Bcr-Abl stabilizes β-catenin in chronic myeloid leukemia through its tyrosine phosphorylation

Self-renewal of Bcr-Abl(+) chronic myeloid leukemia (CML) cells is sustained by a nuclear activated serine/threonine-(S/T) unphosphorylated β-catenin. Although β-catenin can be tyrosine (Y)-phosphorylated, the occurrence and biological relevance of this covalent modification in Bcr-Abl-associated leukemogenesis is unknown. Here we show that Bcr-Abl levels control the degree of β-catenin protein stabilization by affecting its Y/S/T-phospho content in CML cells. Bcr-Abl physically interacts with β-catenin, and its oncogenic tyrosine kinase activity is required to phosphorylate β-catenin at Y86 and Y654 residues. This Y-phospho β-catenin binds to the TCF4 transcription factor, thus representing a transcriptionally active pool. Imatinib, a Bcr-Abl antagonist, impairs the β-catenin/TCF-related transcription causing a rapid cytosolic retention of Y-unphosphorylated β-catenin, which presents an increased binding affinity for the Axin/GSK3β complex. Although Bcr-Abl does not affect GSK3β autophosphorylation, it prevents, through its effect on β-catenin Y phosphorylation, Axin/GSK3β binding to β-catenin and its subsequent S/T phosphorylation. Silencing of β-catenin by small interfering RNA inhibited proliferation and clonogenicity of Bcr-Abl(+) CML cells, in synergism with Imatinib. These findings indicate the Bcr-Abl triggered Y phosphorylation of β-catenin as a new mechanism responsible for its protein stabilization and nuclear signalling activation in CML

The econometrics of monetary policy: an overview

This chapter concentrates on the Econometrics of Monetary Policy. We describe the evolution of models estimated to evaluate the macroeconomic impact of monetary policy. We argue that the main challenge for the econometrics of monetary policy is the combination of theoretical models and information from the data to construct empirical models. The failure of the large econometrics models at the beginning of the 1970s might be explained by their incapability of taking proper account of both these aspects. The great critiques by Lucas and Sims have generated an alternative approach which, at least initially, has been almost entirely dominated by theory. The LSE approach has instead concentrated on the properties of the statistical models and on the best way of incorporating information from the data into the empirical models, paying little attention to the economic foundation of the adopted specification. The realization that the solution of a DSGE model can be approximated by a restricted VAR, which is also a statistical model, has generated a potential link between the two approaches. The open question is which type of VARs are most appropriate for the econometric analysis of monetary policy. JEL Classification: C10, C52, E50 Keywords:Econometrics, Monetary Policy, identification, DSGE, VAR, FAVA