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

LncRNA-MEG3 alleviates high glucose induced inflammation and apoptosis of retina epithelial cells via regulating miR-34a/SIRT1 axis

BACKGROUND

Diabetic retinopathy (DR) is the serious complication of diabetes, which could lead to blindness. Inflammation and apoptosis are hallmark of DR, but mechanism of their regulation is little known. LncRNA-MEG3 is associated with multiple biological processes including proliferation, apoptosis and inflammation response, and is dramatically decreased in DR. However, the role and underlying mechanism of MEG3 in DR is unclear. This study is aimed to reveal the signaling mechanisms of MEG3 in inflammation and apoptosis of DR.

METHODS

ARPE-19 cells were applied for this research. MEG3 was cloned into pcDNA3.1. miR-34a was overexpressed and inhibited by transfecting with mimics and inhibitor, respectively. The expression level was detected by qRT-PCR and western blotting. The targeted regulatory relationship was analyzed by dual luciferase assay. Cytokine secretion, cell viability and apoptosis were detected by ELISA assay, MTT assay and flow cytometry analysis, respectively.

RESULTS

High glucose (HG) inhibited MEG3 and SIRT1 expression and enhanced miR-34a expression. MEG3 could promote SIRT1 expression by targeting miR-34a. MEG3 overexpression and miR-34a knockdown could inhibit HG-induced apoptosis and secretion of inflammation cytokines including IL-1β, IL-6 and TNF-α, but miR-34a overexpression alleviated such effects of MEG3. Furthermore, MEG3 overexpression also inhibited NF-κB signaling pathway and increased Bcl-2/Bax ratio via down-regulating miR-34a.

CONCLUSION

MEG3 could alleviate HG-inducing apoptosis and inflammation via inhibiting NF-κB signaling pathway by targeting miR-34a/SIRT1 axis. This finding illustrated the function and mechanism of MEG3 in DR, and MEG3 might serve as potential therapeutic target for DR.

Pan-cancer characterisation of microRNA across cancer hallmarks reveals microRNA-mediated downregulation of tumour suppressors

microRNAs are key regulators of the human transcriptome across a number of diverse biological processes, such as development, aging and cancer, where particular miRNAs have been identified as tumour suppressive and oncogenic. In this work, we elucidate, in a comprehensive manner, across 15 epithelial cancer types comprising 7316 clinical samples from the Cancer Genome Atlas, the association of miRNA expression and target regulation with the phenotypic hallmarks of cancer. Utilising penalised regression techniques to integrate transcriptomic, methylation and mutation data, we find evidence for a complex map of interactions underlying the relationship of miRNA regulation and the hallmarks of cancer. This highlighted high redundancy for the oncomiR-1 cluster of oncogenic miRNAs, in particular hsa-miR-17-5p. In addition, we reveal extensive miRNA regulation of tumour suppressor genes such as PTEN, FAT4 and CDK12, uncovering an alternative mechanism of repression in the absence of mutation, methylation or copy number changes.

CircRNA ZNF609 functions as a competitive endogenous RNA to regulate FOXP4 expression by sponging miR-138-5p in renal carcinoma

Circular RNA (circRNA) play important roles in the pathological processes of many diseases. By analyzing the results of the GSE100186 chip, we found that the expression of circRNA ZNF609 (circ-ZNF609) was significantly increased in renal cell carcinoma. Recently, there are studies showing that circ-ZNF609 can regulate cell proliferation and invasion ability of various cells. In this study, we investigated whether circ-ZNF609 may affect cell invasion and proliferation in renal carcinoma. Quantitative reverse transcription polymerase chain reaction was performed to detect the expression of circ-ZNF609 in renal carcinoma cell lines and renal epithelial cells. The direct interaction between microRNA-138-5p (miR-138-5p) and forkhead box P4 (FOXP4) or circ-ZNF609 was confirmed by luciferase reporter assay and RNA immunoprecipitation assay. We use Cell Counting Kit-8, 5-ethynyl-2'-deoxyuridine, and Matrigel assays to assess the effect of miR-138-5p or circ-ZNF609 on cell proliferation or invasion ability. And we found that circ-ZNF609 is significantly increased in renal carcinoma cell lines. In addition, the high expression of circ-ZNF609 promotes cell proliferation and invasion ability. In short, our current study reveals the role of the circ-ZNF609/miR-138-5p/FOXP4 regulatory network in renal carcinoma and provides a new perspective for the pathogenesis of renal carcinoma.

The landscape of miRNA-related ceRNA networks for marking different renal cell carcinoma subtypes

We know that different types of cancers usually have different responses to the same treatment. Therefore, it is important to understand the similarities and differences across subtypes of cancers, so as to provide a basis for the individualized treatments. Until now, no comprehensive investigation on competing endogenous RNAs (ceRNAs) has been reported for the three main subtypes of renal cell carcinoma (RCC), so the regulation characteristics of ceRNAs in three subtypes are not well revealed. This paper firstly describes a comparative analysis of ceRNA-ceRNA interaction networks for all the three subtypes of RCC based on differential microRNAs (miRNAs). We comprehensively summarized all miRNA and messenger RNAdata of RCC from 126 matched tumor-normal tissues in The Cancer Genome Atlas, systematically analyzed a total of more than 80 000 ceRNA interactions and highlighted the common and specific properties among them, aiming to identify critical genes to classify them for providing supplementary help in the precise diagnosis of RCC. From three aspects, including common or specific ceRNAs, upregulated or downregulated and classifications across the three subtypes, we highlighted the common and specific properties for the three subtypes and also explored the classification of RCC by combining the specific ceRNAs with differential regulations. Moreover, for the most major subtype of clear cell renal cell carcinoma (KIRC), three critical genes were screened out from KIRC ceRNA network and further demonstrated to be the potential biomarkers of KIRC by performing biological experiments at the transcriptional level.

Global identification and characterization of lncRNAs that control inflammation in malignant cholangiocytes

BACKGROUND

Long noncoding RNAs (lncRNAs) are known to play important roles in different cell contexts, including cancers. However, little is known about lncRNAs in cholangiocarcinoma (CCA), a cholangiocyte malignancy with poor prognosis, and associated with chronic inflammation and damage to the biliary epithelium. This study determined whether lncRNAs were dysregulated and participated in disease diagnosis or pivotal inflammation pathways through a genome-wide lncRNA screening and functional analysis.

RESULTS

We firstly identified a large number of lncRNAs abnormally expressed between 9 pairs of cancerous and adjacent tissues of CCA, and between intra-hepatic CCA and extra-hepatic CCA through a genome-wide profiling. A set of aberrant differentially expressed lncRNAs were further validated in a training set (16 pairs) and a test set (11 pairs) of CCA patient samples. Following assessment of the diagnostic value of the 7 differentially expressed lncRNAs, we confirmed the optimal combination of H19, C3P1, AC005550.3, PVT1, and LPAL2 with area under the curve of 0.8828 [95% CI: 0.7441-1.021, P < 0.001], with 93.75% sensitivity and 81.25% specificity, at the cutoff point of - 0.2884 to distinguish the CCA tissue from the normal ones, suggesting that specific lncRNAs may have potential for detecting CCA. More importantly, the genome-wide locus and lncRNA/mRNA co-expression analyses revealed a set of lncRNAs that participated in inflammation and oxidative stress response pathways by regulating genes in cis or in trans. Finally, APOC1P1, PVT1, and LPAL2 were validated to regulate the migration and some pivotal inflammation genes under the CCA pathogenesis.

CONCLUSIONS

Our findings are the first to show that lncRNAs may not only be potential biomarkers of CCA progression but also respond to inflammation in CCA.

Mesenchymal glioblastoma constitutes a major ceRNA signature in the TGF-β pathway

Rationale: Competitive endogenous RNA (ceRNA) networks play important roles in posttranscriptional regulation. Their dysregulation is common in cancer. However, ceRNA signatures have been poorly examined in the invasive and aggressive phenotypes of mesenchymal glioblastoma (GBM). This study aims to characterize mesenchymal glioblastoma at the mRNA-miRNA level and identify the mRNAs in ceRNA networks (micNET) markers and their mechanisms in tumorigenesis. Methods: The mRNAs in ceRNA networks (micNETs) of glioblastoma were investigated by constructing a GBM ceRNA network followed by integration with a STRING protein interaction network. The prognostic micNET markers of mesenchymal GBM were identified and validated across multiple datasets. ceRNA interactions were identified between micNETs and miR181 family members. LY2109761, an inhibitor of TGFBR2, demonstrated tumor-suppressive effects on both primary cultured cells and a patient-derived xenograft intracranial model. Results: We characterized mesenchymal glioblastoma at the mRNA-miRNA level and reported a ceRNA network that could separate the mesenchymal subtype from other subtypes. Six genes (TGFBR2, RUNX1, PPARG, ACSL1, GIT2 and RAP1B) that interacted with each other in both a ceRNA-related manner and in terms of their protein functions were identified as markers of the mesenchymal subtype. The coding sequence (CDS) and 3'-untranslated region (UTR) of TGFBR2 upregulated the expression of these genes, whereas TGFBR2 inhibition by siRNA or miR-181a/d suppressed their expression levels. Furthermore, mesenchymal subtype-related genes and the invasion phenotype could be reversed by suppressing the six mesenchymal marker genes. Conclusions: This study suggests that the micNETs may have translational significance in the diagnosis of mesenchymal GBM and may be novel therapeutic targets.

Identification and characterization of ncRNA-associated ceRNA networks in Arabidopsis leaf development

Background

Leaf development is a complex biological process that is accompanied by wide transcriptional changes. Many protein-coding genes have been characterized in plant leaves, but little attention has been given to noncoding RNAs (ncRNAs). Moreover, increasing evidence indicates that an intricate interplay among RNA species, including protein-coding RNAs and ncRNAs, exists in eukaryotic transcriptomes, however, it remains elusive in plant leaves.

Results

We detected novel ncRNAs, such as circular RNAs (circRNAs) and long noncoding RNAs (lncRNAs), and further constructed and analyzed their associated competitive endogenous RNA (ceRNA) networks in Arabidopsis leaves. Transcriptome profiling showed extensive changes during leaf development. In addition, comprehensive detection of circRNAs in other plant leaves suggested that circRNAs are widespread in plant leaves. To investigate the complex post-transcriptional interactions in Arabidopsis leaves, we constructed a global circRNA/lncRNA-associated ceRNA network. Functional analysis revealed that ceRNAs were highly correlated with leaf development. These ceRNAs could be divided into six clusters, which were enriched for different functional classes. Stage-specific ceRNA networks were further constructed and comparative analysis revealed different roles of stage common and specific hub ceRNAs.

Conclusions

Our results demonstrate that understanding the ceRNA interactions will lead insights into gene regulations implicated in leaf development.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4993-2) contains supplementary material, which is available to authorized users.

Construction of a microRNA‑associated feed‑forward loop network that identifies regulators of cardiac hypertrophy and acute myocardial infarction

Feed‑forward loops (FFLs) are three‑gene modules that exert significant effects on a series of biological processes and carcinogenesis development. MicroRNA‑associated FFLs (miR‑FFLs) represent a new era in disease research. However, analysis of the miR‑FFL network motifs has yet to be systematically performed, and their potential role in cardiac hypertrophy and acute myocardial infarction (AMI) requires investigation. The present study used a computational method to establish a comprehensive miR‑FFL network for cardiac hypertrophy and AMI, by integrating high‑throughput data from different sources and performing multi‑aspect analysis of the network features. Several heart disease‑associated miR‑FFL motifs were identified that were specific or common to the two diseases investigated. Functional analysis further revealed that miR‑FFL motifs provided specific drug targets for the clinical treatment of cardiac hypertrophy and AMI. Associations between specific drugs associated with heart disease and dysregulated FFLs were also identified. The present study highlighted the components of FFL motifs in cardiac hypertrophy and AMI, and revealed their possibility as heart disease biomarkers and novel treatment targets.

Detection of dysregulated competing endogenous RNA modules associated with clear cell kidney carcinoma

Recent evidence has suggested that competitive endogenous RNAs (ceRNAs) are important regulatory molecules in clear cell kidney carcinoma (KIRC) and their dysregulation may contribute to cancer pathogenesis. However, the critical roles of dysregulated ceRNAs in KIRC remain unknown. In the present study, a KIRC dysregulated ceRNA-ceRNA network (KDCCNet) was constructed based on the ‘ceRNA hypothesis’ by integrating microRNA regulation and expression profiles in cancerous and normal tissues. Two dysregulated patterns of ceRNAs interaction (gain and loss) exist in KDCCNet. The two modules, which are 95% loss interactions and 97% gain interactions, were demonstrated to be able to distinguish normal samples from cancer samples. Two long non-coding (lnc)-RNAs (glucuronidase β pseudogene 11 and LIFR antisense RNA 1) demonstrated significant associations with KIRC prognosis. The present study of the KDCCNet revealed a novel biological mechanism for KIRC and provides novel lncRNAs as candidate prognostic biomarkers.

Survey of miRNA-miRNA cooperative regulation principles across cancer types

Cooperative regulation among multiple microRNAs (miRNAs) is a complex type of posttranscriptional regulation in human; however, the global view of the system-level regulatory principles across cancers is still unclear. Here, we investigated miRNA-miRNA cooperative regulatory landscape across 18 cancer types and summarized the regulatory principles of miRNAs. The miRNA-miRNA cooperative pan-cancer network exhibited a scale-free and modular architecture. Cancer types with similar tissue origins had high similarity in cooperative network structure and expression of cooperative miRNA pairs. In addition, cooperative miRNAs showed divergent properties, including higher expression, greater expression variation and a stronger regulatory strength towards targets and were likely to regulate cancer hallmark-related functions. We found a marked rewiring of miRNA-miRNA cooperation between various cancers and revealed conserved and rewired network miRNA hubs. We further identified the common hubs, cancer-specific hubs and other hubs, which tend to target known anticancer drug targets. Finally, miRNA cooperative modules were found to be associated with patient survival in several cancer types. Our study highlights the potential of pan-cancer miRNA-miRNA cooperative regulation as a novel paradigm that may aid in the discovery of tumorigenesis mechanisms and development of anticancer drugs.

Inflammatory genes are novel prognostic biomarkers for colorectal cancer

Inflammatory genes serve a crucial role in the pathogenesis of inflammation-associated tumors. However, as recent studies have mainly focused on the effects of single inflammatory genes on colorectal cancer (CRC), but not on the global interactions between genes, the underlying mechanisms between inflammatory genes and CRC remain unclear. In the current study, two inflammation-associated networks were constructed based on inflammatory genes, differentially expressed genes (DEGs) in CRC vs. normal samples, and protein-protein interactions (PPIs). These networks included an inflammation-related neighbor network (IRNN) and an inflammation-related DEG network (IRDN). Notably, the results indicated that the inflammatory genes served as important CRC-associated genes in the IRNN. Certain inflammatory genes were more likely to be network hubs and exhibited higher betweenness centralities, indicating that these inflammatory hub genes had central roles in the communication between genes in the IRNN. By contrast, in the IRDN, functional enrichment analysis revealed that genes were enriched in numerous cancer-associated functions and pathways. Subsequently, 14 genes in a module were identified in the IRDN as the potential biomarkers associated with disease-free survival (DFS) in CRC patients in the GSE24550 dataset, the prognosis of which was further validated using three independent datasets (GSE24549, GSE34551 and GSE103479). All 14 genes (including BCAR1, CRK, FYN, GRB2, LCP2, PIK3R1, PLCG1, PTK2, PTPN11, PTPN6, SHC1, SOS1, SRC and SYK) in this module were inflammatory genes, emphasizing the critical role of inflammation in CRC. In conclusion, these findings based on integrated inflammation-associated networks provided a novel insight that may help elucidate the inflammation-mediated mechanisms involved in CRC.

miRNA-mediated 'tug-of-war' model reveals ceRNA propensity of genes in cancers

Competing endogenous RNA (ceRNA) are transcripts that cross‐regulate each other at the post‐transcriptional level by competing for shared microRNA response elements (MREs). These have been implicated in various biological processes impacting cell‐fate decisions and diseases including cancer. There are several studies that predict possible ceRNA pairs by adopting various machine‐learning and mathematical approaches; however, there is no method that enables us to gauge as well as compare the propensity of the ceRNA of a gene and precisely envisages which among a pair exerts a stronger pull on the shared miRNA pool. In this study, we developed a method that uses the ‘tug of war of genes’ concept to predict and quantify ceRNA potential of a gene for the shared miRNA pool in cancers based on a score represented by SoCeR (score of competing endogenous RNA). The method was executed on the RNA‐Seq transcriptional profiles of genes and miRNA available at TCGA along with CLIP‐supported miRNA‐target sites to predict ceRNA in 32 cancer types which were validated with already reported cases. The proposed method can be used to determine the sequestering capability of the gene of interest as well as in ranking the probable ceRNA candidates of a gene. Finally, we developed standalone applications (SoCeR tool) to aid researchers in easier implementation of the method in analysing different data sets or diseases.

Model-based analysis of competing-endogenous pathways (MACPath) in human cancers

Competing endogenous RNA (ceRNA) has emerged as an important post-transcriptional mechanism that simultaneously alters expressions of thousands genes in cancers. However, only a few ceRNA genes have been studied for their functions to date. To understand the major biological functions of thousands ceRNA genes as a whole, we designed Model-based Analysis of Competing-endogenous Pathways (MACPath) to infer pathways co-regulated through ceRNA mechanism (cePathways). Our analysis on breast tumors suggested that NGF (nerve growth factor)-induced tumor cell proliferation might be associated with tumor-related growth factor pathways through ceRNA. MACPath also identified indirect cePathways, whose ceRNA relationship is mediated by mediating ceRNAs. Finally, MACPath identified mediating ceRNAs that connect the indirect cePathways based on efficient integer linear programming technique. Mediating ceRNAs are unexpectedly enriched in tumor suppressor genes, whose down-regulation is suspected to disrupt indirect cePathways, such as between DNA replication and WNT signaling pathways. Altogether, MACPath is the first computational method to comprehensively understand functions of thousands ceRNA genes, both direct and indirect, at the pathway level.

Identification of laryngeal cancer prognostic biomarkers using an inflammatory gene-related, competitive endogenous RNA network

Competitive endogenous RNAs (ceRNAs) act as molecular sponges for microRNAs (miRNAs), and are associated with tumorigenesis in various cancers, including laryngeal cancer (LC). In this work, we constructed an LC-specific inflammatory gene-related ceRNA network (IceNet). In IceNet, ceRNAs targeting inflammation-related genes tended to be network hubs. Additionally, the betweenness centralities of these hub ceRNAs were higher than those of the inflammation-related genes themselves, indicating that the hub ceRNAs in this study played critical roles in communication between IceNet molecules. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses indicated that IceNet molecules are associated with multiple cancer-related functions and signaling pathways. Using cFinder software and survival analyses, we identified a potential prognostic module within IceNet that contains 18 mRNAs and a long non-coding RNA (lncRNA), and we effectively stratified patients into high- and low-risk subgroups with different survival outcomes, independent of patient age and tumor grade. This 18-mRNA and one-lncRNA module provides a novel mechanism for potentially improving LC patient prognostic predictions. Applying the module clinically to differentiate high- and low-risk patients could inform therapeutic decision making and ultimately improve patient outcomes. In addition, these results demonstrate the potential importance of IceNet hub ceRNAs in LC development and progression.

Competing endogenous RNA network analysis identifies critical genes among the different breast cancer subtypes

Although competing endogenous RNAs (ceRNAs) have been implicated in many solid tumors, their roles in breast cancer subtypes are not well understood. We therefore generated a ceRNA network for each subtype based on the significance of both, positive co-expression and the shared miRNAs, in the corresponding subtype miRNA dys-regulatory network, which was constructed based on negative regulations between differentially expressed miRNAs and targets. All four subtype ceRNA networks exhibited scale-free architecture and showed that the common ceRNAs were at the core of the networks. Furthermore, the common ceRNA hubs had greater connectivity than the subtype-specific hubs. Functional analysis of the common subtype ceRNA hubs highlighted factors involved in proliferation, MAPK signaling pathways and tube morphogenesis. Subtype-specific ceRNA hubs highlighted unique subtype-specific pathways, like the estrogen response and inflammatory pathways in the luminal subtypes or the factors involved in the coagulation process that participates in the basal-like subtype. Ultimately, we identified 29 critical subtype-specific ceRNA hubs that characterized the different breast cancer subtypes. Our study thus provides new insight into the common and specific subtype ceRNA interactions that define the different categories of breast cancer and enhances our understanding of the pathology underlying the different breast cancer subtypes, which can have prognostic and therapeutic implications in the future.

Comprehensive characterization of lncRNA-mRNA related ceRNA network across 12 major cancers

Recent studies indicate that long noncoding RNAs (lncRNAs) can act as competing endogenous RNAs (ceRNAs) to indirectly regulate mRNAs through shared microRNAs, which represents a novel layer of RNA crosstalk and plays critical roles in the development of tumor. However, the global regulation landscape and characterization of these lncRNA related ceRNA crosstalk in cancers is still largely unknown. Here, we systematically characterized the lncRNA related ceRNA interactions across 12 major cancers and the normal physiological states by integrating multidimensional molecule profiles of more than 5000 samples. Our study suggest the large difference of ceRNA regulation between normal and tumor states and the higher similarity across similar tissue origin of tumors. The ceRNA related molecules have more conserved features in tumor networks and they play critical roles in both the normal and tumorigenesis processes. Besides, lncRNAs in the pan-cancer ceRNA network may be potential biomarkers of tumor. By exploring hub lncRNAs, we found that these conserved key lncRNAs dominate variable tumor hallmark processes across pan-cancers. Network dynamic analysis highlights the critical roles of ceRNA regulation in tumorigenesis. By analyzing conserved ceRNA interactions, we found that miRNA mediate ceRNA regulation showed different patterns across pan-cancer; while analyzing the cancer specific ceRNA interactions reveal that lncRNAs synergistically regulated tumor driver genes of cancer hallmarks. Finally, we found that ceRNA modules have the potential to predict patient survival. Overall, our study systematically dissected the lncRNA related ceRNA networks in pan-cancer that shed new light on understanding the molecular mechanism of tumorigenesis.

Identification and characterization of lncRNA mediated transcriptional dysregulation dictates lncRNA roles in glioblastoma

Long non-coding RNAs (lncRNAs) modulate gene expression, and lncRNA misregulation is associated with cancer. However, precise functional roles in biological and disease processes have been described for only a few lncRNAs. Identification of genome-wide lncRNA-mediated transcriptional dysregulations may improve cancer treatments. In the present study, we used a computational framework that combined lncRNA and gene expression profiles with transcription factor (TF)-target relationships to comprehensively identify dysregulatory lncRNA-TF-gene triplets. In glioblastoma (GBM), we found that most lncRNAs affect multiple targets and primarily affect TF activity in trans. Six different classes of lncRNA-mediated transcriptional dysregulations were identified, with most lncRNAs either enhancing or attenuating target gene expression. Functional analysis of lncRNAs via their dysregulated targets implicated lncRNA modulators in some hallmarks of cancer, providing a new way to predict lncRNA function. Finally, we identified several lncRNA-TF-gene triplets (including HOTAIR-MXI1-CD58/PRKCE and HOTAIR-ATF5-NCAM1) that are associated with glioblastoma prognosis. The integration of lncRNA modulators into transcriptional regulatory networks will further enhance our understanding of lncRNA functions in cancer.

Identification of prognostic biomarkers in glioblastoma using a long non-coding RNA-mediated, competitive endogenous RNA network

Glioblastoma multiforme (GBM) is a highly malignant brain tumor associated with a poor prognosis. Cross-talk between competitive endogenous RNAs (ceRNAs) plays a critical role in tumor development and physiology. In this study, we present a multi-step computational approach to construct a functional GBM long non-coding RNA (lncRNA)-mediated ceRNA network (LMCN) by integrating genome-wide lncRNA and mRNA expression profiles, miRNA-target interactions, functional analyses, and clinical survival analyses. LncRNAs in the LMCN exhibited specific topological features consistent with a regulatory association with coding mRNAs across GBM pathology. We determined that the lncRNA MCM3AP-AS was involved in RNA processing and cell cycle-related functions, and was correlated with patient survival. MCM3AP-AS and MIR17HG acted synergistically to regulate mRNAs in a network module of the competitive LMCN. By integrating the expression profile of this module into a risk model, we stratified GBM patients in both the The Cancer Genome Atlas and an independent GBM dataset into distinct risk groups. Finally, survival analyses demonstrated that the lncRNAs and network module are potential prognostic biomarkers for GBM. Thus, ceRNAs could accelerate biomarker discovery and therapeutic development in GBM.

Systematic Analysis of RNA Regulatory Network in Rat Brain after Ischemic Stroke

Although extensive studies have identified large number of microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) in ischemic stroke, the RNA regulation network response to focal ischemia remains poorly understood. In this study, we simultaneously interrogate the expression profiles of lncRNAs, miRNAs, and mRNAs changes during focal ischemia induced by transient middle cerebral artery occlusion. A set of 1924 novel lncRNAs were identified and may involve brain injury and DNA repair as revealed by coexpression network analysis. Furthermore, many short interspersed elements (SINE) mediated lncRNA:mRNA duplexes were identified, implying that lncRNAs mediate Staufen1-mediated mRNA decay (SMD) which may play a role during focal ischemia. Moreover, based on the competitive endogenous RNA (ceRNA) hypothesis, a stroke regulatory ceRNA network which reveals functional lncRNA:miRNA:mRNA interactions was revealed in ischemic stroke. In brief, this work reports a large number of novel lncRNAs responding to focal ischemia and constructs a systematic RNA regulation network which highlighted the role of ncRNAs in ischemic stroke.

Construction of a lncRNA-mediated feed-forward loop network reveals global topological features and prognostic motifs in human cancers

Long non-coding RNAs (lncRNAs), transcription factors and microRNAs can form lncRNA-mediated feed-forward loops (L-FFLs), which are functional network motifs that regulate a wide range of biological processes, such as development and carcinogenesis. However, L-FFL network motifs have not been systematically identified, and their roles in human cancers are largely unknown. In this study, we computationally integrated data from multiple sources to construct a global L-FFL network for six types of human cancer and characterized the topological features of the network. Our approach revealed several dysregulated L-FFL motifs common across different cancers or specific to particular cancers. We also found that L-FFL motifs can take part in other types of regulatory networks, such as mRNA-mediated FFLs and ceRNA networks, and form the more complex networks in human cancers. In addition, survival analyses further indicated that L-FFL motifs could potentially serve as prognostic biomarkers. Collectively, this study elucidated the roles of L-FFL motifs in human cancers, which could be beneficial for understanding cancer pathogenesis and treatment.

Construction of an oesophageal cancer-specific ceRNA network based on miRNA, lncRNA, and mRNA expression data

AIM

To explore the expression profiles of microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and mRNAs in oesophageal squamous cell carcinoma (ESCC) in order to construct an oesophageal cancer-specific competing endogenous RNA (ceRNA) network.

METHODS

In this work, the expression data of miRNAs, lncRNAs, and mRNAs in ESCC were obtained. An oesophageal cancer-specific ceRNA network was then constructed and investigated.

RESULTS

CeRNAs have the ability to reduce the targeting activity of miRNAs, leading to the de-repression of specific mRNAs with common miRNA response elements. CeRNA interactions have a critical effect in gene regulation and cancer development.

CONCLUSION

This study suggests a novel perspective on potential oesophageal cancer mechanisms as well as novel pathways for modulating ceRNA networks for treating cancers.

Identification of bladder cancer prognostic biomarkers using an ageing gene-related competitive endogenous RNA network

Competitive endogenous RNAs (ceRNAs) are a newly proposed RNA interaction mechanism that has been associated with the initiation and progression of various cancers. In this study, we constructed an ageing gene related ceRNA network (AgeingCeNet) in bladder cancer. Network analysis revealed that ageing gene ceRNAs have a larger degree and closeness centrality than ageing genes themselves. Notably, the difference of betweenness centrality of ageing genes and their ceRNAs is not significant, suggesting that the ceRNAs of ageing genes and ageing genes themselves both play important communication roles in AgeingCeNet. KEGG pathway enrichment analysis for genes in AgeingCeNet revealed that AgeingCeNet genes are enriched in cancer pathways and several cancer related singaling pathways. We also identified 37 core modules from AgeingCeNet using CFinder software. Next, we identified 2 potential prognostic modules, named K11M14 and K13M4, whose prognostic ability is better than that of age and gender. Finally, we identified microRNAs (miRNAs) regulating the two modules, which include miR-15b-5p, miR-195-5p, miR-30 family members, and several other cancer-related miRNAs. Our study demonstrated that constructing an ageing gene related ceRNA network is a feasible strategy to explore the mechanism of initiation and progression of bladder cancer, which might benefit the treatment of this disease.

Systematic review of computational methods for identifying miRNA-mediated RNA-RNA crosstalk

Posttranscriptional crosstalk and communication between RNAs yield large regulatory competing endogenous RNA (ceRNA) networks via shared microRNAs (miRNAs), as well as miRNA synergistic networks. The ceRNA crosstalk represents a novel layer of gene regulation that controls both physiological and pathological processes such as development and complex diseases. The rapidly expanding catalogue of ceRNA regulation has provided evidence for exploitation as a general model to predict the ceRNAs in silico. In this article, we first reviewed the current progress of RNA-RNA crosstalk in human complex diseases. Then, the widely used computational methods for modeling ceRNA-ceRNA interaction networks are further summarized into five types: two types of global ceRNA regulation prediction methods and three types of context-specific prediction methods, which are based on miRNA-messenger RNA regulation alone, or by integrating heterogeneous data, respectively. To provide guidance in the computational prediction of ceRNA-ceRNA interactions, we finally performed a comparative study of different combinations of miRNA–target methods as well as five types of ceRNA identification methods by using literature-curated ceRNA regulation and gene perturbation. The results revealed that integration of different miRNA–target prediction methods and context-specific miRNA/gene expression profiles increased the performance for identifying ceRNA regulation. Moreover, different computational methods were complementary in identifying ceRNA regulation and captured different functional parts of similar pathways. We believe that the application of these computational techniques provides valuable functional insights into ceRNA regulation and is a crucial step for informing subsequent functional validation studies.

Protein-coding genes, long non-coding RNAs combined with microRNAs as a novel clinical multi-dimension transcriptome signature to predict prognosis in ovarian cancer

Ovarian cancer is prevalent in women which is usually diagnosed at an advanced stage with a high mortality rate. The aim of this study is to investigate protein-coding gene, long non-coding RNA, and microRNA associated with the prognosis of patients with ovarian serous carcinoma by mining data from TCGA (The Cancer Genome Atlas) public database. The clinical data of ovarian serous carcinoma patients was downloaded from TCGA database in September, 2016. The mean age and survival time of 407 patients with ovarian serous carcinoma were 59.71 ± 11.54 years and 32.98 ± 26.66 months. Cox's proportional hazards regression analysis was conducted to analyze genes that were significantly associated with the survival of ovarian serous carcinoma patients in the training group. Using the random survival forest algorithm, Kaplan-Meier and ROC analysis, we kept prognostic genes to construct the multi-dimensional transcriptome signature with max area under ROC curve (AUC) (0.69 in the training group and 0.62 in the test group). The selected signature composed by VAT1L, CALR, LINC01456, RP11-484L8.1, MIR196A1 and MIR148A, separated the training group patients into high-risk or low-risk subgroup with significantly different survival time (median survival: 35.3 months vs. 64.9 months, P < 0.001). The signature was validated in the test group showing similar prognostic values (median survival: 41.6 months in high-risk vs. 57.4 months in low-risk group, P=0.018). Chi-square test and multivariable Cox regression analysis showed that the signature was an independent prognostic factor for patients with ovarian serous carcinoma. Finally, we validated the expression of the genes experimentally.

The global view of mRNA-related ceRNA cross-talks across cardiovascular diseases

Competing endogenous RNA (ceRNA) have received wide attention because they are a novel way to regulate genes through sharing microRNAs (miRNAs) that are crucial for complex processes in many diseases. However, no systematic analysis of ceRNA mechanism in cardiovascular disease (CVD) is known. To gain insights into the global properties of ceRNAs in multi-CVDs, we constructed the global view of mRNA-related ceRNA cross-talk in eight major CVDs from ~2,800 samples. We found common features that could be used to uncover similarities among different CVDs and highlighted a common core ceRNA network across CVDs. Comparative analysis of hub ceRNAs in each network revealed three types of hubs, which might play key roles in diverse biological processes. Importantly, by combining CVD-related pathway genes with ceRNA-ceRNA interactions, common modules that might exert functions in specific mechanisms were identified. In addition, our study investigated a potential mechanistic linkage between pathway cross-talk and ceRNA cross-talk. In summary, this study uncovered and systematically characterized global properties of mRNA-related ceRNA cross-talks across CVDs, which may provide a new layer for exploring biological mechanisms and shed new light on cardiology.

Identification of competing endogenous RNAs of the tumor suppressor gene PTEN: A probabilistic approach

Regulation by microRNAs (miRNAs) and modulation of miRNA activity are critical components of diverse cellular processes. Recent research has shown that miRNA-based regulation of the tumor suppressor gene PTEN can be modulated by the expression of other miRNA targets acting as competing endogenous RNAs (ceRNAs). However, the key sequence-based features enabling a transcript to act as an effective ceRNA are not well understood and a quantitative model associating statistical significance to such features is currently lacking. To identify and assess features characterizing target recognition by PTEN-regulating miRNAs, we analyze multiple datasets from PAR-CLIP experiments in conjunction with RNA-Seq data. We consider a set of miRNAs known to regulate PTEN and identify high-confidence binding sites for these miRNAs on the 3′ UTR of protein coding genes. Based on the number and spatial distribution of these binding sites, we calculate a set of probabilistic features that are used to make predictions for novel ceRNAs of PTEN. Using a series of experiments in human prostate cancer cell lines, we validate the highest ranking prediction (TNRC6B) as a ceRNA of PTEN. The approach developed can be applied to map ceRNA networks of critical cellular regulators and to develop novel insights into crosstalk between different pathways involved in cancer.

Identification of potential cancer-related pseudogenes in lung adenocarcinoma based on ceRNA hypothesis

Pseudogenes are initially regarded as non-functional genomic fossils resulted from inactivating gene mutations during evolution. Far from being silent, pseudogenes are proved to regulate the expression of protein-coding genes through function as microRNA sponge in vivo. The aim of our study was to propose an integrative systems biology approach to identify disease pseudogenes base on competitive endogenous RNA (ceRNA) hypothesis. Here, we applied our method to lung adenocarcinoma (LUAD) RNASeq data from TCGA and identified 33 candidate pseudogenes. We described the characteristics of the candidate pseudogenes and performed functional enrichment. Through analyzing neighboring genes we found these pseudogenes were surrounded by tumor genes and may involve in tumor pathway. Furthermore, the DNA methylation analysis indicated that 21 pseudogenes co-methylated with their competitive mRNAs. In the co-methylated network, we discovered 6 differentially expressed pseudogenes, which we termed potential LUAD-associated pseudogenes. We further revealed that the 3 ceRNA triples (miR-21-5p-NKAPP1-PRDM11, miR-29c-3p-MSTO2P-EZH2 and miR-29c-3p-RPLP0P2-EZH2), whose high risk groups were associated with the poor prognosis of LUAD, may be considered as potential prognostic signatures. Moreover, by integrating target information of microRNA we also provided a new perspective for the discovery of potential small molecule drugs. This work may facilitate cancer research and serve as the basis for future efforts to understand the role of pseudogenes, develop novel biomarkers and improve knowledge of tumor biology.

Integrated analysis of dosage effect lncRNAs in lung adenocarcinoma based on comprehensive network

Accumulating evidences indicate that cancer-related lncRNAs occur frequent somatic copy number alternation (SCNA). Although individual SCNA lncRNAs have been implicated in tumor biology, their regulatory mechanism has not been assessed in a systematic way. In order to explore the expression characteristics and biological functions of SCNA lncRNAs in cancer, we built a computational framework based on lncRNA expression profiles, lncRNA copy numbers and dosage sensitivity score (DSS). First, we found that the lncRNAs with different DSS were involved in distinct biological processes, while those with the same DSS had similar functions. Second, some of the lncRNAs participated in the progression and metastasis of lung adenocarcinoma (LUAD) through cis-acting regulation. In lncRNA-TF-mRNA network, lncRNAs interacted with 4 TFs and affected the immune system, and further influenced LUAD progression. Third, competing endogenous RNA network analysis inferred that lncRNA ENSG00000240990 competed with HOXA10 to absorb hsa-let-7a/b/f/g-5p and affected patient prognosis in LUAD. Last but not least, by integrating target information of miRNA we also provided a new perspective for the discovery of potential small molecule drugs. In summary, we systematically analyzed the regulatory role of SCNA lncRNAs. This work may facilitate cancer research and serve as the basis for future efforts to understand the role of SCNA lncRNAs, develop novel biomarkers and improve knowledge of tumor biology.

Inferring miRNA sponge co-regulation of protein-protein interactions in human breast cancer

Background

Recent studies have shown that the crosstalk between microRNA (miRNA) sponges plays an important role in human cancers. However, the co-regulation roles of miRNA sponges in protein-protein interactions (PPIs) are still unknown.

Results

In this study, we propose a multi-step method called miRSCoPPI to infer miRNA sponge co-regulation of PPIs. We focus on investigating breast cancer (BRCA) related miRNA sponge co-regulation, by integrating heterogeneous data, including miRNA, long non-coding RNA (lncRNA) and messenger RNA (mRNA) expression data, experimentally validated miRNA-target interactions, PPIs and lncRNA-target interactions, and the list of breast cancer genes. We find that the inferred BRCA-related miRSCoPPI network is highly connected and scale free. The top 10% hub genes in the BRCA-related miRSCoPPI network have potential biological implications in breast cancer. By utilizing a graph clustering method, we discover 17 BRCA-related miRSCoPPI modules. Through pathway enrichment analysis of the modules, we find that several modules are significantly enriched in pathways associated with breast cancer. Moreover, 10 modules have good performance in classifying breast tumor and normal samples, and can act as module signatures for prognostication. By using putative computationally predicted miRNA-target interactions, we have consistent results with those obtained using experimentally validated miRNA-target interactions, indicating that miRSCoPPI is robust in inferring miRNA sponge co-regulation of PPIs in human breast cancer.

Conclusions

Taken together, the results demonstrate that miRSCoPPI is a promising tool for inferring BRCA-related miRNA sponge co-regulation of PPIs and it can help with the understanding of the co-regulation roles of miRNA sponges on the PPIs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1672-2) contains supplementary material, which is available to authorized users.

Identifying miRNA sponge modules using biclustering and regulatory scores

Background

MicroRNA (miRNA) sponges with multiple tandem miRNA binding sequences can sequester miRNAs from their endogenous target mRNAs. Therefore, miRNA sponge acting as a decoy is extremely important for long-term loss-of-function studies both in vivo and in silico. Recently, a growing number of in silico methods have been used as an effective technique to generate hypotheses for in vivo methods for studying the biological functions and regulatory mechanisms of miRNA sponges. However, most existing in silico methods only focus on studying miRNA sponge interactions or networks in cancer, the module-level properties of miRNA sponges in cancer is still largely unknown.

Results

We propose a novel in silico method, called miRSM (miRNA Sponge Module) to infer miRNA sponge modules in breast cancer. We apply miRSM to the breast invasive carcinoma (BRCA) dataset provided by The Cancer Genome Altas (TCGA), and make functional validation of the computational results. We discover that most miRNA sponge interactions are module-conserved across two modules, and a minority of miRNA sponge interactions are module-specific, existing only in a single module. Through functional annotation and differential expression analysis, we also find that the modules discovered using miRSM are functional miRNA sponge modules associated with BRCA. Moreover, the module-specific miRNA sponge interactions among miRNA sponge modules may be involved in the progression and development of BRCA. Our experimental results show that miRSM is comparable to the benchmark methods in recovering experimentally confirmed miRNA sponge interactions, and miRSM outperforms the benchmark methods in identifying interactions that are related to breast cancer.

Conclusions

Altogether, the functional validation results demonstrate that miRSM is a promising method to identify miRNA sponge modules and interactions, and may provide new insights for understanding the roles of miRNA sponges in cancer progression and development.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1467-5) contains supplementary material, which is available to authorized users.

Pseudogenes regulate parental gene expression via ceRNA network

The concept of competitive endogenous RNA (ceRNA) was first proposed by Salmena and colleagues. Evidence suggests that pseudogene RNAs can act as a 'sponge' through competitive binding of common miRNA, releasing or attenuating repression through sequestering miRNAs away from parental mRNA. In theory, ceRNAs refer to all transcripts such as mRNA, tRNA, rRNA, long non-coding RNA, pseudogene RNA and circular RNA, because all of them may become the targets of miRNA depending on spatiotemporal situation. As binding of miRNA to the target RNA is not 100% complementary, it is possible that one miRNA can bind to multiple target RNAs and vice versa. All RNAs crosstalk through competitively binding to miRNAvia miRNA response elements (MREs) contained within the RNA sequences, thus forming a complex regulatory network. The ratio of a subset of miRNAs to the corresponding number of MREs determines repression strength on a given mRNA translation or stability. An increase in pseudogene RNA level can sequester miRNA and release repression on the parental gene, leading to an increase in parental gene expression. A massive number of transcripts constitute a complicated network that regulates each other through this proposed mechanism, though some regulatory significance may be mild or even undetectable. It is possible that the regulation of gene and pseudogene expression occurring in this manor involves all RNAs bearing common MREs. In this review, we will primarily discuss how pseudogene transcripts regulate expression of parental genes via ceRNA network and biological significance of regulation.

RNA Function Prediction

Recent studies have shown that a considerable proportion of eukaryotic genomes are transcribed as noncoding RNA (ncRNA), and regulatory ncRNAs have attracted much attention from researchers in many fields, especially of microRNA (miRNA) and long noncoding RNA (lncRNA). However, most ncRNAs are functionally uncharacterized due to the difficulty to accurately identify their targets. In this chapter, we first summarize the most recent advances in ncRNA research and their primary function. We then discuss the current state-of-the-art computational methods for predicting RNA functions, which comprise three different categories: miRNA function prediction approaches using target genes, lncRNA function prediction based on the guilt-by-association principle, and RNA function prediction approaches based on competing endogenous RNA partners. We consider that the application of these techniques can provide valuable functional and mechanistic insights into ncRNAs, and that they are crucial steps in future functional studies.

Extensive ceRNA-ceRNA interaction networks mediated by miRNAs regulate development in multiple rhesus tissues

Crosstalk between RNAs mediated by shared microRNAs (miRNAs) represents a novel layer of gene regulation, which plays important roles in development. In this study, we analyzed time series expression data for coding genes and long non-coding RNAs (lncRNAs) to identify thousands of interactions among competitive endogenous RNAs (ceRNAs) in four rhesus tissues. The ceRNAs exhibited dynamic expression and regulatory patterns during each tissue development process, which suggests that ceRNAs might work synergistically during different developmental stages or tissues to control specific functions. In addition, lncRNAs exhibit higher specificity as ceRNAs than coding-genes and their functions were predicted based on their competitive coding-gene partners to discover their important developmental roles. In addition to the specificity of tissue development, functional analyses demonstrated that the combined effects of multiple ceRNAs can have major impacts on general developmental and metabolic processes in multiple tissues, especially transcription-related functions where competitive interactions. Moreover, ceRNA interactions could sequentially and/or synergistically mediate the crosstalk among different signaling pathways during brain development. Analyzing ceRNA interactions during the development of multiple tissues will provideinsights in the regulation of normal development and the dysregulation of key mechanisms during pathogenesis.

Competing endogenous RNA networks of CYP4Z1 and pseudogene CYP4Z2P confer tamoxifen resistance in breast cancer

Patients with estrogen receptor α (ERα)-positive breast cancer can be treated with endocrine therapy using anti-estrogens such as tamoxifen; nonetheless, patients often develop resistance limiting the success of breast cancer treatment. The potential mechanisms remain elusive. In detail, many miRNAs have been associated with breast cancer tamoxifen resistance, but no studies have addressed the role of miRNA-mediated competitive endogenous RNAs network (ceRNET) in tamoxifen resistance. The ceRNET between CYP4Z1 and pseudogene CYP4Z2P has been revealed to promote breast cancer angiogenesis. However, its function in tamoxifen resistance remains unclear. Here we report CYP4Z1 and CYP4Z2P were downregulated in MCF-7 cells compared with tamoxifen-resistant MCF-7-TamR cells. Enforced upregulation of CYP4Z1- or CYP4Z2P-3'UTR level renders MCF-7 Cells resistant to tamoxifen. We find that overexpression of CYP4Z1- or CYP4Z2P-3'UTR enhances the transcriptional activity of ERα through the activation of ERα phosphorylation. Furthermore, we find that CYP4Z1- and CYP4Z2P-3'UTRs increase ERα activity dependent on cyclin-dependent kinase 3 (CDK3). Reporter gene and western blot assays revealed that CYP4Z1- and CYP4Z2P-3'UTRs act as CDK3 ceRNAs. More importantly, the blocking of CYP4Z1- and CYP4Z2P-3'UTRs reversed tamoxifen resistance in MCF-7-TamR cells. Our data demonstrates that the ceRNET between CYP4Z1 and pseudogene CYP4Z2P acts as a sub-ceRNET to promote CDK3 expression in ER-positive breast cancer and is a potential therapeutic target for treatment of tamoxifen-resistant breast cancer.

IGF1 3'UTR functions as a ceRNA in promoting angiogenesis by sponging miR-29 family in osteosarcoma

Osteosarcoma is one of the most common malignant bone tumors in human worldwide. Angiogenesis is a pivotal process during osteosarcoma development. Insulin-like growth factor 1 (IGF1) has been reported to promote angiogenesis. However, the role of 3' untranslational region (3'UTR) of IGF1 mRNA in angiogenic activity in osteosarcomas is still unknown. In the present study, we performed gain-of-function assays to investigate the role of IGF1-3'UTR in angiogenesis. For the first time, we demonstrated that IGF1 3'UTR increased VEGF expression and promotes angiogenesis in osteosarcoma cells. In addition, RNA-immunoprecipitation and luciferase reporter assays showed that IGF1 3'UTR was a direct target of miR-29s. Our data also demonstrated that there existed a competition of miR-29s between IGF1-3'UTR and VEGF mRNA, and IGF1-3'UTR promoted angiogenesis at least in part via sponging miR-29s. Taken together, our study suggests that IGF1-3'UTR functions as a ceRNA in promoting angiogenesis by sponging miR-29s in osteosarcoma.

SomamiR 2.0: a database of cancer somatic mutations altering microRNA-ceRNA interactions

SomamiR 2.0 (http://compbio.uthsc.edu/SomamiR) is a database of cancer somatic mutations in microRNAs (miRNA) and their target sites that potentially alter the interactions between miRNAs and competing endogenous RNAs (ceRNA) including mRNAs, circular RNAs (circRNA) and long noncoding RNAs (lncRNA). Here, we describe the recent major updates to the SomamiR database. We expanded the scope of the database by including somatic mutations that impact the interactions between miRNAs and two classes of non-coding RNAs, circRNAs and lncRNAs. Recently, a large number of miRNA target sites have been discovered by newly emerged high-throughput technologies for mapping the miRNA interactome. We have mapped 388 247 somatic mutations to the experimentally identified miRNA target sites. The updated database also includes a list of somatic mutations in the miRNA seed regions, which contain the most important guiding information for miRNA target recognition. A recently developed webserver, miR2GO, was integrated with the database to provide a seamless pipeline for assessing functional impacts of somatic mutations in miRNA seed regions. Data and functions from multiple sources including biological pathways and genome-wide association studies were updated and integrated with SomamiR 2.0 to make it a better platform for functional analysis of somatic mutations altering miRNA–ceRNA interactions.