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.

中文翻译：

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从多细胞肿瘤球体的配准质谱和荧光显微图像定量评估抗癌药物疗效

球体——从癌细胞系中生长出来的细胞的三维聚集体——代表了一种用于化疗研究的活组织模型。使用基质辅助激光解吸/电离质谱成像 (MALDI MSI) 确定球体切片中化疗药物的分布。通过激光扫描共聚焦荧光显微镜（LSCM）对增殖或凋亡细胞进行免疫组织化学标记和可视化。通过比较药物处理球体的共同注册的 MALDI MSI 和 LSCM 数据与未经处理的对照球体的仅 LSCM 数据来评估药物疗效。我们开发了一种基于基准的工作流程，用于将低分辨率 MALDI MS 与高分辨率 LSCM 图像进行配准。为了比较药物处理和未处理的不同形状或直径的球体之间的药物和细胞分布，我们引入了一个常见的与扩散相关的坐标，即到球体边界的距离。在称为“剥离”的过程中，我们将一定距离处的平均药物分布与未处理球体和处理球体之间受影响细胞的平均减少相关联。这种新方法可以区分因治疗而死亡的外周细胞和自然死亡的最内层细胞。还介绍了两种新的算法——用于 MALDI MS 图像去噪和通过细胞核的存在对 MALDI MSI 和 LSCM 数据进行加权。我们将一定距离的平均药物分布与未处理球体和处理球体之间受影响细胞的平均减少相关联。这种新方法可以区分因治疗而死亡的外周细胞和自然死亡的最内层细胞。还介绍了两种新的算法——用于 MALDI MS 图像去噪和通过细胞核的存在对 MALDI MSI 和 LSCM 数据进行加权。我们将一定距离的平均药物分布与未处理球体和处理球体之间受影响细胞的平均减少相关联。这种新方法可以区分因治疗而死亡的外周细胞和自然死亡的最内层细胞。还介绍了两种新的算法——用于 MALDI MS 图像去噪和通过细胞核的存在对 MALDI MSI 和 LSCM 数据进行加权。