Value of glycogen synthase 2 in intrahepatic cholangiocarcinoma prognosis assessment and its influence on the activity of cancer cells.

Intrahepatic cholangiocarcinoma (ICC) is the second most common primary liver tumor with increasing incidence worldwide. Metabolic reprogramming caused by metabolic related gene disorders is a prominent hallmark of tumors, among which Glycogen Synthase 2 (GYS2) is the key gene responsible for regulating cellular energy metabolism, and its expression disorders are closely related to various tumors and glycometabolic diseases. However, we still know nothing about its role in ICC. This study is intended to reveal the functional role of GYS2 in the ICC progress and explore the underlying mechanism. Based on the integrated pan-cancer analysis of GYS2 in the GEPIA database, the expression of GYS2 in paired ICC and adjacent non tumor tissues was detected by qPCR. It was found that the expression of GYS2 was significantly down-regulated in ICC. Further analysis showed that its low expression was not only associated with the degree of pathological differentiation, tumor size, microvascular invasion and lymph node metastasis, but also an independent risk factor for unfavorable prognosis. Functional studies have shown that GYS2 overexpression can significantly impair the proliferation, replication, cloning, migration and invasion of cholangiocarcinoma cells, while the silencing GYS2 dramatically promotes the development of the aforementioned phenotypes, the underlying mechanism may be that GYS2 activates the P53 pathway. In conclusions,low GYS2 expression in ICC predicted unfavorable patient outcomes; GYS2 overexpression could significantly impair the proliferation, migration and invasion of cholangiocarcinoma cells via activating the P53 pathway and GYS2 was expected to become a potential therapeutic target for such patients.

An assessment of the in vivo efficacy of the glycogen phosphorylase inhibitor GPi688 in rat models of hyperglycaemia.

BACKGROUND AND PURPOSE: Studies in cultured hepatocytes demonstrate glycogen synthase (GS) activation with glycogen phosphorylase (GP) inhibitors. The current study investigated whether these phenomena occurred in vivo using a novel GP inhibitor. EXPERIMENTAL APPROACH: An allosteric GP inhibitor, GPi688, was evaluated against both glucagon-mediated hyperglycaemia and oral glucose challenge-mediated hyperglycaemia to determine the relative effects against GP and GS in vivo. KEY RESULTS: In rat primary hepatocytes, GPi688 inhibited glucagons-mediated glucose output in a concentration dependent manner. Additionally GP activity was reduced and GS activity increased seven-fold. GPi688 inhibited glucagon-mediated hyperglycaemia in both Wistar (65%) & obese Zucker (100%) rats and demonstrated a long duration of action in the Zucker rat. The in vivo efficacy in the glucagon challenge model could be predicted by the equation; % glucagon inhibition=56.9+34.3[log ([free plasma]/rat IC50)], r=0.921). GPi688 also reduced the blood glucose of obese Zucker rats after a 7 h fast by 23%. In an oral glucose tolerance test in Zucker rats, however, GPi688 was less efficacious (7% reduction) than a glycogen synthase kinase-3 (GSK-3) inhibitor (22% reduction), despite also observing activation (by 45%) of GS in vivo. CONCLUSIONS AND IMPLICATIONS: Although GP inhibition can inhibit hyperglycaemia mediated by increased glucose production, the degree of GS activation induced by allosteric GP inhibitors in vivo, although discernible, is insufficient to increase glucose disposal. The data suggests that GP inhibitors might be more effective clinically against fasting rather than prandial hyperglycaemic control.

Maximum entropy, analysis of kinetic processes involving chemical and folding-unfolding changes in proteins.

We show that numerical inversion of the Laplace transform by using the maximum entropy method can be successfully applied to the analysis of complex kinetic processes involving chemical and folding-unfolding changes in proteins. First, we present analyses of simulated data which support that: (i) the maximum entropy calculation of rate distributions, combined with Monte Carlo analyses of the associated uncertainties, yields results consistent with the information actually supplied by the data, thus preventing their over-interpretation; (ii) maximum entropy analysis may be used to extract discrete rates (corresponding to individual exponential contributions), as well as broad rate distributions (provided, of course, that the adequate information is supplied by the data). We further illustrate the applicability of the maximum entropy analysis with experimental data corresponding to two nontrivial model processes: (a) the kinetics of chemical modification of sulfhydryl groups in glycogen synthase by reaction with Ellman's reagent; (b) the kinetics of folding of ribonuclease a under strongly folding conditions, as monitored by fluorescence and optical absorption. Finally, we discuss that the maximum entropy approach should be particularly useful in studies on protein folding kinetics, which generally involve the comparison between several complex kinetic profiles obtained by using different physical probes. Thus, protein folding kinetics is usually interpreted in terms of kinetic mechanisms involving a comparatively small number of kinetic steps between well-defined protein states. According to this picture, rate distributions derived from experimental kinetic profiles by maximum entropy analysis are expected to show a small number of comparatively narrow peaks, from which we can determine, without a priori assumptions, the number of exponential contributions required to describe each experimental kinetic profile (the number of peaks), together with their amplitudes (from the peak areas), time constant values (from the peak positions), and associated Monte Carlo uncertainties. On the other hand, recent theoretical studies describe protein folding kinetics in terms of the protein energy landscape (the multidimensional surface of energy versus conformational degrees of freedom), emphasize the difficulty in defining a single reaction coordinate for folding, and point out that individual chains may fold by multiple pathways. This indicates that, in some cases at least, folding kinetics might have to be described in terms of broad rate distributions (rather than in terms of a small number of discrete exponential contributions related to kinetic steps between well-defined protein states). We suggest that the maximum entropy procedures described in this work may provide a method to detect this situation and to derive such broad rate distributions from experimental data.