mean ± standard error of the mean (SEM; n = 3 independent experiments). (E) Quantitative reverse-transcription PCR (RT-qPCR) and immunoblot (IB) analyses of CD97 expression in astrocytes, GSCs, and serum-differentiated GSCs (83-Diff and X01-Diff). β-actin was used as a loading control. Error bars represent the mean ± standard deviation (SD; n = 3 independent experiments). (F) Flow cytometry analysis of astrocytes, GSCs, and serum-differentiated GSCs (83-Diff and X01-Diff) using a phycoerythrin (PE)-conjugated anti-CD97 antibody. (G) Flow cytometry analysis of CD97 expression on patient-derived GSCs, stained with a PE-conjugated anti-CD97 antibody. (H and I) CD97 protein expression in NT and GBM tissues (H) and the expression in each GBM subtype (I) according to the CPTAC database. NT, nontumor; CL, classical; MES, mesenchymal; NL, neural; PN, proneural. (J) Kaplan-Meier overall survival curves for patients with GBM presenting high and low CD97 protein expression according to the CPTAC database. Groups were divided by optimal cutpoints using “survminer” R package. The p value was determined using the log rank (Mantel-Cox) test. ∗∗∗∗p < 0.0001, ∗∗∗p < 0.001, ∗p < 0.05, t test in (C), (D), (E), and (H). See also Figure S1.

Figure 2

Validation of CD97 as an optimal GSC marker (A) Bubble plot comparing expression of ADGRE5/CD97 and stem cell-related genes on GSCs and GBM tumors using single-cell RNA sequencing datasets from the study by Restall and Richards. (B) Scatterplots to compare the RNA expression level of ADGRE5 and NES according to patients with GBM in the TCGA, CCGA, and REMBRANDT databases. CD97 is encoded by ADGRE5 gene. Nestin is encoded by NES gene. (C) Scatterplots to compare the protein expression level of CD97 and Nestin according to patients with GBM in the CPTAC database. (D) Flow cytometry plots in which CD97-PE was co-stained along with other GSC markers, including Nestin, Oct 3/4, Nanog, CD133 or CD49f, CD15, or CD44 in 83, X01, and GSC772. Each gate on the x and y axis separates positive from negative cells. The numbers in each quadrant indicate the percentages of cells. (E) Limiting dilution assay (LDA) using CD97^high CD49f^high, CD97^high CD49f^−/low, CD97^−/low CD49f^high, and CD97^−/low CD49f^−/low GSC 83 cells sorted through flow cytometry. (F–H) Confocal images of CD97 (green) and Nestin (red) co-immunofluorescence staining in brain tissues of the X01-xenograft (F) and human patients with GBM who have Nestin^Low (G) and Nestin^High (H). Scale bar, 50 μm. Quantification analysis of the percentage of the cell number CD97⁺/Nestin⁺ and CD97⁻/Nestin⁺ cells. All error bars represent mean ± SD (n = 3 independent experiments) in (E)–(H). ∗∗∗∗p < 0.0001, ∗∗∗p < 0.001, t test. n.s, non-significant. See also Figures S2–S5.

Figure 3

Characterization of CD97^high cells in vitro and in vivo (A) GSC772 cells were stained with an anti-CD97 antibody and analyzed using flow cytometry. The Neg.Ctrl group is shown in gray and the Anti-CD97 group is shown in red. (B–E) RT-qPCR (B) and IB analysis (C) of stemness-related genes, proliferation assays (D), and LDAs (E) in the CD97^high and CD97^−/low subpopulations of GSC772. β-actin was used as a loading control. (F) GSC924 cells were stained with an anti-CD97 antibody and analyzed using flow cytometry as in (A). (G–J) RT-qPCR (G) and IB analysis (H) of stemness-related genes, proliferation assays (I), and LDAs (J) in the CD97^high and CD97^−/low subpopulations of GSC924. GAPDH was used as a loading control. (K) Kaplan-Meier survival curves of mice orthotopically implanted with CD97^high or CD97^−/low GSC772 cells (n = 8, 2.5 × 10⁵ cells/mouse). MST, median survival time. Log rank (Mantel-Cox) test. (L and M) Representative axial MRI (L) and the quantified tumor size (M) of mice bearing orthotopic xenografts of CD97^high or CD97^−/low GSC772 cells. Regions of interest (ROIs) within the tumor are indicated by white polygons. All error bars represent mean ± SD (n = 3 independent experiments). ∗∗∗∗p < 0.0001, ∗∗∗p < 0.001, ∗∗p < 0.01, ∗p < 0.05, t test in (B)–(J), (L), and (M).

Figure 4

CD97 regulates GSC tumorigenicity (A–D) RT-qPCR (A) of CD97 expression, IB analysis (B) of GSC intracellular markers, LDAs (C), and cell proliferation assays (D) in three different GSCs (83, X01, and 528 cells) infected with shCtrl, shCD97-1, or shCD97-3 lentivirus. β-actin, GAPDH, and vinculin were used as loading controls. All error bars represent mean ± SD (n = 3 independent experiments). ∗∗∗∗p < 0.0001, ∗∗∗p < 0.001, ∗∗p < 0.01, t test. (E) Flow cytometry analysis of Annexin V and PI staining in GSCs 83 infected with shCtrl, shCD97-1, or shCD97-3 lentivirus. (F) Kaplan-Meier survival curves of mice bearing orthotopic xenografts of three GSCs infected with shRNA lentivirus (n = 5 or 6, 1 × 10⁴ for 83 and X01, or 1 × 10⁵ for 528 cells/mouse). MST, median survival time. Log rank (Mantel-Cox) test. See also Figures S6–S10.

Figure 5

Screening of downstream targets of CD97 in GSCs (A) Schematic representation of the experimental strategy for the transcriptome analysis. Heatmap of the hierarchical clustering analysis showing the expression of 131 common downregulated genes in CD97-knockdown GSCs (right). (B) Gene set enrichment analysis (GSEA) plot for the regulation of stem cell population maintenance signature from the Gene Ontology Biological Process (GOBP) category comparing the shCtrl and shCD97 groups. NES, normalized enrichment score. (C) Bubble chart showing the top 10 biological processes of Gene Ontology terms for genes downregulated in CD97-knockdown GSCs. Size, gene number; color, −log₁₀ (p value). (D) RT-qPCR of PCBP1, BSG, ARHGAP1, BZW1, BZW2, and DBN1 expression in three different GSCs (83, X01, and 528 cells) infected with shCtrl or shCD97 lentivirus. β-actin was used as a loading control. All error bars represent mean ± SD (n = 3 independent experiments). ∗∗∗∗p < 0.0001, ∗∗∗p < 0.001, ∗∗p < 0.01, ∗p < 0.05, t test. (E) Kaplan-Meier overall survival curves for patients with GBM presenting the high and low expression of the CD97/ARHGAP1 (left), CD97/BZW1 (middle), and CD97/BZW2 (right) mRNAs according to TCGA GBM database. Log rank (Mantel-Cox) test. (F) Bubble chart showing the top 10 hallmark genes enriched in shCtrl GSCs. Size, gene number; color, −log₂ (p value). (G) GSEA plot for the PI3K/AKT/mTOR signaling signature from the Hallmark category comparing the shCtrl and shCD97 groups. See also Figure S11.

Figure 6

mTORC2 inhibition prevents proliferation and self-renewal in GSCs (A) IB analysis of CD97, p-S6K, p-AKT, S6K, AKT, ARHGAP1, BZW1, and BZW2 levels in three different GSCs (83, X01, and 528 cells) infected with shCtrl or shCD97 lentivirus. (B) RT-qPCR of BZW1 expression (left), cell proliferation assay (middle), and LDAs (right) in 83 and X01 GSCs infected with shCtrl and shCD97 lentivirus, followed by BZW1 lentivirus infection. (C–F) IB analysis of p-S6K, p-AKT, S6K, AKT, ARHGAP1, BZW1, and BZW2 levels in three different GSCs (83, X01, and 528 cells) treated with Torin1 48 h (C), AKT inhibitor IV 24 h (D), 24 h rapamycin (E), and JR-AB2-011 24 h (F). (G) Cell proliferation assays (left) and LDAs (right) were performed on 83 and X01 GSCs after treatment with JR-AB2-011. (H) Kaplan-Meier survival curves of mice orthotopically implanted with X01-Luc cells (n = 5, 1 × 10⁵ cells/mouse) and intraperitoneally (i.p.) treated with JR-AB2-011 (4 mg/kg) or vehicle. MST, median survival time. Log rank (Mantel-Cox) test. (I) Schematic representation of the CD97-related signaling pathway regulating the proliferation, self-renewal, and tumor progression of GSCs. Vinculin and GAPDH, and β-actin were used as loading controls in IB, β-actin was used as a loading control in RT-PCR. All error bars represent mean ± SD (n = 3 independent experiments) in (B) and (G). ∗∗∗∗p < 0.0001, ∗∗∗p < 0.001, ∗p < 0.05, t test. See also Figures S12–S15.

Figure 7

Antitumor activity of CD97-targeting CAR Th9 cells against GBM (A) Schematic showing the structure of the second-generation lentiviral vectors encoding CD97-CAR, including the 4-1BB and CD3ζ costimulatory domains. TM, transmembrane domain. (B) RT-qPCR analysis of IL-9 expression in CD8⁺ T cells, CD4⁺ T cells, and Th9 cells. (C) Flow cytometry analysis of CAR expression detected by the fusion protein EGFP. (D) Expansion kinetics of untreated, Ctrl-CAR, and CD97-CAR T cells in vitro (n = 3 independent experiments). (E) Antigen-specific in vitro cytotoxicity of CD97-CAR Th9 cells or Ctrl-CAR Th9 cells toward U87-Luc, 83-Luc, or X01-Luc cells, evaluated using a luciferase activity assay. (F) Flow cytometry analysis of CD4 and CD107a expression on CD97-CAR Th9 cells following incubation with 83-Luc and X01-Luc cells. (G) Representative confocal microscopy images showing CD97-CAR Th9 cells or Ctrl-CAR Th9 cells interacting with 83-Luc and X01-Luc cells at an E:T ratio of 1:1 for 24 h. Scale bar, 50 μm. (H and I) Antigen-specific in vitro cytotoxicity of CD97-CAR Th9 cells toward 83-Luc or X01-Luc cells infected with shCD97 or shCtrl lentivirus (H) and against X01-Luc cells at different E:T ratios (I). (J) Schematic experimental design to evaluate the antitumor effects of CD97-targeting CAR Th9 cells. Mice were implanted with X01-Luc cells (n = 6, 1× 10⁵ cells/mouse) and intracranially injected with CD97-CAR or Ctrl-CAR Th9 cells (1.5 × 10⁶ cells/mouse) on day 4. (K) Flow cytometry analysis showing the expression of CD4 and CD107a within the tumor two days post-treatment of CD97-CAR Th9 or Ctrl-CAR Th9 cells. (L) Bioluminescence images of mice as in (J). (M) Quantification of bioluminescence intensity of photons emitted from each tumor in the images in (L). Data are presented as mean ± SD, two-way ANOVA at day 24, ∗∗∗∗p < 0.0001. (N) Kaplan-Meier survival curve of mice as in (J). MST, median survival time. Log rank (Mantel-Cox) test. GAPDH was used as a loading control. All error bars represent mean ± SD (n = 3 independent experiments) in (B), (D), (E), (H), and (I). ∗∗∗∗p < 0.0001, ∗∗∗p < 0.001, ∗∗p < 0.01, ∗p < 0.05, t test. See also Figures S16–S18.