Biological Function Analysis Research Articles

Proteomic Analysis Reveals Growth Inhibition of Coriolus versicolor by Methanol Extracts of Cinnamomum camphora Xylem

The extracts of decay-resistant tree species are important research objects for the future development of wood preservatives. To understand the antifungal mechanisms of Coriolus versicolor inhibition with methanol extracts of C. camphora xylem, the protein profiles of C. versicolor were analyzed using 2-DE followed by MALDI-TOF/MS and bioinformatic analyses. The results showed that 41 protein spots were obviously changed among the 366-385 protein spots of C. versicolor treated with methanol extracts of C. camphora xylem. Twenty-one protein spots were upregulated, and 20 protein spots were downregulated. Cellular localization was performed to identify these differential proteins, and biological process and functional analysis found that 9 of these proteins were in the cytoplasm, 6 were intracellular, and 5 were in the mitochondrion. A total of 18.8% were mapped to small-molecule metabolic processes, 12.5% to cellular amino acid metabolic processes, and 10.9% to cellular nitrogen compound metabolic processes. Twenty-five percent of the differential proteins were associated with ion bonding, 15% with oxidoreductase activity, and 15% with ATPase activity and transmembrane transport activity. Downregulated expression of aspartate aminotransferase, ATP synthase alpha chain, DEAD/DEAH-box helicase, and phosphoglycerate kinase showed that the methanol extracts of C. camphora xylem disrupted functional aspects such as nitrogen and carbon metabolism, energy metabolism, hormone signal response, and glucose metabolism, eventually leading to C. versicolor inhibition.

Differentially Expressed Functional LncRNAs in Human Subjects With Metabolic Syndrome Reflect a Competing Endogenous RNA Network in Circulating Extracellular Vesicles.

Metabolic syndrome (MetS), a collective cluster of disease risk factors that include dyslipidemia, obesity, inflammation, hypertension, and insulin resistance, affects numerous people worldwide. Accumulating studies have shown that long non-coding RNAs (lncRNAs) serve as competing endogenous RNAs (ceRNAs) to play essential roles in regulating gene expression in various diseases. To explore the role of lncRNAs as ceRNAs in MetS, we examined a MetS-associated network in circulating extracellular vesicles (EVs) collected from the systemic blood of MetS and control patients (n = 5 each). In total, 191 differentially expressed lncRNAs, 1,389 mRNAs, and 138 miRNAs were selected for further analysis. Biological processes and pathway functional enrichment analysis were performed based on the Database for Annotation, Visualization, and Integrated Discovery (DAVID). The lncRNA/mRNA/miRNA ceRNA network was constructed by Cytoscape v3.8 based on the DE-RNAs and included 13 lncRNAs, 8 miRNAs, and 64 mRNAs. MetS patients showed elevated body weight, glucose, blood pressure, insulin, liver injury, and inflammatory marker levels. We found that lncRNAs reflect a ceRNA network that may regulate central cellular processes and complications of MetS, including cancer. These findings suggest that MetS alters the interactions among the ceRNA network components in circulating EVs and that this cargo of circulating EVs may have potential translational ramifications for MetS.

Immune-Related Genes of Megalurothrips usitatus (Bagrall) Against Beauveria brongniartii and Akanthomyces attenuatus Identified Using RNA Sequencing.

Megalurothrips usitatus (Bagrall) is an important pest of legumes worldwide, causing great economic loss every year. Beauveria brongniartii and Akanthomyces attenuatus have shown considerable pathogenicity against M. usitatus in our previous studies. The medial lethal concentration (LC50) and the sublethal lethal concentration (LC25) of B. brongniartii isolate SB010 against M. usitatus were 8.38 × 105 and 1.73 × 105 conidia mL−1, respectively, whereas those of A. attenuatus isolate SCAUDCL-53 against M. usitatus were 4.37 × 105 and 2.97 × 104 conidia mL−1, respectively. This study reports the transcriptome-based explanation of the stress responses of M. usitatus following the application of B. brongniartii and A. attenuatus. The analysis of the transcriptomic data revealed the expression of 254, 207, 195, and 234 immunity-related unigenes by M. usitatus in response to B. brongniartii LC50 (SB1), B. brongniartii LC25 (SB2), A. attenuatus LC50 (V1), and A. attenuatus LC25 (V2), respectively. The biological function and metabolic pathway analyses showed that these unigenes were mainly related to pattern recognition receptors, information transduction factors, and reaction factors, such as scavenger receptor, cytochrome b5, cuticle protein, lysozyme, and serine protease.

Urinary Proteomics Identifying Novel Biomarkers for the Diagnosis and Phenotyping of Carotid Artery Stenosis.

Background: Carotid artery stenosis (CAS) is caused by the formation of atherosclerotic plaques inside the arterial wall and accounts for 20–30% of all strokes. The development of an early, noninvasive diagnostic method and the identification of high-risk patients for ischemic stroke is essential to the management of CAS in clinical practice.Methods: We used the data-independent acquisition (DIA) technique to conduct a urinary proteomic study in patients with CAS and healthy controls. We identified the potential diagnosis and risk stratification biomarkers of CAS. And Ingenuity pathway analysis was used for functional annotation of differentially expressed proteins (DEPs). Furthermore, receiver operating characteristic (ROC) analysis was performed to evaluate the diagnostic values of DEPs.Results: A total of 194 DEPs were identified between CAS patients and healthy controls by DIA quantification. The bioinformatics analysis showed that these DEPs were correlated with the pathogenesis of CAS. We further identified 32 DEPs in symptomatic CAS compared to asymptomatic CAS, and biological function analysis revealed that these proteins are mainly related to immune/inflammatory pathways. Finally, a biomarker panel of six proteins (ACP2, PLD3, HLA-C, GGH, CALML3, and IL2RB) exhibited potential diagnostic value in CAS and good discriminative power for differentiating symptomatic and asymptomatic CAS with high sensitivity and specificity.Conclusions: Our study identified novel potential urinary biomarkers for noninvasive early screening and risk stratification of CAS.

Comprehensive analysis of new prognostic signature based on ferroptosis-related genes in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is an aggressive tumor and the most common subtype of RCC. Ferroptosis is a novel form of regulated cell death, and ferroptosis-related genes (FRGs) have been associated with the prognosis of patients with certain cancers. However, the detailed prognostic correlation between FRGs and ccRCC has not yet been elucidated. To address this, the current study used The Cancer Genome Atlas (TCGA) dataset to explore 64 FRGs and determine their prognostic value in ccRCC. Results showed that 52 out of the 64 genes displayed significantly different expression levels in tumor tissue, and 35 out of the 52 differentially expressed genes (DEGs) were associated with overall survival. Subsequently, a four-gene prognostic signature (CD44, DPP4, NCOA4 and SLC7A11) was constructed and could successfully distinguish ccRCC patients with different prognosis in TCGA train and test sets. Furthermore, clinical ccRCC samples from our medical center were used to verify the application value of the new prognostic signature through immunohistochemistry and quantitative real-time polymerase chain reaction (qRT-PCR). Biological functional analysis implied that immune-related functions and pathways were enriched in the TCGA cohort and the immune status scores were significantly different between high- and low-risk sets. These results suggest that the four ferroptosis-related regulatory genes can act as reliable prognostic biomarkers of ccRCC, and might be exploited as potential targets of therapeutic strategies.

Pharmacokinetic and metabolomics approach based on UHPLC-MS to evaluate therapeutic effect of lignans from S. Chinensis in alzheimer's disease

Lignans from Schisandra chinensis (Turcz.) Baill (LFS) has been proved to improve impaired cognitive ability thereby show potential in treating Alzheimer’s disease (AD). In this study, UHPLC-Q-TOF-MS and UHPLC-QQQ-MS were adopted cooperatively to establish a method synchronously detecting 10 kinds of LFS monomers in rat plasma samples. And this method was further applied for pharmacokinetic study to compare the metabolism of LFS in normal and AD rats. The results indicated that AD rats showed an observably better absorption of LFS compared to normal rats. Based on time-varying plasma concentration of LFS, metabolomics was used to establish a plasma concentration–time-endogenous metabolite connection. In total 54 time-varying endogenous metabolites were screened and most of which were closely associated with AD. And LFS exerted a concentration dependent regulating effect to most of these metabolites. Through biomarker related pathways and biological function analysis, LFS might treat AD through neuroprotection, antioxidant damage and regulating the metabolism of unsaturated fatty acids. This is the first study connecting LFS absorbtion and endogenous metabolite changes with the time lapse. The pharmacokinetics and metabolic profile differences between normal and AD rats were firstly investigated as well. This study provides a novel perspective in exploring the effect and mechanism of LFS in treating AD.

Mechanism of Tetrandrine Against Endometrial Cancer Based on Network Pharmacology.

BackgroundEndometrial cancer (EC) is one of the most common gynaecological malignancies, and its incidence has been rising over the past decade. Tetrandrine, a bisbenzylisoquinoline alkaloid, has been isolated from a vine used in traditional Chinese medicine, Stephania tetrandra. However, the key mechanism of tetrandrine in EC is still unclear.PurposeThis research was designed to predict the molecular mechanisms of tetrandrine against EC based on network pharmacology and to further verify these predictions by in vitro experiments.MethodsThe potential therapeutic targets of tetrandrine against EC were predicted by using public databases. Afterwards, the protein–protein interaction (PPI) network of the common targets was constructed, and the key gene targets were obtained. Biological function and pathway enrichment analyses were performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Furthermore, molecular docking and in vitro experiments were carried out to verify the predictions. The cell counting kit‑8 (CCK‑8) assay, Hoechst 33258 staining, flow cytometry analysis, qRT-PCR, Western blot analysis and an immunofluorescence assay were performed.ResultsOur findings identified 111 potential therapeutic targets of tetrandrine against EC. We obtained 7 key gene targets from the PPI network analysis. Furthermore, GO enrichment analysis indicated that these targets were mainly associated with metabolic processes, responses to stimulus, and biological regulation. The KEGG pathway analysis showed that the common targets were mainly distributed in the PI3K/Akt signalling pathway. A potential interaction of tetrandrine with Akt1 was revealed by molecular docking. In addition, in vitro experiments showed that tetrandrine significantly inhibited cell proliferation and induced apoptosis in Ishikawa and HEC-1-B cells in dose- and time-dependent manners. The results also revealed that tetrandrine can downregulate the expression of Bcl-2 and upregulate the expression of Bax at the mRNA level. The mRNA levels of Akt were not significantly different in the various tetrandrine (0, 10 and 20µM) groups. However, Western blot analysis demonstrated that the protein expression ratios of p-Akt/Akt decreased at the protein level. The results were further confirmed by immunofluorescence assays.ConclusionBased on bioinformatic analysis and experimental verification, our findings demonstrated that tetrandrine exerted tumour-suppressive effects on EC by regulating the PI3K/Akt signalling pathway.

Integrating genome-wide association and transcriptome prediction model identifies novel target genes for osteoporosis

SummaryIn this study, we integrated large-scale GWAS summary data and used the predicted transcriptome-wide association study method to discover novel genes associated with osteoporosis. We identified 204 candidate genes, which provide novel clues for understanding the genetic mechanism of osteoporosis and indicate potential therapeutic targets.IntroductionOsteoporosis is a highly polygenetic disease characterized by low bone mass and deterioration of the bone microarchitecture. Our objective was to discover novel candidate genes associated with osteoporosis.MethodsTo identify potential causal genes of the associated loci, we investigated trait-gene expression associations using the transcriptome-wide association study (TWAS) method. This method directly imputes gene expression effects from genome-wide association study (GWAS) data using a statistical prediction model trained on GTEx reference transcriptome data. We then performed a colocalization analysis to evaluate the posterior probability of biological patterns: associations characterized by a single causal variant or multiple distinct causal variants. Finally, a functional enrichment analysis of gene sets was performed using the VarElect and CluePedia tools, which assess the causal relationships between genes and a disease and search for potential gene’s functional pathways. The osteoporosis-associated genes were further confirmed based on the differentially expressed genes profiled from mRNA expression data of bone tissue.ResultsOur analysis identified 204 candidate genes, including 154 genes that have been previously associated with osteoporosis, 50 genes that have not been previously discovered. A biological function analysis found that 20 of the candidate genes were directly associated with osteoporosis. Further analysis of multiple gene expression profiles showed that 15 genes were differentially expressed in patients with osteoporosis. Among these, SLC11A2, MAP2K5, NFATC4, and HSP90B1 were enriched in four pathways, namely, mineral absorption pathway, MAPK signaling pathway, Wnt signaling pathway, and PI3K-Akt signaling pathway, which indicates a causal relationship with the occurrence of osteoporosis.ConclusionsWe demonstrated that transcriptome fine-mapping identifies more osteoporosis-related genes and provides key insight into the development of novel targeted therapeutics for the treatment of osteoporosis.

Transcriptome Profiling of m6A mRNA Modification in Bovine Mammary Epithelial Cells Treated with Escherichia coli.

Mastitis is a common disease in dairy cows that is mostly caused by E. coli, and it brings massive losses to the dairy industry. N6-Methyladenosine (m6A), a methylation at the N6 position of RNA adenine, is a type of modification strongly associated with many diseases. However, the role of m6A in mastitis has not been investigated. In this study, we used MeRIP-seq to sequence the RNA of bovine mammary epithelial cells treated with inactivated E. coli for 24 h. In this in vitro infection model, there were 16,691 m6A peaks within 7066 mRNA transcripts in the Con group and 10,029 peaks within 4891 transcripts in the E. coli group. Compared with the Con group, 474 mRNAs were hypermethylated and 2101 mRNAs were hypomethylated in the E. coli group. Biological function analyses revealed differential m6A-modified genes mainly enriched in the MAPK, NF-κB, and TGF-β signaling pathways. In order to explore the relationship between m6A and mRNA expression, combined MeRIP-seq and mRNA-seq analyses revealed 212 genes with concomitant changes in the mRNA expression and m6A modification. This study is the first to present a map of RNA m6A modification in mastitis treated with E. coli, providing a basis for future research.

Sex-Specific Age-Related Changes in Methylation of Certain Genes.

The aim of the study was to conduct a functional analysis of sex-specific age-related changes in DNA methylation.Materials and MethodsThe study used a GSE87571 methylation dataset obtained from the blood DNA of 729 individuals aged 14 to 94 using the Illumina Infinium HumanMethylation450K BeadChip (USA). Gene ontology analysis was performed for 3 groups of genes (females, males, and duplicates) using the PANTHER database. The DAVID platform was used to perform KEGG metabolic pathway analysis.ResultsThe studies revealed unique for males and females changes in methylation of CpG sites, associated with certain metabolic processes. It was demonstrated that most of the CpG sites, for which methylation changes with age were revealed in both sexes, are associated with the genes responsible for the development and functioning of the nervous system. In males, unique age-related methylation changes affect CpG sites associated with changes in the immune system and lipid metabolism. In females, most CpGs are associated with changes involved in transcription and translation processes. Analysis of biological functions by KEGG revealed that a unique process associated with age-related changes in methylation of the glutamatergic system is typical for males. In females, unique biological processes with age-related changes include genes responsible for the development of diabetes and genes associated with cAMP signaling cascades (KEGG:04024).ConclusionOur studies reveal fundamental features of sex-dependent changes in methylation of CpG sites with variance increasing, which may indicate differences in age-related changes.

Immune-related gene expression signatures in colorectal cancer.

The immune system is crucial in regulating colorectal cancer (CRC) tumorigenesis. Identification of immune-related transcriptomic signatures derived from the peripheral blood of patients with CRC would provide insights into CRC pathogenesis, and suggest novel clues to potential immunotherapy strategies for the disease. The present study collected blood samples from 59 patients with CRC and 62 healthy control patients and performed whole blood gene expression profiling using microarray hybridization. Immune-related gene expression signatures for CRC were identified from immune gene datasets, and an algorithmic predictive model was constructed for distinguishing CRC from controls. Model performance was characterized using an area under the receiver operating characteristic curve (ROC AUC). Functional categories for CRC-specific gene expression signatures were determined using gene set enrichment analyses. A Kaplan-Meier plotter survival analysis was also performed for CRC-specific immune genes in order to characterize the association between gene expression and CRC prognosis. The present study identified five CRC-specific immune genes [protein phosphatase 3 regulatory subunit Bα (PPP3R1), amyloid β precursor protein, cathepsin H, proteasome activator subunit 4 and DEAD-Box Helicase 3 X-Linked]. A predictive model based on this five-gene panel showed good discriminatory power (independent test set sensitivity, 83.3%; specificity, 94.7%, accuracy, 89.2%; ROC AUC, 0.96). The candidate genes were involved in pathways associated with ‘adaptive immune responses’, ‘innate immune responses’ and ‘cytokine signaling’. The survival analysis found that a high level of PPP3R1 expression was associated with a poor CRC prognosis. The present study identified five CRC-specific immune genes that were potential diagnostic biomarkers for CRC. The biological function analysis indicated a close association between CRC pathogenesis and the immune system, and may reveal more information about the immunogenic and pathogenic mechanisms driving CRC in the future. Overall, the association between PPP3R1 expression and survival of patients with CRC revealed potential new targets for CRC immunotherapy.

Whole transcriptome analysis of the differential RNA profiles and associated competing endogenous RNA networks in LPS-induced acute lung injury (ALI).

Acute lung injury (ALI) is a serious inflammation disease usually arises alveolar epithelial membrane dysfunction and even causes death. Therefore, the aims of this study are to screen the differentially expressed lncRNAs, circRNAs, miRNAs, and mRNAs in ALI based on the high-throughput sequencing. The lipopolysaccharide (LPS)-induced ALI mouse model was established, the injury of ALI mouse model was evaluated through histological analysis with hemotoxylin and eosin (H & E) staining assay, dry/wet ratio, infiltrated-immune cells, ET-1 mRNA expression and released-proinflammation factors. Then, expression data of lncRNAs, circRNAs, miRNAs and mRNAs in ALI were acquired using whole-transcriptome sequencing. The differential expression of lncRNAs (DE lncRNAs), circRNAs (DE circRNAs), miRNAs (DE miRNAs) and mRNAs (DE mRNAs) were identified, and the lncRNA-miRNA-mRNA network and circRNA-miRNA-mRNA network were constructed, and the biological function of target genes were annotated based on bioinformatics analysis. In the present study, the LPS-induced ALI mouse model was successfully established. The biological analysis results showed that total 201 DE lncRNAs, 172 DE circRNAs, 62 DE miRNAs, and 3081 DE mRNAs were identified in ALI. The 182 lncRNA-miRNA-mRNA networks and 32 circRNA-miRNA-mRNA networks were constructed were constructed based on the correlation between lncRNAs/circRNAs, miRNAs, mRNAs. The biological function analysis indicated that TNF signaling pathway, chemokine signaling pathway and so on involved in ALI. In the present study, the differential expression coding and non-coding RNAs (ncRNAs) in ALI were identified, and their regulatory networks were constructed. There might provide the potential biomarkers and underlying mechanism for ALI diagnosis and treatment.

Expression,Protein Interactions and Biological Function Analysis of FaFT in Festuca arundinacea

Expression,Protein Interactions and Biological Function Analysis of FaFT in Festuca arundinacea

Puromycin-Modified Silica Microsphere-Based Nascent Proteomics Method for Rapid and Deep Nascent Proteome Profile.

Nascent proteome is crucial in directly revealing how the expression of a gene is regulated on a translation level. In the nascent protein identification, puromycin capture is one of the pivotal methods, but it is still facing the challenge in the deep profiling of nascent proteomes due to the low abundance of most nascent proteins. Here, we describe the synthesis of puromycin-modified silica microspheres (PMSs) as the sorbent of dispersive solid-phase microextraction and the establishment of the PMS-based nascent proteomics (PMSNP) method for efficient capture and analysis of nascent proteins. The modification efficiency of puromycin groups on silica microspheres reached 91.8% through the click reaction. After the optimization and simplification of PMSNP, more than 3500 and 3900 nascent proteins were rapidly identified in HeLa cells and mouse brains within 13.5 h, respectively. The PMSNP method was successfully applied to explore changes in the translation process in a biological stress model, namely, the lipopolysaccharide-stimulated HeLa cells. Biological functional analyses revealed the unique characters of the nascent proteomes and exhibited the superiority of the PMSNP in the identification of low abundance and secreted nascent proteins, thus demonstrating the sensitivity and immediacy of the PMSNP method.

Gene co-expression network analysis reveals key pathways and hub genes in Chinese cabbage (Brassica rapa L.) during vernalization

BackgroundVernalization is a type of low temperature stress used to promote rapid bolting and flowering in plants. Although rapid bolting and flowering promote the reproduction of Chinese cabbages (Brassica rapa L. ssp. pekinensis), this process causes their commercial value to decline. Clarifying the mechanisms of vernalization is essential for its further application. We performed RNA sequencing of gradient-vernalization in order to explore the reasons for the different bolting process of two Chinese cabbage accessions during vernalization.ResultsThere was considerable variation in gene expression between different-bolting Chinese cabbage accessions during vernalization. Comparative transcriptome analysis and weighted gene co-expression network analysis (WGCNA) were performed for different-bolting Chinese cabbage during different vernalization periods. The biological function analysis and hub gene annotation of highly relevant modules revealed that shoot system morphogenesis and polysaccharide and sugar metabolism caused early-bolting ‘XBJ’ to bolt and flower faster; chitin, ABA and ethylene-activated signaling pathways were enriched in late-bolting ‘JWW’; and leaf senescence and carbohydrate metabolism enrichment were found in the two Chinese cabbage-related modules, indicating that these pathways may be related to bolting and flowering. The high connectivity of hub genes regulated vernalization, including MTHFR2, CPRD49, AAP8, endoglucanase 10, BXLs, GATLs, and WRKYs. Additionally, five genes related to flower development, BBX32 (binds to the FT promoter), SUS1 (increases FT expression), TSF (the closest homologue of FT), PAO and NAC029 (plays a role in leaf senescence), were expressed in the two Chinese cabbage accessions.ConclusionThe present work provides a comprehensive overview of vernalization-related gene networks in two different-bolting Chinese cabbages during vernalization. In addition, the candidate pathways and hub genes related to vernalization identified here will serve as a reference for breeders in the regulation of Chinese cabbage production.

The Influence of Let-7b-5p Target Gene in Cholangiocarcinoma and its Bioinformatic Analysis

Objective: To analyze the biological functions and its clinical significance of let-7b-5p target gene in cholangiocarcinoma utilizing bioinformatics. Methods: The paper focuses on the let-7b-5p target gene, and predicts its biological functions as well as related signal pathways through GO biological function and KEGG signal pathway enrichment analysis. The STRING database and Cytoscape are used to construct a protein-protein interaction network to screen core genes. Results: The results of GO analysis showed that let-7b-5p target gene was mainly enriched in biological processes such as Small GTPase binding, Rho GTPase binding, and Rac GTPase binding. The results of KEGG analysis showed that let-7b-5p target gene was significantly enriched in key signaling pathways including Focal adhesion and ECM-receptor interaction. Through protein-protein interaction network and module analysis, CXCL8 and SDC2 were screened as the core site. Conclusion: let-7b-5p can participate in the regulation of biological functions of tumor cells in cholangiocarcinoma, suggesting that it may play an important role as a tumor suppressor gene and biomarker in the occurrence and development of cholangiocarcinoma, which provides new ideas for its diagnosis and treatment.

Screening of miRNAs as Prognostic Biomarkers for Colon Adenocarcinoma and Biological Function Analysis of Their Target Genes.

We constructed a prognostic risk model for colon adenocarcinoma (COAD) using microRNAs (miRNAs) as biomarkers. Clinical data of patients with COADs and miRNA-seq data were from TCGA, and the differential expression of miRNAs (carcinoma vs. para-carcinoma tissues) was assessed using R software. COAD data were randomly divided into Training and Testing Sets. A linear prognostic risk model was constructed using Cox regression analysis based on the Training Set. Patients were classified as high-risk or low-risk according to the score of the prognostic model. Survival analysis and receiver operating characteristic (ROC) curves were used to evaluate model performance. The gene targets in the prognostic model were identified and their biological functions were analyzed. Analysis of COAD and normal cell lines using qPCR was used to verify the model. There were 134 up-regulated and 140 down-regulated miRNAs. We used the Training Set to develop a prognostic model based on the expression of seven miRNAs. ROC analysis indicated this model had acceptable prediction accuracy (area under the curve=0.784). Kaplan-Meier survival analysis showed that overall survival was worse in the high-risk group. Cox regression analysis showed that the 7-miRNA Risk Score was an independent prognostic factor. The 2,863 predicted target genes were mainly enriched in the MAPK, PI3K-AKT, proteoglycans in cancer, and mTOR signaling pathways. For unknown reasons, expression of these miRNAs in cancerous and normal cells differed somewhat from model predictions. Regardless, the 7-miRNA Risk Score can be used to predict COAD prognosis and may help to guide clinical treatment.

A Novel Nine Apoptosis-Related Genes Signature Predicting Overall Survival for Kidney Renal Clear Cell Carcinoma and its Associations with Immune Infiltration.

Background: This study was designed to establish a sensitive prognostic model based on apoptosis-related genes to predict overall survival (OS) in patients with clear cell renal cell carcinoma (ccRCC). Methods: Obtaining the expression of apoptosis-related genes and associated clinical parameters from online datasets (The Cancer Genome Atlas, TCGA), their biological function analyses were performed through differently expressed genes. By means of LASSO, unadjusted and adjusted Cox regression analyses, this predictive signature was constructed and validated by internal and external databases (both TCGA and ArrayExpress). Results: A total of nine apoptosis-related genes (SLC27A2, TNFAIP2, IFI44, CSF2, IL4, MDK, DOCK8, WNT5A, APP) were ultimately screened as associated hub genes and utilized to construct a prognosis model. Then our constructed riskScore model significantly passed the validation in both the internal and external datasets of OS (all p < 0.05) and verified their expressions by qRT-PCR. Moreover, we conducted the Receiver Operating Characteristic (ROC), finding the area under the ROC curves (AUCs) were all above 0.70 which indicated that riskScore was a stable independent prognostic factor (p < 0.05). Furthermore, prognostic nomograms were established to figure out the relationship between 1-, 3- and 5-year OS and individual parameters for ccRCC patients. Additionally, survival analyses indicated that our riskScore worked well in predicting OS in subgroups of age, gender, grade, stage, T, M, N0, White (all p < 0.05), except for African, Asian and N1 (p > 0.05). We also explored its association with immune infiltration and applied cMap database to seek out highly correlated small molecule drugs. Conclusion: Our study successfully constructed a prognostic model containing nine hub apoptosis-related genes for ccRCC, helping clinicians predict patients’ OS and making the prognostic assessment more standardized. Future prospective studies are required to validate our findings.

Analysis of the potential and mechanism of Ginkgo biloba in the treatment of Alzheimer's disease based on network pharmacology.

Study the principle and possible mechanism of Ginkgo biloba in the treatment of Alzheimer's disease (AD) which is based on network pharmacology. The potential targets of active ingredients of Ginkgo biloba were collected by Traditional Chinese Medicine Integrated Database platform (TCMSP). TCMSP is a pharmacological system for drug discovery from Chinese herbal medicine. The disease targets of AD were searched and collected by the database of gene-disease associations (DisGeNET) and literature. The obtained targets were standardized by the UniProt database. STING network platform and Cytoscape were used to construct protein-protein interaction network (PPI) of the key targets. According to Materscape, we clarify the possible mechanism of action including Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) enrichment analysis. The compound-target network contains 27 active ingredients, 191 related targets, 18 key targets, including PLAU, HMOX1, TNF, INSR, MPO, MAOB, IGF2, IL1B, ESR1, BCL2, ACHE, BAX, GSK3B, PPARG, SLC2A4, NOS3, CASP3, VEGFA. GO enrichment analysis has got a total of 640 GO items, including 609 biological process (BP) items (95.1%), 16 molecular function (MF) items (2.5%) and 15 cellular component (CC) items (2.4%). After KEGG enrichment, 44 pathways were obtained. Through the construction of "component-target-pathway", GO biological function and KEGG pathway enrichment analysis were performed on core targets, and the possibility of Ginkgo biloba for the treatment of AD was explored from multiple targets and pathways, which provided a new approach for multi-target treatment.

Bioinformatic analysis for the identification of potential gene interactions and therapeutic targets in atrial fibrillation.

Atrial fibrillation (AF) is the most common type of tachycardia. The major injury caused by AF is a systemic embolism. Although AF therapies have evolved substantially, the success rate of sinus rhythm maintenance is relatively low. The reason is the incomplete understanding of the AF mechanisms. A Gene Expression Omnibus (GEO) dataset (GSE79768) was downloaded. Differentially expressed genes (DEGs) were identified by bioinformatic analysis. Enriched terms and pathways were identified by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. A protein-protein interaction (PPI) network was constructed to determine regulatory genes. CytoHubba and the Molecular Complex Detection (MCODE) algorithm were used to identify potential hub genes and important modules. The Predicting Associated Transcription Factors From Annotated Affinities (PASTAA) method was used to predict transcription factors (TFs). Two hundred thirty-five upregulated DEGs and seventy-seven downregulated DEGs were identified. In the GO biological process, cellular component, and molecular function analyses, positive regulation of cell migration, anchoring junctions, and cell adhesion molecule binding were enriched significantly. The Hippo signalling pathway was the most significantly enriched pathway. In the PPI network analysis, we found that Class A/1 (rhodopsin-like receptors) may be the critical module. Ten hub genes were extracted, including 6 upregulated genes and 4 downregulated genes. CXCR2, TLR4, and CXCR4 may play critical roles in AF. In the TF prediction, we found that Irf-1 may be implicated in AF. We found that the CXCR4, TLR4, CXCR2 genes, the Hippo signalling pathway and the class A/1 (rhodopsin-like receptors) module may play critical roles in AF occurrence and maintenance, which may provide novel targets for AF treatment.