The survival of women with high-grade epithelial ovarian cancer is directly related to the spread of the tumor. Women with disease limited to the pelvis (early-stage disease) do well with many being cured by surgery only, while those patients whose tumor has spread outside of the pelvis suffer recurrences and the majority will die from the disease. Nevertheless, the standard of care for patients with high-grade ovarian cancer is surgery followed by 6 cycles of chemotherapy (carboplatin/taxol) regardless of the spread of the tumor. Although some early stage patients are benefiting from this strategy, approximately 50-60% of patients with high-grade early stage cancer will not develop recurrent disease even in the absence of chemotherapy. These patients thereby suffered unnecessary short and long-term toxicities of chemotherapy with no benefit. Thus, the development of accurate biomarkers predictive of tumor recurrence becomes essential to identify women with early-stage disease who will benefit from chemotherapy while sparing the rest the unnecessary treatment with quality-of-life and cost-effectiveness ramifications. This approach parallels efforts in breast cancer where tests like “oncotypeDX” or “MammaPrint” provide valuable information on disease recurrence to women with early stage breast cancer. To the best of our knowledge, there is no available large-scale molecular characterization of early-stage ovarian tumors due to the lack of appropriate clinical specimens.
Under a funded DOD project, we have overcome the hindrance of sample paucity and collected 592 early stage ovarian cancer specimens with comprehensive clinical annotation and follow-up. Ongoing studies include profiling of DNA copy number variation and expression of protein coding mRNAs to predict tumor recurrence. Recently, non-protein coding small RNAs (ncRNAs) are emerging as key players in cancer. As a complement to the ongoing DOD project to obtain a comprehensive genomic signature predictive of tumor recurrence in early-stage ovarian tumors, we propose in this study to analyze the expression levels of non-coding small RNAs by microarray based high-throughput technologies in all 592 early stage ovarian cancer specimens. Through comprehensive and rigorous bioinformatic analyses, we expect to develop predictive biomarkers for future prospective stratification of women with early stage ovarian cancer to adjuvant carboplatin/taxol chemotherapy versus careful follow-up. We will also perform integrated analyses of the small ncRNA profile obtained from this study with the profiles of gene expression and copy number variation obtained from the ongoing DOD study. Through this approach, we expect to identify key small ncRNAs with biological significance in regulating the recurrence of early stage ovarian tumor and therefore contribute the identification of therapeutic biomarkers and stratification of early stage ovarian cancer patient most likely to benefit from targeted interventions.
This grant is made possible by a generous donation from Phil and Judy Messing, in memory of Carol S. Messing.
Dr. Wei Wei is a post-doctoral research fellow in the Gillette Center for Women’s Cancer at Massachusetts General Hospital. After obtaining his B.Sc degree in Biological Sciences at Peking University in 2003, he finished his PhD in medical biochemistry at University of Cape Town in 2009. His PhD research focused on the molecular biology of squamous esophageal cancer which is one of the leading causes of cancer-related death in South Africa. Dr. Wei’s current post-doctoral research in the Laboratory of Dr. Michael J Birrer involves high-throughput genomic profiling to identify genomic abnormalities and aberrant gene expression signatures in ovarian cancer. These genomic signatures are then tested for their potential use as biomarkers for early detection or predictors of specific clinical endpoints such as chemotherapeutic response, tumor recurrence, or overall survivor. By using a combination of in vitro cell line models and in vivo orthotopic mouse models, Wei is also investigating the underlying molecular mechanisms of characterized biomarkers to aid the development of personalized targeted therapeutic regimes against ovarian cancer.