Programmed Death-Ligand 1 as a Regulator of Tumor Progression and Metastasis

Programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) immune checkpoint has long been implicated in modeling antitumor immunity; PD-1/PD-L1 axis inhibitors exert their antitumor effects by relieving PD-L1-mediated suppression on tumor-infiltrating T lymphocytes. However, recent studies have unveiled a distinct, tumor-intrinsic, potential role for PD-L1. In this review, we focus on tumor-intrinsic PD-L1 signaling and delve into preclinical evidence linking PD-L1 protein expression with features of epithelial-to-mesenchymal transition program, cancer stemness and known oncogenic pathways. We further summarize data from studies supporting the prognostic significance of PD-L1 in different tumor types. We show that PD-L1 may indeed have oncogenic potential and act as a regulator of tumor progression and metastasis.     

Engineering the xenobiotic substrate specificity of maize glutathione S-transferase I

Glutathione S-transferases (GSTs) are a heterogeneous family of enzymes that catalyse the conjugation of glutathione (GSH) to electrophilic sites on a variety of hydrophobic substrates. In the present study three amino acid residues (Trp12, Phe35 and Ile118) of the xenobiotic binding site (H-site) of maize GST I were altered in order to evaluate their contribution to substrate binding and catalysis. These residues are not conserved and hence may affect substrate specificity and/or product dissociation. The results demonstrate that these residues are important structural moieties that modulate an enzyme's catalytic efficiency and specificity. Phe35 and Ile118 also participate in k(cat) regulation by affecting the rate-limiting step of the catalytic reaction. The effect of temperature on the catalytic activity of the wild-type and mutant enzymes was also investigated. Biphasic Arrhenius and Eyring plots for the wild-type enzyme showed an apparent transition temperature at 35 degrees C, which seems to be the result of a change in the rate-limiting step of the catalytic reaction. Thermodynamic analysis of the activity data showed that the activation energy increases at low temperatures, whereas the entropy change seems to be the main determinant that contributes to the rate-limiting step at high temperatures.     

Evaluation of networks of randomized trials

Randomized trials may be designed and interpreted as single experiments or they may be seen in the context of other similar or relevant evidence. The amount and complexity of available randomized evidence vary for different topics. Systematic reviews may be useful in identifying gaps in the existing randomized evidence, pointing to discrepancies between trials, and planning future trials. A new, promising, but also very much debated extension of systematic reviews, mixed treatment comparison (MTC) meta-analysis, has become increasingly popular recently. MTC meta-analysis may have value in interpreting the available randomized evidence from networks of trials and can rank many different treatments, going beyond focusing on simple pairwise-comparisons. Nevertheless, the evaluation of networks also presents special challenges and caveats. In this article, we review the statistical methodology for MTC meta-analysis. We discuss the concept of inconsistency and methods that have been proposed to evaluate it as well as the methodological gaps that remain. We introduce the concepts of network geometry and asymmetry, and propose metrics for the evaluation of the asymmetry. Finally, we discuss the implications of inconsistency, network geometry and asymmetry in informing the planning of future trials.