Ovarian cancer is most often diagnosed when the disease has already metastasized, while lesions are still below the resolution of conventional imaging modalities. Alterations of the collagen architecture in the extracellular matrix (ECM) have been observed in ovarian cancer and are thought to be a critical step in the initiation and progression of many epithelial carcinomas and we suggest these changes are potential quantitative biomarkers. To study this possibility, we will develop 3D models of the stroma in ovarian cancer to study the role of collagen alterations in disease development and progression. These models will be derived from Second Harmonic Generation (SHG) images of the collagen architecture and fabricated through multiphoton excited (MPE) photochemistry. This fabrication method affords the creation of sub-micron fibers directly from collagen with high fidelity, where the resulting structures are both biocompatible and biomimetic. We have shown that SHG can differentiate ovarian cancer subtypes which represent different diseases with different etiologies. We therefore hypothesize that SHG imaging provides the context to understand the biological relevance of collagen remodeling in the ovarian tumor microenvironment (TME) and thereby inform the creation of biomimetic models to relate collagen alterations and tumor growth. Cancer cell migration and proliferation and gene expression will be studied both in in vitro and in vivo by seeding the scaffolds representing normal and ovarian tumors with cancer cells representing different disease and will decouple the respective roles of cell phenotype and collagen alterations. Intravital imaging will further these studies by correlating tumor growth and collagen alterations with changes in metabolism. We hypothesize these studies will lead to better diagnostics and superior therapies. To achieve these goals we will advance both the SHG imaging and MPE fabrication technologies, where each will inform the other and lead to better insight into ovarian cancer. We propose the following Aims:
Aim 1. Develop refined models of ovarian tumors based on SHG image data.
Aim 2. Use the models in vitro and in vivo to understand cancer cell-stromal interactions.
Aim 3. Develop in vivo SHG imaging system with complete ex vivo capabilities.
Ovarian cancer has poor 5 year survival rates. The development of image-based 3-dimensional scaffolds will enable hypothesis testing of the role of specific cellular and molecular components in ovarian cancer. These new insights may lead to new treatments and better diagnostics for this disease.
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