Angiogenesis

, Volume 17, Issue 4, pp 909–920 | Cite as

Genetic variability of VEGF pathway genes in six randomized phase III trials assessing the addition of bevacizumab to standard therapy

  • Sanne de Haas
  • Paul Delmar
  • Aruna T. Bansal
  • Matthieu Moisse
  • David W. Miles
  • Natasha Leighl
  • Bernard Escudier
  • Eric Van Cutsem
  • Peter Carmeliet
  • Stefan J. Scherer
  • Celine Pallaud
  • Diether Lambrechts
Original Paper

Abstract

Background

Despite extensive translational research, no validated biomarkers predictive of bevacizumab treatment outcome have been identified.

Methods

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.

Results

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.

Conclusions

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.

Keywords

Anti-angiogenesis Bevacizumab Treatment outcome Genetic variant Predictive and prognostic biomarker 

Supplementary material

10456_2014_9438_MOESM1_ESM.pdf (1.5 mb)
Supplementary material 1 (PDF 1550 kb)
10456_2014_9438_MOESM2_ESM.xls (150 kb)
Supplementary material 2 (XLS 150 kb)

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Sanne de Haas
    • 1
  • Paul Delmar
    • 1
  • Aruna T. Bansal
    • 2
  • Matthieu Moisse
    • 3
    • 4
  • David W. Miles
    • 5
  • Natasha Leighl
    • 6
  • Bernard Escudier
    • 7
  • Eric Van Cutsem
    • 8
  • Peter Carmeliet
    • 3
  • Stefan J. Scherer
    • 9
  • Celine Pallaud
    • 1
  • Diether Lambrechts
    • 3
    • 4
  1. 1.F. Hoffmann-La RocheBaselSwitzerland
  2. 2.Acclarogen Ltd, St John’s Innovation CentreCambridgeUK
  3. 3.Vesalius Research CenterVIBLouvainBelgium
  4. 4.Laboratory of Translational Genetics, Department of OncologyUniversity of Leuven3000 LouvainBelgium
  5. 5.Mount Vernon Cancer CentreNorthwoodUK
  6. 6.Department of MedicinePrincess Margaret HospitalTorontoCanada
  7. 7.Institut Gustave RoussyVillejuifFrance
  8. 8.Digestive OncologyUniversity Hospitals Leuven and KU LeuvenLouvainBelgium
  9. 9.Genentech Inc.South San FranciscoUSA

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