Assessment of RACGAP1 as a Prognostic and Immunological Biomarker in Multiple Human Tumors: A Multiomics Analysis.

Several recent studies have pointed out that arc GTPase activating protein 1 (RACGAP1) is a putative oncogene in many human tumors. However, to date, no pan-cancer analysis has been performed to study the different aspects of this gene expression and behavior in tumor tissues. Here, we applied several bioinformatics tools to perform a comprehensive analysis for RACGAP1. First, we assessed the expression of RACGAP1 in several types of human tumors and tried to correlate that with the stage of the tumors analyzed. We then performed a survival analysis to study the correlation between RACGAP1 upregulation in tumors and the clinical outcome. Additionally, we investigated the mutation forms, the correlation with several immune cell infiltration, the phosphorylation status of the interested protein in normal and tumor tissues, and the potential molecular mechanisms of RACGAP1 in cancerous tissue. The results demonstrated that RACGAP1, a highly expressed gene across several types of tumors, correlated with a poor prognosis in several types of human cancers. Moreover, it was found that RACGAP1 affects the tumor immune microenvironment by influencing the infiltration level of several immune cells. Collectively, the current study provides a comprehensive overview of the oncogenic roles of RACGAP1, where our results nominate it as a potential prognostic biomarker and a target for antitumor therapy development.

Design of a MAPK signalling cascade balances energetic cost versus accuracy of information transmission.

Cellular processes are inherently noisy, and the selection for accurate responses in presence of noise has likely shaped signalling networks. Here, we investigate the trade-off between accuracy of information transmission and its energetic cost for a mitogen-activated protein kinase (MAPK) signalling cascade. Our analysis of the pheromone response pathway of budding yeast suggests that dose-dependent induction of the negative transcriptional feedbacks in this network maximizes the information per unit energetic cost, rather than the information transmission capacity itself. We further demonstrate that futile cycling of MAPK phosphorylation and dephosphorylation has a measurable effect on growth fitness, with energy dissipation within the signalling cascade thus likely being subject to evolutionary selection. Considering optimization of accuracy versus the energetic cost of information processing, a concept well established in physics and engineering, may thus offer a general framework to understand the regulatory design of cellular signalling systems.

Establishment and Evaluation of a 6-Gene Survival Risk Assessment Model Related to Lung Adenocarcinoma Microenvironment.

OBJECTIVE: A survival risk assessment model associated with a lung adenocarcinoma (LUAD) microenvironment was established and evaluated to identify effective independent prognostic factors for LUAD. METHODS: The public data were downloaded from the TCGA database, and ESTIMATE prediction software was used to score immune cells and stromal cells for tumor purity prediction. The samples were divided into the high-score group and the low-score group by the median value of the immune score (or stromal score). The Wilcoxon test was used for differential analysis. GO and KEGG enrichment analysis of differentially expressed genes (DEGs) was performed using "clusterProfiler" of R package. Meanwhile, univariate and multivariate regression analysis was performed on DEGs to construct a multivariate Cox risk regression model with variable gene expression levels as independent prognostic factors affecting a tumor microenvironment (TME) and tumor immunity. RESULTS: This study found that LUAD patients with high immune cell (stromal cell) infiltration had better prognosis and were in earlier staging. Functional enrichment analysis revealed that most DEGs were related to the proliferation and activation of immune cells or stromal cells. A survival prediction model composed of 6 TME-related genes (CLEC17A, TAGAP, ABCC8, BCAN, FLT3, and CCR2) was established, and finally, the 6 feature genes closely related to the prognosis of LUAD were proved. The AUC value of the ROC curve in this model was 0.7, indicating that the model was reliable. CONCLUSION: Six genes related to the LUAD microenvironment have a predictive prognostic value in LUAD.

High-fat diet decreases energy expenditure and expression of genes controlling lipid metabolism, mitochondrial function and skeletal system development in the adipose tissue, along with increased expression of extracellular matrix remodelling- and inflammation-related genes.

The aim of the present study was to identify the genes differentially expressed in the visceral adipose tissue in a well-characterised mouse model of high-fat diet (HFD)-induced obesity. Male C57BL/6J mice (n 20) were fed either HFD (189 % of energy from fat) or low-fat diet (LFD, 42 % of energy from fat) for 16 weeks. HFD-fed mice exhibited obesity, insulin resistance, dyslipidaemia and adipose collagen accumulation, along with higher levels of plasma leptin, resistin and plasminogen activator inhibitor type 1, although there were no significant differences in plasma cytokine levels. Energy intake was similar in the two diet groups owing to lower food intake in the HFD group; however, energy expenditure was also lower in the HFD group than in the LFD group. Microarray analysis revealed that genes related to lipolysis, fatty acid metabolism, mitochondrial energy transduction, oxidation-reduction, insulin sensitivity and skeletal system development were down-regulated in HFD-fed mice, and genes associated with extracellular matrix (ECM) components, ECM remodelling and inflammation were up-regulated. The top ten up- or down-regulated genes include Acsm3, mt-Nd6, Fam13a, Cyp2e1, Rgs1 and Gpnmb, whose roles in the deterioration of obesity-associated adipose tissue are poorly understood. In conclusion, the genes identified here provide new therapeutic opportunities for prevention and treatment of diet-induced obesity.

Preliminary functional assessment and classification of DEPDC5 variants associated with focal epilepsy.

The mechanistic target of rapamycin complex 1 (TORC1) senses nutrient availability to regulate eukaryotic anabolic metabolism. In response to limiting concentrations of amino acids, TORC1 kinase activity is inhibited through the GATOR-1 complex. Mutations in DEPDC5, that encodes one of the components of the GATOR-1 complex, have recently been associated with different forms of focal epilepsy. Here, we investigate the effects of 10 DEPDC5 variants identified in individuals with focal epilepsy and two DEPDC5 variants identified in serous ovarian tumors, on TORC1 signaling and GATOR-1 complex formation. According to our functional assessment, three variants clearly disrupted the DEPDC5-dependent inhibition of TORC1. We did not obtain functional evidence to support pathogenicity in the remaining cases. The observed functional differences between the DEPDC5 variants might underlie some of the clinical differences observed in the individuals carrying the different variants.

Investigating differential dynamics of the MAPK signaling cascade using a multi-parametric global sensitivity analysis.

Cell growth critically depends on signalling pathways whose regulation is the focus of intense research. Without utilizing a priori knowledge of the relative importance of pathway components, we have applied in silico computational methods to the EGF-induced MAPK cascade. Specifically, we systematically perturbed the entire parameter space, including initial conditions, using a Monte Carlo approach, and investigate which protein components or kinetic reaction steps contribute to the differentiation of ERK responses. The model, based on previous work by Brightman and Fell (2000), is composed of 28 reactions, 27 protein molecules, and 48 parameters from both mass action and Michaelis-Menten kinetics. Our multi-parametric systems analysis confirms that Raf inactivation is one of the key steps regulating ERK responses to be either transient or sustained. Furthermore, the results of amplitude-differential ERK phosphorylations within the transient case are mainly attributed to the balance between activation and inactivation of Ras while duration-differential ERK responses for the sustained case are, in addition to Ras, markedly affected by dephospho-/phosphorylation of both MEK and ERK. Our sub-module perturbations showed that MEK and ERK's contribution to this differential ERK activation originates from fluctuations in intermediate pathway module components such as Ras and Raf, implicating a cooperative regulatory mode among the key components. The initial protein concentrations of corresponding reactions such as Ras, GAP, and Raf also influence the distinct signalling outputs of ERK activation. We then compare these results with those obtained from a single-parametric perturbation approach using an overall state sensitivity (OSS) analysis. The OSS findings indicate a more pronounced role of ERK's inhibitory feedback effect on catalysing the dissociation of the SOS complex. Both approaches reveal the presence of multiple specific reactions involved in the distinct dynamics of ERK responses and the cell fate decisions they trigger. This work adds a mechanistic insight of the contribution of key pathway components, thus may support the identification of biomarkers for pharmaceutical drug discovery processes.