News — Physics applies to everything. So when Vittorio Cristini, PhD, started researching cancer, he applied physics. The result he got was a set of mathematical equations that describe, for each person, how many of their tumor cells a cancer treatment could kill. Now, Dr. Cristini and his collaborators describe how they applied these equations to pancreatic cancer. It鈥檚 an application that will soon help oncologists use the mathematical model to develop treatment plans for all cancer patients.
Dr. Cristini is a University of New Mexico Professor in the Department of Pathology at the UNM School of Medicine and is the Victor and Ruby Hansen Surface Professor in Molecular Modeling of Cancers. His key collaborators are Eugene Koay, MD, PhD; Christopher H. Crane, MD; and, Jason B. Fleming, MD, FACS, all at the University of Texas MD Anderson Cancer Center. Dr. Cristini鈥檚 previous papers in 鈥淭he Proceedings of the National Academy of Sciences鈥� and 鈥淎CS Nano鈥� described a mathematical model for all tumors. In their most recent paper, published in the 鈥淛ournal of Clinical Investigation,鈥� Dr. Cristini and his collaborators write about ipovascular tumors, which are tumors that don鈥檛 have a good blood supply. Many pancreatic cancers are ipovascular.
The lack of a good blood supply hampers the blood鈥檚 ability to reach all cells. Dr. Cristini explains, 鈥淎ctually, one of the first results of this investigation demonstrated how profoundly different transport is in the tumor region within the pancreas with respect to the normal pancreas surrounding it. Transport impairment is really a signature of cancer.鈥�
Dr. Cristini鈥檚 equations use information from a person鈥檚 initial, minimally- or non-invasive cancer tests. In this study, the researchers used pre-treatment CT scans with contrast from 176 people at the MD Anderson Cancer Center who then underwent chemo-radiation treatment. Using the CT scan information, they calculated a number called the 鈥渂lood volume fraction.鈥� This number is smaller than one, and describes how good 鈥� or not 鈥� a tumor鈥檚 blood supply is. Blood volume fraction is 2 to 10 times smaller in a tumor than in normal tissue.
Dr. Cristini and his collaborators showed previously that liver tumors with high blood volume fraction responded better to chemotherapy drugs than liver tumors with low blood volume fraction. But the relationship was non-linear. As the model equations predicted, high blood volume fraction tumors die far more extensively than low blood volume tumors.
In their most recent paper, the researchers show that ipovascular tumors respond directly to the amount of chemo-radiation treatment; it鈥檚 a simpler, linear response. 鈥淪o, the linear regime of the general model equations works well for ipovascular tumors,鈥� explains Dr. Cristini. Remarkably, their paper showed that the model鈥檚 calculations based on the individual鈥檚 pre-treatment CT scans accurately predicted how well the tumor absorbed the chemotherapy drugs, how well the chemo-radiation treatment worked and even correlated significantly with patient survival.
The equations can use the results from pre-treatment computerized tomography (CT) scans, tissue analyses, and magnetic resonance imaging (MRI). Because oncologists already use these test results to develop a treatment plan, they can use Dr. Cristini鈥檚 equations to adjust their plan to each person. Dr. Cristini now has clinical trials in development at several institutions including the UNM Cancer Center to test this idea. 鈥淲e want to test the model prospectively and also test it in different types of disease,鈥� he says. 鈥淏ut we want to do more. We want to see if we can actually use these mathematics to improve the outcome for people with cancer.鈥�
Paper references
鈥淢echanistic Patient-Specific Predictive Correlation of Tumor Drug Response with Microenvironment and Perfusion Measurements鈥� is published in the August 12, 2013 online Early Edition of Proceedings of the National Academy of Sciences of the United States of America (). Authors include Elaine L. Bearer, Eugene J. Koay, Steven A. Curley, Vittorio Cristini.
鈥淢echanistic modeling identifies drug-uptake history as predictor of tumor drug resistance and nanocarrier-mediated response鈥� is published in the November 4, 2013 online Edition of ACS Nano (). Authors include C. Jeffrey Brinker, Vittorio Cristini.
鈥淭ransport properties of pancreatic cancer describe gemcitabine delivery and response鈥� is published in the March 10, 2014 Online Edition of the Journal of Clinical Investigation (). Authors include Eugene J. Koay, Vittorio Cristini, Christopher H. Crane, Jason B. Fleming.
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