Antiangiogenic therapy is a promising approach for the treatment of breast cancer. In practice, however, only a subset of patients who receive antiangiogenic drugs demonstrate a significant response. A key challenge, therefore, is to discover biomarkers that are predictive of response to antiangiogenic therapy. To address this issue, we have designed a window-of-opportunity study in which bevacizumab is administered as a short-term first-line treatment to primary breast cancer patients. Central to our approach is the use of a detailed pharmacodynamic assessment, consisting of pre- and post-bevacizumab multi-parametric magnetic resonance imaging scans and core biopsies for exon array gene expression analysis. Here, we illustrate three intrinsic patterns of response to bevacizumab and discuss the molecular mechanisms that may underpin each. Our results illustrate how the combination of dynamic imaging data and gene expression profiles can guide the development of biomarkers for predicting response to antiangiogenic therapy. © The Author 2011. Published by Oxford University Press. All rights reserved.

Assessing early therapeutic response to bevacizumab in primary breast cancer using magnetic resonance imaging and gene expression profiles

Buffa F. M.
Investigation
;
2011

Abstract

Antiangiogenic therapy is a promising approach for the treatment of breast cancer. In practice, however, only a subset of patients who receive antiangiogenic drugs demonstrate a significant response. A key challenge, therefore, is to discover biomarkers that are predictive of response to antiangiogenic therapy. To address this issue, we have designed a window-of-opportunity study in which bevacizumab is administered as a short-term first-line treatment to primary breast cancer patients. Central to our approach is the use of a detailed pharmacodynamic assessment, consisting of pre- and post-bevacizumab multi-parametric magnetic resonance imaging scans and core biopsies for exon array gene expression analysis. Here, we illustrate three intrinsic patterns of response to bevacizumab and discuss the molecular mechanisms that may underpin each. Our results illustrate how the combination of dynamic imaging data and gene expression profiles can guide the development of biomarkers for predicting response to antiangiogenic therapy. © The Author 2011. Published by Oxford University Press. All rights reserved.
2011
Mehta, S.; Hughes, N. P.; Buffa, F. M.; Li, S. P.; Adams, R. F.; Adwani, A.; Taylor, N. J.; Levitt, N. C.; Padhani, A. R.; Makris, A.; Harris, A. L.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11565/4061201
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