Polymorphism Interaction to Predict Bevacizumab Efficacy — BEVAGENE  

Metastatic Breast Cancer Clinical Trial

Official title: Polymorphism Interaction to Predict Bevacizumab Efficacy in Advanced Breast Cancer Patients: an Exploratory Retrospective Analysis

Status Completed

Clinical Trial Summary

Although many attempts have been done to identify vascular endothelial growth factor-A (VEGF-A) single nucleotide polymorphisms (SNPs) correlated with bevacizumab response, in advanced cancer patients, the results are still inconclusive.

We will conduct a pharmacogenetic study to assess, in a population of metastatic breast cancer (MBC) patients, the possible predictive role of VEGF-A, VEGF receptor-2 (VEGFR-2), interleukin-8 (IL-8), hypoxia inducible factor-1α (HIF-1α), hypoxia inducible factor-2α (HIF-2α) and thrombospondin-1 (TSP-1) SNPs for bevacizumab response when combined with first-line paclitaxel and for progression free survival (PFS). Analyses will be performed on germline DNA obtained from blood samples and SNPs will be investigated by real-time polymerase chain reaction (PCR) technique. The multifactor dimensionality reduction (MDR) methodology will be applied to investigate the interaction between SNPs.

Clinical Trial Description

Metastatic breast cancer (MBC) patients from eight Italian divisions of Medical Oncology, with histologically confirmed HER2-negative MBC, treated with a first-line therapy including bevacizumab 10 mg/m2 i.v. on days 1 and 15 combined with first-line paclitaxel 90 mg/m2 i.v. on days 1, 8 and 15, every 4 weeks, will be enrolled for the present pharmacogenetic study. MBC patients treated with a first-line chemotherapy including paclitaxel without bevacizumab will be also enrolled as control group.

Sites of metastatic disease will be radiologically re-evaluated according to the Response Evaluation Criteria in Solid Tumors (RECIST) criteria 1.1, in patients with measurable disease. In patients without measurable lesions, progression of disease will be defined when new lesions appeared or when existing lesions evolved. Likewise, in the case of non measurable lesions, deterioration of clinical condition not due to treatment toxicity, will be defined as progression of disease.

Progression-free survival (PFS) will be defined as the period of time from the beginning of the treatment to the first observation of disease progression as above described, or death from any cause. All patients will be assessed for response, PFS and overall survival. Each patient entering the study will sign the informed consent. The protocol has been approved by ethic committee of Azienda Ospedaliera-Universitaria Pisana, Pisa, Italy, (CESM 3077/2010).

Genotyping analyses Blood samples (3 ml) will be collected in ethylenediaminetetraacetic acid (EDTA) tubes and stored at -80°C. Genes and polymorphisms involved in the angiogenesis pathway and already suggested as predictors of bevacizumab response, will be chosen for the present analyses. Germline DNA extraction will be performed using QIAamp DNA Blood Mini Kit (Qiagen, Valencia, California, USA). Allelic discrimination of genes will be performed using an ABI PRISM 7900 SDS instrument (Applied Biosystems, Carlsbad, California, USA) and with validated TaqMan® SNP genotyping assays (Applied Biosystems). PCR reactions will be carried out according to the manufacturer's protocol. Genotyping will be not performed until an adequate number of events (>80% on study population) will be reported in terms of PFS.

Statistical analysis The first aim of this retrospective analysis will be to evaluate the possible role of these investigated gene polymorphisms to predict the bevacizumab response in terms of PFS. The secondary end-points will be the correlations with overall survival (OS) and response rate. All polymorphisms will be analyzed for deviation from the Hardy-Weinberg Equilibrium (HWE) by means of comparison between observed allelic distributions with those expected from the HWE by on χ2 test. Any correlation between gene polymorphisms and response rate will be analyzed by the two-sided Fisher's Exact Test. The association between each individual polymorphism and the most relevant clinical-pathological characteristics with PFS will be tested using a Cox proportional hazards model. The Multifactor Dimensionality Reduction (MDR) methodology will be applied (using version 2.0 beta 6 of MDR software available on http://sourceforge.net/projects/mdr/) to investigate the role of an interaction between gene polymorphisms in identifying biomarkers of paclitaxel plus bevacizumab response.

The genotype combination with the highest PFS benefit correlated with an OS improvement will be chosen for further analyses. The difference in PFS between favourable genetic profiles and the unfavourable genetic profiles will be assessed with the log-rank test and the Kaplan-Meier method to evaluate survival curves. A Cox proportional hazards model, with the possible genetic profiles and the clinical and pathological patient characteristics individually correlated with the PFS, will be used to calculate the adjusted hazards ratio (HR) and the 95% confidence interval (95% CI). A P value of <0.05 will be accepted as statistically significant. The Kaplan-Meier and Cox proportional hazards analyses will be performed using the SPSS version 17.0 (SPSS, Chicago, IL). ;

Study Design

Observational Model: Cohort, Time Perspective: Retrospective

Related Conditions & MeSH terms

• Breast Neoplasms
• Metastatic Breast Cancer

• NCT number: NCT01935102
• Study type: Observational
• Source: University of Pisa
• Status: Completed
• Phase: N/A
• Start date: December 2012
• Completion date: December 2014