Skip to main content

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

Angiogenesis volume 17, pages 909–920 (2014)Cite this article

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.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

References

  1. Hurwitz H, Fehrenbacher L, Novotny W et al (2004) Bevacizumab plus irinotecan, fluorouracil, and leucovorin for metastatic colorectal cancer. N Engl J Med 350(23):2335–2342. doi:10.1056/NEJMoa032691

    Article  PubMed  CAS  Google Scholar 

  2. Sandler A, Gray R, Perry MC et al (2006) Paclitaxel–carboplatin alone or with bevacizumab for non-small-cell lung cancer. N Engl J Med 355(24):2542–2550. doi:10.1056/NEJMoa061884

    Article  PubMed  CAS  Google Scholar 

  3. Miller K, Wang ML, Gralow J et al (2007) Paclitaxel plus bevacizumab versus paclitaxel alone for metastatic breast cancer. New Engl J Med 357(26):2666–2676. doi:10.1056/Nejmoa072113

    Article  PubMed  CAS  Google Scholar 

  4. Miles DW, Chan A, Dirix LY et al (2010) Phase III study of bevacizumab plus docetaxel compared with placebo plus docetaxel for the first-line treatment of human epidermal growth factor receptor 2-negative metastatic breast cancer. J Clin Oncol 28(20):3239–3247. doi:10.1200/JCO.2008.21.6457

    Article  PubMed  CAS  Google Scholar 

  5. Robert NJ, Dieras V, Glaspy J et al (2011) RIBBON-1: randomized, double-blind, placebo-controlled, phase III trial of chemotherapy with or without bevacizumab for first-line treatment of human epidermal growth factor receptor 2-negative, locally recurrent or metastatic breast cancer. J Clin Oncol 29(10):1252–1260. doi:10.1200/Jco.2010.28.0982

    Article  PubMed  CAS  Google Scholar 

  6. Escudier B, Pluzanska A, Koralewski P et al (2007) Bevacizumab plus interferon alfa-2a for treatment of metastatic renal cell carcinoma: a randomised, double-blind phase III trial. Lancet 370(9605):2103–2111. doi:10.1016/S0140-6736(07)61904-7

    Article  PubMed  Google Scholar 

  7. Burger RA, Brady MF, Bookman MA et al (2011) Incorporation of bevacizumab in the primary treatment of ovarian cancer. N Engl J Med 365(26):2473–2483. doi:10.1056/NEJMoa1104390

    Article  PubMed  CAS  Google Scholar 

  8. Perren TJ, Swart AM, Pfisterer J et al (2011) A phase 3 trial of bevacizumab in ovarian cancer. N Engl J Med 365(26):2484–2496. doi:10.1056/NEJMoa1103799

    Article  PubMed  CAS  Google Scholar 

  9. Aghajanian C, Blank SV, Goff BA et al (2012) OCEANS: a randomized, double-blind, placebo-controlled phase III trial of chemotherapy with or without bevacizumab in patients with platinum-sensitive recurrent epithelial ovarian, primary peritoneal, or fallopian tube cancer. J Clin Oncol 30(17):2039–2045. doi:10.1200/Jco.2012.42.0505

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  10. Henriksoon R, Bottomley A, Mason W, Saran F, Wick W, Nishikawa R (2013) Progression-free survival and health-related quality of life in AVAglio, a phase III study of bevacizumab, temozolomide, and radiotherapy in newly diagnosed glioblastoma. J Clin Oncol 31 (Suppl. abstr 2005). http://meetinglibrary.asco.org/content/114612-132

  11. Maru D, Venook AP, Ellis LM (2013) Predictive biomarkers for bevacizumab: are we there yet? Clin Cancer Res 19(11):2824–2827. doi:10.1158/1078-0432.Ccr-12-3409

    Article  PubMed  CAS  Google Scholar 

  12. Sennino B, McDonald DM (2012) Controlling escape from angiogenesis inhibitors. Nat Rev Cancer 12(10):699–709. doi:10.1038/Nrc3366

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  13. Bergers G, Hanahan D (2008) Modes of resistance to anti-angiogenic therapy. Nat Rev Cancer 8(8):592–603. doi:10.1038/Nrc2442

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  14. Eichten A, Adler AP, Cooper B et al (2013) Rapid decrease in tumor perfusion following VEGF blockade predicts long-term tumor growth inhibition in preclinical tumor models. Angiogenesis 16(2):429–441. doi:10.1007/s10456-012-9328-3

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  15. Lambrechts D, Lenz HJ, de Haas S, Carmeliet P, Scherer SJ (2013) Markers of response for the antiangiogenic agent bevacizumab. J Clin Oncol 31(9):1219–1230. doi:10.1200/Jco.2012.46.2762

    Article  PubMed  CAS  Google Scholar 

  16. Brauer MJ, Zhuang GL, Schmidt M et al (2013) Identification and analysis of in vivo VEGF downstream markers link VEGF pathway activity with efficacy of anti-VEGF therapies. Clin Cancer Res 19(13):3681–3692. doi:10.1158/1078-0432.Ccr-12-3635

    Article  PubMed  CAS  Google Scholar 

  17. Hegde PS, Jubb AM, Chen DF et al (2013) Predictive impact of circulating vascular endothelial growth factor in four phase III trials evaluating bevacizumab. Clin Cancer Res 19(4):929–937. doi:10.1158/1078-0432.Ccr-12-2535

    Article  PubMed  CAS  Google Scholar 

  18. Loupakis F, Cremolini C, Fioravanti A et al (2011) Pharmacodynamic and pharmacogenetic angiogenesis-related markers of first-line FOLFOXIRI plus bevacizumab schedule in metastatic colorectal cancer. Br J Cancer 104(8):1262–1269. doi:10.1038/Bjc.2011.85

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  19. Zhang W, Dahlberg SE, Yang D et al (2009) Genetic variants in angiogenesis pathway associated with clinical outcome in NSCLC patients (pts) treated with bevacizumab in combination with carboplatin and paclitaxel: subset pharmacogenetic analysis of ECOG 4599 [abstr 8032]. J Clin Oncol 27(15 Suppl.):414s. http://meetinglibrary.asco.org/content/33186-65

  20. Schneider BP, Wang M, Radovich M et al (2008) Association of vascular endothelial growth factor and vascular endothelial growth factor receptor-2 genetic polymorphisms with outcome in a trial of paclitaxel compared with paclitaxel plus bevacizumab in advanced breast cancer: ECOG 2100. J Clin Oncol 26(28):4672–4678. doi:10.1200/JCO.2008.16.1612

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  21. Jubb AM, Harris AL (2010) Biomarkers to predict the clinical efficacy of bevacizumab in cancer. Lancet Oncol 11(12):1172–1183. doi:10.1016/S1470-2045(10)70232-1

    Article  PubMed  CAS  Google Scholar 

  22. Gerger A, El-Khoueiry A, Zhang W et al (2011) Pharmacogenetic angiogenesis profiling for first-line bevacizumab plus oxaliplatin-based chemotherapy in patients with metastatic colorectal cancer. Clin Cancer Res 17(17):5783–5792. doi:10.1158/1078-0432.CCR-11-1115

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  23. Lambrechts D, Claes B, Delmar P et al (2012) VEGF pathway genetic variants as biomarkers of treatment outcome with bevacizumab: an analysis of data from the AViTA and AVOREN randomised trials. Lancet Oncol 13(7):724–733. doi:10.1016/S1470-2045(12)70231-0

    Article  PubMed  CAS  Google Scholar 

  24. Hansen TF, Christensen RD, Andersen RF, Spindler KLG, Johnsson A, Jakobsen A (2012) The predictive value of single nucleotide polymorphisms in the VEGF system to the efficacy of first-line treatment with bevacizumab plus chemotherapy in patients with metastatic colorectal cancer results from the Nordic ACT trial. Int J Colorectal Dis 27(6):715–720. doi:10.1007/S00384-011-1382-6

    Article  PubMed  Google Scholar 

  25. Schneider BP, Gray RJ, Radovich M et al (2013) Prognostic and predictive value of tumor vascular endothelial growth factor gene amplification in metastatic breast cancer treated with paclitaxel with and without bevacizumab; results from ECOG 2100 trial. Clin Cancer Res 19(5):1281–1289. doi:10.1158/1078-0432.Ccr-12-3029

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  26. Loupakis F, Cremolini C, Dongyun Y et al (2013) Prospective validation of candidate SNPs of VEGF/VEGFR pathway in metastatic colorectal cancer patients treated with first-line FOLFIRI plus bevacizumab. Plos One 8(7):e66774. doi:10.1371/journal.pone.0066774

  27. Van Cutsem E, Vervenne WL, Bennouna J et al (2009) Phase III trial of bevacizumab in combination with gemcitabine and erlotinib in patients with metastatic pancreatic cancer. J Clin Oncol 27(13):2231–2237. doi:10.1200/JCO.2008.20.0238

    Article  PubMed  Google Scholar 

  28. Reck M, von Pawel J, Zatloukal P et al (2009) Phase III trial of cisplatin plus gemcitabine with either placebo or bevacizumab as first-line therapy for nonsquamous non-small-cell lung cancer: AVAiL. J Clin Oncol 27(8):1227–1234. doi:10.1200/Jco.2007.14.5466

    Article  PubMed  CAS  Google Scholar 

  29. Ohtsu A, Shah MA, Van Cutsem E et al (2011) Bevacizumab in combination with chemotherapy as first-line therapy in advanced gastric cancer: a randomized, double-blind, placebo-controlled phase III study. J Clin Oncol 29(30):3968–3976. doi:10.1200/Jco.2011.36.2236

    Article  PubMed  CAS  Google Scholar 

  30. Barret JC (2009) Haploview: visualization and analysis of SNP genotype data. Cold Spring Harb Protoc 10:pdb.ip71. doi:10.1101/pdb.ip71

    Google Scholar 

  31. Pettersson FH, Anderson CA, Clarke GM et al (2009) Marker selection for genetic case–control association studies. Nat Protoc 4(5):743–752. doi:10.1038/Nprot.2009.38

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  32. Lambrechts D, Moisse M, Delmar P et al (2014) Genetic markers of bevacizumab-induced hypertension. Angiogenesis. doi:10.1007/s10456-014-9424-7

    Google Scholar 

  33. Grundberg E, Small KS, Hedman AK et al (2012) Mapping cis- and trans-regulatory effects across multiple tissues in twins. Nat Genet 44(10):1084–1089. doi:10.1038/ng.2394

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  34. Yang TP, Beazley C, Montgomery SB et al (2010) Genevar: a database and Java application for the analysis and visualization of SNP-gene associations in eQTL studies. Bioinformatics 26(19):2474–2476. doi:10.1093/bioinformatics/btq452

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  35. Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate—a practical and powerful approach to multiple testing. J R Stat Soc B 57(1):289–300

    Google Scholar 

  36. Goeman JJ, van de Geer SA, de Kort F, van Houwelingen HC (2004) A global test for groups of genes: testing association with clinical outcome. Bioinformatics 20:93–99

    Article  PubMed  CAS  Google Scholar 

  37. Goeman JJ, Oosting J, Cleton-Jansen AM, Anninga JK, van Houwelingen HC (2005) Testing association of a pathway with survival using gene expression data. Bioinformatics 21(9):1950–1957. doi:10.1093/Bioinformatics/Bti267

    Article  PubMed  CAS  Google Scholar 

  38. Zou H, Hastie T (2005) Regularization and variable selection via the elastic net. J R Stat Soc B 67:301–320. doi:10.1111/J.1467-9868.2005.00503.X

    Article  Google Scholar 

  39. Friedman J, Hastie T, Tibshirani R (2008) Regularization paths for generalized linear models via coordinate descent. J Stat Soft 33:1–22

    Google Scholar 

  40. Simon N, Friedman J, Hastie T, Tibshirani R (2011) Regularization paths for Cox’s proportional hazards model via coordinate descent. J Stat Soft 39:1–13

    Google Scholar 

  41. Choi I, Lee YS, Chung HK et al (2013) Interleukin-8 reduces post-surgical lymphedema formation by promoting lymphatic vessel regeneration. Angiogenesis 16(1):29–44. doi:10.1007/s10456-012-9297-6

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  42. Nakata I, Yamashiro K, Nakanishi H, Tsujikawa A, Otani A, Yoshimura N (2011) VEGF gene polymorphism and response to intravitreal bevacizumab and triple therapy in age-related macular degeneration. Jpn J Ophthalmol 55(5):435–443. doi:10.1007/S10384-011-0061-Z

    Article  PubMed  CAS  Google Scholar 

  43. Chen J, Michan S, Juan AM et al (2013) Neuronal sirtuin1 mediates retinal vascular regeneration in oxygen-induced ischemic retinopathy. Angiogenesis 16(4):985–992. doi:10.1007/s10456-013-9374-5

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  44. Xia GB, Kageyama Y, Hayashi T, Kawakami S, Yoshida M, Kihara M (2001) Regulation of vascular endothelial growth factor transcription by endothelial PAS domain protein 1 (EPAS1) and possible involvement of EPAS1 in the angiogenesis of renal cell carcinoma. Cancer 91(8):1429–1436. doi:10.1002/1097-0142(20010415)91:8<1429:Aid-Cncr1149>3.0.Co;2-V

    Article  PubMed  CAS  Google Scholar 

  45. Favier J, Plouin PF, Corvol P, Gasc JM (2002) Angiogenesis and vascular architecture in pheochromocytomas—distinctive traits in malignant tumors. Am J Pathol 161(4):1235–1246. doi:10.1016/S0002-9440(10)64400-8

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  46. Favier J, Lapointe S, Maliba R, Sirois MG (2007) HIF2 alpha reduces growth rate but promotes angiogenesis in a mouse model of neuroblastoma. BMC Cancer 7. doi:10.1186/1471-2407-7-139

  47. Keith B, Johnson RS, Simon MC (2011) HIF1α and HIF2α: sibling rivalry in hypoxic tumour growth and progression. Nat Rev Cancer 12:9–22

    PubMed  PubMed Central  Google Scholar 

  48. Jubb AM, Turley H, Moeller HC et al (2009) Expression of delta-like ligand 4 (Dll4) and markers of hypoxia in colon cancer. Br J Cancer 101(10):1749–1757. doi:10.1038/Sj.Bjc.6605368

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  49. Talks KL, Turley H, Gatter KC et al (2000) The expression and distribution of the hypoxia-inducible factors HIF-1 alpha and HIF-2 alpha in normal human tissues, cancers, and tumor-associated macrophages. Am J Pathol 157(2):411–421. doi:10.1016/S0002-9440(10)64554-3

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  50. Shay JES, Simon MC (2012) Hypoxia-inducible factors: crosstalk between inflammation and metabolism. Semin Cell Dev Biol 23(4):389–394. doi:10.1016/J.Semcdb.04.004

    Article  PubMed  CAS  Google Scholar 

  51. Simonson TS, Yang YZ, Huff CD et al (2010) Genetic evidence for high-altitude adaptation in Tibet. Science 329(5987):72–75. doi:10.1126/Science.1189406

    Article  PubMed  CAS  Google Scholar 

  52. Yi X, Liang Y, Huerta-Sanchez E et al (2010) Sequencing of 50 human exomes reveals adaptation to high altitude. Science 329(5987):75–78. doi:10.1126/Science.1190371

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  53. Beall CM, Cavalleri GL, Deng LB et al (2010) Natural selection on EPAS1 (HIF2 alpha) associated with low hemoglobin concentration in Tibetan highlanders. Proc Natl Acad Sci USA 107(25):11459–11464. doi:10.1073/Pnas.1002443107

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  54. Lambrechts D, Storkebaum E, Morimoto M et al (2003) VEGF is a modifier of amyotrophic lateral sclerosis in mice and humans and protects motoneurons against ischemic death. Nat Genet 34(4):383–394. doi:10.1038/ng1211

    Article  PubMed  CAS  Google Scholar 

  55. Han SW, Kim GW, Seo JS et al (2004) VEGF gene polymorphisms and susceptibility to rheumatoid arthritis. Rheumatology (Oxf) 43(9):1173–1177. doi:10.1093/rheumatology/keh281

    Article  CAS  Google Scholar 

Download references

Acknowledgments

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.

Author information

Authors and Affiliations

  1. F. Hoffmann-La Roche, Basel, Switzerland

    Sanne de Haas, Paul Delmar & Celine Pallaud

  2. Acclarogen Ltd, St John’s Innovation Centre, Cambridge, UK

    Aruna T. Bansal

  3. Vesalius Research Center, VIB, Herestraat 49 Box 912, 3000, Louvain, Belgium

    Matthieu Moisse, Peter Carmeliet & Diether Lambrechts

  4. Laboratory of Translational Genetics, Department of Oncology, University of Leuven, Herestraat 49 Box 912, 3000 Louvain, Belgium

    Matthieu Moisse & Diether Lambrechts

  5. Mount Vernon Cancer Centre, Northwood, UK

    David W. Miles

  6. Department of Medicine, Princess Margaret Hospital, Toronto, ON, Canada

    Natasha Leighl

  7. Institut Gustave Roussy, Villejuif, France

    Bernard Escudier

  8. Digestive Oncology, University Hospitals Leuven and KU Leuven, Louvain, Belgium

    Eric Van Cutsem

  9. Genentech Inc., South San Francisco, CA, USA

    Stefan J. Scherer

Authors
  1. Sanne de Haas
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Paul Delmar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Aruna T. Bansal
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Matthieu Moisse
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. David W. Miles
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Natasha Leighl
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Bernard Escudier
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Eric Van Cutsem
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Peter Carmeliet
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Stefan J. Scherer
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Celine Pallaud
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Diether Lambrechts
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Diether Lambrechts.

Additional information

Sanne de Haas and Paul Delmar have contributed equally to this work.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PDF 1550 kb)

Supplementary material 2 (XLS 150 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

de Haas, S., Delmar, P., Bansal, A.T. et al. Genetic variability of VEGF pathway genes in six randomized phase III trials assessing the addition of bevacizumab to standard therapy. Angiogenesis 17, 909–920 (2014). https://doi.org/10.1007/s10456-014-9438-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10456-014-9438-1

Keywords

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