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Current Research Projects

Project Title Identification of Novel Genetic Risk Factors that Contribute to the Risk for Breast Cancer

Researcher: Paul Goodfellow, PhD, The Ohio State University College of Medicine, Columbus, OH, and Jennifer Ivanovich, MS, Washington University School of Medicine, St. Louis, MO at Washington University School of Medicine

Study Abstract: Breast cancer takes its greatest toll on young women. Young women frequently have biologically aggressive tumors. They often present with advanced disease and their tumors are frequently hormone non-responsive, thereby limiting treatment options. Young women suffer lower than average disease-free and overall survival.
The work proposed is focused on discovery of the as yet unknown genetic risk factors that underlie development of early-onset breast cancer. These findings will pave the way for future studies to elucidate how
genetic risk and environmental factors interact and account for the aggressive tumors and poor outcome young breast cancer patients experience. We hypothesize copy number variants (CNVs) play an important role in risk for development of early-onset breast cancer. Three inter-related aims are proposed to identify the CNVs and genes they impact that are important in early-onset breast cancer.

Aim 1. Assess copy number variants (CNVs) in 120 BRCA1 and BRCA2 negative breast cancer patients diagnosed <40 along with their biologic parents. We will map CNVs at high density in the genomes of 120 early-onset breast cancer patients, comparing their CNV make-up with their parents’.

Aim 2. Validate CNVs and evaluate an additional cohort of early-onset breast cancer patients for variants identified in Aim 1. CNVs identified in Aim 1 will be validated using a high resolution custom array to identify candidate breast cancer susceptibility loci. A total of 240 cases will be investigated. Variant-specific
PCR amplicons will be developed for a select set of CNVs.

Aim 3. Characterize CNVs and candidate genes to determine their role in breast cancer risk. Mutation analysis will be our primary method for determining if a CNV-associated candidate gene is involved in breast cancer risk. Mutations seen in breast cancer cases but not in controls would be taken as evidence for a gene’s
role in breast cancer susceptibility. We will investigate families for co-segregation of CNVs with cancer and use
family member DNAs to verify and refine interpretation of allelism for CNVs of interest.