Identification and Validation of Glomerulotubular Crosstalk Genes Mediating IgA Nephropathy by Integrated Bioinformatics

BackgroundIgA nephropathy (IgAN), which has been reported as the most prevalent glomerulonephritis globally, is the major contributor to end-stage renal illness. This bioinformatics study aimed to explore glomeruli-tubulointerstitial crosstalk genes and dysregulated pathways relating to the pathogenesis of IgAN. MethodsThe microarray datasets from the Gene Expression Omnibus (GEO) database were searched. Weighted gene co-expression network analysis (WGCNA) and differentially expressed genes (DEGs) of both glomeruli and tubulointerstitial were conducted individually. The co-expression gene modules of tubulointerstitial and glomeruli were compared via gene function enrichment analysis. Subsequently, the crosstalk co-expression network was constructed via the STRING database and key genes were mined from the crosstalk network. Results583 DEGs and eight modules were identified in glomeruli samples, while 272 DEGs and four modules were in tubulointerstitial samples. There were 119 overlapping DEGs of the two groups. Among the distinctive modules, four modules in glomeruli and one module in tubulointerstitial were positively associated with IgAN. While four modules in glomeruli and two modules in tubulointerstitial were negatively associated with IgAN. The top ten key genes screened by CytoHubba were ITGAM, ALB, TYROBP, ITGB2, CYBB, HCK, CSF1R, LAPTM5, FN1and CTSS. The above genes were all validated using another two datasets, and all of the key genes demonstrated possible diagnostic significance. Conclusionshe crosstalk genes confirmed in this study may provide novel insight into the pathogenesis of IgAN. Immune-related pathways are associated with both glomerular and tubulointerstitial injuries in IgAN. The glomerulotubular crosstalk might perform a role in the pathogenesis of IgAN.

Predicting the Molecular Mechanism of Sini Jia Renshen Decoction in Treating Severe COVID-19 Patients Based on Network Pharmacology and Molecular Docking

Objective: To explore the potential mechanism of Sini jia Renshen Decoction (SJRD) in the treatment of COVID-19 based on network pharmacology and molecular docking. Methods: The active compounds and potential therapeutic targets of SJRD were collected through the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP). Then a string database was used to build a protein–protein interactions (PPI) network between proteins, and use the David database to perform gene ontology (GO) function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on core targets. Then we used Cytoscape software to construct an active ingredients-core target-signaling pathway network, and finally the active ingredients of SJRD were molecularly docked with the core targets to predict the mechanism of SJRD in the treatment of COVID-19. Results: A total of 136 active compounds, 51 core targets and 93 signaling pathways were selected. Molecular docking results revealed that quercetin, 3,22-dihydroxy-11-oxo-delta(12)-oleanene-27-alpha-methoxycarbonyl-29-oic acid, 18α-hydroxyglycyrrhetic acid, gomisin B and ignavine had considerable binding ability with ADRB2, PRKACA, DPP4, PIK3CG and IL6. Conclusions: This study preliminarily explored the mechanism of multiple components，multiple targets，and multiple pathways of SJRD in the treatment of COVID-19 by network pharmacology．

Integrative COVID-19 Biological Network Inference with Probabilistic Core Decomposition

The SARS-CoV-2 coronavirus is responsible for millions of deaths around the world. To help contribute to the understanding of crucial knowledge and to further generate new hypotheses relevant to SARS-CoV-2 and human protein interactions, we make use of the information abundant Biomine probabilistic database and extend the experimentally identified SARS-CoV-2-human protein-protein interaction (PPI) network in silico. We generate an extended network by integrating information from the Biomine database and the PPI network. To generate novel hypotheses, we focus on the high-connectivity sub-communities that overlap most with the PPI network in the extended network. Therefore, we propose a new data analysis pipeline that can efficiently compute core decomposition on the extended network and identify dense subgraphs. We then evaluate the identified dense subgraph and the generated hypotheses in three contexts: literature validation for uncovered virus targeting genes and proteins, gene function enrichment analysis on subgraphs, and literature support on drug repurposing for identified tissues and diseases related to COVID-19. The majority types of the generated hypotheses are proteins with their encoding genes and we rank them by sorting their connections to known PPI network nodes. In addition, we compile a comprehensive list of novel genes, and proteins potentially related to COVID-19, as well as novel diseases which might be comorbidities. Together with the generated hypotheses, our results provide novel knowledge relevant to COVID-19 for further validation.

Construction of a circRNA-miRNA-mRNA Regulatory Network Reveals Potential Mechanism and Treatment Options for Osteosarcoma

BackgroundOsteosarcoma is a common malignant primary bone tumor in adolescents and children. Numerous studies have shown that circRNAs were involved in the proliferation and invasion of various tumors. However, the role of circRNAs in osteosarcoma remains unclear. Here, we aimed to explore the regulatory network among circRNA-miRNA-mRNA in osteosarcoma.MethodsThe circRNA (GSE140256), microRNA (GSE28423), and mRNA (GSE99671) expression profiles of osteosarcoma were collected from the Gene Expression Omnibus (GEO) database. Differentially expressed circRNAs, miRNAs and mRNAs were identified. CircRNA-miRNA interactions and miRNA-mRNA interactions were determined by Circular RNA Interactome (CircInteractome) database and microRNA Data Integration Portal (mirDIP) database, respectively. Then, we constructed a regulatory network. Function enrichment analysis of miRNA and mRNA was performed by DIANA-miRPath v3.0 and Metascape database, respectively. mRNAs with significant prognostic value were identified based on expression profiles from The Cancer Genome Atlas (TCGA) database, and we constructed a subnetwork for them. To make the most of the network, we used the CLUE database to predict potential drugs for the treatment of osteosarcoma based on mRNA expression in the network. And we used the STITCH database to analyze and validate the interactions among these drugs and mRNAs, and to further screen for potential drugs.ResultsA total of 9 circRNAs, 19 miRNAs, 67 mRNAs, 54 pairs of circRNA-miRNA interactions and 110 pairs of miRNA-mRNA interactions were identified. A circRNA-miRNA-mRNA network was constructed. Function enrichment analysis indicated that these miRNAs and mRNAs in the network were involved in the process of tumorigenesis and immune response. Among these mRNAs, STC2 and RASGRP2 with significantly prognostic value were identified, and we constructed a subnetwork for them. Based on mRNA expression in the network, three potential drugs, quinacridine, thalidomide and zonisamide, were screened for the treatment of osteosarcoma. Among them, quinacridine and thalidomide have been proved to have anti-tumor effects in previous studies, while zonisamide has not been reported. And a corresponding drug-protein interaction network was constructed.ConclusionOverall, we constructed a circRNA-miRNA-mRNA regulatory network to investigate the possible mechanism in osteosarcoma, and predicted that quinacridine, thalidomide and zonisamide could be potential drugs for the treatment of osteosarcoma.

Validation of the Functions and Prognostic Values of Synapse Associated Proteins in Lower-grade Glioma

Synapse and synapse associated proteins (SAPs) play critical roles in various neurodegeneration diseases and brain tumors. However, in lower-grade gliomas (LGG), SAPs have not been explored systematically. Herein, we are going to explore SAPs expression profile and its clinicopathological significance in LGG which can offer new insights to glioma therapy. In this study, we integrate a list of SAPs that covered 231 proteins with synaptogenesis activity and post synapse formation. The LGG RNA-seq data were downloaded from GEO, TCGA and CGGA database. The prognosis associated SAPs in key modules of PPI (protein-protein interaction networks) was regarded as hub SAPs. Western blot, quantitative reverse transcription PCR (qRT-PCR) and immunochemistry results from HPA database were used to verify the expression of hub SAPs. There were 68 upregulated SAPs and 44 downregulated SAPs in LGG tissue compared with normal brain tissue. Data from function enrichment analysis revealed functions of differentially expressed SAPs in synapse organization and glutamatergic receptor pathway in LGGs. Survival analysis revealed that four SAPs, GRIK2, GABRD, GRID2 and ARC were correlate with the prognosis of LGG patients. Interestingly, we found that GABRD were upregulated in LGG patients with seizures, indicating that SAPs may link to the pathogenesis of seizures in glioma patients. The four-SAPs signature was revealed as an independent prognostic factor in gliomas. Our study presented a novel strategy to assess the prognostic risks of LGGs, based on the expression of SAPs.

Network Pharmacology Reveals Polyphyllin II as One Hit of Nano Chinese Medicine Monomers against Nasopharyngeal Carcinoma

Nasopharyngeal carcinoma (NPC) is a malignant tumor in southern China, and nano Traditional Chinese Medicine (TCM) represents great potential to cancer therapy. To predict the potential targets and mechanism of polyphyllin II against NPC and explore its possibility for the future nano-pharmaceutics of Chinese medicine monomers, network pharmacology was included in the present study. Totally, ninety-four common potential targets for NPC and polyphyllin II were discovered. Gene Ontology (GO) function enrichment analysis showed that biological processes and functions mainly concentrated on apoptotic process, protein phosphorylation, cytosol, protein binding, and ATP binding. In addition, the anti-NPC effects of polyphyllin II mainly involved in the pathways related to cancer, especially in the PI3K-Akt signaling indicated by the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The “drug-target-disease” network diagram indicated that the key genes were SRC, MAPK1, MAPK14, and AKT1. Taken together, this study revealed the potential drug targets and underlying mechanisms of polyphyllin II against NPC through modern network pharmacology, which provided a certain theoretical basis for the future nano TCM research.

Integrative Analysis of Three Novel Competing Endogenous RNA Biomarkers with a Prognostic Value in Lung Adenocarcinoma

Increasing evidence has shown competitive endogenous RNAs (ceRNAs) play key roles in numerous cancers. Nevertheless, the ceRNA network that can predict the prognosis of lung adenocarcinoma (LUAD) is still lacking. The aim of the present study was to identify the prognostic value of key ceRNAs in lung tumorigenesis. Differentially expressed (DE) RNAs were identified between LUAD and adjacent normal samples by limma package in R using The Cancer Genome Atlas database (TCGA). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway function enrichment analysis was performed using the clusterProfiler package in R. Subsequently, the LUAD ceRNA network was established in three steps based on ceRNA hypothesis. Hub RNAs were identified using degree analysis methods based on Cytoscape plugin cytoHubba. Multivariate Cox regression analysis was implemented to calculate the risk score using the candidate ceRNAs and overall survival information. The survival differences between the high-risk and low-risk ceRNA groups were determined by the Kaplan-Meier and log-rank test using survival and survminer package in R. A total of 2,989 mRNAs, 185 lncRNAs, and 153 miRNAs were identified. GO and KEGG pathway function enrichment analysis showed that DE mRNAs were mainly associated with “sister chromatid segregation,” “regulation of angiogenesis,” “cell adhesion molecules (CAMs),” “cell cycle,” and “ECM-receptor interaction.” LUAD-related ceRNA network was constructed, which comprised of 54 nodes and 78 edges. Top ten hub RNAs (hsa-miR-374a-5p, hsa-miR-374b-5p, hsa-miR-340-5p, hsa-miR-377-3p, hsa-miR-21-5p, hsa-miR-326, SNHG1, RALGPS2, and PITX2) were identified according to their degree. Kaplan-Meier survival analyses demonstrated that hsa-miR-21-5p and RALGPS2 had a significant prognostic value. Finally, we found that a high risk of three novel ceRNA interactions (SNHG1-hsa-miR-21-5p-RALGPS2, SNHG1-hsa-miR-326-RALGPS2, and SNHG1-hsa-miR-377-3p-RALGPS2) was positively associated with worse prognosis. Three novel ceRNAs (SNHG1-hsa-miR-21-5p-RALGPS2, SNHG1-hsa-miR-326-RALGPS2, and SNHG1-hsa-miR-377-3p-RALGPS2) might be potential biomarkers for the prognosis and treatment of LUAD.

Construction and analysis of the lncRNA-miRNA-mRNA network based on competitive endogenous RNA reveal functional lncRNAs in oral cancer

Background There is a growing body of evidence suggesting that long non-coding RNAs(lncRNAs) can function as a microRNA(miRNA) sponge in various diseases including oral cancer. However, we are still not very clear about the pathophysiological function of lncRNAs. Methods We constructed a lncRNA-miRNA-mRNA network in oral cancer based on the competitive endogenous RNA(ceRNA) theory with the human expression profiles GSE74530 from the Gene Expression Omnibus (GEO) database and used topological analysis to determine the hub lncRNAs in the regulatory ceRNA network. Then, function enrichment analysis was performed by R package Cluster Profiler. Results A total of 238 potential co-dysregulated competing triples were obtained in the lncRNA-assoicated ceRNA network of oral cancer, which consisted of 10 lncRNA nodes, 41 miRNA nodes, and 122 mRNA nodes. Additionally, we found three lncRNAs( HCP5 , AGAP11 , HCG22 ) exhibiting superior potential as diagnostic and prognostic markers of oral cancer. Conclusions Our findings will provide novel insights for understanding the ceRNA regulation in oral cancer and identify three novel lncRNAs as potential molecular biomarkers.

Transcriptomic Analysis Reveals the Molecular Adaptation of Three Major Secondary Metabolic Pathways to Multiple Macronutrient Starvation in Tea (Camellia sinensis)

Tea (Camellia sinensis (L.) O. Kuntze) is a widely consumed beverage. Lack of macronutrients is a major cause of tea yield and quality losses. Though the effects of macronutrient starvation on tea metabolism have been studied, little is known about their molecular mechanisms. Hence, we investigated changes in the gene expression of tea plants under nitrogen (N), phosphate (P), and potassium (K) deficient conditions by RNA-sequencing. A total of 9103 differentially expressed genes (DEG) were identified. Function enrichment analysis showed that many biological processes and pathways were common to N, P, and K starvation. In particular, cis-element analysis of promoter of genes uncovered that members of the WRKY, MYB, bHLH, NF-Y, NAC, Trihelix, and GATA families were more likely to regulate genes involved in catechins, l-theanine, and caffeine biosynthetic pathways. Our results provide a comprehensive insight into the mechanisms of responses to N, P, and K starvation, and a global basis for the improvement of tea quality and molecular breeding.

The complexity and robustness of gene network inside the story between miRNAs and splicing isoforms in sacred lotus

BACKGROUND. Gene expression is complex and regulated by multiple molecular mechanisms, such as miRNA-mediated gene inhibition and alternative-splicing of pre-mRNAs. However, coordination of interaction between miRNAs with different splicing isoforms, and the role of splicing isoform in response to different cellular environments are largely unexplored in plants. In this study, we analyzed the miRNA and mRNA transcriptome from lotus ( Nelumbo nucifera ), an economically important flowering plant. RESULTS. Through RNA-seq expression analyses among six lotus tissues, the negative regulatory roles of most miRNAs are reflected by their tissue-biased expression and the negative correlation with their targets in expression. Further, the central roles of miRNAs in the gene network was unveiled as there are more frequent interactions between miRNAs and hub isoforms than between miRNAs and non-hub isoforms. Surprisingly, for many genes, their corresponding isoforms were assigned to different co-expressed modules, and they exhibited more divergent mRNA structures including presence and absence of miRNA binding sites, suggesting functional divergence for many isoforms is escalated by both structural and expression divergence. The gene function enrichment analysis of miRNA targeted reveals that miRNAs are involved in regulation of lotus growth and development by regulating plant hormone-related pathway genes. CONCLUSION. Taken together, we carry out a comprehensive and deep analysis between miRNA and mRNA transcriptome to study coordination of interaction between miRNAs with different splicing isoforms. Our study on lotus highlights not only the complicate interactions between the miRNAs and transcript isoforms but also functional divergence of many transcript isoforms from the same locus in plant.