Cancer therapy involves great unknowns. But what if doctors had some help in predicting how their pediatric oncology patients might respond to a particular treatment? What if physicians could save critical time and prevent unnecessary side effects by confidently choosing the most effective drug intervention for their young patients the first time out?
Those are scenarios that Dr. Diana Azzam of the Robert Stempel College of Public Health & Social Work would like to help make possible. She has received a $400,000 grant from the Cornelia T. Bailey Foundation, in collaboration with Dr. Maggie Fader and Dr. Daria Salyakina from Nicklaus Children’s Hospital, for an observational study that will have her testing the efficacy of standard drug protocols on individual children’s tumor tissue. She will treat doctor-provided samples of sarcoma—an aggressive form of cancer that represents 14 percent of childhood cancer cases—with the pharmaceuticals most commonly prescribed for the disease as well as commonly used combinations of those drugs, roughly 40 possibilities in all.
In her campus lab, Azzam will then assess how well each given drug effectively kills cancer cells from each of the 15 patient cases that will make up her study. Those results will not be shared with doctors until after patients’ clinical treatments have been completed. At that point, a correlation will be made to understand how closely the lab results reflect the effect of using a particular drug or drugs as part of clinical treatment.
“A close correlation,” Azzam explains, “will tell me that this assay is predictive.”
Azzam refers to this type of testing as “drug sensitivity” because it shows how sensitive patients’ cells are to a particular drug or drug combination. The more “sensitive” the cells are, the more likely they are to be killed by the drug(s). Other types of personalized medicine—tailored to the individual patient—have shown much promise in recent years with the advent of new laboratory advances.
The goal, she explains, is to one day utilize such predictive testing to help oncologists make the best treatment decision at the outset of new patient diagnoses to save time in finding a winner–often, one ineffective drug is replaced with another, and so on, until one works–and to prevent myriad negative side effects that can occur with the introduction of each new drug.
If successful, Azzam hopes her research will build doctors’ trust in the technology.
“It’s challenging for oncologists to really believe that whatever test we do in the lab really works on the patient,” she says. “For me to do that, I need to show that drug testing correlates and can predict how the patient responds.”