Automated quantitative image analysis for ex vivo metastasis assays reveals differing lung composition requirements for metastasis suppression by KISS1

Eric D. Young, Kyle Strom, Ashley F. Tsue, Joseph L. Usset, Seth MacPherson, John T. McGuire, Danny R. Welch

Imaging is broadly used in biomedical research, but signal variation complicates automated analysis. Using the Pulmonary Metastasis Assay (PuMA) to study metastatic colonization by the metastasis suppressor KISS1, we cultured GFP-expressing melanoma cells in living mouse lung ex vivo for 3 weeks. Epifluorescence images of cells were used to measure growth, creating large datasets which were time consuming and challenging to quantify manually due to scattering of light from outside the focal plane. To address these challenges, we developed an automated workflow to standardize the measurement of disseminated cancer cell growth by applying statistical quality control to remove unanalyzable images followed and a filtering algorithm to quantify only in-focus cells. Using this tool, we demonstrate that expression of the metastasis suppressor KISS1 does not suppress growth of melanoma cells in the PuMA, in contrast to the robust suppression of lung metastasis observed in vivo. This result may suggest that a factor required for metastasis suppression is present in vivo but absent in the PuMA, or that KISS1 suppresses lung metastasis at a step in the metastatic cascade not tested by the PuMA. Together, these data provide a new tool for quantification of metastasis assays and further insight into the mechanism of KISS1 mediated metastasis suppression in the lung.