Endocrine Abstracts

Epidermal growth factor (EGF) and heregulin (HRG) act via ErbB receptors, to stimulate Akt and ERK. These drive breast cancer cell proliferation and the network is targeted in cancer therapy (1). Single cell responses show marked cell-cell variation and information theory provides statistical measures that take the effect this noise has on information transfer into account (2). Here we quantify the mutual information (MI) between stimulus concentration and effects in MCF7 cells as measures of information transfer, activating ErbB1 homodimers with EGF and ErbB2-ErbB3 heterodimers with HRG, and then using single cells measures of pAkt or ppERK (immunofluorescence staining and high content imaging) to calculate MI values (I(response;stimulus)). EGF caused the expected increases in pAkt and ppERK that were transient (maximal at 5 min and lost by 60 min) whereas HRG caused sustained increases in both. Maximal I(ppERK;stimulus) and I(pAkt;stimulus) values were comparable (˜0.7Bit). Both values mirrored kinetics of the population averaged phosphorylation responses (maximal at 5 min for EGF and comparable at 5–60 min for HRG) indicating that cell-cell heterogeneity does not scale with the population averaged responses, and when both responses were measured in parallel, joint sensing increased MI values by only ˜0.1 Bit. Thus, using this novel approach to quantify information transfer via ErbB receptors reveals that individual MCF7 cells are unreliable sensors of EGF and HRG concentration (with most information lost through signalling), and that concomitant activation of these two effectors does not greatly increase information transfer whereas agonist-induced receptor internalisation (that is rapid for ErbB1 homodimers but not for ErbB2-ErbB3 heterodimers) does reduce it in this model.

References

1. Yarden Y, Sliwkowski MX (2001) Untangling the ErbB signalling network. Molecular Cell Biology. 2:127.

2. Voliotis M et al. (2014) Information transfer by leaky, heterogeneous, protein kinase signaling systems. PNAS (USA). 111:E326.