Trial Information

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).