"They have been focusing on the right pathway, but the wrong molecules in that pathway," Amina Qutub says. (Credit: Michael Roach/Flickr)

brains

Why these brain tumor drugs miss the mark

Drugs that target insulin pathways to slow or stop the growth of brain tumors are on the wrong track, even if they’re going in the right direction, researchers say.

Studies have shown patients who are obese, diabetic, or both have the highest incidence of glioblastomas. Therapies that attack the insulin signaling pathway thought to influence tumor development have been successful in animal trials but failed in subsequent human trials.

Rice University bioengineers led by Amina Qutub believe that’s because they go after the wrong targets.

“They have been focusing on the right pathway, but the wrong molecules in that pathway,” Qutub says.

Through detailed computer models and experiments on cell types, the researchers, writing this month in PLOS Computational Biology, provide deeper understanding of interactions between key factors in the insulin signaling pathway that influences the growth of brain tumors.

The new work is the first to establish, through a computer model, mechanisms that show why some brain tumors are insulin-sensitive while others appear to be insulin-insensitive. Earlier experimental studies have looked at two aspects of the insulin pathway suspected of influencing glioblastomas, but they were never considered in tandem until now.

Patient responses to drugs that affect the insulin pathway depend on the type of tumor, she says.

“In vitro and in patients, some glioblastomas are sensitive to insulin and others aren’t. We’re saying that for those who are—and many are—you really need to target the pathway we’re describing.”

The lab is preparing experiments on glioblastoma cells to see how they respond to stimuli that affect the pathways.

Qutub notes other recent studies suggested diabetes might actually reduce the risk of glioblastoma, while still others say exercise and glucose control can cut risk.

Computational modeling of all the possibilities can help clarify the picture, she adds.

“By modeling, we can test different scenarios rapidly before going back into the lab, without being wedded to a particular animal model or subset of human studies,” she says.

Rice undergraduate Angela Liao is coauthor of the paper. The National Science Foundation supported the research.

Source: Rice University

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