A Combined Genome-Wide Association Study (GWAS) and microRNA (miRNA) Profiling Approach for the Identification of Bevacizumab Response Predictors in Metastatic Breast Cancer

In certain solid neoplasias, antiangiogenic therapies improve response rates and time to progression. However, treatment with antiangiogenic drugs do not improve patient´s overall survival, in addition to being quite toxic and expensive. It is therefore critical to identify reliable predictive factors for drug efficacy and potential toxicity. Pharmacogenomics and pharmacogenetics are emerging as important tools in the optimization of different therapeutic strategies against cancer. Thus, gene expression profiling and genome-wide association studies (GWAS) offer the promise to more effectively tailor individual cancer treatments by identifying new biomarkers for clinical efficacy. They likely represent a real progress in our understanding of cancer as a complex process and an improvement in patient management and treatment. This grant proposal is aimed at: i) identify genetic variants (SNPs) responsible for the different bevacizumab treatment response observed in metastatic breast cancer patients and ii) determine specific blood microRNA (miRNA) signatures associated with the bevacizumab response The reference endpoint for patient selection will be progression free survival (PFS). To increase the statistical significance of the study, patients will be categorized in two groups: non-responders (PFS<12 weeks) and best responders (PFS>52 weeks). Blood samples will be drawn prospectively from selected patients, they will be processed to obtain purified total DNA and RNA and, finally, they will be analyzed by next-gen GWAS and miRNA profiling, respectively. DNA samples will be hybridized to ultrahigh density Omni microarrays, containing 2.5 million genetic variants while RNA samples will be hybridized to Affymetrix microarrays containing an up-to-date collection of human miRNA sequences (miRBase v15, 1105 human miRNA probes). Standard computational analysis of both sets of microarray data will performed and the results will be correlated with the main endpoint of the study (PFS).