Integrated analysis of long non-coding RNAs and mRNA expression profiles reveals the potential role of lncRNAs in gastric cancer pathogenesis

Exosomal MicroRNAs modulate the cognitive function in fasudil treated APPswe/PSEN1dE9 transgenic (APP/PS1) mice model of Alzheimer's disease

Alzheimer's disease (AD) is characterized by cognitive decline stemming from the accumulation of beta-amyloid (Aβ) plaques and the propagation of tau pathology through synapses. Exosomes, crucial mediators in neuronal development, maintenance, and intercellular communication, have gained attention in AD research. Yet, the molecular mechanisms involving exosomal miRNAs in AD remain elusive. In this study, we treated APPswe/PSEN1dE9 transgenic (APP/PS1) mice, a model for AD, with either vehicle (ADNS) or fasudil (ADF), while C57BL/6 (control) mice received vehicle (WT). Cognitive function was evaluated using the Y-maze test, and AD pathology was confirmed through immunostaining and western blot analysis of Aβ plaques and phosphorylated tau. Exosomal RNAs were extracted, sequenced, and analyzed from each mouse group. Our findings revealed that fasudil treatment improved cognitive function in AD mice, as evidenced by increased spontaneous alternation in the Y-maze test and reduced Aβ plaque load and phosphorylated tau protein expression in the hippocampus. Analysis of exosomal miRNAs identified three miRNAs (mmu-let-7i-5p, mmu-miR-19a-3p, mmu-miR-451a) common to both ADNS vs ADF and WT vs ADNS groups. Utilizing miRTarBase software, we predicted and analyzed target genes associated with these miRNAs. Gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of miRNA target genes indicated that mmu-miR-19a-3p and mmu-miR-451a are implicated in signal transduction, immune response, cellular communication, and nervous system pathways. Specifically, mmu-miR-19a-3p targeted genes involved in the sphingolipid signaling pathway, such as Pten and Tnf, while mmu-miR-451a targeted Nsmaf, Gnai3, and Akt3. Moreover, mmu-miR-451a targeted Myc in signaling pathways regulating the pluripotency of stem cells. In conclusion, fasudil treatment enhanced cognitive function by modulating exosomal MicroRNAs, particularly mmu-miR-451a and mmu-miR-19a-3p. These miRNAs hold promise as potential biomarkers and therapeutic targets for novel AD treatments.

Learning Association Characteristics by Dynamic Hypergraph and Gated Convolution Enhanced Pairwise Attributes for Prediction of Disease-Related lncRNAs

As the long non-coding RNAs (lncRNAs) play important roles during the incurrence and development of various human diseases, identifying disease-related lncRNAs can contribute to clarifying the pathogenesis of diseases. Most of the recent lncRNA-disease association prediction methods utilized the multi-source data about the lncRNAs and diseases. A single lncRNA may participate in multiple disease processes, and multiple lncRNAs usually are involved in the same disease process synergistically. However, the previous methods did not completely exploit the biological characteristics to construct the informative prediction models. We construct a prediction model based on adaptive hypergraph and gated convolution for lncRNA-disease association prediction (AGLDA), to embed and encode the biological characteristics about lncRNA-disease associations, the topological features from the entire heterogeneous graph perspective, and the gated enhanced pairwise features. First, the strategy for constructing hyperedges is designed to reflect the biological characteristic that multiple lncRNAs are involved in multiple disease processes. Furthermore, each hyperedge has its own biological perspective, and multiple hyperedges are beneficial for revealing the diverse relationships among multiple lncRNAs and diseases. Second, we encode the biological features of each lncRNA (disease) node using a strategy based on dynamic hypergraph convolutional networks. The strategy may adaptively learn the features of the hyperedges and formulate the dynamically evolved hypergraph topological structure. Third, a group convolutional network is established to integrate the entire heterogeneous topological structure and multiple types of node attributes within an lncRNA-disease-miRNA graph. Finally, a gated convolutional strategy is proposed to enhance the informative features of the lncRNA-disease node pairs. The comparison experiments indicate that AGLDA outperforms seven advanced prediction methods. The ablation studies confirm the effectiveness of major innovations, and the case studies validate AGLDA's ability in application for discovering potential disease-related lncRNA candidates.

Graph Reasoning Method Based on Affinity Identification and Representation Decoupling for Predicting lncRNA-Disease Associations

An increasing number of studies have shown that dysregulation of lncRNAs is related to the occurrence of various diseases. Most of the previous methods, however, are designed based on homogeneity assumption that the representation of a target lncRNA (or disease) node should be updated by aggregating the attributes of its neighbor nodes. However, the assumption ignores the affinity nodes that are far from the target node. We present a novel prediction method, GAIRD, to fully leverage the heterogeneous information in the network and the decoupled node features. The first major innovation is a random walk strategy based on width-first searching and depth-first searching. Different from previous methods that only focus on homogeneous information, our new strategy learns both the homogeneous information within local neighborhoods and the heterogeneous information within higher-order neighborhoods. The second innovation is a representation decoupling module to extract the purer attributes and the purer topologies. Third, a module based on group convolution and deep separable convolution is developed to promote the pairwise intrachannel and interchannel feature learning. The experimental results show that GAIRD outperforms comparing state-of-the-art methods, and the ablation studies prove the contributions of major innovations. We also performed case studies on 3 diseases to further demonstrate the effectiveness of the GAIRD model in applications.

Specific topology and topological connection sensitivity enhanced graph learning for lncRNA-disease association prediction

Predicting disease-related candidate long noncoding RNAs (lncRNAs) is beneficial for exploring disease pathogenesis due to the close relations between lncRNAs and the occurrence and development of human diseases. It is a long-term and challenging task to adequately extract specific and local topologies in individual lncRNA network and individual disease network, and integrate the information of the connection relationships. We propose a new graph learning-based prediction method to encode specific and local topologies from each individual network, neighbor topologies with different connection relationships, and pairwise attributes. We first construct a lncRNA network composed of all the lncRNA nodes and their similarities, and a single disease network that contains all the disease nodes and disease similarities. Then, a network-aware graph convolutional autoencoder is constructed to encode the specific and local topologies of each network. Secondly, a heterogeneous network is established to embed all lncRNA, disease, and miRNA nodes and their various connections. Afterwards, a connection-sensitive graph neural network is designed to deeply integrate the neighbor node attributes and connection characteristics in the heterogeneous network and learn neighbor topological representations. We also construct both connection-level and topology representation-level attention mechanisms to extract informative connections and topological representations. Finally, we build a multi-layer convolutional neural networks with weighted residuals to adaptively complement the detailed features to pairwise attribute encoding. Comprehensive experiments and comparison results demonstrated that NCPred outperforms seven state-of-the-art prediction methods. The ablation studies demonstrated the importance of local topology learning, neighbor topology learning, and pairwise attribute encoding. Case studies on prostate, lung, and breast cancers further revealed NCPred's capacity to screen potential candidate disease-related lncRNAs.

Epigenetic mechanisms of lncRNA in response to thermal stress during embryogenesis of allotetraploid Cyprinus carpio

Embryogenesis and epigenetic mechanisms of lncRNA may play an important role in the formation of temperature tolerance in allotetraploid Cyprinus carpio. To investigate the response of lncRNA to thermal stress during embryogenesis of C. carpio, transcriptome sequencing was performed on 81 embryo or larva samples from different early development stages and temperatures. We identified 45,097 lncRNAs and analyzed transcriptome variation during embryogenesis. Stage-specific and temperature-specific DE lncRNAs and DEGs were screened. GO and KEGG analysis identified numerous pathways involved in thermal stress. Temperature-specific regulation of cis-/trans-/antisense lncRNAs was analyzed. Interaction network analysis identified 6 hub lncRNAs and many hub genes, such as cdk1 and hsf1. Decreased expression of many essential genes regulated by lncRNAs may lead to the death of embryos at 33 °C. Our findings provide new insights into the regulation of lncRNA in thermal stress response during embryogenesis and contribute to the understanding of environmental adaptation of allotetraploid species.

Semantic Meta-Path Enhanced Global and Local Topology Learning for lncRNA-Disease Association Prediction

Since abnormal expression of long non-coding RNAs (lncRNAs) is associated with various human diseases, identifying disease-related lncRNAs helps reveal the pathogenesis of diseases. Existing methods for lncRNA-disease association prediction mainly focus on multi-sourced data related to lncRNAs and diseases. The rich semantic information of meta-paths, composed of multiple kinds of connections between lncRNA and disease nodes, is neglected. We propose a new prediction method, MGLDA, to encode and integrate the semantics of multiple meta-paths, the global topology of heterogeneous graph, and pairwise attributes of lncRNA and disease nodes. First, a tri-layer heterogeneous graph is constructed to associate multi-sourced data across the lncRNA, disease, and miRNA nodes. Afterwards, we establish multiple meta-paths connecting the lncRNA and disease nodes to derive and denote various semantics. Each meta-path contains its specific semantics formulated by an embedding strategy, and each embedding covers local topology formed by the diverse semantic connections among the lncRNA, disease, and miRNA nodes. We construct multiple graph convolutional autoencoders (GCA) with topology-level attention to learn global and multiple local topologies from the tri-layer graph and each meta-path, respectively. The topology-level attention mechanism can learn the importance of various global and local topologies for adaptive pairwise topology fusion. Finally, a convolutional autoencoder learns the attribute representations of lncRNA-disease pairs, which integrates the learnt detailed and representative pairwise features. Experimental results show that MGLDA outperforms other state-of-the-art prediction methods in comparison and retrieves more real lncRNA-disease associations in the top-ranked candidates. The ablation study also demonstrates the important contributions of the local and global topology learning, and pairwise attribute learning. Case studies on three diseases further demonstrate MGLDA's ability to identify potential disease-related lncRNAs.

Comprehensive analysis of aberrantly expressed circRNAs, mRNAs and lncRNAs in patients with nasopharyngeal carcinoma

BACKGROUND

The location of nasopharyngeal cancer is hidden, so it is difficult to diagnose at an early stage. In this study, we aimed to investigate the expression profiles of circRNAs, mRNAs and IncRNAs and to provide some basis for further studies.

METHODS

Expression profiles of circRNAs, mRNAs, and lncRNAs were analyzed using microarray techniques. The differentially expressed ncRNA was calculated by bioinformatics.

RESULTS

A total of 3048 circRNAs, 2179 lncRNAs, and 2015 mRNAs were detected to be significantly differentially expressed in NPC. The most upregulated circRNAs, lncRNAs, and mRNAs were hsa-circ-0067562, NONHSAT232922.1, and HOXB13, respectively. And, the most downregulated circRNAs, lncRNAs, and mRNAs were hsa_circ_0078837, lnc-TTC8-4:3, and LTF, respectively. The number of upregulated DE lncRNAs was more than twice than those downregulated. Our data showed that 80.44% of pairs of lncRNAs and cis-mRNAs demonstrated positive correlations. For lncRNAs and trans-mRNAs pairs, 53.7% of pairs showed positive correlation. LncRNA-mediated cis regulation is a prevalent regulatory mode in the development of nasopharyngeal carcinoma. CR1, LRMP and SORBS2 are predicted to be mediated not only by cis-acting lncRNA modes of action, but also by trans-acting lncRNA mechanisms. Additionally, we constructed a diagnostic prediction model with a high sensitivity and specificity.

CONCLUSION

Our study characterized the landscape of circRNAs, mRNAs and lncRNAs in NPC tissue and provided novel insights into the molecular mechanisms of NPC.

Cuproptosis-Related lncRNA Gene Signature Establishes a Prognostic Model of Gastric Adenocarcinoma and Evaluate the Effect of Antineoplastic Drugs

BACKGROUND

One of the most frequent malignancies of the digestive system is stomach adenocarcinoma (STAD). Recent research has demonstrated how cuproptosis (copper-dependent cell death) differs from other cell death mechanisms that were previously understood. Cuproptosis regulation in tumor cells could be a brand-new treatment strategy. Our goal was to create a cuproptosis-related lncRNA signature. Additionally, in order to evaluate the possible immunotherapeutic advantages and drug sensitivity, we attempted to study the association between these lncRNAs and the tumor immune microenvironment of STAD tumors.

METHODS

The TCGA database was accessed to download the RNA sequencing data, genetic mutations, and clinical profiles for TCGA STAD. To locate lncRNAs related to cuproptosis and build risk-prognosis models, three techniques were used: co-expression network analysis, Cox-regression techniques, and LASSO techniques. Additionally, an integrated methodology was used to validate the models' predictive capabilities. Then, using GO and KEGG analysis, we discovered the variations in biological functions between each group. The link between the risk score and various medications for STAD treatment was estimated using the tumor mutational load (TMB) and tumor immune dysfunction and rejection (TIDE) scores.

RESULT

We gathered 22 genes linked to cuproptosis based on the prior literature. Six lncRNAs related to cuproptosis were used to create a prognostic marker (AC016394.2, AC023511.1, AC147067.2, AL590705.3, HAGLR, and LINC01094). After that, the patients were split into high-risk and low-risk groups. A statistically significant difference in overall survival between the two groups was visible in the survival curves. The risk score was demonstrated to be an independent factor affecting the prognosis by both univariate and multivariate Cox regression analysis. Different risk scores were substantially related to the various immunological states of STAD patients, as further evidenced by immune cell infiltration and ssGSEA analysis. The two groups had differing burdens of tumor mutations. In addition, immunotherapy was more effective for STAD patients in the high-risk group than in the low-risk group, and risk scores for STAD were substantially connected with medication sensitivity.

CONCLUSIONS

We discovered a marker for six cuproptosis-associated lncRNAs linked to STAD as prognostic predictors, which may be useful biomarkers for risk stratification, evaluation of possible immunotherapy, and assessment of treatment sensitivity for STAD.

Learning global dependencies and multi-semantics within heterogeneous graph for predicting disease-related lncRNAs

Motivation

Long noncoding RNAs (lncRNAs) play an important role in the occurrence and development of diseases. Predicting disease-related lncRNAs can help to understand the pathogenesis of diseases deeply. The existing methods mainly rely on multi-source data related to lncRNAs and diseases when predicting the associations between lncRNAs and diseases. There are interdependencies among node attributes in a heterogeneous graph composed of all lncRNAs, diseases and micro RNAs. The meta-paths composed of various connections between them also contain rich semantic information. However, the existing methods neglect to integrate attribute information of intermediate nodes in meta-paths.

Results

We propose a novel association prediction model, GSMV, to learn and deeply integrate the global dependencies, semantic information of meta-paths and node-pair multi-view features related to lncRNAs and diseases. We firstly formulate the global representations of the lncRNA and disease nodes by establishing a self-attention mechanism to capture and learn the global dependencies among node attributes. Second, starting from the lncRNA and disease nodes, respectively, multiple meta-pathways are established to reveal different semantic information. Considering that each meta-path contains specific semantics and has multiple meta-path instances which have different contributions to revealing meta-path semantics, we design a graph neural network based module which consists of a meta-path instance encoding strategy and two novel attention mechanisms. The proposed meta-path instance encoding strategy is used to learn the contextual connections between nodes within a meta-path instance. One of the two new attention mechanisms is at the meta-path instance level, which learns rich and informative meta-path instances. The other attention mechanism integrates various semantic information from multiple meta-paths to learn the semantic representation of lncRNA and disease nodes. Finally, a dilated convolution-based learning module with adjustable receptive fields is proposed to learn multi-view features of lncRNA-disease node pairs. The experimental results prove that our method outperforms seven state-of-the-art comparing methods for lncRNA-disease association prediction. Ablation experiments demonstrate the contributions of the proposed global representation learning, semantic information learning, pairwise multi-view feature learning and the meta-path instance encoding strategy. Case studies on three cancers further demonstrate our method’s ability to discover potential disease-related lncRNA candidates.

Contact

zhang@hlju.edu.cn or peiliangwu@ysu.edu.cn

Supplementary information

Supplementary data are available at Briefings in Bioinformatics online.

The Antigastric Cancer Effect of Triptolide is Associated With H19/NF-κB/FLIP Axis

Background and Objective: Triptolide (TP), one of the fat-soluble components extracted from the Chinese medicinal herb Tripterygium wilfordii Hook F. (TWHF), possesses strong antitumor bioactivities, but its dose-dependent side effects restrict its wide application. This study was designed to investigate whether inflammatory factors increased the antitumor effects of the nontoxic dose of TP on gastric cancer cells and tried to explore the possible molecular mechanisms.

Method: AGS and MKN45 cells were treated with different doses of TP and TNF-α. Cell viability and apoptosis were detected in vitro. In addition, NF-κB mediated prosurvival signals and cytoprotective proteins, especially FLICE-inhibitory protein (FLIP), were detected to determine their effects on TP/TNF-α–induced apoptosis. Moreover, the function of lncRNA H19/miR-204-5p/NF-κB/FLIP axis was investigated in vitro, and the antigastric cancer effect of TP plus TNF-α was proved in the mice xenograft model.

Result:In vitro experimental results showed that TP pretreatment promoted apoptosis in AGS and MKN45 cells upon TNF-α exposure. TP/TNF-α–mediated apoptosis was partly mediated by the inhibitory effect of NF-κB–mediated FLIP expression. Oncogene H19 lying in the upstream pathway of NF-κB played a vital role upon TNF-α exposure, and bioinformatics analysis proved that H19 participated in TP/TNF-α–induced apoptosis via binding of miR-204-5p. Lastly, a low dose of TP and TNF-α inhibited the tumor weight and tumor volume of AGS and MKN45 cells in vivo.

Conclusion: TP pretreatment increased apoptosis in TNF-α–stimulated gastric cancer cells, which are dependent on the disruption of the H19/miR-204-5p/NF-κB/FLIP axis. Cotreatment of TP and TNF-α is a better option for enhancing the anticancer effect and lowering the side effect of TP.

A Long Noncoding RNA Derived from lncRNA-mRNA Networks Modulates Seed Vigor

The discovery of long noncoding RNAs (lncRNAs) has filled a great gap in our understanding of posttranscriptional gene regulation in a variety of biological processes related to plant stress responses. However, systematic analyses of the lncRNAs expressed in rice seeds that germinate under cold stress have been elusive. In this study, we performed strand-specific whole transcriptome sequencing in germinated rice seeds under cold stress and normal temperature. A total of 6258 putative lncRNAs were identified and expressed in a stage-specific manner compared to mRNA. By investigating the targets of differentially expressed (DE) lncRNAs of LT-I (phase I of low temperature)/NT-I (phase I of normal temperature), it was shown that the auxin-activated signaling pathway was significantly enriched, and twenty-three protein-coding genes with most of the members of the SAUR family located in chromosome 9 were identified as the candidate target genes that may interact with five lncRNAs. A seed vigor-related lncRNA, SVR, which interplays with the members of the SAUR gene family in cis was eventually identified. The CRISPR/Cas 9 engineered mutations in SVR cause delay of germination. The findings provided new insights into the connection between lncRNAs and the auxin-activated signaling pathway in the regulation of rice seed vigor.

Characterizing the landscape of cervical squamous cell carcinoma immune microenvironment by integrating the single-cell transcriptomics and RNA-Seq

Background

Cervical squamous cell carcinoma (CSCC), caused by the infection of high‐risk human papillomavirus, is one of the most common malignancies in women worldwide.

Methods

RNA expression data, including those from the Cancer Genome Atlas, Gene Expression Omnibus, and Genotype‐Tissue Expression databases, were used to identify the expression of RNAs in normal and tumor tissue. Correlation analysis was performed to identify the immune‐related long noncoding RNAs (IRLs) and hypoxia‐related genes (IRHs) that can influence the activity of the immune system. Prognosis models of immune‐related RNAs (IRRs) were used to construct a coexpression network of the immune system. We identified the role of IRRs in immunotherapy by correlation analysis with immune checkpoint genes (ICGs). We then validated the expression data by integrating two single‐cell sequencing data sets of CSCC to identify the key immune features.

Results

In total, six immune‐related gene (IRG), four IRL, and five IRH signatures that can significantly influence the characteristics of the tumor immune microenvironment (TIME) were selected using machine learning methods. The expression level of ICGs was significantly upregulated in GZMB⁺CD8⁺ T‐cells and tumor‐associated macrophages (TAMs) in tumor tissues. TGFBI⁺ TAMs are a kind of blood‐derived monocyte‐derived M0‐like TAM linked to hypoxia and a poor prognosis. IFI30⁺ M1‐like TAMs participate in the process of immune‐regulation and showed a role in the promotion of CD8⁺ T‐cells and Type 1 T helper (Th1)/Th2 cells in the coexpression network, together with several IRLs, IRGs, and ICGs.

Conclusions

CD16⁺ monocyte‐derived IFI30⁺ TAMs participated in our coexpression network to regulate the TIME, showing the potential to be a novel immunotherapy target. The enrichment of M0‐like TAMs was associated with a worse prognosis in the high‐risk score group with IRH signatures. Remarkably, M0‐like TAMs in tumor tissues overexpressed TGFBI and were associated with several well‐known tumor‐proliferation pathways.

Graph Triple-Attention Network for Disease-related LncRNA Prediction

Abnormal expressions of long non-coding RNAs (lncRNAs) are associated with various human diseases. Identifying disease-related lncRNAs can help clarify complex disease pathogeneses. The latest methods for lncRNA-disease association prediction rely on diverse data about lncRNAs and diseases. These methods, however, cannot adequately integrate the neighbour topological information of lncRNA and disease nodes. Moreover, more intrinsic features of lncRNA-disease node pairs can be explored to better predict the latent associations between lncRNAs and diseases. We developed a novel method, named GTAN, to predict the association propensities between lncRNAs and diseases. GTAN integrates various information about lncRNAs and diseases, including similarities, associations and interactions among lncRNAs, diseases and miRNAs, and exploits neighbour topology and attribute representations of a pair of lncRNA-disease nodes. We adopted in GTAN a graph neural network architecture with three attention mechanisms and multi-layer convolutional neural networks. First, a neighbour-level self-attention mechanism is constructed to learn the importance of each neighbour for an interested lncRNA or disease node. Second, topology-level attention is proposed to enhance contextual dependencies among multiple local topology representations of the lncRNA or disease node. An attention-enhanced graph neural network framework is then established to learn a topology representation of top-ranked neighbours for a pair of lncRNA-disease nodes. GTAN also has attribute-level attention to distinguish various contributions of attributes of the lncRNA-disease pair. Finally, attribute representation is learned by multi-layer CNN to integrate detailed features and representative features of the pair. Extensive experimental results demonstrated that GTAN outperformed state-of-the-art methods. The improved recall rates also showed GTANs capacity for retrieving more actual lncRNA-disease associations in the top-ranked candidates. The ablation studies confirmed the important contributions of three attention mechanisms. Case studies on lung cancer, prostate cancer and colon cancer further showed GTANs ability in discovering potential lncRNA candidates related to diseases.

Tumor Inhibitory Effect of Long Non-coding RNA LOC100505817 on Gastric Cancer

Gastric cancer (GC) is one of the major malignancies worldwide. Emerging evidence has revealed the potential involvement of long noncoding RNA (lncRNA) in human genetic disorders and cancer, but the role of LOC100505817 remains unknown. Thus, in this study, we isolated tissues from GC patients to characterize the functional importance of LOC100505817 in GC tumorigenesis. We also proposed a hypothesis that the regulation of Wnt/β-catenin pathway by LOC100505817 was regulated by miR-20a-mediated WT1. After the collection of cancer tissues and adjacent tissues were obtained from GC patients, expression of LOC100505817, Wnt/β-catenin pathway- and EMT-related genes was quantified. Ectopic expression and knockdown experiments were applied in order to investigate the protective role of LOC100505817 in the progression of GC. Subsequently, cell viability, flow cytometry for apoptosis and cell cycle were detected via CCK-8, while migration and invasion were determined using scratch test and Transwell assay respectively. Then interactions among LOC100505817, miR-20a and WT1 were explored by dual luciferase reporter gene assay, RNA pull down assay and RNA binding protein immunoprecipitation (RIP) assay. The results found poor expression LOC100505817 was poorly expressed in GC cells and tissues. Overexpressed LOC100505817 resulted in the significant reduction of cell proliferation, migration and invasion as well as the expression of Wnt2b, β-catenin, CyclinD1, N-cadherin, Vimentin and snail, while increased cell apoptosis along with the expression of E-cadherin. Wnt/β-catenin pathway and EMT in GC cells were suppressed by LOC100505817 through miR-20a-inhibted WT1. In summary, our results provided evidence suggesting that LOC100505817 inhibits GC through LOC100505817-mediated inhibition of Wnt/β-catenin pathway, that leads to the overall restraining of GC cell proliferation, migration and invasion through miR-20a-reduced WT1.

Transcriptome Analysis of lncRNA-mRNA Interactions in Chronic Atrophic Gastritis

The aim of this study was to identify prognosis-related differentially expressed lncRNAs and mRNAs in chronic atrophic gastritis (CAG). By analysis of high-throughput whole-transcriptome sequencing data, the levels of lncRNAs and mRNAs between CAG and chronic non-atrophic gastritis were compared pairwisely. In total, 97,282 lncRNA transcripts and 20,307 mRNA transcripts were acquired, including 50 upregulated and 66 downregulated lncRNAs and 377 upregulated and 763 downregulated mRNAs in CAG (p < 0.05, fold change ≥ 2). Moreover, the interactions of the differentially expressed genes in CAG were investigated by gene ontology enrichment analysis, showing that the enriched genes are involved in many biological processes, such as MAP kinase activity, heat generation, and protein modification processes. Through the construction of co-expression networks of the differentially expressed genes in CAG, three critical lncRNAs nodes were identified as potential key factors in CAG. Eight mRNAs common in both the co-expression network and the protein-protein interaction network were selected via Venn analysis, including DGKA, EIF6, HKDC1, DHRS11, 1, KRT15, TESPA1, and CDHR2. Finally, the expression levels of five differentially expressed lncRNAs in CAG were confirmed by quantitative real-time polymerase chain reaction. In conclusion, this study presents novel promising biomarkers for the diagnosis of CAG.

Identification of key long non-coding RNAs in gastric adenocarcinoma

BACKGROUND

Gastric cancer is the third leading cause of cancer-related deaths worldwide.

OBJECTIVE

The present study aims to identify key long non-coding RNAs (lncRNAs) and their potential roles in the pathogenesis of gastric adenocarcinoma.

METHODS

The lncRNA and mRNA expression profile between gastric adenocarcinoma and adjacent non-tumor tissues were obtained from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) between gastric adenocarcinoma and adjacent non-tumor tissues were identified after bioinformatics analysis. DElncRNA-DEmRNA co-expression network and DElncRNA-nearby DEmRNA interaction network were constructed, respectively. Functional annotation for DEmRNAs interacted with DElncRNAs was performed. Receiver operating characteristic (ROC) analysis of selected DElncRNAs was conducted.

RESULTS

Based on TCGA, the mRNA and lncRNA expression profiles of 375 gastric adenocarcinoma and 32 adjacent non-tumor tissues were downloaded. A total of 1502 DEmRNAs and 928 DElncRNAs between gastric adenocarcinoma and adjacent non-tumor tissues were identified. HOXC-AS3 might involve with gastric adenocarcinoma by regulating a set of HOX genes (HOXC8, HOXC9, HOXC10, HOXC11, HOXC12 and HOXC13) with cis-effect. AC115619.1-APOA4/APOB and AP006216.2-APOA1/APOA4 integrations might play roles in gastric adenocarcinoma through regulating pathways of Fat digestion and absorption and Vitamin digestion and absorption. Six lncRNAs including (HOTAIR, C20orf166-AS1, PGM5-AS1, HOXC-AS3, HOXC-AS2 and AC012531.1) have excellent diagnostic value for gastric adenocarcinoma.

CONCLUSIONS

This study identifies key lncRNAs in gastric adenocarcinoma which provides clues for exploring the pathogenesis and developing potential biomarkers for gastric adenocarcinoma.

lncRNA VIM‑AS1 promotes cell proliferation, metastasis and epithelial‑mesenchymal transition by activating the Wnt/β‑catenin pathway in gastric cancer

The present study aimed to explore the biological functions and molecular mechanisms of the long non-coding RNA VIM antisense RNA 1 (VIM-AS1) in gastric cancer (GC). The expression of VIM-AS1 was analyzed in tissues from patients with GC and GC cell lines by reverse transcription-quantitative (RT-q)PCR. The relationship between VIM-AS1 expression and overall survival time of patients with GC was also assessed. To determine the biological functions of VIM-AS1, Cell Counting Kit-8 assay, colony formation assay, flow cytometry, wound healing assay and Transwell assay were employed. The targeting relationship among VIM-AS1, microRNA (miR)-8052 and frizzled 1 (FZD1) was verified by the dual luciferase reporter gene assay. The underlying molecular mechanism of VIM-AS1 on GC was determined by RT-qPCR and western blotting. In addition, tumor formation was detected in nude mice. The results of the present study demonstrated that VIM-AS1 was highly expressed in GC tissues and cells. In addition, VIM-AS1 expression was demonstrated to be closely related to the prognosis of patients with GC. Notably, silencing VIM-AS1 inhibited the proliferation, migration and invasion, and enhanced apoptosis of AGS and HGC-27 cells. Silencing VIM-AS1 significantly increased the protein expression levels of cleaved caspase-3, Bax and E-cadherin, but decreased the protein expression levels of Bcl-2, N-cadherin, vimentin, matrix metalloproteinase (MMP)-2, MMP-9, β-catenin, cyclin D1, C-myc and FZD1. Additionally, silencing VIM-AS1 inhibited tumor growth in nude mice. Cumulatively, the present study demonstrated that VIM-AS1 may promote cell proliferation, migration, invasion and epithelial-mesenchymal transition by regulating FDZ1 and activating the Wnt/β-catenin pathway in GC.

Exosomal long non-coding RNA UCA1 functions as growth inhibitor in esophageal cancer

PURPOSE

Esophageal cancer is a highly lethal and broad-spreading malignant tumor worldwide. Exosome-carrying lncRNAs play an essential role in the pathogenesis of various cancers.

RESULTS

The results revealed that the expression of UCA1 was decreased in esophageal cancer tissues and plasma exosomes. UCA1 was enriched in exosomes, and exosomal UCA1 was a promising biomarker for the diagnosis of esophageal cancer with 86.7% sensitivity and 70.2% specificity. Overexpression of UCA1 played anticancer roles in esophageal cancer cells through inhibiting cell proliferation, invasion and migration, and colony formation. Also, exosomal UCA1 was taken up by esophageal cancer cells and inhibited the progression of esophageal cancer in vitro and tumor growth in vivo. Furthermore, exosomal UCA1 could directly target miRNA-613 in esophageal cancer cells.

CONCLUSIONS

The results suggested that exosomal UCA1 inhibits tumorigenesis and progression of esophageal cancer in vitro and in vivo, and might be a promising biomarker for esophageal cancer.

PATIENT AND METHODS

In this study, we determined the expression of UCA1 in esophageal cancer tissues, plasma exosomes of patients with esophageal cancer. We determined the potential of exosomal UCA1 as a biomarker and its effect on the pathogenesis and progression of esophageal cancer in vitro and in vivo.

Identification and characterization of long noncoding RNAs provide insight into the regulation of gene expression in response to heat stress in rainbow trout (Oncorhynchus mykiss)

Rainbow trout are typical cold-water fish species. However, with the intensification of global warming, high temperatures have severely restricted the development of aquaculture during the summer. Understanding the molecular regulatory mechanisms of rainbow trout responses to heat stress will be beneficial for alleviating heat stress-related damage. In this study, we performed RNA-seq of liver tissues from rainbow trout under heat stress (24 °C) and control conditions (18 °C) to identify lncRNAs and target genes by strand-specific library. Changes in nonspecific immune parameters revealed that a strong stress response occurred in rainbow trout at 24 °C. More than 658 million filtered reads and 5916 lncRNAs were identified from six libraries. A total of 927 novel lncRNAs were identified, and 428 differentially expressed lncRNAs were screened with stringent thresholds. The RNA-seq results were verified by RT-qPCR. In addition, a regulatory network of lncRNA-mRNA functional interactions was constructed, and the potential antisense, cis and trans targets of lncRNAs were predicted. GO and KEGG enrichment analyses showed that many target genes involved in maintenance of homeostasis or adaptation to stress and stimuli were highly induced under heat stress. Several regulatory pathways were also found to be involved in heat stress, including the thyroid hormone signaling pathway, the PI3K-Akt signaling pathway, and the estrogen signaling pathway, among others. These results broaden our understanding of lncRNAs associated with heat stress and provide new insights into the lncRNA mediated regulation of the rainbow trout heat stress response.

Identification and Annotation of Potential Function of Regulatory Antisense Long Non-Coding RNAs Related to Feed Efficiency in Bos taurus Bulls

Long non-coding RNAs (lncRNAs) can influence transcriptional and translational processes in mammalian cells and are associated with various developmental, physiological and phenotypic conditions. However, they remain poorly understood and annotated in livestock species. We combined phenotypic, metabolomics and liver transcriptomic data of bulls divergent for residual feed intake (RFI) and fat accretion. Based on a project-specific transcriptome annotation for the bovine reference genome ARS-UCD.1.2 and multiple-tissue total RNA sequencing data, we predicted 3590 loci to be lncRNAs. To identify lncRNAs with potential regulatory influence on phenotype and gene expression, we applied the regulatory impact factor algorithm on a functionally prioritized set of loci (n = 4666). Applying the algorithm of partial correlation and information theory, significant and independent pairwise correlations were calculated and co-expression networks were established, including plasma metabolites correlated with lncRNAs. The network hub lncRNAs were assessed for potential cis-actions and subjected to biological pathway enrichment analyses. Our results reveal a prevalence of antisense lncRNAs positively correlated with adjacent protein-coding genes and suggest their participation in mitochondrial function, acute phase response signalling, TCA-cycle, fatty acid β-oxidation and presumably gluconeogenesis. These antisense lncRNAs indicate a stabilizing function for their cis-correlated genes and a putative regulatory role in gene expression.

Roles of chicken growth hormone receptor antisense transcript in chicken muscle development and myoblast differentiation

Muscle is one of the important economic traits in poultry production, and its production depends on the increased number of muscle fibers during the embryonic stage. Chicken GHR gene can transcribe in double directions, possessing not only GHR-S but also GHR-AS. The 2 kinds of transcripts are partially complementation in sequences and interact with each other. Until now, the roles and mechanisms of GHR-AS in myoblast differentiation was still unknown. In this study, we not only analyzed the GHR-AS expression patterns in myoblast differentiation phase but also clarified that GHR-AS promoted myoblast differentiation via GH-GHR-IGF1 signal pathway. Quantitative PCR analysis indicated that GHR-AS was increased during myoblast differentiation. Sub-cellular localization showed that GHR-AS and GHR-S were expressed at a higher level in the nucleus than that in the cytoplasm. The expression of MyoD and MyHC and the myoblast differentiation significantly increased after GHR-AS overexpression, while the distance between wounds decreased, suggesting that GHR-AS repressed myoblast migration and promoted differentiation. Additionally, the expression of GHR -AS, IGF1 and MyHC increased after GH protein treated, and the myoblast differentiation also increased. In conclusion, GHR-AS promoted myoblast differentiation by enhancing fusion and inhibiting migration possibly via GH-GHR-IGF1 signal pathway.

Aberrant expressed long non-coding RNAs in laryngeal squamous-cell carcinoma

PURPOSE

Laryngeal squamous-cell carcinoma (LSCC) is the second most common malignant tumor of head and neck squamous cell carcinoma. The study was aimed to identify key long non-coding RNAs (lncRNAs) biomarkers for LSCC.

METHODS

Differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) between LSCC and adjacent tissues were obtained based on The Cancer Genome Atlas. DElncRNA-DEmRNAs co-expression and DElncRNA-nearby-target DEmRNA interaction networks were constructed. Receiver operating characteristic and survival analysis were performed. A published dataset were as used to validate the result of bioinformatics analysis.

RESULTS

We obtained 1103 DEmRNAs and 306 DElncRNAs between LSCC and adjacent tissues. A total of 338 DElncRNA-DEmRNA co-expression pairs and 229 DElncRNA-nearby-target DEmRNA pairs were obtained. Ten DElncRNAs and six DEmRNAs has great diagnostic value for LSCC. HOXB9 has potential prognostic value for LSCC. The results of GSE84957 validation were generally consistent with our results.

CONCLUSION

Our study provided clues for understanding the mechanism and developing potential biomarkers for LSCC.

Screening and evaluating of long non-coding RNAs in prenatal and postnatal pituitary gland of sheep

Long non-coding RNAs are transcribed into RNA molecules that are >200 nucleotides in length. However, the expression and function analysis of lncRNAs in the sheep pituitary gland are still lacking. In this study, we identified 1755 lncRNAs (545 annotated lncRNAs and 1210 novel lncRNAs) from RNA-seq data in the pituitary gland of embryonic and adult sheep. A total of 235 lncRNAs were differentially expressed between embryonic and adult group. We verified the presence of some lncRNAs using RT-PCR and DNA sequencing, and identified some differentially expressed lncRNAs using qPCR. We also investigated the role of cis-acting lncRNAs on target genes. GO and KEGG enrichment analysis revealed that the target genes of lncRNAs were involved in the regulation of hormones secretion and some signaling pathways in the sheep pituitary gland. Our study provides comprehensive expression profiles of lncRNAs and valuable resource for understanding their function in the pituitary gland.

Computational Analysis of lncRNA Function in Cancer

Long noncoding RNAs (lncRNAs) have been shown to play crucial roles in cancer biology. With the help of computational analysis illustrated here, the joint effects of lncRNAs and clinical variables can be quantified in a Cox model on cancer recurrence. Of importance, the predictive accuracy was then validated with the prognostic scores computed based on the suggested model. Further investigation of these potential lncRNAs would provide useful insights following the study of the mechanisms underlying the differential expression of these lncRNAs in association with and possibly contributing to cancer recurrence. Ultimately, the expanding knowledge of the function of lncRNAs curated by computational analysis will suggest new targets for cancer treatment.

LncRNAs with miRNAs in regulation of gastric, liver, and colorectal cancers: updates in recent years

Long noncoding RNA (lncRNA) is a kind of RNAi molecule composed of hundreds to thousands of nucleotides. There are several major types of functional lncRNAs which participate in some important cellular pathways. LncRNA-RNA interaction controls mRNA translation and degradation or serves as a microRNA (miRNA) sponge for silencing. LncRNA-protein interaction regulates protein activity in transcriptional activation and silencing. LncRNA guide, decoy, and scaffold regulate transcription regulators of enhancer or repressor region of the coding genes for alteration of expression. LncRNA plays a role in cellular responses including the following activities: regulation of chromatin structural modification and gene expression for epigenetic and cell function control, promotion of hematopoiesis and maturation of immunity, cell programming in stem cell and somatic cell development, modulation of pathogen infection, switching glycolysis and lipid metabolism, and initiation of autoimmune diseases. LncRNA, together with miRNA, are considered the critical elements in cancer development. It has been demonstrated that tumorigenesis could be driven by homeostatic imbalance of lncRNA/miRNA/cancer regulatory factors resulting in biochemical and physiological alterations inside the cells. Cancer-driven lncRNAs with other cellular RNAs, epigenetic modulators, or protein effectors may change gene expression level and affect the viability, immortality, and motility of the cells that facilitate cancer cell cycle rearrangement, angiogenesis, proliferation, and metastasis. Molecular medicine will be the future trend for development. LncRNA/miRNA could be one of the potential candidates in this category. Continuous studies in lncRNA functional discrepancy between cancer cells and normal cells and regional and rational genetic differences of lncRNA profiles are critical for clinical research which is beneficial for clinical practice.

A Multi-Cohort and Multi-Omics Meta-Analysis Framework to Identify Network-Based Gene Signatures

Although massive amounts of condition-specific molecular profiles are being accumulated in public repositories every day, meaningful interpretation of these data remains a major challenge. In an effort to identify the biomarkers that describe the key biological phenomena for a given condition, several approaches have been developed over the past few years. However, the majority of these approaches either (i) do not consider the known intermolecular interactions, or (ii) do not integrate molecular data of multiple types (e.g., genomics, transcriptomics, proteomics, epigenomics, etc.), and thus potentially fail to capture the true biological changes responsible for complex diseases (e.g., cancer). In addition, these approaches often ignore the heterogeneity and study bias present in independent molecular cohorts. In this manuscript, we propose a novel multi-cohort and multi-omics meta-analysis framework that overcomes all three limitations mentioned above in order to identify robust molecular subnetworks that capture the key dynamic nature of a given biological condition. Our framework integrates multiple independent gene expression studies, unmatched DNA methylation studies, and protein-protein interactions to identify methylation-driven subnetworks. We demonstrate the proposed framework by constructing subnetworks related to two complex diseases: glioblastoma and low-grade gliomas. We validate the identified subnetworks by showing their ability to predict patients' clinical outcome on multiple independent validation cohorts.

Chicken GHR antisense transcript regulates its sense transcript in hepatocytes

An increasing number of evidences indicated that long noncoding RNAs (LncRNAs) regulate a variety of biological progresses via different mechanisms. Our previous study had identified a chicken growth hormone receptor (GHR) antisense transcript (GHR-AS) which regulated GHR sense transcript (GHR-S) in LMH cells. In the present study, roles of GHR-AS and its regulatory mechanism were analyzed in chicken hepatocytes. The expression patterns of liver GHR-S, GHR-AS and Let-7b ascended with the development of chicken. The hepatocytes proliferation was promoted and more cells entered into DNA synthesis (S) phase when GHR-AS was overexpressed while the cell proliferation was slowed and fewer cells were in S phase when GHR-AS was interfered. Meanwhile, the GHR-S increased when we overexpressed GHR-AS while it reduced when GHR-AS was inhibited. The S1 Nuclease protection assay indicated that GHR-S and GHR-AS formed RNA duplex via GHR-S 3' untranslation regon (3'UTR). In hepatocytes or LMH cells, the half-time of GHR-S showed a delayed trend when GHR-AS or GHR-AS 5' untranslation regon (5'UTR) was overexpressed. Furthermore, the level of GHR-S can be decreased by Let-7b mimics whereas it was partially rescued when co-transfected pGHR-AS or pGHR-AS 5'UTR with Let-7b mimics. Based on our findings, GHR-AS affected hepatocytes proliferation and improved GHR-S stability possibly by forming RNA duplex between GHR-S and GHR-AS, competing with Let-7b.

Integrated analysis of long noncoding RNA and mRNA expression profiles reveals the potential role of long noncoding RNA in different bovine lactation stages

Long noncoding RNA (lncRNA) play a critical role in mammary development and breast cancer biology. Despite their important role in the mammary gland, little is known of the roles of lncRNA in bovine lactation, particularly regarding the molecular processes underlying it. To characterize the role of lncRNA in bovine lactation, 4 samples of Holstein cow mammary gland tissue at peak and late lactation stages were examined after biopsy. We then profiled the transcriptome of the mammary gland using RNA sequencing technology. Further, functional lncRNA-mRNA coexpression pairs were constructed to infer the function of lncRNA using a generalized linear model, followed by gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. More than 1,000 putative lncRNA were identified, 117 of which were differentially expressed between peak and late lactation stages. Bovine lncRNA were shorter, with fewer exon numbers, and expressed at significantly lower levels than protein-coding genes. Seventy-two differentially expressed (DE) lncRNA were coexpressed with 340 different protein-coding genes. The KEGG pathway analysis showed that target mRNA for DE lncRNA were mainly related to lipid and glucose metabolism, including the peroxisome proliferator-activated receptors and 5' adenosine monophosphate-activated protein kinase signaling pathways. Further bioinformatics and integrative analyses revealed that 12 DE lncRNA potentially played important roles in bovine lactation. Our findings provide a valuable resource for future bovine transcriptome studies, facilitate the understanding of bovine lactation biology, and offer functional information for cattle lactation.

Comparative Transcriptome Profiling Analysis of Red- and White-Fleshed Strawberry (Fragaria�ananassa) Provides New Insight into the Regulation of the Anthocyanin Pathway

Anthocyanins are water-soluble pigments in plants. They confer both economic and healthy profits for humans. To gain a deeper insight into the regulation of anthocyanin biosynthesis in octoploid strawberry (Fragaria�ananassa; Fa), a widely consumed economically important fruit, we performed comparative transcriptomic analysis of red- and white-fleshed strawberry cultivars in two ripening stages. In total, 365,455 non-redundant transcripts were assembled from the RNA sequencing (RNAseq) data. Of this collection, 377 were annotated as putative anthocyanin-related transcripts. Differential expression analysis revealed that 57 anthocyanin biosynthesis transcripts were down-regulated, and 89 transcription factors (TFs) were either down- or up-regulated under anthocyanin deficiency. Additionally, amongst the 50,601 putative long non-coding RNAs (lncRNAs) identified here, 68 lncRNAs were differentially expressed and co-expressed with differentially expressed anthocyanin-related mRNAs; 2,070 co-expressing lncRNA-mRNA pairs were generated. Expression profile analysis revealed that it was the limited expression of FaF3'H (flavonoid 3'-hydroxylase) that blocked the cyanidin 3-glucoside accumulation in the two investigated strawberry cultivars. This was further supported by a transient overexpression experiment with FaMYB10. The down-regulated lncRNAs might participate in anthocyanin regulation by acting as targets for microRNAs (miRNAs). The level of competitive intensity in miRNA and lncRNA for the same mRNA targets was probably lower in the white-fleshed strawberries, which can release the repression effect of the mRNAs in red-fleshed strawberry as a result. This study for the first time presents lncRNAs related to anthocyanins in strawberries, provides new insights into the anthocyanin regulatory network and also lays the foundation for identifying new anthocyanin regulators in strawberry.

Identification of cancer-related miRNA-lncRNA biomarkers using a basic miRNA-lncRNA network

LncRNAs are regulatory noncoding RNAs that play crucial roles in many biological processes. The dysregulation of lncRNA is thought to be involved in many complex diseases; lncRNAs are often the targets of miRNAs in the indirect regulation of gene expression. Numerous studies have indicated that miRNA-lncRNA interactions are closely related to the occurrence and development of cancers. Thus, it is important to develop an effective method for the identification of cancer-related miRNA-lncRNA interactions. In this study, we compiled 155653 experimentally validated and predicted miRNA-lncRNA associations, which we defined as basic interactions. We next constructed an individual-specific miRNA-lncRNA network (ISMLN) for each cancer sample and a basic miRNA-lncRNA network (BMLN) for each type of cancer by examining the expression profiles of miRNAs and lncRNAs in the TCGA (The Cancer Genome Atlas) database. We then selected potential miRNA-lncRNA biomarkers based on the BLMN. Using this method, we identified cancer-related miRNA-lncRNA biomarkers and modules specific to a certain cancer. This method of profiling will contribute to the diagnosis and treatment of cancers at the level of gene regulatory networks.

Identification and functional characterization of long non-coding RNAs in human gastric cancer

Abnormal regulation of long non-coding RNAs (lncRNAs) appears to be a primary feature of numerous types of human cancer. However, the association between the dysregulation of lncRNAs and functional alterations in gastric cancer (GC) remains unclear. In previous studies, we applied microarray and bioinformatics analyses to screen for key lncRNAs from the tumor tissues and matched adjacent non-tumor tissues of 10 patients with GC. There were seven key lncRNAs demonstrated to be significantly different between carcinoma tissues and adjacent non-tumor tissues. In the present study, the expression of these seven selected lncRNAs were validated in 82 patients with GC to further investigate the association between lncRNAs and GC clinical characterization. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) results demonstrated that RP5-919F19, MCPH1 antisense RNA 1 (CTD-2541M15) and urothelial carcinoma-associated 1 (UCA1) exhibited consistent upregulation in cancer compared with adjacent non-tumor tissues, whereas AP000459, LOC101928316, tumor suppressor candidate 8 (LINC01071) and maternally expressed 3 (MEG3) showed consistent downregulation. The results from the microarray and RT-qPCR experiments achieved 100% agreement. A correlation analysis indicated that RP5-919F19, LOC101928316 and MEG3 were significantly associated with tumor differentiation degree, RP5-919F19, UCA1 and MEG3 were significantly associated with lymph node metastasis, and RP5-919F19, CTD-2541M15 and UCA1 were significantly associated with tumor-node-metastasis stage (P<0.05). In addition, it was identified that the differential expression of LINC01071 and LOC101928316 significantly correlated with the age and gender of the GC patients, respectively (P<0.05). The results suggest that the lncRNAs RP5-919F19, LOC101928316, CTD-2541M15, UCA1 and MEG3 are closely associated with the invasion and metastasis of GC, which reveals these indicators as potential specificity biomarkers for the diagnosis, prognosis and classification of GC. Thus, these lncRNAs merit further study as novel candidate biomarkers for the clinical diagnosis of GC and as potential targets for therapy.

Genome-wide analysis of differentially expressed lncRNAs and mRNAs in primary gonadotrophin adenomas by RNA-seq

Recently, long non-coding RNAs (lncRNAs) have received increased research interest owing to their participation via distinct mechanisms in the biological processes of nonfunctional pituitary adenomas. However, changes in the expression of lncRNAs in gonadotrophin adenoma, which is the most common nonfunctional pituitary adenomas, have not yet been reported. In this study, we performed a genome-wide analysis of lncRNAs and mRNAs obtained from gonadotrophin adenoma patients’ samples and normal pituitary tissues using RNA-seq. The differentially expressed lncRNAs and mRNAs were identified using fold-change filtering. We identified 839 lncRNAs and 1015 mRNAs as differentially expressed. Gene Ontology analysis indicated that the biological functions of differentially expressed mRNAs were related to transcription regulator activity and basic metabolic processes. Ingenuity Pathway Analysis was performed to identify 64 canonical pathways that were significantly enriched in the tumor samples. Furthermore, to investigate the potential regulatory roles of the differentially expressed lncRNAs on the mRNAs, we constructed general co-expression networks for 100 coding and 577 non-coding genes that showed significantly correlated expression patterns in tumor cohort. In particular, we built a special sub-network of co-expression involving 186 lncRNAs interacting with 15 key coding genes of the mTOR pathway, which might promote the pathogenesis of gonadotrophin tumor. This is the first study to explore the patterns of genome-wide lncRNAs expression and co-expression with mRNAs, which might contribute to the molecular pathogenesis of gonadotrophin adenoma.

Long non-coding RNA BCYRN1 promotes the proliferation and metastasis of cervical cancer via targeting microRNA-138 in vitro and in vivo

Cervical cancer is one of the most malignant types of tumor and the fourth leading cause of cancer-associated mortality in females worldwide. High expression of brain cytoplasmic RNA 1 (BCYRN1) has been detected in various tumors. The present study aimed to investigate the effect of BCYRN1 in the viability and motility of cervical cancer, and the relevant mechanism. The results demonstrated that BCYRN1 was upregulated in cervical cancer tissues compared with normal tissues. Elevated levels of BCYRN1 were also detected in three human cervical cancer cell lines (SiHa, HeLa and CaSki) compared with non-cancerous ectocervical epithelial cell line (Ect1/E6E7). The expression of BCYRN1 was suppressed following transfection with small interfering RNA (siRNA) in HeLa cells. The silence of BCYRN1 significantly reduced cell viability and motility. Furthermore, microRNA (miR)-138 was predicted as a direct target of BCYRN1 and the expression of miR-138 was elevated in HeLa cells transfected with BCYRN1 siRNA. Subsequently, elevated levels of miR-138 were suppressed by transfection with miR-138 inhibitor in HeLa cells pretreated with BCYRN1 siRNA. The targeting association between BCYRN1 and miR-138 was supported by luciferase reporter assays. Additionally, BCYRN1 siRNA partially counteracted the effect of miR-138 inhibitor on promoting cell viability and mobility in HeLa cells. Finally, the in vivo experiment verified that BCYRN1 siRNA was able to prevent tumor growth, and reduced the expression of migration marker proteins metalloproteinase 2 and vascular endothelial cell growth factor, with enhanced expression levels of miR-138. These results suggest that lncRNA BCYRN1 promotes the proliferation and invasion of cervical cancer via targeting miR-138.

Anti-cancer effect of low dose of celecoxib may be associated with lnc-SCD-1:13 and lnc-PTMS-1:3 but not COX-2 in NCI-N87 cells

In order to investigate the mechanism of celecoxib and whether long non-coding RNAs (lncRNAs) were involved in the effects of celecoxib treatment in NCI-N87 cells, NCI-N87 cells were treated with 15, 30 and 60 µM celecoxib and an MTT assay was performed to assess cell viability. Following treatment with 15 µM celecoxib, the cell cycle and apoptosis were analyzed by flow cytometry, and the mRNA levels of lnc-SCD-1:13, lnc-PTMS-1:3, cyclooxygenase-2 (COX-2), integrin α3 (ITGA3) and DSH homolog 1 (DVL1) were detected by reverse transcription quantitative PCR (RT-qPCR) in NCI-N87 cells. MTT analysis demonstrated that celecoxib significantly inhibited cell viability in treated cells compared with untreated cells. Flow cytometry analysis revealed that, compared with untreated cells, the percentage of cells in the G0/G1 phase was significantly increased, and the percentage of cells in the S and G2 phase was decreased. In addition, the percentage of early and late apoptotic cells was increased in cells treated with 15 µM celecoxib compared with the control. RT-qPCR analysis also demonstrated that the mRNA levels of lnc-SCD-1:13, lnc-PTMS-1:3, ITGA3 and DVL1 were increased following treatment with celecoxib (15 µM; P<0.05). However, there were no significant differences in the expression of COX-2 mRNA between cells treated with celecoxib (15 µM) and untreated cells. The present study demonstrated that a low dose of celecoxib may be involved in regulating cell growth independent of COX-2 in NCI-N87 cells. Furthermore, ITGA3 and/or DVL1 co-expressed with lnc-SCD-1:13 and lnc-PTMS-1:3 may be associated with the effects of treatment with a low dose of celecoxib in NCI-N87 cells.

Long non-coding RNA MSTO2P promotes the proliferation and colony formation in gastric cancer by indirectly regulating miR-335 expression

Long non-coding RNAs are emerging as new players in gene regulation, but whether long non-coding RNAs influence the expression of microRNA is unclear. The expression levels of misato family member 2, pseudogene were significantly associated with lymphatic metastasis and distal metastasis in 80 paired gastric cancer tissues using real-time quantitative reverse transcription polymerase chain reaction experiments. The effects of long non-coding RNA misato family member 2, pseudogene were assessed by overexpressing or downexpressing long non-coding RNA misato family member 2, pseudogene in gastric cancer cells. Long non-coding RNA misato family member 2, pseudogene promoted gastric cancer cell growth, colony formation, migration, and invasion in gastric cancer cells. Long non-coding RNA misato family member 2, pseudogene influenced biologic functions in gastric cancer cells via indirectly regulating the activation of miR-335. Our results reveal long non-coding RNA misato family member 2, pseudogene as an oncogenic long non-coding RNA that promotes cell growth and invasion. Therefore, long non-coding RNAs might function as key regulatory hubs in gastric cancer progression.

The long noncoding RNA, TINCR, functions as a competing endogenous RNA to regulate PDK1 expression by sponging miR-375 in gastric cancer

BACKGROUND

Accumulating evidence indicates that the long noncoding RNA, TINCR, plays a critical role in cancer progression and metastasis. However, the overall biological role and mechanisms of TINCR that were involved in human gastric cancer (GC) progression remain largely unknown.

METHODS

TINCR expression was measured in 56 paired tumor and adjacent nontumor tissue samples by real-time polymerase chain reaction (PCR). Insights of the mechanism of competitive endogenous RNAs (ceRNAs) were gained from bioinformatic analysis, luciferase assays. The effects of TINCR and miR-375 on GC cell apoptosis and proliferation were studied by RNA interference approaches in vitro and in vivo. The correlation of TINCR and PDK1 was identified by real-time PCR and Western blot analysis.

RESULTS

Our results showed that miR-375 level decreased and TINCR level increased in tumor tissues. In addition, TINCR was a target of miR-375 and inhibited its expression in GC cells. Furthermore, the low expression of TINCR increased cell apoptosis and inhibited the proliferation of GC cells, while the downregulation of miR-375 reversed the function. In particular, TINCR could negatively regulate the miR-375 expression and increased the PDK1 expression in GC cells. Finally, tumor growth suppression was retarded with miR-375 downregulated in TINCR knockdown of GC cell xenografts.

CONCLUSION

The long noncoding RNA TINCR functions as a competing endogenous RNA to regulate PDK1 expression by sponging miR-375 in GC. The ceRNA regulatory network of TINCR/miR-375/PDK1 allows us to better understand the pathogenesis of GC and facilitate the development of long noncoding RNA (lncRNA)-directed diagnostics in GC.

Long non-coding RNA C5orf66-AS1 is downregulated in pituitary null cell adenomas and is associated with their invasiveness

Pituitary null cell adenoma is a challenging clinical condition, and its pathogenesis remains to be elucidated. We performed this study to determine the roles of C5orf66-AS1, NORAD, and TINCR in the pathogenesis and invasion of pituitary null cell adenomas. Expression of the three long non-coding RNAs in pituitary null cell adenoma tissues of 11 patients and normal pituitary tissues from four donors was examined by performing quantitative reverse transcription-polymerase chain reaction. We found that C5orf66-AS1 expression was lower in pituitary null cell adenoma tissues than in normal pituitary tissues. Moreover, C5orf66-AS1 expression level was significantly lower in invasive pituitary null cell adenomas than in non-invasive ones. After transfection of C5orf66-AS1 into pituitary adenoma cells, assessment of cell viability and invasion suggested that overexpressed C5orf66-AS1 inhibited cell viability and cell invasion. In silico algorithms predicted several cis- and trans-acting target genes of C5orf66-AS1, including PITX1 and SCGB3A1. In addition, expression of some of the predicted target genes was determined using microarray data of another cohort with pituitary null cell adenomas. It showed that some of these target genes were differentially expressed between pituitary null cell adenoma tissues and normal pituitary tissues as well as between invasive and non-invasive tumors. Co-expression analysis in RNA sequencing data showed that PAQR7 was the most correlated gene of C5orf66-AS1 and that several predicted trans-acting target genes, including SCGB3A1, were highly correlated with C5orf66-AS1. NORAD and TINCR expression was not statistically significant in the complete cohort; however, a negative correlation was observed between NORAD expression and maximum tumor diameter in some subgroups. These results indicate that C5orf66-AS1 suppresses the development and invasion of pituitary null cell adenomas. However, our results do not provide enough statistical evidence to support the roles of NORAD and TINCR in the development and invasion of pituitary null cell adenomas.

Deregulated lncRNAs in B Cells from Patients with Active Tuberculosis

Role of lncRNAs in human adaptive immune response to TB infection is largely unexplored. To address this issue, here we characterized lncRNA expression profile in primary human B cell response to TB infection using microarray assay. Several lncRNAs and mRNAs were chosen for RT-qPCR validation. Bioinformatics prediction was applied to delineate function of the deregulated mRNAs. We found that 844 lncRNAs and 597 mRNAs were differentially expressed between B cell samples from individuals with or without TB. KEGG pathway analysis for the deregulated mRNAs indicated a number of pathways, such as TB, TLR signaling pathway and antigen processing and presentation. Moreover, corresponding to the dysregulation of many lncRNAs, we also found that their adjacent protein-coding genes were also deregulated. Functional annotation for the corresponding mRNAs showed that these lncRNAs were mainly associated with TLR signaling, TGF-β signaling. Interestingly, SOCS3, which is a critical negative regulator of cytokine response to TB infection and its nearby lncRNA XLOC_012582, were highly expressed in active TB B cells. Subsequent RT-qPCR results confirmed the changes. Whether upregulated XLOC_012582 causes SOCS3 overexpression and is eventually involved in the context of exacerbations of active TB represents an interesting issue that deserves to be further explored. Taken together, for the first time, we identified a set of deregulated lncRNAs in active TB B cells and their functions were predicted. Such findings provided novel insight into the pathogenesis of TB and further studies should focus on the function and pathogenic mechanisms of the lncRNAs involved in active TB.

Molecular mechanisms of long noncoding RNAs on gastric cancer

Long noncoding RNAs (lncRNAs) are non-protein coding transcripts longer than 200 nucleotides. Aberrant expression of lncRNAs has been found associated with gastric cancer, one of the most malignant tumors. By complementary base pairing with mRNAs or forming complexes with RNA binding proteins (RBPs), some lncRNAs including GHET1, MALAT1, and TINCR may mediate mRNA stability and splicing. Other lncRNAs, such as BC032469, GAPLINC, and HOTAIR, participate in the competing endogenous RNA (ceRNA) network. Under certain circumstances, ANRIL, GACAT3, H19, MEG3, and TUSC7 exhibit their biological roles by associating with microRNAs (miRNAs). By recruiting histone-modifying complexes, ANRIL, FENDRR, H19, HOTAIR, MALAT1, and PVT1 may inhibit the transcription of target genes in cis or trans. Through these mechanisms, lncRNAs form RNA-dsDNA triplex. CCAT1, GAPLINC, GAS5, H19, MEG3, and TUSC7 play oncogenic or tumor suppressor roles by correlated with tumor suppressor P53 or onco-protein c-Myc, respectively. In conclusion, interaction with DNA, RNA and proteins is involved in lncRNAs' participation in gastric tumorigenesis and development.

Co-expressed differentially expressed genes and long non-coding RNAs involved in the celecoxib treatment of gastric cancer: An RNA sequencing analysis

The aim of the present study was to investigate the mechanisms of long non-coding RNAs (lncRNAs) in a gastric cancer cell line treated with celecoxib. The human gastric carcinoma cell line NCI-N87 was treated with 15 µM celecoxib for 72 h (celecoxib group) and an equal volume of dimethylsulfoxide (control group), respectively. Libraries were constructed by NEBNext Ultra RNA Library Prep kit for Illumina. Paired-end RNA sequencing reads were aligned to a human hg19 reference genome using TopHat2. Differentially expressed genes (DEGs) and lncRNAs were identified using Cuffdiff. Enrichment analysis was performed using GO-function package and KEGG profile in Bioconductor. A protein-protein interaction network was constructed using STRING database and module analysis was performed using ClusterONE plugin of Cytoscape. ATP5G1, ATP5G3, COX8A, CYC1, NDUFS3, UQCRC1, UQCRC2 and UQCRFS1 were enriched in the oxidative phosphorylation pathway. CXCL1, CXCL3, CXCL5 and CXCL8 were enriched in the chemokine signaling and cytokine-cytokine receptor interaction pathways. ITGA3, ITGA6, ITGB4, ITGB5, ITGB6 and ITGB8 were enriched in the integrin-mediated signaling pathway. DEGs co-expressed with lnc-SCD-1:13, lnc-LRR1-1:2, lnc-PTMS-1:3, lnc-S100P-3:1, lnc-AP000974.1-1:1 and lnc-RAB3IL1-2:1 were enriched in the pathways associated with cancer, such as the basal cell carcinoma pathway in cancer. In conclusion, these DEGs and differentially expressed lncRNAs may be important in the celecoxib treatment of gastric cancer.

Exploring the role of molecular biomarkers as a potential weapon against gastric cancer: A review of the literature

Gastric cancer (GC) is a global health problem and a major cause of cancer-related death with high recurrence rates ranging from 25% to 40% for GC patients staging II-IV. Unfortunately, while the majority of GC patients usually present with advanced tumor stage; there is still limited evidence-based therapeutic options. Current approach to GC management consists mainly of; endoscopy followed by, gastrectomy and chemotherapy or chemo-radiotherapy. Recent studies in GC have confirmed that it is a heterogeneous disease. Many molecular characterization studies have been performed in GC. Recent discoveries of the molecular pathways underlying the disease have opened the door to more personalized treatment and better predictable outcome. The identification of molecular markers is a useful tool for clinical managementin GC patients, assisting in diagnosis, evaluation of response to treatment and development of novel therapeutic modalities. While chemotherapeutic agents have certain physiological effects on the tumor cells, the prediction of the response is different from one type of tumor to the other. The specificity of molecular biomarkers is a principal feature driving their application in anticancer therapies. Here we are trying to focus on the role of molecular pathways of GC and well-established molecular markers that can guide the therapeutic management.

Integrated analysis of long non-coding RNA competing interactions reveals the potential role in progression of human gastric cancer

Abnormal expression of long non-coding RNAs (lncRNAs) have been shown to play an important role in tumor biology. The Cancer Genome Atlas (TCGA) platform is a large sample sequencing database of lncRNAs, and further analysis of the associations between these data and patients' clinical related information can provide new approaches to find the functions of lncRNA. In the present study, 361 RNA sequencing profiles of gastric cancer (GC) patients were selected from TCGA. Then, we constructed the lncRNA-miRNA-mRNA competitive endogenous RNA (ceRNA) network of GC. There were 25 GC specific lncRNAs (fold change >2, p<0.05) identified, 19 of them were included in ceRNA network. Subsequently, we selected these 19 key lncRNAs and analyzed the correlations with clinical features and overall survival, 14 of them were discriminatively expressed with tumor size, tumor grade, TNM stage and lymphatic metastasis (p<0.05). In addition, eight lncRNAs (RPLP0P2, FOXD2-AS1, H19, TINCR, SLC26A4-AS1, SMIM10L2A, SMIM10L2B and SNORD116-4) were found to be significantly associated with overall survival (log-rank p<0.05). Finally, two key lncRNAs HOTAIR and UCA1 were selected for validation of their expression levels in 82 newly diagnosed GC patients by qRT-PCR. Results showed that the fold changes between TCGA and qRT-PCR were 100% in agreement. In addition, we also found that HOTAIR was significantly correlated with tumor size and lymphatic metastasis (p<0.05), and UCA1 was significantly correlated with tumor size, TNM stage and lymphatic metastasis (p<0.05). The clinical relevance of the two lncRNAs and the bioinformatics analysis results were almost the same. Overall, our study showed the GC specific lncRNAs expression patterns and a ceRNA network in GC. Clinical features related to GC specific lncRNAs also suggested these lncRNAs are worthwhile for further study as novel candidate biomarkers for the clinical diagnosis of GC and potential indicators for prognosis.

Identification of differentially expressed signatures of long non-coding RNAs associated with different metastatic potentials in gastric cancer

BACKGROUND

Gastric cancer (GC) is known for its lymph node metastasis and outstanding morbidity and mortality. Thus, improvement in the current knowledge regarding the molecular mechanism of GC is urgently needed to discover novel biomarkers involved in its progression and prognosis. Several long, non-coding RNAs (lncRNAs) play important roles in gastric tumorigenesis and metastasis. However, the signature of lncRNA-associated metastasis in GC is not fully clarified.

METHODS

We determined the lncRNA and mRNA expression profiles correlating to GC with or without lymph node-metastasis based on microarray analysis. Twelve differentially expressed lncRNAs and six differentially expressed mRNAs were validated by real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) assay.

RESULTS

The relationships between the aberrantly expressed lncRNAs XLOC_010235 or RP11-789C1.1 and lymph node metastasis, pathologic metastasis status, distal metastasis and TNM (tumour, node, and metastasis) stage were found to be significantly different. Via survival analysis, patients who had high-expressed XLOC_010235 or low-expressed RP11-789C1.1 showed significantly worse survival than patients with inverse-expressed XLOC_010235 or RP11-789C1.1.

CONCLUSION

In summary, this current study highlights some evidence regarding the potential role of lncRNAs in GC and posits that specific lncRNAs can be identified as novel, poor prognostic biomarkers in GC.

Circulating microRNAs and long non-coding RNAs in gastric cancer diagnosis: An update and review

Gastric cancer (GC) is the fourth most common cancer and the third leading cause of cancer mortality worldwide. MicroRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are the most popular non-coding RNAs in cancer research. To date, the roles of miRNAs and lncRNAs have been extensively studied in GC, suggesting that miRNAs and lncRNAs represent a vital component of tumor biology. Furthermore, circulating miRNAs and lncRNAs are found to be dysregulated in patients with GC compared with healthy individuals. Circulating miRNAs and lncRNAs may function as promising biomarkers to improve the early detection of GC. Multiple possibilities for miRNA secretion have been elucidated, including active secretion by microvesicles, exosomes, apoptotic bodies, high-density lipoproteins and protein complexes as well as passive leakage from cells. However, the mechanism underlying lncRNA secretion and the functions of circulating miRNAs and lncRNAs have not been fully illuminated. Concurrently, to standardize results of global investigations of circulating miRNAs and lncRNAs biomarker studies, several recommendations for pre-analytic considerations are put forward. In this review, we summarize the known circulating miRNAs and lncRNAs for GC diagnosis. The possible mechanism of miRNA and lncRNA secretion as well as methodologies for identification of circulating miRNAs and lncRNAs are also discussed. The topics covered here highlight new insights into GC diagnosis and screening.

Long noncoding ribonucleic acid specific for distant metastasis of gastric cancer is associated with TRIM16 expression and facilitates tumor cell invasion in vitro

BACKGROUND AND AIM

Increasing evidence has indicated that long noncoding ribonucleic acids (lncRNAs) play a major role in cancers. Although certain lncRNAs has been reported to play a role in gastric cancer (GC), specific lncRNAs involved in distant metastasis of GC remain unknown.

METHODS

Differentially expressed mRNAs and lncRNAs between stage IV and non-stage IV GC were obtained by microarray. Gene ontology and pathway analysis were used to study functions of differential mRNAs. Algorithms were used to predict potential gene targets of cis or trans-acting lncRNAs. Network analysis was performed to analyze each pair of gene-lncRNA, gene-gene, or lncRNA-lncRNA interactions. Expression of lncRNA special for distant metastasis of GC (SDMGC) and target gene TRIM16 were tested in GC tissues and cell lines. RNAi and overexpression were used to observe the biological functions of SDMGC and TRIM16 on GC cells.

RESULTS

502 mRNAs and 440 lncRNAs were found to be differentially expressed. 74 gene ontology terms and 38 pathways were associated with the dysregulated transcripts. Fourteen core factors were determined by network analysis. Expression of SDMGC and TRIM16 was upregulated in the distant metastasis tissues, compared with primary GC tissues, which were positive correlation. Silencing of SDMGC or TRIM16 was demonstrated to decrease cell invasion and migration, while upregulated of SDMGC or TRIM16 could promote cell invasion and migration. However, little effect on proliferation, cell cycle, colony formation, and apoptosis was found.

CONCLUSIONS

SDMGC is obviously upregulated in stage IV GC and may represent a new marker and therapeutic target for GC treatment.

LncRNAs: emerging biomarkers in gastric cancer

Long noncoding RNAs (lncRNAs) recently have been recognized as having a critical role in cancer development and progression. Gastric cancer remains a major clinical challenge worldwide owing to poor prognosis and limited treatment options. Accumulating studies have demonstrated that lncRNAs may play an active role in tumorigenesis, metastasis, prognosis and drug resistance of gastric cancer. Here, we collect recent knowledge to show differential expression of lncRNA in gastric cancer and their underlying mechanism of activities in gastric cancer involved in epigenetic, transcription and post-transcriptional processing. This review focuses on the regulation and function of gastric cancer-related lncRNAs and provides an overview of current effects to exploit them to be potential biomarkers and therapeutic targets for gastric cancer.

Long non-coding RNA Linc00152 is involved in cell cycle arrest, apoptosis, epithelial to mesenchymal transition, cell migration and invasion in gastric cancer

Gastric cancer remains a serious threat to public health with high incidence and mortality worldwide. Accumulating evidence demonstrates that long non-coding RNAs (lncRNAs) play important roles in regulating gene expression and are involved in various pathological processes, including gastric cancer. To investigate the possible role of dysregulated lncRNAs in gastric cancer development, we performed lncRNA microarray and identified 3141 significantly differentially expressed lncRNAs in gastric cancer tissues. Next, some of deregulated lncRNAs were validated among about 60 paired gastric cancer specimens such as Linc00261, DKFZP434K028, RPL34-AS1, H19, HOTAIR and Linc00152. Our results found that the decline of DKFZP434K028 and RPL34-AS1, and the increased expression of Linc00152 positively correlated with larger tumor size. The high expression levels of HOTAIR were associated with lymphatic metastasis and poor differentiation. Since the biological roles of Linc00152 are largely unknown in gastric cancer pathogenesis, we assessed its functions by silencing its up-regulation in gastric cancer cells. We found that Linc00152 knockdown could inhibit cell proliferation and colony formation, promote cell cycle arrest at G1 phase, trigger late apoptosis, reduce the epithelial to mesenchymal transition (EMT) program, and suppress cell migration and invasion. Taken together, we delineate the gastric cancer lncRNA signature and demonstrate the oncogenic functions of Linc00152. These findings may have implications for developing lncRNA-based biomarkers for diagnosis and therapeutics for gastric cancer.

Long Noncoding RNA in Digestive Tract Cancers: Function, Mechanism, and Potential Biomarker

Digestive tract cancers (DTCs) are a leading cause of cancer-related death worldwide. Current therapeutic tools for advanced stage DTCs have limitations, and patients with early stage DTCs frequently have a missed diagnosis due to shortage of efficient biomarkers. Consequently, it is necessary to develop novel biomarkers for early diagnosis and novel therapeutic targets for treatment of DTCs. In recent years, long noncoding RNAs (lncRNAs), a class of noncoding RNAs with >200 nucleotides, have been shown to be aberrantly expressed in DTCs and to have an important role in DTC development: the expression profiles of lncRNAs strongly correlated with poor survival of patients with DTCs, and lncRNAs acted as oncogenes or tumor suppressor genes in DTC progression. In this review, we summarized the functional lncRNAs and expounded on their regulatory mechanisms in DTCs.