Search Tool For The Retrieval Of Interacting Genes/Proteins Research Articles

DDX10 promotes the proliferation and metastasis of colorectal cancer cells via splicing RPL35

BackgroundColorectal cancer (CRC) has become the second deadliest cancer in the world and severely threatens human health. An increasing number of studies have focused on the role of the RNA helicase DEAD-box (DDX) family in CRC. However, the mechanism of DDX10 in CRC has not been elucidated.MethodsIn our study, we analysed the expression data of CRC samples from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Subsequently, we performed cytological experiments and animal experiments to explore the role of DDX10 in CRC cells. Furthermore, we performed Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and protein–protein interaction (PPI) network analyses. Finally, we predicted the interacting protein of DDX10 by LC–MS/MS and verified it by coimmunoprecipitation (Co-IP) and qPCR.ResultsIn the present study, we identified that DDX10 mRNA was extremely highly expressed in CRC tissues compared with normal colon tissues in the TCGA and GEO databases. The protein expression of DDX10 was measured by immunochemistry (IHC) in 17 CRC patients. The biological roles of DDX10 were explored via cell and molecular biology experiments in vitro and in vivo and cell cycle assays. We found that DDX10 knockdown markedly reduced CRC cell proliferation, migration and invasion. Then, we constructed a PPI network with the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). GO and KEGG enrichment analysis and gene set enrichment analysis (GSEA) showed that DDX10 was closely related to RNA splicing and E2F targets. Using LC–MS/MS and Co-IP assays, we discovered that RPL35 is the interacting protein of DDX10. In addition, we hypothesize that RPL35 is related to the E2F pathway and the immune response in CRC.ConclusionsIn conclusion, provides a better understanding of the molecular mechanisms of DDX10 in CRC and provides a potential biomarker for the diagnosis and treatment of CRC.

Network Pharmacology Analysis of Molecular Mechanism of Curcuma longa L. Extracts Regulating Glioma Immune Inflammatory Factors: Implications for Precise Cancer Treatment.

Curcuma longa L. has been associated with different antioxidant, antiinflammatory, bactericidal and anticancer effects, but the mechanisms of the effects are not yet clearly understood. This study aimed to investigate the key targets and the effect of potential molecular mechanisms of Curcuma longa L. extracts on glioma using different network pharmacology analysis approaches. The components of Curcuma longa were extracted by gas chromatography-mass spectrometry (GC-MS), and the active components related to the occurrence and development of glioma were determined by traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) database, and the same targets of the active components and glioma were screened by network pharmacology approach. Then, the protein's function and regulatory pathway of the common targets were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The protein's action and regulatory pathway of the common targets were analyzed with the Cytoscape package using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database to construct the target interaction network through which the key targets were identified. GC-MS combined with TCMSP database was used to identify the active components related to the occurrence and development of glioma in Curcuma longa. Finally, we identified the active components 1-(1,5-Dimethyl-4-hexenyl)-4-methyl benzene and Zingiberene. At the same time, 190 target genes of Curcuma longa extracts on glioma were obtained using the Venn diagram. The results of GO analysis showed that the biological processes involved included a response to stimulation, metabolic process, inflammatory process, cell differentiation, and regulation of biological processes. KEGG analysis showed that the PI3K-Akt signaling pathway, MAPK signaling pathway, Th17 cell differentiation, and proteoglycan pathway might be involved in cancer. Further analyses showed that the IL-17 signaling pathway and Interleukin-4 and interleukin-13 signaling were involved in the inflammatory pathway. The analysis of key nodes showed that GSK3B, MAPK14, HSP90AA1, MAPK3 and MAPK8 were IL-17 signaling pathways, while HIF1A and JAK3 were Interleukin-4 and interleukin-13 signaling pathways. Curcuma longa extracts can regulate the occurrence and development of glioma by regulating the immune-inflammatory responses.

Network pharmacology and molecular docking analysis reveals the mechanism of asiaticoside on COVID-19.

BackgroundAsiaticoside (AS) is a saponin extracted from the traditional Chinese herbal medicine Centella Asiatica, which has the effects of reducing inflammatory infiltration and anti-oxidation in pneumonia and combating pulmonary fibrosis. We hypothesize that AS might have therapeutic potential for the treatment of the coronavirus disease 2019 (COVID-19). With the help of network pharmacology and molecular docking techniques, this study discussed the underlying molecular mechanism of AS in the treatment of COVID-19.MethodsThe molecular structure of AS was obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) system. The targets of AS were achieved using PharmMapper, SwissTargetPrediction, and the Comparative Toxicogenomics Database (CTD). The targets corresponding to COVID-19 were obtained using GeneCards, Online Mendelian Inheritance in Man (OMIM), and CTD database. Then, a target protein-protein interaction (PPI) network was formed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. A network of AS, COVID-19, and their co-targets was built using Cytoscape. Afterwards, the co-targets were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Moreover, the predictions of crucial targets were further investigated by performing molecular docking with AS.ResultsA total of 45 core targets of AS were found to be engaged in the pathogenesis of COVID-19. The KEGG enrichment analysis indicated that AS might be protective against COVID-19 through inflammation- and immune-related signaling pathways, including interleukin-17 (IL-17) signaling, T helper 17 (Th17) cell differentiation pathway, Coronavirus disease-COVID-19, MAPK, the PI3K-Akt signaling pathway, and so on. The results of molecular docking showed that AS had a high affinity with those core targets.ConclusionsThe beneficial effect of AS on COVID-19 might be through regulating multiple immune or inflammation-related targets and signaling pathways.

Exploration of the Molecular Mechanism of Polygonati Rhizoma in the Treatment of Osteoporosis Based on Network Pharmacology and Molecular Docking.

ObjectiveTo explore the effective components and mechanism of Polygonati Rhizoma (PR) in the treatment of osteoporosis (OP) based on network pharmacology and molecular docking methods.MethodsThe effective components and predicted targets of PR were obtained through the Traditional Chinese Medicine Systems Pharmacology and Analysis Platform (TCMSP) database. The disease database was used to screen the disease targets of OP. The obtained key targets were uploaded to the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database for protein-protein interaction (PPI) network analysis. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of key targets. Analysis and docking verification of chemical effective drug components and key targets were performed with IGEMDOCK software.ResultsA total of 12 chemically active components, 84 drug target proteins and 84 common targets related to drugs and OP were obtained. Key targets such as JUN, TP53, AKT1, ESR1, MAPK14, AR and CASP3 were identified through PPI network analysis. The results of enrichment analysis showed that the potential core drug components regulate the HIF-1 signaling pathway, PI3K-Akt signaling pathway, estrogen signaling pathway and other pathways by intervening in biological processes such as cell proliferation and apoptosis and estrogen response regulation, with an anti-OP pharmacological role. The results of molecular docking showed that the key targets in the regulatory network have high binding activity to related active components.ConclusionsPR may regulate OP by regulating core target genes, such as JUN, TP53, AKT1, ESR1, AR and CASP3, and acting on multiple key pathways, such as the HIF-1 signaling pathway, PI3K-Akt signaling pathway, and estrogen signaling pathway.

Estrogen receptor 1 and Aurora kinase A as potential diagnostic biomarkers for cervical cancer

Cervical cancer (CC) is the fourth most common cause of death among women globally. Nearly 90% of CC mortality occurs in low- and middle-income countries. Hence there is an urgent need for identification of new biomarkers for the early diagnosis and treatment of CC. Current research aims to investigate the effect and mechanism of estrogen receptor 1 and aurora kinase A as potential diagnostic biomarkers for cervical cancer. Gene microarray datasets GSE8703 and GSE9750 were acquired from the Gene Set Omnibus and evaluated using GEO2R to identify the differentially expressed genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the differentially expressed genes were performed using the clusterProfiler R package. A protein-protein interaction (PPI) network was constructed using Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and visualized using Cytoscape; hub genes were screened using the cytoHubba plug-in. Receiver operating characteristic curve and survival analysis was performed for candidate genes in the Gene Expression Profiling Interactive Analysis Database. The University of California, Santa Cruz, (UCSC)-XENA platform was used to analyze the pan-cancer biomarker expression. The relative expression of biomarkers in normal and cervical cancer tissues was determined using the Human Protein Atlas Database. Estrogen receptor 1 (ESR1) and Aurora kinase A (AURKA) were identified as potential biomarkers for cervical cancer. ESR1 was actively expressed in normal cervical tissues but limited in cervical cancer tissues. AURKA was least expressed in normal tissues and highly expressed in cervical cancer tissues. The results were confirmed by immunohistochemistry. The biomarkers identified herein can enable early diagnosis and serve as the therapeutic targets for cervical cancer.

Hypermethylation Effects of Yiqihuoxue Decoction in Diabetic Atherosclerosis Using Genome-Wide DNA Methylation Analyses.

PurposeTo investigate if a traditional Chinese medicine formulation, called “Yiqihuoxue” (YQHX), could improve diabetic atherosclerosis (DA) and explore potential mechanisms based on DNA methylation.MethodsApolipoprotein E-knockout mice were administered streptozotocin (50 mg/d, i.p.) for 5 days and fed a high-fat diet for 16 weeks. Mice were divided randomly into DA model, rosiglitazone, as well as low-, medium-, and high-dose YQHX groups. Ten healthy C57BL/6J mice were the control group. Serum levels of fasting insulin, blood glucose, homeostasis model-insulin resistance index (HOMA-IR), serum lipids, and inflammatory factors were analyzed after the final treatment. Aorta tissues were collected for staining (hematoxylin and eosin, and Oil red O). Genomic DNA was extracted for methyl-capture sequencing (MC-seq). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) databases were used to analyze differentially methylated genes. Pyrosequencing was used to verify MC-seq data.ResultsLow-dose and high-dose YQHX could reduce the HOMA-IR (P < 0.05). Low-dose YQHX reduced expression of total cholesterol (TC), low-density lipoprotein-cholesterol (LDL-C), TNF-α, andI L-6 in serum compared with that in the model group (P < 0.05). Medium-dose YQHX decoction inhibited the expression level of TNF-α (P < 0.05). High-dose YQHX decreased the expression level of IL-6 (P < 0.05). Staining also showed the anti-atherosclerosis effects of YQHX (P < 0.05). MC-seq revealed many abnormally hypermethylated and hypomethylated genes in DA mice compared with those in the control group. KEGG database analysis showed that the hypermethylated genes induced by YQHX treatment were related to pathways in cancer, Hippo signaling, and mitogen activated protein kinase. The network analysis suggested that the hypermethylated genes epidermal growth factor receptor(Egfr) and phosphoinositide-3-kinase regulatory subunit 1(Pik3r1) induced by YQHX treatment had important roles in DA. Pyrosequencing revealed that YQHX treatment increased methylation of AKT1, Nr1h3 and Fabp4 significantly (P < 0.05).ConclusionYQHX decoction had positive treatment effects against DA, because it could regulate aberrant hypomethylation of DNA.

The role of exercise intensity on fatty liver in rats.

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease and is often caused by obesity. Currently, moderate-intensity continuous training (MICT) and high-intensity interval training (HIIT) are two effective treatments for reducing fat mass in patients with obesity and NAFLD. However, the comparative fat-reducing effects and underlying molecular mechanisms of MICT and HIIT remain unclear. This comprehensive study was performed on male Wistar rats treated with standard diet, high-fat diet, MICT, and HIIT to explore their comparative fat-reducing effects and corresponding molecular mechanisms. HIIT had a greater effect on hepatic vacuolation density and lipid content reduction than MICT, and triglyceride and total cholesterol levels in the serum and the liver demonstrated different sensitivities to different exercise training programs. At the molecular level, both MICT and HIIT altered the processes of fatty acid synthesis, fatty acid transport, fatty acid β-oxidation, and cholesterol synthesis, wherein the transcriptional and translational levels of signaling molecules peroxisome proliferator-activated receptors (PPARs) regulating fatty acid and cholesterol synthesis were strongly changed. Moreover, the metabolic pathways of amino acids, bile acids, and carbohydrates were also affected according to transcriptome analysis, and the changes in the above-mentioned processes in the HIIT group were greater than those in the MICT group. In combination with the search tool for the retrieval of interacting genes/proteins (STRING) analysis and the role of PPARs in lipid metabolism, as well as the expression pattern of PPARs in the MICT and HIIT groups, the MICT-and HIIT-induced fat loss was mediated by the PPAR pathway, causing feedback responses in fatty acid, steroid, amino acid, bile acid, and carbohydrate metabolism, and HIIT had a better fat-reducing effect, which may be initiated by PPAR-α. This study provides a theoretical basis for targeted therapy of patients with obesity and NAFLD.

Multiple Myeloma: Bioinformatic Analysis for Identification of Key Genes and Pathways.

Multiple myeloma (MM) is a hematological malignancy in which monoclonal plasma cells multiply in the bone marrow and monoclonal immunoglobulins are overproduced in older people. Several molecular and cytogenetic advances allow scientists to identify several genetic and chromosomal abnormalities that cause the disease. The comprehension of the pathophysiology of MM requires an understanding of the characteristics of malignant clones and the changes in the bone marrow microenvironment. This study aims to identify the central genes and to determine the key signaling pathways in MM by in silico approaches. A list of 114 differentially expressed genes (DEGs) is important in the prognosis of MM. The DEGs are collected from scientific publications and databases (https://www.ncbi.nlm.nih.gov/). These data are analyzed by Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) software (https://string-db.org/) through the construction of protein-protein interaction (PPI) networks and enrichment analysis of the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, by CytoHubba, AutoAnnotate, Bingo Apps plugins in Cytoscape software (https://cytoscape.org/) and by DAVID database (https://david.ncifcrf.gov/). The analysis of the results shows that there are 7 core genes, including TP53; MYC; CDND1; IL6; UBA52; EZH2, and MDM2. These top genes appear to play a role in the promotion and progression of MM. According to functional enrichment analysis, these genes are mainly involved in the following signaling pathways: Epstein-Barr virus infection, microRNA pathway, PI3K-Akt signaling pathway, and p53 signaling pathway. Several crucial genes, including TP53, MYC, CDND1, IL6, UBA52, EZH2, and MDM2, are significantly correlated with MM, which may exert their role in the onset and evolution of MM.

Comparative Transcriptomic Analysis of Root Cadmium Responses in Two Chinese Rice Cultivars Yuzhenxiang and Xiangwanxian 12

Cadmium (Cd) pollution in paddy soil is an increasingly serious issue in rice production. It has been reported that there is a higher or lower grain Cd accumulation in the rice cultivars Yuzhenxiang (YZX) or Xiangwanxian 12 (XWX), respectively. To better manage the Cd pollution problem, the genes that might play vital roles in governing the difference in root Cd responses between these two rice cultivars were examined. In this study, the results of RNA sequencing (RNA-seq) showed that there were 341 and 161 differentially expressed genes in the roots of YZX and XWX after Cd exposure, respectively. Among these genes, 7 genes, such as Os06g0196300 (OsJ_019618), Os07g0570700 (OsJ_24808), ADI1, GDCSH, HSFB2C, PEX11-4, and CLPB1, possessed higher degree nodes with each other, through interaction analysis by the STRING (search tool for the retrieval of interacting genes/proteins) software, suggesting that they might play vital roles in Cd response. Based on GO enrichment analysis, 41 differently expressed genes after Cd treatment in YZX or XWX were identified to be related to Cd response. Through comparative transcriptomic analysis, 257 genes might be associated with the root Cd response difference between YZX and XWX. Furthermore, we supposed that ADI1, CFBP1, PEX11-4, OsJ_019618, OsJ_24808, GDCSH, CLPB1, LAC6, and WNK3 might be implicated in Cd response based on the combined analysis of RT-qPCR, interaction, and GO annotation analysis. In conclusion, the numerous genes that might be related to Cd stress response and root Cd response difference between YZX and XWX at the booting stage may be of benefit for the development of rice varieties with low Cd consumption.

Long Non-Coding RNA- Associated Competing Endogenous RNA Axes in T-Cells in Multiple Sclerosis.

Multiple sclerosis (MS) is an immune-mediated demyelinating and degenerative disease with unknown etiology. Inappropriate response of T-cells to myelin antigens has an essential role in the pathophysiology of MS. The clinical and pathophysiological complications of MS necessitate identification of potential molecular targets to understand the pathogenic events of MS. Since the functions and regulatory mechanisms of long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) in MS are yet uncertain, we conducted a bioinformatics analysis to explain the lncRNA-associated ceRNA axes to clarify molecular regulatory mechanisms involved in T-cells responses in MS. Two microarray datasets of peripheral blood T-cell from subjects with relapsing-remitting MS and matched controls containing data about miRNAs (GSE43590), mRNAs and lncRNAs (GSE43591) were downloaded from the Gene Expression Omnibus database. Differentially expressed miRNAs (DEmiRNAs), mRNAs (DEmRNAs), and lncRNAs (DElncRNAs) were identified by the limma package of the R software. Protein-protein interaction (PPI) network and module were developed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and the Molecular Complex Detection (MCODE) Cytoscape plugin, respectively. Using DIANA-LncBase and miRTarBase, the lncRNA-associated ceRNA axes was constructed. We conducted a Pearson correlation analysis and selected the positive correlations among the lncRNAs and mRNAs in the ceRNA axes. Lastly, DEmRNAs pathway enrichment was conducted by the Enrichr tool. A ceRNA regulatory relationship among Small nucleolar RNA host gene 1 (SNHG1), hsa-miR-197-3p, YOD1 deubiquitinase (YOD1) and zinc finger protein 101 (ZNF101) and downstream connected genes was identified. Pathway enrichment analysis showed that DEmRNAs were enriched in “Protein processing in endoplasmic reticulum” and “Herpes simplex virus 1 infection” pathways. To our knowledge, this would be the first report of a possible role of SNHG1/hsa-miR-197-3p/YOD1/ZNF101 axes in the pathogenesis of MS. This research remarks on the significance of ceRNAs and prepares new perceptions for discovering the molecular mechanism of MS.

High Expression of BCL11A Predicts Poor Prognosis for Childhood MLL-r ALL.

BackgroundDespite much improvement in the treatment for acute lymphoblastic leukemia (ALL), childhood ALLs with MLL-rearrangement (MLL-r) still have inferior dismal prognosis. Thus, defining mechanisms underlying MLL-r ALL maintenance is critical for developing effective therapy.MethodsGSE13159 and GSE28497 were selected via the Oncomine website. Differentially expressed genes (DEGs) between MLL-r ALLs and normal samples were identified by R software. Next, functional enrichment analysis of these DEGs were carried out by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). Then, the key hub genes and modules were identified by Weighted Gene Co-expression Network Analysis (WGCNA). Therapeutically Applicable Research to Generate Effective Treatments (TARGET) ALL (Phase I) of UCSC Xena analysis, qPCR, and Kaplan-Meier analysis were conducted for validating the expression of key hub genes from bone marrow cells of childhood ALL patients or ALL cell lines.ResultsA total of 1,045 DEGs were identified from GSE13159 and GSE28497. Through GO, KEGG, GSEA, and STRING analysis, we demonstrated that MLL-r ALLs were upregulating “nucleosome assembly” and “B cell receptor signal pathway” genes or proteins. WGCNA analysis found 18 gene modules using hierarchical clustering between MLL-r ALLs and normal. The Venn diagram was used to filter the 98 hub genes found in the key module with the 1,045 DEGs. We identified 18 hub genes from this process, 9 of which were found to be correlated with MLL-r status, using the UCSC Xena analysis. By using qPCR, we validated these 9 hub key genes to be upregulated in the MLL-r ALLs (RS4;11 and SEM) compared to the non-MLL-r ALL (RCH-ACV) cell lines. Three of these genes, BCL11A, GLT8D1 and NCBP2, were shown to be increased in MLL-r ALL patient bone marrows compared to the non-MLL-r ALL patient. Finally, Kaplan–Meier analysis indicated that childhood ALL patients with high BCL11A expression had significantly poor overall survival.ConclusionThese findings suggest that upregulated BCL11A gene expression in childhood ALLs may lead to MLL-r ALL development and BCL11A represents a new potential therapeutic target for childhood MLL-r ALL.

Prediction of Genes Involved in Lung Cancer with a Systems Biology Approach Based on Comprehensive Gene Information.

Over the past few years, hundreds of genes have been reported in relation to lung cancer. Systems biology studies can help validate this association and find the most valid genes to use in the diagnosis and treatment. We reviewed the candidate genes for lung cancer in 120 published articles from September 1, 1993, to September 1, 2020. We obtained 134 up- and 36 downregulated genes for lung cancer in this article. The genes extracted from the articles were imported to Search Tool for the Retrieval of Interacting genes/proteins (STRING) to construct the protein-protein interaction (PPI) Network and pathway enrichment. GO ontology and Reactome databases were used for describing the genes, average length of survival, and constructing networks. Then, the ClusterONE plugin of Cytoscape software was used to analyze and cluster networks. Hubs and bottleneck nodes were defined based on their degree and betweenness. Common genes between the ClusterONE plugin and network analysis consisted of seven genes (BRCA1-TP53-CASP3-PLK1-VEGFA-MDM2-CCNB1 and PLK1), and two genes (PLK1 and TYMS) were selected as survival factors. Our drug-gene network showed that CASP3, BRCA1, TP53, VEGFA, and MDM2 are common genes that are involved in this network. Also, among the drugs recognized in the drug-gene network, five drugs such as paclitaxel, oxaliplatin, carboplatin, irinotecan, and cisplatin were examined in different studies. It seems that these seven genes, with further studies and confirmatory tests, could be potential markers for lung cancer, especially PLK1 that has a significant effect on the survival of patients. We provide the novel genes into the pathogenesis of lung cancer, and we introduced new potential biomarkers for this malignancy.

Mechanism of astragaloside Ⅳ alleviating PC12 cell injury by activating PI3K/AKT signaling pathway: based on network pharmacology and in vitro experiments

In this study, the molecular mechanism of astragaloside Ⅳ(AS-Ⅳ) in the treatment of Parkinson's disease(PD) was explored based on network pharmacology, and the potential value of AS-Ⅳ in alleviating neuronal injury in PD by activating the PI3 K/AKT signaling pathway was verified through molecular docking and in vitro experiments. Such databases as SwissTargetPrediction, BTMAN-TAM, and GeneCards were used to predict the targets of AS-Ⅳ for the treatment of PD. The Search Tool for the Retrieval of Interacting Genes/Proteins(STRING) was employed to analyze protein-protein interaction(PPI) and construct a PPI network, and the Database for Annotation, Visualization and Integrated Discovery(DAVID) was used for Gene Ontology(GO) term enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis. Based on the results of GO enrichment analysis and KEGG pathway analysis, the PI3 K/AKT signaling pathway was selected for further molecular docking and in vitro experiments in this study. The in vitro cell model of PD was established by MPP~+. The cell viability was measured by MTT assay and effect of AS-Ⅳ on the expression of the PI3 K/AKT signaling pathway-related genes and proteins by real-time polymerase chain reaction(RT-PCR) and Western blot. Network pharmacology revealed totally 122 targets of AS-Ⅳ for the treatment of PD, and GO enrichment analysis yielded 504 GO terms, most of which were biological processes and molecular functions. Totally 20 related signaling pathways were screened out by KEGG pathway analysis, including neuroactive ligand-receptor interaction, PI3 K/AKT signaling pathway, GABAergic synapse, and calcium signaling pathway. Molecular docking demonstrated high affinity of AS-Ⅳ to serine/threonine-protein kinases(AKT1, AKT2), phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit gamma(PIK3 CG), and phosphoinositide-3-kinase, catalytic, alpha polypeptide(PIK3 CA) on the PI3 K/AKT signaling pathway. In vitro experiments showed that AS-Ⅳ could effectively inhibit the decrease of the viability of PC12 induced by MPP~+ and up-regulate the mRNA expression levels of AKT1 and PI3 K as well as the phosphorylation levels of AKT and PI3 K. As an active component of Astragali Radix, AS-Ⅳ acts on PD through multiple targets and pathways. Furthermore, it inhibits neuronal apoptosis and protects neurons by activating the PI3 K/AKT signaling pathway, thereby providing reliable theoretical and experimental supports for the treatment of PD with AS-Ⅳ.

The effect of PPP2CA expression on the prognosis of patients with hepatocellular carcinoma and its molecular biological characteristics.

To investigate the role of the PPP2CA gene in the prognosis of patients with hepatocellular carcinoma (HCC) and its molecular biological characteristics. We performed comparison of the expression of PPP2CA in HCC and non-HCC tissues of HCC patients who underwent surgery for the first time in the Tumor Hospital of Guangxi Medical University from July 2017 to July 2019, and retrospectively analyzed the relevant clinical data and prognosis. The GSE76427 data set and bioinformatics and public databases were used to compare the expression of PPP2CA between HCC and non-cancer tissues. Gene Ontology (GO) analysis was performed of PPP2CA and its differential genes and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. A protein-protein interaction (PPI) network of PPP2CA and its differentially expressed genes (DEGs) was constructed from the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database and visualized by Cytoscape software. The immunohistochemistry (IHC) of tissue sections confirmed that PPP2CA was highly expressed in most HCC tissues; the high expression of PPP2CA was significantly correlated with microvascular invasion (MVI) and portal vein tumor thrombi (P<0.05). Participants in the PPP2CA high expression group had worse overall survival (OS; P=0.04) and recurrence-free survival (RFS; P=0.019). The PPP2CA gene and 71 DEGs were mainly enriched in the nuclear division, organelle fission, nuclear chromosome separation, and chromatid separation process, and KEGG analysis revealed enrichment in drug metabolism-cytochrome metabolism of xenobiotics by P450 and cytochrome P450. Finally, through the PPI network, CCNA2, AURKB, TOP2A, NCAPG, MCM2, CDC20, CCMB2, AURKA, and MGST1 were identified as the top 9 highly connected hub genes. The PPP2CA gene is highly expressed in HCC tissues. The high expression of PPP2CA is significantly associated with poor prognosis. Through the analysis of DEGs, GO and KEGG pathway analysis, it was found that PPP2CA may act on liver cancer through multiple targets and multiple pathways, and PPP2CA plays a promoting role in HCC.

Functions of 1,25-dihydroxy vitamin D3, vitamin D3 receptor and interleukin-22 involved in pathogenesis of gout arthritis through altering metabolic pattern and inflammatory responses.

BackgroundGouty arthritis (GA) is a common type of inflammatory arthritis. Recent studies demonstrated that 1,25-dihydroxy vitamin D3 (1,25(OH) 2 VD3) and vitamin D3 receptor (VD-R) play a protective role in acute inflammation, but interleukin-22(IL-22) promotes inflammation, especially for arthritis. However, our understanding of the responses of 1,25(OH) 2VD3 and IL-22 to gout was still unclear. Presently, in-depth metabolomics, bioinformatics and clinical characteristics analyses were performed to elucidate the pathogenesis and valuable clinical indicators of gouty arthritis.MethodsPeripheral venous blood was taken for investigation. The levels of IL-22 and 1,25(OH)2VD3 were determined in patient’s plasma via ELISA, and the mRNA levels of IL-22 and VD-R were measured via qRT-PCR. The interaction network of VD-R and IL22 were constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and the biological function of the related proteins were analyzed by Clusterprofiler Metabolomics were performed to decipher the metabolic variations of GA.ResultsThe levels of VD-R and 1,25(OH) 2 VD3 were identified to be low. What,s more, GA patients were reported to have high expression of IL-22. And IL-22 levels positively correlated with C-reactiveprotein (CRP) serum levels in the bivariate correlation analysis, whereas the level of 1,25(OH) 2VD3 negatively correlated with that of CRP. GO and KEGG analyses revealed that IL-22 and 1,25(OH) 2 VD3 were involved in stress immunity and inflammatory responses. These pathways are known to play a role in GA pathogenesis. Meanwhile, the metabolic profiles of GA serum showed that the increase in various amino acids and uric acid are involved in GA pathogenesis. Importantly, VD-R and IL22 closely correlated with the level of key metabolites uric acid, whose increase promoted the occurrence of GA.ConclusionGA patients have low levels of VD-R and 1,25(OH) 2 VD3, and high levels of IL-22 together with various amino acids and uric acid. The levels of IL-22 and 1,25(OH) 2VD3 were positively and negatively correlated with C-reactive protein (CRP) serum levels, respectively. Both IL-22 and 1,25(OH) 2 VD3 functioned in GA-related immune and inflammatory responses, and closely correlated with the level of GA-related uric acid. Overall, IL-22, VD-R and 1,25(OH) 2 VD3 play functionally important roles in inflammatory responses and are relevant to gout pathogenesis.

Identification and development of a novel 5-gene diagnostic model based on immune infiltration analysis of osteoarthritis

BackgroundOsteoarthritis (OA), which is due to the progressive loss and degeneration of articular cartilage, is the leading cause of disability worldwide. Therefore, it is of great significance to explore OA biomarkers for the prevention, diagnosis, and treatment of OA.Methods and materialsThe GSE129147, GSE57218, GSE51588, GSE117999, and GSE98918 datasets with normal and OA samples were downloaded from the Gene Expression Omnibus (GEO) database. The GSE117999 and GSE98918 datasets were integrated, and immune infiltration was evaluated. The differentially expressed genes (DEGs) were analyzed using the limma package in R, and weighted gene co-expression network analysis (WGCNA) was used to explore the co-expression genes and co-expression modules. The co-expression module genes were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. A protein–protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, and hub genes were identified by the degree, MNC, closeness, and MCC algorithms. The hub genes were used to construct a diagnostic model based on support vector machines.ResultsThe Immune Score in the OA samples was significantly higher than in the normal samples, and a total of 2313 DEGs were identified. Through WGCNA, we found that the yellow module was significantly positively correlated with the OA samples and Immune Score and negatively correlated with the normal samples. The 142 DEGs of the yellow module were related to biological processes such as regulation of inflammatory response, positive regulation of inflammatory response, blood vessel morphogenesis, endothelial cell migration, and humoral immune response. The intersections of the genes obtained by the 4 algorithms resulted in 5 final hub genes, and the diagnostic model constructed with these 5 genes showed good performance in the training and validation cohorts.ConclusionsThe 5-gene diagnostic model can be used to diagnose OA and guide clinical decision-making.

Reconstruction and analysis of the aberrant lncRNA-miRNA-mRNA network based on competitive endogenous RNA in adenoid cystic carcinoma of the salivary gland.

BackgroundThe aim of this work was to investigate the competing endogenous RNA (ceRNA) network in adenoid cystic carcinoma of the salivary gland (SACC).MethodsDifferentially expressed lncRNAs (DElncRNAs), miRNAs (DEmiRNAs), and mRNAs (DEmRNAs) between cancer tissues and normal salivary gland (NSG) in ACC were identified using data from the Gene Expression Omnibus (GEO) database. Functional annotation and pathway enrichment analysis of DEmRNAs were performed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. The miRNAs that are targeted by lncRNAs were predicted using miRanda and PITA, while the target mRNAs of miRNAs were retrieved from miRanda, miRWalk, and TargetScan. A protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, and then we constructed the lncRNA-miRNA-mRNA networks of ACC.ResultsDifferentially expressed RNAs were identified in SACC. Upon comparing cancer tissues and NSG tissues, 103 upregulated and 52 downregulated lncRNAs and 745 upregulated and 866 downregulated mRNAs were identified in GSE88804; in addition, 39 upregulated and 43 downregulated miRNAs were identified in GSE117275. GO enrichment analyses revealed that the most relevant GO terms were regulation of transcription DNA-templated, transcription DNA-templated, and cell division. KEGG pathway enrichment analysis showed that differentially expressed genes (DEGs) were mainly enriched in the cell cycle, pathways in cancer, PI3K-Akt signaling pathway, breast cancer, and microRNAs in cancer. The PPI network consisted of 27 upregulated and 54 downregulated mRNAs. By constructing ceRNA network, NONHSAT251752.1-hsa-miR-6817-5p-NOTCH1, NONHSAT251752.1-hsa-miR-204-5p/hsa-miR-138-5p-CDK6 regulatory axises were identified and all genes in the network were verified by qRT-PCR.ConclusionsThe present study constructed ceRNA networks in SACC and provided a novel perspective of the molecular mechanisms for SACC.

Identification of potential biomarkers for diagnosis of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) has a high mortality rate owing to its complexity. Identification of abnormally expressed genes in HCC tissues compared to those in normal liver tissues is a viable strategy for investigating the mechanisms of HCC tumorigenesis and progression as a means of developing novel treatments. A significant advantage of the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) is that the data therein were collected from different independent researchers and may be integrated, allowing for a more robust data analysis. Accordingly, in the present study, the gene expression profiles for HCC and control samples were downloaded from the GEO and TCGA. Functional enrichment analysis was performed using a Metascape dataset, and a protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/proteins (STRING) online database. The prognostic value of mRNA for HCC was assessed using the Kaplan-Meier Plotter, a public online tool. A gene mRNA heatmap and DNA amplification numbers were obtained from cBioPortal. A total of 2,553 upregulated genes were identified. Functional enrichment analysis revealed that these differentially expressed genes (DEGs) were mainly accumulated in metabolism of RNA and the cell cycle. Considering the complexity and heterogeneity of the molecular alterations in HCC, multiple genes for the prognostication of patients with HCC are more reliable than a single gene. Thus, the PPI network and univariate Cox regression analysis were applied to screen candidate genes (small nuclear ribonucleoprotein polypeptide B and B1, nucleoporin 37, Rac GTPase activating protein 1, kinesin family member 20A, minichromosome maintenance 10 replication initiation factor, ubiquitin conjugating enzyme E2 C and hyaluronan mediated motility receptor) that are associated with the overall survival and progression-free survival of patients with HCC. In conclusion, the present study identified a set of genes that are associated with overall survival and progression-free survival of patients with HCC, providing valuable information for the prognosis of HCC.

Identification of novel hub genes associated with lymph node metastasis of head and neck squamous cell carcinoma by completive bioinformatics analysis.

BackgroundHead and neck squamous cell carcinoma (HNSCC) is one of the most serious diseases affecting populations worldwide and lymph node metastasis is a key pathological feature of HNSCC which predicts poor survival. However, the molecular mechanisms associated with the development of lymph node metastasis in HNSCC have not been fully elucidated.MethodsDifferentially expressed genes (DEGs) were identified in two HNSCC datasets (GES6631 and GES58911). Functional annotation analysis was constructed via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Meanwhile, the protein-protein interaction (PPI) network and module analysis using Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and Cytoscape were carried out to identify the hub genes. The expression differences, overall survival (OS), and disease-free survival (DFS) of hub genes were analyzed by Gene Expression Profiling Interactive Analysis 2 (GEPIA2) and verified by immunohistochemistry (IHC) from Human Protein Atlas (HPA). Moreover, receiver operating characteristic (ROC) curve analysis was conducted to judge whether those hub genes had good diagnostic and prognostic ability, and the web tool Tumor Immune Estimation Resource (TIMER) was used to analyze the correlation of hub genes’ expression and immune infiltration.ResultsIn total, 913 DEGs including 476 upregulated and 437 downregulated genes were identified. The genes Aurora kinase A (AURKA), CyclinB1 (CCNB1), Cyclin-dependent kinase regulatory subunit 1B (CKS1B), Serpin Family H Member 1(SERPINH1), and Transforming growth factor-beta-induced protein (TGFBI) were screened out as hub genes and were associated with lymph node metastasis, showing notably abnormal expression in HNSCC samples, and the high expression of all the hub genes in HNSCC patients was related to worse overall survival.ConclusionsThe genes AURKA, CCNB1, CKS1B, SERPINH1, and TGFBI may be involved in the lymph node metastasis of HNSCC and reveal the potential to serve as molecular biomarkers in the diagnosis of HNSCC. This study may help to elucidate the molecular mechanisms of the development of lymph node metastasis and facilitate the selection of targets for the treatment and diagnosis of HNSCC.

Cyclin-dependent kinase 19 upregulation correlates with an unfavorable prognosis in hepatocellular carcinoma

ObjectivesCyclin-dependent kinase 19 (CDK19) is a component of the mediator coactivator complex, which is required for transcriptional activation. In this study, we utilized public databases and wet-bench hepatic cell line experiments to elucidate the potential roles of CDK19 in hepatocellular cancer (HCC).Materials and methodsWe studied the relationships between CDK19 expression and several clinical features related to HCC via the Oncomine and UALCAN databases. The prognostic value of CDK19 was tested using the Kaplan–Meier Plotter database. We presented the mutations of CDK19 and addressed the relation of CDK19 expression with immune cell infiltration by means of the cBioPortal, Catalogue of Somatic Mutations in Cancer (COSMIC) and Tumor IMmune Estimation Resource (TIMER) databases. Hub genes were obtained and further analyzed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. To test the in silico findings, we knocked down CDK19 with short hairpin RNA (shRNA) technology in two hepatic cell lines and conducted several functional characterization experiments.ResultsMarked CDK19 upregulation was found in HCC tissues versus normal liver tissues, and CDK19 mRNA expression had high diagnostic value in HCC patients. Subgroup analysis showed that CDK19 overexpression was associated with sex, tumor stage and TP53 mutation status. The prognostic value of CDK19 upregulation for overall survival (OS) was significant in patients with stage 2–3, stage 3–4, and grade 2 disease. One percent of the patients had CDK19 mutations, but no relationship between CDK19 mutation and prognosis was observed. CDK19 was positively correlated with the abundances of CD4 + T cells, macrophages and dendritic cells. We identified 10 genes correlated with CDK19, 8 of which presented excellent prognostic value in HCC. These hub genes were directly involved in cell division and regulation of the G2/M cell cycle transition. Protein–protein interaction (PPI) and pathway predictions indicated that CDK19 is highly likely to be involved in several cellular functions, such as proliferation, migration, and invasion. These functions were strongly interfered from two independent hepatic cell lines after CDK19 knockdown.ConclusionsCDK19 could be a prognostic marker in HCC, and its therapeutic potential in HCC needs further study.