Genetic variability of VEGF pathway genes in six randomized phase III trials assessing the addition of bevacizumab to standard therapy
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Despite extensive translational research, no validated biomarkers predictive of bevacizumab treatment outcome have been identified.
We performed a meta-analysis of individual patient data from six randomized phase III trials in colorectal, pancreatic, lung, renal, breast, and gastric cancer to explore the potential relationships between 195 common genetic variants in the vascular endothelial growth factor (VEGF) pathway and bevacizumab treatment outcome.
The analysis included 1,402 patients (716 bevacizumab-treated and 686 placebo-treated). Twenty variants were associated (P < 0.05) with progression-free survival (PFS) in bevacizumab-treated patients. Of these, 4 variants in EPAS1 survived correction for multiple testing (q < 0.05). Genotype-by-treatment interaction tests revealed that, across these 20 variants, 3 variants in VEGF-C (rs12510099), EPAS1 (rs4953344), and IL8RA (rs2234671) were potentially predictive (P < 0.05), but not resistant to multiple testing (q > 0.05). A weak genotype-by-treatment interaction effect was also observed for rs699946 in VEGF-A, whereas Bayesian genewise analysis revealed that genetic variability in VHL was associated with PFS in the bevacizumab arm (q < 0.05). Variants in VEGF-A, EPAS1, and VHL were located in expression quantitative loci derived from lymphoblastoid cell lines, indicating that they affect the expression levels of their respective gene.
This large genetic analysis suggests that variants in VEGF-A, EPAS1, IL8RA, VHL, and VEGF-C have potential value in predicting bevacizumab treatment outcome across tumor types. Although these associations did not survive correction for multiple testing in a genotype-by-interaction analysis, they are among the strongest predictive effects reported to date for genetic variants and bevacizumab efficacy.
KeywordsAnti-angiogenesis Bevacizumab Treatment outcome Genetic variant Predictive and prognostic biomarker
We thank all patients who volunteered to participate in the genetic biomarker protocol of these studies and the research staff at the Vesalius Research Center, in particular Gilian Peuteman, Dominiek Smeets, and Thomas Van Brussel. The trials included in this analysis were sponsored and funded by F. Hoffmann-La Roche, Basel, Switzerland. Funding for statistical analyses and third-party medical writing support for this paper were also provided by F. Hoffmann-La Roche. Sanne de Haas and Paul Delmar are employees of F. Hoffmann-La Roche Ltd. Matthieu Moisse is supported by the Fund for Scientific Research Flanders (FWO). The work of Peter Carmeliet is funded by long-term structural funding Methusalem by the Flemish Government. Diether Lambrechts is supported by the Seventh Framework Programme of the European Community for Research (AngioPredict). The trials included in this analysis were sponsored and funded by F. Hoffmann-La Roche, Basel, Switzerland. Funding for statistical analyses and third-party medical writing support for this paper were also provided by F. Hoffmann-La Roche.
Conflict of interest
Sanne de Haas and Paul Delmar are employees of F. Hoffmann-La Roche, Basel, Switzerland. Aruna T. Bansal is a paid consultant of F. Hoffmann-La Roche. Eric Van Cutsem, Diether Lambrechts, and Peter Carmeliet have received research funding from F. Hoffmann-La Roche related to research into biomarkers for bevacizumab. David Miles has received honoraria from F. Hoffmann-La Roche for advisory boards and speaker engagements. Celine Pallaud is a former employee of F. Hoffmann-La Roche, Basel, Switzerland. Stefan Scherer is a former employee of Genentech. The remaining authors have declared no potential conflict of interest.
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