Yang Lijing, Ma Xiaojuan, Yang Decao, Song Jiagui, Yang Jianling, Sun Yan, Wang Yan, Xue Lixiang
Institute of Medical Innovation and Research, Peking University Third Hospital; Cancer Center of Peking University Third Hospital.
Institute of Medical Innovation and Research, Peking University Third Hospital; Cancer Center of Peking University Third Hospital;
J Vis Exp. 2025 Sep 5(223). doi: 10.3791/68833.
Brain tumors, especially gliomas, are challenging to treat because of their aggressive nature, complex tumor microenvironment, and resistance to conventional therapies. Traditional two-dimensional (2D) cell cultures often fail to replicate the true tumor environment, leading to inaccurate predictions of drug efficacy. Extracellular flux analysis technology, typically used for real-time metabolic analysis in 2D cultures, measures key metabolic parameters, such as the extracellular acidification rate (ECAR) and oxygen consumption rate (OCR), providing insights into cellular metabolism. The use of 3D models represents a significant advancement, as they more accurately mimic the in vivo tumor environment. The extracellular flux analyzer was adapted to three-dimensional (3D) glioma cell models, enabling the analysis of critical metabolic pathways, including glycolysis and oxidative phosphorylation, in a more physiologically relevant context. U87 cells were seeded at appropriate densities in a 96-well low-attachment plate and cultured for 5 days. On day 5, 3D spheroid formation was observed via high-content imaging. The successfully formed spheroids were then transferred to a metabolic assay plate coated with poly-L-lysine for metabolic analysis. To improve the accuracy of these measurements, high-content imaging systems assess 3D cell size, allowing for precise normalization of extracellular flux data and minimizing metabolic variations due to differences in cell size. This integrated approach provides a more reliable analysis of glioma cell metabolic responses to drug treatments, revealing potential mechanisms of drug resistance. Ultimately, this methodology offers valuable insights into the metabolic dynamics of gliomas and supports the development of novel, clinically relevant therapeutic strategies.
脑肿瘤，尤其是神经胶质瘤，因其侵袭性、复杂的肿瘤微环境以及对传统疗法的耐药性而难以治疗。传统的二维（2D）细胞培养常常无法复制真实的肿瘤环境，导致对药物疗效的预测不准确。细胞外流量分析技术通常用于二维培养中的实时代谢分析，可测量关键的代谢参数，如细胞外酸化率（ECAR）和耗氧率（OCR），从而深入了解细胞代谢。三维（3D）模型的使用代表了一项重大进展，因为它们能更准确地模拟体内肿瘤环境。细胞外流量分析仪适用于三维（3D）神经胶质瘤细胞模型，能够在更符合生理情况的背景下分析关键的代谢途径，包括糖酵解和氧化磷酸化。将U87细胞以适当密度接种于96孔低吸附板中并培养5天。在第5天，通过高内涵成像观察到三维球体形成。然后将成功形成的球体转移至涂有聚-L-赖氨酸的代谢分析板进行代谢分析。为提高这些测量的准确性，高内涵成像系统会评估三维细胞大小，以便对细胞外流量数据进行精确归一化，并将由于细胞大小差异导致的代谢变化降至最低。这种综合方法能更可靠地分析神经胶质瘤细胞对药物治疗的代谢反应，揭示潜在的耐药机制。最终，该方法为神经胶质瘤的代谢动态提供了有价值的见解，并支持开发新的、具有临床相关性的治疗策略。
