Carlos Bais1, Barbara Mueller1, Mark F Brady1, Robert S Mannel1, Robert A Burger1, Wei Wei1, Koen M Marien1, Mark M Kockx1, Amreen Husain1, Michael J Birrer1. 1. Genentech Inc., South San Francisco, CA; F Hoffmann-La Roche Ltd, Basel, Switzerland; NRG Statistical and Data Center, Roswell Park Cancer Institute, Buffalo, NY; University of Oklahoma, Oklahoma City, OK; Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, University of Pennsylvania, Philadelphia, PA; Center for Cancer Research, Gillette Center for Gynecologic Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA; HistoGeneX NV, Antwerp, Belgium; Division of Physiopharmacology, University of Antwerp, Antwerp, Belgium.
Abstract
Background: Combining bevacizumab with frontline chemotherapy statistically significantly improved progression-free survival (PFS) but not overall survival (OS) in the phase III GOG-0218 trial. Evaluation of candidate biomarkers was an exploratory objective. Methods:Patients with stage III (incompletely resected) or IV ovarian cancer were randomly assigned to receive six chemotherapy cycles with placebo or bevacizumab followed by single-agent placebo or bevacizumab. Five candidate tumor biomarkers were assessed by immunohistochemistry. The biomarker-evaluable population was categorized into high or low biomarker-expressing subgroups using median and quartile cutoffs. Associations between biomarker expression and efficacy were analyzed. All statistical tests were two-sided. Results: The biomarker-evaluable population (n = 980) comprising 78.5% of the intent-to-treat population had representative baseline characteristics and efficacy outcomes. Neither prognostic nor predictive associations were seen for vascular endothelial growth factor (VEGF) receptor-2, neuropilin-1, or MET. Higher microvessel density (MVD; measured by CD31) showed predictive value for PFS (hazard ratio [HR] for bevacizumab vs placebo = 0.40, 95% confidence interval [CI] = 0.29 to 0.54, vs 0.80, 95% CI = 0.59 to 1.07, for high vs low MVD, respectively, P interaction = .003) and OS (HR = 0.67, 95% CI = 0.51 to 0.88, vs 1.10, 95% CI = 0.84 to 1.44, P interaction = .02). Tumor VEGF-A was not predictive for PFS but showed potential predictive value for OS using a third-quartile cutoff for high VEGF-A expression. Conclusions: These retrospective tumor biomarker analyses suggest a positive association between density of vascular endothelial cells (the predominant cell type expressing VEGF receptors) and tumor VEGF-A levels and magnitude of bevacizumab effect in ovarian cancer. The potential predictive value of MVD (CD31) and tumor VEGF-A is consistent with a mechanism of action driven by VEGF-A signaling blockade.
RCT Entities:
Background: Combining bevacizumab with frontline chemotherapy statistically significantly improved progression-free survival (PFS) but not overall survival (OS) in the phase III GOG-0218 trial. Evaluation of candidate biomarkers was an exploratory objective. Methods:Patients with stage III (incompletely resected) or IV ovarian cancer were randomly assigned to receive six chemotherapy cycles with placebo or bevacizumab followed by single-agent placebo or bevacizumab. Five candidate tumor biomarkers were assessed by immunohistochemistry. The biomarker-evaluable population was categorized into high or low biomarker-expressing subgroups using median and quartile cutoffs. Associations between biomarker expression and efficacy were analyzed. All statistical tests were two-sided. Results: The biomarker-evaluable population (n = 980) comprising 78.5% of the intent-to-treat population had representative baseline characteristics and efficacy outcomes. Neither prognostic nor predictive associations were seen for vascular endothelial growth factor (VEGF) receptor-2, neuropilin-1, or MET. Higher microvessel density (MVD; measured by CD31) showed predictive value for PFS (hazard ratio [HR] for bevacizumab vs placebo = 0.40, 95% confidence interval [CI] = 0.29 to 0.54, vs 0.80, 95% CI = 0.59 to 1.07, for high vs low MVD, respectively, P interaction = .003) and OS (HR = 0.67, 95% CI = 0.51 to 0.88, vs 1.10, 95% CI = 0.84 to 1.44, P interaction = .02). TumorVEGF-A was not predictive for PFS but showed potential predictive value for OS using a third-quartile cutoff for high VEGF-A expression. Conclusions: These retrospective tumor biomarker analyses suggest a positive association between density of vascular endothelial cells (the predominant cell type expressing VEGF receptors) and tumorVEGF-A levels and magnitude of bevacizumab effect in ovarian cancer. The potential predictive value of MVD (CD31) and tumorVEGF-A is consistent with a mechanism of action driven by VEGF-A signaling blockade.
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