Tumor Microvessel Density as a Potential Predictive Marker for Bevacizumab Benefit: GOG-0218 Biomarker Analyses

J Natl Cancer Inst. 2017 Nov 1;109(11):djx066. doi: 10.1093/jnci/djx066.

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.

Publication types

  • Clinical Trial, Phase III
  • Randomized Controlled Trial
  • Research Support, Non-U.S. Gov't
  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Angiogenesis Inhibitors / therapeutic use*
  • Antineoplastic Combined Chemotherapy Protocols / therapeutic use*
  • Bevacizumab / therapeutic use*
  • Biomarkers, Tumor / analysis*
  • Biomarkers, Tumor / metabolism
  • Carboplatin / administration & dosage
  • Confidence Intervals
  • Disease-Free Survival
  • Double-Blind Method
  • Drug Administration Schedule
  • Female
  • Humans
  • Intention to Treat Analysis
  • Microvessels
  • Middle Aged
  • Neuropilin-1 / metabolism
  • Ovarian Neoplasms / blood supply*
  • Ovarian Neoplasms / drug therapy*
  • Ovarian Neoplasms / metabolism
  • Ovarian Neoplasms / pathology
  • Paclitaxel / administration & dosage
  • Platelet Endothelial Cell Adhesion Molecule-1 / analysis
  • Proto-Oncogene Proteins c-met / metabolism
  • Retrospective Studies
  • Vascular Endothelial Growth Factor A / metabolism
  • Vascular Endothelial Growth Factor Receptor-2 / metabolism

Substances

  • Angiogenesis Inhibitors
  • Biomarkers, Tumor
  • Platelet Endothelial Cell Adhesion Molecule-1
  • Vascular Endothelial Growth Factor A
  • Neuropilin-1
  • Bevacizumab
  • Carboplatin
  • MET protein, human
  • Proto-Oncogene Proteins c-met
  • Vascular Endothelial Growth Factor Receptor-2
  • Paclitaxel