According to the American Cancer Society, breast cancer is the most common cancer among American women, except for skin cancers, and about one in eight women in the United States will develop invasive breast cancer during their lifetime. The National Institutes of Health recently awarded a $1.08 million grant to The University of Texas at San Antonio (UTSA) to combine computational modeling with biological information to advance our understanding of what may cause breast cells to become cancerous.
The research team includes UTSA electrical and computer engineering professors Yufei Huang and Jianqiu (Michelle) Zhang along with Manjeet K. Rao, an RNA biologist, and Yidong Chen, an expert in bioinformatics, from the University of Texas Health Science Center San Antonio.
This three-year grant will allow the researchers to study the link between cancer and mRNA methylation, a newly discovered epigenetic process that commands the orderly functions of human cells. Using deep genome sequencing and computer modeling, their goal is to search for abnormalities in the methylation process that might lead to diseases such as cancer.
"By bringing together computer engineers who are experts in computational modeling with experts in biology and genome sequencing, we have added a new dimension to the emerging study of mRNA methylation," said Huang. "We are going to conduct some truly groundbreaking research over the next few years."
Huang says the research will hopefully shed new light on the role of mRNA methylation in regulating the dynamics between normal and diseased states in breast cancer, providing leads to more effective strategies for therapeutic intervention.
"The research to be performed at UTSA through this prestigious NIH grant has the potential to fundamentally change how we see human diseases," said Daniel Pack, chair of the UTSA Department of Electrical and Computer Engineering.
To address the need for the high computing power needed to run the study's simulations, the team will also work with researchers at the UTSA Open Cloud Laboratory.
Source: University of Texas at San Antonio