Abstract

In vitro invasiveness is a fundamental measure of metastatic capacity of cells grown in culture, as the ability of a cell to permeate a semi‐solid matrix is perhaps the best indicator of its potential to invade tissue layers in vivo. However, there are significant drawbacks to current methodologies for studying in vitro invasiveness. Collagen or Matrigel provide physiologically relevant substrates for an invasive barrier, but they are costly, susceptible to batch variance, and require cold storage and minimal handling at room temperature. Transwell membranes and compartmentalized microscope slides are commonly used platforms to measure cell invasion, but these are also costly and labor‐intensive to set up and quantify. An ideal invasiveness assay would be inexpensive, user‐friendly, replicable, and scalable. To this end, we developed a method that uses standard tissue culture plate in which we form a matrix of agarose solution mixed with supplemented culture medium. Wells are made in the gel with a serological pipette, and cells are seeded into the well. The cells permeate the surrounding gel matrix over seven days, at which point the cells are fixed with paraformaldehyde solution. The area of cell invasion into the gel is the measured output of the assay. This can be measured manually, by marking the invasive edge in four cardinal positions, measuring two diameters with a caliper and calculating the invasive area. The quantification can also be automated by staining the gel with cresyl violet, imaging with a standard camera and quantifying the invasive area with a simple Image J code, or by staining the cells with 4′,6‐diamidino‐2‐phenylindole (DAPI) or a similar fluorescent nuclear label and measuring the invasive area with a blot imager. The results correlate with existing methods to quantify invasiveness while being far less labor‐intensive and costly. In summary, this method to quantify cell invasion is simple, reliable, and feasible for any researcher with basic tissue culture supplies. The method also provides quantifiable data that can be collected manually or automated and scaled to fit a wide range of needs.

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