Exploring the Spatially Dependent Proteome of Ovarian Cancer Tissue

Abstract

Ovarian cancer is a formidable disease often associated with a poor prognosis due to its acquired drug resistance, lack of early detection methods, and high mortality rate. There remains an urgent need to develop new approaches for early diagnosis of ovarian cancer and strategies for reversing drug resistance. We hypothesize that ovarian cancer cells interact with host cells in the tumor microenvironment in a poorly understood mechanism resulting in drug resistance. The tumor microenvironment is very complex, consisting of multiple cell types. In addition, the tissue cells continuously communicate with one another through the secretion and uptake of extracellular vesicles. Recently, we developed a new generation of Laser Capture Microdissection (LCM) to interrogate the tumor microenvironment by isolating specific cells from a heterogeneous tissue section and separating them into distinct homogeneous samples. We used this technology coupled with mass spectrometry (MS) to compare the proteome of extracellular vesicles to the tumor cells subpopulations. In order to explore the function of the differential expressed proteins, we utilized a cell culture model of human ovarian cancer cells as they adapted to cisplatin treatment. Finally, we investigated the spatially dependent relationship between cisplatin therapy and p53 expression. With our newly developed methods in tissue molecular profiling, we were able to highlight the importance of p53 intracellularly and in the interstitial space.