A prognostic biomarker NRG1 promotes U-87 MG glioblastoma cell malignancy by inhibiting autophagy via ERBB2/AKT/mTOR pathway.

Glioblastoma (GBM) is the most common and aggressive primary brain malignancy. Studies have shown that autophagy-related (ATG) genes play important roles in regulating GBM malignancy. However, the mechanism still needs to be fully elucidated. Based on clinical and gene expression information of GBM patients downloaded from The The Cancer Genome Atlas database, Kaplan-Meier, univariate Cox regression, least absolute shrinkage and selection operator regression and multivariate Cox regression were applied to construct a risk signature for GBM prognosis, followed by validation using receiver operating characteristic analysis. Next, Cell Counting Kit-8, wound healing assay, flow cytometry, monodansyl cadaverine autophagy staining assay, immunofluorescence staining and western blot, either in the absence or presence of ERBB2/AKT/mTOR inhibitors, were carried out in GBM U87 cell line to explore molecular pathway underlying GBM malignancy. A three-ATG-gene signature (HIF1A, ITGA3, and NGR1) was constructed for GBM prognosis with the greatest contribution from NRG1. In vitro experiments showed that NRG1 promoted U87 cell migration and proliferation by inhibiting autophagy, and ERBB2/AKT/mTOR is a downstream pathway that mediates the autophagy-inhibitory effects of NRG1. We constructed an ATG gene prognostic model for GBM and demonstrated that NRG1 inhibited autophagy by activating ERBB2/AKT/mTOR, promoting GBM malignancy, thus providing new insights into the molecular contribution of autophagy in GBM malignancy.

Three Oxidative Stress-Related Genes That Associate Endometrial Immune Cells Are Considered as Potential Biomarkers for the Prediction of Unexplained Recurrent Implantation Failure.

Recurrent implantation failure (RIF) represents a new challenge in the field of assisted reproductive technology (ART). Considering the known effects of immune cell regulation on embryo implantation process, as well as our gene set variation analysis (GSVA) results that suggested the association between RIF and pathways of oxidative stress and immune responses, we hypothesized that oxidative stress- related genes (OSGs) associated with aberrant immunological factor may represent novel biomarkers for unexplained RIF. We therefore screened out the immune cell coexpressed OSGs by performing CIBERSORT, LM22 matrix and Pearson correlation, followed by constructing an OSG signature by least absolute shrinkage and selection operator (LASSO) regression. Three OSGs (AXL, SLC7A11 and UBQLN1) were then identified to establish a RIF risk signature, which showed high ability to discriminating RIF from fertile control. A nomogram was established, with a free online calculator for easier clinical application. Finally, Chilibot, protein-protein interaction analysis and BioGPS were sequentially applied for the investigation of functional relationships of these three genes with RIF and other OSGs, as well as their expression abundance across different human tissues. In conclusion, we identified an OSG signature that are relevant novel markers for the occurrence of unexplained RIF.

Identification of long non-coding RNA biomarkers and signature scoring, with competing endogenous RNA networks- targeted drug candidates for recurrent implantation failure.

Recurrent implantation failure (RIF) remains a source of frustration and presents challenges to clinicians in the practice of assisted reproductive technology (ART). Long non-coding RNAs (lncRNAs) are increasingly recognised as potential biomarkers in various diseases. In this study, eight differentially expressed lncRNAs (LINC00645, LINC00844, LINC02349, AC010975.1, AC022034.1, AC096719.1, AC104072.1 and DLGAP1-AS3) to distinguish RIF from fertile women were identified by RobustRankAggreg (RRA). A two-lncRNA signature for predicting RIF was established by least absolute shrinkage and selection operator (LASSO) regression, with accuracy confirmed by receiver operating characteristic (ROC) curves. After lncRNA-microRNA-mRNA regulatory networks were established by Cytoscape 3.7.2, Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) analyses were performed, suggesting that the lncRNA-miRNA-mRNA regulatory networks were associated with biological processes involved in endometrial receptivity. Finally, three putative drugs (miconazole, terfenadine and STOCK1N-35215) for RIF were predicted by a Connectivity Map. In conclusion, we identified eight lncRNA biomarkers and a two-lncRNA signature for predicting RIF, as well as proposing three candidate drugs against RIF by targeting the ceRNA networks.

Identification and validation of a five-lncRNA signature for predicting survival with targeted drug candidates in ovarian cancer.

The dysregulation of long non-coding RNAs (lncRNAs) plays a crucial role in ovarian cancer (OC). In this study, we screened out five differentially expressed lncRNAs (AC092718.4, AC138035.1, BMPR1B-DT, RNF157-AS1, and TPT1-AS1) between OC and normal ovarian based on TCGA and GTEx RNA-seq databases by using Kaplan-Meier analysis and univariate Cox, LASSO, and multivariate Cox regression. Then, a risk signature was constructed, with 1, 3, 5-year survival prediction accuracy confirmed by ROC curves, and an online survival calculator for easier clinical use. With lncRNA-microRNA-mRNA regulatory networks established, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed, suggesting the involvement of a variety of cancer-related functions and pathways. Finally, five candidate small-molecule drugs (thioridazine, trifluoperazine, loperamide, LY294002, and puromycin) were predicted by Connectivity Map. In conclusion, we identified a 5-lncRNA signature of prognostic value with its ceRNA networks, and five candidate drugs against OC.[Figure: see text].

The emerging role of the chondroitin sulfate proteoglycan family in neurodegenerative diseases.

Chondroitin sulfate (CS) is a kind of linear polysaccharide that is covalently linked to proteins to form proteoglycans. Chondroitin sulfate proteoglycans (CSPGs) consist of a core protein, with one or more CS chains covalently attached. CSPGs are precisely regulated and they exert a variety of physiological functions by binding to adhesion molecules and growth factors. Widely distributed in the nervous system in human body, CSPGs contribute to the major component of extracellular matrix (ECM), where they play an important role in the development and maturation of the nervous system, as well as in the pathophysiological response to damage to the central nervous system (CNS). While there are more than 30 types of CSPGs, this review covers the roles of the most important ones, including versican, aggrecan, neurocan and NG2 in the pathogenesis of neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis and multiple sclerosis. The updated reports of the treatment of neurodegenerative diseases are involving CSPGs.

A risk signature of three autophagy-related genes for predicting lower grade glioma survival is associated with tumor immune microenvironment.

Treatment for lower-grade gliomas (LGG) has been challenging. Though emerging approaches such as immunotherapy is promising, it is still faced with immune tolerance, an obstacle that may be overcome by targeting autophagy-related (ATG) genes. After identifying three differentially expressed ATG genes (RIPK2, MUL1 and CXCR4), we constructed an ATG gene risk signature by Kaplan-Meier, univariate Cox regression, least absolute shrinkage and selection operator regression and multivariate Cox regression, followed by internal and external validation using K-M and ROC analysis. Since gene set enrichment analysis (GSEA) suggested that the signature was strongly associated with immune cell functions, CIBERSORT, LM22 matrix and Pearson correlation were further performed, showing that the risk signature was significantly correlated with immune cell infiltration and immune checkpoint genes. In conclusion, we identified and independently validated an ATG gene risk signature for LGG patients, as well as discovering its significant association with LGG immune microenvironment.

Global dynamics and optimal control of a cholera transmission model with vaccination strategy and multiple pathways.

In this paper, we consider a cholera infection model with vaccination and multiple transmission pathways. Dynamical properties of the model are analyzed in detail. It is shown that the disease-free equilibrium is globally asymptotically stable if the basic reproduction number is less than unity; the endemic equilibrium exists and is globally asymptotically stable if the basic reproduction number is greater than unity. In addition, the model is successfully used to fit the real disease situation of cholera outbreak in Somalia. We consider an optimal control problem of cholera transmission with vaccination, quarantine, treatment and sanitation control strategies, and use Pontryagin's minimum principle to determine the optimal control level. The optimal control problem is solved numerically.

Neuregulin 1 enhances cell adhesion molecule L1 like expression levels and promotes malignancy in human glioma.

Neural cell adhesion molecular L1-like protein (CHL1) is a member of the cell adhesion molecule L1 family and serves an important role in the development and progression of tumors. The cytokine neuregulin 1 (NRG1) has been indicated in the tumorigenesis and promotion of metastasis through the modulation of L1. However, the roles of NRG1 in regulating CHL1 in glioma have not been elucidated. The present study investigated the protein expression levels and roles of CHL1 and the possible correlation between NRG1 and CHL1 protein expression levels in human gliomas, both in vivo and in vitro. Using immunohistochemistry coupled with a human glioma tissue microarray, it was demonstrated that the percentage of CHL1-positive areas was the highest in grade II glioma tissues. Using immunofluorescence staining, a positive correlation was identified between the expression levels of CHL1 and proliferating cell nuclear antigen. In addition, CHL1 downregulation also resulted in increased senescence of U-87 MG human glioblastoma cells. In vitro, administration of NRG1α induced a significant increase in CHL1 protein expression levels in human glioma SHG-44 and U251 cells and in human glioblastoma U-87 MG cells, whereas NRG1ß failed to increase CHL1 expression levels in U251 cells. These findings were further confirmed by the downregulation of NRG1 expression levels using small interfering RNA treatment, which resulted in the reduction of CHL1 protein expression levels in U-87 MG cells. These data indicate that NRG1 can regulate CHL1 protein expression levels in gliomas, that it is correlated with malignancy, and that NRG1 may contribute to malignancy by upregulating CHL1 protein expression levels in glioma/glioblastoma cells.

Identification and validation of a six-lncRNA prognostic signature with its ceRNA networks and candidate drugs in lower-grade gliomas.

Gliomas account for 75% of the primary malignant brain tumors and a majority of lower-grade gliomas (LGG) inevitably develop into glioblastoma. The dysregulation of lncRNAs play a crucial role in LGG. In the present study, we first screened out six differentially expressed lncRNAs (AC021739.2, AL031722.1, AL354740.1, FGD5-AS1, LINC00844, and NEAT1) based on TCGA and GTEx RNA-seq databases. LncRNA prognostic signature was then established by Kaplan-Meier and multivariate Cox proportional hazards regression, with its predictive value validated by time-dependent receiver operating characteristic (ROC) curves. After lncRNA-miRNA-mRNA regulatory networks were established by Cytoscape 3.7.2, Gene Oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed, with results enriched in various malignancy-related functions and pathways. Finally, six putative drugs (irinotecan, camptothecin, mitoxantrone, azacitidine, mestranol, and enilconazole) were predicted by Connectivity Map. In conclusion, we identified a 6-lncRNA prognostic signature with its ceRNA networks, and six candidate drugs against LGG.

Mathematical analysis of an age-structured HIV-1 infection model with CTL immune response.

In this paper, an age-structured HIV-1 infection model with CTL immune response is investigated. In the model, we consider the infection age (i.e. the time that has elapsed since an HIV virion has penetrated the cell) of infected $T$ cells. The asymptotic smoothness of the semi-flow generated by the system is established. By calculation, the immune-inactivated reproduction rate $\mathscr{R}_0$ and the immune-activated reproduction rate $\mathscr{R}_1$ are obtained. By analyzing the corresponding characteristic equations, the local stability of an infection-free steady state and a CTL-inactivated infection steady state of the model is established. By using the persistence theory for infinite dimensional system, the uniform persistence of the system is established when $\mathscr{R}_1>1$. By means of suitable Lyapunov functionals and LaSalle's invariance principle, it is shown that if $\mathscr{R}_0<1$, the infection-free steady state is globally asymptotically stable; if $\mathscr{R}_1<1< \mathscr{R}_0$, sufficient conditions are derived for the global stability of the CTL-inactivated infection steady state; if $\mathscr{R}_1>1$, sufficient conditions are obtained for the global attractivity of the CTL-activated infection steady state. Numerical simulations are carried out to illustrate the feasibility of the theoretical results.

Transmission dynamics of cholera with hyperinfectious and hypoinfectious vibrios: mathematical modelling and control strategies.

Cholera is a common infectious disease caused by Vibrio cholerae, which has different infectivity. In this paper, we propose a cholera model with hyperinfectious and hypoinfectious vibrios, in which both human-to-human and environment-to-human transmissions are considered. By analyzing the characteristic equations, the local stability of disease-free and endemic equilibria is established. By using Lyapunov functionals and LaSalle's invariance principle, it is verified that the global threshold dynamics of the model can be completely determined by the basic reproduction number. Numerical simulations are carried out to illustrate the corresponding theoretical results and describe the cholera outbreak in Haiti. The study of optimal control helps us seek cost-effective solutions of time-dependent control strategies against cholera outbreaks, which shows that control strategies, such as vaccination and sanitation, should be taken at the very beginning of the outbreak and become less necessary after a certain period.