Optimal sequencing of anti-HER2 therapy throughout the continuum of HER2-positive breast cancer: evidence and clinical considerations.

Abstract

With the advent of the monoclonal antibody trastuzumab over 2 decades ago for breast cancer therapy, the outcome of patients with human epidermal growth factor receptor (HER) 2-positive disease has improved dramatically. Based on its substantial efficacy and good tolerability, trastuzumab has become the therapeutic gold standard for early as well as advanced breast cancer. Nevertheless, despite adjuvant trastuzumab, patients do experience recurrence and require further anti-HER2-targeted therapy. Next to the small molecule tyrosine kinase inhibitor lapatinib, which was the first approved therapy option after trastuzumab failure, several new anti-HER2 agents are currently already available for clinical use [i.e. pertuzumab, T-DM1 (trastuzumab emtansine)] or are still being evaluated (e.g. afatinib, neratinib). Recent evidence from neoadjuvant as well as metastatic therapy suggests that dual blockade may be superior to single-agent HER2 blockade. While the number of available or potential therapies has increased considerably, no additional predictive biomarkers beyond HER2 have been validated for the use of the different anti-HER2 therapies. Moreover, novel therapeutic concepts such as the antibody-drug conjugate T-DM1 warrant excellent determination methodology for HER2 and suggest re-evaluation of tumor biology upon first metastasis. The clinical challenge remains to optimally choose, utilize, and sequence anti-HER2 therapy in early as well as metastatic breast cancer. This article will provide evidence-based guidance for sequencing anti-HER2 therapy throughout the continuum of breast cancer therapy.

DOI: 10.1007/s40265-013-0118-z

Cite this paper

@article{Harbeck2013OptimalSO, title={Optimal sequencing of anti-HER2 therapy throughout the continuum of HER2-positive breast cancer: evidence and clinical considerations.}, author={Nadia Harbeck and Rachel Wuerstlein}, journal={Drugs}, year={2013}, volume={73 15}, pages={1665-80} }