miRNA-target Regulatory Network Research Articles

Integrative analyses of ferroptosis and immune related biomarkers and the osteosarcoma associated mechanisms

Osteosarcoma (OS) is the most common primary malignant bone tumor with high metastatic potential and relapse risk. To study the regulatory mechanism of the OS microenvironment, a complex regulatory network involving the ferroptosis- and immune response-related genes remains to be established. In the present study, we determined the effect of a comprehensive evaluation system established on the basis of ferroptosis- and immune-related genes on the immune status, related biomarkers, prognosis, and the potential regulatory networks underlying OS based on the TARGET and Gene Expression Omnibus databases that contain information on OS patients by bioinformatics analyses. We first characterized individual ferroptosis scores and immune scores through gene set variation analysis (GSVA) against TARGET-OS datasets. We then identified differentially expressed genes by score groups. Weighted gene co-expression network analysis was performed to identify the most relevant ferroptosis-related and immune-related gene modules, which facilitated the identification of 327 ferroptosis gene and 306 immune gene candidates. A 4-gene (WAS, CORT, WNT16, and GLB1L2) signature was constructed and valuation using the least absolute shrinkage and selection operator-Cox regression models to effectively predict OS prognosis. The prediction efficiency was further validated by GSE39055. We stratified patients based on the prognostic scoring systems. Eight hub genes (namely CD3D, CD8A, CD3E, IL2, CD2, MYH6, MYH7, and MYL2) were identified, and TF–miRNA target regulatory networks were constructed. Furthermore, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, gene set enrichment analysis, and GSVA were used to determine the signature’s potential pathways and biological functions, which showed that the hub genes were enriched in ferroptosis-associated biological functions and immune-associated molecular mechanisms. Thereafter, we investigated the proportion and infiltration extent of 22 infiltrating immune cells by using CIBERSORT, which revealed significant subgroup differences in CD8 + T cells, M0 macrophages, and M2 macrophages. In conclusion, we determined a new ferroptosis-related and immune-related gene signature for predicting OS patients’ prognosis and further explored the ferroptosis and immunity interactions during OS development, which provides insights into the exploration of molecular mechanisms and targeted therapies in patients with OS.

Molecular profiles of predictive biomarkers for platinum-based chemotherapy in Non-Small Cell Lung Cancer (NSCLC)

BackgroundNon-small cell lung cancer (NSCLC) is the principal subtype of lung cancer. Among all therapeutic options, platinum-based chemotherapy agents, especially Cisplatin, are still commonly used treatment for NSCLC patients. However, developing chemoresistance in NSCLC cells often gives rise to chemotherapy failure. Therefore, more studies are required to shed light on gene interaction and cellular pathways involved in initiating and developing resistance to platinum-based chemotherapy in NSCLC. Hence, it is urgent to find the key genes, microRNA (miRNAs), and potential molecular mechanisms implicated in chemoresistance and present markers to predict response to platinum-based chemotherapy in NSCLC patients. MethodsThe microarray datasets GSE6410, GSE7035, GSE14814, GSE26704, GSE73302 were downloaded from the Gene Expression Omnibus (GEO) database and were analyzed using R software. Functional and pathway enrichment analyses were performed using the Enrich R site. Then, the protein-protein interaction (PPI) network and hub genes were obtained using the Cytoscape software. Further, the miRSystem database was performed to predict the miRNAs regulating the hub genes. Moreover, Cytoscape software and the CytoHubba plugin were used to construct the miRNA-target interaction network and hub modules. Finally, the Kaplan–Meier curve was used to demonstrate the survival curves and assess the association of the genes signature with clinical outcomes. ResultsA total of 142 differentially expressed genes (DEGs) were found. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses present the p53 signaling pathway as the most significant pathway.Besides, from the top ten terms obtained of Biological Process, Molecular Function, and Cellular Component, the first ones, including cholesterol biosynthetic process, the extrinsic component of external side of plasma membrane, cytokine activity, were selected respectively. Based on the PPI network, the ten nodes with the highest degree were screened as hub genes. In addition, from the miRNA–target regulatory network in Cytoscape, ten hub nodes were found. Ultimately, according to Kaplan–Meier curve, BTG2 and TP53I3 with p-value <0.05 were associated with a better prognosis. ConclusionsIn the present study, DEGs, candidate miRNAs, and underlying mechanisms involved in chemoresistance were identified to suggest potential biomarkers to provide new clues for the prediction of response to platinum-based chemotherapy.

Microarray Analysis of Small Extracellular Vesicle-Derived miRNAs Involved in Oxidative Stress of RPE Cells.

The aim of this study was to investigate the miRNA profiles of nanosized small extracellular vesicles (sEVs) from human retinal pigment epithelial (RPE) cells under oxidative damage. ARPE-19 cells were cultured with ox-LDL (100 mg/L) or serum-free medium for 48 hours, sEVs were then extracted, and miRNA sequencing was conducted to identify the differentially expressed genes (DEGs) between the 2 groups. RNA sequence results were validated using quantitative real-time PCR. The Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes pathway, and ingenuity pathway analyses (IPA) were performed for the DEGs. Results revealed that oxidative stress inhibited RPE cell viability and promoted sEV secretion. A total of 877 DEGs from sEVs were identified, of which 272 were downregulated and 605 were upregulated. In total, 66 enriched GO terms showed that the 3 most significant enrichment terms were cellular processes (biological processes), cell (cellular component), and catalytic activity (molecular function). IPA were used to explore DEGs associated with oxidation damage and further construct a miRNA-target regulatory network. This study identified several DEGs from oxidation-stimulated RPE cells, which may act as potential RNA targets for prognosis and diagnosis of RPE degeneration.

ASDmiR: A Stepwise Method to Uncover miRNA Regulation Related to Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a class of neurodevelopmental disorders characterized by genetic and environmental risk factors. The pathogenesis of ASD has a strong genetic basis, consisting of rare de novo or inherited variants among a variety of multiple molecules. Previous studies have shown that microRNAs (miRNAs) are involved in neurogenesis and brain development and are closely associated with the pathogenesis of ASD. However, the regulatory mechanisms of miRNAs in ASD are largely unclear. In this work, we present a stepwise method, ASDmiR, for the identification of underlying pathogenic genes, networks, and modules associated with ASD. First, we conduct a comparison study on 12 miRNA target prediction methods by using the matched miRNA, lncRNA, and mRNA expression data in ASD. In terms of the number of experimentally confirmed miRNA–target interactions predicted by each method, we choose the best method for identifying miRNA–target regulatory network. Based on the miRNA–target interaction network identified by the best method, we further infer miRNA–target regulatory bicliques or modules. In addition, by integrating high-confidence miRNA–target interactions and gene expression data, we identify three types of networks, including lncRNA–lncRNA, lncRNA–mRNA, and mRNA–mRNA related miRNA sponge interaction networks. To reveal the community of miRNA sponges, we further infer miRNA sponge modules from the identified miRNA sponge interaction network. Functional analysis results show that the identified hub genes, as well as miRNA-associated networks and modules, are closely linked with ASD. ASDmiR is freely available at https://github.com/chenchenxiong/ASDmiR.

Gene expression in rat placenta after exposure to di(2-ethylhexyl) phthalate.

The organic compound di(2-ethylhexyl) phthalate (DEHP) is widely used as a plasticizer in many products. Exposure to DEHP has been reported to lead to adverse pregnancy outcomes by suppressing placenta growth and development. The aim of this study was to determine the gene expression profiles of rat placenta exposed to (DEHP) and identify genes crucial for the DEHP response. Three groups of Wistar rats were administered an intragastric dose of 1,000 mg/kg DEHP, 500 mg/kg DEHP, or corn oil, RNA was isolated from placenta tissue, and hybridization was performed. Gene expression profiles were analyzed by identifying functional enrichment, differentially expressed genes (DEGs), protein-protein interaction (PPI) networks and modules, and transcription factor (TF)-miRNA-target regulatory networks. We obtained 2,032 DEGs, including cytochrome P450, family 2, subfamily R, polypeptide 1 (CYP2R1), sterol O-acyltransferase 2 (SOAT2), and 24-dehydrocholesterol reductase (DHCR24) from the steroid biosynthesis pathway and somatostatin receptor 4 (SSTR4) and somatostatin receptor 2 (SSTR2) in the neuroactive ligand-receptor interaction pathway. The PPI network included 476 nodes, 2,682 interaction pairs, and three sub-network modules. Moreover, eight miRNAs, three TFs, and 176 regulatory pairs were obtained from the TF-miRNA-target regulatory network. CYP2R1, SOAT2, DHCR24, SSTR4, and SSTR2 may affect DEHP influence on rat placenta development.

Hsa-miR-106b-5p participates in the development of chronic thromboembolic pulmonary hypertension via targeting matrix metalloproteinase 2.

BackgroundChronic thromboembolic pulmonary hypertension (CTEPH) is characterized by elevated pressure in pulmonary arteries. This study was performed to explore the critical miRNAs and genes affecting the pathogenesis of CTEPH.MethodsGSE56914 dataset (10 CTEPH whole blood samples and 10 control samples) was downloaded from the Gene Expression Omnibus database. Using limma package, the differentially expressed miRNAs (DE-miRNAs) were acquired. After miRNA-target pairs were obtained using miRWalk2.0 tool, a miRNA-target regulatory network was built by Cytoscape software. Using DAVID tool, significantly enriched pathways involving the target genes were identified. Moreover, the protein–protein interaction network and transcription factor-target regulatory network were built by the Cytoscape software. Additionally, quantitative real-time PCR (qRT-PCR) experiments and luciferase assay were conducted to validate miRNA/gene expression and miRNA–target regulatory relationship, respectively.ResultsThere were 25 DE-miRNAs (8 up-regulated and 17 down-regulated) between CTEPH and control groups. The target genes of has-let-7b-3p, has-miR-17-5p, has-miR-3202, has-miR-106b-5p, and has-miR-665 were enriched in multiple pathways such as “Insulin secretion”. qRT-PCR analysis confirmed upregulation of hsa-miR-3202, hsa-miR-665, and matrix metalloproteinase 2 (MMP2) as well as downregulation of hsa-let-7b-3p, hsa-miR-17-5p, and hsa-miR-106b-5p. Luciferase assay indicated that MMP2 was negatively mediated by hsa-miR-106b-5p.ConclusionsThese miRNAs and genes were associated with the pathogenesis of CTEPH. Besides, hsa-miR-106b-5p was involved in the development of CTEPH via targeting MMP2.

Identification of Molecular Signatures in Mild Intrinsic Atopic Dermatitis by Bioinformatics Analysis.

BackgroundAtopic dermatitis (AD) is recognized as a common inflammatory skin disease and frequently occurred in Asian and Black individuals.ObjectiveSince the limitation of dataset associated with human severe AD, this study aimed to screen potential novel biomarkers involved in mild AD.MethodsExpression profile data (GSE75890) were obtained from the database of Gene Expression Omnibus. Using limma package, the differentially expressed genes (DEGs) between samples from AD and healthy control were selected. Furthermore, function analysis was conducted. Meanwhile, the protein-protein interaction (PPI) network and transcription factor (TF)-miRNA-target regulatory network were constructed. And quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate the expressions patterns of key genes.ResultsIn total, 285 DEGs including 214 upregulated and 71 downregulated genes were identified between samples from two groups. The upregulated DEGs were mainly involved in nine pathways, such as hematopoietic cell lineage, pertussis, p53 signaling pathway, staphylococcus aureus infection, and cell cycle, while tight junction was the only pathway enriched by the downregulated DEGs. Cyclin B (CCNB)1, CCNB2, cyclin A (CCNA)2, C-X-C motif chemokine ligand (CXCL)10, and CXCL9 were key nodes in PPI network. The TF-miRNA-target gene regulatory network focused on miRNAs such as miR-106b, miR-106a, and miR-17, TFs such as nuclear factor kappa B subunit 1, RELA proto-oncogene, Sp1 transcription factor, and genes such as matrix metallopeptidase 9, peroxisome proliferator activated receptor gamma , and serpin family E member 1. Moreover, the upregulation of these genes, including CCNB1, CCNB2, CCNA2, CXCL10, and CXCL9 were confirmed by qRT-PCR.ConclusionCCNB1, CCNB2, CCNA2, and CXCL9 might be novel markers of mild AD. miR-106b and miR-17 may involve in regulation of immune response in AD patients.

Screening of Critical Genes Involved in Metastasis and Prognosis of High-Grade Serous Ovarian Cancer by Gene Expression Profile Data.

We aimed to identify critical genes for metastasis and prognosis of high-grade serous ovarian cancer (HGSOC). The mRNA data of GSE73064 including 15 HGSOC samples (5 primary tumor cells, 5 ascites tumor cells, and 5 metastasis tumor cells) were applied for the present analysis. The data were first preprocessed using robust multiarray average (RMA) method, and time-series gene expression analyses were performed using short time-series expression miner (version 1.3.11). Then, functional analysis for clustered genes was conducted, and protein-protein interaction (PPI) network was constructed. Subnetwork module was also analyzed. After that, we analyzed the miRNA regulatory network. Finally, survival analysis was performed. In this study, PPBP, ITGB2, and ITGAM were genes with higher degrees in the PPI network. miR-4469, miR-6734-5p, and miR-1304-5p were several of important miRNAs in the miRNA-target regulatory network. In addition, survival analysis showed that nine genes such as CLEC5A, FPR1, and CXCL12 might be important for HGSOC prognosis. PPBP, ITGB2, and ITGAM may be critical for HGSOC metastasis. CLEC5A, FPR1, and CXCL12 may be important for the prognosis of HGSOC. Furthermore, miR-4469, miR-6734-5p, and miR-1304-5p may be important miRNAs associated with HGSOC.

MIENTURNET: an interactive web tool for microRNA-target enrichment and network-based analysis

BackgroundmiRNAs regulate the expression of several genes with one miRNA able to target multiple genes and with one gene able to be simultaneously targeted by more than one miRNA. Therefore, it has become indispensable to shorten the long list of miRNA-target interactions to put in the spotlight in order to gain insight into understanding the regulatory mechanism orchestrated by miRNAs in various cellular processes. A reasonable solution is certainly to prioritize miRNA-target interactions to maximize the effectiveness of the downstream analysis.ResultsWe propose a new and easy-to-use web tool MIENTURNET (MicroRNA ENrichment TURned NETwork) that receives in input a list of miRNAs or mRNAs and tackles the problem of prioritizing miRNA-target interactions by performing a statistical analysis followed by a fully featured network-based visualization and analysis. The statistics is used to assess the significance of an over-representation of miRNA-target interactions and then MIENTURNET filters based on the statistical significance associated with each miRNA-target interaction. In addition, the holistic approach of the network theory is used to infer possible evidences of miRNA regulation by capturing emergent properties of the miRNA-target regulatory network that would be not evident through a pairwise analysis of the individual components.ConclusionMIENTURNET offers the possibility to consistently perform both statistical and network-based analyses by using only a single tool leading to a more effective prioritization of the miRNA-target interactions. This has the potential to avoid researchers without computational and informatics skills to navigate multiple websites and thus to independently investigate miRNA activity in every cellular process of interest in an easy and at the same time exhaustive way thanks to the intuitive web interface. The web application along with a well-documented and comprehensive user guide are freely available at http://userver.bio.uniroma1.it/apps/mienturnet/without any login requirement.

Downregulations of miR-449a and miR-145-5p Act as Prognostic Biomarkers for Endometrial Cancer.

This investigation aimed to explore the underlying prognosis-associated microRNA (miRNA) biomarkers in endometrial cancer. Homo sapiens miRNA data set GSE35794 and miRNA data in TGGA database were downloaded and applied to screen the differentially expressed miRNAs (DE-miRNAs) using unpaired t-test in limma package in R. Basing on Venn analysis, the overlapped DE-miRNAs were screened and their potential targets were predicted according to miRWalk followed by target functional enrichment analyses and protein-protein interaction network visualized using Cytoscape. Finally, according to the information provided by the The Cancer Genome Atlas (TCGA) database, correlations between miRNAs or targets and patient prognosis were analyzed by survival package in R. A total of 24 overlapped DE-miRNAs were identified between endometrioid endometrial cancer samples and normal samples. Then, the miRNA-target regulatory network was constructed, including 11 upregulated miRNAs (e.g., miR-200a, miR-200b, and miR-200c) and five downregulated miRNAs (e.g., miR-449a, miR-145-5p, and miR-145-3p). Lymphocyte enhancer factor-1 (LEF1) was predicted to be a target of miR-449a and SOX11 was a target of miR-145-5p. Functional enrichment analyses of these targets were significantly related to the biological process of "negative regulation of transcription from RNA polymerase II promoter" and "positive regulation of transcription from RNA polymerase II promoter" (e.g., NOTCH1, LEF1, and SOX11). In addition, survival analysis showed that miR-449a, miR-145-5p, and LEF1 were approximately correlated with the overall survival prognosis of endometrial cancer patients. Downregulations of miR-449a and miR-145-5p might be involved in the pathogenesis of endometrial cancer and could act as prognostic biomarkers for endometrial cancer patients.

Gene and microRNA Signatures Are Associated with the Development and Survival of Glioblastoma Patients.

This study was aimed to identify hub genes associated with the development of glioblastoma (GBM) by conducting a bioinformatic analysis. The raw gene expression data were downloaded from the Gene Expression Omnibus database and The Cancer Genome Atlas project. After the differentially expressed genes (DEGs) were identified, the functional enrichment analysis of DEGs was conducted. Subsequently, the protein-protein interaction (PPI) network, molecular complex detection clusters, and transcriptional factor (TF)-miRNA-target regulatory network were constructed, respectively. Furthermore, the survival analysis of prognostic outcomes and genes was analyzed. In addition, the expression of key genes was validated by quantitative real-time PCR (qRT-PCR) analysis. A total of 884 DEGs, including 418 upregulated and downregulated genes, were identified between GBM and normal samples. The PPI network comprised a set of 3418 pairs involving 751 nodes, and AKT1 and CDK2 were the critical genes in the network. A total of seven clusters were identified, the genes in which were intensively associated with cell cycle, cholinergic synapse, and extracellular matrix (ECM)-receptor interaction. qRT-PCR analysis indicated that AKT1 and CDK2 were significantly upregulated, and NRXN3 and NPTX2 were significantly downregulated in GBM samples. The TF-miRNA-target regulatory networks were built, in which CCNB1, RFC5, microRNA524, and microRNA34b were key regulators. There were 43 genes, including NPTX2 and NRXN3, significantly related to the prognostic outcomes of GBM patients. These crucial genes might be promising options for GBM treatment.

Integrated analysis of miRNA and mRNA expression profiles in 2-, 6-, and 12-month-old Small Tail Han Sheep ovaries reveals that oar-miR-432 downregulates RPS6KA1 expression

Small Tail Han Sheep are an excellent local sheep breed in China, and their outstanding reproductive performance is one of their very important biological characteristics. Clarifying the ovary development process of these ewes should provide a theoretical basis for improving their reproductive efficiency. In this study, we identified the differentially expressed (DE) microRNAs (miRNAs) in 2-, 6-, and 12-month-old small-tail Han sheep ovaries by constructing and analyzing the miRNA expression profiles. These findings clarify the molecular mechanisms regulating the excellent reproductive performance of small-tail Han ewes. We used RNA-Seq technology and bioinformatic to analyze these profiles. Eleven, 13, and 19 DE miRNAs were identified in the 2- vs 6-, 6- vs 12-, and 2- vs 12-month-old ovaries, respectively. In total, 54, 37, and 198 predicted target genes of these DE miRNAs were identified in these three groups, respectively. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses showed that in the 2- vs 6-month-old ovaries, the target genes of DE known sheep miRNAs were involved in 102 GO terms and seven signaling pathways; in the 6- vs 12-month-old ovaries, the target genes of DE known sheep miRNAs were involved in 52 GO terms and three signaling pathways; and in the 2- vs 12-month-old ovaries, the target genes of DE known sheep miRNAs were involved in 88 GO terms and six signaling pathways. Three miRNA–target regulatory networks were constructed based on these DE miRNA–target interactions. Nine miRNAs were selected to confirm to the accuracy of the miRNA sequencing data with qRT-PCR. The site at which oar-miR-432 binds RPS6KA1 was determined with a dual-luciferase system. This is the first integrated analysis the expression profiles of miRNAs and their targets during ovarian development in small-tail Han sheep. These data clarify the molecular regulatory mechanisms underlying sheep ovarian development and identify biomarkers that influence the reproductive performance of small-tail Han ewes.

Identification of dysregulated microRNAs in canine malignant melanoma.

Inhibiting aberrantly upregulated microRNAs (miR/miRNAs) has emerged as a novel focus for therapeutic intervention in human melanoma. Thus, identifying upregulated miRNAs is essential for identifying additional melanoma-associated therapeutic targets. In the present study, microarray-based miRNA profiling of canine malignant melanoma (CMM) tissue obtained from the oral cavity was performed and differential expression was confirmed by a reverse transcription-quantitative polymerase chain reaction (RT-qPCR). An analysis of the microarray data revealed 17 dysregulated miRNAs; 5 were upregulated and 12 were downregulated. RT-qPCR analysis was performed for 2 upregulated (miR-204 and miR-383), 3 downregulated (miR-122, miR-143 and miR-205) and 6 additional oncogenic miRNAs (oncomiRs; miR-16, miR-21, miR-29b, miR-92a, miR-125b and miR-222). The expression levels of seven of the miRNAs, miR-16, miR-21, miR-29b, miR-122, miR-125b, miR-204 and miR-383 were significantly upregulated; however, the expression of miR-205 was downregulated in CMM tissues compared with normal oral tissues. The microarray and RT-qPCR analyses validated the upregulation of two potential oncomiRs miR-204 and miR-383. The present study additionally constructed a protein interaction network and a miRNA-target regulatory interaction network using STRING and Cytoscape. In the proposed network, cyclin dependent kinase 2 was a target for miR-383, sirtuin 1 and tumor protein p53 were targets for miR-204 and ATR serine/threonine kinase was a target for both. It was concluded that miR-383 and miR-204 were potential oncomiRs that may be involved in regulating melanoma development by evading DNA repair and apoptosis.

Potentially critical roles of TNPO1, RAP1B, ZDHHC17, and PPM1B in the progression of coronary atherosclerosis through microarray data analysis.

This study aimed to identify more potentially critical genes associated with atherosclerotic coronary artery disease (CAD). Gene expression profile of GSE12288 was downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened in atherosclerotic CAD samples compared with controls, followed by weighed gene coexpression network analysis (WGCNA) by which the most significant module was identified. Gene coexpression network was constructed based on genes in the most significant module, and functional annotation was also performed. In addition, microRNAs (miRNAs) that were directly associated with CAD were screened from the literature, and the miRNA-target regulatory network was constructed based on genes in the most significant module, followed by Gene Ontology (GO) and pathway enrichment analysis. Furthermore, we used another data set of GSE42148 from the GEO database to perform data validation. WGCNA analysis showed that the turquoise module may have the most important role in atherosclerotic CAD. Genes in this module were involved in translational elongation and intracellular signal transduction. Besides, we identified five confirmed CAD-related miRNAs. TNPO1, RAP1B, and ZDHHC17 could be targeted by four of these miRNAs. Genes such as PPM1B could be regulated by three miRNAs. Moreover, TNPO1 and ZDHHC17 were involved in the GO terms associated with protein localization and transport and the immune system; RAP1B and PPM1B were linked with intracellular signal transduction-related pathways. In addition, PPM1B and ZDHHC17 had accordantly significant expression changes in another data set GSE42148. TNPO1, RAP1B, ZDHHC17, and PPM1B may play essential roles in the progression of coronary atherosclerosis.

Asthma MicroRNA Regulome Development Using Validated miRNA-Target Interaction Visualization.

Asthma is a common multifactorial complex disease caused by an interaction of genetic and environmental factors. There are no robust biomarkers or molecular diagnostics for asthma or its detailed phenotypic stratification in the clinic. Regulatory and epigenomic factors are priority candidates for asthma biomarker discovery and translational research because this common disease emerges in association with host/environment interactions. In this context, epigenomic molecular events such as microRNA (miRNA) silencing affect asthma susceptibility and severity. We report here an analysis of the miRNAs in the literature, their targets associated with asthma, and present the findings organized as an miRNA-target network, an miRNA regulome of asthma. The miRNA-target interactions in asthma were extracted from the PubMed and the Web of Science databases, while the miRNA-target network was visualized with the Cytoscape tool. Genomic locations of miRNA and target genes were displayed using the Ensembl Whole Genome tool. We cataloged miRNAs associated with asthma and their experimentally validated targets, retrieving 48 miRNAs associated with asthma, and 54 experimentally validated miRNA targets. Four central molecules involved in 34.5% of all interactions were identified in the network. The miRNA-target pairs were constructed as an asthma-associated miRNA-target regulatory network. The network revealed subnetworks pointing toward potential asthma biomarker candidates. The asthma miRNA regulome reported here offers a strong foundation for future translational research and systems medicine applications for asthma diagnostic and therapeutic innovation. Developed protocol for constructing miRNA regulome could now be used for biomarker development in multifactorial diseases.

Analysis of NFKB2‑mediated regulation of mechanisms underlying the development of Hodgkin's lymphoma.

Nuclear factor-κB (NF-κB) is widely involved in various lymphoid malignancies. However, its exact functional role and potential regulatory mechanisms in Hodgkin's lymphoma (HL) remains unclear. The present study aimed to investigate the regulatory mechanism of NF-κB in HL by analysis of a gene expression profile that was obtained from HL cells with or without NF-κB subunit 2 (NFKB2) knockdown. The GSE64234 dataset containing 6 HL cell line specimens transfected with small interfering (si)RNA against NFKB2 and 6 control specimens transfected with non-targeting siRNA sequences was downloaded from the Gene Expression Omnibus database. Based on these data, differentially expressed genes (DEGs) were screened for following data preprocessing. Functional enrichment analysis was subsequently conducted among the identified upregulated and downregulated DEGs. Additionally, a protein-protein interaction (PPI) network was constructed and module analyses were performed. Finally, microRNAs (miRNAs/miRs) targeting the identified DEGs were predicted for the construction of a miRNA-target regulatory network. A total of 253 DEGs were identified, consisting of 109 upregulated and 144 downregulated DEGs. Pathway enrichment analysis revealed that B-cell lymphoma 2-like 1 (BCL2L1) was significantly enriched in the NF-κB signaling pathway, and colony-stimulating factor 2 (CSF2) and BCL2L1 were enriched in the Jak-signal transducer and activator of transcription (STAT) signaling pathway. BCL2L1 and CSF2 were determined to be hub genes in the PPI network. A total of 6 miRNAs, including let-7a-5p, miR-9-5p, miR-155-5p, miR-135a-5p, miR-17-5p and miR-375, were identified in the miRNA-target regulatory network. The results of the present study indicated that NFKB2 may be involved in HL development through regulation of BCL2L1, CSF2, miR-135a-5p, miR-155-5p and miR-9-5p expression, as well as the modulation of Jak-STAT and NF-κB signaling pathways.

Integrated analysis of gene expression signatures associated with colon cancer from three datasets

PurposeThe present study aimed to elucidate the pathogenesis of colon cancer and identify genes associated with tumor development. MethodsThree datasets, two (GSE74602 and GSE44861) from the Gene Expression Omnibus database and RNA-Seq colon cancer data from The Cancer Genome Atlas data portal, were downloaded. These three datasets were grouped using a meta-analysis approach, and differentially expressed genes (DEGs) were identified between colon tumor samples and adjacent normal samples. Functional enrichment analysis and regulatory factor predication were performed for significant genes. Additionally, small-molecule drugs associated with colon cancer were predicted, and a prognostic risk model was constructed. ResultsThere were 251 overlapping DEGs (135 up- and 116 downregulated) between cancer samples and control samples in the three datasets. The DEGs were mainly involved in protein transport and apoptotic and neurotrophin signaling pathways. A total of 70 small-molecule drugs were predicated to be associated with colon cancer. Additionally, in the miRNA–target regulatory network, we found that SLC44A1 can be targeted by hsa-miR-183, hsa-miR-206, and hsa-miR-147, while KLF13 can be regulated by hsa-miR-182, hsa-miR-206, and hsa-miR-153. Moreover, the results of the prognostic risk model showed that four genes (VAMP1, P2RX5, CACNB1, and CRY2) could divide the samples into high and low risk groups. ConclusionSLC44A1 and KLF13 may be involved in tumorigenesis and the metastasis of colon cancer by miRNA regulation. In addition, a four-gene (VAMP1, P2RX5, CACNB1, and CRY2) expression signature may have prognostic and predictive value in colon cancer.

Up-regulation of YPEL1 and YPEL5 and down-regulation of ITGA2 in erlotinib-treated EGFR-mutant non-small cell lung cancer: A bioinformatic analysis

PurposeThis study aimed to identify genes with significant alteration following treatment of epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC) with tyrosine kinase inhibitors (TKIs). MethodsWe downloaded microarray data of GSE67051 from the Gene Expression Omnibus (GEO) database. Genes with differential expression were identified in two groups: erlotinib-treated versus DMSO-treated PC9 cells and erlotinib-treated versus DMSO-treated HCC827 cells. Functional enrichment analysis and protein-protein interaction (PPI) network were performed on the overlapping differentially expressed genes (DEGs). Additionally, miRNAs that can regulate the DEGs were predicted. Small-molecule drugs, with possible synergistic or antagonistic actions with respect to erlotinib, were screened; data validation using another dataset was conducted. ResultsIn total, 1466 and 839 DEGs were identified in the aforementioned comparison groups, respectively, among which 267 overlapping up-regulated and 73 down-regulated were observed. The overlapping up- and down-regulated genes were significantly associated with different functions and pathways. ITGA2 had higher centrality scores in the PPI network. Seventy small-molecule drugs, with either possible synergistic or antagonistic roles with erlotinib, were identified. Moreover, up-regulated YPEL1, YPEL2, and YPEL5 were enriched in the miRNA-target regulatory network. Implementing data validation, we found YPEL1, YPEL5, and ITGA2 displayed similar expression profiles in the two datasets. ConclusionYPEL1 and YPEL5 may be related to the action of erlotinib, and down-regulation of ITGA2 may be associated with the development of acquired resistance to erlotinib in EGFR-mutant NSCLCs. Furthermore, several small-molecule drugs that may have synergistic and antagonistic roles with erlotinib were identified.

Bioinformatic analysis of gene expression profiles of pituitary gonadotroph adenomas.

The aim of the present study was to identify genes, microRNAs (miRNAs/miRs) or pathways associated with the development of pituitary gonadotroph adenomas. The array data of GSE23207, which included 16 samples of multiple endocrine neoplasia-associated rat pituitary homozygous mutations and 5 pituitary tissue samples from healthy rats, were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were analyzed prior to functional enrichment analysis and protein-protein interaction (PPI) network construction. miRNAs associated with DEGs were predicted, and an miRNA-target regulatory network was constructed. A total of 187 upregulated and 370 downregulated DEGs were identified in the pituitary gonadotroph adenoma group compared with the healthy (control) group. Cyclin-dependent kinase (Cdk) 1 exhibited the highest degree in the PPI network. The upregulated DEGs were predominately enriched in ‘neuroactive ligand-receptor interaction’ pathway, and downregulated DEGs were mainly enriched in ‘cell cycle’. The DEGs in module were predominately enriched in the ‘cell cycle’, whereas DEGs in module b and c were enriched in ‘neuroactive ligand-receptor interaction’. miR-374, −153, −145 and −33 were identified as important miRNAs in the regulation of the DEGs. Cdk1, cyclin (Ccn) A2, Ccnb1, ‘cell cycle’ and ‘neuroactive ligand-receptor interaction’ pathways may serve important roles in the development of pituitary gonadotroph adenomas; Ccna2 and Ccnb1 may contribute to this development via an effect on the ‘cell cycle’ pathway. Furthermore, miR-374 and −145 may contribute to the development of pituitary gonadotroph adenomas via regulation of the expression of target genes.

Abiotic Stress Responsive miRNA-Target Network and Related Markers (SNP, SSR) in Brassica juncea.

Abiotic stress is one of the major factors responsible for huge yield loss in crop plants. MicroRNAs play a key role in adaptive responses of plants under abiotic stress conditions through post-transcriptional gene regulations. In present study, 95 potential miRNAs were predicted in Brassica juncea using comparative genomics approach. It was noted that these miRNAs, target several transcription factors (TFs), transporter family proteins, signaling related genes, and protease encoding genes. Nineteen distinct miRNA-target regulatory networks were observed with significant involvement in regulation of transcription, response to stimulus, hormone and auxin mediated signaling pathway related gene ontology (GO) term. The sucrose-starch metabolism and pentose-gluconate interconversion pathways were found significantly enriched for these target genes. Molecular markers such as Simple Sequence Repeats (SSR) and Single Nucleotide Polymorphism (SNPs) were identified on miRNAs (miR-SSRs and miR-SNPs) and their target genes in B. juncea. Notably, one of the miR-SNP (C/T) was found at the 5th position on mature region of miR2926. This C/T transition led to the distorted and unstable hairpin structure of miR2926, consequently complete loss of target function. Hence, findings from this study will lay a foundation for marker assisted breeding for abiotic stress tolerant varieties of B. juncea.