Automated tracking of tumor-stroma morphology in microtissues identifies targets within the tumor microenvironment for therapeutic intervention
Oncotarget, Impact Journals, 2015
Link for the paper (and the supplementary materials)
Abstract: Cancer-associated fibroblasts (CAFs) constitute an important part of the tumor microenvironment and promote invasion via paracrine functions and physical impact on the tumor. Although the importance of including CAFs into three-dimensional (3D) cell cultures has been acknowledged, computational support for quantitative live-cell measurements of complex cell cultures has been lacking. Here, we have developed a novel automated pipeline to model tumor-stroma interplay, track motility and quantify morphological changes of 3D co-cultures, in real-time live-cell settings. The platform consists of microtissues from prostate cancer cells, combined with CAFs in extracellular matrix that allows biochemical perturbation. Tracking of fibroblast dynamics revealed that CAFs guided the way for tumor cells to invade and increased the growth and invasiveness of tumor organoids. We utilized the platform to determine the efficacy of inhibitors in prostate cancer and the associated tumor microenvironment as a functional unit. Interestingly, certain inhibitors selectively disrupted tumor-CAF interactions, e.g. focal adhesion kinase inhibitors specifically blocked tumor growth and invasion concurrently with fibroblast spreading and motility. This complex phenotype was not detected in other standard in vitro models. These results highlight the advantage of our approach, which recapitulates tumor histology and can significantly improve the cancer target validation in vitro.
Incucyte FLR real-time live-cell imaging of LNCaP organoids (phase contrast) and PF179T CAFs (green) co-cultured for 14 days in Matrigel, Matrigel/collagen mixture and collagen. Scale bar: 200 μm. B. Fibroblast morphology and dynamics was analyzed from the time-lapse images in an automated fashion. CAF cohort segmentation was performed by local adaptive thresholding and example images of segmented CAFs in three matrices are described. C. Schematic drawing depicts how branching of each CAF cohort was assessed by extracting the closed contour and detecting the convex hull of the contour as well as contour convexity defects. D. Quantification of fibroblast growth rate (area), motion per frame, number of extensions per cluster and extension size per cluster, is shown over time. Every dot represents a value per each time frame of the image sequence. Segmented real-time live-cell image sequences from three different ECMs were used for quantification. Col: collagen, Mtg/col: Matrigel/collagen 1:1 mixture, Mtg: Matrigel.