Evaluation of Consistency in Spheroid Invasion Assays.

Multicellular tumor spheroids embedded in a matrix represent invaluable tools to analyze cell invasion. Spheroid sizes and invasiveness are the main observables easily measurable to evaluate effects of biological or pharmaceutical manipulations on invasion. They largely account for these 3-D platforms variability, leading to flaws in data interpretation. No method has been established yet that characterizes this variability and guarantees a reliable use of 3-D platforms. Spheroid initial/end sizes and invasiveness were systematically analyzed and compared in spheroids of U87MG cells generated by three different methods and embedded at different times in a collagen matrix. A normality test was used to characterize size distribution. We introduced the linearity-over-yield analysis as a novel mathematical tool to assess end sizes and invasion reproducibility. We further provide a proof of concept by applying these tools to the analysis of a treatment known to be effective beforehand. We demonstrate that implementation of these statistical and mathematical tools warranted a confident quantification and interpretation of in 3-D conducted assays. We propose these tools could be incorporated in a guideline for generation and use of 3-D platforms.

A Novel Computer-Assisted Approach to evaluate Multicellular Tumor Spheroid Invasion Assay.

Multicellular tumor spheroids (MCTSs) embedded in a matrix are re-emerging as a powerful alternative to monolayer-based cultures. The primary information gained from a three-dimensional model is the invasiveness of treatment-exposed MCTSs through the acquisition of light microscopy images. The amount and complexity of the acquired data and the bias arisen by their manual analysis are disadvantages calling for an automated, high-throughput analysis. We present a universal algorithm we developed with the scope of being robust enough to handle images of various qualities and various invasion profiles. The novelty and strength of our algorithm lie in: the introduction of a multi-step segmentation flow, where each step is optimized for each specific MCTS area (core, halo, and periphery); the quantification through the density of the two-dimensional representation of a three-dimensional object. This latter offers a fine-granular differentiation of invasive profiles, facilitating a quantification independent of cell lines and experimental setups. Progression of density from the core towards the edges influences the resulting density map thus providing a measure no longer dependent on the sole area size of MCTS, but also on its invasiveness. In sum, we propose a new method in which the concept of quantification of MCTS invasion is completely re-thought.