Esophageal cancer occurs in two major histologic types;squamous cell carcinoma (SCC) and adenocarcinoma (EA) both of which have an extremely poor prognosis. Although these tumors are often treated as one disease, they have distinct differences in epidemiology, risk factors and biological behavior. In Westernized countries the incidence of SCC has been steadily decreasing over the past 25 years, while EA rates have been increasing dramatically (~400%). In fact, EA now has the fastest rate of increased incidence of any tumor in the United States. This is most likely linked to the rise in obesity and the high prevalence of gastroesophageal reflux disease, which is estimated to affect up to 44% of the American population and is strongly linked to the development of EA. Despite this rise, research on esophageal adenocarcinoma is made difficult by the relatively low number of cases per year and the inability of single institutions to acquire large patient cohorts for study. Consequently much less is known about the biology of this disease than about more prevalent tumor types. On a genome-wide scale, very little is known about the genetic aberrations and gene expression alterations that are specific to EA. Partly as a result of these deficiencies in our knowledge, there are currently very few biomarkers for disease diagnosis, progression or prognosis and there are no targeted therapeutic agents indicated for the treatment of this highly lethal tumor. Our research group is in a strong position to address these deficiencies since we have a multi-disciplinary team focused on translational research and our ongoing, R01-funded studies have enabled us to develop large tissue banks with detailed clinical information on all patients. In this proposal, we intend to utilize these resources in order to generate molecular staging tools and to identify novel therapeutic targets to improve the treatment of esophageal adenocarcinoma patients. Specifically, we propose to examine the genome of EA using high density DNA arrays in order to identify genomic regions that are frequently altered in this tumor type. We will then identify all genes within these altered regions and extract their expression levels from Affymetrix U133 arrays. Genes whose expression levels correlate with DNA copy number change will be cross-referenced against """"""""druggable"""""""" target databases in order to identify potential new therapeutic targets for esophageal adenocarcinoma. We will also determine which of the regions and genes are associated with disease stage, metastasis and survival. The association of these regions and the expression of genes within them with clinical endpoints will then be validated in an independent tumor set using quantitative PCR. Finally, validated prognostic markers will be combined to develop a molecular staging algorithm that can be used to guide therapy for esophageal adenocarcinoma patients. Thus, at the end of this study we will have identified, verified and validated novel genetic markers that could be used for diagnosis, staging and treatment of esophageal adenocarcinoma.
Esophageal adenocarcinoma is increasing faster than any other malignancy and typically has a late diagnosis and poor outcome. Despite major advances in high-throughput genomic analysis methods, this disease remains largely unstudied at the level of genome-wide DNA alterations. The identification of specific DNA alterations and the genes within them could lead to markers for diagnosis, progression and prognosis as well as providing novel targets for therapeutic discovery and treatment of esophageal adenocarcinoma.
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