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Background Nonalcoholic fatty liver disease and its advanced stage, nonalcoholic steatohepatitis (NASH), are the major cause of hepatocellular carcinoma (HCC) and other end-stage liver disease. However, the potential mechanism and therapeutic strategies have not been clarified. This study aimed to identify potential roles of miRNA/mRNA axis in the pathogenesis and drug combinations in the treatment of NASH. Methods Microarray GSE59045 and GSE48452 were downloaded from the Gene Expression Omnibus and analyzed using R. Then we obtained differentially expressed genes (DE-genes). DAVID database was used for Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analysis. Protein-protein interaction (PPI) networks were used for the identification of hub genes. We found upstream regulators of hub genes using miRTarBase. The expression and correlation of key miRNA and its targets were detected by qPCR. Drug Pair Seeker was employed to predict drug combinations against NASH. The expression of miRNA and hub genes in HCC was identified in the Cancer Genome Atlas database and Human Protein Atlas database. Results Ninety-four DE-genes were accessed. GO and KEGG analysis showed that these predicted genes were linked to lipid metabolism. Eleven genes were identified as hub genes in PPI networks, and they were highly expressed in cells with vigorous lipid metabolism. hsa-miR-335-5p was the upstream regulator of 9 genes in the 11 hub genes, and it was identified as a key miRNA. The hub genes were highly expressed in NASH models, while hsa-miR-335-5p was lowly expressed. The correlation of miRNA-mRNA was established by qPCR. Functional verification indicated that hsa-miR-335-5p had inhibitory effect on the development of NASH. Finally, drug combinations were predicted and the expression of miRNA and hub genes in HCC was identified. Conclusions In the study, potential miRNA-mRNA pathways related to NASH were identified. Targeting these pathways may be novel strategies against NASH.

Purpose This study aims to identify differentially expressed genes (DEGs) in macrophages exposed to ultra-high-molecular-weight polyethylene (UHMWPE) or vitamin E-blended UHMWPE (VE-UHMWPE) particles, thereby providing potential targets for the treatment of inflammatory osteolysis. Methods The GSE104589 dataset of genome expression in macrophages exposed to UHMWPE and VE-UHMWPE was downloaded from the Gene Expression Omnibus database to identify DEGs. Functional enrichment analysis was performed using DAVID, and the corresponding protein–protein interaction (PPI) network was constructed from the STRING database. Important modules were selected using the molecular complex detection algorithm, and hub genes were identified in cytoHubba. MicroRNAs targeting these DEGs were obtained from the TarBase, miRTarBase, and miRecords databases, while transcription factors (TFs) targeting DEGs were predicted from the ENCODE database. Finally, the top five DEGs were validated by quantitative real‐time polymerase chain reaction (qRT-PCR). Results A total of 112 DEGs (44 upregulated and 68 downregulated DEGs) were screened. Immune and inflammatory responses were significantly related in gene ontology analysis, and 18 signaling pathways were enriched according to Kyoto Encyclopedia of Genes and Genomes pathway analysis. The PPI network involving 85 nodes and 266 protein pairs indicated that IL1β, CXCL1, ICAM1, CCL5 and CCL4 showed higher degrees. qRT-PCR analysis of the top five DEGs revealed a decreasing trend in the VE-UHMWPE group compared with the UHMWPE group. Key microRNAs (hsa-miR-144, hsa-miR-21, and hsa-miR-221) and TFs (RELA and NFKB1) were predicted to be correlated with the pathogenesis of inflammatory osteolysis through microRNA-TF regulatory network analysis. Conclusion The present study helps shed light on the molecular mechanisms underlying the changes in the wear-induced inflammatory process after blending vitamin E with UHMWPE. Hub genes including IL1β, CXCL1, ICAM1, CCL5, and CCL4, key microRNAs (hsa-miR-144, hsa-miR-21, and hsa-miR-221) and TFs (RELA and NFKB1) may serve as prognostic and therapeutic targets of inflammatory osteolysis., Video abstract Point your SmartPhone at the code above. If you have a QR code reader the video abstract will appear. Or use: https://youtu.be/IkgdRqf1aSU

Background Clear‐cell renal cell carcinoma (ccRCC) is stubborn to traditional chemotherapy and radiation treatment, which makes its clinical management a major challenge. Recently, we have made efforts in understanding the etiology of ccRCC. Increasing evidence revealed that the competing endogenous RNA (ceRNA) was involved in the development of varied tumors. However, a comprehensive analysis of the prognostic model based on lncRNA‐miRNA‐mRNA ceRNA regulatory network of ccRCC with large‐scale sample size and RNA‐sequencing expression data is still limited. Methods RNA‐sequencing expression data were taken out from GTEx database and TCGA database, a total of 354 samples with ccRCC and 157 normal controlled samples were included in our study. The ccRCC‐specific genes were obtained by WGCNA and differential expression analysis. Following, the communication of mRNAs and lncRNAs with targeted miRNAs were predicted by MiRcode, starBase, miRTarBase, and TargetScan. A gene signature of eight genes was further constructed by univariate Cox regression, Lasso methods, and multivariate Cox regression analysis. Results A total of 2191 mRNAs and 1377 lncRNAs was identified, and a dysregulated ceRNA network for ccRCC was established using 7 mRNAs, 363 lncRNAs, and 3 miRNAs. Further, a gene signature including eight genes based on this ceRNA was determined followed by the development of a nomogram predicting 1‐, 3‐, and 5‐year survival probability for ccRCC. Conclusion It could contribute to a better understanding of ccRCC tumorigenesis mechanism and guide clinicians to make a more accurate treatment decision., We constructed a nomogram predicting 1‐, 3‐, and 5‐OS of ccRCC patients with a gene signature based on the ccRCC‐specific dysregulated ceRNA network and some other clinical factors. It could contribute to a better understanding of ccRCC tumorigenesis mechanism and guide clinicians to make a more accurate treatment decision.

Aim. This study is aimed at constructing the competing endogenous RNA (ceRNA) network in chromophobe renal cell carcinoma (ChRCC). Methods. Clinical and RNA sequence profiles of patients with ChRCC, including messenger RNAs (mRNAs), microRNAs (miRNAs), and long noncoding RNAs (lncRNAs), were obtained from The Cancer Genome Atlas (TCGA) database. “edgeR” and “clusterProfiler” packages were utilized to obtain the expression matrices of differential RNAs (DERNAs) and to conduct gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Weighted gene coexpression network analysis (WGCNA) was performed to screen the highly related RNAs, and miRcode, StarBase, miRTarBase, miRDB, and TargetScan datasets were used to predict the connections between them. Univariate and multivariate Cox proportional hazards regressions were performed in turn to elucidate prognosis-related mRNAs in order to construct the ceRNA regulatory network. Results. A total of 1628 DElncRNAs, 104 DEmiRNAs, and 2619 DEmRNAs were identified. WGCNA showed significant correlation in 1534 DElncRNAs, 98 DEmiRNAs, and 2543 DEmRNAs, which were related to ChRCC. Fourteen DEmiRNAs, 113 DElncRNAs, and 43 DEmRNAs were screened. Nine mRNAs (ALPL, ARHGAP29, CADM2, KIT, KLRD1, MYBL1, PSD3, SFRP1, and SLC7A11) significantly contributed to the overall survival (OS) of patients with ChRCC ( P < 0.05 ). Furthermore, two mRNAs (CADM2 and SFRP1) appeared to be independent risk factors for ChRCC. Conclusion. The findings revealed the molecular mechanism of ChRCC and potential therapeutic targets for the disease.

The aim of this study was to establish a novel competing endogenous RNA (ceRNA) network able to predict prognosis in patients with triple-negative breast cancer (TNBC). Differential gene expression analysis was performed using the GEO2R tool. Enrichr and STRING were used to conduct protein-protein interaction and pathway enrichment analyses, respectively. Upstream lncRNAs and miRNAs were identified using miRNet and mirTarBase, respectively. Prognostic values, expression, and correlational relationships of mRNAs, lncRNAs, and miRNAs were examined using GEPIA, starBase, and Kaplan-Meier plotter. It total, 860 upregulated and 622 downregulated differentially expressed mRNAs were identified in TNBC. Ten overexpressed and two underexpressed hub genes were screened. Next, 10 key miRNAs upstream of these key hub genes were predicted, of which six upregulated miRNAs were significantly associated with poor prognosis and four downregulated miRNAs were associated with good prognosis in TNBC. NEAT1 and MAL2 were selected as key lncRNAs. An mRNA-miRNA-lncRNA network in TNBC was constructed. Thus, we successfully established a novel mRNA-miRNA-lncRNA regulatory network, each component of which is prognostic for TNBC.

Background: Sepsis is a life-threatening disease caused by the dysregulated host response to the infection and the major cause of death of patients in the intensive care unit (ICU). Objective: Early diagnosis of sepsis could significantly reduce in-hospital mortality. Though generated from infection, the development of sepsis follows its own psychological process and disciplines, alters with gender, health status and other factors. Hence, the analysis of mass data by bioinformatics tools and machine learning is a promising method for exploring early diagnosis. Methods: We collected miRNA and mRNA expression data of sepsis blood samples from Gene Expression Omnibus (GEO) and ArrayExpress databases, screened out differentially expressed genes (DEGs) by R software, predicted miRNA targets on TargetScanHuman and miRTarBase websites, conducted Gene Ontology (GO) term and KEGG pathway enrichment analysis based on overlapping DEGs. The STRING database and Cytoscape were used to build protein-protein interaction (PPI) network and predict hub genes. Then we constructed a Random Forest model by using the hub genes to assess sample type. Results: Bioinformatic analysis of GEO dataset revealed 46 overlapping DEGs in sepsis. The PPI network analysis identified five hub genes, SOCS3, KBTBD6, FBXL5, FEM1C and WSB1. Random Forest model based on these five hub genes was used to assess GSE95233 and GSE95233 datasets, and the area under the curve (AUC) of ROC was 0.900 and 0.7988, respectively, which confirmed the efficacy of this model. Conclusion: The integrated analysis of gene expression in sepsis and the effective Random Forest model built in this study may provide promising diagnostic methods for sepsis.

Purpose Progestin resistance is a critical obstacle for endometrial conservative therapy. Therefore, studies to acquire a more comprehensive understanding of the mechanisms are urgent. However, the pivotal molecules are still unexplored. Materials and methods We downloaded GSE121367 from the GEO database. The "limma" R language package was applied to identify differentially expressed genes (DEGs). We conducted Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA). Protein-protein interaction was constructed by STRING and visualized in Cytoscape. The tumor immune microenvironment was explored by the TISIDB database. Methylation validation and overall survival analysis were conducted by the TCGA database. In addition, the upstream modulators of hub genes were predicted by miRTarBase and Network Analyst databases. The expression levels of candidate genes were validated by quantitative real-time PCR (qRT-PCR), Western blot, and immunohistochemical assay (IHC). Cell growth, clone formation, migration, invasion, and wound healing assays were studied to explore the role of MSX1 in progestin resistance in vitro. Results A total of 3,282 DEGs were identified and they were mostly enriched in the cell adhesion pathway. We screened out ten hub genes whose genomic alteration rates were low based on the current endometrial carcinoma sample sets. Has-miR-335-5p, has-miR-124-3p, MAZ, and TFDP1 were the most prominent upstream regulators. The methylation status of CDH1, JAG1, EPCAM, and MSX1 was decreased, corresponding to their high protein expression, which also predicted better overall survival. The homeobox protein of MSX1 showed significant tissue specificity and better prognostic value and its knockdown inhibited epithelial-mesenchymal transitions (EMT) and enhanced progesterone efficacy. Conclusion Our study identified that the gene of MSX1 promised to be the specific indicator and therapeutic target for progestin resistance. This would shed new light on the underlying biological mechanism to overcome progestin resistance of endometrial cancer.

This study aims to explore the molecular mechanism by which HAS2-AS1 acts as a ceRNA to promote the invasion and migration of glioma cells, which will provide a novel potential target for the targeted therapy of glioma. Gene expression profiles and corresponding clinical data were accessed from the TCGA_LGG and TCGA_GBM databases and then differential analysis was conducted using the "edgeR" package. miRDB, miRTarBase and TargetScan databases were employed to predict target genes and sequentially a ceRNA network was constructed. Quantitative real-time PCR was performed to detect gene expression in glioma cells. Transwell assay was operated to assess cell migratory and invasive abilities. Western blot was conducted to evaluate the protein expression. Dual-luciferase reporter assay and RNA immunoprecipitation experiment were performed to validate the targeting relationship between genes. HAS2-AS1 was markedly upregulated in glioma, and the overall survival time of patients with high HAS2-AS1 expression was significantly shorter than that of patients with low one. Silencing HAS2-AS1 inhibited the migration and invasion of glioma cells, while overexpressing HAS2-AS1 produced opposite results. miR-137 was validated as a direct target of and negatively regulated by HAS2-AS1. Further exploration of the downstream target gene indicated that EZH2 competed with HAS2-AS1 to interact with miR-137. Suppressing miR-137 or up-regulating EZH2 reversed the impact of HAS2-AS1 knockdown on glioma cell invasion and migration. HAS2-AS1 regulates EZH2 by sponging miR-137 for the migratory and invasive abilities of glioma cells, which provides a new idea for exploring metastasis mechanism of glioma.

Hepatoblastoma (HB) is one of the most common liver malignancies in children, while the molecular basis of the disease is largely unknown. Therefore, this study aims to explore the key genes and molecular mechanisms of the pathogenesis of HB using a bioinformatics approach. The gene expression dataset GSE131329 was used to find differentially expressed genes (DEGs). Functional and enrichment analyses of the DEGs were performed by the EnrichR. Then, the protein-protein interaction (PPI) network of the up-regulated genes was constructed and visualized using STRING database and Cytoscape software, respectively. MCODE was used to detect the significant modules of the PPI network, and cytoHubba was utilized to rank the important nodes (genes) of the PPI modules. Overall, six ranking methods were employed and the results were validated by the Oncopression database. Moreover, the upstream regulatory network and the miRNA-target interactions of the up-regulated DEGs were analyzed by the X2K web and the miRTarBase respectively. A total of 594 DEGs, including 221 up- and 373 down-regulated genes, were obtained, which were enriched in different cellular and metabolic processes, human diseases, and cancer. Furthermore, 15 hub genes were screened, out of which, 11 were validated. Top 10 transcription factors, kinases, and miRNAs were also determined. To the best of our knowledge, the association of RACGAP1, MKI67, FOXM1, SIN3A, miR-193b, and miR-760 with HB was reported for the first time. Our findings may be used to shed light on the underlying mechanisms of HB and provide new insights for better prognosis and therapeutic strategies.

Background Pancreatic carcinoma is one of the most malignant cancers globally. However, a systematic mRNA-miRNA-lncRNA/pseudogene network associated with the molecular mechanism of pancreatic cancer progression has not been described. Results The significant DEGs identified comprised 159 up-regulated and 92 down-regulated genes. According to the expression and survival analysis, three genes (COL12A1, APOL1, and MMP14) were significantly higher in tumor samples when compared with normal controls and their upregulation indicated a poor prognosis. Subsequently, 28, 17, and 11 miRNAs were predicted to target COL12A1, APOL1, and MMP14, respectively. The hsa-miR-26b-5p-COL12A1 axis showed a potential in suppressing the progression of pancreatic cancer. Moreover, 12 lncRNAs and 92 pseudogenes were predicted to potentially bind to the hsa-miR-26b-5p. Based on the results from expression and correlation analysis, NAMPTP1/HCG11-hsa-miR-26b-5p-COL12A1 competing endogenous RNA (ceRNA) sub-network was associated with the prognosis of pancreatic cancer. Conclusions In a word, we elucidate a new NAMPTP1/ HCG11-hsa-miR-26b-5p-COL12A sub-network in the progression of pancreatic cancer, which may serve as a promising diagnostic biomarker or effective therapeutic target for pancreatic cancer. Materials and methods Differentially expressed genes (DEGs) were first identified by mining GSE28735, GSE62452 and GSE41368 datasets. Functional enrichment analysis was conducted using the DAVID database. Protein-protein interaction (PPI) network was performed using the STRING database, and hub genes were identified by Cytoscape. Upstream miRNAs and pseudogenes /lncRNAs of mRNAs were forecast using miRTarBase, miRNet, and starBase. Expression, survival, and correlation analysis of genes, miRNAs, and pseudogenes /lncRNAs were validated using GEPIA, Kaplan-Meier, and starBase.

Lots of studies indicated that many microRNAs (miRNAs) are associated with the prognosis of patients with laryngeal cancer (LC). The objective of our study is to identify potential core miRNAs associated with the pathogenesis and prognosis of LC. Using the Cancer Genome Atlast database, we identified 70 differentially expressed miRNAs between LC tumor specimens and non-tumor specimens. Then Cox regression analyses and the least absolute shrinkage and selection operator regression signature were performed to detect miRNA prognostic markers. A nomogram integrating miRNA prognostic markers was constructed to predict overall survival (OS) for LC patients. The potential target genes of the key miRNA were predicted by miRTarBase and miRDB databases. Subsequently, their potential functions were revealed by gene ontology annotation and kyoto encyclopedia of genes and genomes pathway enrichment analysis. Related biological pathways of the key target gene involved in LC were detected through gene set enrichment analysis (GSEA). A prognostic miRNA signature was constructed. The up-regulated miR‐105–1 was related to a worse OS (p = 0.043), which suggested that miR‐105–1 may likely be the key miRNA prognostic marker. Survival analyses and paired expression analyses of target genes indicated that ENDOU may be the key target gene. Finally, we conducted GSEA to elucidate the pathways enriched between low- and high-ENDOU expression datasets. Our findings might bring some new light on the pathogenesis of LC. Then, it might facilitate doctors to predict the prognosis and improve treatment outcomes for LC patients. However, the behaviors of LC are relatively heterogeneous, and the TCGA database cannot provide detailed information about the subsites and treatment modalities of LC. Further molecular biological experiments and clinical investigations would be required to confirm this conclusion.

Objective. MicroRNAs play vital roles in the development of endometriosis. It is reported that miR-200b-3p is downregulated in endometriosis, although its mechanisms in this disease remain still unclear. Therefore, the purpose of this study was to explore the function and potential regulatory network of miR-200b-3p in endometriosis through database analysis.Methods. The endometriosis gene expression profiles were downloaded from the GEO database to screen differentially expressed genes (DEGs). The predicted and validated target genes of miR-200b-3p were obtained from miRWalk and miRTarBase database. Then, a comparison was performed between miR-200b-3p target genes and DEGs. GO enrichment and KEGG pathway analysis of the target genes was performed using clusterProfiler package. STRING was used to predict the protein-protein interaction among the proteins encoded by the target genes. Then, TransmiR, LncBase, StarBase, PROMO, and AnimalTFDB were employed to identify interactive transcription factors and lncRNAs of miR-200b-3p.Results. miR-200b-3p was associated with the transcription factors DNMT1, EZH2, HNF1B, JUN, MYB, ZEB1, and ZEB2 during the pathogenesis of endometriosis. The downstream 110 target genes were involved in the biological processes of positive regulation of MAPK cascade, muscle cell proliferation, organ growth, vasculogenesis, and axon development. KEGG analysis revealed that the main pathways related to miR-200b-3p were microRNAs in cancer, PI3K-Akt signaling pathway, colorectal cancer, and tight junction. In addition, four lncRNAs such as MALAT1, NEAT1, SNHG22, and XIST interacted with miR-200b-3p and were associated with transcription factors FOXP3 and YY1.Conclusion. The predicted target genes and molecular regulatory network of miR-200b-3p in endometriosis not only revealed its biological function but also provided a valuable guideline for further research.

Background Emerging evidence suggests that competing endogenous RNAs plays a crucial role in the development and progress of pancreatic adenocarcinoma (PAAD). The objective was to identify a new lncRNA-miRNA-mRNA network as prognostic markers, and develop and validate a multi-mRNAs-based classifier for predicting overall survival (OS) in PAAD. Methods Data on pancreatic RNA expression and clinical information of 445 PAAD patients and 328 normal subjects were downloaded from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and Genotype-Tissue Expression (GTEx). The weighted correlation network analysis (WGCNA) was used to analyze long non-coding RNA (lncRNA) and mRNA, clustering genes with similar expression patterns. MiRcode was used to predict the sponge microRNAs (miRNAs) corresponding to lncRNAs. The downstream targeted mRNAs of miRNAs were identified by starBase, miRDB, miRTarBase and Targetscan. A multi-mRNAs-based classifier was develop using least absolute shrinkage and selection operator method (LASSO) COX regression model, which was tested in an independent validation cohort. Results A lncRNA-miRNA-mRNA co-expression network which consisted of 60 lncRNAs, 3 miRNAs and 3 mRNAs associated with the prognosis of patients with PAAD was established. In addition, we constructed a 14-mRNAs-based classifier based on a training cohort composed of 178 PAAD patients, of which the area under receiver operating characteristic (AUC) in predicting 1-year, 3-year, and 5-year OS was 0.719, 0.806 and 0.794, respectively. The classifier also shown good prediction function in independent verification cohorts, with the AUC of 0.604, 0.639 and 0.607, respectively. Conclusions A novel competitive endogenous RNA (ceRNA) network associated with progression of PAAD could be used as a reference for future molecular biology research.

Background Circular RNAs (circRNAs) were elucidated to act as competing endogenous RNAs (ceRNAs) and to play significant roles in cancer initiation and progression. We aimed to identify the important circRNAs in lung adenocarcinoma and intended to predict the functions of them via the bioinformatics analysis. Methods We extracted data from three Gene Expression Omnibus (GEO) datasets, GSE101586, GSE101684, and GSE104854, and identified the common differentially expressed circRNAs. Agarose gel electrophoresis and Sanger sequencing were used to verify these significant circRNAs. Then, qRT-PCR was performed to validate the expression through matched tissues and cell lines. Afterwards, a ceRNA network was constructed and functional analysis was performed to predict the potential mechanisms of circRNAs. Results Five circRNAs (hsa_circ_0072088, hsa_circ_0082564, hsa_circ_0008274, hsa_circ_0000519 and hsa_circ_0003528) were identified differentially expressed in the three datasets. Following the Agarose gel electrophoresis and qRT-PCR validation, hsa_circ_0072088 and hsa_circ_0008274 were chosen for further analysis. A ceRNA network of hsa_circ_0072088 and hsa_circ_0008274 was built based on the CSCD/TargetScan/MiRTarbase/StarBase 3.0. Then, the functional analysis showed that several meaningful terms were identified, such as "epithelial to mesenchymal transition (EMT)", "Cellular response to TGF-β stimulus", "MAPK signaling pathway", and "PI3K-AKT signaling pathway". Finally, several significant circRNA/miRNA/mRNA regulatory axes, which were predicted relating to cancer progress, were noted from the network. Conclusion We identified significant circRNAs and meaningful circRNA-miRNA-mRNA networks to provide novel insight into pathogenesis and therapy of lung adenocarcinoma.

Emerging evidence demonstrates that competing endogenous RNA (ceRNA) hypothesis has played a role in molecular biological mechanisms of cancer occurrence and development. But the effect of ceRNA network in bladder cancer (BC), especially lncRNA‐miRNA‐mRNA regulatory network of BC, was not completely expounded. By means of The Cancer Genome Atlas (TCGA) database, we compared the expression of RNA sequencing (RNA‐Seq) data between 19 normal bladder tissue and 414 primary bladder tumours. Then, weighted gene co‐expression network analysis (WGCNA) was conducted to analyse the correlation between two sets of genes with traits. Interactions between miRNAs, lncRNAs and target mRNAs were predicted by MiRcode, miRDB, starBase, miRTarBase and TargetScan. Next, by univariate Cox regression and LASSO regression analysis, the 86 mRNAs obtained by prediction were used to construct a prognostic model which contained 4 mRNAs (ACTC1 + FAM129A + OSBPL10 + EPHA2). Then, by the 4 mRNAs in the prognostic model, a ceRNA regulatory network with 48 lncRNAs, 14 miRNAs and 4 mRNAs was constructed. To sum up, the ceRNA network can further explore gene regulation and predict the prognosis of BC patients.

The incidence and mortality rate of hepatocellular carcinoma (HCC) nowadays is still at high levels. The regulatory roles of pseudogene in cancers have been gradually recognized in recent years. However, comprehensive investigation of abnormally expressed pseudogene and related mechanisms in HCC remains lacking. GSE124535 dataset was used to identify differentially expressed pseudogenes in HCC tissues compared with normal tissues. Prognostic value of these differentially expressed pseudogenes was analyzed at GEPIA. StarBase used to analyze microRNAs (miRNAs) can bind with pseudogene, while the targets for these miRNAs were analyzed at miRTarBase. Protein-protein interaction (PPI) network was then established for miRNA targets, after that hub genes were selected. Expression correlation of pseudogene and hub genes was analyzed at StarBase. In total, 16 upregulated and 17 downregulated pseudogenes were identified. Pseudogene HSPB1P1 was identified abnormally expressed in 20 types of human cancers and could be used as an indicator for poorer overall survival of patients with HCC. Functional analyses showed that HSPB1P1 was strongly correlated with signaling pathways related to cancer progression. Further studied revealed that HSPB1P1 could direct regulate the EZH2 expression in HCC. In summary, our study indicated that HSPB1P1 was a predictor for poorer overall survival of patients with HCC and may be potential therapeutic target against HCC.

Alzheimer’s Disease (AD) is a progressive neurodegenerative disorder and the most common cause of dementia; however, early diagnosis of the disease is challenging. Research suggests that biomarkers found in blood, such as microRNAs (miRNA), may be promising for AD diagnostics. Experimental data on miRNA–target interactions (MTI) associated with AD are scattered across databases and publications, thus making the identification of promising miRNA biomarkers for AD difficult. In response to this, a list of experimentally validated AD-associated MTIs was obtained from miRTarBase. Cytoscape was used to create a visual MTI network. STRING software was used for protein–protein interaction analysis and mirPath was used for pathway enrichment analysis. Several targets regulated by multiple miRNAs were identified, including: BACE1, APP, NCSTN, SP1, SIRT1, and PTEN. The miRNA with the highest numbers of interactions in the network were: miR-9, miR-16, miR-34a, miR-106a, miR-107, miR-125b, miR-146, and miR-181c. The analysis revealed seven subnetworks, representing disease modules which have a potential for further biomarker development. The obtained MTI network is not yet complete, and additional studies are needed for the comprehensive understanding of the AD-associated miRNA targetome.

Coronary heart disease (CHD) is a global health concern with high morbidity and mortality rates. This study aimed to identify the possible long non-coding RNA (lncRNA) biomarkers of CHD. The lncRNA- and mRNA-related data of patients with CHD were downloaded from the Gene Expression Omnibus database (GSE113079). The limma package was used to identify differentially expressed lncRNAs and mRNAs (DElncRNAs and DEmRNAs, respectively). Then, miRcode, TargetScan, miRDB, and miRTarBase databases were used to form the competing endogenous RNA (ceRNA) network. Furthermore, SPSS Modeler 18.0 was used to construct a logistic stepwise regression prediction model for CHD diagnosis based on DElncRNAs. Of the microarray data, 70% was used as a training set and 30% as a test set. Moreover, a validation cohort including 30 patients with CHD and 30 healthy controls was used to verify the hub lncRNA expression through real-time reverse transcription-quantitative PCR (RT-qPCR). A total of 185 DElncRNAs (114 upregulated and 71 downregulated) and 382 DEmRNAs (162 upregulated and 220 downregulated) between CHD and healthy controls were identified from the microarray data. Furthermore, through bioinformatics prediction, a 38 lncRNA-21miRNA-40 mRNA ceRNA network was constructed. Next, by constructing a logistic stepwise regression prediction model for 38 DElncRNAs, we screened two hub lncRNAs AC010082.1 and AC011443.1 (p < 0.05). The sensitivity, specificity, and area under the curve were 98.41%, 100%, and 0.995, respectively, for the training set and 93.33%, 91.67%, and 0.983, respectively, for the test set. We further verified the significant upregulation of AC010082.1 (p < 0.01) and AC011443.1 (p < 0.05) in patients with CHD using RT-qPCR in the validation cohort. Our results suggest that lncRNA AC010082.1 and AC011443.1 are potential biomarkers of CHD. Their pathological mechanism in CHD requires further validation.

Background: Previous studies have identified differentially expressed microRNAs in autism spectrum disorder (ASD), however, results are discrepant. We aimed to systematically review this topic and perform bioinformatic analysis to identify genes and pathways associated with ASD miRNAs.Methods: Following the Preferred Reporting Items for Systematic reviews and Meta-Analyses, we searched the Web of Science, PubMed, Embase, Scopus, and OVID databases to identify all studies comparing microRNA expressions between ASD persons and non-ASD controls on May 11, 2020. We obtained ASD miRNA targets validated by experimental assays from miRTarBase and performed pathway enrichment analysis using Metascape and DIANA-miRPath v3. 0.Results: Thirty-four studies were included in the systematic review. Among 285 altered miRNAs reported in these studies, 15 were consistently upregulated, 14 were consistently downregulated, and 39 were inconsistently dysregulated. The most frequently altered miRNAs including miR-23a-3p, miR-106b-5p, miR-146a-5p, miR-7-5p, miR-27a-3p, miR-181b-5p, miR-486-3p, and miR-451a. Subgroup analysis of tissues showed that miR-146a-5p, miR-155-5p, miR-1277-3p, miR-21-3p, miR-106b-5p, and miR-451a were consistently upregulated in brain tissues, while miR-4742-3p was consistently downregulated; miR-23b-3p, miR-483-5p, and miR-23a-3p were consistently upregulated in blood samples, while miR-15a-5p, miR-193a-5p, miR-20a-5p, miR-574-3p, miR-92a-3p, miR-3135a, and miR-103a-3p were consistently downregulated; miR-7-5p was consistently upregulated in saliva, miR-23a-3p and miR-32-5p were consistently downregulated. The altered ASD miRNAs identified in at least two independent studies were validated to target many autism risk genes. TNRC6B, PTEN, AGO1, SKI, and SMAD4 were the most frequent targets, and miR-92a-3p had the most target autism risk genes. Pathway enrichment analysis showed that ASD miRNAs are significantly involved in pathways associated with cancer, metabolism (notably Steroid biosynthesis, Fatty acid metabolism, Fatty acid biosynthesis, Lysine degradation, Biotin metabolism), cell cycle, cell signaling (especially Hippo, FoxO, TGF-beta, p53, Thyroid hormone, and Estrogen signaling pathway), adherens junction, extracellular matrix-receptor interaction, and Prion diseases.Conclusions: Altered miRNAs in ASD target autism risk genes and are involved in various ASD-related pathways, some of which are understudied and require further investigation.

Background: The complicated molecular mechanisms underlying the therapeutic effect of electroacupuncture (EA) on ischemic stroke are still unclear. Recently, more evidence has revealed the essential role of the microRNA (miRNA)–mRNA networks in ischemic stroke. However, a systematic analysis of novel key genes, miRNAs, and miRNA–mRNA networks regulated by EA in ischemic stroke is still absent.Methods: We established a middle cerebral artery occlusion (MCAO) mouse model and performed EA therapy on ischemic stroke mice. Behavior tests and measurement of infarction area were applied to measure the effect of EA treatment. Then, we performed RNA sequencing to analyze differentially expressed genes (DEGs) and functional enrichment between the EA and control groups. In addition, a protein–protein interaction (PPI) network was built, and hub genes were screened by Cytoscape. Upstream miRNAs were predicted by miRTarBase. Then hub genes and predicted miRNAs were verified as key biomarkers by RT-qPCR. Finally, miRNA–mRNA networks were constructed to explore the potential mechanisms of EA in ischemic stroke.Results: Our analysis revealed that EA treatment could significantly alleviate neurological deficits in the affected limbs and reduce infarct area of the MCAO model mice. A total of 174 significant DEGs, including 53 upregulated genes and 121 downregulated genes, were identified between the EA and control groups. Functional enrichment analysis showed that these DEGs were associated with the FOXO signaling pathway, NF-kappa B signaling pathway, T-cell receptor signaling pathway, and other vital pathways. The top 10 genes with the highest degree scores were identified as hub genes based on the degree method, but only seven genes were verified as key genes according to RT-qPCR. Twelve upstream miRNAs were predicted to target the seven key genes. However, only four miRNAs were significantly upregulated and indicated favorable effects of EA treatment. Finally, comprehensive analysis of the results identified the miR-425-5p-Cdk1, mmu-miR-1186b-Prc1, mmu-miR-434-3p-Prc1, and mmu-miR-453-Prc1 miRNA–mRNA networks as key networks that are regulated by EA and linked to ischemic stroke. These networks might mainly take place in neuronal cells regulated by EA in ischemic stroke.Conclusion: In summary, our study identified key DEGs, miRNAs, and miRNA–mRNA regulatory networks that may help to facilitate the understanding of the molecular mechanism underlying the effect of EA treatment on ischemic stroke.

Made available in DSpace on 2022-04-29T08:45:57Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-09-22 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) MicroRNAs (miRNAs) play an important role in the pathophysiology of preeclampsia (PE). However, the expression of circulating miRNAs was not analyzed in the second trimester of pregnancy, a period of major relevance to identify predictive biomarkers for PE. Therefore, we examined the expression profiles of 84 circulating miRNAs using a PCR array in plasma collected between 20 and 25 weeks of gestation from pregnant women, who subsequently developed PE and those who remained healthy during pregnancy, randomly selected from a prospective cohort. Overall, 23 miRNAs had a fold change > 2.0 and were considered to be upregulated in plasma from pregnant women who subsequently developed PE, even before the onset of clinical symptoms of PE. However, only miR-204-5p was statistically significant (P = 0.0082). Experimentally validated interactions for the target genes of miR-204-5p extracted from miRTarBase were used in the gene set functional enrichment analysis to identify Reactome pathways. The network connecting the 37 target genes for miR-204-5p revealed pathways of known pathophysiological relevance during the early development of PE and included key genes related to PE, such as BDNF, MMP-9, MALAT1, TGFBR2, and SIRT1. We further depicted downstream targets of SIRT1 that are related to the vascular endothelial function or implicated in the pathophysiology of PE, namely, FOXO1, NFκB, HIF-1α, NOS3, and PPAR-γ. Our novel findings provide for circulating miRNAs upregulated in the second trimester on plasma from pregnant women who subsequently developed PE that is potentially related to the early development of PE, which may guide further studies focused on the validation of potential predictive biomarkers in PE. Department of Genetics Ecology and Evolution Institute of Biological Sciences Federal University of Minas Gerais Department of Biophysics and Pharmacology Institute of Biosciences Universidade Estadual Paulista (UNESP) Department of Gynecology and Obstetrics Ribeirao Preto Medical School University of São Paulo Ribeirao Preto Department of Biophysics and Pharmacology Institute of Biosciences Universidade Estadual Paulista (UNESP) FAPESP: #2008/53593-0 CNPq: #2014-5/305587 FAPESP: #2015/20461-8 CAPES: [Finance Code 001]

Gallbladder cancer (GBC), the most common malignancy in the biliary tract, is highly lethal malignant due to seldomly specific symptoms in the early stage of GBC. This study aimed to identify exosome-derived miRNAs mediated competing endogenous RNAs (ceRNA) participant in GBC tumorigenesis. A total of 159 differentially expressed miRNAs (DEMs) was identified as exosome-derived miRNAs, contains 34 upregulated exo-DEMs and 125 downregulated exo-DEMs based on the expression profiles in GBC clinical samples downloaded from the Gene Expression Omnibus database with the R package. Among them, 2 up-regulated exo-DEMs, hsa-miR-125a-3p and hsa-miR-4647, and 5 down-regulated exo-DEMs, including hsa-miR-29c-5p, hsa-miR-145a-5p, hsa-miR-192-5p, hsa-miR-194-5p, and hsa-miR-338-3p, were associated with the survival of GBC patients. Results of the gene set enrichment analysis showed that the cell cycle-related pathways were activated in GBC tumor tissues, mainly including cell cycle, M phase, and cell cycle checkpoints. Furthermore, the dysregulated ceRNA network was constructed based on the lncRNA-miRNA-mRNA interactions using miRDB, TargetScan, miRTarBase, miRcode, and starBase v2.0., consisting of 27 lncRNAs, 6 prognostic exo-DEMs, and 176 mRNAs. Together with prognostic exo-DEMs, the STEAP3-AS1/hsa-miR-192-5p/MAD2L1 axis was identified, suggesting lncRNA STEAP3-AS1, might as a sponge of exosome-derived hsa-miR-192-5p, modulates cell cycle progression via affecting MAD2L1 expression in GBC tumorigenesis. In addition, the biological functions of genes in the ceRNA network were also annotated by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. Our study promotes exploration of the molecular mechanisms associated with tumorigenesis and provide potential targets for GBC diagnosis and treatment. Supplementary Information The online version contains supplementary material available at 10.1007/s12032-021-01594-8.

Long non-coding RNAs (lncRNAs) act as competing endogenous RNAs (ceRNAs) to regulate mRNA expression through sponging microRNA in tumorigenesis and progression. However, following the discovery of new RNA interaction, the differentially expressed RNAs and ceRNA regulatory network are required to update. Our study comprehensively analyzed the differentially expressed RNA and corresponding ceRNA network and thus constructed a potentially predictive tool for prognosis. “DESeq2” was used to perform differential expression analysis. Two hundred and six differentially expressed (DE) lncRNAs, 222 DE miRNAs, and 2,463 DE mRNAs were found in this study. The lncRNA-mRNA interactions in the miRcode database and the miRNA-mRNA interactions in the starBase, miRcode, and mirTarBase databases were searched, and a competing endogenous RNA (ceRNA) network with 186 nodes and 836 interactions was subsequently constructed. Aberrant expression patterns of lncRNA NR2F1-AS1 and lncRNA AC010168.2 were evaluated in two datasets (GSE89006, GSE31684), and real-time polymerase chain reaction was also performed to validate the expression pattern. Furthermore, we found that these two lncRNAs were independent prognostic biomarkers to generate a prognostic lncRNA signature by univariate and multivariate Cox analyses. According to the lncRNA signature, patients in the high-risk group were associated with a poor prognosis and validated by an external dataset. A novel genomic-clinicopathologic nomogram to improve prognosis prediction of bladder cancer was further plotted and calibrated. Our study deepens the understanding of the regulatory ceRNA network and provides an easy-to-do genomic-clinicopathological nomogram to predict the prognosis in patients with bladder cancer.

Objective. This study is aimed at identifying key genes involved in neurological damage in preterm infants and at determining their potential circRNA-miRNA-mRNA regulatory mechanisms. Methods. Differentially expressed miRNAs, mRNAs, and circRNAs were downloaded from the GEO database. GO and KEGG enrichment analyses were used to determine possible relevant functions of differentially expressed mRNAs. The TTRUST database was used to predict differential TF-mRNA regulatory relationships. Then, CircMIR, miRDB, TargetScan and miRTarBase were then used to map circRNA/miRNA-TF/mRNA interaction networks. Finally, GSEA enrichment analysis was performed on the core transcription factors. Results. A total of 640 mRNAs, 139 circRNAs, and 206 differentially expressed miRNAs associated with neurological injury in preterm infants were obtained. Based on the findings of Cytoscape and PPI network analysis, the hsa_circ_0008439-hsa-mir-3665-STAT3-MMP3 regulatory axis was established. GSEA analysis revealed that suppressed expression levels of STAT3 were associated with upregulated oxidative phosphorylation pathways in the neurological injury group of preterm infants. Conclusions. The circRNA-miRNA-TF-mRNA regulatory network of neurological injury in preterm infants can be used to elucidate on the pathogenesis of brain injury and help us with the early detection of brain injury in preterm infants.

Dengue fever virus (DENV) is a global health threat that is becoming increasingly critical. However, the pathogenesis of dengue has not yet been fully elucidated. In this study, we employed bioinformatics analysis to identify potential biomarkers related to dengue fever and clarify their underlying mechanisms. The results showed that there were 668, 1901, and 8283 differentially expressed genes between the dengue-infected samples and normal samples in the GSE28405, GSE38246, and GSE51808 datasets, respectively. Through overlapping, a total of 69 differentially expressed genes (DEGs) were identified, of which 51 were upregulated and 18 were downregulated. We identified twelve hub genes, including MX1, IFI44L, IFI44, IFI27, ISG15, STAT1, IFI35, OAS3, OAS2, OAS1, IFI6, and USP18. Except for IFI44 and STAT1, the others were statistically significant after validation. We predicted the related microRNAs (miRNAs) of these 12 target genes through the database miRTarBase, and finally obtained one important miRNA: has-mir-146a-5p. In addition, gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were carried out, and a protein–protein interaction (PPI) network was constructed to gain insight into the actions of DEGs. In conclusion, our study displayed the effectiveness of bioinformatics analysis methods in screening potential pathogenic genes in dengue fever and their underlying mechanisms. Further, we successfully predicted IFI44L and IFI6, as potential biomarkers with DENV infection, providing promising targets for the treatment of dengue fever to a certain extent., Author summary Dengue fever is a mosquito borne viral disease caused by a single stranded RNA virus with four serotypes. DENV infection can cause various diseases, such as breakbone fever, haemorrhagic fever, and shock syndrome. As one of the most viral diseases leading to incidence rate and mortality in animal arthropods, Dengue fever has become an increasingly serious global health threat. However, the pathogenesis of dengue fever has not been fully elucidated. In this study, we used bioinformatics analysis to identify potential biomarkers associated with dengue fever and elucidate their underlying mechanisms. Finally, we predicted that IFI44L and IFI6 might be potential biomarkers of DENV infection. This finding provides a promising target for the treatment of dengue fever to a certain extent. In addition, the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, protein–protein interaction (PPI) network were implemented to analyze the key differentially expressed genes after DENV infection, and the related mechanisms were illuminated by this study.

Abnormal metabolism, including abnormal fatty acid metabolism, is an emerging hallmark of cancer. The current study sought to investigate the potential prognostic value of fatty acid metabolism-related long noncoding RNAs (lncRNAs) in colorectal cancer (CRC). To this end, we obtained the gene expression data and clinical data of patients with CRC from The Cancer Genome Atlas (TCGA) database. Through gene set variation analysis (GSVA), we found that the fatty acid metabolism pathway was related to the clinical stage and prognosis of patients with CRC. After screening differentially expressed RNAs, we constructed a fatty acid metabolism-related competing endogenous RNA (ceRNA) network based on the miRTarBase, miRDB, TargetScan, and StarBase databases. Next, eight fatty acid metabolism-related lncRNAs included in the ceRNA network were identified to build a prognostic signature with Cox and least absolute shrinkage and selection operator (LASSO) regression analyses, and a nomogram was established based on the lncRNA signature and clinical variables. The signature and nomogram were further validated by Kaplan–Meier survival analysis, Cox regression analysis, calibration plots, receiver operating characteristic (ROC) curves, decision curve analysis (DCA). Besides, the TCGA internal and the quantitative real-time polymerase chain reaction (qRT-PCR) external cohorts were applied to successfully validate the robustness of the signature and nomogram. Finally, in vitro assays showed that knockdown of prognostic lncRNA TSPEAR-AS2 decreased the triglyceride (TG) content and the expressions of fatty acid synthase (FASN) and acetyl-CoA carboxylase 1 (ACC1) in CRC cells, which indicated the important role of lncRNA TSPEAR-AS2 in modulating fatty acid metabolism of CRC. The result of Oil Red O staining showed that the lipid content in lncRNA TSPEAR-AS2 high expression group was higher than that in lncRNA TSPEAR-AS2 low expression group. Our study may provide helpful information for fatty acid metabolism targeting therapies in CRC.

Parkinson's disease (PD) and Multiple System Atrophy (MSA) are progressive neurodegenerative diseases with overlap of symptoms in early stages of disease. No reliable biomarker exists and the diagnosis is mainly based on clinical features. Several studies suggest that miRNAs are involved in PD and MSA pathogenesis. Our goal was to study two serum circulating microRNAs (miR-96-5p and miR-339-5p) as novel biomarkers for the differential diagnosis between PD and MSA. Serum samples were obtained from 51 PD patients, 52 MSA patients and 56 healthy controls (HC). We measured levels of miRNAs using quantitative PCR and compared the levels of miR-96-5p and miR-339-5p among PD, MSA and HC groups using a one-way analysis of variance. Correlations between miRNA expression and clinical data were calculated using Pearson's rho test. We used the miRTarBase to detect miRNA targets and STRING to evaluate co-expression relationship among target genes. MiR-96-5p was significantly increased in MSA patients compared with HC (Fold change (fc): 3.6; p = 0.0001) while it was decreased in PD patients compared with HC (Fold change: 4; p = 0.0002). Higher miR-96-5P levels were directly related to longer disease duration in MSA patients. We observed a significant increase of miR-339-5p in MSA patients compared with PD patients (fc: 2.5; p = 0.00013). miR-339-5p was increased in MSA patients compared with HC (fc: 2.4; p = 0.002). We identified 32 target genes of miR-96-5p and miR-339-5p, some of which are involved in neurodegenerative diseases. The study of those miRNAs could be useful to identify non-invasive biomarkers for early differential diagnosis between PD and MSA.

BackgroundSystemic lupus erythematosus (SLE) is an autoimmune disease that can affect multiple systems. Pulmonary arterial hypertension (PAH) has a close linkage with SLE. However, the inter-relational mechanisms between them are still unclear. This article aimed to explore the shared gene signatures and potential molecular mechanisms in SLE and PAH.MethodsThe microarray data of SLE and PAH in the Gene Expression Omnibus (GEO) database were downloaded. The Weighted Gene Co-Expression Network Analysis (WGCNA) was used to identify the co-expression modules related to SLE and PAH. The shared genes existing in the SLE and PAH were performed an enrichment analysis by ClueGO software, and their unique genes were also performed with biological processes analyses using the DAVID website. The results were validated in another cohort by differential gene analysis. Moreover, the common microRNAs (miRNAs) in SLE and PAH were obtained from the Human microRNA Disease Database (HMDD) and the target genes of whom were predicted through the miRTarbase. Finally, we constructed the common miRNAs–mRNAs network with the overlapped genes in target and shared genes. ResultsUsing WGCNA, four modules and one module were identified as the significant modules with SLE and PAH, respectively. A ClueGO enrichment analysis of shared genes reported that highly activated type I IFN response was a common feature in the pathophysiology of SLE and PAH. The results of differential analysis in another cohort were extremely similar to them. We also proposed a disease road model for the possible mechanism of PAH secondary to SLE according to the shared and unique gene signatures in SLE and PAH. The miRNA–mRNA network showed that hsa-miR-146a might regulate the shared IFN-induced genes, which might play an important role in PAH secondary to SLE.ConclusionOur work firstly revealed the high IFN response in SLE patients might be a crucial susceptible factor for PAH and identified novel gene candidates that could be used as biomarkers or potential therapeutic targets.

Buze Chen,1,2,&ast; Xin Jin,3,&ast; Haihong Wang,1 Qingmei Zhou,1 Guilin Li,3 Xiaoyuan Lu1 1Department of Gynecology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, 221000, People’s Republic of China; 2Xuzhou Medical University, Xuzhou, Jiangsu, 221000, People’s Republic of China; 3Department of Gynecology, Maternal and Child Health Care Hospital Affiliated to Xuzhou Medical University, Xuzhou, Jiangsu, 221000, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Xiaoyuan LuDepartment of Gynecology, The Affiliated Hospital of Xuzhou Medical University, No. 99 West Huaihai Road, Quanshan District, Xuzhou, 221000, Jiangsu, People’s Republic of ChinaTel +86-180 52268119Email 18052268119@189.cnGuilin LiDepartment of Gynecology, Maternal and Child Health Care Hospital Affiliated to Xuzhou Medical University, No. 46 Heping Road, Yunlong District, Xuzhou, Jiangsu, 221000, People’s Republic of ChinaTel +86-18936372957Email liguilin8@126.comBackground: The present study aims to explore the expression, clinical significance, and prospective pathway signaling of miR-501-3p in ovarian cancer (OC) based on database and informatics analysis.Methods: Kruskal–Wallis test, Wilcoxon sign-rank test, and logistic regression were used to evaluate the relationship between clinical features and miR-501-3p expression. Kaplan–Meier survival curve analysis was used to explore the relationship between miR-501-3p expression and the prognosis of OC patients. The miRNA targets were obtained from databases TargetScan, miRanda, TarBase, miRTarBase, miR2Disease, miRecords, and miRWalk. GO and KEGG analyses were used to analyze the significant involvement of miR-501-3p target genes in function.Results: The low miR-501-3p expression in OC was significantly associated with histologic grade (P=0.015). Low miR-501-3p expression predicted a poorer overall survival (HR: 0.77; 95% CI: 0.61– 0.96; P=0.02) and disease-specific survival (HR: 0.77; 95% CI: 0.61– 0.99; P=0.038). GO and KEGG analyses demonstrated that miR-501-3p might participate in the development of OC by pathways including one carbon pool by folate, protein digestion and absorption, cell cycle, kaposi sarcoma-associated herpesvirus infection, and viral carcinogenesis.Conclusions: Low miR-501-3p expression is significantly associated with poor survival in OC patients. It may be a promising prognostic biomarker for OC patients.Keywords: microRNA-501-3p, ovarian cancer, prognosis, the cancer genome atlas, gene expression

Systemic sclerosis (SSc) is an immune-mediated connective tissue disease characterized by fibrosis of multi-organs, and SSc-related interstitial lung disease (SSc-ILD) is a leading cause of morbidity and mortality. To explore molecular biological mechanisms of SSc-ILD, we constructed a competing endogenous RNA (ceRNA) network for prediction. Expression profiling data were obtained from the Gene Expression Omnibus (GEO) database, and differential expressed mRNAs and miRNAs analysis was further conducted between normal lung tissue and SSc lung tissue. Also, the interactions of miRNA–lncRNA, miRNA–mRNA, and lncRNA–mRNA were predicted by online databases including starBase, LncBase, miRTarBase, and LncACTdb. The ceRNA network containing 11 lncRNAs, 7 miRNAs, and 20 mRNAs were constructed. Based on hub genes and miRNAs identified by weighted correlation network analysis (WGCNA) method, three core sub-networks—SNHG16, LIN01128, RP11-834C11.4(LINC02381)/hsa-let-7f-5p/IL6, LINC01128/has-miR-21-5p/PTX3, and LINC00665/hsa-miR-155-5p/PLS1—were obtained. Combined with previous studies and enrichment analyses, the lncRNA-mediated network affected LPS-induced inflammatory and immune processes, fibrosis development, and tumor microenvironment variations. The ceRNA network, especially three core sub-networks, may be served as early biomarkers and potential targets for SSc, which also provides further insights into the occurrence, progression, and accurate treatment of SSc at the molecular level.

BackgroundA detailed means of prognostic stratification in patients with non-small cell lung cancer (NSCLC) is urgently needed to support individualized treatment plans. Recently, microRNAs (miRNAs) have been used as biomarkers due to their previously reported prognostic roles in cancer. This study aimed to construct an immune-related miRNA signature that effectively predicts NSCLC patient prognosis.MethodsThe miRNAs and mRNA expression and mutation data of NSCLC was obtained from The Cancer Genome Atlas (TCGA). Immune-associated miRNAs were identified using immune scores calculated by the ESTIMATE algorithm. LASSO-penalized multivariate survival models were using for development of a tumor immune-related miRNA signature (TIM-Sig), which was evaluated in several public cohorts from the Gene Expression Omnibus (GEO) and the CellMiner database. The miRTarBase was used for constructing the miRNA-target interactions.ResultsThe TIM-Sig, including 10 immune-related miRNAs, was constructed and successfully predicted overall survival (OS) in the validation cohorts. TIM-Sig score negatively correlated with CD8+ T cell infiltration, IFN-γ expression, CYT activity, and tumor mutation burden. The correlation between TIM-Sig score and genomic mutation and cancer chemotherapeutics was also evaluated. A miRNA-target network of 10 miRNAs in TIM-Sig was constructed. Further analysis revealed that these target genes showed prognostic value in both lung squamous cell carcinoma and adenocarcinoma.ConclusionsWe concluded that the immune-related miRNAs demonstrated a potential value in clinical prognosis.

BACKGROUND: The aim of the study was to suggest a high specific and sensitive blood biomarker for early GC diagnosis. METHODS: the expression data of miRNAs and mRNAs were collected from the blood samples of the GC patients based on literature mining. Bioinformatics tools and databases (PANTHER, TargetScan, miRTarBase, miRDB, STRING, and Cytoscape) were used to predict the regulatory relationship. Subsequently, expression level of the selected miRNA was evaluated in the blood samples of gastritis patients to recognize the common miRNA between the GC and gastritis patients. RESULTS: Analysis of 40 target genes by MCODE (installed in Cytoscape software) indicated 4 hub genes (WWP1, SKP2, KLHL42, and FBXO11) as a significant cluster in the PPI network related to miR-21, with Node Score Cutoff: 0.2, Degree Cutoff: 2 and K-Core: 2. In addition, the miRNA RT-qPCR results showed that, the expression level of miR-21 was significantly higher in gastritis group compared to the healthy group (p< 0.05). CONCLUSION: the present study clearly demonstrated the increasing level of blood miR-21 among the gastritis patients infected by H. pylori. Therefore, the altered miRNAs, especially overexpression of onco-miRs, may identify a potential link between miRNAs and pathogenesis of the H. pylori–related complications.

BACKGROUND Gastric adenocarcinoma (GAC) mortality rates have remained relatively changed over the past 30 years, and it continues to be one of the leading causes of cancer-related death. AIM To search for novel miRNAs related to GAC prognosis and further investigate the effect of miR-96-5p on MGC-803 cells. METHODS The miRNA expression profile data of GAC based on The Cancer Genome Atlas were obtained and used to screen differently expressed miRNAs (DEMs) and DEMs related to GAC prognosis. Then, the expression of DEMs related to GAC prognosis was identified in GAC tumor samples and adjacent normal samples by qRT-PCR. The target gene, ZDHHC5, of miR-96-5p was predicted using TargetScan, miRTarBase, and miRDB databases and confirmed by luciferase reporter assay. Furthermore, MGC-803 cells were transfected with inhibitor NC, miR-96-5p inhibitor, si-ZDHHC5, or miR-96-5p inhibitor + si-ZDHHC5, and then cell apoptosis was detected by flow cytometry. The expression of ZDHHC5, Bcl-2, and COX-2 was detected using western blotting. RESULTS A total of 299 DEMs and 35 DEMs related to GAC prognosis were screened based on The Cancer Genome Atlas. Then compared with adjacent normal samples, the levels of miR-96-5p, miR-222-5p, and miR-652-5p were remarkably increased, while miR-125-5p, miR-145-3p, and miR-379-3p levels were reduced in GAC tumor samples (P < 0.01), which were consistent with bioinformatics analysis. Furthermore, ZDHHC5 was defined as a direct target gene of miR-96-5p. miR-96-5p inhibition increased the number of apoptotic cells as well as promoted the expression of ZDHHC5, Bcl-2, and COX-2 in MGC-803 cells (P < 0.01). After ZDHHC5 inhibition, the number of apoptotic cells and the expression of ZDHHC5, Bcl-2, and COX-2 were reduced. The addition of an miR-96-5p inhibitor partly reversed these effects (P < 0.01). CONCLUSION Our findings identified six miRNAs related to GAC prognosis and suggested that downregulated miR-96-5p might induce cell apoptosis via upregulating ZDHHC5 expression in MGC-803 cells.

Ovarian cancer (OC) is a leading cause of death among women worldwide. Various evidences suggest that oncomiRs and Toll-like receptor 4 (TLR-4) signaling pathways appear to be key players in the initiation and progression of OC. It seems there exists a continuous intercommunication between cancer cells and normal microbiota of the vagina. The biological impacts of vaginal isolated lactococcus lactis on CAOV-4 cells were investigated using several molecular biology experiments, including flow cytometry, DAPI staining, DNA ladder, and scratch assay. The expression of microRNAs (miRNAs/miRs) 21, 200b, and TLR-4 in the CAOV-4 cells was also evaluated by the real-time RT-PCR assay. Furthermore, an integrative in silico analysis was conducted using normalized web-available microarray data (GSE14407) to revalidate the experimental findings and identify potential biomarkers in ovarian cancer. Protein-protein interactions (PPIs) network was studied by means of the STRING database using Cytoscape v3.6.1. The miRNA target genes were identified using the dbDEMC v2.0, miRTarBase, and miRDB databases. Our data demonstrated that L. lactis probiotic candidate downregulates TLR-4, miR-21, and miR-200b expression levels, which correlates with induction of apoptosis as confirmed by DAPI staining, DNA ladder assay, annexin V/PI staining, and inhibition of migration validated by scratch assay. By in silico analysis, several targets (miR-17-5p-BCL2, miR-21-5p-MKNK2, miR-129-5p-CDK6) were identified, while BCL2, CCNB1, and VEGFA were found as the hub proteins in the miRNA-target and PPI networks. Further, downregulation of the TLR-4, miR-21, and miR-200b was partially validated by the in silico analysis. Based on our findings, the vaginal isolated probiotic strain presents great potential to control the ovarian cancer which may provide beneficial impact on the clinical management of ovarian cancer.

PURPOSE Endometrial carcinoma (EC), a common gynecological malignancy with high incidence, affects the mental and physical health of women. Mounting evidence shows that long noncoding RNAs (lncRNAs), messenger RNAs (mRNAs), and microRNAs (miRNAs) have instrumental roles in various biological processes associated with the pathogenesis of EC. In this research, we intend to further study the mechanism of EC and the potential predictive markers of EC. METHODS First, we obtained original data of EC RNA transcripts from The Cancer Genome Atlas database and performed differential analysis. Subsequently, according to the miRcode online software, relationship pairs of lncRNA-miRNA were constructed, and miRNA-mRNA pairs were established based on miRDB, TargetScan, and miRTarBase. Then, we constructed the competing endogenous RNA (ceRNA) network based on lncRNA-miRNA and miRNA-mRNA pairs. To further explain the function of the ceRNA network and explore the potential prognostic markers, functional enrichment analysis, and survival analysis were carried out. RESULTS The research showed that there were 744 differential expression lncRNAs (DElncRNAs), 164 differential expression miRNAs (DEmiRNAs), and 2447 differential expression mRNAs (DEmRNAs) between EC tissues and normal tissues. Subsequently, we built 103 DEmiRNA-DEmRNA interaction pairs and 369 DElncRNA-DEmiRNA pairs. Then, we established the ceRNA network of EC, including 62 DElncRNAs, 26 DEmiRNAs, and 70 DEmRNAs. Moreover, 10 of 62 lncRNAs, 19 of 70 mRNAs, and 4 of 26 miRNAs that closely related to the survival of EC with P

BACKGROUND Melanoma of the skin can be associated with early metastases and poor prognosis. This study aimed to identify microRNAs (miRNAs) and target genes associated with prognosis in melanoma using bioinformatics analysis. MATERIAL AND METHODS The Gene Expression Omnibus (GEO) database identified the microarray dataset GSE20994. Differentially expressed miRNAs (DE-miRNAs) were first identified using R language software and validated by GEO2R. Potential target genes of DE-miRNAs were screened, and their targets and prognostic role were evaluated in the miRTarBase database. Pathway enrichment and functional annotation analysis for target genes were established using the DAVID database. miRNA-hub gene networks and protein-protein interaction (PPI) networks were constructed and visualized using the STRING database and Cytoscape. Kaplan-Meier survival curves were constructed using transcriptome and survival data from the UALCAN web tool. RESULTS There were 132 upregulated and 134 down-regulated DE-miRNAs identified from human melanoma samples. From the top three upregulated miRNAs, there were 580 potential predicted target genes, and from the top three down-regulated miRNAs, there 543 potential predicted target genes. miR-300 was upregulated, and miR-629 was down-regulated in melanoma. Two pivotal bub genes, TP53 and GAPDH, were identified in the PPI network. Five out of ten hub genes were modulated by upregulated miR-580, and five by miR-629. Increased mRNA expression of DAPK2 was associated with increased OS, and increased mRNA expression of SKCM, TECPR2, and ZNF781 were associated with reduced OS. CONCLUSIONS Bioinformatics analysis identified miRNAs and target genes associated with melanoma that may represent potential prognostic and therapeutic biomarkers.

Background: As a class of endogenous noncoding RNAs, some circular RNAs (circRNAs) have recently been reported to play a role in the regulation of tumorigenesis and progression in colorectal cancer (CRC). However, the mechanisms by which most these circRNAs function in CRC are still unclear. Purpose: The objective of this study was to identify the role of circRNA-ITGA7 in CRC cell proliferation. Patients and methods: Human genome-wide circRNA microarray v2 analysis was used for expression profile analysis. Target genes were predicted using online bioinformatics database, including TargetScan, miRDB, miRTarbase and miRMap. Gene overexpression and silencing cell models were built using cell transfection. qRT-PCR and Western blot were performed for gene and protein expression assessment. CCK8, colony formation and cell cycle analysis were used for proliferation testing. Annexin V-FITC analysis was performed for apoptosis detection. Results: CircRNA sequencing analysis suggested that compared to that in adjacent normal control tissue, the expression of circ-ITGA7, a novel circRNA, is decreased significantly in CRC. Gain-of-function studies further demonstrated that circ-ITGA7 suppressed proliferation of CRC cells. Based on prediction and verification, we subsequently revealed that miR-3187-3p is a circ-ITGA7-associated miRNA. Furthermore, RNA sequencing and bioinformatics analyses showed that ASXL1-5'UTR, the target of miR-3187-3p, is upregulated in circ-ITGA7-overexpressed cells and mediates the circ-ITGA7-induced suppression of proliferation. Conclusion: Circ-ITGA7 might suppress CRC proliferation by sponging miR-3187-3p and increasing ASXL1 expression. Thus, circ-ITGA7 might be a potential diagnostic biomarker and a therapeutic target for CRC.

Objective: MicroRNAs (miRNAs) have been explored in malignancies. We investigated the functions of clustered miRNAs hsa-miR-221/222-3p in hepatocellular carcinoma (HCC). Methods: Human miRNA tissue atlas website was determined expression levels in liver tissue. Four databases, TarBase, miRTarBase, miRecords and miRPathDB, were found experimentally validated target genes of clustered miRNAs. TargetScanHuman was predicted target genes. The STRING website was depicted protein-protein interaction (PPI) networks. The OncoLnc website analyzed prognostic values for hsa-miR-221/222-3p and their target genes. The MCODE plugin calculated modules of PPI networks. Receiver operating characteristic (ROC) curves were predicted 1, 3, and 5 years prognostic values. Results: Expression of clustered miRNAs was high in liver tissues. A total of 1577 target genes were identified. Enrichment analysis showed that target genes were enriched mainly in cancer, Wnt signaling and ErbB signaling pathways. Two modules were calculated using PPI networks. Has-miR-221-3p was not associated with prognosis (P = 0.401). Has-miR-222-3p and target genes ESR1, TMED7, CBFB, ETS2, UBE2J1 and UBE2N of the clustered miRNAs were associated with HCC survival (all P < 0.05). Has-miR-222-3p, CBFB, and UBE2N showed good performance of ROC in prognosis prediction at 1, 3, and 5 years (all area under curves > 0.600). Conclusion: Has-miR-222-3p and target genes, especially CBFB, UBE2N, may serve as prognostic predictors for HCC.

Background: Recently, increasing evidence has uncovered the roles of mRNA-miRNA-lncRNA network in multiple human cancers. However, a systematic mRNA-miRNA-lncRNA network linked to pancreatic cancer prognosis is still absent. Methods: Differentially expressed genes (DEGs) were first identified by mining {"type":"entrez-geo","attrs":{"text":"GSE16515","term_id":"16515"}}GSE16515 and {"type":"entrez-geo","attrs":{"text":"GSE15471","term_id":"15471"}}GSE15471 datasets. DAVID database was utilized to conduct functional enrichment analysis. Protein-protein interaction (PPI) network was built using STRING database, and hub genes were identified by Cytoscape plug-in CytoHubba. Upstream miRNAs and lncRNAs of mRNAs were predicted by miRTarBase and miRNet, respectively. Expression, survival and correlation analysis for genes, miRNAs and lncRNAs were performed via GEPIA, Kaplan-Meier plotter and starBase. Results: 734 and 180 upregulated and downregulated significant DEGs were identified, respectively. Functional enrichment analysis revealed that they were significantly enriched in focal adhesion, pathways in cancer and metabolic pathways. According to node degree, hub genes in the PPI networks were screened, such as TGFB1 and ALB. Among the top 20 hub genes, 7 upregulated genes and 2 downregulated hub genes had significant prognostic values in pancreatic cancer. 33 miRNAs were predicted to target the 9 key genes. But only high expression of 8 miRNAs indicated favorable prognosis in pancreatic cancer. Then, 90 lncRNAs were predicted to potentially bind to the 8 miRNAs. SCAMP1, HCP5, MAL2 and LINC00511 were finally identified as key lncRNAs. By combination of results from expression, survival and correlation analysis demonstrated that MMP9/ITGB1-miR-29b-3p-HCP5 competing endogenous RNA (ceRNA) sub-network was linked to prognosis of pancreatic cancer. Conclusions: In a word, we established a novel mRNA-miRNA-lncRNA sub-network, among which each RNA may be utilized as a prognostic biomarker of pancreatic cancer.

Purpose Breast cancer (BC) remains a serious health threat for women due to its high incidence and the trend of rejuvenation. Accumulating evidence has highlighted that microRNAs (miRNAs) and messenger RNAs (mRNAs) could play important roles in various biological processes involved in the pathogenesis of BC. The present study aimed to identify potential prognostic biomarkers associated with BC. Methods Here, original gene expression profiles of patients with BC was downloaded from The Cancer Genome Atlas (TCGA) database. TargetScan, miRDB, and miRTarBase databases were used to predict the target genes of prognostic-related differentially expressed miRNAs (DEMs). Subsequently, functional enrichment analysis and topological analysis were performed on the overlaps of target genes and differentially expressed mRNAs (DEGs), and Kaplan-Meier analysis was used to predict prognosis-related target genes to identify prognostic biomarkers. Results A total of 218 DEMs and 2222 DEGs were extracted in which eight miRNAs were associated with prognosis, and 278 target DEGs were screened out incorporated into functional enrichment analysis and protein-protein interaction network visualization studies. Additionally, five hub genes (CXCL12, IGF1, LEF1, MMP1, and RACGAP1) were observed as potential biomarkers for BC prognosis through survival analysis. Conclusion We performed a distinctive correlation analysis of miRNA-mRNA in BC patients, and identified eight miRNAs and five hub genes may be effective biomarkers for the prognosis of BC patients.

To better understand the molecular mechanism for the pathogenesis of follicular thyroid carcinoma (FTC), this study aimed at identifying key miRNAs and their target genes associated with FTC, as well as analyzing their interactions. Based on the gene microarray data GSE82208 and microRNA dataset GSE62054, the differentially expressed genes (DEGs) and microRNAs (DEMs) were obtained using R and SAM software. The common DEMs from R and SAM were fed to three different bioinformatic tools, TargetScan, miRDB, and miRTarBase, respectively, to predict their biological targets. With DEGs intersected with target genes of DEMs, the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed through the DAVID database. Then a protein-protein interaction (PPI) network was constructed by STRING. Finally, the module analysis for PPI network was performed by MCODE and BiNGO. A total of nine DEMs were identified, and their function might work through regulating hub genes in the PPI network especially KIT and EGFR. KEGG analysis showed that intersection genes were enriched in the PI3K-Akt signaling pathway and microRNAs in cancer. In conclusion, the study of miRNA-mRNA network would offer molecular support for differential diagnosis between malignant FTC and benign FTA, providing new insights into the potential targets for follicular thyroid carcinoma diagnosis and treatment.

Background: Epigenetic gene regulation is important in human cancer.Aim of Study: We investigated the possible role of acetyla-tion level in the regulation of microRNAs (miRNAs) expres-sion in hepatocellular carcinoma.Material and Methods: We first determined the inhibitory concentration (IC20, IC35 and IC50) of the histone deacetylase inhibitor Sodium Butyrate (SB) in HepG2 and Huh7 cells. Then, we analyzed the expression level of five miRNAs (miR-133b, miR-122-5p, miR-26a-5p, miR-539-5p and miR-518f-3p after treatment using qRT-PCR assay. MiRTarBase, MiROB and GeneCards databases were used for the identification of strong validated targets of examined microRNAs, and the detection of possible functions of the selected targets and related pathways.Results: SB revealed an anti-proliferative effect in both HepG2 and Huh7 cells, with IC50 values of 6.7mM and 9.2mM, respectively. MiR-133b showed up-regulation in HepG2 and miR-122-5p was down-regulated in HepG2 and Huh7 (29.5 and 1000 folds) in a dose dependent manner. MiR-26a-5p exhibited decrease in its level in both cell lines at IC35, but was increased at IC50 in HepG2 cells. MiR-518f-3p showed increase in its level during various doses of SB in both cell lines. Finally, miR-539-5p showed down expression in both cell lines. Prediction pathway analysis referred to the important role of each of miR-133b, miR-122-5p and miR-26a-5p in proliferation, apoptosis, angiogenesis and metastasis.Conclusion: Sub-lethal doses of SB have significant effects on miRNAs expression in human hepatocellular car-cinoma cells. Understanding the epigenetic regulation of miRNAs may enhance the development of therapeutic strate-gies against HCC.

BACKGROUND The aims of this study were to use RNA expression profile bioinformatics data from cases of thyroid cancer from the Cancer Genome Atlas (TCGA), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and the Gene Ontology (GO) databases to construct a competing endogenous RNA (ceRNA) network of mRNAs, long noncoding RNAs (lncRNAs), and microRNAs (miRNAs). MATERIAL AND METHODS TCGA provided RNA profiles from 515 thyroid cancer tissues and 56 normal thyroid tissues. The DESeq R package analyzed high-throughput sequencing data on differentially expressed RNAs. GO and KEGG pathway analysis used the DAVID 6.8 and the ClusterProfile R package. Kaplan-Meier survival statistics and Cox regression analysis were performed. The thyroid cancer ceRNA network was constructed based on the miRDB, miRTarBase, and TargetScan databases. RESULTS There were 1,098 mRNAs associated with thyroid cancer; 101 mRNAs were associated with overall survival (OS). Multivariate analysis developed a risk scoring system that identified seven signature mRNAs, with a discriminative value of 0.88, determined by receiver operating characteristic (ROC) curve analysis. A ceRNA network included 13 mRNAs, 31 lncRNAs, and seven miRNAs. Four out of the 31 lncRNAs and all miRNAs were down-regulated, and the remaining RNAs were upregulated. Two lncRNAs (MIR1281A2HG and OPCML-IT1) and one miRNA (miR-184) were significantly associated with OS in patients with thyroid cancer. CONCLUSIONS Differential RNA expression profiling in thyroid cancer was used to construct a ceRNA network of mRNAs, lncRNAs, and miRNAs that showed potential in evaluating prognosis.

Down syndrome, a genetic disorder of known attribution reveals several types of brain abnormalities resulting in mental retardation, inadequacy in speech and memory. In this study, we have presented a consolidative network approach to comprehend the intricacy of the associated genes of Down syndrome. In this analysis, the differentially expressed genes (DEG's) were identified and the central networks were constructed as upregulated and downregulated. Subsequently, GNB5, CDC42, SPTAN1, GNG2, GNAZ, PRKACB, SST, CD44, FGF2, PHLPP1, APP, and FYN were identified as the candidate hub genes by using topological parameters. Later, Fpclass a PPI tool identified WASP gene, a co-expression interacting partner with highest network topology. Moreover, an enhanced enrichment pathway namely Opioid signaling was obtained using ClueGo, depicting the roles of the hub genes in signaling and neuronal mechanisms. The transcriptional regulatory factors and the common miRNA connected to them were identified by using MatInspector and miRTarbase. Later, a regulatory network constructed showed that PLAG, T2FB, CREB, NEUR, and GATA were the most commonly connected transcriptional factors and hsa-miR-122-5p was the most prominent miRNA. In a nutshell, these hub genes and the enriched pathway could help understand at a molecular level and eventually used as therapeutic targets for Down syndrome.

Keloids are a common dermal pathological disorder characterized by the excessive deposition of extracellular matrix components; however, the exact pathogenesis of the disease is still not clear. Studies increasingly suggest that microRNAs (miRNAs) can play a key role in the process of keloid scarring. In this study, the valuable miRNAs and target genes were screened and the interaction network was constructed. We also predicted target genes of reported miRNAs using TargetScan and miRTarBase software. Cytoscape 3.0.1 further showed the interaction network of miRNA and target genes. Among the various miRNAs involved in keloid pathogenesis, miRNA-21, miRNA-141-3p, miRNA-181a, and miRNA-205 were thought to up-regulate the proliferation and decrease apoptosis of keloid-derived fibroblasts through the PI3K/Akt/mammalian target of rapamycin (mTOR) signaling pathway. miRNA-637 and miRNA-1224 inhibited keloid fibroblasts proliferation and promoted apoptosis via the transforming growth factor (TGF)-β1/Smad3 signaling pathway. miRNA-21 was also involved in mitochondrial-mediated apoptosis and miRNA-31 targeted vascular endothelial growth factor (VEGF) signaling pathway. miRNA-199a may be one key factor in the cell cycle checkpoint signal pathway of keloid-derived fibroblasts. It was also found that miRNA-29a and miRNA-196a mediated collagen metabolism. These pivotal miRNAs and regulatory processes further improve the data on the epigenetic mechanisms of keloids and provide hope for the use of small molecules in the treatment of keloids.

Chaosen Yue,1 Yaoyao Ren,2 Hua Ge,1 Chaojie Liang,1 Yingchen Xu,1 Guangming Li,1 Jixiang Wu1 1Department of General Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, People’s Republic of China; 2Department of Anesthesiology, Beijing Tongren Hospital, Capital Medical University, Beijing, People’s Republic of China Background: Hepatocellular carcinoma (HCC) is an extremely common malignant tumor with worldwide prevalence. The aim of this study was to identify potential prognostic genes and construct a competing endogenous RNA (ceRNA) regulatory network to explore the mechanisms underlying the development of HCC. Methods: Integrated analysis was used to identify potential prognostic genes in HCC with R software based on the GSE14520, GSE17548, GSE19665, GSE29721, GSE60502, and the Cancer Genome Atlas databases. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway-enrichment analyses were performed to explore the molecular mechanisms of potential prognostic genes. Differentially expressed miRNAs (DEMs) and lncRNAs (DELs) were screened based on the Cancer Genome Atlas database. An lncRNA–miRNA–mRNA ceRNA regulatory network was constructed based on information about interactions derived from the miRcode, TargetScan, miRTarBase, and miRDB databases. Results: A total of 152 potential prognostic genes were screened that were differentially expressed in HCC tissue and significantly associated with overall survival of HCC patients. There were 13 key potential prognostic genes in the ceRNA regulatory network: eleven upregulated genes (CCNB1, CEP55, CHEK1, EZH2, KPNA2, LRRC1, PBK, RRM2, SLC7A11, SUCO, and ZWINT) and two downregulated genes (ACSL1 and CDC37L1) whose expression might be regulated by eight DEMs and 61 DELs. Kaplan–Meier curve analysis showed that nine DELs (AL163952.1, AL359878.1, AP002478.1, C2orf48, C10orf91, CLLU1, CLRN1-AS1, ERVMER61-1, and WARS2-IT1) in the ceRNA regulatory network were significantly associated with HCC-patient prognoses. Conclusion: This study identified potential prognostic genes and constructed an lncRNA–miRNA–mRNA ceRNA regulatory network of HCC, which not only has important clinical significance for early diagnoses but also provides effective targets for HCC treatments and could provide new insights for HCC-interventional strategies. Keywords: hepatocellular carcinoma, prognostic gene, ceRNA

Hepatocellular carcinoma (HCC) is a common and aggressive malignant neoplasm with an increasing incidence rate among cancers worldwide. This study aimed to establish a competing-endogenous RNA (ceRNA) network to further understand the ceRNA regulatory mechanism and pathogenesis in HCC. mRNA and miRNA expression data and corresponding clinical characteristics of HCC patients were downloaded from The Cancer Genome Atlas Data Portal. The different expression profiles of mRNA, lncRNA, and miRNA (referred to as DEmRNAs, DElncRNAs, and DEmiR-NAs, respectively) screened 374 HCC tumor tissues and 50 adjacent nontumor control tissues. The miRcode database was used to predict interactions between DElncRNAs and DEmiRNAs. The miRTarBase, miRDB, and TargetScan databases were used to retrieve miRNA-targeted mRNAs. The lncRNA-miRNA-mRNA ceRNA network was constructed based on matched DElncRNA-DEmiRNA and DEmiRNA-DEmRNA pairs. Functional enrichment analysis revealed the biological processes and pathways of DEmRNAs involved in the development of HCC. Key differentially expressed RNAs in the ceRNA network were further analyzed for their relationships with overall survival in HCC patients. A total of 1,982 mRNAs, 1,081 lncRNAs, and 126 miRNAs were identified as differentially expressed. The ceRNA network was constructed including 74 DElncRNAs, 35 DEmRNAs, and 16 DEmiRNAs. 13 DElncRNAs and 19 DEmRNAs were identified as prognosis-related biomarkers. Twenty-five Gene Ontology terms and 8 Kyoto Encyclopedia of Genes and Genomes pathways were found to be significantly enriched by DEmRNAs in the ceRNA network. Our results demonstrated tumor-specific mRNA, lncRNA, and miRNA expression patterns and enabled us to construct a ceRNA network that provided new insights into the molecular mechanisms of HCC. Key differentially expressed RNAs associated with total survival were also identified as promising biomarkers for survival prediction.

Yahui Jiang,&ast; Yiwen Shi,&ast; Tianjiao Lyu, Hua Liu, Lifei Shen, Tianyu Zhou, Weiwei Feng Department of Gynecology and Obstetrics, Ruijin Hospital, Shanghai Jiaotong University, School of Medicine, Shanghai, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Weiwei FengDepartment of Gynecology and Obstetrics, Ruijin Hospital, Shanghai Jiaotong University, School of Medicine, Shanghai, 200025, People’s Republic of ChinaTel/Fax +86-21-64370045Email fww12066@rjh.com.cnPurpose: Ovarian cancer, manifested by malignant ascites, is the most lethal gynaecological cancer. Suspended ascites-derived spheroids may contribute to ovarian cancer metastasis. MicroRNAs (miRNAs) are also associated with ovarian cancer metastasis. Here, we aimed to investigate the differentially expressed miRNAs (DE-miRNAs) in ascites-derived spheroids compared with primary tumour tissues, which may regulate ovarian cancer metastasis.Methods: The DE-miRNAs between ovarian cancer primary tumour tissues and ascites-derived spheroids were identified by GEO2R screening in samples from 3 high-grade serous ovarian cancer (HGSOC) patients of dataset GSE65819. We used MiRTarBase, TargetScanHuman7.2 and STRING to predict the target hub genes of DE-miRNAs and DAVID to perform functional analysis of hub genes. ALGGEN PROMO and TransmiR v2.0 were used to predict transcription factors (TFs) that potentially regulate DE-miRNAs expression. The observed differences in DE-miRNAs expression were validated with samples from 12 HGSOC patients and 2 ovarian cancer cell lines using PCR. The functions of DE-miRNAs on ovarian cancer progression were verified by invasion, adherent, and angiogenesis assays.Results: Through bioinformatics screening and experimental validation, miR-199a-3p, miR-199b-3p, miR-199a-5p, miR-126-3p and miR-145-5p were identified as being significantly downregulated in ascites-derived spheroids compared with primary tumour tissues. In addition, TFAP2A was identified as a potentially common upstream TF regulating the expression of the above mentioned DE-miRNAs. The overexpression of miR-199a-3p, miR-199b-3p, miR-199a-5p lead to invasion inhibition, and the overexpression of miR-126-3p, miR-145-5p, miR-199a-5p and miR-199b-3p lead to adhesion inhibition of suspended ovarian cancer cells. High-expressed miR-126-3p, miR-199a-3p, miR-199a-5p and miR-199b-3p contributed to apoptosis of suspended ovarian cancer cells.Conclusion: The downregulated expression of miR-199a-3p, miR-199b-3p, miR-199a-5p, miR-126-3p and miR-145-5p in ascites-derived spheroids plays a key role in promoting ovarian cancer progression, which may represent novel molecules for targeted therapy for ovarian cancer.Keywords: ovarian cancer, metastasis, ascites-derived spheroids, primary tumour tissue, microRNAs

Background Thoracic aortic aneurysm (TAA) is a potentially life-threatening disease for which few medical therapies are available. Thus, it is critically important to investigate the underlying molecular mechanisms of TAA, and identify potential targets for TAA treatment. Methods Differentially expressed miRNAs (DEMs) and differentially expressed genes (DEGs) were screened, and a weighted correlation network analysis (WGCNA) was employed to construct a weighted miRNA co-expression network using GSE110527. The DEMs were then mapped into the whole co-expression network of all samples, and a DEM coexpression network was created. Molecular Complex Detection (MCODE) was used to identify crucial miRNAs. Target genes were predicted using the miRTarbase database, and further screened by identifying genes that overlapped with the DEGs of GSE26155. The screened target genes were validated using GSE9106, and the successfully validated genes were considered as crucial genes. Finally, a miRNA risk score for diagnosing TAA was calculated by undertaking a least absolute shrinkage and selection operator (LASSO) regression. Results The tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) signaling pathway was found in DEM functional enrichment. Crucial miRNAs were identified and target genes were predicted and associated with the regulation of the TRAIL signaling pathway. Next, 113 important target genes were identified as overlapping with the DEGs of GSE26155. These genes were further validated, and 5 successfully validated genes were considered as crucial genes. Finally, the miRNA risk score calculated by the LASSO regression was shown to have potential diagnostic value. Conclusions We performed a WGCNA analysis to construct a weighted miRNA co-expression network, predicted target genes of crucial miRNAs, identified crucial genes, and finally calculated a miRNA risk score. The results showed that pathways and genes associated with apoptosis appear to play an important role in TAA pathogenesis, and that medications targeting apoptosis might slow TAA progression. Future in vitro and in vivo experimental studies need to be undertaken to further validate our findings and investigate the mechanistic details of these crucial miRNAs and crucial genes.

Background: Hypertrophic cardiomyopathy (HCM) is a myocardial disease with unidentified pathogenesis. Increasing evidence indicated the potential role of microRNA (miRNA)-mRNA regulatory network in disease development. This study aimed to explore the miRNA-mRNA axis in HCM.Methods: The miRNA and mRNA expression profiles obtained from the Gene Expression Omnibus (GEO) database were used to identify differentially expressed miRNAs (DEMs) and genes (DEGs) between HCM and normal samples. Target genes of DEMs were determined by miRTarBase. Gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to identify biological functions of the DEGs and DEMs. miRNA-mRNA regulatory network was constructed to identify the hub genes and miRNAs. Logistic regression model for HCM prediction was established basing on the network.Results: A total of 224 upregulated and 366 downregulated DEGs and 10 upregulated and 14 downregulated DEMs were determined. We identified 384 DEM-targeted genes, and 20 of them were overlapped with the DEGs. The enriched functions include extracellular structure organization, organ growth, and phagosome and melanoma pathways. The four miRNAs and three mRNAs, including hsa-miR-373, hsa-miR-371-3p, hsa-miR-34b, hsa-miR-452, ARHGDIA, SEC61A1, and MYC, were identified through miRNA-mRNA regulatory network to construct the logistic regression model. The area under curve (AUC) values over 0.9 suggested the good performance of the model.Conclusion: The potential miRNA-mRNA regulatory network and established logistic regression model in our study may provide promising diagnostic methods for HCM.