New tool developed by Vanderbilt investigators for cancer treatments
Vito Quaranta, M.D., seated, and colleagues, from left, Darren Tyson, Ph.D., Shawn Garbett and Peter Frick (photo by Anne Rayner, courtesy of Vanderbilt University)
NASHVILLE, TN (WSMV) -
A new tool to observe cell behavior has revealed surprising clues about how cancer cells respond to therapy and may offer a way to further refine personalized cancer treatments.
The approach, developed by investigators at Vanderbilt-Ingram Cancer Center, shows the targeted therapy that acts on a growth factor receptor mutated in some lung, brain and other cancers, doesn't simply kill tumor cells. The drug also causes some tumor cells to go into a non-dividing state.
The new tool, reported Aug. 12 in Nature Methods may offer ways to improve personalized cancer therapy by predicting tumor response and testing combinations of targeted therapies in an individual patient's tumor.
In the personalized approach to cancer treatment, a patient's tumor is analyzed for a set of mutations to which there are matching drugs that act on those mutations.
This approach has worked rather well for many cancers that carry specific mutations, said senior author Vito Quaranta, M.D., professor of Cancer Biology.
"The genetics is well understood, the clinical effect is understood and the chemistry behind the therapy is understood, but there is a missing piece," Quaranta said. "Believe it or not, what is actually not understood is how cells respond to these drugs, what is actually happening."
But even if the tumor is composed entirely of genetically identical cells, a drug will not affect all cells the same way.
"Some of these cells may die, some may just stop dividing and sit there, and some may keep dividing, but more slowly," Quaranta said.
However, no current tests can provide an accurate, detailed picture of cell behavior needed to understand tumor response to drugs.
So, the investigators, led by first author Darren Tyson, Ph.D., research assistant professor of Cancer Biology, combined powerful automated, time-lapse microscopy with analytical tools.
Using these techniques, they could capture the behavior of lung cancer cells every six to 10 minutes for up to 10 days. As they expected, the targeted therapy killed some cells, while other stopped dividing.
They observed that the drug even affected genetically identical cells differently.
"These cells are clearly genetically identical as identical as they can possibly be..., but you get completely different responses: one dies and the other one doesn't," Tyson said. "This suggests that there are other things besides genetics that have to be taken into account."
What those other factors are remains unclear, but the investigators are conducting follow-up experiments to determine what might underlie this differential response.
"And presumably, it is those [non-dividing] cells that ultimately result in tumor recurrence," Tyson said.
Quaranta and colleagues hope to take the technology into small clinical trials to test whether it can predict a patient's response to therapy.
"We think that we might be able to forecast what the response is going to be," Quaranta said. "We can take samples from the tumor, subject them to this [test], and since we're looking at response over time, we will have a rate of response."
This could tell tumor doctors how long a patient's tumor will respond to a given therapy before it recurs. Such information could also help determine which patients will require more aggressive treatment, and Quaranta believes this will be able to test combinations of drugs on a patient's tumor cells to find the right combination to induce a response.
Copyright WSMV 2012 (Meredith Corporation). All rights reserved.
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