Methylation is an epigenetic mechanism of gene silencing found to be important in cancer progression. Many tumor suppressor genes are believed to be inactivated by methylation events. Therefore studying the process of methylation can advance our understanding of carcinogenesis. We propose to develop and implement computational and experimental approaches to measuring de novo methylation kinetics in cancer cells. Our overall aim is to quantify the rate of promoter methylation in cell lines with different genetic backgrounds. We will construct mathematical models which describe promoter methylation in a population of cells growing exponentially in vitro. Several assumptions regarding the methylation process are uncertain;therefore, we will consider a variety of different models. Testing these models will allow us to reject certain assumptions, and to determine which model is most consistent with data. We will conduct in vitro experiments to quantify the process of de novo methylation in several cancer cell lines. We will obtain time-series measurements of the colony size as well as methylation data, by using COBRA and pyrosequencing techniques. We will then use data from the experiments in order to distinguish which models are incorrect, and which model is most consistent with data. This will shed light on the mechanisms which underlie the methylation process. We will then use the experimentally validated, best-fitting model in order to calculate the site-specific and average rates of promoter methylation in cells with different genetic backgrounds. Lab summary: This project would help us better understand the speed/rate of colon cancer development that happens as a result of inappropriate DNA methylation, a mechanism that is prevalent in most human cancers. Since DNA methylation is a reversible process, a better knowledge of rate of cancer development in these patients would allow timely institution of methylation-reversing therapies that have implications for cancer prevention.Project Narrative: The initiation and progression of cancers involves both genetic and epigenetic modifications of cells. While genetic modifications (mutations) have been studied in detail, epigenetic changes (methylation) are not well understood, so we propose to study the methylation process of cancer gene promoters. By testing and rejecting various mathematical models we will find which mechanisms are key to the process, and use the best-fitting model to measure the actual methylation rate in different cell lines.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project (R01)
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Modeling and Analysis of Biological Systems Study Section (MABS)
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Li, Jerry
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University of California Irvine
Biostatistics & Other Math Sci
Schools of Arts and Sciences
United States
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