Transcriptional profiling of exosomes derived from plasma of canine with mammary tumor by RNA-seq analysis

Canine mammary tumor (CMT) are the second most common tumor in dogs. Exosomes can act as biomarkers for the early diagnosis of tumors, and also be involved in the pathogenesis and metastasis mechanism of tumors. The expression profile of exosomal RNA revealed that there were a total of 5547 differentially expressed mRNAs, and 196 differentially expressed lncRNAs. GO and KEGG enrichment analysis found that the differentially expressed mRNAs and lncRNA target genes were associated with metabolic processes, DNA replication, cell proliferation, cell junction, and cell adhesion. In conclusion, this study revealed lncRNA and mRNA expression profiles in exosomes derived from plasma of CMT and further annotated their potential functions. The data obtained in this study will also provide valuable resources for understanding lncRNA information in plasma exosomes of dogs with CMT, and contribute to the study of early diagnostic markers and pathogenesis of CMT.     

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.     

Comprehensive analysis of lncRNA–miRNA–mRNA during proliferative phase of rat liver regeneration

This study aims to reveal the regulatory mechanism of lncRNAs–miRNAs–mRNAs network during the proliferative phase of liver regeneration (LR). High-throughput sequencing technology was performed, and a total of 1,738 differentially expressed lncRNAs (DE lncRNAs), 167 known differentially expressed miRNAs (DE miRNAs), and 2,727 differentially expressed mRNAs were identified. Then, the target DE lncRNAs and DE mRNAs regulated by the same miRNAs were screened and a ceRNA regulatory network containing 32 miRNAs, 107 lncRNAs, and 270 mRNAs was constructed. Insulin signaling pathway, pyrimidine metabolism, axon guidance, carbohydrate digestion and absorption, and pyruvate metabolism were significantly enriched in the network. Through literature review and the regulatory relationship between lncRNAs and miRNAs, nine core lncRNAs were identified, which might play important roles during the proliferative phase of rat LR. This study analyzed lncRNA–miRNA–mRNA regulatory network for the first time during the proliferative phase of rat LR, providing clues for exploring the mechanism of LR and the treatment of liver diseases.     

Expression profile of long non-coding RNAs in cervical spondylotic myelopathy of rats by microarray and bioinformatics analysis

IntroductionIt has been reported that a wide range of long non-coding RNAs (lncRNAs) are implicated in numerous diseases such as tumor, cardiopathy and neurological disorders. Identifying the differentially expressed (DE) profile of lncRNAs in cervical spondylotic myelopathy (CSM) is essential to understand the mechanisms of CSM.MethodsMicroarray assay, quantitative real-time PCR (qRT-PCR) and bioinformatics analysis were employed to reveal the DE profile and potential functions of lncRNAs in CSM.ResultsMicroarray analysis displayed the DE profiles of lncRNAs and mRNAs in rats between the CSM group and the control (CON) group. Thereinto, 1266 DE lncRNAs (738 up-regulation and 528 down-regulation) and 847 mRNAs (487 up-regulation and 360 down-regulation) with >1.1 fold change (FC) were finally identified. Moreover, 17 lncRNAs (13 up-regulation and 4 down-regulation) and 18 mRNAs (13 up-regulation and 5 down-regulation) were found deregulated by >2 FC. Further bioinformatics analysis showed the most remarkable biological processes among up-regulated RNAs contain cellular response to interferon-beta, inflammatory response and innate immune response, which may involve in CSM. Besides, related DE mRNAs of 17 DE lncRNAs in the genome were related to signaling pathway about NOD-like receptor, TNF, and apoptosis. In addition, a co-expression network of lncRNA-mRNA was established for analyzing the biological roles of lncRNAs. Among these, we found a ceRNA network related to CSM. Finally, the expressions of the DE lncRNAs and ceRNA network confirmed by qRT-PCR were in agreement with microarray data.ConclusionsOur study revealed the DE profiles of lncRNAs and mRNAs for CSM. Those dysregulated RNAs may represent potential therapeutic targets of CSM for further study.     

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.     

Impact of chronic intermittent hypoxia on the long non-coding RNA and mRNA expression profiles in myocardial infarction

Chronic intermittent hypoxia (CIH) is the primary feature of obstructive sleep apnoea (OSA), a crucial risk factor for cardiovascular diseases. Long non-coding RNAs (lncRNAs) in myocardial infarction (MI) pathogenesis have drawn considerable attention. However, whether CIH participates in the modulation of lncRNA profiles during MI is yet unclear. To investigate the influence of CIH on MI, cardiac damage was assessed by histology and echocardiography, and lncRNA and mRNA integrated microarrays were screened. MI mouse model showed myocardial hypertrophy, aggravated inflammation and fibrosis, and compromised left ventricle function under CIH. Compared with normoxia, 644 lncRNAs and 1084 differentially expressed mRNAs were identified following CIH for 4 weeks, whereas 1482 lncRNAs and 990 mRNAs were altered at 8 weeks. Strikingly, reoxygenation after CIH markedly affected 1759 lncRNAs and 778 mRNAs. Of these, 11 lncRNAs modulated by CIH were restored after reoxygenation and were validated by qPCR. The GO terms and KEGG pathways of genes varied significantly by CIH. lncRNA-mRNA correlation further showed that lncRNAs, NONMMUT032513 and NONMMUT074571 were positively correlated with ZEB1 and negatively correlated with Cmbl. The current results demonstrated a causal correlation between CIH and lncRNA alternations during MI, suggesting that lncRNAs might be responsible for MI aggravation under CIH.     

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 mitochondrial function‐associated lncRNAs in septic mice myocardium

The present study aimed to analyze long noncoding RNA (lncRNA) and messenger RNA (mRNA) expression profiles in septic mice heart and to identify potential lncRNAs and mRNAs that be responsible for cardiac mitochondrial dysfunction during sepsis. Mice were treated with 10 mg/kg of lipopolysaccharides to induce sepsis. LncRNAs and mRNAs expression were evaluated by using lncRNA and mRNA microarray or real‐time polymerase chain reaction technique. LncRNA‐mRNA coexpression network assay, Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed. The results showed that 1275 lncRNAs were differentially expressed in septic myocardium compared with those in the control group. A total of 2769 mRNAs were dysregulated in septic mice heart, most of which are mainly related to the process of inflammation, mitochondrial metabolism, oxidative stress, and apoptosis. Coexpression network analysis showed that 14 lncRNAs were highly correlated with 11 mitochondria‐related differentially expressed mRNA. Among all lncRNAs and their cis‐acting mRNAs, 41 lncRNAs‐mRNA pairs (such as NONMMUG004378 and Apaf1 gene) were enriched in GO terms and KEGG pathways. In summary, we gained some specific lncRNAs and their potential target mRNAs that might be involved in mitochondrial dysfunction in septic myocardium. These findings provide a panoramic view of lncRNA and might allow developing new treatment strategies for sepsis.     

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.     

A landscape of Long non-coding RNAs reveals the leading transcriptome alterations in murine aorta during aging

Considerable studies have given convincing evidence of a forefront position for vascular aging in preventing cardiovascular disease. Various functions of Long non-coding RNAs (lncRNAs) are becoming increasingly distinct in aging-related diseases. This study aims at a better insight into the expression profile and mechanisms of lncRNAs in vascular senescence. High-throughput sequencing was used to detect the differential expression (DE) of lncRNAs and mRNAs in the aorta of 96 W and 8 W-old mice, while 1423 lncRNAs and 80 mRNAs were differentially expressed. By performing GO and KEGG enrichment analysis, we found that DE lncRNAs were mainly involved in purine metabolism and cGMP-PKG signaling pathways. In addition, a co-expression functional network of DE lncRNAs and DE mRNAs was constructed, and ENSMUST00000218874 could interact with 41 DE mRNAs, suggesting that it may play an essential role in vascular senescence. This study reveals DE lncRNAs in naturally aging vascular, which may provide new ideas and targets for aging-related cardiovascular diseases.     

Five key lncRNAs considered as prognostic targets for predicting pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, and the 5‐year survival rate was only 7.7%. To improve prognosis, a screening biomarker for early diagnosis of pancreatic cancer is in urgent need. Long non‐coding RNA (lncRNA) expression profiles as potential cancer prognostic biomarkers play critical roles in development of tumorigenesis and metastasis of cancer. However, lncRNA signatures in predicting the survival of a patient with PDAC remain unknown. In the current study, we try to identify potential lncRNA biomarkers and their prognostic values in PDAC. LncRNAs expression profiles and corresponding clinical information for 182 cases with PDAC were acquired from The Cancer Genome Atlas (TCGA). A total of 14 470 lncRNA were identified in the cohort, and 175 PDAC patients had clinical variables. We obtained 108 differential expressed lncRNA via R packages. Univariate and multivariate Cox proportional hazards regression, lasso regression was performed to screen the potential prognostic lncRNA. Five lncRNAs have been recognized to significantly correlate with OS. We established a linear prognostic model of five lncRNA (C9orf139, MIR600HG, RP5‐965G21.4, RP11‐436K8.1, and CTC‐327F10.4) and divided patients into high‐ and low‐risk group according to the prognostic index. The five lncRNAs played independent prognostic biomarkers of OS of PDAC patients and the AUC of the ROC curve for the five lncRNAs signatures prediction 5‐year survival was 0.742. In addition, targeted genes of MIR600HG, C9orf139, and CTC‐327F10.4 were explored and functional enrichment was also conducted. These results suggested that this five‐lncRNAs signature could act as potential prognostic biomarkers in the prediction of PDAC patient's survival.     

Effect of emodin on long non-coding RNA-mRNA networks in rats with severe acute pancreatitis-induced acute lung injury

Long non-coding RNAs (lncRNAs) contribute to disease pathogenesis and drug treatment effects. Both emodin and dexamethasone (DEX) have been used for treating severe acute pancreatitis-associated acute lung injury (SAP-ALI). However, lncRNA regulation networks related to SAP-ALI pathogenesis and drug treatment are unreported. In this study, lncRNAs and mRNAs in the lung tissue of SAP-ALI and control rats, with or without drug treatment (emodin or DEX), were assessed by RNA sequencing. Results showed both emodin and DEX were therapeutic for SAP-ALI and that mRNA and lncRNA levels differed between untreated and treated SAP-ALI rats. Gene expression profile relationships for emodin-treated and control rats were higher than DEX-treated and -untreated animals. By comparison of control and SAP-ALI animals, more up-regulated than down-regulated mRNAs and lncRNAs were observed with emodin treatment. For DEX treatment, more down-regulated than up-regulated mRNAs and lncRNAs were observed. Functional analysis demonstrated both up-regulated mRNA and co-expressed genes with up-regulated lncRNAs were enriched in inflammatory and immune response pathways. Further, emodin-associated lncRNAs and mRNAs co-expressed modules were different from those associated with DEX. Quantitative polymerase chain reaction demonstrates selected lncRNA and mRNA co-expressed modules were different in the lung tissue of emodin- and DEX-treated rats. Also, emodin had different effects compared with DEX on co-expression network of lncRNAs Rn60_7_1164.1 and AABR07062477.2 for the blue lncRNA module and Nrp1 for the green mRNA module. In conclusion, this study provides evidence that emodin may be a suitable alternative or complementary medicine for treating SAP-ALI.     

Distinct Hippocampal Expression Profiles of Long Non-coding RNAs in an Alzheimer’s Disease Model

Alzheimer’s disease (AD), the most prevalent form of dementia worldwide, is a complex neurodegenerative disease characterized by the progressive loss of memory and other cognitive functions. The pathogenesis of AD is not yet completely understood. Although long non-coding RNAs (lncRNAs) have recently been shown to play a role in AD pathogenesis, the specific influences of lncRNAs in AD remain largely unknown; in particular, hippocampal lncRNA expression profiles in AD rats are lacking. In this study, microarray analysis was performed to investigate the hippocampal expression patterns of dysregulated lncRNAs in a rat model of AD. A total of 315 lncRNAs and 311 mRNAs were found to be significantly dysregulated in the AD model (≥2.0 fold, p < 0.05). Then, quantitative real-time PCR was used to validate the expression of selected lncRNAs and mRNAs. Bioinformatics tools and databases were employed to explore the potential lncRNA functions. This is the first study to comprehensively identify dysregulated hippocampal lncRNAs in AD and to demonstrate the involvement of different lncRNA expression patterns in the hippocampal pathogenesis of AD. This information will enable further research on the pathogenesis of AD and facilitate the development of novel AD therapeutics targeting lncRNAs.