Abstract
Multicellular tumor spheroids (MCTSs) can serve as in vitro models for solid tumors and have become widely used in basic cancer research and drug screening applications. The major challenges when studying MCTSs by optical microscopy are imaging and analysis due to light scattering within the 3-dimensional structure. Herein, we used an ultrasound-based MCTS culture platform, where A498 renal carcinoma MCTSs were cultured, DAPI stained, optically cleared and imaged, to connect nuclear segmentation to biological information at the single cell level. We show that DNA-content analysis can be used to classify the cell cycle state as a function of position within the MCTSs. We also used nuclear volumetric characterization to show that cells were more densely organized and perpendicularly aligned to the MCTS radius in MCTSs cultured for 96 h compared to 24 h. The method presented herein can in principle be used with any stochiometric DNA staining protocol and nuclear segmentation strategy. Since it is based on a single counter stain a large part of the fluorescence spectrum is free for other probes, allowing measurements that correlate cell cycle state and nuclear organization with e.g., protein expression or drug distribution within MCTSs.
Highlights
Solid cancer tumors are complex 3-dimensional (3D) environments where multiple cell types embedded in extra-cellular matrix interact through direct cell–cell contact or soluble factors[1,2]
The methods outlined in this study demonstrate the possibilities for biological and structural single cell resolution data extraction in multicellular tumor spheroids (MCTSs) using a simple clearing and counter-staining protocol, leaving the rest of the fluorescence spectrum free for other fluorescent probes
The ultrasonic standing wave (USW) MCTS culture platform consist of a silicon-glass multiwell chip and a transducer fitted with chip clamping equipment which has previously been described in detail[37,38,39]
Summary
Solid cancer tumors are complex 3-dimensional (3D) environments where multiple cell types embedded in extra-cellular matrix interact through direct cell–cell contact or soluble factors[1,2]. One type of 3D cancer cell culture is multicellular tumor spheroids (MCTSs) which are spherical aggregates of one or several cell types They are appreciated for combining the advantages of regular 2D culture (robustness and reproducibility) while introducing important 3D physiological aspects of solid tumors such as gas- and nutrient g radients[5]. While nuclear segmentation is an appealing target for image analysis due to ease-of-labeling and simple geometrical structure, the segmentation methods require the ability to resolve and handle tightly packed nuclei due to the high cell density in MCTSs. There are several commercial and freely available 3D nuclear segmentation software tools that are either based on machine learning or more classical methods[24]. Other notable approaches include line-of-sight d ecomposition[30] and gradient flow t racking[31]
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