Intra-tumoral heterogeneity of gemcitabine delivery and mass transport in human pancreatic cancer.
Academic Article
Overview
abstract
There is substantial heterogeneity in the clinical behavior of pancreatic cancer and in its response to therapy. Some of this variation may be due to differences in delivery of cytotoxic therapies between patients and within individual tumors. Indeed, in 12 patients with resectable pancreatic cancer, we previously demonstrated wide inter-patient variability in the delivery of gemcitabine as well as in the mass transport properties of tumors as measured by computed tomography (CT) scans. However, the variability of drug delivery and transport properties within pancreatic tumors is currently unknown. Here, we analyzed regional measurements of gemcitabine DNA incorporation in the tumors of the same 12 patients to understand the degree of intra-tumoral heterogeneity of drug delivery. We also developed a volumetric segmentation approach to measure mass transport properties from the CT scans of these patients and tested inter-observer agreement with this new methodology. Our results demonstrate significant heterogeneity of gemcitabine delivery within individual pancreatic tumors and across the patient cohort, with gemcitabine DNA incorporation in the inner portion of the tumors ranging from 38 to 74% of the total. Similarly, the CT-derived mass transport properties of the tumors had a high degree of heterogeneity, ranging from minimal difference to almost 200% difference between inner and outer portions of the tumor. Our quantitative method to derive transport properties from CT scans demonstrated less than 5% difference in gemcitabine prediction at the average CT-derived transport value across observers. These data illustrate significant inter-patient and intra-tumoral heterogeneity in the delivery of gemcitabine, and highlight how this variability can be reproducibly accounted for using principles of mass transport. With further validation as a biophysical marker, transport properties of tumors may be useful in patient selection for therapy and prediction of therapeutic outcome.
