Differential expression of long noncoding RNAs in congenital microtia

ObjectiveTo analyse lncRNA expression profiles in microtia using bioinformatics analysis.MethodsWe examined lncRNA expression profiles in residual ear cartilage and normal ear cartilage from individual congenital microtia patients.ResultsThe gene chips used in this study included 30586 lncRNAs and 26109 mRNA probes. Intotal, 180 lncRNAs with differential expression weredetected in the residual ear cartilage compared with the normal cartilage, including 74 up-regulated and 106down-regulated lncRNAs. Signalling pathway analysis highlighted glyceride metabolism, osteoclast differentiation, andtumour growth. The results of qRT-PCR analysis were consistent with those of themicroarray.ConclusionDifferential expression of lncRNAs occurs in microtia. These lncRNAs and related signalling pathways may play an important role in the occurrence and development ofmicrotia.     

Hypoxia-related LncRNAs signature predicts prognosis and is associated with immune infiltration and progress of head and neck squamous cell carcinoma

BackgroundDisclosing prognostic information is necessary to enable good treatment selection and improve patient outcomes. Previous studies suggest that hypoxia is associated with an adverse prognosis in patients with HNSCC and that long non-coding RNAs (lncRNAs) show functions in hypoxia-associated cancer biology. Nevertheless, the understanding of lncRNAs in hypoxia related HNSCC progression remains confusing.MethodsData were downloaded from TCGA and GEO database. Bioinformatic tools including R packages GEOquery, limma, pheatmap, ggplot2, clusterProfiler, survivalROC and survcomp and LASSO cox analysis were utilized. Si-RNA transfection, CCK8 and real-time quantified PCR were used in functional study.ResultsGEO data (GSE182734) revealed that lncRNA regulation may be important in hypoxia related response of HNSCC cell lines. Further analysis in TCGA data identified 314 HRLs via coexpression analysis between differentially expressed lncRNAs and hypoxia-related mRNAs. 23 HRLs were selected to build the prognosis predicting model using lasso Cox regression analyses. Our model showed excellent performance in predicting survival outcomes among patients with HNSCC in both the training and validation sets. We also found that the risk scores were related to tumor stage and to tumor immune infiltration. Moreover, LINC01116 were selected as a functional study target. The knockdown of LINC01116 significantly inhibited the proliferation of HNSCC cells and effected the hypoxia induced immune and the NF-κB/AKT signaling.ConclusionsData analysis of large cohorts and functional experimental validation in our study suggest that hypoxia related lncRNAs play an important role in the progression of HNSCC, and its expression model can be used for prognostic prediction.     

Long non-coding RNA ROR decoys gene-specific histone methylation to promote tumorigenesis

BackgroundLong non-coding RNAs (lncRNAs) are not translated into proteins and were initially considered to be part of the ‘dark matter’ of the genome. Recently, it has been shown that lncRNAs play a role in the recruitment of chromatin modifying complexes and can influence gene expression. However, it is unknown if lncRNAs function in a similar way in cancer.ResultsHere, we show that the lncRNA ROR occupies and activates the TESC promoter by repelling the histone G9A methyltransferase and promoting the release of histone H3K9 methylation. Suppression of ROR in tumors results in silencing of TESC expression, and G9A-mediated histone H3K9 methylation in the TESC promoter is restored, which significantly reduces tumor growth and metastasis. Without ROR silencing, TESC knockdown presents consistent and significant reductions in tumor progression.ConclusionsOur results reveal a novel mechanism by which ROR may serve as a decoy oncoRNA that blocks binding surfaces, preventing the recruitment of histone modifying enzymes, thereby specifying a new pattern of histone modifications that promote tumorigenesis.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-015-0705-2) contains supplementary material, which is available to authorized users.     

A comprehensive study of construction and analysis of competitive endogenous RNA networks in lung adenocarcinoma

BackgroundLong noncoding RNAs (lncRNAs) have gain increasing attention in lung adenocarcinoma. In this study, we aimed at constructing and analyzing the lncRNAs and the related proteins based competitive endogenous RNA (ceRNA) network.MethodsRNA expression data of lung adenocarcinoma were extracted from the TCGA database. Differentially expressed (DE) lncRNAs, messenger RNAs (mRNAs) and microRNAs (miRNAs) were identified and then a DElncRNA-DEmiRNA-DEmRNA ceRNA network was constructed for lung adenocarcinoma. We also analyzed the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment of the DEgenes. Kaplan-Meier survival curves were also been further utilized for exploring the prognostic factors.ResultsAfter compared and calculated lncRNA, mRNA and miRNA expression profiles between lung adenocarcinoma and normal samples, 1709 differential expressed lncRNAs, 2554 differential expressed mRNAs and 116 differential expressed miRNAs were finally identified. Afterwards, a lncRNA mediated ceRNA network was constructed, according to the interactions among 544 pairs of DElncRNA-DEmiRNA relationships and 47 pairs of DEmiRNA-DEmRNA relationships. As for the survival analyses, we found 10 DElncRNAs, 25 DEmRNAs and 7 miRNAs have statistically prognostic significance for overall survival, respectively.ConclusionsThis study provides meaningful information for deeper understanding the underlying molecular mechanism of lung adenocarcinoma and for evaluating prognosis, which could monitor recurrence, guide clinical treatment drugs and subsequent related researches.     

Identification and expression analysis of lncRNA in seven organs of Rhinopithecus roxellana

Long non-coding RNA (lncRNA) represents a new direction to identify expression profiles and regulatory mechanisms in various organisms. Here, we report the first dataset of lncRNAs of the golden snub-nosed monkey (GSM), including 12,557 putative lncRNAs identified from seven organs. Compared with mRNA, GSM lncRNA had fewer exons and isoforms, and longer length. LncRNA showed more obvious tissue-specific expression than mRNA. However, for the top ten most abundant genes in each organ, mRNAs expression was more tissue-specific than lncRNAs. By identification of specifically expressed lncRNAs and mRNAs in each organ, it indicates that the expression of SEG-lncRNA (specifically expressed lncRNA) and SEG-mRNA (specifically expressed mRNA) had high correlation. In particular, combined our lncRNA and mRNA data, we identified 92 heart SEG-lncRNAs targeted ten mRNA genes in the oxidative phosphorylation pathway and upregulated the expression of these target genes such as ND4, ATP6, and ATP8. These may contribute to GSM adaption to its high-elevation environment. We also identified 171 liver SEG-lncRNAs, which targeted 27 genes associated with the metabolism of xenobiotics and leaded to high expression of these target genes in liver. These lncRNAs may play important roles in GSM adaptation to a folivory diet.

     

Immune-related long noncoding RNA signature for predicting survival and immune checkpoint blockade in hepatocellular carcinoma

Long noncoding RNAs (lncRNAs) show multiple functions, including immune response. Recently, the immune-related lncRNAs have been reported in some cancers. We first investigated the immune-related lncRNA signature as a potential target in hepatocellular carcinoma (HCC) survival. The training set (n = 368) and the independent external validation cohort (n = 115) were used. Immune genes and lncRNAs coexpression were constructed to identify immune-related lncRNAs. Cox regression analyses were perfumed to establish the immune-related lncRNA signature. Regulatory roles of this signature on cancer pathways and the immunologic features were investigated. The correlation between immune checkpoint inhibitors and this signature was examined. In this study, the immune-related lncRNA signature was identified in HCC, which could stratify patients into high- and low-risk groups. This immune-related lncRNA signature was correlated with disease progression and worse survival and was an independent prognostic biomarker. Our immune-related lncRNA signature was still a powerful tool in predicting survival in each stratum of age, gender, and tumor stage. This signature mediated cell cycle, glycolysis, DNA repair, mammalian target of rapamycin signaling, and immunologic characteristics (i.e., natural killer cells vs. Th1 cells down, etc). This signature was associated with immune cell infiltration (i.e., macrophages M0, Tregs, CD4 memory T cells, and macrophages M1, etc.,) and immune checkpoint blockade (ICB) immunotherapy-related molecules (i.e., PD-L1, PD-L2, and IDO1). Our findings suggested that the immune-related lncRNA signature had an important value for survival prediction and may have the potential to measure the response to ICB immunotherapy. This signature may guide the selection of the immunotherapy for HCC.     

Genome‐wide characterization and developmental expression profiling of long non‐coding RNAs in Sogatella furcifera

The genome‐wide characterization of long non‐coding RNA (lncRNA) in insects demonstrates their importance in fundamental biological processes. Essentially, an in‐depth understanding of the functional repertoire of lncRNA in insects is pivotal to insect resources utilization and sustainable pest control. Using a custom bioinformatics pipeline, we identified 1861 lncRNAs encoded by 1852 loci in the Sogatella furcifera genome. We profiled lncRNA expression in different developmental stages and observed that the expression of lncRNAs is more highly temporally restricted compared to protein‐coding genes. More up‐regulated Sogatella furcifera lncRNA expressed in the embryo, 4th and 5th instars, suggesting that increased lncRNA levels may play a role in these developmental stages. We compared the relationship between the expression of Sogatella furcifera lncRNA and its nearest protein gene and found that lncRNAs were more correlated to their downstream coding neighbors on the opposite strand. Our genome‐wide profiling of lncRNAs in Sogatella furcifera identifies exciting candidates for characterization of lncRNAs, and also provides information on lncRNA regulation during insect development.     

应用慢病毒shRNA文库结合二代测序筛选白血病细胞系增殖相关lncRNA北大核心CSCD

长链非编码RNA(long non-coding RNA,lncRNA)是包括细胞增殖在内的许多细胞过程的重要调节因子。虽然已有研究表明多种lncRNA在造血系统恶性肿瘤的发生发展过程中发挥重要作用,但是缺少一个更全面和无偏倚的方法同时研究多个lncRNA中对白血病细胞系产生功能性影响的lncRNA。在此,我们利用短发夹RNA(short hairpin RNA,shRNA)文库结合高通量测序的方法,筛选对白血病细胞系增殖有影响的lncRNA,确定了74个候选lncRNAs。从中选取lncRNA C20orf204-203作为验证研究对象,发现C20orf204-203在K562和THP-1细胞系中均定位于胞质,敲降C20orf204-203的K562和THP-1细胞系增殖能力降低,早期凋亡细胞增加,BAD基因在mRNA水平上表达量增加,TP53、BCL2蛋白表达量下降,在THP-1细胞系中Caspase 3蛋白表达量减少,激活型Caspase 3蛋白表达量上升,但是二者变化在两种细胞系中不一致。结果表明,在白血病细胞系中敲降lncRNA C20orf204-203会使细胞增殖能力降低。但其在不同细胞系作用途径和机制可能存在差异。这一研究表明了利用shRNA文库结合高通量测序大规模研究lncRNA在白血病细胞系中发挥作用的可行性。     

The joint role of methylation and immune-related lncRNAs in ovarian cancer: Defining molecular subtypes and developing prognostic signature

IntroductionComplex outcome of ovarian cancer (OC) stems from the tumor immune microenvironment (TIME) influenced by genetic and epigenetic factors. This study aimed to comprehensively explored the subclasses of OC through lncRNAs related to both N6-methyladenosine (m6A)/N1-methyladenosine (m1A)/N7-methylguanosine (m7G)/5-methylcytosine (m5C) in terms of epigenetic variability and immune molecules and develop a new set of risk predictive systems.Material and methodsThe lncRNA data of OC were collected from TCGA. Spearman correlation analysis on lncRNA data of OC with immune-related gene expression and with m6A/m5C/m1A/m7G were respectively conducted. The m6A/m5C/m1A/m7G-related m6A/m5C/m1A/m7G related immune lncRNA subtypes were identified on the basis of the prognostic lncRNAs. Heterogeneity among subtypes was evaluated by tumor mutation analysis, tumor microenvironment (TME) component analysis, response to immune checkpoint blocked (ICB) and chemotherapeutic drugs. A risk predictive system was developed based on the results of Cox regression analysis and random survival forest analysis of the differences between each specific cluster and other clusters.ResultsThree m6A/m5C/m1A/m7G-related immune lncRNA subtypes of OC showing distinct differences in prognosis, mutation pattern, TIME components, immunotherapy and chemotherapy response were identified. A set of risk predictive system consisting of 10 lncRNA for OC was developed, according to which the risk score of samples in each OC dataset was calculated and risk type was defined.ConclusionsThis study classified three m6A/m5C/m1A/m7G-related immune lncRNA subtypes with distinct heterogeneous mutation patterns, TME components, ICB therapy and immune response, and provided a set of risk predictive system consisted of 10 lncRNA for OC.