Breast cancer genomics-related projects involving CSBL:

Cincinnati Breast Cancer and Environment Research Center (BCERC).

The Breast Cancer & the Environment Research Centers (BCERC) are a joint effort of the National Institute for Environmental Health Sciences (NIEHS) and the National Cancer Institute (NCI). Research scientists and breast cancer survivors/ advocates partner to conduct human and animal/tissue culture studies. The new centers are the University of Cincinnati; Fox Chase Cancer Center, Philadelphia, PA; University of California, San Francisco; and Michigan State University, East Lansing. For more information about the BCERCs go to http://www.bcerc.org.

One of the key objectives of the Cincinnati BCERC (PI: Sue Heffelfinger) project is to understand how obesity and high fat diets impact mammary gland development and its susceptibility to cancer due to environmental exposures. Microarray studies (gene expression analyses) of the mammary gland tissues from a short-term dietary study in the presence or absence of carcinogens are in progress. These studies will provide insight into the effects of specific fatty acids on gene expression patterns in healthy vs. malignant mammary gland.

Center For Environmental Genomics (CEG)

CEG is a NIEHS funded center (PI: Shuk-Mei Ho) whose purpose is to support environmental health research by offering medium for collaborative research efforts and research support through its research support cores. The goal of CEG is to improve human health through the translation of basic and applied research into clinical practice, and to provide the community with the necessary information to make informed decisions for promoting a healthier environment and lifestyle. The objective of the Bioinformatics F&S Core (Core Director: Medvedovic, M) is to assists investigators in converting the genomic and protein data into meaningful information by the use of appropriate data-management and computational/statistical tools.

Bayesian mixtures for modeling functional genomics data

The objective of this project is to develop a comprehensive framework for identifying statistically significant patterns in functional genomics data. The project is funded by the grant R01HG003749 from NHGRI (PI: Medvedovic, M). Based on the context-specific Bayesian infinite mixture models, mathematical models will be developed that facilitate identifying and modeling of explanatory variables associated with biological samples that have been expressionally profiled using microarrays, and incorporating prior knowledge about gene expression profiles into the process of identifying biologically meaningful patterns of expression. Corresponding computational tools for fitting these models will be developed, optimized and delivered to biomedical community by developing a Bioconductor package and as stand-alone applications. The validation of the procedures will include identification of putative regulators of transcriptional program of initiated mammary epithelium through the large scale computational analysis of public microarray data. The wet lab validation will be performed by siRNA-based knock-down experiments involving putative regulators identified in computational analysis.

Global gene expression profiles for the very early prediction of breast cancer

•The main hypothesis of the study is that global gene expression profiles of white blood cells can be used as an early and accurate indicator and predictor of breast cancer. The project is funded by a grant from Ohio Cancer Research Association (OCRA) (Co-PIs: Medvedovic, M and Tomlinson, CR). The goals of the project is to identify gene expression profiles in white blood cells that can server as biomarkers of early mammary carcinogenesis and to validate the predictive power of these gene expression profiles in an independent prospective study.

Polygenic Effects of Obesity in Mammary Carcinogenesis: A New Model

•The main hypothesis of the study is that adiposity is a risk factor for mammary tumor carcinogenesis independent of dietary fat consumption. The project is funded by a pilot grant from Center for Environmental Genetics (CEG) (PI: Heffelfinger). The goals of the project are to characterize mammary gland tumor response to DMBA in DIO and DR inbred strains and characterize mammary gland gene expression at time of maximal carcinogen susceptibility

Laboratory for Statistical Genomics and Systems Biology
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