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.     

Long noncoding RNAs expression in gastric cancer

Long noncoding RNAs (lncRNAs) have been involved in the pathogenesis of several human cancers including gastric cancer. In the current study, we selected five lncRNAs namely NEAT1, TUG1, PANDA, UCA1, and GHET1 to assess their expressions in gastric cancer samples compared with adjacent noncancerous tissues (ANCTs) from the same patients. Some previous reports have shown contribution of these lncRNAs in gastric cancer. However, we aimed to explore their associations with patients’ clinicopathological data and their potential as diagnostic biomarkers. Significant associations were found between site of primary tumor and relative expression of all lncRNAs in cancer samples compared with ANCTs. Besides, GHET1 relative expression was associated with lymph node status. The diagnostic power of GHET1 was higher from other lncRNAs. Combination of GHET1, TUG1, UCA1, and PANDA increased the diagnostic power and significance (AUC = 0.8; P < 0.0001). The current study supports participation of lncRNAs in the pathogenesis of gastric cancer and highlights their potential as diagnostic biomarkers.     

Analysis of long noncoding RNA expression profiles in the whole blood of neonates with hypoxic-ischemic encephalopathy

Long noncoding RNAs (lncRNAs) have been shown to participate in many biological processes. To investigate the expression profiles of lncRNAs and their potential functions in neonatal hypoxic-ischemic encephalopathy (HIE), we detected the lncRNA and messenger RNA (mRNA) expression in the peripheral blood samples from HIE patients and controls using a microarray. A total of 376 lncRNAs and 126 mRNAs were differentially expressed between the HIE and the non-HIE samples (fold change > 2). Quantitative real-time polymerase chain reaction was used to validate the microarray data. Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analysis were performed to determine the gene function. Furthermore, the lncRNA-mRNA coexpression network was generated to predict the potential targets of lncRNAs. In conclusion, our study first demonstrated the differential expression profiles of lncRNAs in the whole blood of infants with HIE and may provide a new view of the distinct lncRNA functions in HIE.     

长非编码RNA

人类基因组序列的约5%～10%被稳定转录,蛋白质编码基因仅约占1%,其余4%～9%的序列虽能转录,但转录物功能尚不明确。尽管如此,已确证在非蛋白质编码转录物中,含有具备调节功能的非编码RNA(noncoding RNA,ncRNA)。与具有调节功能的短链非编码RNA[如微RNA(microRNA)、小干扰RNA(siRNA),、Piwi-RNA]相比,长非编码RNA(long noncoding RNA,lncRNA)在数量上占大多数。lncRNA通过多种方式产生,以多种途径调节靶基因表达,参与调控生物体生长、发育、衰老、死亡等过程;lncRNA功能异常往往导致疾病发生。本文综述了lncRNA的起源、分类、作用分子机制及lncRNA异常与疾病的相关性等内容,旨在充分了解这一重要新型调控分子。     

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.     

New insights into the role of microRNAs and long noncoding RNAs in most common neurodegenerative diseases

Neurodegenerative diseases (NDs) are a diversity of neurological disorders characterized by the progressive degeneration of the structure and function of the central nervous system (CNS). The most common NDs are Alzheimer's disease (AD), Parkinson's disease (PD), and Huntington's disease (HD). Recently, many studies have investigated associations between common NDs with noncoding RNAs (ncRNAs) molecules. ncRNAs are regulatory molecules in the normal functioning of the CNS. Two of the most important ncRNAs are microRNAs (miRNAs) and long noncoding RNAs (lncRNAs). These types of ncRNAs are involved in different biological processes including brain development, maturation, differentiation, neuronal cell specification, neurogenesis, and neurotransmission. Increasing data has demonstrated that miRNAs and lncRNAs have strong correlations with the development of NDs, particularly gene expression. Besides, ncRNAs can be introduced as new biomarkers for diagnosis and prognosis of NDs. Hence, in this review, we summarized the involvement of various miRNAs and lncRNAs in most common NDs followed by a correlation of ncRNAs dysregulation with the AD, PD, and HD.     

A novel risk signature that combines 10 long noncoding RNAs to predict neuroblastoma prognosis

Neuroblastoma (NBL) is the most frequently encountered extracranial solid neoplasm and impacts significantly on the survival of patients, especially in cases of advanced tumor stage or relapse. A long noncoding RNA (lncRNA) signature to predict the survival of patients with NBL is proposed in this paper. Differentially expressed lncRNA (DElncRNA) was selected using the Limma plus Voom package in R based on the RNA-sequencing data downloaded from the Therapeutically Applicable Research To Generate Effective Treatments database and Genotype-Tissue Expression database. Univariate cox regression analysis, least absolute shrinkage and selection operator regression analysis, and multivariate cox regression analysis were conducted to identify candidate DElncRNAs for the risk signature. Consequently, 10 DElncRNAs were designated as candidate DElncRNAs for the risk signature. Time-dependent receiver operating characteristic curves and Kapan–Meier survival curves confirmed the efficacy of the risk signature in predicting the survival of patients with NBL (area under the curve = 0.941; p ≤ .001). One of the DElncRNA constituent subparts (LINC01010) was significantly associated with the survival outcome of patients with NBL in GSE62564 (p = .004). Thus, a risk signature comprising 10 DElncRNAs was identified as effective for individual risk stratification and the survival prediction outcomes of patients with NBL.