ABSTRACT
Chronic lymphocytic leukemia (CLL) is a heterogeneous disease, whose presentation and clinical course are highly variable. Identification of novel prognostic factors may contribute to improving the CLL classification and providing indications for treatment options. The zinc finger protein ZNF224 plays a key role in cell transformation, through the control of apoptotic and survival pathways. In this study, we evaluated the potential application of ZNF224 as a novel marker of CLL progression and therapy responsiveness. To this aim, we analyzed ZNF224 expression levels in B lymphocytes from CLL patients at different stages of the disease and in patients showing different treatment outcomes. The expression of ZNF224 was significantly increased in disease progression and dramatically decreased in patients in complete remission after chemotherapy. Gene expression correlation analysis performed on datasets of CLL patients revealed that ZNF224 expression was well correlated with that of some prognostic and predictive markers. Moreover, bioinformatic analysis coupled ZNF224 to NF-κB pathway, and experimental data demonstrated that RNA interference of ZNF224 reduced the activity of the NF-κB survival pathway in CLL cells. Consistently with a pro-survival role, ZNF224 knockdown raised spontaneous and drug-induced apoptosis and inhibited the proliferation of peripheral blood mononuclear cells from CLL patients. Our findings provide evidence for the involvement of ZNF224 in the survival of CLL cells via NF-κB pathway modulation, and also suggest ZNF224 as a prognostic and predictive molecular marker of CLL disease.
ABSTRACT
Although the simple diffusion model can effectively describe the movement of eukaryotic cells on a culture surface observed at relatively low sampling frequency, at higher sampling rates more complex models are often necessary to better fit the experimental data. Currently available models can describe motion paths by involving additional parameters, such as linearity or directional persistence in time. However sometimes difficulties arise as it is not easy to effectively evaluate persistence in presence of a directional bias. Here we present a procedure which helps solve this problem, based on a model which describes displacement as the vectorial sum of three components: diffusion, persistence and directional bias. The described model has been tested by analysing the migratory behaviour of simulated cell populations and used to analyse a collection of experimental datasets, obtained by observing cell cultures in time lapse microscopy. Overall, the method produces a good description of migration behaviour as it appears to capture the expected increase in the directional bias in presence of wound without a large concomitant increase in the persistence module, allowing it to remain as a physically meaningful quantity in the presence of a directional stimulus.
