Temporal expression and functional analysis of long non‐coding RNAs in colorectal cancer initiation

Long non‐coding RNAs (lncRNAs) have potential applications in clinical diagnosis and targeted cancer therapies. However, the expression profile of lncRNAs in colorectal cancer (CRC) initiation is still unclear. In this study, the expression profiles of lncRNAs and mRNAs were determined by microarray at specific tumour stages in an AOM/DSS‐induced primary colon cancer model. The temporal expression of lncRNAs was analysed by K‐means clustering. Additionally, weighted correlation network analysis (WGCNA) and gene ontology analysis were performed to construct co‐expression networks and establish functions of the identified lncRNAs and mRNAs. Our results suggested that 4307 lncRNAs and 5798 mRNAs are deregulated during CRC initiation. These differential expression genes (DEGs) exhibited a clear correlation with the differential stage of tumour initiation. WGCNA results suggested that a series of hub lncRNAs are involved in regulating cell stemness, colon inflammation, oxidative stress response and cell death at each stage. Among them, lncRNA H19 was up‐regulated in colon tumours and correlated with poor patient prognosis. Collectively, we have been the first to demonstrate the temporal expression and function of lncRNAs in CRC initiation. These results provide novel diagnosis and therapy targets for CRC.     

Identification and development of long non‐coding RNA‐associated regulatory network in colorectal cancer

Colorectal cancer (CRC) is one of the leading causes of cancer‐associated death globally. Long non‐coding RNAs (lncRNAs) have been identified as micro RNA (miRNA) sponges in a competing endogenous RNA (ceRNA) network and are involved in the regulation of mRNA expression. This study aims to construct a lncRNA‐associated ceRNA network and investigate the prognostic biomarkers in CRC. A total of 38 differentially expressed (DE) lncRNAs, 23 DEmiRNAs and 27 DEmRNAs were identified by analysing the expression profiles of CRC obtained from The Cancer Genome Atlas (TCGA). These RNAs were chosen to develop a ceRNA regulatory network of CRC, which comprised 125 edges. Survival analysis showed that four lncRNAs, six miRNAs and five mRNAs were significantly associated with overall survival. A potential regulatory axis of ADAMTS9‐AS2/miR‐32/PHLPP2 was identified from the network. Experimental validation was performed using clinical samples by quantitative real‐time PCR (qRT‐PCR), which showed that expression of the genes in the axis was associated with clinicopathological features and the correlation among them perfectly conformed to the ‘ceRNA theory’. Overexpression of ADAMTS9‐AS2 in colon cancer cell lines significantly inhibited the miR‐32 expression and promoted PHLPP2 expression, while ADAMTS9‐AS2 knockdown had the opposite effects. The constructed novel ceRNA network may provide a comprehensive understanding of the mechanisms of CRC carcinogenesis. The ADAMTS9‐AS2/miR‐32/PHLPP2 regulatory axis may serve as a potential therapeutic target for CRC.     

Prognostic value of the tumor-specific ceRNA network in epithelial ovarian cancer

Epithelial ovarian cancer is one of the leading causes of cancer-related death worldwide. Growing evidence indicates that multiple complex altered pathways play important regulatory roles in the development and progression of a variety of cancers, including epithelial ovarian cancer. However, the underlying mechanisms remain unclear. First, we identified differentially expressed messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), and microRNAs (miRNAs) in epithelial ovarian cancer by comparing the expression profiles between epithelial ovarian cancer samples and normal tissue samples in different GEO datasets. Then, GO- and KEGG-pathway-enrichment analyses were applied to investigate the primary functions of the overlapped differentially expressed mRNAs. Moreover, the primary enriched genes were used to construct the signal-network with Cytoscape software. In addition, we integrated the relationship among lncRNAs-miRNAs-mRNAs to create a competing endogenous RNA network. Finally, mRNAs that were associated with patient prognosis in epithelial ovarian cancer were selected using univariate Cox regression analysis. A total of 2,225 mRNAs, 336 lncRNAs, and 14 miRNAs were shown to be differentially expressed in epithelial ovarian cancer compared with normal tissues. The dysregulated mRNAs were primarily enriched in cell division and signal transduction, according to Gene Ontology, whereas, according to KEGG, they were primarily enriched in metabolic pathways and pathways in cancer. A total of 10 mRNAs were associated with patient prognosis in ovarian cancer. This study identifies a novel lncRNA–miRNA–mRNA network, which may suggest potential molecular mechanisms underlying the development of epithelial ovarian cancer, providing new insights for survival prediction and interventional strategies for epithelial ovarian cancer.     

Molecular mechanisms of long noncoding RNAs

Long noncoding RNAs (lncRNAs) are an important class of pervasive genes involved in a variety of biological functions. Here we discuss the emerging archetypes of molecular functions that lncRNAs execute-as signals, decoys, guides, and scaffolds. For each archetype, examples from several disparate biological contexts illustrate the commonality of the molecular mechanisms, and these mechanistic views provide useful explanations and predictions of biological outcomes. These archetypes of lncRNA function may be a useful framework to consider how lncRNAs acquire properties as biological signal transducers and hint at their possible origins in evolution. As new lncRNAs are being discovered at a rapid pace, the molecular mechanisms of lncRNAs are likely to be enriched and diversified.     

Time-Series Clustering of lncRNA-mRNA Expression during the Adipogenic Transdifferentiation of Porcine Skeletal Muscle Satellite Cells

Skeletal muscle satellite cells (SMSCs), which are multifunctional muscle-derived stem cells, can differentiate into adipocytes. Long-chain non-coding RNA (lncRNA) has diverse biological functions, including the regulation of gene expression, chromosome silencing, and nuclear transport. However, the regulatory roles and mechanism of lncRNA during adipogenic transdifferentiation in muscle cells have not been thoroughly investigated. Here, porcine SMSCs were isolated, cultured, and induced for adipogenic differentiation. The expressions of lncRNA and mRNA at different time points during transdifferentiation were analysed using RNA-seq analysis. In total, 1005 lncRNAs and 7671 mRNAs showed significant changes in expression at differential differentiation stages. Time-series expression analysis showed that the differentially expressed (DE) lncRNAs and mRNAs were clustered into 5 and 11 different profiles with different changes, respectively. GO, KEGG, and REACTOME enrichment analyses revealed that DE mRNAs with increased expressions during the trans-differentiation were mainly enriched in the pathways for lipid metabolism and fat cell differentiation. The genes with decreased expressions were mainly enriched in the regulation of cell cycle and genetic information processing. In addition, 1883 DE mRNAs were regulated by 193 DE lncRNAs, and these genes were related to the controlling in cell cycle mainly. Notably, three genes in the fatty acid binding protein (FABP) family significantly and continuously increased during trans-differentiation, and 15, 13, and 11 lncRNAs may target FABP3, FABP4, and FABP5 genes by cis- or trans-regulation, respectively. In conclusion, these studies identify a set of new potential regulator for adipogenesis and cell fate and help us in better understanding the molecular mechanisms of trans-differentiation.     

Integrative analysis of competing endogenous RNA networks reveals the functional lncRNAs in heart failure

Heart failure has become one of the top causes of death worldwide. It is increasing evidence that lncRNAs play important roles in the pathology processes of multiple cardiovascular diseases. Additionally, lncRNAs can function as ceRNAs by sponging miRNAs to affect the expression level of mRNAs, implicating in numerous biological processes. However, the functional roles and regulatory mechanisms of lncRNAs in heart failure are still unclear. In our study, we constructed a heart failure‐related lncRNA‐mRNA network by integrating probe re‐annotation pipeline and miRNA‐target interactions. Firstly, some lncRNAs that had the central topological features were found in the heart failure‐related lncRNA‐mRNA network. Then, the lncRNA‐associated functional modules were identified from the network, using bidirectional hierarchical clustering. Some lncRNAs that involved in modules were demonstrated to be enriched in many heart failure‐related pathways. To investigate the role of lncRNA‐associated ceRNA crosstalks in certain disease or physiological status, we further identified the lncRNA‐associated dysregulated ceRNA interactions. And we also performed a random walk algorithm to identify more heart failure‐related lncRNAs. All these lncRNAs were verified to show a strong diagnosis power for heart failure. These results will help us to understand the mechanism of lncRNAs in heart failure and provide novel lncRNAs as candidate diagnostic biomarkers or potential therapeutic targets.     

Expression profiling of long noncoding RNAs associated with vasculogenic mimicry in osteosarcoma

Osteosarcoma (OS) is the most common highly malignant bone tumor in teens. Vasculogenic mimicry (VM) is defined as de novo extracellular matrix-rich vascular-like networks formed by highly aggressive tumor cells. We previously reported the presence of VM and it is an unfavorable prognostic factor in OS patients. Long noncoding RNAs (lncRNAs) are aberrantly expressed in OS and involved in cancer cell VM. However, lncRNAs in VM formation of OS have not been investigated. We, therefore, profiled the expression of lncRNAs in highly aggressive OS cell line 143B compared with its parental poorly aggressive cell line HOS. The differentially expressed (DE) lncRNAs and messenger RNA (mRNAs) were subjected to constructed lncRNA-mRNA coexpressed network. The top-ranked hub gene lncRNA n340532 knockdown 143B cells were used for in vitro and in vivo VM assays. The annotation of DE lncRNAs was performed according to the coexpressed mRNAs by Gene Ontology and pathway analysis. A total of 1360 DE lncRNAs and 1353 DE mRNAs were screened out. lncRNA MALAT1 and FTX, which have known functions related to VM formation and tumorigenesis were identified in our data. The coexpression network composed of 226 lncRNAs and 118 mRNAs in which lncRNA n340532 had the highest degree number. lncRNA n340532 knockdown reduced VM formation in vitro. The suppression of n340532 also exhibited potent anti-VM and antimetastasis effect in vivo, suggesting its potential role in OS VM and metastasis. Furthermore, n340532 coexpressed with 10 upregulation mRNAs and 3 downregulation mRNAs. The enriched transforming growth factor-β signaling pathway, angiogenesis and so forth were targeted by those coexpressed mRNAs, implying n340532 may facilitate VM formation in OS through these pathways and gene functions. Our findings provide evidence for the potential role of lncRNAs in VM formation of OS that could be used in the clinic for anti-VM therapy in OS.     

长链非编码RNA表征及其在结直肠癌发生发展中的作用和临床意义

长非编码RNA（long non-coding RNAs, lncRNAs）是一类转录本长度大于200个核苷酸,不具有蛋白质编码功能的非编码RNA（non-coding RNA, ncRNA）。人类基因组中,ncRNA基因占比超过90%,数量远大于蛋白质编码基因。作为生物大分子,lncRNA具有特定的初级和高级结构,在基因表达调控等生物学进程中发挥着特有的功能。lncRNA数量多,结构各异,因此鉴定和表征新的lncRNA,探索其结构和功能,是当前基因研究领域的热点之一。在临床疾病机制研究中,大量结果表明,lncRNA与临床疾病发生发展,特别是肿瘤的发生发展具有密切的相关性。伴随着后基因组学时代基因鉴定和功能探索方法的不断进步,探索lncRNA在疾病发生中的功能及表达变化,深入解锁lncRNA在疾病发生中涉及的分子机制,将为疾病早期预防、诊断和预后提供有效参考。基于以上的研究大背景,本文对lncRNA的定义、基因鉴定的策略和方法,高级结构检测及其对应的生物学功能,以及lncRNA的分类进行了阐述;另一方面,基于lncRNA与肿瘤发生发展的密切关系,本文以经典抑癌基因p53为切入点,对多种p53相关的lncRNA在结直肠癌（colorectal cancer, CRC）发生发展中的作用进行了归纳小结,阐述了lncRNA在结直肠癌中的表达变化、涉及的分子互作机制和信号通路,对其作为分子标志物在临床中的应用潜力进行了评估。我们乐观地认为,作为生物分子标志物,lncRNA将为包括癌症在内的疾病治疗提供全新、精准和个性化的分子靶点。     

Comprehensive bioinformatics analysis identifies lncRNA HCG22 as a migration inhibitor in esophageal squamous cell carcinoma

Esophageal cancer is one of the most lethal malignancies worldwide, and esophageal squamous cell carcinoma (ESCC) is the dominant histological type. However, the long noncoding RNA (lncRNA) alterations in ESCC have not been elucidated to date. In this study, reliable databases from Gene Expression Omnibus (GEO), which analyzed lncRNA expression in ESCC tumor tissues and adjacent normal tissues were searched, and common differentially expressed lncRNAs and genes were analyzed. Next, cis- trans analysis was performed to predict the underlying relationships between altered lncRNAs and mRNAs, and the lncRNA-mRNA regulatory network was established. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of altered lncRNA-related genes were performed. The promising lncRNA HCG22 was validated by quantitative polymerase chain reaction (qPCR), and clinicopathological data were collected to identify the relationship between lncRNA HCG22 expression level and clinical features. Finally, Transwell assays were performed to explore the biological functions of lncRNA HCG22 in ESCC cells. Two hundred forty-one lncRNAs and 835 mRNAs were observed to be remarkably altered between ESCC tumor tissues and adjacent normal tissues. The lncRNA-mRNA regulatory network showed the coexpression association between lncRNA HCG22 and SPINK7 and ADAMTS12. GO and KEGG analyses showed that HCG22 and ADAMTS12 had potential biological functions in the cell migration of ESCC. The downregulation of lncRNA HCG22 in ESCC tumor tissues was validated by qPCR, and the clinicopathological data showed a noticeable correlation between lncRNA HCG22 expression level and the ESCC differentiational degree and clinical TNM stage. Kaplan-Meier analysis showed that patients with ESCC having low lncRNA HCG22 expression in ESCC tissues had considerably shorter overall survival compared with patients with ESCC having high lncRNA HCG22 expression. Following Transwell assays confirmed the migratory role of lncRNA HCG22 in ESCC cells. In conclusion, lncRNA HCG22 was downregulated in ESCC tissues and can be a migration inhibitor of ESCC cells, and SPINK7 and ADAMTS12 are promising to be the regulatory targets of lncRNA HCG22.     

Identification of lncRNA–miRNA–mRNA regulatory network associated with epithelial ovarian cancer cisplatin-resistant

To construct a long noncoding RNA (lncRNA)–microRNA (miRNA)–messenger RNA (mRNA) regulatory network related to epithelial ovarian cancer (EOC) cisplatin-resistant, differentially expressed genes (DEGs), differentially expressed lncRNAs (DELs), and differentially expressed miRNAs (DEMs) between MDAH and TOV-112D cells lines were identified. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to analyze the biological functions of DEGs. Downstream mRNAs or upstream lncRNAs for miRNAs were analyzed at miRTarBase 7.0 or DIANA-LncBase V2, respectively. A total of 485 significant DEGs, 85 DELs, and 5 DEMs were identified. Protein–protein interaction (PPI) network of DEGs contrains 81 nodes and 141 edges was constructed, and 25 hub genes related to EOC cisplatin-resistant were identified. Subsequently, a lncRNA–miRNA–mRNA regulatory network contains 4 lncRNAs, 4 miRNAs, and 35 mRNAs was established. Taken together, our study provided evidence concerning the alteration genes involved in EOC cisplatin-resistant, which will help to unravel the mechanisms underlying drug resistant.     

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.     

Identification of lncRNA‐associated differential subnetworks in oesophageal squamous cell carcinoma by differential co‐expression analysis

Differential expression analysis has led to the identification of important biomarkers in oesophageal squamous cell carcinoma (ESCC). Despite enormous contributions, it has not harnessed the full potential of gene expression data, such as interactions among genes. Differential co‐expression analysis has emerged as an effective tool that complements differential expression analysis to provide better insight of dysregulated mechanisms and indicate key driver genes. Here, we analysed the differential co‐expression of lncRNAs and protein‐coding genes (PCGs) between normal oesophageal tissue and ESCC tissues, and constructed a lncRNA‐PCG differential co‐expression network (DCN). DCN was characterized as a scale‐free, small‐world network with modular organization. Focusing on lncRNAs, a total of 107 differential lncRNA‐PCG subnetworks were identified from the DCN by integrating both differential expression and differential co‐expression. These differential subnetworks provide a valuable source for revealing lncRNA functions and the associated dysfunctional regulatory networks in ESCC. Their consistent discrimination suggests that they may have important roles in ESCC and could serve as robust subnetwork biomarkers. In addition, two tumour suppressor genes (AL121899.1 and ELMO2), identified in the core modules, were validated by functional experiments. The proposed method can be easily used to investigate differential subnetworks of other molecules in other cancers.