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U.S. National Institutes of Health
Last Updated: 03/05/10

Steven W. Johnson, University of Pennsylvania
“Molecular Classification of Ovarian Tumors”

Abstract: Ovarian cancer is the fourth leading cause of cancer deaths among women in the United States and is the most fatal gynecologic malignancy. There is a need to be able to accurately predict outcome based on the molecular characteristics of ovarian tumors such as subtype, grade and degree of malignancy. In addition, understanding the molecular basis for the response of tumors to chemotherapy is also important for the design of new treatment regimens and for the identification of new drug targets. Therefore, defining the gene expression or molecular profiles of ovarian tumors will be an important step towards improving diagnosis and treatment. Recently, significant advances have been made in methodologies directed at the identification and quantitation of differentially expressed genes. The technique of cDNA array screening is capable of establishing gene expression profiles for the majority of the genes expressed in the human genome and new developments in “real time” quantitative RT-PCR enable the accurate determination of gene expression levels in tumor specimens and microdissected tissue. Using this technology, we propose to: Specific Aim number 1. Establish comprehensive molecular profiles for ovarian tumors with respect to grade and degree of malignancy using cDNA array screening. This will be a retrospective study in which primary ovarian tumors will be analyzed by standard histologic methods. Messenger RNA will be isolated from the same specimens and used as probes for cDNA array screening. The molecular profiles that are generated will be used to define a set of genes whose expression denotes a specific ovarian tumor grade and degree of malignancy. Specific Aim number 2. Establish comprehensive molecular profiles for ovarian tumors from patients that are either responsive or non-responsive to platinum-based combination chemotherapy. The availability of a molecular profile that predicts patient response to chemotherapy will enable physicians to individualize treatment for ovarian cancer. Also, the identification of genes that are associated with poor prognosis may define targets that will lead to the design of new drugs or treatment regimens. Specific Aim number 3. Validate the molecular profiles established in Specific Aims number 1 and number 2 by applying quantitative assays of gene expression to a statistically significant number of tumor samples representing the same histologic types, outcome and response to chemotherapy. The set of expressed cDNAs that define the type of ovarian tumor and response to chemotherapy will be measured in a statistically significant number of tumor samples representing each phenotype using “real time” quantitative PCR. This high-throughput technology will facilitate the measurement of gene expression in large numbers of tumor specimens and will establish a standard pathologic assay for routine analyses.