Daniel Bolon, PhD, professor of biochemistry & molecular pharmacology, studies drug resistance in cancer cells.
His lab at UMass Chan Medical School works to systematically quantify the impacts of mutations on protein function.
“I study drug resistance so that we can prevent cancer from taking people that we love too soon,” Dr. Bolon said. “Because cancer is common and deadly, most of us have lost someone that we would have dearly loved to spend more time with.”
Losing his grandfather to cancer is what ignited his passion for his research. As a child, he didn’t enjoy drinking milk, and his grandfather would often encourage him to do so by offering him milk with a plate of cookies. Young Bolon would only take one sip, but his grandfather remained patient and kind.
“When I learned that he had cancer, I was scared,” Bolon said. “I was shocked when he died a short time later. I know many of us can relate. Losing my grandfather motivated me to understand drug resistance and cancer so that all of us can have more time with the people that we love.”
Bolon earned his bachelor’s degree in biochemistry at Duke University and his PhD from Caltech, where he studied computational enzyme design. In 2005, he joined the faculty at UMass Chan Medical School where he’s devoted time to studying anti-cancer drug resistance.
“Cancer cells tend to divide rapidly and make imperfect copies of themselves, which fuels the development of drug resistance,” Bolon said. “Anti-cancer drugs often kill the majority of cancer cells, but if a small number of the imperfect copies can figure out how to outsmart the cancer drugs, they will multiply and the cancer that comes back cannot be effectively treated.”
Drug resistance is complex, and the number of possible mutations is nearly limitless. Bolon said a single cancer gene could mutate in hundreds of thousands of different ways.
His lab is pioneering strategies to analyze all possible mutations in a gene that could lead to drug resistance. Among the key innovations they’ve developed are generating libraries of all mutations and using high throughput DNA sequencing to track each possible variant.
“Using the approach, we can rapidly and comprehensively determine how hundreds of drugs impact drug resistance,” he said. “This gives us a tool that we can use early in drug development to identify the potential drugs with the lowest chance of developing drug resistance.”