PURPOSE Anticipating toxicities with gemcitabine is an ongoing story, and deregulation in cytidine deaminase (CDA) could be associated with increased risk of developing early severe toxicities on drug exposure. PATIENTS AND METHODS A simple test to evaluate CDA phenotypic status was first validated in an animal model investigating relationships between CDA activity and gemcitabine-related toxicities. Next, relevance of this test as a marker for toxicities was retrospectively tested in a first subset of 64 adult patients treated with gemcitabine alone, then it was tested in a larger group of 130 patients who received gemcitabine either alone or combined with other drugs and in 20 children. Additionally, search for the 435 T>C, 208 G>A and 79 A>C mutations on the CDA gene was performed. Results In mice, CDA deficiency impacted on gemcitabine pharmacokinetics and had subsequent lethal toxicities. In human, 12% of adult patients experienced early severe toxicities after gemcitabine administration. A significant difference in CDA activities was observed between patients with and without toxicities (1.2 +/- 0.8 U/mg v 4 +/- 2.6 U/mg; P < .01). Conversely, no genotype-to-phenotype relationships were found. Of note, the patients who displayed particularly reduced CDA activity all experienced strong toxicities. Gemcitabine was well tolerated in children, and no CDA deficiency was evidenced. CONCLUSION Our data suggest that CDA functional testing could be a simple and easy marker to discriminate adult patients at risk of developing severe toxicities with gemcitabine. Particularly, this study demonstrates that CDA deficiency, found in 7% of adult patients, is associated with a maximum risk of developing early severe toxicities with gemcitabine.

Defining tumor stage at diagnosis is a pivotal point for clinical decisions about patient treatment strategies. In this respect, early detection of occult metastasis invisible to current imaging methods would have a major impact on best care and long-term survival. Mathematical models that describe metastatic spreading might estimate the risk of metastasis when no clinical evidence is available. In this study, we adapted a top-down model to make such estimates. The model was constituted by a transport equation describing metastatic growth and endowed with a boundary condition for metastatic emission. Model predictions were compared with experimental results from orthotopic breast tumor xenograft experiments conducted in Nod/Scidg mice. Primary tumor growth, metastatic spread and growth were monitored by 3D bioluminescence tomography. A tailored computational approach allowed the use of Monolix software for mixed-effects modeling with a partial differential equation model. Primary tumor growth was described best by Bertalanffy, West, and Gompertz models, which involve an initial exponential growth phase. All other tested models were rejected. The best metastatic model involved two parameters describing metastatic spreading and growth, respectively. Visual predictive check, analysis of residuals, and a bootstrap study validated the model. Coefficients of determination were R 2 ¼ 0:94 for primary tumor growth and R 2 ¼ 0:57 for metastatic growth. The data-based model development revealed several biologically significant findings. First, information on both growth and spreading can be obtained from measures of total metastatic burden. Second, the postulated link between primary tumor size and emission rate is validated. Finally, fast growing peritoneal metastases can only be described by such a complex partial differential equation model and not by ordinary differential equation models. This work advances efforts to predict metastatic spreading during the earliest stages of cancer. Cancer Res; 74(22); 6397-407. Ó2014 AACR.

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