Advances in biological regulation最新文献

Genetic alterations of the PIK3CA gene, encoding the p110α catalytic subunit of PI3Kα enzyme, are found in a broad spectrum of human cancers. Many cancer-associated PIK3CA mutations occur at 3 hotspot locations and are termed canonical mutations. Canonical mutations result in hyperactivation of PI3K and promote oncogenesis via the PI3K/AKT/mTOR and PI3K/COX-2/PGE2 signaling pathways. These mutations also may serve as predictive biomarkers of response to PI3K inhibitors, as well as NSAID therapy. A large number of non-canonical PIK3CA mutations have also been identified in human tumors, but their functional properties are poorly understood. Here we review the landscape of PIK3CA mutations in different cancers and efforts underway to define the functional properties of non-canonical PIK3CA mutations. In addition, we summarize what has been learned from clinical trials of PI3K inhibitors as well as current trials incorporating these molecular targeting agents.

Mutated genes of the RAS family encoding small GTP-binding proteins drive numerous cancers, including pancreatic, colon and lung tumors. Besides the numerous effects of mutant RAS gene expression on aberrant proliferation, transformed phenotypes, metabolism, and therapy resistance, the most striking consequences of chronic RAS activation are changes of the genetic program. By performing systematic gene expression studies in cellular models that allow comparisons of pre-neoplastic with RAS-transformed cells, we and others have estimated that 7 percent or more of all transcripts are altered in conjunction with the expression of the oncogene. In this context, the number of up-regulated transcripts approximates that of down-regulated transcripts. While up-regulated transcription factors such as MYC, FOSL1, and HMGA2 have been identified and characterized as RAS-responsive drivers of the altered transcriptome, the suppressed factors have been less well studied as potential regulators of the genetic program and transformed phenotype in the breadth of their occurrence. We therefore have collected information on downregulated RAS-responsive factors and discuss their potential role as tumor suppressors that are likely to antagonize active cancer drivers. To better understand the active mechanisms that entail anti-RAS function and those that lead to loss of tumor suppressor activity, we focus on the tumor suppressor HREV107 (alias PLAAT3 [Phospholipase A and acyltransferase 3], PLA2G16 [Phospholipase A2, group XVI] and HRASLS3 [HRAS-like suppressor 3]). Inactivating HREV107 mutations in tumors are extremely rare, hence epigenetic causes modulated by the RAS pathway are likely to lead to down-regulation and loss of function.

Pancreatic islets are micro-organs composed of a mixture of endocrine and non-endocrine cells, where the former secrete hormones and peptides necessary for metabolic homeostasis. Through vasculature and innervation the cells within the islets are in communication with the rest of the body, while they interact with each other through juxtacrine, paracrine and autocrine signals, resulting in fine-tuned sensing and response to stimuli. In this context, cellular protrusion in islet cells, such as primary cilia and filopodia, have gained attention as potential signaling hubs. During the last decade, several pieces of evidence have shown how the primary cilium is required for islet vascularization, function and homeostasis. These findings have been possible thanks to the development of ciliary/basal body specific knockout models and technological advances in microscopy, which allow longitudinal monitoring of engrafted islets transplanted in the anterior chamber of the eye in living animals. Using this technique in combination with optogenetics, new potential paracrine interactions have been suggested. For example, reshaping and active movement of filopodia-like protrusions of δ-cells were visualized in vivo, suggesting a continuous cell remodeling to increase intercellular contacts. In this review, we discuss these recent discoveries regarding primary cilia and filopodia and their role in islet homeostasis and intercellular islet communication.

During the first year of the pandemic, East Asian countries have reported fewer infections, hospitalizations, and deaths from COVID-19 disease than most countries in Europe and the Americas. Our goal in this paper is to generate and evaluate hypothesis that may explain this striking fact. We consider five possible explanations: (1) population age structure (younger people tend to have less severe COVID-19 disease upon infection than older people); (2) the early adoption of lockdown strategies to control disease spread; (3) genetic differences between East Asian population and European and American populations that confer protection against COVID-19 disease; (4) seasonal and climactic contributors to COVID-19 spread; and (5) immunological differences between East Asian countries and the rest of the world. The evidence suggests that the first four hypotheses are unlikely to be important in explaining East Asian COVID-19 exceptionalism. Lockdowns, in particular, fail as an explanation because East Asian countries experienced similarly good infection outcomes despite vast differences in lockdown policies adopted by different countries to control the COVID-19 epidemic. The evidence to date is consistent with our fifth hypothesis – pre-existing immunity unique to East Asia – but there are still essential parts of this story left for scientists to check.

The counts of confirmed cases and deaths in isolated SARS-CoV-2 outbreaks follow the Gompertz growth function for locations of very different sizes. This lack of dependence on region size leads us to hypothesize that virus spread depends on the universal properties of the network of social interactions. We test this hypothesis by simulating the propagation of a virus on networks of different topologies or connectivities. Our main finding is that we can reproduce the Gompertz growth observed for many early outbreaks with a simple virus spread model on a scale-free network, in which nodes with many more neighbors than average are common. Nodes that have very many neighbors are infected early in the outbreak and then spread the infection very rapidly. When these nodes are no longer infectious, the remaining nodes that have most neighbors take over and continue to spread the infection. In this way, the rate of spread is fastest at the very start and slows down immediately. Geometrically we see that the "surface" of the epidemic, the number of susceptible nodes in contact with the infected nodes, starts to rapidly decrease very early in the epidemic and as soon as the larger nodes have been infected. In our simulation, the speed and impact of an outbreak depend on three parameters: the average number of contacts each node makes, the probability of being infected by a neighbor, and the probability of recovery. Intelligent interventions to reduce the impact of future outbreaks need to focus on these critical parameters in order to minimize economic and social collateral damage.

Mathematical models were used widely to inform policy during the COVID pandemic. However, there is a poor understanding of their limitations and how they influence decision-making. We used systematic review search methods to find early modelling studies that determined the reproduction number and analysed its use and application to interventions and policy in the UK. Up to March 2020, we found 42 reproduction number estimates (39 based on Chinese data: R₀ range 2.1–6.47). Several biases affect the quality of modelling studies that are infrequently discussed, and many factors contribute to significant differences in the results of individual studies that go beyond chance. The sources of effect estimates incorporated into mathematical models are unclear. There is often a lack of a relationship between transmission estimates and the timing of imposed restrictions, which is further affected by the lag in reporting. Modelling studies lack basic evidence-based methods that aid their quality assessment, reporting and critical appraisal. If used judiciously, models may be helpful, especially if they openly present the uncertainties and use sensitivity analyses extensively, which need to consider and explicitly discuss the limitations of the evidence. However, until the methodological and ethical issues are resolved, predictive models should be used cautiously.