Related Experiment Video
Updated: Sep 29, 2025

Tumor Treating Field Therapy in Combination with Bevacizumab for the Treatment of Recurrent Glioblastoma
Published on: October 27, 2014
A pharmacogenetic interaction analysis of bevacizumab with paclitaxel in advanced breast cancer patients
Luigi Coltelli1,2, Giacomo Allegrini1,2, Paola Orlandi3
1Department of Oncology, Azienda USL Toscana Nord Ovest, Pisa, Italy.
Abstract:
To investigate pharmacogenetic interactions among VEGF-A, VEGFR-2, IL-8, HIF-1α, EPAS-1, and TSP-1 SNPs and their role on progression-free survival (PFS) in metastatic breast cancer (MBC) patients treated with bevacizumab plus first-line paclitaxel or with paclitaxel alone. Analyses were performed on germline DNA, and SNPs were investigated by real-time PCR technique. The multifactor dimensionality reduction (MDR) methodology was applied to investigate the interaction between SNPs. The present study was an explorative, ambidirectional cohort study: 307 patients from 11 Oncology Units were evaluated retrospectively from 2009 to 2016, then followed prospectively (NCT01935102). Two hundred and fifteen patients were treated with paclitaxel and bevacizumab, whereas 92 patients with paclitaxel alone. In the bevacizumab plus paclitaxel group, the MDR software provided two pharmacogenetic interaction profiles consisting of the combination between specific VEGF-A rs833061 and VEGFR-2 rs1870377 genotypes. Median PFS for favorable genetic profile was 16.8 vs. the 10.6 months of unfavorable genetic profile (p = 0.0011). Cox proportional hazards model showed an adjusted hazard ratio of 0.64 (95% CI, 0.5-0.9; p = 0.004). Median OS for the favorable genetic profile was 39.6 vs. 28 months of unfavorable genetic profile (p = 0.0103). Cox proportional hazards model revealed an adjusted hazard ratio of 0.71 (95% CI, 0.5-1.01; p = 0.058). In the 92 patients treated with paclitaxel alone, the results showed no effect of the favorable genetic profile, as compared to the unfavorable genetic profile, either on the PFS (p = 0.509) and on the OS (p = 0.732). The pharmacogenetic statistical interaction between VEGF-A rs833061 and VEGFR-2 rs1870377 genotypes may identify a population of bevacizumab-treated patients with a better PFS.
Insights
Specific gene variants in VEGF-A and VEGFR-2 may predict better progression-free survival (PFS) for metastatic breast cancer patients treated with bevacizumab. This pharmacogenetic interaction highlights potential personalized treatment strategies.
Area of Science:
- Pharmacogenetics
- Oncology
- Genomics
Background:
- Metastatic breast cancer (MBC) treatment often involves chemotherapy combined with targeted therapies like bevacizumab.
- Identifying predictive biomarkers for treatment response is crucial for optimizing patient outcomes.
- Pharmacogenetic interactions can influence drug efficacy and toxicity.
Purpose of the Study:
- To investigate pharmacogenetic interactions among specific single nucleotide polymorphisms (SNPs) in VEGF-A, VEGFR-2, IL-8, HIF-1α, EPAS-1, and TSP-1.
- To determine the role of these SNPs in progression-free survival (PFS) and overall survival (OS) for MBC patients treated with bevacizumab plus paclitaxel or paclitaxel alone.
Main Methods:
- An ambidirectional cohort study involving 307 MBC patients treated between 2009 and 2016.
- Germline DNA was analyzed using real-time PCR to identify SNPs.
- Multifactor dimensionality reduction (MDR) was employed to analyze SNP interactions.
Main Results:
- A significant pharmacogenetic interaction between VEGF-A (rs833061) and VEGFR-2 (rs1870377) genotypes was identified in patients receiving bevacizumab plus paclitaxel.
- Patients with a favorable genetic profile demonstrated significantly longer median PFS (16.8 vs. 10.6 months) and OS (39.6 vs. 28 months).
- No significant effect of this genetic profile was observed in patients treated with paclitaxel alone.
Conclusions:
- The pharmacogenetic interaction between VEGF-A rs833061 and VEGFR-2 rs1870377 genotypes may identify MBC patients likely to benefit from bevacizumab treatment.
- This finding supports the potential for personalized medicine approaches in MBC by leveraging genetic biomarkers.
- Further validation is warranted to confirm these pharmacogenetic predictors in clinical practice.
Related Concept Videos
Combination Therapies and Personalized Medicine
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
Drugs that Stabilize Microtubules

