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Research Description
The Institute of Genomic Research is working in collaboration with the H. Lee Moffitt Cancer Research Center and Large Scale Proteomics as part of the Director's Challenge Program at the National Cancer Institute. Our goal is to use the tools and techniques developed through genomics and functional genomics to create molecular fingerprints of human cancers. Our work uses microarray analysis and proteomics to study tumor metastasis with a focus on colon cancer.Cancer is the second leading cause of death in the United States, accounting for nearly one quarter of total human mortality, and colon cancer is second only to lung cancer in mortality and morbidity. Cancer is known to arise from an accumulation of genetic changes within a cell and that knowledge provides hope that we will be able to better understand and treat this dread disease.
The cellular program that directs tumor progression is known to activate a number of specific genes in different tumor types and stages, and many more such genes await discovery. An understanding of those changes that occur during this process could provide an important set of tools for cancer prevention, early detection, diagnosis, and the development of optimal treatment protocols. The ability to produce a molecular expression fingerprint of each tumor may prove to be extremely important as histologically similar tumors may in fact be the result of substantially different genetic changes; changes that may play in important role in the tumor's progression and response to treatment.
Recently developed microarray analysis techniques and advances in 2D gel and mass spec analysis present unique opportunities to investigate gene function on a genomic scale; in particular, we hope to catalog genes that play a significant role in the etiology of human cancers. As a first step, we will identify genes exhibiting a differential expression pattern in normal and tumor cells; such an identification may lead to an understanding of the roles played by many genes whose functions are currently unknown. In parallel, we will use techniques developed for the analysis of protein expression to examine and identify candidate proteins that may be involved in, or diagnostic or prognostic of, tumor development and response. We will build on these studies to develop clinical and laboratory protocols, databases, and data visualization and analysis software necessary to extend these studies to clinical samples and eventually to allow for the clinical diagnostic use of expression analysis.
