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. 2020 Sep 2;9(9):264.
doi: 10.3390/biology9090264.

An Experimentally Defined Hypoxia Gene Signature in Glioblastoma and Its Modulation by Metformin

Marta Calvo Tardón  1 , Eliana Marinari  1 , Denis Migliorini  2 , Viviane Bes  1 , Stoyan Tankov  1 , Emily Charrier  1 , Thomas A McKee  3 , Valérie Dutoit  1 , Pierre-Yves Dietrich  1 , Erika Cosset  1 , Paul R Walker  1
Affiliations

An Experimentally Defined Hypoxia Gene Signature in Glioblastoma and Its Modulation by Metformin

Marta Calvo Tardón et al. Biology (Basel). .

Abstract

Glioblastoma multiforme (GBM) is the most common and aggressive primary brain tumor, characterized by a high degree of intertumoral heterogeneity. However, a common feature of the GBM microenvironment is hypoxia, which can promote radio- and chemotherapy resistance, immunosuppression, angiogenesis, and stemness. We experimentally defined common GBM adaptations to physiologically relevant oxygen gradients, and we assessed their modulation by the metabolic drug metformin. We directly exposed human GBM cell lines to hypoxia (1% O2) and to physioxia (5% O2). We then performed transcriptional profiling and compared our in vitro findings to predicted hypoxic areas in vivo using in silico analyses. We observed a heterogenous hypoxia response, but also a common gene signature that was induced by a physiologically relevant change in oxygenation from 5% O2 to 1% O2. In silico analyses showed that this hypoxia signature was highly correlated with a perinecrotic localization in GBM tumors, expression of certain glycolytic and immune-related genes, and poor prognosis of GBM patients. Metformin treatment of GBM cell lines under hypoxia and physioxia reduced viable cell number, oxygen consumption rate, and partially reversed the hypoxia gene signature, supporting further exploration of targeting tumor metabolism as a treatment component for hypoxic GBM.

Keywords: glioblastoma; glioblastoma microenvironment; hypoxia; hypoxia gene signature; metformin; physioxia.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

Figure 1
Figure 1
Whole transcriptome analysis of Ge835, Ge898, Ge904, LN18, and LN229 glioblastoma multiforme (GBM) cell lines cultured under hypoxia (1% O2), physioxia (5% O2), or hyperoxia (21% O2) for 48 h. (a) Gene set enrichment analysis for hypoxia geneset comparing transcriptional profiles of hypoxia versus physioxia; (b) Venn diagram of comparisons between hypoxia and physioxia, and hypoxia and hyperoxia; (c) Enrichment scores of gene families from DAVID analysis.
Figure 2
Figure 2
Expression and correlation of the hypoxia gene signature using the Ivy-GAP database. (a) Expression of the hypoxia gene signature in different areas of human GBM (n = 270) biopsies; (b,c) Correlation matrix of the hypoxia signature with (b) immune-related genes or (c) three metabolic pathways gene lists. List of immune-related genes (from left to right and top to bottom): ARG2, ARG1, TGFB1, IDO1, IL10, CD163, MRC1, CCR4, CCR7, CD80, CD3G, CD3D, CD3E, GZMB, PRF1, CD86, IL1A, IL6, IL1B, IL8, CCL20, TNF, IFNG, IL2, ICAM1, ITGAL, ITGA4, ITGB2.
Figure 3
Figure 3
Correlation of the hypoxia signature with survival of high-grade glioma patients. (a) Expression of the hypoxia gene signature (z-score) across patients from TCGA database (n = 528), segregated by high and low expression of the signature; (b–e) Kaplan–Meier survival curves corresponding with high (red) or low (black) expression of the hypoxia signature in (b) TCGA (n = 528), (c) Rembrandt (n = 267), (d) Phillips (n = 100), and (e) Freije (n = 85) databases.
Figure 4
Figure 4
Functional assays of human and mouse GBM cell lines exposed to metformin. (a) Effect of 10 mM metformin on viable cell number under physioxia; (b) Table indicating TP53 mutation status of all GBM cell lines used; mutant or wild type (WT); (c) Basal oxygen consumption rate (OCR) and (d) basal extracellular acidification rate (ECAR) of Ge835 and Ge904 GBM cell lines in vitro at 21%, 5%, and 1% O2, with the indicated concentrations of metformin (mean of 3 independent experiments +/- SD; 2-way ANOVA, Sidak’s adjusted p-value. ** p < 0.01, *** p < 0.001, **** p < 0.0001).
Figure 5
Figure 5
Metformin modulation of the upregulated genes of our hypoxia gene signature. Heat map represents fold-changes of expression between metformin-treated (10 mM, 48 h) versus vehicle-treated cells (red, FC > 2; blue, FC < 0.5). mRNA expression measured by qPCR of upregulated genes from the hypoxia gene signature on Ge835, LN18, and Ge904 treated with metformin or vehicle and exposed to physioxia or hypoxia. Fold change values are tabulated in Table S2.
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References

    1. Louis D.N., Perry A., Reifenberger G., von Deimling A., Figarella-Branger D., Cavenee W.K., Ohgaki H., Wiestler O.D., Kleihues P., Ellison D.W. The 2016 World Health Organization Classification of Tumors of the Central Nervous System: A summary. Acta Neuropathol. 2016;131:803–820. doi: 10.1007/s00401-016-1545-1. - DOI - PubMed
    1. Wen P.Y., Kesari S. Malignant gliomas in adults. N. Engl. J. Med. 2008;359:492–507. doi: 10.1056/NEJMra0708126. - DOI - PubMed
    1. Stupp R., Mason W.P., van den Bent M.J., Weller M., Fisher B., Taphoorn M.J., Belanger K., Brandes A.A., Marosi C., Bogdahn U., et al. Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N. Engl. J. Med. 2005;352:987–996. doi: 10.1056/NEJMoa043330. - DOI - PubMed
    1. Verhaak R.G., Hoadley K.A., Purdom E., Wang V., Qi Y., Wilkerson M.D., Miller C.R., Ding L., Golub T., Mesirov J.P., et al. Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1. Cancer Cell. 2010;17:98–110. doi: 10.1016/j.ccr.2009.12.020. - DOI - PMC - PubMed
    1. Phillips H.S., Kharbanda S., Chen R., Forrest W.F., Soriano R.H., Wu T.D., Misra A., Nigro J.M., Colman H., Soroceanu L., et al. Molecular subclasses of high-grade glioma predict prognosis, delineate a pattern of disease progression, and resemble stages in neurogenesis. Cancer Cell. 2006;9:157–173. doi: 10.1016/j.ccr.2006.02.019. - DOI - PubMed

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