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Voltage-gated ion channels mediate the electrotaxis of glioblastoma cells in a hybrid PMMA/PDMS microdevice

机译:电压门控离子通道介导混合PMMA / PDMS微型设备中的胶质母细胞瘤细胞的静电

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摘要

Transformed astrocytes in the most aggressive form cause glioblastoma, the most common cancer in the central nervous system with high mortality. The physiological electric field by neuronal local field potentials and tissue polarity may guide the infiltration of glioblastoma cells through the electrotaxis process. However, microenvironments with multiplex gradients are difficult to create. In this work, we have developed a hybrid microfluidic platform to study glioblastoma electrotaxis in controlled microenvironments with high throughput quantitative analysis by machine learning-powered single cell tracking software. By equalizing the hydrostatic pressure difference between inlets and outlets of the microchannel, uniform single cells can be seeded reliably inside the microdevice. The electrotaxis of two glioblastoma models, T98G and U-251MG, requires an optimal laminin-containing extracellular matrix and exhibits opposite directional and electro-alignment tendencies. Calcium signaling is a key contributor in glioblastoma pathophysiology but its role in glioblastoma electrotaxis is still an open question. Anodal T98G electrotaxis and cathodal U-251MG electrotaxis require the presence of extracellular calcium cations. U-251MG electrotaxis is dependent on the P/Q-type voltage-gated calcium channel (VGCC) and T98G is dependent on the R-type VGCC. U-251MG electrotaxis and T98G electrotaxis are also mediated by A-type (rapidly inactivating) voltage-gated potassium channels and acid-sensing sodium channels. The involvement of multiple ion channels suggests that the glioblastoma electrotaxis is complex and patient-specific ion channel expression can be critical to develop personalized therapeutics to fight against cancer metastasis. The hybrid microfluidic design and machine learning-powered single cell analysis provide a simple and flexible platform for quantitative investigation of complicated biological systems.
机译:以最具侵略性的形式转化的星形胶质细胞引起胶质母细胞瘤,它是中枢神经系统中最常见的癌症,死亡率很高。由神经元局部电场电势和组织极性引起的生理电场可通过电出租车过程引导胶质母细胞瘤细胞的浸润。但是,很难创建具有多重梯度的微环境。在这项工作中,我们已经开发了一种混合型微流体平台,通过受控于机器学习的单细胞跟踪软件,可以在受控的微环境中研究胶质母细胞瘤的电轴,并进行高通量定量分析。通过均衡微通道入口和出口之间的静水压力差,可以在微设备内部可靠地播种均匀的单细胞。两种胶质母细胞瘤模型(T98G和U-251MG)的电出租车需要一种最佳的含层粘连蛋白的细胞外基质,并表现出相反的方向和电排列趋势。钙信号传导是胶质母细胞瘤病理生理的关键因素,但其在胶质母细胞瘤电出租车中的作用仍然是一个悬而未决的问题。阳极T98G电动和阴极U-251MG电动需要细胞外钙阳离子的存在。 U-251MG的电动势取决于P / Q型电压门控钙通道(VGCC),而T98G取决于R型VGCC。 U-251MG电动和T98G电动也通过A型(快速失活)电压门控钾通道和酸敏感钠通道介导。多个离子通道的参与表明,胶质母细胞瘤的电趋向性是复杂的,并且患者特异性离子通道的表达对于开发针对癌症转移的个性化疗法可能至关重要。混合微流体设计和机器学习支持的单细胞分析为复杂生物系统的定量研究提供了一个简单而灵活的平台。

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