LncRNA作为ceRNA调控肿瘤的发生发展

长链非编码RNA(lncRNA)是长度大于200 bp,不编码蛋白质的内源性RNA分子.近年来的研究表明,lncRNA可以作为一种竞争性内源RNA(competing endogenous RNA,ceRNA)吸附miRNA,参与靶基因的表达调控,从而在肿瘤的发生发展中发挥重要的作用.本文从lncRNA作为ceRNA发挥生物学功能这一角度,概述了相关lncRNA在肿瘤发生发展中的作用及机制.揭秘lncRNA与miRNA在肿瘤发生中的相互作用,将为肿瘤的诊断和治疗提供新思路.     

长非编码RNA作为ceRNA分子在乳腺癌中的调控机制

乳腺癌是全球女性最常见的异质性恶性肿瘤，分为多种亚型，不同亚型的临床治疗方式和效果不同。多项研究表明长非编码RNA(lncRNA)在乳腺癌的进展中起着关键作用，其中由lncRNA-miRNA-mRNA相互作用形成的ceRNA网络是RNA分子间的一种新调节机制。LncRNA通过该网络广泛参与乳腺癌的增殖、迁移、凋亡等多种生物学过程，可作为诊断和治疗的分子靶点。该文重点阐述了lncRNA介导的ceRNA调控机制，系统总结了lncRNA相关ceRNA网络在调控不同乳腺癌亚型的增殖、迁移和耐药性中的研究进展，旨在为乳腺癌的精准治疗和lncRNA研究提供新见解。     

lncRNA与miRNA相互调控作用及其与肿瘤的关系研究

长链非编码RNA (long non-coding RNA,lncRNA)是一类转录本长度大于200 bp的非编码RNA,可作为人类基因组中一类重要的调控分子通过多种方式发挥其生物学功能.近年来的研究表明,lncRNA也可以作为一种竞争性内源性RNA (competing endogenous RNA, ceRNA) 与miRNA相互作用,参与靶基因的表达调控,并在肿瘤的发生发展中发挥重要的作用.本综述在简要介绍lncRNA功能研究现状和主要研究方法的基础上,进一步分析了lncRNA与miRNA之间的互相调控关系及其在肿瘤发生发展中的作用,以便为后续的研究提供新的思路.     

非编码RNA与基因表达调控

近年来,随着对基因组的深入研究,发现真核生物中存在许多形态和功能各异的非编码RNA分子,这类RNA分子并不表达蛋白质,但它们在基因转录水平、转录后水平及翻译水平起了重要的调控作用。具有调控作用的RNA分子种类非常丰富,如长链非编码RNA(long non-coding RNA,lncRNA)、miRNA、PIWI相互作用RNA(PIWI-interacting RNA,piRNA)、内源性小干扰RNA(endogenous small interfering RNA,endo-siRNA)、竞争性内源RNA(competitive endogenous RNA,ceRNA)等,它们使基因表达过程更为丰富、严谨和有序。本文综述几类典型的非编码RNA对基因表达的调节作用,以助于理解细胞中RNA分子调节网络的功能和机制。     

竞争性内源RNA的生物学功能及其调控

最新研究表明,RNA之间可以通过竞争结合共同的microRNA反应元件(microRNA response element, MRE)实现相互调节,这种调控模式构成竞争性内源RNA(Competing endogenous RNA, ceRNA)。已发现的ceRNA包括蛋白编码mRNA和非编码RNA,其中后者包括假基因转录物、长链非编码RNA(Long non-coding RNA, lncRNA)、环状RNA(Circular RNA, circRNA)等。文章主要从ceRNA分类的角度,阐述各类ceRNA构成的调控网络发挥的生物学功能在病理和生理相关过程中的作用,以及可能影响ceRNA调控有效性的因素。     

生物节律基因非编码RNA调控机制

节律性的振荡不仅存在于生物节律中枢也存在于外周器官、组织及细胞中,其产生依赖于节律基因的转录、转录后及翻译后水平调控。近几年,生物节律转录后水平调控机制研究成为热点。非编码RNA(ncRNAs)调控组分小RNA(microRNA)与长链非编码RNA(lncRNA)作为参与转录后调控的重要分子,已有研究表明microRNA与lncRNA调控节律基因mRNA与蛋白的相位及振幅。本文概述microRNA与lncRNA参与昼夜节律中枢与外周调控的研究进展,为生物节律转录后调控机制的进一步研究提供参考。     

反义lncRNA在NSCLC中的作用及机制

非小细胞肺癌(non-small cell lung cancer,NSCLC)在我国发病率和死亡率非常高,严重威胁着公众健康。由于缺乏敏感有效的早期诊断指标、易复发、易产生耐药性等因素,NSCLC的临床治疗效果一直不佳,导致患者预后差及生存率低。反义长链非编码RNA(long non-coding RNA,lncRNA)的异常表达与NSCLC发生发展密切相关,在NSCLC的增殖、凋亡、侵袭、迁移、上皮-间充质转化(epithelial-mesenchymal transition,EMT)和耐药等方面均发挥着重要作用,已成为近年来的研究热点。本文探讨反义lncRNA在NSCLC发生发展过程中的功能及具体调控机制,旨在为NSCLC患者提供更有效的治疗理论参考。     

子宫内膜癌中的lncRNA-miRNA-mRNA ceRNA网络的整合分析

子宫内膜癌(uterine corpus endometrial carcinoma, UCEC)是危害女性健康的癌症之一,但其发生发展机制尚不完全清楚。基因的异常表达在细胞癌变过程中发挥着重要的作用。本研究利用生物信息学方法对UCEC中异常表达的基因进行网络调控分析,为UCEC的机制研究及预后治疗提供理论依据。首先,利用"limma"包筛选得到差异表达的RNA分子;接着,利用R软件中的"GDCRNATools"包构建lncRNA-miRNA-mRNAceRNA网络;最后,利用DAVID(TheDatabasefor Annotation,Visualization and Integrated Discovery)、R软件中的"survival"包、MCODE(Molecular COmplex Detection)插件、StarBase数据库等对ceRNA网络中的RNA分子进行综合分析。结果显示,在UCEC中,我们鉴定了1 319个mRNA、68个lncRNA及100个miRNA为差异表达的RNA分子。同时,利用这些UCEC中的差异表达RNA分子,成功构建了ceRNA网络,结果表明,HCG11、LINC00958、LINC00667、MAGI2-AS3和AC093010.3可能具有ceRNA的功能。通过进一步对该网络成员的分析,结果发现,该网络中的mRNA分子聚集于内皮细胞增殖、细胞骨架和锌离子结合负调控等生物学过程中。生存分析显示,hsa-miR-449a、LINC00958、PKIA和DPYSL2等19个差异表达的RNA分子与UCEC患者预后显著相关。最后,利用MCODE插件对ceRNA网络进行筛选,共获得一个子网络,其成员分别是LINC00667、hsa-miR-449a、hsa-miR-34a-5p和RECK。该研究结果提示,在UCEC的发生发展中存在lncRNA、miRNA和mRNA的差异表达,并且这些RNA分子之间存在ceRNA网络模式的调控,其中一些关键分子与患者的预后相关,这将为进一步研究与理解UCEC的发病机制及预后提供理论依据。     

长链非编码RNA在白血病发生发展中的调控机制研究进展

长链非编码RNA (Long noncoding RNA,lncRNA) 是一类长度大于200 nt且不具备蛋白编码能力或仅编码微肽的RNA分子。LncRNA参与调控细胞增殖、分化和凋亡等生物学过程,与多种恶性血液病的发生、复发及转移密切相关。文章结合最新研究报道,对lncRNA在白血病发生过程中异常表达的功能、调控机制和潜在临床应用方面进行综述。概括了lncRNA可以通过表观遗传修饰、核糖体RNA转录、竞争性结合miRNA,以及参与糖代谢途径、活化肿瘤相关信号通路等多种方式调控白血病的发生发展及化疗中产生的多药耐药性。这些机制研究为深入了解白血病的发病机理、发现新的预后标志物和潜在的治疗靶标,为解决临床上治疗白血病所面临的患者耐药性的产生和治疗后复发等难题提供了新的参考依据。     

长链非编码RNA在头颈部肿瘤中的研究进展

长链非编码RNA(long noncoding RNA,lncRNA)是一类长度大于200个核苷酸的、缺少特异完整的开放阅读框、极少有蛋白编码功能的非编码RNA。研究表明lncRNA是参与基因表达的关键调控分子,从表观遗传、转录及转录后等多种水平调控相关靶基因的表达。近年来lncRNA在头颈部疾病中的研究开始受到关注。现就lncRNA在头颈部肿瘤中的研究进展作一综述。     

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.     

Interaction of long noncoding RNA MEG3 with miRNAs: A reciprocal regulation

The competitive endogenous RNA (ceRNA) hypothesis suggests that a long noncoding RNA (lncRNA) can function as sinks for pools of microRNAs (miRNAs); thereby, in the presence of ceRNA, messenger RNAs (mRNAs) targeted by specific miRNAs can liberate and translate to protein. Maternally expressed gene 3 (MEG3) is a lncRNA, which its expression has been detected in various normal tissues, while it is lost or downregulated in human tumors. The MEG3 is an imprinted gene which, is methylated and suppressed by DNA methyltransferases (DNMTs) family. Also, miRNAs are involved in the regulation of MEG3 gene expression. Interestingly, the lncRNA MEG3 (lnc-MEG3), as a ceRNA affects various cell processes such as proliferation, apoptosis, and angiogenesis by sponging miRNAs. These miRNAs, in turn, regulate different mRNAs in different pathways. This review focuses on the interaction between lnc-MEG3 and experimentally validated miRNAs. In addition, the discussion supplemented by some data obtained from mirPath (v.3) and TarBase (v.8) databanks to provide more details about the pathways affected by this ceRNA.     

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.     

Reconstruction and analysis of the aberrant lncRNA‐miRNA‐mRNA network based on competitive endogenous RNA in CESC

A growing body of studies has demonstrated that long non‐coding RNA (lncRNA) are regarded as the primary section of the ceRNA network. This is thought to be the case owing to its regulation of protein‐coding gene expression by functioning as miRNA sponges. However, functional roles and regulatory mechanisms of lncRNA‐mediated ceRNA in cervical squamous cell carcinoma (CESC), as well as their use for potential prediction of CESC prognosis, remains unknown. The aberrant expression profiles of mRNA, lncRNA, and miRNA of 306 cervical squamous cancer tissues and three adjacent cervical tissues were obtained from the TCGA database. A lncRNA‐mRNA‐miRNA ceRNA network in CESC was constructed. Meanwhile, Gene Ontology (GO) and KEGG pathway analysis were performed using Cytoscape plug‐in BinGo and DAVID database. We identified a total of 493 lncRNA, 70 miRNA, and 1921 mRNA as differentially expressed profiles. An aberrant lncRNA‐mRNA‐miRNA ceRNA network was constructed in CESC, it was composed of 50 DElncRNA, 18 DEmiRNA, and 81 DEmRNA. According to the overall survival analysis, 3 out of 50 lncRNA, 10 out of 81 mRNA, and 1 out of 18 miRNA functioned as prognostic biomarkers for patients with CESC (P value < 0.05). We extracted the sub‐network in the ceRNA network and found that two novel lncRNA were recognized as key genes. These included lncRNA MEG3 and lncRNA ADAMTS9‐AS2. The present study provides a new insight into a better understanding of the lncRNA‐related ceRNA network in CESC, and the novel recognized ceRNA network will help us to improve our understanding of lncRNA‐mediated ceRNA regulatory mechanisms in the pathogenesis of CESC.     

Long noncoding RNA MEG3 play an important role in osteosarcoma development through sponging microRNAs

More and more evidence indicate long noncoding RNAs (lncRNAs) as competing endogenous RNAs (ceRNAs) to indirectly regulate messenger RNAs (mRNAs) by acting as microRNA (miRNA) sponges, which represents a novel layer of gene regulation that plays a critical role in the development of cancers. However, functional roles and regulatory mechanisms of lncRNA-mediated ceRNAs network in osteosarcoma are still largely unknown. Here, we comprehensively compared the expression profiles of mRNAs, lncRNAs, and miRNAs between osteosarcoma and normal samples from the Gene Expression Omnibus (GEO) to elaborate related latent mechanisms. Two lncRNAs, ie, LINC01560 and MEG3, were identified to be aberrantly expressed. Importantly, MEG3 was considered as a promising diagnostic biomarker and therapeutic target for patients with osteosarcoma according to the Kaplan-Meier analysis of another independent osteosarcoma data set from the Cancer Genome Atlas (P = 0.05). Eventually, we successfully established a dysregulated lncRNA-related ceRNA network, including one osteosarcoma-specific lncRNA, three miRNAs and four mRNAs. In conclusion, this study should be beneficial for improving our understanding of the lncRNA-mediated ceRNA regulatory mechanisms in the pathogenesis of osteosarcoma and providing it with novel candidate diagnostic and therapeutic biomarkers.     

Screening of significant biomarkers related with prognosis of liver cancer by lncRNA-associated ceRNAs analysis

This study aimed to identify significant biomarkers related to the prognosis of liver cancer using long noncoding RNA (lncRNA)-associated competing endogenous RNAs (ceRNAs) analysis. Differentially expressed mRNA and lncRNAs between liver cancer and paracancerous tissues were screened, and the functions of these mRNAs were predicted by gene ontology and pathway enrichment analyses. A ceRNA network consisting of differentially expressed mRNAs and lncRNAs was constructed. LncRNA FENDRR and lncRNA HAND2-AS1 were hub nodes in the ceRNA network. A risk score assessment model consisting of eight genes (PDE2A, ESR1, FBLN5, ALDH8A1, AKR1D1, EHHADH, ADRA1A, and GNE) associated with prognosis were developed. Multivariate Cox regression suggested that both pathologic_T and risk group could be regarded as independent prognostic factors. Furthermore, a nomogram model consisting of pathologic_T and risk group showed a good prediction ability for predicting the survival rate of liver cancer patients. The nomogram model consisting of pathologic_T and a risk score assessment model could be regarded as an independent factor for predicting prognosis of liver cancer.     

Integrated analysis of a competing endogenous RNA network reveals key long noncoding RNAs as potential prognostic biomarkers for hepatocellular carcinoma

Growing evidence has revealed that long noncoding RNAs (lncRNAs) have an important impact on tumorigenesis and tumor progression via a mechanism involving competing endogenous RNAs (ceRNAs). However, their use in predicting the survival of a patient with hepatocellular carcinoma (HCC) remains unclear. The aim of this study was to develop a novel lncRNA expression–based risk score system to accurately predict the survival of patients with HCC. In our study, using expression profiles downloaded from The Cancer Genome Atlas database, the differentially expressed messenger RNAs (mRNAs), lncRNAs, and microRNAs (miRNAs) were explored in patients with HCC and normal liver tissues, and then a ceRNA network constructed. A risk score system was established between lncRNA expression of the ceRNA network and overall survival (OS) or recurrence-free survival (RFS); it was further analyzed for associations with the clinical features of patients with HCC. In HCC, 473 differentially expressed lncRNAs, 63 differentially expressed miRNAs, and 1417 differentially expressed mRNAs were detected. The ceRNA network comprised 41 lncRNA nodes, 12 miRNA nodes, 24 mRNA nodes, and 172 edges. The lncRNA expression–based risk score system for OS was constructed based on six lncRNAs (MYLK-AS1, AL359878.1, PART1, TSPEAR-AS1, C10orf91, and LINC00501), while the risk score system for RFS was based on four lncRNAs (WARS2-IT1, AL359878.1, AL357060.1, and PART1). Univariate and multivariate Cox analyses showed the risk score systems for OS or RFS were significant independent factors adjusted for clinical factors. Receiver operating characteristic curve analysis showed the area under the curve for the risk score system was 0.704 for OS, and 0.71 for RFS. Our result revealed a lncRNA expression–based risk score system for OS or RFS can effectively predict the survival of patients with HCC and aid in good clinical decision-making.