1. Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN;
2. Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN;
3. Department of Medicine, Indiana University School of Medicine, Indianapolis, IN;
4. Scripps Research Institute, University of Medicine and Pharmac, La Jolla, CA.
# Current address: Department of Medicine, Stanford University, Palo Alto, CA.
* Current address: Thomas Jefferson University Hospitals, Philadelphia, PA.
Bevacizumab, the recombinant antibody targeting vascular endothelial growth factor (VEGF), improves progression-free but not overall survival in metastatic breast cancer. To seek further insights in resistance mechanisms to bevacizumab at the molecular level, we developed VEGF and non-VEGF-driven ER-positive MCF7-derived xenograft models allowing comparison of tumor response at different timepoints. VEGF gene (MV165) overexpressing xenografts were initially sensitive to bevacizumab, but eventually acquired resistance. In contrast, parental MCF7 cells derived tumors were de novo insensitive to bevacizumab. Microarray analysis with qRT-PCR validation revealed that Follistatin (FST) and NOTCH were the top signaling pathways associated with resistance in VEGF-driven tumors (P<0.05). Based on the presence of VEGF, treatment with bevacizumab resulted in altered patterns of metagenes and PAM50 gene expression. In VEGF-driven model after short and long-term bevacizumab treatments, a change in the intrinsic subtype (luminal to myoepithelial/basal-like) was observed in association with increased expression of genes implicated with cancer stem cell phenotype (P<0.05). Our results show that the presence or absence of VEGF expression affects the response to bevacizumab therapy and gene pathways. In particular, long-term bevacizumab treatment shifts the cancer cells to a more aggressive myoepithelial/basal subtype in VEGF-expressing model, but not in non-VEGF model. These findings could shed light on variable results to anti-VEGF therapy in patients and emphasize the importance of patient stratification based on the VEGF expression. Our data strongly suggest consideration of patient subgroups for treatment and designing novel combinatory therapies in the clinical setting.
Keywords: Bevacizumab, vascular endothelial growth factor, breast cancer, estrogen receptor, de novo and acquired resistance.