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首页> 外文期刊>Microscopy and microanalysis: The official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada >Quantitative Assessment of Anti-Cancer Drug Efficacy From Coregistered Mass Spectrometry and Fluorescence Microscopy Images of Multicellular Tumor Spheroids
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Quantitative Assessment of Anti-Cancer Drug Efficacy From Coregistered Mass Spectrometry and Fluorescence Microscopy Images of Multicellular Tumor Spheroids

机译:从核心瘤颗粒颗粒质谱和荧光显微镜图像的抗癌药物功效的定量评估

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Spheroids-three-dimensional aggregates of cells grown from a cancer cell line-represent a model of living tissue for chemotherapy investigation. Distribution of chemotherapeutics in spheroid sections was determined using the matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI). Proliferating or apoptotic cells were immunohistochemically labeled and visualized by laser scanning confocal fluorescence microscopy (LSCM). Drug efficacy was evaluated by comparing coregistered MALDI MSI and LSCM data of drug-treated spheroids with LSCM only data of untreated control spheroids. We developed a fiducial-based workflow for coregistration of low-resolution MALDI MS with high-resolution LSCM images. To allow comparison of drug and cell distribution between the drug-treated and untreated spheroids of different shapes or diameters, we introduced a common diffusion-related coordinate, the distance from the spheroid boundary. In a procedure referred to as "peeling", we correlated average drug distribution at a certain distance with the average reduction in the affected cells between the untreated and the treated spheroids. This novel approach makes it possible to differentiate between peripheral cells that died due to therapy and the innermost cells which died naturally. Two novel algorithms-for MALDI MS image denoising and for weighting of MALDI MSI and LSCM data by the presence of cell nuclei-are also presented.
机译:从癌细胞系生长的细胞的三维聚集体 - 代表化疗调查的活组织模型。使用基质辅助激光解吸/电离质谱法(MALDI MSI)测定球形部分中化学治疗剂的分布。通过激光扫描共焦荧光显微镜(LSCM)免疫和化学标记和可视化增殖或凋亡细胞。通过将药物处理的球体的MARDI MSI和LSCM数据与LSCM的数据进行比较,评估药物疗效,仅使用LSCM的未处理对照球体的数据进行评估。我们开发了基于基于基于基于基于基于基于基于基于基于基于基于基于基于基于基于基于基于基于基于基于基于GMADI MS与高分辨率LSCM图像的工作流程。为了允许在药物处理和未处理的不同形状或直径的未经处理的球状体之间的药物和细胞分布比较,我们引入了普通的扩散相关坐标,距离球形边界的距离。在称为“剥离”的过程中,我们在一定距离下与受影响细胞之间的平均降低相关的平均药物分布与未处理的球体之间的平均值相关。这种新的方法使得可以区分因治疗而死亡的周围细胞和自然死亡的最内部细胞。还提出了两种新颖的算法 - 用于MALDI MS图像去噪和用于通过细胞核存在的MALDI MSI和LSCM数据的加权。

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