Cancer Specific Long Noncoding RNAs Show Differential Expression Patterns and Competing Endogenous RNA Potential in Hepatocellular Carcinoma

Long noncoding RNAs (lncRNAs) regulate gene expression by acting with microRNAs (miRNAs). However, the roles of cancer specific lncRNA and its related competitive endogenous RNAs (ceRNA) network in hepatocellular cell carcinoma (HCC) are not fully understood. The lncRNA profiles in 372 HCC patients, including 372 tumor and 48 adjacent non-tumor liver tissues, from The Cancer Genome Atlas (TCGA) and NCBI GEO omnibus (GSE65485) were analyzed. Cancer specific lncRNAs (or HCC related lncRNAs) were identified and correlated with clinical features. Based on bioinformatics generated from miRcode, starBase, and miRTarBase, we constructed an lncRNA-miRNA-mRNA network (ceRNA network) in HCC. We found 177 cancer specific lncRNAs in HCC (fold change ≥ 1.5, P < 0.01), 41 of them were also discriminatively expressed with gender, race, tumor grade, AJCC tumor stage, and AJCC TNM staging system. Six lncRNAs (CECR7, LINC00346, MAPKAPK5-AS1, LOC338651, FLJ90757, and LOC283663) were found to be significantly associated with overall survival (OS, log-rank P < 0.05). Collectively, our results showed the lncRNA expression patterns and a complex ceRNA network in HCC, and identified a complex cancer specific ceRNA network, which includes 14 lncRNAs and 17 miRNAs in HCC.     

The mRNA related ceRNA–ceRNA landscape and significance across 20 major cancer types

Cross-talk between competitive endogenous RNAs (ceRNAs) through shared miRNAs represents a novel layer of gene regulation that plays important roles in the physiology and development of cancers. However, a global view of their system-level properties across various types of cancers is still unknown. Here, we constructed the mRNA related ceRNA–ceRNA interaction landscape across 20 cancer types by systematically analyzing molecular profiles of 5203 tumors and miRNA regulations. Our study highlights the conserved features shared by pan-cancer and higher similarity within similar origin cell type. Moreover, a core ceRNA network was identified. Function analysis identified a common theme of cancer hallmarks, however they exhibit phenotype-specific connectivity patterns. Besides, we found a marked rewiring in the ceRNA program between various cancers, and further revealed conserved and rewired network ceRNA hubs in each cancer, which were tensely competitive interactions to constitute conserved and cancer-specific modules. By providing mechanistic linkage between known cancer miRNAs, their mediated ceRNA–ceRNA interactions, and the associations with known cancer hallmarks, the inferred cancer ceRNA–ceRNA interaction landscape will serve as a powerful public resource for further biological discoveries of tumorigenesis.     

Construction and analysis of the abnormal lncRNA–miRNA–mRNA network in hypoxic pulmonary hypertension

The incidence of hypoxic pulmonary hypertension (HPH) is increasing. Accumulating evidence suggests that long noncoding RNAs (lncRNAs) play an important role in HPH, but the functions and mechanism have yet to be fully elucidated. In the present study, we established a HPH rat model with 8 h of hypoxia exposure (10% O₂) per day for 21 days. High-throughput sequencing identified 60 differentially expressed (DE) lncRNAs, 20 DE miRNAs and 695 DE mRNAs in rat lung tissue. qRT-PCR verified the accuracy of the results. The DE mRNAs were significantly enriched in immune response, inflammatory response, leukocyte migration, cell cycle, cellular response to interleukin-1, IL-17 signalling pathway, cytokine–cytokine receptor interaction and Toll-like receptor signalling pathway. According to the theory of competing endogenous RNA (ceRNA) networks, lncRNA–miRNA–mRNA network was constructed by Cytoscape software, 16 miRNAs and 144 mRNAs. The results suggested that seven DE lncRNAs (Ly6l, AABR07038849.2, AABR07069008.2, AABR07064873.1, AABR07001382.1, AABR07068161.1 and AABR07060341.2) may serve as molecular sponges of the corresponding miRNAs and play a major role in HPH.     

Integrated analysis of co‐expression and ceRNA network identifies five lncRNAs as prognostic markers for breast cancer

Long non‐coding RNAs (lncRNAs), which competitively bind miRNAs to regulate target mRNA expression in the competing endogenous RNAs (ceRNAs) network, have attracted increasing attention in breast cancer research. We aim to find more effective therapeutic targets and prognostic markers for breast cancer. LncRNA, mRNA and miRNA expression profiles of breast cancer were downloaded from TCGA database. We screened the top 5000 lncRNAs, top 5000 mRNAs and all miRNAs to perform weighted gene co‐expression network analysis. The correlation between modules and clinical information of breast cancer was identified by Pearson's correlation coefficient. Based on the most relevant modules, we constructed a ceRNA network of breast cancer. Additionally, the standard Kaplan‐Meier univariate curve analysis was adopted to identify the prognosis of lncRNAs. Ultimately, a total of 23 and 5 modules were generated in the lncRNAs/mRNAs and miRNAs co‐expression network, respectively. According to the Green module of lncRNAs/mRNAs and Blue module of miRNAs, our constructed ceRNA network consisted of 52 lncRNAs, 17miRNAs and 79 mRNAs. Through survival analysis, 5 lncRNAs (AL117190.1, COL4A2‐AS1, LINC00184, MEG3 and MIR22HG) were identified as crucial prognostic factors for patients with breast cancer. Taken together, we have identified five novel lncRNAs related to prognosis of breast cancer. Our study has contributed to the deeper understanding of the molecular mechanism of breast cancer and provided novel insights into the use of breast cancer drugs and prognosis.     

Long non-coding RNAs and their implications in cancer epigenetics

LncRNAs (long non-coding RNAs) have emerged as key molecular players in the regulation of gene expression in different biological processes. Their involvement in epigenetic processes includes the recruitment of histone-modifying enzymes and DNA methyltransferases, leading to the establishment of chromatin conformation patterns that ultimately result in the fine control of genes. Some of these genes are related to tumorigenesis and it is well documented that the misregulation of epigenetic marks leads to cancer. In this review, we highlight how some of the lncRNAs implicated in cancer are involved in the epigenetic control of gene expression. While very few lncRNAs have already been identified as players in determining the cancer-survival outcome in a number of different cancer types, for most of the lncRNAs associated with epigenetic regulation only their altered pattern of expression in cancer is demonstrated. Thanks to their tissue-specificity features, lncRNAs have already been proposed as diagnostic markers in specific cancer types. We envision the discovery of a wealth of novel spliced and unspliced intronic lncRNAs involved in epigenetic networks or in highly location-specific epigenetic control, which might be predominantly altered in specific cancer subtypes. We expect that the characterization of new lncRNA (long non-coding RNA)–protein and lncRNA–DNA interactions will contribute to the discovery of potential lncRNA targets for use in therapies against cancer.     

Integrated analysis of ceRNA network and tumor-infiltrating immune cells in esophageal cancer

Background: Esophageal cancer (ESCA) is one of the most commonly diagnosed cancers in the world. Tumor immune microenvironment is closely related to tumor prognosis. The present study aimed at analyzing the competing endogenous RNA (ceRNA) network and tumor-infiltrating immune cells in ESCA.Methods: The expression profiles of mRNAs, lncRNAs, and miRNAs were downloaded from the Cancer Genome Atlas database. A ceRNA network was established based on the differentially expressed RNAs by Cytoscape. CIBERSORT was applied to estimate the proportion of immune cells in ESCA. Prognosis-associated genes and immune cells were applied to establish prognostic models basing on Lasso and multivariate Cox analyses. The survival curves were constructed with Kaplan–Meier method. The predictive efficacy of the prognostic models was evaluated by the receiver operating characteristic (ROC) curves.Results: The differentially expressed mRNAs, lncRNAs, and miRNAs were identified. We constructed the ceRNA network including 23 lncRNAs, 19 miRNAs, and 147 mRNAs. Five key molecules (HMGB3, HOXC8, HSPA1B, KLHL15, and RUNX3) were identified from the ceRNA network and five significant immune cells (plasma cells, T cells follicular helper, monocytes, dendritic cells activated, and neutrophils) were selected via CIBERSORT. The ROC curves based on key genes and significant immune cells all showed good sensitivity (AUC of 3-year survival: 0.739, AUC of 5-year survival: 0.899, AUC of 3-year survival: 0.824, AUC of 5-year survival: 0.876). There was certain correlation between five immune cells and five key molecules.Conclusion: The present study provides an effective bioinformatics basis for exploring the potential biomarkers of ESCA and predicting its prognosis.     

The mRNA–miRNA–lncRNA Regulatory Network and Factors Associated with Prognosis Prediction of Hepatocellular Carcinoma

The aim of this study was to identify novel prognostic mRNA and microRNA (miRNA) biomarkers for hepatocellular carcinoma (HCC) using methods in systems biology. Differentially expressed mRNAs, miRNAs, and long non-coding RNAs (lncRNAs) were compared between HCC tumor tissues and normal liver tissues in The Cancer Genome Atlas (TCGA) database. Subsequently, a prognosis-associated mRNA co-expression network, an mRNA–miRNA regulatory network, and an mRNA–miRNA–lncRNA regulatory network were constructed to identify prognostic biomarkers for HCC through Cox survival analysis. Seven prognosis-associated mRNA co-expression modules were obtained by analyzing these differentially expressed mRNAs. An expression module including 120 mRNAs was significantly correlated with HCC patient survival. Combined with patient survival data, several mRNAs and miRNAs, including CHST4, SLC22A8, STC2, hsa-miR-326, and hsa-miR-21 were identified from the network to predict HCC patient prognosis. Clinical significance was investigated using tissue microarray analysis of samples from 258 patients with HCC. Functional annotation of hsa-miR-326 and hsa-miR-21-5p indicated specific associations with several cancer-related pathways. The present study provides a bioinformatics method for biomarker screening, leading to the identification of an integrated mRNA–miRNA–lncRNA regulatory network and their co-expression patterns in relation to predicting HCC patient survival.     

Construction and analysis of dysregulated lncRNA-associated ceRNA network in colorectal cancer

Colorectal cancer (CRC) is one of the most frequently diagnosed digestive system cancer. The aim of the present study was to investigate the interactions among messenger RNAs (mRNAs), microRNAs (miRNAs), and long noncoding RNAs (lncRNAs) in CRC to reveal the mechanisms of CRC. Differentially expressed genes (DEGs) were identified from public gene expression data sets. One thousand eighty-one common dysregulated mRNAs in two data sets were identified. Gene function analysis and protein-protein interaction network analysis indicated that these DEGs might play important roles in CRC. LINC00365 was selected through coding- noncoding network analysis and its expression was validated upregulated in 22 paired clinical samples and four CRC cell lines. A competing endogenous RNA network composed of 70 miRNAs, nine mRNAs, and LINC00365 was constructed. Eight of nine mRNAs were validated upregulated in The Cancer Genome Atlas data set. Our results suggested that LINC00365 was an oncogene in CRC and it could regulate the expression of several mRNAs through sponging miRNAs.     

Prediction of a competing endogenous RNA co‐expression network as a prognostic marker in glioblastoma

Due to its high proliferation capacity and rapid intracranial spread, glioblastoma (GBM) has become one of the least curable malignant cancers. Recently, the competing endogenous RNAs (ceRNAs) hypothesis has become a focus in the researches of molecular biological mechanisms of cancer occurrence and progression. However, there is a lack of correlation studies on GBM, as well as a lack of comprehensive analyses of GBM molecular mechanisms based on high‐throughput sequencing and large‐scale sample sizes. We obtained RNA‐seq data from The Cancer Genome Atlas (TCGA) and Genotype‐Tissue Expression (GTEx) databases. Further, differentially expressed mRNAs were identified from normal brain tissue and GBM tissue. The similarities between the mRNA modules with clinical traits were subjected to weighted correlation network analysis (WGCNA). With the mRNAs from clinical‐related modules, a survival model was constructed by univariate and multivariate Cox proportional hazard regression analyses. Thereafter, we carried out Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Finally, we predicted interactions between lncRNAs, miRNAs and mRNAs by TargetScan, miRDB, miRTarBase and starBase. We identified 2 lncRNAs (NORAD, XIST), 5 miRNAs (hsa‐miR‐3613, hsa‐miR‐371, hsa‐miR‐373, hsa‐miR‐32, hsa‐miR‐92) and 2 mRNAs (LYZ, PIK3AP1) for the construction of a ceRNA network, which might act as a prognostic biomarker of GBM. Combined with previous studies and our enrichment analysis results, we hypothesized that this ceRNA network affects immune activities and tumour microenvironment variations. Our research provides novel aspects to study GBM development and treatment.     

Comprehensive analysis of a ceRNA network reveals potential prognostic cytoplasmic lncRNAs involved in HCC progression

The aberrant expression of long noncoding RNAs (lncRNAs) has drawn increasing attention in the field of hepatocellular carcinoma (HCC) biology. In the present study, we obtained the expression profiles of lncRNAs, microRNAs (miRNAs), and messenger RNAs (mRNAs) in 371 HCC tissues and 50 normal tissues from The Cancer Genome Atlas (TCGA) and identified hepatocarcinogenesis-specific differentially expressed genes (DEGs, log fold change ≥ 2, FDR < 0.01), including 753 lncRNAs, 97 miRNAs, and 1,535 mRNAs. Because the specific functions of lncRNAs are closely related to their intracellular localizations and because the cytoplasm is the main location for competitive endogenous RNA (ceRNA) action, we analyzed not only the interactions among these DEGs but also the distributions of lncRNAs (cytoplasmic, nuclear or both). Then, an HCC-associated deregulated ceRNA network consisting of 37 lncRNAs, 10 miRNAs, and 26 mRNAs was constructed after excluding those lncRNAs located only in the nucleus. Survival analysis of this network demonstrated that 15 lncRNAs, 3 miRNAs, and 16 mRNAs were significantly correlated with the overall survival of HCC patients (p < 0.01). Through multivariate Cox regression and lasso analysis, a risk score system based on 13 lncRNAs was constructed, which showed good discrimination and predictive ability for HCC patient survival time. This ceRNA network-construction approach, based on lncRNA distribution, not only narrowed the scope of target lncRNAs but also provided specific candidate molecular biomarkers for evaluating the prognosis of HCC, which will help expand our understanding of the ceRNA mechanisms involved in the early development of HCC.     

An atlas and analysis of bovine skeletal muscle long noncoding RNAs

Long noncoding RNAs (lncRNAs) have various biological functions and have been extensively studied in recent years. However, the identification and characterization of bovine lncRNAs in skeletal muscle has been very limited compared with that of lncRNAs in other model organisms. In this study, 7188 bovine skeletal muscle lncRNAs were identified by RNA‐Seq and a stringent screening procedure in four different muscle tissues. These lncRNAs shared many characteristics with other mammalian lncRNAs, such as a shorter open reading frame and lower expression level than for mRNAs. Furthermore, the chromosomal locations and global expression patterns for these lncRNAs are also described in detail. More importantly, we detected the important interaction relationships of lncRNAs–miRNAs–mRNAs related to muscle development among 36 lncRNAs, 62 miRNAs and 12 mRNAs. Our results provide a global expression pattern of lncRNAs specific to bovine skeletal muscle and provide important targets for revealing the function of bovine muscle development by thoroughly studying the interaction relationships of lncRNAs–miRNAs–mRNAs.     

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

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

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

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

Novel link prediction for large-scale miRNA-lncRNA interaction network in a bipartite graph

Background

Current knowledge and data on miRNA-lncRNA interactions is still limited and little effort has been made to predict target lncRNAs of miRNAs. Accumulating evidences suggest that the interaction patterns between lncRNAs and miRNAs are closely related to relative expression level, forming a titration mechanism. It could provide an effective approach for characteristic feature extraction. In addition, using the coding non-coding co-expression network and sequence data could also help to measure the similarities among miRNAs and lncRNAs. By mathematically analyzing these types of similarities, we come up with two findings that (i) lncRNAs/miRNAs tend to collaboratively interact with miRNAs/lncRNAs of similar expression profiles, and vice versa, and (ii) those miRNAs interacting with a cluster of common target genes tend to jointly target at the common lncRNAs.

Methods

In this work, we developed a novel group preference Bayesian collaborative filtering model called GBCF for picking up a top-k probability ranking list for an individual miRNA or lncRNA based on the known miRNA-lncRNA interaction network.

Results

To evaluate the effectiveness of GBCF, leave-one-out and k-fold cross validations as well as a series of comparison experiments were carried out. GBCF achieved the values of area under ROC curve of 0.9193, 0.8354+/??0.0079, 0.8615+/??0.0078, and 0.8928+/??0.0082 based on leave-one-out, 2-fold, 5-fold, and 10-fold cross validations respectively, demonstrating its reliability and robustness.

Conclusions

GBCF could be used to select potential lncRNA targets of specific miRNAs and offer great insights for further researches on ceRNA regulation network.