Department of Neurosurgery, University of Erlangen-Nürnberg, Erlangen, Germany.
Institute of Medical Radiology, University Clinic of St Pölten, St Pölten, Austria.
Neuro Oncol. 2018 Oct 9;20(11):1536-1546. doi: 10.1093/neuonc/noy066.
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.
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.
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).
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.
肿瘤内氧代谢的异质性，加上新生血管化（NV）的不同模式以及能量代谢的重新编程，影响了脑胶质瘤的肿瘤微环境（TME）景观。了解 TME 中的缺氧和血管周围生态位对于理解治疗失败至关重要。
对 52 例未经治疗的脑胶质瘤（异柠檬酸脱氢酶 1 野生型 [IDH1wt]）患者进行了一项生理 MRI 方案检查，该方案包括多参数定量血氧水平依赖（qBOLD）方法和血管结构测绘（VAM）。氧代谢（线粒体氧张力）和新生血管化（微血管密度和类型）的成像生物标志物信息融合用于对 6 种不同的 TME 进行分类：坏死、缺氧伴/不伴新生血管化、氧化磷酸化（OxPhos）和糖酵解伴/不伴新生血管化。使用 Kaplan-Meier 分析和 Cox 比例风险模型评估不同 TME 体积分数与无进展生存期（PFS）的关联。
检测到 TME 的常见空间结构：中央坏死，周围环绕肿瘤缺氧（伴有功能失调和功能正常的新生血管），以及不同的 TME 分别以 OxPhos 和糖酵解为主，分别用于能量产生。不同 TME 占总肿瘤体积的百分比揭示了脑胶质瘤 IDH1wt 的两种明显不同的亚型：糖酵解占主导的表型，主要为功能性新生血管；坏死/缺氧占主导的表型，约有 50%的新生血管为功能失调。表现为坏死/缺氧为主的患者 PFS 明显较短（P = 0.035）。
我们的非侵入性绘图方法允许对 TME 进行分类，并检测脑胶质瘤中的肿瘤支持生态位，这可能有助于临床患者管理和研究。
