High-Resolution Imaging of Tumor Spheroids and Organoids Enabled by Expansion Microscopy

Three-dimensional cell cultures are able to better mimic the physiology and cellular environments found in tissuesin vivocompared to cells grown in two dimensions. In order to study the structure and function of cells in 3-D cultures, light microscopy is frequently used. The preparation of 3-D cell...

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Veröffentlicht in:FRONTIERS IN MOLECULAR BIOSCIENCES 2020-09, Vol.7, p.208-208
Hauptverfasser: Edwards, Steven J., Carannante, Valentina, Kuhnigk, Kyra, Ring, Henrik, Tararuk, Tatsiana, Hallböök, Finn, Blom, Hans, Önfelt, Björn, Brismar, Hjalmar
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Sprache:eng
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Zusammenfassung:Three-dimensional cell cultures are able to better mimic the physiology and cellular environments found in tissuesin vivocompared to cells grown in two dimensions. In order to study the structure and function of cells in 3-D cultures, light microscopy is frequently used. The preparation of 3-D cell cultures for light microscopy is often destructive, including physical sectioning of the samples, which can result in the loss of 3-D information. In order to probe the structure of 3-D cell cultures at high resolution, we have explored the use of expansion microscopy and compared it to a simple immersion clearing protocol. We provide a practical method for the study of spheroids, organoids and tumor-infiltrating immune cells at high resolution without the loss of spatial organization. Expanded samples are highly transparent, enabling high-resolution imaging over extended volumes by significantly reducing light scatter and absorption. In addition, the hydrogel-like nature of expanded samples enables homogenous antibody labeling of dense epitopes throughout the sample volume. The improved labeling and image quality achieved in expanded samples revealed details in the center of the organoid which were previously only observable following serial sectioning. In comparison to chemically cleared spheroids, the improved signal-to-background ratio of expanded samples greatly improved subsequent methods for image segmentation and analysis.
ISSN:2296-889X
2296-889X
DOI:10.3389/fmolb.2020.00208