PKPD Modeling of VEGF, sVEGFR-2, sVEGFR-3 and sKIT as Biomarkers of Tumor Response and Overall Survival Following Sunitinib Treatment in GIST
Emma K. Hansson(1), Paul Westwood(1), Michael Amantea(2), Jonathan French (2), Brett Houk (2). Peter A. Milligan(2), Mats O. Karlsson(1), Lena E. Friberg(1)
(1) Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden; (2) Pfizer Global Research and Development
Objectives: The aim of the present study was to investigate potential biomarker relationships for tumor response and treatment outcome (overall survival) with focus on VEGF, sVEGFR-2, sVEGFR-3, and sKIT following Sutent® (sunitinib) treatment in patients with gastro-intestinal stromal tumors (GIST).
Methods: Data on the four biomarkers, tumor size and survival were available from 303 patients following up to 85 weeks of treatment with sunitinib and/or placebo. The time courses of the biomarkers were characterized by individual parameter estimates obtained from previously developed indirect-response models . Dose, daily AUC and relative change in biomarkers from baseline over time were evaluated to describe the longitudinal tumor size data with a tumor growth inhibition model . Observed tumor size at baseline was incorporated as a covariate acknowledging a residual error in the measurement . A logistic regression model for the time course of dropout was developed where different tumor size measures, time, AUC and progressive disease were evaluated as predictors. A time-to-event model with a hazard function including potential predictors such as tumor size/biomarker levels at baseline and relative change in tumor size/ biomarkers from baseline over time was developed to describe the survival over time.
Results: The predicted time course (relative to baseline) for sKIT described the longitudinal tumor size data statistically significantly better than dose or daily AUC. However, the model improved significantly when AUC and sVEGFR-3 were also added as predictors. Drop out was characterized by length of treatment, tumor size and progressive disease according to the RECIST criteria. The relative change in sVEGFR-3 over time and tumor size at baseline were significant predictors of survival.
Conclusions: The identified relationships between the circulating soluble proteins sKIT, sVEGFR-3 and tumor size and between tumor size, sVEGFR-3, and overall survival indicates a potential use of these biomarkers as early predictors of tumor response and clinical outcome in GIST. sKIT and sVEGFR-3 appear to be on the casual path of GIST and could be hypothesized to be a marker for the inhibitory effect of sunitinib on KIT (a kinase part of the pathogenesis) and for the anti-angiogenic activity.
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