Invasive epithelial ovarian cancer (EOC) diagnosed at an advanced stage (III/IV) is characterized by 5-year survival rates of only ~30%. In contrast, EOCs detected at stage I have survival rates of over 90%, and are often cured by surgical intervention. Currently, most EOCs are diagnosed at the later stages and, as a result, ovarian cancer is the most lethal gynecological malignancy in Western societies, despite being only the 5th most common. Detecting EOCs earlier would be a realistic way to reduce mortality and improve survival rates for this disease. However, no biomarker currently exists that is sensitive or specific enough to be used as a screening biomarker to detect early-stage EOC in at risk populations. This proposed project aims to identify biomarkers that are derived from the stroma of EOCs that could be used in to detect early- stage EOCs and in doing so, improve survival rates for invasive ovarian cancer. A solid tumor can be considered to function in a manner analogous to all organs in the body, in that the epithelial cells are just one cell population existing and communicating within a heterogeneous mix of stromal cells and extracellular matrix. Up to 70% of an ovarian cancer is stroma. The tumor stroma is dynamic, co- evolving with tumor to support all stages of carcinogenesis, and is vital for maintaining homeostasis of the tumor. For EOC, the development of the tumor stroma is poorly understood, but it appears that both normal ovarian fibroblasts and mesenchymal stem cells have the capacity to develop into cancer-associated fibroblasts (CAFs). Genomic aberrations are rarely detected in ovarian CAFs, suggesting regulatory elements may have a role in the differentiation of CAFs. This proposed project aims to profile changes in the expression of a class of regulatory RNAs, long non-coding RNAs (lncRNAs), which occur during CAF development. LncRNAs have recently been shown to have a role in differentiation processes that are analogous to the development of CAFs from CAF precursor cells. Moreover, lncRNAs are now known to be major mechanistic drivers underlying deregulation of pathways commonly aberrated in cancer (e.g. p53 signaling). In this study, lncRNAs differentially expressed in ovarian CAFs compared to CAF precursors will be identified, and downstream lncRNA-target genes profiled. A list of candidate biomarkers for detection of EOC will be created from these data;the biomarkers may either be the lncRNAs or the protein-coding genes regulated at the transcript level by these lncRNAs. Using an existing in vivo heterotypic model of EOC, the biomarkers will be evaluated by testing their abundance in the blood of a mammalian model using PCR or ELISA-based assays. The next stage of this research will be to test the best performing biomarkers in patient sera samples taken preceding a diagnosis of invasive EOC.
Compared to many other cancers, survival rates for invasive ovarian cancer have shown little improvement over the last four decades. Detecting ovarian cancers prior to spread of disease throughout the abdominal cavity is a feasible way to improve survival rates;unfortunately no biomarker currently exists which can effectively detect early-stage ovarian tumors. We propose identifying and validating novel biomarkers from the tumor support network, the tumor stroma, as an innovative approach to early detection of ovarian carcinoma.