Different expression profile of mRNA and long noncoding RNA in autoimmune thyroid diseases patients

Increasing evidence has found that long noncoding RNAs (lncRNAs) and message RNAs (mRNAs) play an important role in the progress of autoimmune thyroid diseases (AITD). So, in this study, the different expressed of lncRNA and mRNA was screened by microarray analysis and quantitative real-time polymerase chain reaction (PCR). To further investigate the relationship among the differentially expressed genes, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Gene ontology (GO) were used for biofunctions and signaling pathways analysis, respectively. Finally, the interaction relationship between lncRNA and mRNAs was analysis with lncRNA-mRNA coexpression network. The result found that the abnormal expression of lncRNAs and mRNAs were 1615 and 1913, respectively. The altered genes included CD40LG, IFNG, CTLA4, FAS, STAT1, STAT3, and STAT4. These were enriched in presentation and antigen processing, Th1 and Th2 cell differentiation, natural killer cell-mediated cytotoxicity, B cell receptor signaling pathway, Th17 cell differentiation, and cell adhesion molecules (CAMs), all of which had been suggested to be associated with immunopathogenic mechanisms and AITD-induced pathophysiologic changes. A coexpression network profile was contained with 126 network nodes and 477 connections which were based on seven mRNAs and 119 interacted lncRNAs. The outcomes of differentially expressed lncRNAs and their coreralated mRNAs in our study revealed that lncRNAs involved in immunopathogenic mechanisms may play a crital role in the pathogenesis of AITD.     

ceRNA network construction and comparison of gastric cancer with or without Helicobacter pylori infection

Gastric cancer (GC) is a lethal disease, and among its variety of etiological factors, Helicobacter pylori (H. pylori) infection is the strongest risk factor. However, the genetic and molecular mechanisms underlying H. pylori-related GC need further elucidation. We investigated the competing endogenous RNA (ceRNA) network differences between H. pylori (+) and H. pylori (−) GC. The long noncoding RNA (lncRNA), microRNA (miRNA), and messenger RNA (mRNA) expression data from 32 adjacent noncancerous samples and 18 H. pylori (+) and 141 H. pylori (−) stomach adenocarcinoma samples were downloaded from the TCGA database. After construction of lncRNA–miRNA–mRNA ceRNA networks of H. pylori (+) and H. pylori (−) GC, Panther and Kobas databases were used to analyze the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Finally, survival analysis was used to discover the key genes. In H. pylori (+) GC, we identified a total of 1,419 lncRNAs, 82 miRNAs, and 2,501 mRNAs with differentially expressed profiles. In H. pylori (−) GC, 2,225 lncRNAs, 130 miRNAs, and 3,146 mRNAs were differentially expressed. Furthermore, three unique pathways (cytokine–cytokine receptor interaction, HIF-1 signaling pathway, and Wnt signaling pathway) were enriched in H. pylori (+) GC. According to the overall survival analysis, three lncRNAs (AP002478.1, LINC00111, and LINC00313) and two mRNAs (MYB and COL1A1) functioned as prognostic biomarkers for patients with H. pylori (+) GC. In conclusion, our study has identified the differences in ceRNA regulatory networks between H. pylori (+) and H. pylori (−) GC and provides a rich candidate reservoir for future studies.     

Long noncoding RNA expression profiles during the NEL-like 1 protein–induced osteogenic differentiation

Long noncoding RNAs (lncRNAs) are important modulators of mesenchymal stem cells (MSCs) in cellular differentiation. However, the regulatory mechanisms of lncRNAs in NEL-like 1 (NELL-1)-induced osteogenic differentiation of human adipose–derived stem cells remain elusive. Expression profiles of lncRNAs and messenger RNAs during NELL-1-induced osteogenesis were obtained using high-throughput sequencing. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and gene coexpression networks were performed. We identified 323 statistically differentially expressed lncRNAs during osteogenesis and NELL-1-induced osteogenesis, and three lncRNAs (ENST00000602964, ENST00000326734, and TCONS_00006792) were identified as core regulators. Hedgehog pathway markers, including IHH and GLI1, were downregulated, while the antagonists of this pathway (GLI3 and HHIP) were upregulated during NELL-1-induced osteogenesis. In this process, the antagonist of Wnt, SFRP1, was downregulated. According to the analysis, we speculated that lncRNAs played important roles in NELL-1-induced osteogenesis via the crosstalk between Hedgehog and Wnt pathways.     

Identification of messenger and long noncoding RNAs associated with gallbladder cancer via gene expression profile analysis

The present study aimed to investigate the long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) involved in the progression of gallbladder cancer and explore the potential physiopathologic mechanisms of gallbladder cancer in terms of competing endogenous RNAs (ceRNAs). The original lncRNA and mRNA expression profile data (nine gallbladder cancer tissues samples and nine normal gallbladder samples) in GSE76633 was downloaded from the Gene Expression Omnibus database. Differentially expressed mRNAs and lncRNAs between gallbladder cancer tissue and normal control were selected and the pathways in which they are involved were analyzed using bioinformatics analyses. MicroRNAs (miRNAs) were also predicted based on the differentially expressed mRNAs. Finally, the co-expression relation between lncRNA and mRNA was analyzed and the ceRNA network was constructed by combining the lncRNA-miRNA, miRNA-mRNA, and lncRNA-mRNA pairs. Overall, 373 significantly differentially expressed mRNAs and 47 lncRNAs were identified between cancer and normal tissue samples. The upregulated genes were significantly enriched in the extracellular matrix (ECM)-receptor interaction pathway, while the downregulated genes were involved in the complement and coagulation cascades. Altogether, 128 co-expression relations between lncRNA and mRNA were obtained. In addition, 196 miRNA-mRNA regulatory relations and 145 miRNA-lncRNA relation pairs were predicted. Finally, the lncRNA-miRNA-gene ceRNA network was constructed by combining the three types of relation pairs, such as XLOC_011309-miR-548c-3p-SPOCK1 and XLOC_012588-miR-765-CEACAM6. mRNAs and lncRNAs may be involved in gallbladder cancer progression via ECM-receptor interaction pathways and the complement and coagulation cascades. Moreover, ceRNAs such as XLOC_011309-miR-548c-3p-SPOCK1 and XLOC_012588-miR-765-CEACAM6 can also be implicated in the pathogenesis of gallbladder cancer.     

mRNA/lncRNA expression patterns and the function of fibrinogen‐like protein 2 in Meishan pig endometrium during the preimplantation phases

Embryonic implantation involves a complex and well‐coordinated interaction between the developing conceptus and maternal uterus, and the preimplantation period has a major impact on litter size in pigs. The present study aimed to investigate the vital messenger RNAs (mRNAs) and long noncoding RNAs (lncRNAs) that regulate preimplantation in Meishan pigs. The enriched Gene Ontology terms were all related to “binding.” Furthermore, “ECM‐receptor interaction” was predicted as an important pathway that regulated the success of implantation. We speculated that the differentially expressed mRNAs S100A9, ANXA8, MUC16, and FGL2 and the differentially expressed lncRNAs TCONS_11206566, TCONS_09904861, and TCONS_1252933 may play vital roles in the process of implantation. Furthermore, this study verified that FGL2 was highly expressed on Day 12 of pregnancy, and we also investigated the function of FGL2 during preimplantation in vivo. In conclusion, this study provides useful information for further analyses of the molecular mechanisms of implantation in Chinese domestic pigs.     

LINC01101 and LINC00277 expression levels as novel factors in HPV‐induced cervical neoplasia

Recently long non‐coding RNAs were identified as new factors involved in gene expression regulation. To gain insight into expression pattern of these factors related to E7 HPV18 oncogene, this study uses HeLa cell culture transfected with E7‐siRNA. Gene expression profile was investigated using microarray analysis. After analysing the microarray results, we identified 15,387 RNA species differentially expressed in E7‐siRNA‐transfected cells compared with controls (fold change >2). The expression profiles of lncRNA species highlighted 731 lncRNAs and 203 lincRNAs. We selected two lincRNAs (LINC01101 and LINC00277) and we evaluated the expression profile in HPV‐induced neoplasia. Both lincRNAs investigated display a significantly reduced pattern of expression in cervical lesions and cancer, associated with clinical parameters. A connection between HPV presence and lincRNAs was noted. hrHPV‐positive samples exhibit significantly reduced LINC01101 and LINC00277 expression level (P < 0.05). These results provide new insights into involvement of lncRNA in HPV‐induced cervical cancer, enriching our understanding of their potential role in this pathology.     

Identification of immune-related lncRNAs to improve the prognosis prediction for patients with papillary thyroid cancer

Objective: To identify immune-related long non-coding RNAs (lncRNAs) in papillary thyroid cancer (PTC).Methods: The Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases were used to obtain the gene expression profile. Immune-related lncRNAs were screened from the Molecular Signatures Database v4.0 (MsigDB). We performed a survival analysis of critical lncRNAs. Further, the function of prognostic lncRNAs was inferred using the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) to clarify the possible mechanisms underlying their predictive ability. The assessment was performed in clinical samples and PTC cells.Results: We obtained 4 immune-related lncRNAs, 15 microRNAs (miRNAs), and 375 mRNAs as the key mediators in the pathophysiological processes of PTC from the GEO database. Further, Lasso regression analysis identified seven prognostic markers (LINC02550, SLC26A4-AS1, ACVR2B-AS1, {"type":"entrez-nucleotide","attrs":{"text":"AC005479.2","term_id":"4508155","term_text":"AC005479.2"}}AC005479.2, LINC02454, and AL136366.1), most of which were related to tumor development. The KEGG pathway enrichment analysis showed different, changed genes mainly enriched in the cancer-related pathways, PI3K-Akt signaling pathway, and focal adhesion. Only SLC26A4-AS1 had an intersection in the results of the two databases.Conclusion: LncRNA SLC26A4-AS1, which is the most associated with prognosis, may play an oncogenic role in the development of PTC.     

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.     

Construction of lncRNA-associated ceRNA networks to identify prognostic lncRNA biomarkers for glioblastoma

Long noncoding RNAs (lncRNAs) serve as competitive endogenous RNAs (ceRNAs) that play significant regulatory roles in the pathogenesis of tumors. However, the role of lncRNAs, especially the lncRNA-related ceRNA regulatory network, in glioblastoma (GBM) has not been fully elucidated. The goal of the current study was to construct lncRNA-microRNA-mRNA-related ceRNA networks for further investigation of their mechanism of action in GBM. We downloaded data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases and identified differential lncRNAs, microRNAs (miRNAs), and messenger RNAs (mRNAs) associated with GBM. A ceRNA network was constructed and analyzed to examine the relationship between lncRNAs and patients’ overall survival. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGGs) were used to analyze the related mRNAs to indirectly explain the mechanism of action of lncRNAs. The potential effective drugs for the treatment of GBM were identified using the connectivity map (CMap). After integrated analysis, we obtained a total of 210 differentially expressed lncRNAs, 90 differentially expressed miRNAs, and 2508 differentially expressed mRNAs (DEmRNAs) from the TCGA and GEO databases. Using these differential genes, we constructed a lncRNA-associated ceRNA network. Six lncRNAs in the ceRNA network were associated with the overall survival of patients with GBM. Through KEGG analysis, it was found that the DEmRNAs involved in the network are related to cancer-associated pathways, for instance, mitogen-activated protein kinase and Ras signaling pathways. CMap analysis revealed four small-molecule compounds that could be used as drugs for the treatment of GBM. In this study, a multi-database joint analysis was used to construct a lncRNA-related ceRNA network to help identify the regulatory functions of lncRNAs in the pathogenesis of GBM.