Study shows how a protein coding gene confers breast cancer susceptibility during DNA transcriptionSep. 30, 2021, 9:04 AM
by Tom Wilemon
New research from Vanderbilt-Ingram Cancer Center provides insight into how genetic variants convey breast cancer susceptibility by altering the transcription factor proteins that convert DNA strands into RNA.
The research, published recently in Nature Communications, identified 22 breast cancer risk-associated transcription factors and 52 previously unreported breast cancer susceptibility genes. The investigators analyzed the interactions of the protein coding genes FOXA1, ESR1 and E2F1, which are known master regulators of gene expression that affect breast cancer risk.
The study established the landscape of genetic variations for transcription factor-DNA bindings associated with breast cancer risk. The research approaches utilized by the investigators can also be applied to other human cancers as well, to advance the general understanding of genetic and molecular mechanisms of cancers.
“The pioneer factor FOXA1 plays a particularly important role in breast cancer susceptibility, because we found that not only the association between genetic variations of transcription factor-DNA bindings for FOXA1 and breast cancer risk was the strongest among all the transcription factors investigated, but also FOXA1 showed significant synergy with other relevant transcription factors,” said Wanqing Wen, MD, MPH, research associate professor of Medicine and the study’s corresponding author.
Previous research utilizing genome-wide association studies (GWAS) had revealed that breast cancer risk was related to transcription factor proteins, but those studies had suboptimal statistical power and failed to investigate interactions between transcription factors because they focused on a limited number of GWAS-identified single nucleotide polymorphism (SNPs). The researchers also used a series of methods in their data analysis, which are explained in the paper.
“It is a major challenge in genetic studies to identify disease-related transcription factors-DNA bindings altered by risk genetic variants that regulate susceptibility genes,” said Xingyi Guo, PhD, associate professor of Medicine and Biomedical Informatics, who conceived and designed the study with Wen.
“Our developed analytic approach provides a new way to explore the mechanisms underlying risk variants identified from GWAS. Our study showed promising results in improving the discovery of breast cancer susceptibility genes by integrating investigation of transcription factor-DNA bindings with transcriptome-wide association analysis,” Guo said.
Others contributing to the study were Zhishan Chen, PhD, Jiandong Bao, PhD, Quan Long, Xiao-ou Shu, MD, PhD, MPH, and Wei Zheng, MD, PhD, MPH. The study was supported primarily by National Institutes of Health grants R37 CA227130 and R01 CA188214.