Quantitative Assessment of Anti-Cancer Drug Efficacy From Coregistered Mass Spectrometry and Fluorescence Microscopy Images of Multicellular Tumor Spheroids
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Year of publication | 2019 |
Type | Article in Periodical |
Magazine / Source | Microscopy and Microanalysis |
MU Faculty or unit | |
Citation | |
Web | http://dx.doi.org/10.1017/S1431927619014983 |
Doi | http://dx.doi.org/10.1017/S1431927619014983 |
Keywords | confocal microscopy; image registration; MALDI MS; mass spectrometry imaging; peeling |
Description | Spheroids—three-dimensional aggregates of cells grown from a cancer cell line—represent a model of living tissue for chemotherapy inves- tigation. 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. |
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