Joseph Wang leads research to differentiate between aggressive and slow growing cancers; strives for more tailored patient treatment

A team of Electrical and Computer Engineering (ECE) researchers led by Yue (Joseph) Wang, professor of Electrical, Computer, and Biomedical Engineering, has helped identify biomarkers that can differentiate between aggressive and slow growing prostate cancers and between different levels of aggressiveness in ovarian cancers.

Wang’s research team at Virginia Tech’s Computational Bioinformatics and Bio-imaging Laboratory (CBIL) uses electrical and computer engineering methodologies and computational and modeling tools to solve biomedical problems and to gain a deeper understanding of the structure and function of the genome. The team is currently studying gene copy number changes. The biomarkers for aggressive prostate and ovarian cancers are based on different copy numbers of a segment of DNA. Humans should normally have two copies of each strand of DNA, one from each parent, Wang explained. “This is a nice, built-in redundancy that engineers can appreciate. It helps keep our system stable,” he said. “If one copy gets deleted for some reason, you still have a copy to sustain normal function.”

However, recent discoveries show that strands of DNA segments can get partially or completely deleted (or in contrast amplified) and that many differences can exist between populations and individuals. Called copy number variation (CNV), these changes can be inherited, or they can occur through local mutations after birth, called copy number alternations (CNAs).

“Copy number changes can cause disease. If one copy is deleted, the person may be ok, but if both get deleted, the person will almost definitely get cancer,” Wang said. “Once a person has cancer, the cancer evolves and the oncogene gets amplified. A gene may have three, four, or five copies,” he said. “We have seen either some deletions or amplification in different DNA segments.”

The segments contain sequences of nucleotide base pairs, whose measured hybridization intensities can be treated as signals to electrical and computer engineers. Wang’s team applies signal processing, pattern recognition, and computational modeling to analyze the sequences in the cancer genes to extract the gene copy number differences. “What we do is to identify where those changes occur and how often,” Wang said.

Wang’s dream is a personalized medicine in which doctors can precisely determine how an individual patient’s cancer or other disease will behave, and then target a precise treatment plan based on expected outcomes. He is working to help achieve that dream.   

“There is a considerable gap between ever growing information and our scientific ability to analyze those data,” Wang said.  “I want to trace back to the root of the mystery; I like the every day challenge this type of research presents.”

CBIL is based at the Advanced Research Institute (ARI) in Arlington, Va.

Note: Wang and his research team are among the co-authors of an international collaborative research paper recently published in Nature Medicine. The paper is titled “Copy Number Analysis Indicates Monoclonal Origin of Lethal Metastatic Prostate Cancer.” The group performed bioinformatics research that played a critical role in obtaining the scientific discoveries reported in the paper.

Posted April 23, 2009