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Team identifies new gene candidates for breast cancer risk

Jun. 28, 2018, 8:51 AM

An international coalition led by scientists at Vanderbilt University Medical Center and the QIMR Berghofer Medical Research Institute in Herston, Australia, has identified 48 candidate susceptibility genes for breast cancer risk, including 14 genes at loci (chromosome regions) not yet reported for breast cancer.

Their findings, published June 18 in the journal Nature Genetics, provide new insights into the biology and genetics of breast cancer, the most common cancer among women in many countries around the globe.

“This study has provided substantial novel information to improve our understanding of breast cancer genetics and biology,” said Wei Zheng, MD, PhD, MPH, the paper’s senior author and director of the Vanderbilt Epidemiology Center.

Genetic factors play an important role in breast cancer etiology (causation), said Zheng, who is the Anne Potter Wilson Professor of Medicine and chief of the Division of Epidemiology in the Vanderbilt University School of Medicine.

To date, genetic markers in approximately 170 chromosome regions have been identified in association with breast cancer risk. However, these genetic factors explain only a small fraction of heritability for breast cancer and the genes responsible for the associations remain unknown in most of these regions.

To identify novel breast cancer risk loci and likely causal genes, the researchers conducted a transcriptome-wide association study (TWAS) of nearly 123,000 women of European descent who had been diagnosed for breast cancer and 106,000 controls (women without disease). More than 200 investigators in 22 countries contributed to the study.

The researchers first built mathematic models to predict expression levels of genes across the human genome using data from a small set of women whose breast tissue samples were analyzed for gene expression.

Then they used these models to predict gene expression in a large number of breast cancer patients and controls using data about their genetic make-up. Finally, genetically predictive expression levels of genes in cases and controls were compared to identify genes that were expressed differently in the two groups.

“This research design is very cost-efficient and powerful in identifying candidate risk genes for breast cancer,” said Lang Wu, PhD, a former Vanderbilt postdoctoral fellow and now research instructor in Medicine, who is one of two first authors of the paper.

Of the genes identified in the study, the researchers selected 13 genes for functional analyses. In 11 cases, silencing the genes influenced cell proliferation and the ability to form colonies, two characteristics of tumor growth.

This provided further evidence that the identified genes might be involved in breast cancer risk. The findings provide multiple new targets for further study and raise hopes for development of more precise risk prediction strategies for breast cancer, the researchers said.

The functional analyses were led by Georgia Chenevix-Trench, PhD, head of the Cancer Genetics Laboratory at QIMR Berghofer and the paper’s co-corresponding author with Zheng.

Other Vanderbilt faculty members who contributed to the study were Jirong Long, Ph.D., Xingyi Guo, PhD, Xiao-Ou Shu, MD, PhD, MPH, Qiuyin Cai, MD, PhD, Bingshan Li, MD, PhD, and Martha Shrubsole, PhD.

The research was supported in part by National Institutes of Health grants CA158473, CA148677, CA218892 and CA160056.

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