With no available targeted therapies, basal-like breast cancers are particularly aggressive cancers with a poor prognosis. Basal-like breast cancers have unique stromal-epithelial interactions within their microenvironments. The availability of quantitative 3D tissue culture assays to measure the response of basal-like cell line models in their microenvironments may lead to new treatment options in this disease. In particular, mesenchymal cell motility is a necessary precursor to the migration and metastasis of cancer, but there is a lack of quantitative and high-throughput methods for studying motility in tissue cultures. We will employ Optical Coherence Tomography (OCT) to perform high frame rate, non-invasive, volumetric imaging to quantify motility and morphogenesis of mammary organoid tissue cultures. Our long-term hypothesis is that the spatial pattern and frequency-dependence of mammary organoid motility obtained by OCT is correlated with metastatic potential, and that the motility phenotype in 3D culture is an in vivo relevant metric for screening therapeutic agents. Our first specific aim will be to identify motility phenotypes associated with morphogenesis and malignancy. This will be performed using high frame rate OCT to monitor fluctuations in the 0.002 - 100 Hz band arising from the motility of mammary epithelial cells (MECs) in co-culture with fibroblasts. We will quantify the motilities of basal-like epithelial cel types, comparing normal to pre-malignant to invasive basal-like cancer cells, as a function of fibroblast density in 3D co-culture. Hyperspectral (motility spectrum plus space) imaging data will be visualized with advanced techniques to display multiple scalar fields on surfaces and in volumes. These motility data will be used in conjunction with gene expression profiles to identify motility-based phenotypes of breast cancer malignancy. Our second specific aim will be to quantify the inhibition of motility in basal MECs when exposed to anti- cancer treatments. We hypothesize that stromal fibroblasts promote basal-like cancer cell motility via hepatocyte growth factor (HGF) signaling through the c-Met receptor. Employing the panel of motility phenotypes identified in Aim 1, we will study the response of basal-like MECs to anti-HGF or other c-Met inhibitors. Importantly, ultrahigh resolution OCT may be capable of resolving the heterogeneous response of cells within MEC organoids, identifying motile cells that do not respond to treatment. At the conclusion of this proposal we will have (1) developed a quantitative and automated tool for measuring motility of breast cells in 3D tissue cultures, (2) identified cancer-relevant motility phenotypes, and (3) applied these tools to predict the efficacy of a potential treatment for basal-like breast cancer. This will constitute a new tool for high throughput micro-assays for pre-clinical testing, providing quantitative targets for treatment development, and new fundamental insight into the tumor microenvironment.
Cancer cells must exhibit motility before they can metastasize, and thus motility may be a good metric for predicting whether drugs can suppress cancer progression. We propose to develop a system for rapidly measuring cell motility in tissue cultures, which may be useful for drug screening and for revealing cell signaling in the tumor microenvironment. We propose to apply this system to study a potential treatment for basal-like breast cancers, which are triple negative and currently have few treatment options.
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