Metastatic spread is the single-most powerful predictor of poor outcome in Ewing sarcoma (ES). Therefore targeting pathways that drive metastasis has tremendous potential to reduce the burden of disease in ES. We previously showed that activation of the ERBB4 tyrosine kinase suppresses anoikis, or detachment-induced cell death, and induces chemoresistance in ES cell lines in vitro. We now show that ERBB4 is transcriptionally overexpressed in ES cell lines derived from chemoresistant or metastatic ES tumours. ERBB4 activates the PI3K-Akt cascade and focal adhesion kinase (FAK), and both pathways contribute to ERBB4-mediated activation of the Rac1 GTPase in vitro and in vivo. ERBB4 augments tumour invasion and metastasis in vivo, and these effects are blocked by ERBB4 knockdown. ERBB4 expression correlates significantly with reduced disease-free survival, and increased expression is observed in metastatic compared to primary patient-matched ES biopsies. Our findings identify a novel ERBB4-PI3K-Akt-FAK-Rac1 pathway associated with aggressive disease in ES. These results predict that therapeutic targeting of ERBB4, alone or in combination with cytotoxic agents, may suppress the metastatic phenotype in ES.

The behaviour of the French franc/deutschmark exchange rate is examined in this paper. During the time period studied, these currencies were constrained to lie within prescribed bands relative to one another and the usual random walk explanation of the exchange rate may not be appropriate. The data are examined for evidence of non-linear structure and it is shown that a piecewise linear SETAR model provides a better explanation and superior forecasting performance than a random walk.

The behaviour of the French franc/deutschmark exchange rate is examined in this paper. During the time period studied, these currencies were constrained to lie within prescribed bands relative to one another and the usual random walk explanation of the exchange rate may not be appropriate. The data are examined for evidence of non‐linear structure and it is shown that a piecewise linear SETAR model provides a better explanation and superior forecasting performance than a random walk.