Researchers have found that dye absorption patterns in computed tomography scans act as a surrogate for chemotherapy delivery and may help predict patient response to treatment—and lead to more effective drug delivery methods.
Computed tomography (CT) may help researchers predict which patients are likely to respond to treatment and lead to more-effective delivery methods, a recent study has found.
The study, published in the April issue of the Journal of Clinical Investigation, tests the hypothesis that the dense stroma surrounding pancreatic tumors prevents effective delivery of chemotherapy into cancer cells, leading to poor clinical outcomes (J Clin Invest 2014;124:1525–36). Investigators enrolled 12 patients with primary pancreatic cancer who received gemcitabine (Gemzar; Eli Lilly) during surgical resection and analyzed their tumors after surgery to assess drug penetration.
“This is the first study in humans where we've been able to measure if chemotherapy given intravenously is actually getting into a pancreatic cancer tumor and performing its function,” says Jason Fleming, MD, professor of surgical oncology at The University of Texas MD Anderson Cancer Center in Houston and the study's corresponding author. “We found that delivery of gemcitabine into the tumors was much more variable than previously thought.”
By analyzing tumor DNA, the researchers found that the variability was tied to expression of the protein hENT1, which has been shown to facilitate transport of gemcitabine across the cell membrane. Drug penetration was lowest in patients with dense, fibrotic tumors and low hENT1, and those patients also had the poorest responses to therapy.
The researchers then analyzed CT scans from 110 patients who had previously received presurgical gemcitabine-based chemoradiation. They noted a correlation between the absorption patterns of the dye used in CT scans and clinical outcome, suggesting a possible method for predicting the effectiveness of therapy.
“The IV dye used in CT scans acts as a surrogate for the chemotherapy that you would give intravenously. Knowing this, we could use the CT scan as a predictive study that could tell us which patients would respond poorly to therapy so we could hopefully use other drugs to modify that delivery,” explains Fleming. “For example, you could assess the hENT1 expression status and collagen density of the tumor, combined with imaging data, to get a profile of the expected efficacy of IV therapies in an individual patient.”
A patient predicted to respond poorly to chemotherapy, based on data from a CT scan and a biopsy, says Fleming, might receive a drug prior to chemotherapy that might alter the tumor's blood vessels [such as the hypertension drug losartan (Cozaar; Merck)] to improve delivery of chemotherapy.
Preliminary data suggest that using imaging to predict responses to therapy may be effective for other types of solid tumors, says Fleming.
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