CircRNA expression profiles and regulatory networks in the vitreous humor of people with high myopia.

Myopia is a global health and economic issue. Circular RNAs (circRNAs) have been shown to play an important role in the pathogenesis of many ocular diseases. We first evaluated the circRNA profiles and possible roles in vitreous humor samples of individuals with high myopia by a competitive endogenous RNA (ceRNA) array. Vitreous humor samples were collected from 15 high myopic (5 for ceRNA array, and 10 for qPCR) and 15 control eyes (5 for ceRNA array, and 10 for qPCR) with idiopathic epiretinal membrane (ERM) and macular hole (MH). 486 circRNAs (339 upregulated and 147 downregulated) and 264 mRNAs (202 upregulated and 62 downregulated) were differentially expressed between the high myopia and control groups. The expression of hsa_circ_0033079 (hsa-circDicer1), hsa_circ_0029989 (hsa-circNbea), hsa_circ_0019072 (hsa-circPank1) and hsa_circ_0089716 (hsa-circEhmt1) were validated by qPCR. Pearson analysis and multivariate regression analysis showed positive and significant correlations for axial length with hsa-circNbea and hsa-circPank1. KEGG analysis showed that the target genes of circRNAs were enriched in the mTOR, insulin, cAMP, and VEGF signaling pathways. GO analysis indicated that circRNAs mainly targeted transcription, cytoplasm, and protein binding. CircRNA-associated ceRNA network analysis and PPI network analysis identified several critical genes for myopia. The expression of circNbea, circPank1, miR-145-5p, miR-204-5p, Nras, Itpr1 were validated by qPCR in the sclera of form-deprivation myopia (FDM) mice model. CircPank1/miR-145-5p/NRAS and circNbea/miR-204-5p/ITPR1 were identified and may be important in the progression of myopia. Our findings suggest that circRNAs may contribute to the pathogenesis of myopia and may serve as potential biomarkers.

Constructed the ceRNA network and predicted a FEZF1-AS1/miR-92b-3p/ZIC5 axis in colon cancer.

The purpose of this study was to identify the role of FEZF1-AS1 in colon cancer and predicted the underlying mechanism. We extracted sequencing data of colon cancer patients from The Cancer Genome Atlas database, identified the differential expression of long noncoding RNA, microRNA, and messenger RNA, constructed a competitive endogenous RNA network, and then analyzed prognosis. Then, we used the enrichment analysis databases for functional analysis. Finally, we studied the FEZF1-AS1/miR-92b-3p/ZIC5 axis. We detected the expression of FEZF1-AS1, miR-92b-3p, and ZIC5 via quantitative reverse transcription-PCR, transfected colon cancer cell RKO with lentivirus and conducted FEZF1-AS1 knockdown, and performed cancer-related functional assays. It indicated that many RNA in the competitive endogenous RNA network, such as ZIC5, were predicted to be related to overall survival of colon cancer patients, and enrichment analysis showed cancer-related signaling pathways, such as PI3K/AKT signaling pathway. The expression of FEZF1-AS1 and ZIC5 was significantly higher and that of miR-92b-3p was lower in the colon cancer than in the normal colon tissues. FEZF1-AS1 promoted the migration, proliferation, as well as invasion of RKO. According to the prediction, FEZF1-AS1 and ZIC5 might competitively bind to miR-92b-3p, leading to the weakening of the inhibitory impact of miR-92b-3p on ZIC5 and increasing expression of ZIC5, thus further activating the PI3K/AKT signaling pathway, which led to the occurrence and development of colon cancer. The study suggested that FEZF1-AS1 might be an effective diagnosis biomarker for colon cancer.

Role of ceRNA network in inflammatory cells of rheumatoid arthritis. / CeRNAç½‘ç»œåœ¨ç±»é£Žæ¹¿å ³èŠ‚ç‚Žçš„ç‚Žç—‡ç»†èƒžä¸­çš„ä½œç”¨.

Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease caused by inflammatory cells. Various inflammatory cells involved in RA include fibroblast-like synoviocytes, macrophages, CD4+T-lymphocytes, B lymphocytes, osteoclasts and chondrocytes. The close interaction between various inflammatory cells leads to imbalance of immune response and disorder of the expression of mRNA in inflammatory cells. It helps to drive production of pro-inflammatory cytokines and stimulate specific antigen-specific T- and B-lymphocytes to produce autoantibodies which is an important pathogenic factor for RA. Competing endogenous RNA (ceRNA) can regulate the expression of mRNA by competitively binding to miRNA. The related ceRNA network is a new regulatory mechanism for RNA interaction. It has been found to be involved in the regulation of abnormal biological processes such as proliferation, apoptosis, invasion and release of inflammatory factors of RA inflammatory cells. Understanding the ceRNA network in 6 kinds of RA common inflammatory cells provides a new idea for further elucidating the pathogenesis of RA, and provides a theoretical basis for the discovery of new biomarkers and effective therapeutic targets.

The landscape of the long non-coding RNAs and circular RNAs of the abdominal fat tissues in the chicken lines divergently selected for fatness.

BACKGROUND: Excessive deposition of abdominal fat poses serious problems in broilers owing to rapid growth. Recently, the evolution of the existing knowledge on long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) have established their indispensable roles in multiple physiological metabolic processes, including adipogenesis and fat deposition. However, not much has been explored on their profiles in the abdominal fat tissues of broilers to date. In the study, we aimed to characterize the vital candidates of lncRNAs and circRNAs and their underlying regulations for abdominal fat deposition in broilers. RESULTS: The present study sequenced the lncRNAs and circRNAs expression profiles in the abdominal fat tissues isolated from 7-week-old broilers, who were divergently selected for their fatness. It identified a total of 3359 lncRNAs and 176 circRNAs, demonstrating differential expressed (DE) 30 lncRNAs and 17 circRNAs between the fat- and lean-line broilers (|log2FC| ≥ 1, P < 0.05). Subsequently, the 20 cis-targets and 48 trans-targets of the candidate DE lncRNAs were identified for depositing abdominal fat by adjacent gene analysis and co-expression analysis, respectively. In addition, the functional enrichment analysis showed the DE lncRNAs targets and DE circRNAs host genes to be mainly involved in the cellular processes, amino/fatty acid metabolism, and immune inflammation-related pathways and GO terms. Finally, the vital 16 DE lncRNAs located in cytoplasm and specifically expressed in fat/lean line and their targets were used to construct the lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) regulatory network, comprising 7 DE lncRNAs, 28 miRNAs, 11 DE mRNAs. Notably, three lncRNAs including XR_001468036.2, XR_003077610.1 and XR_001466431.2 with the most connected degrees might play hub regulatory roles in abdominal fat deposition of broilers. CONCLUSIONS: This study characterized the whole expression difference of lncRNAs and circRNAs between the two lines broilers with divergently ability of abdominal fat. The vital candidate DE lncRNAs/circRNAs and ceRNA regulations were identified related to the deposition of abdominal fat in chicken. These results might further improve our understanding of regulating the non-coding RNAs in obesity.

Pyroptosis-related prognosis model, immunocyte infiltration characterization, and competing endogenous RNA network of glioblastoma.

BACKGROUND: Glioblastoma (GBM) has a high incidence rate, invasive growth, and easy recurrence, and the current therapeutic effect is less than satisfying. Pyroptosis plays an important role in morbidity and progress of GBM. Meanwhile, the tumor microenvironment (TME) is involved in the progress and treatment tolerance of GBM. In the present study, we analyzed prognosis model, immunocyte infiltration characterization, and competing endogenous RNA (ceRNA) network of GBM on the basis of pyroptosis-related genes (PRGs). METHODS: The transcriptome and clinical data of 155 patients with GBM and 120 normal subjects were obtained from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx). Lasso (Least absolute shrinkage and selection operator) Cox expression analysis was used in predicting prognostic markers, and its predictive ability was tested using a nomogram. A prognostic risk score formula was constructed, and CIBERSORT, ssGSEA algorithm, Tumor IMmune Estimation Resource (TIMER), and TISIDB database were used in evaluating the immunocyte infiltration characterization and tumor immune response of differential risk samples. A ceRNA network was constructed with Starbase, mirtarbase, and lncbase, and the mechanism of this regulatory axis was explored using Gene Set Enrichment Analysis (GSEA). RESULTS: Five PRGs (CASP3, NLRP2, TP63, GZMB, and CASP9) were identified as the independent prognostic biomarkers of GBM. Prognostic risk score formula analysis showed that the low-risk group had obvious survival advantage compared with the high-risk group, and significant differences in immunocyte infiltration and immune related function score were found. In addition, a ceRNA network of messenger RNA (CASP3, TP63)-microRNA (hsa-miR-519c-5p)-long noncoding RNA (GABPB1-AS1) was established. GSEA analysis showed that the regulatory axis played a considerable role in the extracellular matrix (ECM) and immune inflammatory response. CONCLUSIONS: Pyroptosis and TME-related independent prognostic markers were screened in this study, and a prognosis risk score formula was established for the first time according to the prognosis PRGs. TME immunocyte infiltration characterization and immune response were assessed using ssGSEA, CIBERSORT algorithm, TIMER, and TISIDB database. Besides a ceRNA network was built up. This study not only laid foundations for further exploring pyroptosis and TME in improving prognosis of GBM, but also provided a new idea for more effective guidance on clinical immunotherapy to patients and developing new immunotherapeutic drugs.

Identification of the potential biological target molecules related to primary open-angle glaucoma.

BACKGROUND: To identify the potential biological target molecules and the corresponding interaction networks in primary open-angle glaucoma (POAG) development. METHODS: The microarray datasets of GSE138125 and GSE27276 concerning lncRNA and mRNA expression profiles in trabecular meshwork of POAG were downloaded from the Gene Expression Omnibus database. The R software was applied to identify differentially expressed (DE) lncRNAs and mRNAs in POAG, and to perform GO and KEGG functional enrichment analysis. Protein-protein interaction (PPI) network and module analysis, and lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network were performed by Cytoscape software. RESULTS: A total of 567 DE-mRNAs were identified from GSE138125 and GSE27276, including 298 up-regulated and 269 down-regulated mRNAs, which were found enriching in biological processes of extracellular matrix organization and epidermis development, respectively. KEGG pathway enrichment analysis further revealed that module genes in PPI network were primarily involved in the AGE-PAGE, PI3K-Akt and TGF-ß signaling pathways. Moreover, 897 up-regulated and 1036 down-regulated DE-lncRNAs were identified from GSE138125. Through literature review and databases searching, we obtained 712 lncRNA-miRNA and 337 miRNA-mRNA pairs based on the selected eight POAG-related miRNAs. After excluding 702 lncRNAs and 284 mRNAs that were not comprised in the DE-lncRNA and DE-mRNAs, a total of 53 lncRNA nodes, eight miRNA nodes, 10 mRNA nodes, and 78 edges were included in the final ceRNA network. CONCLUSIONS: This study demonstrated the lncRNA and mRNA expression profiles of trabecular meshwork in POAG patients and the normal controls, and identified potentially ceRNAs and pathways which might improve the pathogenic understanding of this ocular disease.

Mitochondrial Aldehyde Dehydrogenase 2 Represents a Potential Biomarker of Biochemical Recurrence in Prostate Cancer Patients.

BACKGROUND: We aimed to explore the role of mitochondrial aldehyde dehydrogenase 2 (ALDH2) in prostate cancer (PCa) patients and provide insights into the tumor immune microenvironment (TME) for those patients undergoing radical radiotherapy. METHODS: We performed all analyses using R version 3.6.3 and its suitable packages. Cytoscape 3.8.2 was used to establish network of competing endogenous RNAs (ceRNAs). RESULTS: Downregulation of ADLH2 was significantly associated with higher risk of BCR-free survival (HR: 0.40, 95%CI: 0.24-0.68, p = 0.001) and metastasis-free survival (HR: 0.21, 95%CI: 0.09-0.49, p = 0.002). Additionally, ALDH2 repression contributed to significantly shorter BCR-free survival in the TCGA database (HR: 0.55, 95%CI: 0.33-0.93, p = 0.027). For immune checkpoints, patients that expressed a higher level of CD96 had a higher risk of BCR than their counterparts (HR: 1.79, 95%CI: 1.06-3.03, p = 0.032), as well as NRP1 (HR: 2.18, 95%CI: 1.29-3.69, p = 0.005). In terms of the TME parameters, the spearman analysis showed that ALDH was positively associated with B cells (r: 0.13), CD8+ T cells (r: 0.19), neutrophils (r: 0.13), and macrophages (r: 0.17). Patients with higher score of neutrophils (HR: 1.75, 95%CI: 1.03-2.95, p = 0.038), immune score (HR: 1.92, 95%CI: 1.14-3.25, p = 0.017), stromal score (HR: 2.52, 95%CI: 1.49-4.26, p = 0.001), and estimate score (HR: 1.81, 95%CI: 1.07-3.06, p = 0.028) had higher risk of BCR than their counterparts. Our ceRNA network found that PART1 might regulate the expression of ALDH via has-miR-578 and has-miR-6833-3p. Besides, PHA-793887, PI-103, and piperlongumine had better correlations with ALDH2. CONCLUSIONS: We found that ALDH2 might serve as a potential biomarker predicting biochemical recurrence for PCa patients.

AC016405.3 functions as an oncogenic long non-coding RNA by regulating ERBB3 via sponging miR-22-3p in breast cancer.

BACKGROUND: Increasing studies reported that long non-coding RNAs are involved in regulating breast cancer (BRCA) progression. However, the specific roles and mechanisms of lncRNAs in BRCA remain largely unknown. Here, we sought to explore the functions and mechanisms of AC016405.3 in BRCA progression. METHODS: Bioinformatic analysis for AC016405.3, miR-22-3p, and ERBB3 were performed on starBase. The expressions of AC016405.3, miR-22-3p, and ERBB3 were examined by RT-qPCR. The functions of AC016405.3 on the proliferation, migration, and invasion of cells were evaluated by conducting CCK-8, colony formation, wound-healing, and Transwell assays. The subcellular distribution of AC016405.3 in BRCA cells was identified by performing fluorescence in situ hybridization (FISH) and subcellular fractionation techniques. Dual-luciferase assay was applied to validate the interactions of miR-22-3p with AC016405.3 or ERBB3. The interaction between ERBB3 and miR-22-3p was also tested by Anti-Ago2 RNA immunoprecipitation (RIP) assay. RESULTS: The results showed that AC016405.3 is highly expressed in BRCA tissues as well as cells and positively correlated with poor prognosis in BRCA patients. Silencing AC016405.3 obviously repressed the malignant behaviors of BRCA cells. Mechanistically, AC016405.3 functioned as a competing endogenous RNA (ceRNA) for miR-22-3p in the cytoplasm and sponged miR-22-3p to release its suppression of ERBB3. Rescue experiments revealed that the suppression role induced by AC016405.3 depletion on malignant behaviors of BRCA cells could be obviously counter by inhibiting miR-22-3p or overexpressing ERBB3. CONCLUSION: AC016405.3 promotes BRCA progression by the derepression of ERBB3 via sponging miR-22-3p, which may represent a potential target for BRCA treatment.

Identification of circRNA-miRNA-mRNA Regulatory Network in Bladder Cancer by Integrated Analysis.

INTRODUCTION: Bladder cancer (BC) is a common malignant tumor in the urinary system with high mortality and recurrence rates. This study sought to identify crucial circular RNAs (circRNAs) associated with BC. METHODS: The mRNA, miRNA, and circRNA expression profiles of BC were downloaded from GEO database. The differentially expressed mRNAs (DEmRNAs), miRNAs (DEmiRNAs), and circRNAs (DEcircRNAs) were identified using bioinformatics method. Combining circRNA-miRNA pairs with miRNA-mRNA pairs, the competing endogenous RNA (ceRNA; DEcircRNA-DEmi-RNA-DEmRNA) regulatory network was constructed. Functional annotation of host gene of DEcircRNAs and DEmRNAs in ceRNA regulatory network were performed. qRT-PCR validation was performed. RESULTS: A total of 4,003 DEmRNAs, 25 DEmiRNAs, and 119 DEcircRNAs were obtained. The ceRNA network contained 18 circRNA-miRNA pairs and 699 mi-RNA-mRNA pairs, including 17 circRNAs, 4 miRNAs, and 624 mRNAs. Functional annotation of DEmRNAs in ceRNA regulatory network revealed that these DEmRNAs were significantly enriched in glycerolipid metabolism, p53 signaling pathway, and oocyte meiosis. Except for hsa_circ_0028173, expression of the others in the qRT-PCR results was consistent with that in our integrated analysis, generally. CONCLUSION: We speculate that hsa_circ_0008035/hsa-miR-107/MSRB3 and hsa_circ_0028173/hsa-miR-338-3p/TPX2/GATA3 interaction pairs may play a vital role in BC.

Potential Regulatory Role of lncRNA-miRNA-mRNA in Coronary Artery Disease (CAD).

Coronary artery disease (CAD) is a high-incidence of heart disease. We aimed to identify potential biomarkers linked to the progression of CAD using multiple sets of data mining analysis methods. The long noncoding RNA (lncRNA) + messenger RNA (mRNA) data set GSE113079 and microRNA (miRNA) data set GSE28858 were downloaded from Gene Expression Omnibus. After data preprocessing, differentially expressed mRNA, lncRNA, and miRNA were identified using limma software. In addition, weighted gene co-expression network analysis (WGCNA) was used for the construction and screening of modules related to disease states. Besides, key mRNAs and lncRNAs were extracted for protein-protein interaction (PPI) network construction and lncRNA-mRNA co-expression analysis. Additionally, the final integration resulted in the lncRNA-miRNA-mRNA relationship pairs (competing endogenous RNA (ceRNA) network). Finally, CTD 2020 update database was used for the verification of the expression level of the candidate genes. A total of 1319 differentially expressed mRNAs and 1983 lncRNAs were screened. After WGCNA, a total of 234 mRNAs and 546 lncRNAs were identified. A PPI network including 127 mRNA corresponding proteins was constructed. The ceRNA network included 24 up-regulated lncRNAs, 16 down-regulated miRNAs, and 42 up-regulated mRNAs. Through the validation of CTD 2020 update database, 21 CAD related mRNAs, and four important ceRNAs those may be participated in the pathogenesis of CAD were obtained. In this study, through multiple sets of data mining methods, the regulatory relationship of lncRNA, miRNA, and mRNA was comprehensively analyzed, and the important role of lncRNA-miRNA-mRNA in the pathogenesis of CAD was emphasized.

Identifying prognostic biomarkers in endometrial carcinoma based on ceRNA network.

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 < .05 were obtained. Notably, based on this network, it was found that LINC00261-hsa-mir-31 pair and LINC00261-hsa-mir-211 target pairs could be used as the potential prognostic markers of EC. CONCLUSION: This research recommended an available basis for the molecular mechanism of EC and prognosis prediction, which could help guide the subsequent treatments and predict the prognosis for patients with EC.

Comprehensive analysis of differential immunocyte infiltration and the potential ceRNA networks during epicardial adipose tissue development in congenital heart disease.

BACKGROUND: To detect the development, function and therapeutic potential of epicardial adipose tissue (EAT); analyze a related gene expression dataset, including data from neonates, infants, and children with congenital heart disease (CHD); compare the data to identify the codifferentially expressed (DE) mRNAs and lncRNAs and the corresponding miRNAs; generate a potential competitive endogenous RNA (ceRNA) network; and assess the involvement of immunocyte infiltration in the development of the EAT. METHODS: Multiple algorithms for linear models for microarray data algorithms (LIMMA), CIBERSORT, gene-set enrichment analysis (GSEA), and gene set variation analysis (GSVA) were used. The miRcode, miRDB, miRTarBase, and TargetScan database were used to construct the ceRNA network. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the DE mRNAs were performed. RESULTS: Thirteen co-DE mRNAs and 47 co-DE lncRNAs were subsequently identified. The related categories included negative regulation of myoblast differentiation, regulation of ion transmembrane transport, and heart development, which were primarily identified for further pathway enrichment analysis. Additionally, the hub ceRNA network in EAT development involving MIR210HG, hsa-miR-449c-5p, and CACNA2D4 was generated and shown to target monocyte infiltration. CONCLUSION: These findings suggest that the pathways of myoblast differentiation and ion transmembrane transport may be potential hub pathways involved in EAT development in CHD patients. In addition, the network includes monocytes, MIR210HG, and CACNA2D4, which were shown to target the RIG-I-like receptor signaling pathway and PPAR signaling pathway, indicating that these factors may be novel regulators and therapeutic targets in EAT development.

Identification of a competing endogenous RNA network associated with prognosis of pancreatic adenocarcinoma.

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.

Identification of prognostic factors for intrahepatic cholangiocarcinoma using long non-coding RNAs-associated ceRNA network.

BACKGROUND: Accumulating amount of evidence has highlighted the important roles of long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) in tumor pathogenesis. However, the roles of long non coding RNAs (lncRNAs) in the lncRNA-related ceRNA network of intrahepatic cholangiocarcinoma (ICC) still remain enigmatic. The current study aims to identify prognostic factors in the lncRNA-related ceRNA network of ICC. METHODS: The transcriptome sequencing data of lncRNAs, messenger RNA (mRNA) and microRNA (miR) were downloaded from the SRA and TCGA databases. Differentially expressed lncRNAs (DElncRNAs), DEmiRs and DEmRNAs were identified and adopted to construct an lncRNA-miR-mRNA ceRNA network. ICC-associated DEmRNAs were adopted to construct the protein-protein interaction (PPI) network. The expression of the top 6 genes in the hub module was validated with mRNA transcriptome sequencing data and ICC-related gene expression dataset GSE45001, followed by GO and KEGG pathway enrichment analysis. The relationship between the hub gene-associated ceRNA network and the overall survival of patients with ICC was predicted by conducting a Kaplan-Meier survival analysis. RESULTS: Sixty co-expressed DEmRNAs were identified in the ceRNA network. The top 6 hub genes consisted of downregulated FOS, IGF2, FOXO1 and NTF3, upregulated IGF1R, and insignificantly downregulated HGF in ICC tissues, when compared to that of normal adjacent tissues, followed by the successful construction of lncRNA-miR-hub network consisting of 86 ceRNA modules. MME-AS1 and hsa-miR-182 were associated with overall survival in ICC patients. FOS, IGF1R, IGF2, FOXO1, and NTF3 might target "TGF-ß signaling pathway", "the hedgehog signaling pathway", "retinol metabolism", or "type II diabetes mellitus" pathways respectively. CONCLUSION: These results indicate that FOS, IGF1R, IGF2, FOXO1, and NTF3 were useful prognostic factors in determining the prognosis of patients with ICC.

Construction of asthma related competing endogenous RNA network revealed novel long non-coding RNAs and potential new drugs.

BACKGROUND: Asthma is a heterogeneous disease characterized by chronic airway inflammation. Long non-coding RNA can act as competing endogenous RNA to mRNA, and play significant role in many diseases. However, there is little known about the profiles of long non-coding RNA and the long non-coding RNA related competing endogenous RNA network in asthma. In current study, we aimed to explore the long non-coding RNA-microRNA-mRNA competing endogenous RNA network in asthma and their potential implications for therapy and prognosis. METHODS: Asthma-related gene expression profiles were downloaded from the Gene Expression Omnibus database, re-annotated with these genes and identified for asthma-associated differentially expressed mRNAs and long non-coding RNAs. The long non-coding RNA-miRNA interaction data and mRNA-miRNA interaction data were downloaded using the starBase database to construct a long non-coding RNA-miRNA-mRNA global competing endogenous RNA network and extract asthma-related differentially expressed competing endogenous RNA network. Finally, functional enrichment analysis and drug repositioning of asthma-associated differentially expressed competing endogenous RNA networks were performed to further identify key long non-coding RNAs and potential therapeutics associated with asthma. RESULTS: This study constructed an asthma-associated competing endogenous RNA network, determined 5 key long non-coding RNAs (MALAT1, MIR17HG, CASC2, MAGI2-AS3, DAPK1-IT1) and identified 8 potential new drugs (Tamoxifen, Ruxolitinib, Tretinoin, Quercetin, Dasatinib, Levocarnitine, Niflumic Acid, Glyburide). CONCLUSIONS: The results suggested that long non-coding RNA played an important role in asthma, and these novel long non-coding RNAs could be potential therapeutic target and prognostic biomarkers. At the same time, potential new drugs for asthma treatment have been discovered through drug repositioning techniques, providing a new direction for the treatment of asthma.

Long noncoding RNA HOXA-AS2 regulates the expression of SCN3A by sponging miR-106a in breast cancer.

Breast cancer is the most commonly diagnosed cancer that affects women worldwide. This study aimed to investigate the competing endogenous RNAs (ceRNAs) mechanism in breast cancer. Microarray data were downloaded from the University of California Santa Cruz (UCSC) Xena database. The limma package was used to screen the differentially expressed messenger RNAs (DEMs) and differentially expressed long noncoding RNAs (DELs). Subsequently, functional analysis was performed using DAVID tool. After constructing the protein-protein interaction (PPI) network, we identified the major gene modules using the Cytoscape software. Univariate survival analysis in the survival package was performed. Finally, the ceRNA regulatory network was constructed to identify the critical genes. A total of 1380 DEMs and 345 DELs were identified in breast cancer samples compared with normal samples. Functional enrichment analysis showed that DEMs were mainly involved in cell division, and cell cycle. We screened four major gene modules and identified the hub nodes in these functional modules. Several DEMs (including FABP7, C4BPA, and LAMB3) and three long noncoding RNAs (lncRNAs) (LINC00092, SLC26A4.AS1, and COLCA1) exhibited significant correlation with patients' survival outcomes. In the ceRNA network, the lncRNA HOXA-AS2 regulated the expression level of SCN3A by interacting with hsa-miR-106a-5p. Thus, our study investigated the ceRNA mechanism in breast cancer. The results showed that lncRNA HOXA-AS2 might modulate the expression of SCN3A by sponging miR-106a in breast cancer.

Competing endogenous RNA network of endometrial carcinoma: A comprehensive analysis.

Competing endogenous RNA (ceRNA) network is dysregulated in the initiation and progression of tumors. In the present study, we explored the regulatory mechanism of ceRNA in endometrial carcinoma (EC) and the potential key molecules with potential value in the diagnosis, treatment, and prognosis of EC. The long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) expression profiles (552 EC tissues and 35 nontumor tissues) and microRNAs (miRNAs) expression profiles (546 EC tissues and 33 nontumor tissues) were downloaded from The Cancer Genome Atlas database to identify differentially expressed RNAs (DERNAs) in EC. An integrated bioinformatics analysis was used to construct an EC-specific ceRNA network and select key molecules. As a result, 96 differentially expressed lncRNAs (DElncRNAs), 29 differentially expressed miRNAs (DEmiRNAs), and 77 differentially expressed mRNAs (DEmRNAs) were identified. An EC-specific ceRNA network was built based on nine DElncRNAs significantly associated with overall survival. CCNB1 was found as a key gene in EC through the weighted gene coexpression network analysis and protein-protein interaction network analysis. Our ceRNA network showed C2orf48 and LINC00483 might upregulate CCNB1 via competing with miR-183. In addition, we found a subnetwork which contained survival-associated DERNAs (AC110491.1, LINC00483-miR-192-GRHL1). The results of reverse transcription quantitative polymerase chain reaction supported the relative expressions of C2orf48, LINC00483 were upregulated and that of AC110491.1 was downregulated in EC. We further found C2orf48 was upregulated in serous EC, endometrioid EC, and mixed serous and endometrioid EC. LINC00483 was upregulated in mixed serous and endometrioid EC compared with that in the normal tissues according to UALCAN database. In addition, candidate small molecular drugs were screened out by ConnectivityMap based on the 77 DEmRNAs in the ceRNA network. Eventually, C2orf48, LINC00483, and AC110491.1 were identified as three key lncRNAs in EC.

An eight-lncRNA signature predicts survival of breast cancer patients: a comprehensive study based on weighted gene co-expression network analysis and competing endogenous RNA network.

PURPOSE: To identify a lncRNA signature to predict survival of breast cancer (BRCA) patients. METHODS: A total of 1222 BRCA case and control datasets were downloaded from the TCGA database. The weighted gene co-expression network analysis of differentially expressed mRNAs was performed to generate the modules associated with BRCA overall survival status and further construct a hub on competing endogenous RNA (ceRNA) network. LncRNA signatures for predicting survival of BRCA patients were generated using univariate survival analyses and a multivariate Cox hazard model analysis and validated and characterized for prognostic performance measured using receiver operating characteristic (ROC) curves. RESULTS: A prognostic score model of eight lncRNAs signature was identified as Prognostic score = (0.121 × EXPAC007731.1) + (0.108 × EXPAL513123.1) + (0.105 × EXPC10orf126) + (0.065 × EXPWT1-AS) + (- 0.126 × EXPADAMTS9-AS1) + (- 0.130 × EXPSRGAP3-AS2) + (0.116 × EXPTLR8-AS1) + (0.060 × EXPHOTAIR) with median score 1.088. Higher scores predicted higher risk. The lncRNAs signature was an independent prognostic factor associated with overall survival. The area under the ROC curves (AUC) of the signature was 0.979, 0.844, 0.99 and 0.997 by logistic regression, support vector machine, decision tree and random forest models, respectively, and the AUCs in predicting 1- to 10-year survival were between 0.656 and 0.748 in the test dataset from TCGA database. CONCLUSIONS: The eight-lncRNA signature could serve as an independent biomarker for prediction of overall survival of BRCA. The lncRNA-miRNA-mRNA ceRNA network is a good tool to identify lncRNAs that is correlated with overall survival of BRCA.

LncRNA H19 regulates PI3K-Akt signal pathway by functioning as a ceRNA and predicts poor prognosis in colorectal cancer: integrative analysis of dysregulated ncRNA-associated ceRNA network.

BACKGROUND: It is becoming increasingly clear that cancers can rarely be ascribed to just one or a few genomic variations. Genes generally do not function alone, but in groups that function as "networks". This study aimed to develop a competing endogenous RNA (ceRNA) network to elucidate the role of long non-coding RNA H19 in colorectal cancer. METHODS: Large-scale RNA-seq data was obtained from The Cancer Genome Atlas database. Differentially expressed RNAs were identified by bioinformatics analysis, and a competing endogenous RNA network was constructed. Functional enrichment analysis and correlation analysis between competing endogenous RNAs and clinical features were performed to reveal their roles in the tumorigenesis of colorectal cancer. To verify the conclusions derived from bioinformatics analysis, we investigated the effect of lncRNA H19 knockdown in human colorectal cancer cell lines HT-29 and HCT116. RESULTS: The present study successfully identify various cancer-specific lncRNAs and pseudogenes in CRC. The lncRNA/pseudogene-miRNA-mRNA ceRNA network was constructed using 10 lncRNAs, 5 pseudogenes, 122 mRNAs and 39 miRNAs. In the ceRNA network of CRC, H19 up-regulates various cancer-related mRNA by competitively sponging various miRNA, and participates in PI3K-Akt signaling pathway in this manner. Cox regression and correlation analysis showed that H19 and some other competing endogenous RNAs in the network are associated with poor prognosis and clinical parameters such as tumor grade and metastasis. Knockdown of H19 reduces the protein level of MET, ZEB1, and COL1A1 in vitro. CONCLUSIONS: H19 regulates PI3K-Akt signal pathway through a competing endogenous RNA network and predicts poor prognosis in colorectal cancer. The pseudogene RPLP0P2 may be an important oncogene like H19 and needs to be studied further.

A Competing Endogenous RNA Network Reveals Novel Potential lncRNA, miRNA, and mRNA Biomarkers in the Prognosis of Human Colon Adenocarcinoma.

BACKGROUND: Accumulating evidence indicated that long noncoding RNAs (lncRNAs) have a wide range of biological functions and may play significant roles in tumorigenesis and progression. However, the understanding of its functions and related competitive endogenous RNAs (ceRNAs) networks is much less than that of protein-coding genes, particularly in colon adenocarcinoma. METHODS: We comprehensively analyzed the sequencing data of protein-coding and noncoding RNAs in colon adenocarcinoma patients from The Cancer Genome Atlas (TCGA) database. Next, we constructed colon adenocarcinoma-specific ceRNA network and evaluated the effect of these RNAs on overall survival (OS) for colon adenocarcinoma patients. RESULTS: Totally, 1138 differentially expressed lncRNAs (DElncRNAs), 245 microRNAs (DEmiRNAs), and 2081 mRNAs (DEmRNAs) were identified using a threshold of |log2FoldChange| >2.0 and adjusted P-value < 0.01. Subsequently, a colon adenocarcinoma-specific ceRNA network was successfully established with133 DElncRNAs, 29 DEmiRNAs, and 55 DEmRNAs. Among ceRNA network, seven DElncRNAs (AL590483.1, AP004609.1, ARHGEF26-AS1, HOX transcript antisense RNA (HOTAIR), ITCH-IT1, KCNQ1OT1, and LINC00491), four DEmiRNAs (hsa-mir-143, hsa-mir-183, hsa-mir-216a, and hsa-mir-424), and six DEmRNAs (FJX1, TPM2, ULBP2, PDCD4, PLAU, and SERPINE1) significantly correlated with OS (all P-value < 0.05). Notably, several interactions were highlighted in the ceRNA network, such as "KCNQ1OT1-hsa-mir-183-PDCD4", "KCNQ1OT1-hsa-mir-424-TPM2", "HOTAIR-hsa-mir-143-SERPINE1", and "ARHGEF26-AS1-hsa-mir-143-SERPINE1". CONCLUSIONS: These findings reveal several molecules might be novel important prognostic factors and potential treatment targets for colon adenocarcinoma. In addition, these observations contribute to a more comprehensive understanding of lncRNA-related ceRNA network and provide novel strategies for subsequent functional studies of lncRNAs in colon adenocarcinoma.