Ovarian serous cystadenocarcinoma (OvCa) accounts for 90% of ovarian cancers and is most often detected in its later stages, has limited therapies and carries a poor prognosis?the 5-year survival rate for patients with late stage disease is less than 50%. Counterintuitively, OvCa is exquisitely sensitive to initial therapies with most patients achieving a complete clinical response. 80% of patients; however, will eventually relapse with metastases and an acquired tumor chemoresistance. Patients diagnosed with relapsed disease consequently have a tragic average survival of 12 to 18 months. Maintenance regimens to improve the overall survival of recurrent disease show limited success. The Cancer Genome Atlas (TCGA) has sequenced hundreds of primary OvCa tumors to improve our understanding of the disease. Results thus far have been humbling?very few recurrent base pair mutations are observed. Nevertheless, what has been appreciated is a remarkable degree of genomic structural variation. This instability creates a prime environment for the production of fusion genes and OvCa has been shown to harbor more transcript fusions per tumor than most other TCGA-analyzed cancers. Given the inherently unstable OvCa genome and the fact that acquired structural variation has been observed in recurrent OvCa, we hypothesize that fusion genes play a role in the enhanced malignancy observed in relapsed disease. To test this hypothesis, we will analyze massively parallel RNA sequencing (RNA-seq) on patient-matched primary / recurrent tumor pairs. Fusion genes will be detected and prevalence of fusions will be compared between primary and recurrent tumor samples using a customized bioinformatics pipeline. Preliminary work has identified multiple RT-PCR validated, in-frame, relapse-specific fusion transcripts involving known cancer modulators. Additionally, some fusions were found in multiple samples and cell lines suggesting a selection of particular fusion RNA drivers. Next, we will screen for recurrence of discovered fusion genes using a high-throughput NanoString fusion assay. Clinical associations (patient overall survival, therapy responses, etc.) will be made to determine if fusion gene presence, or overexpression of fusion gene partners, are clinically informative biomarkers. Lastly, we will define the biological effects of discovered fusions using in vitro models. Cancer cell lines will be engineered to harbor gene fusions and we will assess for increases in malignant phenotypes such as cellular proliferation, drug sensitivity, and cellular migration / invasion. The ultimate goals of this study will be (1) to increase our understanding of the role fusions genes play in cancer, beyond primary disease and (2) to identify novel therapeutic targets and biomarkers for OvCa , in accordance with the National Cancer Institute (NCI) mission statement.
Ovarian cancer (OvCa) is the deadliest gynecologic cancer (14,000 deaths per year, 5th leading cause of cancer death among women), largely because it is often diagnosed late, there are limited treatment options and even when treatments are initially effective, patients have a high probability for their cancer to both relapse and develop therapy resistance. Although the disease is poorly understood, sequencing studies show that OvCa has an especially unstable genome that frequently causes genes to fuse together. The proposed study will use next-generation sequencing, cutting-edge molecular techniques and ovarian cancer models to define the biological role that fusion genes play in relapsed ovarian cancer, perhaps providing personalized therapy targets and biomarkers that may improve patient outcomes.
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