PHGDH-mediated endothelial metabolism drives glioblastoma resistance to chimeric antigen receptor T cell immunotherapy

Abstract

The efficacy of immunotherapy is limited by the paucity of T cells delivered and infiltrated into the tumors through aberrant tumor vasculature. Here, we report that phosphoglycerate dehydrogenase (PHGDH)-mediated endothelial cell (EC) metabolism fuels the formation of a hypoxic and immune-hostile vascular microenvironment, driving glioblastoma (GBM) resistance to chimeric antigen receptor (CAR)-T cell immunotherapy. Our metabolome and transcriptome analyses of human and mouse GBM tumors identify that PHGDH expression and serine metabolism are preferentially altered in tumor ECs. Tumor microenvironmental cues induce ATF4-mediated PHGDH expression in ECs, triggering a redox-dependent mechanism that regulates endothelial glycolysis and leads to EC overgrowth. Genetic PHGDH ablation in ECs prunes over-sprouting vasculature, abrogates intratumoral hypoxia, and improves T cell infiltration into the tumors. PHGDH inhibition activates anti-tumor T cell immunity and sensitizes GBM to CAR T therapy. Thus, reprogramming endothelial metabolism by targeting PHGDH may offer a unique opportunity to improve T cell-based immunotherapy.

Keywords: ATF4; CAR T immunotherapy; PHGDH; endothelial metabolism; glycolysis; vascular pruning.

Figure 1.. Metabolomic and transcriptomic analyses identify altered serine metabolism and PHGDH expression in tumor ECs.

Human ECs were isolated from normal brains or GBM tumors. (A,B) Cellular metabolites were analyzed by LC-MS (n = 3–5 human samples, pooled from three assays). (A) Dimensionality reduction analysis. Ellipse lines with center diamonds indicate 95% Cl ranges with means. (B) Pathway analysis of changed metabolites in tumor ECs for 65 metabolites in 28 metabolism pathways. (C,D) RNA was extracted from human ECs derived from tumors or normal brains, or treated with or without tumor-conditioned medium (-CM), followed by bulk RNA-seq analysis. Metabolic genes from KEGG database were analyzed. (C) Genes wtih >50% changed expression by tumor-CM treatment and in tumor-derived ECs were analyzed and plotted in KEGG metabolism modules. (D) Heatmap of gene expression for top two upregulated modules. (E,F) Human normal brain and tumor ECs were lyzed. (E) Cell lysates were immunoblotted. (F) RNA was extracted and analyzed by RT-PCR. PHGDH expression was normalized with vinculin expression (mean ± SEM, n = 3–4 human samples with 4 technical replicates). Statistical analysis between normal brain and tumor ECs was performed by unpaired two-tailed Student’s t test.

Figure 2.. Single-cell and bulk RNAseq reveals a critical and selective role of PHGDH for cell proliferation in tumor ECs.

(A-F) GBM was genetically induced in Ntv-a;Ink4a-Arf^−/−;Pten^fl/fl;LSL-Luc mice, followed by tumor implantation into Rosa-LSL-tdTomato;Cdh5-Cre^ERT2 mice. Tumor-derived single-cell suspension was analyzed by single-cell RNAseq (n = 4 mice). (A) Schematic approach. (B) Uniform manifold approximation and projection (UMAP) analysis of transcriptome gene signature in tdTomato⁺ ECs. (C) PHGDH expression in ECs derived from normal brain and GBM tumors. (D) EC distribution in difference cell cycle phases (mean ± SEM). (E) PHGDH expression in proliferating and quiescent ECs from all samples. (F) Left, tdTomato+ ECs were re-clustered and subjected to cell trajectory construction. Right, gene expression kinetics of Phgdh, Ki67 (Mki67), and Ribosomal Protein L36 (Rpl36) are expressed as a function of pseudotime in (top) normal brain and (bottom) tumor ECs. (G-I) Meta-analysis of integrated single-cell RNAseq data of human GBM (n = 60 patients). (G) UMAP analysis of tumor ECs. (H) PHGDH expression in proliferating and quiescent ECs. (I) Tumor ECs were subjected to cell trajectory construction analysis. Gene expression kinetics of Phgdh, Ki67, and Rpl36 are expressed as a function of pseudotime. (J-L) ECs derived from human GBM tumors were treated with CRISPR sgRNA targeting PHGDH or control sequence. (J) RNA was analyzed by RT-PCR (n = 3, mean ± SEM). Statistical analysis by two-way ANOVA. (K,L) RNA was extracted and analyzed by bulk RNAseq. (K) Heatmap of genes with >50% expression changes. (L) Pathway analysis of the altered genes, visualizing the complex association between genes and gene sets, with the graph showing the average expression changes of the top regulated genes, and with the dots showing the pathways these genes are mapped to. (M) Human ECs derived from normal brains or GBM tumors were treated with PHGDH inhibitors, WQ2101 and WQ2201, followed by cell viability analysis (n = 3, mean ± SEM). Results are expressed as % of the values at time 0. (N) GBM ECs were labeled with CellTrace Far Red and co-cultured in an in vitro flow system, followed by treatment with or without WQ2201 and imaging. Top, Representative images. Grid indicates 100 mm. Bottom, quantified results (n = 3, mean ± SEM). Statistical analysis by unpaired Student’s t test.

Figure 3.. PHGDH modulates redox homeostasis and glycolytic carbon flux to regulate proliferation in tumor ECs.

(A-G) Human tumor ECs derived from patients with GBM were treated with WQ2201 and subjected to [U-13C]-glucose isotopomer tracing. (A) Schematic carbon flux and role of PHGDH in metabolism pathways. Pentose phosphate pathway, PPP; Serine synthesis pathway, SSP; TCA cycle, tricarboxylic acid cycle. (B-G) Relative integrated peak intensities for (B) SSP-, (C) glycolysis-, (D) TCA cycle-, (E) PPP-, (F) 2-HG-, and (G) nucleotide synthesis-related metabolites. Statistical analysis by Student’s t-test (n = 3 EC samples, mean ± SEM). (B) Left, abundance of serine and glycine were analyzed 3 h after glucose tracing. Right, quantified fraction of labeled m+3 serine and m+2 glycine. (C-G) Metabolites were analyzed 24 h after glucose tracing. (H-K) Human tumor ECs were treated with or without WQ2201 for 24 h, followed by biochemical analysis of (H) total GSH, (I) ratio of GSH/GSSG, (J) NADH, and (K) ratio of NAD+/NADH. Statistic analysis by Student’s t-test (n = 5–6 EC samples, mean ± SEM). (L) Human tumor ECs were treated with WQ2201 in the medium supplemented with different molecules for 96 h, followed by cell viability analysis. Statistical analysis by two-way ANOVA (n = 6 assays, mean ± SEM). (M) Human tumor ECs were treated with WQ2201 in the medium supplemented with GSH for 24 h, followed by [U-13C]-glucose isotype tracing for 24 h. Shown are relative integrated peak intensities for glycolysis. Statistical analysis by two-way ANOVA (n = 3 EC samples, mean ± SEM).

Figure 4.. ATF4 induces PHGDH expression in ECs under GBM conditions.

(A,B) RNA was extracted from ECs derived from GBM tumors (n = 5 human patients) or normal brains (n = 3 humans), or treated with or without tumor-conditioned medium (n = 3 humans), followed by RNA-seq analysis. (A) Gene expression levels of ENCODE-predicated transcriptional factors (TFs) that potentially bind to PHGDH promoter. Top upregulated (> 50% in both groups) TFs are listed. (B) Pathway analysis of top up-regulated TFs. (C) Human GBM- and normal brain-derived ECs were treated with siRNA targeting ATF4, NRF2, or control sequence. Cell lysates were immunoblotted. (D,E) Human GBM-derived ECs were treated with (D) siRNA targeting ATF4 or control sequence, or (E) ISRIB or thapsigargin. RNA was analyzed by RT-PCR. Statistical significance was determined by (D) Student’s t test or (E) one-way ANOVA (n = 3 human patients, mean ± SEM). (F) Nuclei extracts from normal or tumor ECs were immunoprecipitated with an anti-ATF4 antibody or a control antibody, followed by ChIP analysis of ATF4 binding to the PHGDH promoter (n = 3 EC samples, mean ± SEM). Statistical analysis by two-way ANOVA. Ab, antibody. (G,H) Human normal brain ECs were pre-treated with siRNA targeting ATF4 or control sequence, followed by (G) incubation with VEGF or tumor-conditioned medium (tumor-CM) and (H) exposure to hypoxia or serine- and glycine-free medium. Statistical analysis by one-way ANOVA (n = 3 EC samples, mean ± SEM). (G) RNA was analyzed by RT-PCR. (H) Cell lysates were immunoblotted. (I,J) Human normal brain ECs were treated with (I) VEGF, tumor-CM, (J) hypoxia, or serine/glycine-depleted medium. Nuclei extracts were immunoprecipitated and analyzed by ChIP (n = 3 EC samples, mean ± SEM). Statistical analysis by two-way ANOVA. (K) Human normal brain ECs or GBM ECs were treated with siRNA targeting ATF4 or control sequence, followed by calcein AM cell proliferation analysis (n = 5 EC samples, mean ± SD). Statistical analysis by Student’s t test.

Figure 5.. Endothelial-specific knockdown of PHGDH reduces vascular aberrancy and attenuates GBM growth.

(A,B) Phgdhfl/fl mice were generated by insertion of loxP sites into mouse genome, followed by crossing with Cdh5-CreERT2 mice. (A) Schematic approach for generation of Phgdh^fl/fl (control) or Chd5-Cre^ERT2;Phgdh^fl/+ (PHGDH-EC^KD) mice. 2 weeks old mice were treated with tamoxifen. Inset: ECs were isolated from mouse brains and aortas, and subjected to RT-PCR analysis (n = 4–5 mice). Statistical analysis by two-way ANOVA. (B-D) Primary GBM was induced in Ntv-a;Ink4a-Arf^−/−;Pten^−/−;LSL-Luc donor mice by RCAS-mediated somatic gene transfer. Single-cell tumor suspension was transplanted into control and PHGDH-EC^KD recipient mice. (B) Schematic approach. (C) Animal survival was monitored for 60 days after injection (n = 11–12 mice). MS, median survival. Statistical analysis by LogRank. (D) Tumor growth was analyzed by whole-body bioluminescence imaging. Dashed lines with shadow area indicate non-linear Loess regression with 95% Cl range (n = 11–12 mice). (E-G) GBM was genetically induced by RCAS-mediated somatic gene transfer, followed by transplantation into control or PHGDH-EC^KD recipient mice. Tumors were excised and analyzed by light sheet fluorescence imaging. (E) Schematic approach. (F) Vasculature and hypoxia were imaged in tumors. Top, representative images. Bottom, quantitative results for tumor vascular characters and hypoxia in 1 mm³ tissues (n = 3 mice for control group, n = 6 mice for PHGDH-EC^KD group, mean ± SEM). Statistical analysis by two-tailed Student’s t test. (G) Tumor tissues were stained with anti-CD3 antibody, followed by imaging. Top, representative images. Bottom, quantitative results in 1 mm3 tissues (n = 3 mice for control group, n = 6 mice for PHGDH-EC^KD group, mean ± SEM). Statistical analysis by two-tailed Student’s t test.

Figure 6.. PHGDH inhibition prunes tumor vasculature and improves T cell infiltration and activation in GBM.

(A-H) GBM was genetically by RCAS-mediated somatic gene transfer, followed by transplantation into (B,C) Rosa-LSL-tdTomato;Cdh5-Cre^ERT2 and (D-H) WT C57BL/6 recipient mice. Mice were treated with saline or WQ2201, and tumors were excised and analyzed. (A) Schematic approach. (B) Vasculature and hypoxia were imaged in tumors. Top, representative images. Bottom, quantitative results for tumor vascular characters and hypoxia in 1 mm³ tissues (n = 5 mice for normal brain group, n = 3 mice for other groups, mean ± SEM). Statistical analysis by two-tailed Student’s t test. (C) Tumor tissues were stained with anti-CD3 antibody, followed by imaging. Top, representative images. Bottom, quantitative results in 1 mm³ tissues (n = 3 mice for normal brain and saline group, n = 4 mice for WQ2201 group, mean ± SEM). Statistical analysis by two-tailed Student’s t test. (D-H) Tumor-derived single-cell suspensions were analyzed using (D-F) CyTOF and (G,H) flow cytometry. (D) Representative CyTOF results. (E,F) CyTOF analysis of T cells (n = 3 mice, mean ± SEM). Statistical analysis by two-tailed Student’s t test. (G,H) Flow cytometry analysis of (G) total and (H) subpopulation T cells (mean ± SEM, n = 3–10 mice, specific n value is indicated). Statistical analysis by two-tailed Mann-Whitney t test. (G) Left, representative sortings. Right, Quantitative results.

Figure 7.. PHGDH inhibition improves EGFRviii CAR T immunotherapy in GBM.

GBM was induced in mice by transplantation of RCAS/Tva-induced murine tumors or GL261 glioma cells. After tumor induction, mice were treated with saline or WQ2201, followed by CAR T cell therapy. (A) Experimental approach. (B) T cell trafficking in RCAS tumors was imaged by bioluminescence. Left, representative sortings. Right, quantitative results (n = 5 mice, mean ± SEM). Statistical analysis by two-way ANOVA. (C,D) Mouse survival was monitored for 60 days in (C) RCAS and (D) GL261 model. Statistical analysis by LogRank (n = 10 mice). (E,F) Tumor growth was analyzed by bioluminescence imaging in (E) RCAS and (F) GL261 model. Dashed lines with shadow area indicate non-linear Loess regression with 95% Cl range (n = 10 mice). (G) A schematic model.