Targeting the ERBB-module in HER2-low breast cancer

About 70-80% of primary breast tumors show low or no detectable expression of HER2, however, other members of the ERBB family of receptor tyrosine kinases (RTK), EGFR and ERBB3, are frequently produced as potent drivers of tumor progression and of metastasis. The HER2Low consortium will therefore address the clinically relevant question, how to optimize treatment of breast cancer patients expressing HER2 at low to moderate levels. As a matter of fact, the complex interplay of different receptors can maintain downstream signaling even after inhibition of single receptors by targeted therapeutics.
The key hypothesis of HER2Low is that a comprehensive targeting of the EGFR/ERBB receptor module by suitable combinations of targeting drugs can efficiently shut down the cancer-driving signaling properties of this receptor module in individual tumors. Since not only in HER2-low breast cancer but also in metastatic disease, members of the ERBB family, ERBB3 in particular, are often upregulated, patients could potentially benefit from a combinatorial targeting of the RTK signaling network that we are out to decipher on a mechanistic level.
Along these lines, we will employ a systems medicine approach to identify strategies for an efficient inhibition of EGFR/ERBB receptors, and develop biological models of cellular systems expressing HER2 at low to moderate levels along with other EGFR/ERBB receptors. There, we will focus on drug response towards RG7160, pertuzumab, and RG7116 which are all therapeutic antibodies targeting EGFR, HER2, and ERBB3, respectively. Mathematical models will then be compared with quantitative data obtained from the analysis of clinical samples to validate patterns of drug response. Our final aim is to predict efficient drug combinations to steer personalized therapy decisions based on the proteomic profile of a tumor.


Subprojects in HER2Low:

SP 1   Dynamic data of drug response in cell line models of HER2-low breast cancer

SP 2   In vitro and in vivo testing of phenotypic model predictions

SP 3   ODE-based modeling of drug response in HER2-low breast cancer

SP 4   Pathway-activation profiling of clinical samples for biomarker discovery

Keywords: breast cancer, HER, ERBB, therapy, antibody, modelling

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