Human cancers, including serous ovarian cancer, are not a single disease but instead are a heterogeneous collection of diseases with distinct molecular mechanisms and clinical characteristics. While substantial progress has been made in the development and directed administration of new cancer therapies, most patients with advanced solid tumors will succumb to their disease. This observation is due in part to the molecular heterogeneity of human cancers since a given drug may only be active in that subpopulation of patients whose tumor exhibits dependence on the drug target. In some cases, the mutational status of specific genes has been used as a means to identify patients that are likely to respond to a particular therapy; however, these opportunities are rare and only represent a small fraction of patients. This is especially true in serous ovarian cancer where litte or no progress has been made in the use of targeted therapeutic agents. Therefore the goal of this proposal is to utilize an integrated genomics approach to investigate serous ovarian cancer in order to identify novel drivers of cancer genesis, regulators of oncogenic pathway activity, and to identify genetic interactions to develop novel therapeutic regimens. The proposed studies will use experimentally-derived gene expression signatures to analyze patterns of oncogenic pathway activity in high- grade serous ovarian tumors as a conceptual framework to integrate multiple forms of genomic data. This strategy will identify, and experimentally validate, novel genes amplified in human tumors that function to regulate aspects of oncogenic Ras signaling, cancer phenotypes, and cancer cell line viability. Finally, the proposed strategy provides a means to identify genetic, and pathway, interactions that can identify novel therapeutic targets and serve as a guide to develop rational therapeutic strategies that can match the complexity of the disease in order to enhance response and overcome therapeutic resistance. Candidate: Dr. Michael L. Gatza earned his Ph.D. in cell and molecular biology at Baylor College of Medicine and is currently a postdoctoral fellow in the lab of Dr. Joseph Nevins at Duke University. My scientific career can be characterized as multidisciplinary in training, as my graduate work relied on traditional molecular biology and genetics strategies while my postdoctoral studies have utilized large-scale genomics and computational approaches. My research plan in the current K99/R00 application seeks to integrate these approaches and will provide the basis for an integrative, independent research program. During the NRSA F32 funded period of postdoctoral training, my work focused on the investigation of tumor heterogeneity and resulted in first author publications in PNAS and Breast Cancer Research and contributed to six additional published studies. Two additional first author papers and three collaborative papers are in various stages of peer review. K99/R00 funding would aid in my goal of obtaining a tenure-track faculty position at a major research university, a position which I plan to apply for during the K99 phase of the award, by providing additional, necessary training in biostatistics and genomics, laboratory management, and grant writing. The mentored phase will take place in a rich scientific environment in which to publish additional studies and to further establish experimental and theoretical techniques and skills necessary to establish an independent laboratory. In the K99 phase of the award, I would be able to immediately address questions that have emerged from preliminary findings which will result in one to two substantial papers over the funding period. The mentored phase will enable me to develop additional preliminary data that will be the foundation of studies carried out in the R00 phase and that will be the basis of an R01 application submitted during this period. Environment and Training Plan: Studies will be carried out in the laboratory of Dr. Joseph Nevins at Duke University in the Institute for Genome Sciences and Policy (IGSP). The IGSP is a unique multi-disciplinary institute that brings together biostatisticians, computational biologists, molecular biologists, and physician- scientist to build collaborations and integrate expertise; this is an outstanding environment for the proposed studies and training to occur. The training plan encompasses four key components and will be overseen by a five member post-doc advisory committee comprised of Drs. Joseph Lucas, Bernard Mathey-Prevot, Jen-Tsan Chi, Andrew Berchuck, and Joseph Nevins who are experts in biostatistics, multi-dimensional data analysis, functional cancer genomics, RNAi and RNAi-based screens, cancer biology, and in the clinical care of ovarian cancer patients. The proposed career development and training plan takes advantages of resources available at Duke and includes didactic coursework in statistics and computational biology; development of theoretical and practical bioinformatics and experimental approaches; seminars in grant writing and laboratory management; practical training in the management of scientific staff through mentoring of undergraduate students; and scientific interactions, both at Duke and abroad, in the form of laboratory meetings, formal seminar series, and by attending and presenting my research at international conferences. Finally, my post- doctoral advisory committee will serve as a valuable resource not only for scientific training but will provide career advice and guidance including insight into how to navigate the inherent challenges I will encounter as I move from a mentored position to an independent investigator.
The research described in this proposal will provide a rational framework for the integration of multiple forms of genome-level data in order to investigate the complexity and heterogeneity of serous ovarian cancer with the potential to identify novel therapeutic strategies. It is expected that these studies will result in a more complete understanding of oncogenic pathway regulation and the identification of drivers of pathway activity in serous ovarian cancer. Gaining a more complete understanding of these mechanisms will ultimately aid in the development of rational therapeutic strategies that can match the complexity of the disease and result in improved therapeutic response.
