Intratumoral heterogeneity of oxygen metabolism and neovascularization uncovers 2 survival-relevant subgroups of IDH1 wild-type glioblastoma - Stadlbauer, Andreas; Zimmermann, Max; Dörfler, Arnd; Oberndorfer, Stefan; Buchfelder, Michael; Coras, Roland; Kitzwoegerer, Melitta; Roessler, Karl (Neuro-Oncology, 2018)
Background: The intratumoral heterogeneity of oxygen metabolism in combination with variable patterns of neovascularization (NV) as well as reprogramming of energy metabolism affects the landscape of tumor microenvironments (TMEs) in glioblastoma. Knowledge of the hypoxic and perivascular niches within the TME is essential for understanding treatment failure. Methods: Fifty-two patients with untreated glioblastoma (isocitrate dehydrogenase 1 wild type [IDH1wt]) were examined with a physiological MRI protocol including a multiparametric quantitative blood oxygen level dependent (qBOLD) approach and vascular architecture mapping (VAM). Imaging biomarker information about oxygen metabolism (mitochondrial oxygen tension) and neovascularization (microvascular density and type) were fused for classification of 6 different TMEs: necrosis, hypoxia with/without neovascularization, oxidative phosphorylation (OxPhos), and glycolysis with/without neovascularization. Association of the different TME volume fractions with progression-free survival (PFS) was assessed using Kaplan-Meier analysis and Cox proportional hazards models. Results: A common spatial structure of TMEs was detected: central necrosis surrounded by tumor hypoxia (with defective and functional neovasculature) and different TMEs with a predominance of OxPhos and glycolysis for energy production, respectively. The percentage of the different TMEs on the total tumor volume uncovered 2 clearly different subtypes of glioblastoma IDH1wt: a glycolytic dominated phenotype with predominantly functional neovasculature and a necrotic/hypoxic dominated phenotype with approximately 50% of defective neovasculature. Patients with a necrotic/hypoxic dominated phenotype showed significantly shorter PFS (P = 0.035). Conclusions: Our non-invasive mapping approach allows for classification of the TME and detection of tumor-supportive niches in glioblastoma which may be helpful for both clinical patient management and research.
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