Epithelial ovarian carcinoma is the leading cause of death from gynecologic cancer in the US. Approximately 75% of patients present with advanced stage disease, for which the five-year survival rate remains below 30%, whereas the five-year survival rate for stage I disease is 93%. Therefore, it is anticipated that effective methods of early detection of ovarian cancer would substantially reduce overall mortality rates for this disease. Despite much effort, there are currently no reliable procedures for the early detection of ovarian cancer available. ? ? In the past decade, a substantial amount of evidence for the occurrence of extensive alterations of DNA methylation patterns in cancer cells has accumulated. We and others have recently shown that these abnormal DNA methylation patterns can be detected in tumor-derived DNA in the serum and plasma of cancer patients. ? ? We propose to use a sophisticated automated methylation analysis technology that we have developed, called MethyLight, to screen a large panel of genes to identify markers specific for ovarian cancer, compared to non-neoplastic ovarian tissue. This will allow the correlation of methylated markers in ovarian tumors with clinicopathological features, and with response to chemotherapy and overall survival. Subsequently, we can use the information obtained in this screen of tissue samples to develop markers for the detection of ovarian tumor-derived DNA in the serum of patients with existing or recurring disease. Finally, we propose to use the most promising biomarkers to evaluate the capacity to detect preclinical relapse of disease, as a function of time before clinical diagnosis of relapse.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA096958-02
Application #
6660336
Study Section
Clinical Oncology Study Section (CONC)
Program Officer
Lively, Tracy (LUGO)
Project Start
2002-09-24
Project End
2007-08-31
Budget Start
2003-09-01
Budget End
2004-08-31
Support Year
2
Fiscal Year
2003
Total Cost
$325,406
Indirect Cost
Name
University of Southern California
Department
Surgery
Type
Schools of Medicine
DUNS #
072933393
City
Los Angeles
State
CA
Country
United States
Zip Code
90089
Shen, Hui; Fridley, Brooke L; Song, Honglin et al. (2013) Epigenetic analysis leads to identification of HNF1B as a subtype-specific susceptibility gene for ovarian cancer. Nat Commun 4:1628
Campan, Mihaela; Moffitt, Melissa; Houshdaran, Sahar et al. (2011) Genome-scale screen for DNA methylation-based detection markers for ovarian cancer. PLoS One 6:e28141
Dafou, Dimitra; Grun, Barbara; Sinclair, John et al. (2010) Microcell-mediated chromosome transfer identifies EPB41L3 as a functional suppressor of epithelial ovarian cancers. Neoplasia 12:579-89
Houshdaran, Sahar; Hawley, Sarah; Palmer, Chana et al. (2010) DNA methylation profiles of ovarian epithelial carcinoma tumors and cell lines. PLoS One 5:e9359
Teschendorff, Andrew E; Menon, Usha; Gentry-Maharaj, Aleksandra et al. (2010) Age-dependent DNA methylation of genes that are suppressed in stem cells is a hallmark of cancer. Genome Res 20:440-6
Campan, Mihaela; Weisenberger, Daniel J; Trinh, Binh et al. (2009) MethyLight. Methods Mol Biol 507:325-37
Weisenberger, Daniel J; Trinh, Binh N; Campan, Mihaela et al. (2008) DNA methylation analysis by digital bisulfite genomic sequencing and digital MethyLight. Nucleic Acids Res 36:4689-98
Ehrlich, M; Woods, C B; Yu, M C et al. (2006) Quantitative analysis of associations between DNA hypermethylation, hypomethylation, and DNMT RNA levels in ovarian tumors. Oncogene 25:2636-45
Laird, Peter W (2005) Cancer epigenetics. Hum Mol Genet 14 Spec No 1:R65-76
Widschwendter, Martin; Jiang, Guanchao; Woods, Christian et al. (2004) DNA hypomethylation and ovarian cancer biology. Cancer Res 64:4472-80