Metastatic Breast Cancer (MBC) patients from ten 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 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 measurables lesions, progression of disease will be defined when new lesions appeared or when existing lesions evolved. In the case of non measurables lesions, deterioration of clinical condition not due to treatment toxicity, will be defined as progression 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 for response, PFS and overall survival. Each patient entering the study will sign the informed consent. The protocol has been approved by Ethics Committee Vast Area Northwest of Tuscany (CEAVNO), Pisa, Italy (30/04/2014). Genotyping analyses blood samples (3 ml.) will be collected in ethylenediaminetetraacetic acid 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 QIamp 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 single nucleotide polymorphism (SNP) genotyping assays (Applied Byosistems). Polymerase chain 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 prospective analysis will be evaluate the possible role of VEGFR-2 rs11133360/IL-8 rs4073 polymorphism genetic interaction 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 x2 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. Tha Kaplan-Meier and Cox proportional hazards analyses will be performed using the SPSS version 17.0 (SPSS, Chicago, IL).
