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. 2017 May 23;8(39):64932-64953.
doi: 10.18632/oncotarget.18117. eCollection 2017 Sep 12.

Notch signaling regulates metabolic heterogeneity in glioblastoma stem cells

N Sumru Bayin  1   2   3 , Joshua D Frenster  1   2 , Rajeev Sen  1 , Sheng Si  1   4 , Aram S Modrek  1 , Nataliya Galifianakis  1   5 , Igor Dolgalev  6 , Valerio Ortenzi  7 , Irineu Illa-Bochaca  8 , Anadjeet Khahera  1 , Jonathan Serrano  7 , Luis Chiriboga  7 , David Zagzag  1   7   9   10 , John G Golfinos  1   9   10 , Werner Doyle  1 , Aristotelis Tsirigos  7   11 , Adriana Heguy  6 , Mitch Chesler  1   5 , Mary Helen Barcellos-Hoff  12   13 , Matija Snuderl  7   9   10 , Dimitris G Placantonakis  1   2   5   9   10
Affiliations

Notch signaling regulates metabolic heterogeneity in glioblastoma stem cells

N Sumru Bayin et al. Oncotarget. .

Abstract

Glioblastoma (GBM) stem cells (GSCs) reside in both hypoxic and vascular microenvironments within tumors. The molecular mechanisms that allow GSCs to occupy such contrasting niches are not understood. We used patient-derived GBM cultures to identify GSC subtypes with differential activation of Notch signaling, which co-exist in tumors but occupy distinct niches and match their metabolism accordingly. Multipotent GSCs with Notch pathway activation reside in perivascular niches, and are unable to entrain anaerobic glycolysis during hypoxia. In contrast, most CD133-expressing GSCs do not depend on canonical Notch signaling, populate tumors regardless of local vascularity and selectively utilize anaerobic glycolysis to expand in hypoxia. Ectopic activation of Notch signaling in CD133-expressing GSCs is sufficient to suppress anaerobic glycolysis and resistance to hypoxia. These findings demonstrate a novel role for Notch signaling in regulating GSC metabolism and suggest intratumoral GSC heterogeneity ensures metabolic adaptations to support tumor growth in diverse tumor microenvironments.

Keywords: CD133; Notch signaling; glioblastoma stem cells; tumor metabolism; tumor vasculature.

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Conflict of interest statement

CONFLICTS OF INTEREST None

Figures

Figure 1
Figure 1. Notch activation and CD133 cell surface expression show differential intratumoral localization in human GBM
a., i. H&E reveals areas of microvascular proliferation (top panel) and PPN (bottom panel) within the same human GBM biospecimen. a., ii. Nuclear NICD1 immunoreactivity is seen in perivascular areas but not in PPN regions. a., iii. In contrast, CD133 immunoreactivity is seen in both microenvironments. b. Schematic of the lentiviral vector used to monitor Notch pathway activation. The 20 bp-long Notch response element contains a consensus GTGGGAA site found in Notch transcriptional targets. c. Schematic depicting the approach for obtaining patient-derived primary tumorsphere cultures and orthotopic tumor xenografts after transduction with NotchLenti. Scattered Notch-activated (GFP+) cells (arrowheads) were observed in tumorspheres in vitro. d. Flow cytometry histograms of GBM lines show gradients of (i) increased GFP fluorescence after transduction with NotchLenti and (ii) CD133 immunoreactivity after incubation with anti-CD133 antibody (n = 3 primary cultures). e. Immunofluorescent analysis of xenograft tumors generated by GBML8 cells modified with NotchLenti reveals perivascular GFP staining for Notch activation. f. Quantification of the distance of GFP+ or CD133-expressing cells from the vasculature (i) in xenograft tumors generated with 2 patient-derived cultures already modified with NotchLenti shows that GFP+ cells prefer a perivascular localization. (n = 3 animals for each condition, ii: GBML8: ANOVA, F(2,8) = 16.93, P < 0.003 and iii: GBML20: ANOVA, F(2,8) = 6.049, P < 0.03). H&E: hematoxylin and eosin; N: necrosis; BV: Blood vessel; CMV: Cytomegalovirus; GFP: Green Fluorescence Protein; CD105: Endoglin; DAPI: nuclear counter stain; ns: not significant.
Figure 2
Figure 2. Segregation of Notchhi and CD133hi cell populations
a., i Flow cytometric analysis of an intracranial tumor xenograft derived from GBML8-NotchLenti cells shows the segregation of CD133 expression (CD133hi) and Notch activation (Notchhi). a., ii Flow cytometric analysis of cell surface CD133 and Notch activation (GFP reporter) in 3 primary cultures in vitro shows that there is only partial overlap between the two markers. For the analysis in a., GFP gates were drawn based on parental cultures not transduced with NotchLenti, and CD133 gates were based on control conditions without antibody (as shown in Supplementary Figure 2c). b. Experimental plan for studying Notchhi and CD133hi cells. c. FACS-sorted CD133hi, Notchhi and DP cells were compared to DN cells for CD133 (PROM1) and HES5 mRNA expression by qPCR. The experiment was performed on two different primary cultures transduced with NotchLenti: (i) GBML8, and (ii) GBML20 (n = 3 FACS experiments/primary cell line, t-tests, P < 0.05). d. After FACS isolation, cells were seeded at low density (10 cells/μl) and tumorsphere formation was analyzed 7 days after isolation. Only Notch-activated populations (Notchhi and DP) showed decreased tumorsphere formation upon pharmacological inhibition of the Notch pathway with 10 µM DAPT in 2 cultures: (i) GBML8: ANOVA, F(7,14) = 9.472, P < 0.0002, (ii) GBML20: ANOVA, F(1.4) = 74.98, P < 0.001) (n = 3 experiments/primary cell line). e. To further confirm CD133hi and Notchhi cells represent distinct populations in GBM, we performed RNA-seq from FACS isolated cells from GBML8 and GBML20. RNA sequencing revealed 420 genes that were differentially expressed in CD133hi and Notchhi GSCs compared to DN cells (P < 0.05). f. When the RNA-seq data were analyzed for known GSC markers, CD133hi and Notchhi cells showed enrichment for these transcripts compared to the DN population (n = 7 genes, ANOVA F(1, 6) = 7.490, P < 0.03). ns: not significant.
Figure 3
Figure 3. Notchhi cells reside higher in the cellular hierarchy in vivo
a. Cells were isolated with FACS and xenograft tumors generated were analyzed by flow cytometry and histology 6 months after injection. b., i Tumor cells were isolated from intracranial xenografts generated either by CD133hi or Notchhi cells (GBML8) after confirmation of tumors with MRI. b., ii-iii Flow cytometric analysis revealed that tumors initiated by CD133hi GSCs contained significantly lower numbers of Notchhi cells, whereas CD133 percentages did not significantly change between the two different types of tumors (n = 3 animals/condition, ANOVA F(1,8) = 9.7, P < 0.01). c. Confocal immunofluorescence analysis of tumor xenografts generated by parental (i), CD133hi (ii) and Notchhi (iii) GBML8 cells shows that tumors generated by Notchhi GSCs more closely resemble parental tumors than CD133hi tumors (n = 3 animals/condition).
Figure 4
Figure 4. CD133hi and Notchhi GSCs have distinct angiogenic properties
a. Representative images of GBML8 xenografts show the contrast in vascular morphology of tumors derived from Notchhi (top panel) and CD133hi (bottom panel) cells (n = 3 animals/cell type). b. No significant change was observed in the number of vessels and average vascular area in xenografts generated by Notchhi or CD133hi cells from cultures GBML8 and GBML20 (4 20x fields/condition, n = 3 animals/cell type, t-tests, P > 0.05). c. Notchhi-initiated tumors contain large-caliber vessels, which are absent in CD133hi tumors (GBML8 and GBML20, n = 3 animals/cell type; Wilcoxon test, P < 0.001). d.,e. CD133hi tumors showed reduced perfusion (Evans Blue staining) and increased hypoxia (pimonidazole staining), compared to tumors generated by Notchhi cells (representative images from GBML8 xenografts, n = 3 animals/condition). f. Tumors initiated by Notchhi and CD133hi cells do not contain hNA+ endothelium (CD105+ cells) (representative images from GBML8 xenografts, n = 3 animals/cell type). g. α-SMA+ pericytes envelope larger vessels in Notchhi tumors (top panel). CD133hi tumors are devoid of pericytes (representative images from GBML8 xenografts, n = 3 animals/cell type). h. Lineage tracing in GBML8 xenografts shows GFP+ pericytes, indicating that they are derived from Notchhi cells. The inset shows that CD105+ endothelium is GFP- (n = 3 animals). ns: not significant.
Figure 5
Figure 5. CD133hi GSCs selectively utilize anaerobic glycolysis
a. GSEA analysis of transcriptomes of CD133hi and Notchhi cells revealed enrichment of hypoxia-responsive genes in CD133hi GSCs. b. Heatmap showing differentially expressed genes between CD133hi and Notchhi cells from the same gene set as in (a). c. Fold enrichment of critical hypoxia-induced genes in the CD133hi population. d. Schematic representation of these genes in the glycolytic and oxidative phosphorylation pathways. e. Western blotting for HIF1α shows increased protein levels after 24 hours of hypoxia in 3 different GBM cultures. f. CD133hi GSCs had higher total lactate levels than Notchhi GSCs in normoxic conditions (n = 3 experiments/primary cell line, t-tests, P < 0.04). g. CD133hi cells had significantly lower intracellular pH compared to Notchhi cells in normoxia (GBML8, t-test, P < 10-12). h. After 24 hours of hypoxia, CD133hi cells were able to further increase lactate production compared to Notchhi cells (n = 3 experiments, GBML8: t-test, P < 0.05, GBML20: t-test, P < 0.03). NES: normalized enrichment score; ETC: electron transport chain.
Figure 6
Figure 6. CD133hi GSCs expand in hypoxic conditions at the expense of Notchhi GSCs
a., b. Flow cytometry shows increased abundance of CD133hi cells after 24 hours of hypoxia in 2 of 3 cultures (GBML8 and GBML33: t-test, P < 0.02). c. The abundance of Notchhi GSCs significantly decreases in the same conditions (t-test, P < 0.02, n = 3 primary cultures). d. Percent of cells in apoptosis analyzed by TUNEL assay: (i) GBML8: ANOVA, F(1,8) = 5.57, P < 0.05; (ii) GBML20: ANOVA, F(1,8) = 10.79, P < 0.01. e. Percent Ki67+ cells in CD133hi and Notchhi GSCs from two different GBM cultures after 24 hours of hypoxia: (i) GBML8: ANOVA, F(1,8) = 0.047, P > 0.05; (ii) GBML20: ANOVA, F(1,8) = 1.9, P > 0.05). f. FACS-isolated CD133hi and Notchhi cells were allowed to form tumorspheres after 24 hours of hypoxia. Tumorsphere formation was analyzed 7 days later. Notchhi GSCs showed a significant reduction in their tumorsphere formation ability after hypoxia, whereas no significant change was observed in CD133hi GSCs: (i) GBML8: ANOVA, F(1,8) = 20.27, P < 0.002; (ii) GBML20: ANOVA, F(1,8) = 56.10, P < 0.018.
Figure 7
Figure 7. Ectopic Notch activation reprograms metabolism
a. Schematic representation of the lentiviral constructs used for ectopic activation of the Notch pathway (NICD-OE) or the control vector (mCherry) and the experimental plan. b. Representative FACS plot from GBML8 cells that were infected with either NICD-OE or mCherry virus, showing transduction efficiency. c. FACS-isolated mCherry+ cells from GBML8, GBML20 and GBML61 cultures showed increased HES5 transcript in the NICD-OE condition (n = 3 primary cultures, t-test, P < 0.02). d., e. Lactate level measurements in FACS-isolated mCherry+ cells after 24 hours of (d). normoxia or (e) hypoxia. NICD-OE led to significant downregulation in lactate levels in 3 primary cultures: (d) t-test, P < 0.001; (e) t-test, P < 0.05). (f-g) mCherry+ cells from GBML8 and GBML20 cells transduced with NICD-OE or mCherry virus were subjected to tumorsphere formation assay under normoxia or hypoxia. Ectopic Notch activation led to reduced tumorsphere formation under hypoxic conditions, whereas mCherry control did not show any change (n = 3/condition): f. GBML8: ANOVA, F(3,8) = 6.543, P < 0.05; (g) GBML20: ANOVA, F(3,12) = 8.256, P < 0.01. ns: not significant.
Figure 8
Figure 8. Schematic summarizing the role of distinct GSCs in tumor progression
See this image and copyright information in PMC

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