Virginia Tech Electrical and Computer Engineering professors Dr. Jason Xuan and Dr. Joseph Wang are conducting research on the correlation of a high-fat diet and breast cancer risk in future generations. I found this topic to be very intriguing, so I traveled two hours to Virginia Tech’s research center in Arlington, Virginia to find out more about it. The research began one year ago and is scheduled to last four more years. Virginia Tech’s part in the research is entirely engineering related. The larger project, in collaboration with Georgetown University, Johns Hopkins University, the National Children’s Hospital and the National Institutes of Health, is multidisciplinary and involves not just engineers, but doctors, biologists, and psychologists too.
Breast cancer risk has become even more of a hot topic recently due to celebrities like Angelina Jolie. Jolie had a double mastectomy in early 2013 after finding out she had the gene mutation that drastically increased her risk of developing breast cancer. But a mutated gene accounts for only 5 to 10% of the risk. Frightening statistics, such as one out of eight women developing breast cancer at some point in their life, make breast cancer a big concern for many women. Ten years ago, Dr. Xuan heard a personal account from a woman on a radio show about her firsthand experience with breast cancer. He was deeply touched by this story and knew he wanted to combine engineering with breast cancer research.
To research the effects of a high-fat diet on breast cancer risk in future generations, experiments are conducted using rats. Rats are fed a fatty diet, and a tumor is chemically induced in each rat in order to get more direct results rather than letting the rats naturally develop the cancer. Then data is collected on the next three generations of females. When comparing mothers and daughters, they look for both the number of tumors developed in the daughter and the number of daughters who developed tumors. They also study the gene expressions of the rats and count terminal end buds, bulbous parts of their genes that could potentially develop into cancer, to determine cancer risk.
The fatty diet is tied to the estrogen level and hormonal system of the rat. Diet is one disruptor that affects DNA methylation, one of the controlling mechanisms of the expression of genes. Disruptors such as a high-fat diet cause a change in the DNA methylation of the rat, and therefore alter their DNA. This alteration in DNA can be inherited by future generations, which is how they can be affected by the diet choices of a woman during her pregnancy.
So far, the experiment data demonstrates that a higher number of rats developed cancer if they had a mother who was fed a high-fat diet. In the control group (rats with tumors induced, but are fed a healthy diet), those who developed cancer had a larger number of tumors. So far, the experiment has confirmed that a greater number of rats born from a mother who ate a high-fat diet would develop cancer, but an unexpected complication comes with the number of tumors in the rats that developed cancer from both groups.
One big question I had about this research project was about the role electrical and computer engineering played in breast cancer research. I found out that engineering comes in for the measurements, screening, identifying, modeling, developing algorithms, and conducting and analyzing data. Dr. Xuan explained how this research was a big challenge because new engineering approaches for these problems had to be created since the research involves biological systems. Regular textbook methods cannot be used easily. A lot of engineering innovation is required. They have to take this breast cancer risk problem and translate it into an engineering problem that they can solve.
Ph.D. student Xiao Wang is one of the students working under Dr. Xuan and Dr. Wang. Her job is to link the rat experimental data and the data collected from woman patients and their babies. The pregnant woman patients were put into two groups based on their regular diets and hormone levels. Then after the babies were born they studied the babies’ DNA methylation status and gene expressions to assess breast cancer risk. A big part of the research involves determining which specific subset of genes is responsible for the risk. This will allow researchers to obtain more accurate results, rather than trying to collect data from a random sampling of genes.
When I asked Dr. Xuan what comes next after this research has concluded, he answered that personalized medicine is the future for breast cancer treatment. Drugs need to be tailored to women in order to be most effective. There will probably never be one cure-all drug for every woman. Dr. Xuan projects that it will take about 20 years before personalized cancer medicine and treatments will become available. Currently, there is a hormone drug on the market that is used to help with breast cancer, but it is only helpful for five years or less, and there is no new drug to help after that time period.
I asked Dr. Wang the same question, and he answered that preventative medicine is of extreme importance, more so than a cure. He also commented on how preventive medicine would help with healthcare costs for Americans because less people would be getting breast cancer, and as a result, medical costs would decrease. Dr. Wang also proposed the idea of obesity being a potential link to cancer risk that should be researched, since obesity is already linked to so many other diseases.
All in all, researchers hope the findings from these experiments will lead to prevention and lifestyle guidelines. This would translate into diet guidelines for pregnant women and societal awareness of the detrimental effects that a poor diet can have on your descendants.
Ph.D. student Xiao Wang and Dr. Jason Xuan are working in the lab to link the experimental rat data and the data collected from women patients, and to discover which specific genes are responsible for cancer risk.
Author, Sarah Stewart, is a junior in Industrial and Systems Engineering. This article was first published in the September 2013 issue of Engineers’ Forum.