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. 2017 Sep 5;117(6):813-825.
doi: 10.1038/bjc.2017.263. Epub 2017 Aug 10.

Regulation of hypoxia-induced autophagy in glioblastoma involves ATG9A

Affiliations

Regulation of hypoxia-induced autophagy in glioblastoma involves ATG9A

Siti Aminah Abdul Rahim et al. Br J Cancer. .

Abstract

Background: Hypoxia is negatively associated with glioblastoma (GBM) patient survival and contributes to tumour resistance. Anti-angiogenic therapy in GBM further increases hypoxia and activates survival pathways. The aim of this study was to determine the role of hypoxia-induced autophagy in GBM.

Methods: Pharmacological inhibition of autophagy was applied in combination with bevacizumab in GBM patient-derived xenografts (PDXs). Sensitivity towards inhibitors was further tested in vitro under normoxia and hypoxia, followed by transcriptomic analysis. Genetic interference was done using ATG9A-depleted cells.

Results: We find that GBM cells activate autophagy as a survival mechanism to hypoxia, although basic autophagy appears active under normoxic conditions. Although single agent chloroquine treatment in vivo significantly increased survival of PDXs, the combination with bevacizumab resulted in a synergistic effect at low non-effective chloroquine dose. ATG9A was consistently induced by hypoxia, and silencing of ATG9A led to decreased proliferation in vitro and delayed tumour growth in vivo. Hypoxia-induced activation of autophagy was compromised upon ATG9A depletion.

Conclusions: This work shows that inhibition of autophagy is a promising strategy against GBM and identifies ATG9 as a novel target in hypoxia-induced autophagy. Combination with hypoxia-inducing agents may provide benefit by allowing to decrease the effective dose of autophagy inhibitors.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Hypoxia sensitises GBM cells to autophagy inhibitors. Chloroquine and bevacizumab were administered as single agents or simultaneously in P3 (A: 20 mg kg−1) and T16 (B: 20 and 50 mg kg−1) PDXs. Kaplan–Meier graphs show the survival of mice upon treatment. See Supplementary Table S1 for summary. Abbreviations: Bev=Bevacizumab; CQ=chloroquine; log-rank test, *P<0.05, **P<0.01, ***P<0.001. (C) Blood vessels from control and treated P3 PDXs were visualised by mouse-specific anti-CD31 (scale bars 100 μm). (D) Quantification of vessel number per mm2 upon treatment (mean±s.e.m., *P<0.05, **P<0.01, ***P<0.001). (E) The cytotoxic effect of inhibitors (chloroquine 20 μM, mefloquine 10 μM) was analysed for PDX-derived spheroids and NHA after 72 h treatment in normoxia and hypoxia. Representative images of treated spheroids are presented (‘green’=viable, ‘red’=dead). (F) Quantification of cell death upon treatment displayed as % of dead cells/volume (n⩾5, *P<0.05, **P<0.01, ***P<0.001). (G) Sensitivity of GBM cultures to chloroquine and mefloquine 72 h after treatment. Concentration gradients were used to determine the median inhibitory concentration (IC50). IC50 are expressed as mean±s.e.m. (n⩾3, *P<0.05, **P<0.01, ***P<0.001).
Figure 2
Figure 2
Hypoxia activates autophagy in GBM cells. (A) DEG lists between hypoxia 12 h vs normoxia and hypoxia 7 days vs normoxia (FDR<0.01; any FC, n=3–6) were subjected to IPA. Autophagy-associated genes (Moussay et al, 2011) were significantly altered (threshold: −log(P value) >1.3). (B) Upstream Regulator analysis (IPA) predicted activation of HIF1α and FOXO3 network upon hypoxia (threshold: z-score >2 and P value of overlap <0.05; *P<0.05 **P<0.01, ***P<0.001). (C) Western blot analysis showing LC3-I/II. Increase of autophagy in hypoxia is visualised by increased LC3-II (lower band)/LC3-I (upper band) ratio in the presence of chloroquine (mean±s.e.m., n=3; *P<0.05, **P<0.01, ***P<0.001). Representative images were cropped from the same blot (CQ=chloroquine, N=normoxia, H: 0.1–0.5% O2 48 h hypoxia). (D) Western blot analysis showing p62 degradation upon hypoxia (mean normalised to total protein content±s.e.m., n=3; **P<0.01). Representative images were cropped from the same blots. Control cells (normoxia, no chloroquine) were used as an internal calibration (value=‘1’). (E) Representative images show an increase in autophagosome formation upon hypoxia. Cells were exposed to hypoxia for 16 h in the presence of chloroquine. Autophagosomes were counted as LC3B–GFP-positive vacuoles 24 h after transfection; (mean±s.e.m.; n=34; *P<0.05, **P<0.01).
Figure 3
Figure 3
ATG9A is specifically activated upon autophagic response to hypoxia. (A) Genes directly related to autophagy (knowledge-driven selection) were extracted from DEG lists between hypoxia 12 h vs normoxia and hypoxia 7 days vs normoxia (FDR<0.01; any FC) for each culture (n=3–6). Venn diagrams reveal commonly deregulated genes. (B) Heatmap shows expression levels for selected genes in NCH421k in normoxia, 12 h and 7 days hypoxia. See Supplementary Table S3 for more autophagy-related genes. (C) QPCR confirmed increased ATG9A expression in hypoxia. EZRIN was used as a reference (mean±s.e.m.; n=3; *P<0.05, **P<0.01, ***P<0.001). NCH421k cells were used as an internal calibration (value=‘1’).
Figure 4
Figure 4
ATG9A knockdown decreases GBM cell proliferation and increases mouse survival. (A) QPCR confirmation of shATG9A knockdown (mean±s.e.m.; n=3; *P<0.05). (B) Proliferation of shATG9A cells was decreased significantly in normoxic and hypoxic conditions (mean±s.e.m.; n=3; *P<0.05, **P<0.01, ***P<0.001). (C) Representative images show lack of increased autophagosome formation upon hypoxia in shATG9 U87 cells. Cells were exposed to hypoxia for 16 h in the presence of chloroquine. Autophagosomes were counted as LC3B–Tomato-positive vacuoles 24 h after transfection; GFP positivity confirms shRNA expression (mean±s.e.m.; n=34; ***P value <0.001). (D) ATG9A depletion in NCH421k and NCH644 prolonged the survival of tumour-bearing mice (n=6–8). (E) Targeted in vivo shRNA screen in NCH421k cells. shRNA targeting ATG9A but not BNIP3L was depleted after in vivo (n=5) and in vitro (normoxia, n=3) growth. Relative representation of respective shRNAs after selection pressure is presented as ratios compared with the original shRNA pool before selection (baseline). For detailed experimental setup, see (Sanzey et al, 2015).

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