Discovery of microRNA-mRNA modules via population-based probabilistic learning

MicroRNAs as Sensitizers of Tyrosine Kinase Inhibitor Resistance in Cancer: Small Molecule Partnerships

Tyrosine kinase inhibitors (TKIs) have revolutionized cancer treatments by being less toxic and improving the survival of cancer patients. The greatest challenge to their success is the resistance exhibited by cancer patients. However, the potential of microRNAs (miRNAs) for sensitizing molecules to TKIs has been well recognized, with several reports publishing promising results. Nonetheless, this therapeutic window faces challenges and several often-overlooked limitations. One of the most fundamental challenges is selecting the optimal miRNA candidates for clinical trials, as miRNAs are promiscuous and regulate hundreds of targets. In this review, we describe how miRNAs enhance sensitivity to TKIs across various types of cancer. We highlight several challenges and limitations in achieving a successful collaboration between small molecules (TKIs-miRNAs). Our focus is on proposing a workflow to select the most suitable miRNA candidate, recommending several available bioinformatics tools to develop a successful therapeutic partnership between TKIs and miRNAs. We hope that this initial proposal will provide valuable support for future research.

Identifying miRNA-Gene Common and Specific Regulatory Modules for Cancer Subtyping by a High-Order Graph Matching Model

Identifying regulatory modules between miRNAs and genes is crucial in cancer research. It promotes a comprehensive understanding of the molecular mechanisms of cancer. The genomic data collected from subjects usually relate to different cancer statuses, such as different TNM Classifications of Malignant Tumors (TNM) or histological subtypes. Simple integrated analyses generally identify the core of the tumorigenesis (common modules) but miss the subtype-specific regulatory mechanisms (specific modules). In contrast, separate analyses can only report the differences and ignore important common modules. Therefore, there is an urgent need to develop a novel method to jointly analyze miRNA and gene data of different cancer statuses to identify common and specific modules. To that end, we developed a High-Order Graph Matching model to identify Common and Specific modules (HOGMCS) between miRNA and gene data of different cancer statuses. We first demonstrate the superiority of HOGMCS through a comparison with four state-of-the-art techniques using a set of simulated data. Then, we apply HOGMCS on stomach adenocarcinoma data with four TNM stages and two histological types, and breast invasive carcinoma data with four PAM50 subtypes. The experimental results demonstrate that HOGMCS can accurately extract common and subtype-specific miRNA-gene regulatory modules, where many identified miRNA-gene interactions have been confirmed in several public databases.

miRModuleNet: Detecting miRNA-mRNA Regulatory Modules

Increasing evidence that microRNAs (miRNAs) play a key role in carcinogenesis has revealed the need for elucidating the mechanisms of miRNA regulation and the roles of miRNAs in gene-regulatory networks. A better understanding of the interactions between miRNAs and their mRNA targets will provide a better understanding of the complex biological processes that occur during carcinogenesis. Increased efforts to reveal these interactions have led to the development of a variety of tools to detect and understand these interactions. We have recently described a machine learning approach miRcorrNet, based on grouping and scoring (ranking) groups of genes, where each group is associated with a miRNA and the group members are genes with expression patterns that are correlated with this specific miRNA. The miRcorrNet tool requires two types of -omics data, miRNA and mRNA expression profiles, as an input file. In this study we describe miRModuleNet, which groups mRNA (genes) that are correlated with each miRNA to form a star shape, which we identify as a miRNA-mRNA regulatory module. A scoring procedure is then applied to each module to further assess their contribution in terms of classification. An important output of miRModuleNet is that it provides a hierarchical list of significant miRNA-mRNA regulatory modules. miRModuleNet was further validated on external datasets for their disease associations, and functional enrichment analysis was also performed. The application of miRModuleNet aids the identification of functional relationships between significant biomarkers and reveals essential pathways involved in cancer pathogenesis. The miRModuleNet tool and all other supplementary files are available at https://github.com/malikyousef/miRModuleNet/

A review on methods for predicting miRNA–mRNA regulatory modules

Identification of complex interactions between miRNAs and mRNAs in a regulatory network helps better understand the underlying biological processes. Previously, identification of these interactions was based on sequence-based predicted target binding information. With the advancement in high-throughput omics technologies, miRNA and mRNA expression for the same set of samples are available. This helps develop more efficient and flexible approaches that work by integrating miRNA and mRNA expression profiles with target binding information. Since these integrative approaches of miRNA–mRNA regulatory modules (MRMs) detection is sufficiently able to capture the minute biological details, 26 such algorithms/methods/tools for MRMs identification are comprehensively reviewed in this article. The study covers the significant features underlying every method. Therefore, the methods are classified into eight groups based on mathematical approaches to understand their working and suitability for one’s study. An algorithm could be selected based on the available information with the users and the biological question under investigation.

A holistic miRNA-mRNA module discovery

The regulatory role of the Micro-RNAs (miRNAs) in the messenger RNAs (mRNAs) gene expression is well understood by the biologists since some decades, even though the delving into specific aspects is in progress. In this paper we will focus on miRNA-mRNA modules, where regulation jointly occurs in miRNA-mRNA pairs. Namely, we propose a holistic procedure to identify miRNA-mRNA modules within a population of candidate pairs. Since current methods still leave open issues, we adopt the strategy of postponing any decision on the value of the module ingredients exactly at the end, i.e. at the moment of biologically exploiting the results. This diverts chains of statistical tests into sequences of specially-devised-evolving metrics on the possible solutions. This strategy is rather expensive under a computational perspective, so needing implementations on HPC. The reward stands in the discovery of new modules, possibly hosting non differentially expressed miRNAs and mRNAs and pairs containing genes that currently are considered not targeted. In the paper we implement the procedure on a Multiple Myeloma dataset publicly available on GEO platform, as a template of a cancer instance analysis, and hazard some biological issues. These results, jointly with the normal manageability of the computations, suggest that the discovery procedure may be profitably extended to a wide spectrum of diseases where miRNA-mRNA interactions play a relevant role.

miRcorrNet: machine learning-based integration of miRNA and mRNA expression profiles, combined with feature grouping and ranking

A better understanding of disease development and progression mechanisms at the molecular level is critical both for the diagnosis of a disease and for the development of therapeutic approaches. The advancements in high throughput technologies allowed to generate mRNA and microRNA (miRNA) expression profiles; and the integrative analysis of these profiles allowed to uncover the functional effects of RNA expression in complex diseases, such as cancer. Several researches attempt to integrate miRNA and mRNA expression profiles using statistical methods such as Pearson correlation, and then combine it with enrichment analysis. In this study, we developed a novel tool called miRcorrNet, which performs machine learning-based integration to analyze miRNA and mRNA gene expression profiles. miRcorrNet groups mRNAs based on their correlation to miRNA expression levels and hence it generates groups of target genes associated with each miRNA. Then, these groups are subject to a rank function for classification. We have evaluated our tool using miRNA and mRNA expression profiling data downloaded from The Cancer Genome Atlas (TCGA), and performed comparative evaluation with existing tools. In our experiments we show that miRcorrNet performs as good as other tools in terms of accuracy (reaching more than 95% AUC value). Additionally, miRcorrNet includes ranking steps to separate two classes, namely case and control, which is not available in other tools. We have also evaluated the performance of miRcorrNet using a completely independent dataset. Moreover, we conducted a comprehensive literature search to explore the biological functions of the identified miRNAs. We have validated our significantly identified miRNA groups against known databases, which yielded about 90% accuracy. Our results suggest that miRcorrNet is able to accurately prioritize pan-cancer regulating high-confidence miRNAs. miRcorrNet tool and all other supplementary files are available at https://github.com/malikyousef/miRcorrNet.

MicroRNA‑101 inhibits renal tubular epithelial‑to‑mesenchymal transition by targeting TGF‑β1 type I receptor

MicroRNAs (miRNAs/miRs) are key regulators of renal interstitial fibrosis (RIF). The present study was designed to identify miRNAs associated with the development of RIF, and to explore the ability of these identified miRNAs to modulate the renal tubular epithelial‑to‑mesenchymal transition (EMT) process. To this end, miRNAs that were differentially expressed between normal and fibrotic kidneys in a rat model of mercury chloride (HgCl₂)‑induced RIF were detected via an array‑based approach. Bioinformatics analyses revealed that miR‑101 was the miRNA that was most significantly downregulated in the fibrotic renal tissue samples, and this was confirmed by RT‑qPCR, which also demonstrated that this miRNA was downregulated in transforming growth factor (TGF)‑β1‑treated human proximal tubular epithelial (HK‑2) cells. When miR‑101 was overexpressed, this was sufficient to reverse TGF‑β1‑induced EMT in HK‑2 cells, leading to the upregulation of the epithelial marker, E‑cadherin, and the downregulation of the mesenchymal marker, α‑smooth muscle actin. By contrast, the downregulation of miR‑101 using an inhibitor exerted the opposite effect. The overexpression of miR‑101 also suppressed the expression of the miR‑101 target gene, TGF‑β1 type I receptor (TβR‑I), and thereby impaired TGF‑β1/Smad3 signaling, while the opposite was observed upon miR‑101 inhibition. To further confirm the ability of miR‑101 to modulate EMT, the HK‑2 cells were treated with the TβR‑I inhibitor, SB‑431542, which significantly suppressed TGF‑β1‑induced EMT in these cells. Notably, miR‑101 inhibition exerted a less pronounced effect upon EMT‑related phenotypes in these TβR‑I inhibitor‑treated HK‑2 cells, supporting a model wherein miR‑101 inhibits TGF‑β1‑induced EMT by suppressing TβR‑I expression. On the whole, the present study demonstrates that miR‑101 is capable of inhibiting TGF‑β1‑induced tubular EMT by targeting TβR‑I, suggesting that it may be an important regulator of RIF.

An efficient framework to identify key miRNA-mRNA regulatory modules in cancer

MOTIVATION

Micro-RNAs (miRNAs) are known as the important components of RNA silencing and post-transcriptional gene regulation, and they interact with messenger RNAs (mRNAs) either by degradation or by translational repression. miRNA alterations have a significant impact on the formation and progression of human cancers. Accordingly, it is important to establish computational methods with high predictive performance to identify cancer-specific miRNA-mRNA regulatory modules.

RESULTS

We presented a two-step framework to model miRNA-mRNA relationships and identify cancer-specific modules between miRNAs and mRNAs from their matched expression profiles of more than 9000 primary tumors. We first estimated the regulatory matrix between miRNA and mRNA expression profiles by solving multiple linear programming problems. We then formulated a unified regularized factor regression (RFR) model that simultaneously estimates the effective number of modules (i.e. latent factors) and extracts modules by decomposing regulatory matrix into two low-rank matrices. Our RFR model groups correlated miRNAs together and correlated mRNAs together, and also controls sparsity levels of both matrices. These attributes lead to interpretable results with high predictive performance. We applied our method on a very comprehensive data collection by including 32 TCGA cancer types. To find the biological relevance of our approach, we performed functional gene set enrichment and survival analyses. A large portion of the identified modules are significantly enriched in Hallmark, PID and KEGG pathways/gene sets. To validate the identified modules, we also performed literature validation as well as validation using experimentally supported miRTarBase database.

AVAILABILITY AND IMPLEMENTATION

Our implementation of proposed two-step RFR algorithm in R is available at https://github.com/MiladMokhtaridoost/2sRFR together with the scripts that replicate the reported experiments.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Fuzheng Huayu recipe, a traditional Chinese compound herbal medicine, attenuates renal interstitial fibrosis via targeting the miR-21/PTEN/AKT axis

OBJECTIVE

MicroRNAs (miRNAs) may be viable targets for treating renal interstitial fibrosis (RIF). Fuzheng Huayu recipe (FZHY), a traditional Chinese compound herbal medicine, is often used in China to treat fibrosis. This study sought to assess the mechanisms through which FZHY influences miRNAs to treat RIF.

METHODS

RIF was induced in rats by mercury chloride and treated with FZHY. Hydroxyproline content, Masson's staining and type I collagen expression were used to evaluate renal collagen deposition. Renal miRNA profiles were evaluated using a miRNA microarray. Those miRNAs that were differentially expressed following FZHY treatment were identified and subjected to bioinformatic analyses. The miR-21 target gene phosphatase and tensin homolog (PTEN) expression and AKT phosphorylation in kidney tissues were assessed via Western blotting. In addition, HK-2 human proximal tubule epithelial cells were treated using angiotensin II (Ang-II) to induce epithelial-to-mesenchymal transition (EMT), followed by FZHY exposure. miR-21 and PTEN expressions were evaluated via quantitative reverse transcription-polymerase chain reaction (qRT-PCR), while E-cadherin and α-smooth muscle actin (α-SMA) expressions were assessed by immunofluorescent staining and qRT-PCR. Western blotting was used to assess PTEN and AKT phosphorylation.

RESULTS

FZHY significantly decreased kidney collagen deposition, hydroxyproline content and type I collagen level. The miRNA microarray identified 20 miRNAs that were differentially expressed in response to FZHY treatment. Subsequent bioinformatic analyses found that miR-21 was the key fibrosis-related miRNA regulated by FZHY. FZHY also decreased PTEN expression and AKT phosphorylation in fibrotic kidneys. Results from in vitro tests also suggested that FZHY promoted E-cadherin upregulation and inhibited α-SMA expression in Ang-II-treated HK-2 cells, effectively reversing Ang-II-mediated EMT. We also determined that FZHY reduced miR-21 expression, increased PTEN expression and decreased AKT phosphorylation in these cells.

CONCLUSION

miR-21 is the key fibrosis-related miRNA regulated by FZHY. The ability of FZHY to modulate miR-21/PTEN/AKT signaling may be a viable approach for treating RIF.

The Construction and Analysis of lncRNA-miRNA-mRNA Competing Endogenous RNA Network of Schwann Cells in Diabetic Peripheral Neuropathy

Background

Diabetes mellitus is a worldwide disease with high incidence. Diabetic peripheral neuropathy (DPN) is one of the most common but often ignored complications of diabetes mellitus that cause numbness and pain, even paralysis. Recent studies demonstrate that Schwann cells (SCs) in the peripheral nervous system play an essential role in the pathogenesis of DPN. Furthermore, various transcriptome analyses constructed by RNA-seq or microarray have provided a comprehensive understanding of molecular mechanisms and regulatory interaction networks involved in many diseases. However, the detailed mechanisms and competing endogenous RNA (ceRNA) network of SCs in DPN remain largely unknown.

Methods

Whole-transcriptome sequencing technology was applied to systematically analyze the differentially expressed mRNAs, lncRNAs and miRNAs in SCs from DPN rats and control rats. Gene ontology (GO) and KEGG pathway enrichment analyses were used to investigate the potential functions of the differentially expressed genes. Following this, lncRNA-mRNA co-expression network and ceRNA regulatory network were constructed by bioinformatics analysis methods.

Results

The results showed that 2925 mRNAs, 164 lncRNAs and 49 miRNAs were significantly differently expressed in SCs from DPN rats compared with control rats. 13 mRNAs, 7 lncRNAs and 7 miRNAs were validated by qRT-PCR and consistent with the RNA-seq data. Functional and pathway analyses revealed that many enriched biological processes of GO terms and pathways were highly correlated with the function of SCs and the pathogenesis of DPN. Furthermore, a global lncRNA–miRNA–mRNA ceRNA regulatory network in DPN model was constructed and miR-212-5p and the significantly correlated lncRNAs with high degree were identified as key mediators in the pathophysiological processes of SCs in DPN. These RNAs would contribute to the diagnosis and treatment of DPN.

Conclusion

Our study has shown that differentially expressed RNAs have complex interactions among them. They also play critical roles in regulating functions of SCs involved in the pathogenesis of DPN. The novel competitive endogenous RNA network provides new insight for exploring the underlying molecular mechanism of DPN and further investigation may have clinical application value.

Folate inhibits miR-27a-3p expression during cervical carcinoma progression and oncogenic activity in human cervical cancer cells

BACKGROUND

Folate deficiency has been long implicated in cancer development. Although the role of folate in preventing cervical cancer is still unclear, emerging evidence shows that microRNAs (miRs) have great influence on tumor cell migration and invasion.

OBJECTIVES

The purpose of this study was to conduct an integrated analysis of miR expression in squamous cell carcinoma tissues with adequate or deficient serum folate. Further, study conducted tissue validation and functional analysis of miRs to uncover novel pathogenic mechanisms on the role of folate in squamous cell carcinoma (SCC).

MATERIALS AND METHODS

miR expression profiles were obtained from five paired primary SCC tumors with sufficient or deficient serum folate levels through Affymetrix GeneChip microRNA 4.0. This was followed by an integrated bioinformatics analysis and expanded sample size to verify core miRs by molecular biological validation. HeLa and SiHa cells with different concentrations of folate were used to clarify the roles of miR-27a on cell proliferation, migration, and invasion. MiR-27a expression was measured by the quantitative real-time polymerase chain reaction. Cell counting proliferation, wound healing, and transwell invasion assays were used to determine cell survival, proliferation, migration, and invasion abilities, respectively.

RESULTS

Our study found increasing miR-27a expression in serum of normal, high-grade squamous intraepithelial lesion (HSIL), and SCC tissues (in order of magnitude), which trend was negatively correlated with serum folate content. Further, there were significant differences in cellular miR-27a expression between 200 nM and 500 nM folate concentrations, with higher folate concentrations showing lower proliferation, migration, and invasion in SCC. Finally, miR-27a promoted proliferation and invasion in HeLa cells, whereas a miR-27a inhibitor blocked cell proliferation and invasion.

CONCLUSION

There is a significant association between miR-27a expression and folate during cervical carcinoma progression. Therefore, miR-27a could be used as a new biomarker for SCC diagnosis and prediction, suggesting a new therapeutic strategy for SCC treatment.

Biclustering analysis of transcriptome big data identifies condition-specific microRNA targets

We present a novel approach to identify human microRNA (miRNA) regulatory modules (mRNA targets and relevant cell conditions) by biclustering a large collection of mRNA fold-change data for sequence-specific targets. Bicluster targets were assessed using validated messenger RNA (mRNA) targets and exhibited on an average 17.0% (median 19.4%) improved gain in certainty (sensitivity + specificity). The net gain was further increased up to 32.0% (median 33.4%) by incorporating functional networks of targets. We analyzed cancer-specific biclusters and found that the PI3K/Akt signaling pathway is strongly enriched with targets of a few miRNAs in breast cancer and diffuse large B-cell lymphoma. Indeed, five independent prognostic miRNAs were identified, and repression of bicluster targets and pathway activity by miR-29 was experimentally validated. In total, 29 898 biclusters for 459 human miRNAs were collected in the BiMIR database where biclusters are searchable for miRNAs, tissues, diseases, keywords and target genes.

A Fast PC Algorithm for High Dimensional Causal Discovery with Multi-Core PCs

Discovering causal relationships from observational data is a crucial problem and it has applications in many research areas. The PC algorithm is the state-of-the-art constraint based method for causal discovery. However, runtime of the PC algorithm, in the worst-case, is exponential to the number of nodes (variables), and thus it is inefficient when being applied to high dimensional data, e.g., gene expression datasets. On another note, the advancement of computer hardware in the last decade has resulted in the widespread availability of multi-core personal computers. There is a significant motivation for designing a parallelized PC algorithm that is suitable for personal computers and does not require end users' parallel computing knowledge beyond their competency in using the PC algorithm. In this paper, we develop parallel-PC, a fast and memory efficient PC algorithm using the parallel computing technique. We apply our method to a range of synthetic and real-world high dimensional datasets. Experimental results on a dataset from the DREAM 5 challenge show that the original PC algorithm could not produce any results after running more than 24 hours; meanwhile, our parallel-PC algorithm managed to finish within around 12 hours with a 4-core CPU computer, and less than six hours with a 8-core CPU computer. Furthermore, we integrate parallel-PC into a causal inference method for inferring miRNA-mRNA regulatory relationships. The experimental results show that parallel-PC helps improve both the efficiency and accuracy of the causal inference algorithm.

High-Order Correlation Integration for Single-Cell or Bulk RNA-seq Data Analysis

Quantifying or labeling the sample type with high quality is a challenging task, which is a key step for understanding complex diseases. Reducing noise pollution to data and ensuring the extracted intrinsic patterns in concordance with the primary data structure are important in sample clustering and classification. Here we propose an effective data integration framework named as HCI (High-order Correlation Integration), which takes an advantage of high-order correlation matrix incorporated with pattern fusion analysis (PFA), to realize high-dimensional data feature extraction. On the one hand, the high-order Pearson's correlation coefficient can highlight the latent patterns underlying noisy input datasets and thus improve the accuracy and robustness of the algorithms currently available for sample clustering. On the other hand, the PFA can identify intrinsic sample patterns efficiently from different input matrices by optimally adjusting the signal effects. To validate the effectiveness of our new method, we firstly applied HCI on four single-cell RNA-seq datasets to distinguish the cell types, and we found that HCI is capable of identifying the prior-known cell types of single-cell samples from scRNA-seq data with higher accuracy and robustness than other methods under different conditions. Secondly, we also integrated heterogonous omics data from TCGA datasets and GEO datasets including bulk RNA-seq data, which outperformed the other methods at identifying distinct cancer subtypes. Within an additional case study, we also constructed the mRNA-miRNA regulatory network of colorectal cancer based on the feature weight estimated from HCI, where the differentially expressed mRNAs and miRNAs were significantly enriched in well-known functional sets of colorectal cancer, such as KEGG pathways and IPA disease annotations. All these results supported that HCI has extensive flexibility and applicability on sample clustering with different types and organizations of RNA-seq data.

microRNA-messenger RNA regulatory network of esophageal squamous cell carcinoma and the identification of miR-1 as a biomarker of patient survival

Emerging evidence indicates that microRNAs (miRNAs) play an important role in tumor carcinogenesis and progression by targeting gene expression. The goal of this study was to comprehensively analyze the vital functional miRNAs and their target genes in esophageal squamous cell carcinoma (ESCC) and to explore the clinical significance and mechanisms of miR-1 in ESCC. First, the miRNA and messenger RNA (mRNA) expression profiles of ESCC were determined with microarray technology. Using an integrated analysis of miRNAs and their target genes with multistep bioinformatics methods, the miRNA-mRNA regulatory network in ESCC was constructed. Next, miR-1 expression in 292 ESCC patients and its relationship with clinicopathological features and prognosis were detected by in situ hybridization. Furthermore, the biological functions of miR-1 were determined with in vitro and in vivo functional experiments. Finally, real-time quantitative reverse transcription polymerase chain reaction, Western blot analysis, and luciferase reporter assays were performed to verify the target genes of miR-1. In this study, 67 miRNAs and 2992 genes were significantly differentially expressed in ESCC tissues compared with their expression in adjacent normal tissues, and an miRNA-mRNA regulatory network comprising 59 miRNAs and 162 target mRNAs was identified. Low miR-1 expression was correlated with pathological T stage, lymph node metastasis, vessel invasion, and poor clinical outcome. miR-1 suppressed ESCC cell proliferation and invasion and promoted ESCC cell apoptosis. Fibronectin 1 (FN1) was verified as a direct target of miR-1. Taken together, the present results suggest that miR-1 may be a valuable prognostic predictor for ESCC, and the miR-1/FN1 axis may be a therapeutic target.

Effects of Icariin on Atherosclerosis and Predicted Function Regulatory Network in ApoE Deficient Mice

Objective. Icariin plays a pivotal role in ameliorating atherosclerosis for animal models although its comprehensive biological role remains largely unexplored. This study aimed to fully understand the effects of icariin on atherosclerosis in high-fat diet-induced ApoE^-/- mice and investigate mRNA-miRNA regulation based on microarray and bioinformatics analysis. Methods. The areas of atherosclerotic lesions in en face aorta were evaluated. Microarray analysis was performed on atherosclerotic aortic tissues. The integrative analysis of mRNA and miRNA profiling was utilized to suggest specific functions of gene and supply an integrated and corresponding method to study the protective effect of icariin on atherosclerosis. Results. Icariin attenuated the development of atherosclerosis that the mean atherosclerotic lesion area was reduced by 5.8% (P < 0.05). Significant changes were observed in mRNA and miRNA expression patterns. Several miRNAs obtained from the miRNA-Gene-Network might play paramount part in antiatherosclerotic effect of icariin, such as mmu-miR-6931-5p, mmu-miR-3547-5p, mmu-miR-5107-5p, mmu-miR-6368, and mmu-miR-7118-5p. Specific miRNAs and GO terms associated with icariin in the pathogenesis of atherosclerosis were validated using GO analysis and miRNA-GO-Network. MiRNA-Pathway-Network indicated that icariin induced miRNAs mainly regulate the signaling pathways of PI3K/Akt signaling pathway, Ras signaling pathway, ErbB signaling pathway, and VEGF signaling pathway in aorta atherosclerotic lesion. Conclusions. Our data provides evidence that icariin is able to exhibit one antiatherosclerotic action by mediating multiple biological processes or cascades, suggesting the pleiotropic effects of icariin in atherosclerosis alleviation. The identified gene functional categories and pathways are potentially valuable targets for future development of RNA-guided gene regulation to fight disease.

Genome-wide identification of microRNAs in decidual natural killer cells from patients with unexplained recurrent spontaneous abortion

PROBLEM

This study revealed miRNA regulation and functional microarray-based profiles of miRNAs in the natural killer (NK) cells of the decidual tissue obtained from patients with unexplained recurrent spontaneous abortion (URSA).

METHOD OF STUDY

Patients with URSA were categorized based on the occurrence of at least two or more successive spontaneous abortions between 7th and 10th gestational week. Total RNA was isolated from the NK cells of the decidual tissue obtained from patients with induced abortion at about the 8th gestational week. The potential contribution of regulatory miRNAs to a genetic predisposition to URSA was characterized by comparison with healthy and fertile controls and bioinformatics analyses.

RESULTS

Analysis of the miRNA expression profiles identified 50 miRNAs that were differentially expressed, including one down-regulated and 49 up-regulated miRNAs in the URSA group. MiRNA-Gene-Network, miRNA-GO-Network and miRNA-Gene-TF-Network were constructed. The key miRNAs, genes, GOs and core TFs in the network were determined.

CONCLUSION

Our results suggest that a close relationship exists between the aberrant miRNAs and URSA. Furthermore, these findings support the notion that altered expression of miRNAs may contribute to the clinical diagnosis of URSA and the potential to develop novel strategies for therapeutic targets against URSA.

Comprehensive analysis of differentially expressed microRNAs and mRNAs in dorsal root ganglia from streptozotocin-induced diabetic rats

Diabetic peripheral neuropathy is a common complication associated with diabetes mellitus with a pathogenesis that is incompletely understood. By regulating RNA silencing and post-transcriptional gene expression, microRNAs participate in various biological processes and human diseases. However, the relationship between microRNAs and the progress of diabetic peripheral neuropathy still lacks a thorough exploration. Here we used microarray microRNA and mRNA expression profiling to analyze the microRNAs and mRNAs which are aberrantly expressed in dorsal root ganglia from streptozotocin-induced diabetic rats. We found that 37 microRNAs and 1357 mRNAs were differentially expressed in comparison to non-diabetic samples. Bioinformatics analysis indicated that 399 gene ontology terms and 29 Kyoto Encyclopedia of Genes and Genomes pathways were significantly enriched in diabetic rats. Additionally, a microRNA-gene network evaluation identified rno-miR-330-5p, rno-miR-17-1-3p and rno-miR-346 as important players for network regulation. Finally, quantitative real-time polymerase chain reaction analysis was used to confirm the microarray results. In conclusion, this study provides a systematic perspective of microRNA and mRNA expression in dorsal root ganglia from diabetic rats, and suggests that dysregulated microRNAs and mRNAs may be important promotors of peripheral neuropathy. Our results may be the underlying framework of future studies regarding the effect of the aberrantly expressed genes on the pathophysiology of diabetic peripheral neuropathy.

hsa-miR-301a- and SOX10-dependent miRNA-TF-mRNA regulatory circuits in breast cancer

Breast cancer is the most common cancer among women and the molecular pathways that play main roles in breast cancer regulation are still not completely understood. MicroRNAs (miRNAs) and transcription factors (TFs) are important regulators of gene expression. It is important to unravel the relation of TFs, miRNAs, and their targets within regulatory networks to clarify the processes that cause breast cancer and the progression of it. In this study, mRNA and miRNA expression studies including breast tumors and normal samples were extracted from the GEO microarray database. Two independent mRNA studies and a miRNA study were selected and reanalyzed. Differentially expressed (DE) mRNAs and miRNAs between breast tumor and normal samples were listed by using BRBArray Tools. CircuitsDB2 analysis conducted with DE miRNAs and mRNAs resulted in 3 significant circuits that are SOX10- and hsamiR-301a-dependent. The following significant circuits were characterized and validated bioinformatically by using web-based tools: SOX10→hsa-miR-301a→HOXA3, SOX10→hsa-miR-301a→KIT, and SOX10→hsa-miR-301a→NFIB. It can be concluded that regulatory motifs involving miRNAs and TFs may be useful for understanding breast cancer regulation and for predicting new biomarkers.

Comprehensive gene and microRNA expression profiling on cardiovascular system in zebrafish co-exposured of SiNPs and MeHg

Air pollution has been shown to increase cardiovascular diseases. However, little attention has been paid to the combined effects of PM and air pollutants on the cardiovascular system. To explore this, a high-throughput sequencing technology was used to determine combined effects of silica nanoparticles (SiNPs) and MeHg in zebrafish. Our study demonstrated that SiNPs and MeHg co-exposure could cause significant changes in mRNA and miRNA expression patterns in zebrafish. The differentially expressed (DE) genes in profiles 17 and 26 of STC analysis suggest that SiNPs and MeHg co-exposure had more proinflammatory and cardiovascular toxicity in zebrafish than single exposure. Major gene functions associated with cardiovascular system in the co-exposed zebrafish were discerned from the dynamic-gene-network, including stxbp1a, celf4, ahr1b and bai2. In addition, the prominently expressed pathway of cardiac muscle contraction was targeted by 3 DE miRNAs identified by the miRNA-pathway-network (dre-miR-7147, dre-miR-26a and dre-miR-375), which included 23 DE genes. This study presents a global view of the combined SiNPs and MeHg toxicity on the dynamic expression of both mRNAs and miRNAs in zebrafish, and could serve as fundamental research clues for future studies, especially on cardiovascular system toxicity.

Predictive analysis of long non-coding RNA expression profiles in diffuse large B-cell lymphoma

Long non-coding RNAs (lncRNAs) are implicated in many tumors. To find novel targets for study of diffuse large B-cell lymphoma (DLBCL), our team performed genome-wide analyses of lncRNA expression in 5 DLBCL cell lines using the 4*180K Agilent lncRNA Chip system, and in normal B cells. Five lncRNAs were validated by quantitative reverse transcription polymerase chain reaction. The differentially expressed lncRNAs and mRNAs were identified via false discovery rate and fold-change filtering. Potential targets correlated with DLBCL were recognized via gene ontology and pathway analysis. Establishment of the co-expression network was done using Cytoscape. In total, 1053 lncRNAs and 4391 mRNAs were dysregulated in DLBCL cells, being comparing with normal B cells. The results suggested that the expressions of the 5 lncRNAs were consistent with the chip results. Several terms including the cell cycle, apoptosis, B cell receptor and NF-κB signaling pathways were important in the progression of DLBCL. The chromosome locations of a few lncRNAs and the associated coexpressed genes were demonstrated by cis-regulatory gene analyses. The results of trans-analyses showed that multiple transcription factors regulated lncRNA and gene expression. Those outstanding lncRNAs in each group were implicated in the regulation of the TF-lncRNA-target gene network. Our study identified a set of lncRNAs differentially expressed in DLBCL cells.

Expression Profiling of Cellular MicroRNA in Asymptomatic HBsAg Carriers and Chronic Hepatitis B Patients

Background

MicroRNAs (miRNAs) may serve as potential molecular markers to predict liver injury resulting from chronic hepatitis B (CHB). In the present study, we want to study the expression profile and clinical significance of miRNAs at different stages of CHB virus infection.

Methods

Using miRNA microarray, we investigated the global expression profiles of cellular miRNA in asymptomatic hepatitis B antigen carriers (ASCs) and CHB patients, compared with healthy controls (HCs).

Results

We identified 79 and 203 differentially expressed miRNAs in the peripheral blood mononuclear cells of ASCs and CHB patients compared to HCs, respectively. Some of these miRNAs were common to ASCs and CHB patients, but another set of miRNAs that showed differential expression between ASCs and CHB patients was also identified. Gene ontology and pathway enrichment analysis showed that the target genes of the identified miRNAs played a role in important biological functions, such as learning or memory, cell-cell adherens junction, ion channel inhibitor activity, TGF-beta signaling pathway, and p53 signaling pathway.

Conclusion

We identified some significant differentially expressed miRNA in different phases of HBV infection, which might serve as biomarkers or therapeutic targets in the future.

Circular RNA Profiling and Bioinformatic Modeling Identify Its Regulatory Role in Hepatic Steatosis

Circular RNAs (circRNAs) exhibit a wide range of physiological and pathological activities. To uncover their role in hepatic steatosis, we investigated the expression profile of circRNAs in HepG2-based hepatic steatosis induced by high-fat stimulation. Differentially expressed circRNAs were subjected to validation using QPCR and functional analyses using principal component analysis, hierarchical clustering, target prediction, gene ontology (GO), and pathway annotation, respectively. Bioinformatic integration established the circRNA-miRNA-mRNA regulatory network so as to identify the mechanisms underlying circRNAs' metabolic effect. Here we reported that hepatic steatosis was associated with a total of 357 circRNAs. Enrichment of transcription-related GOs, especially GO: 0006355, GO: 004589, GO: 0045944, GO: 0045892, and GO: 0000122, demonstrated their specific actions in transcriptional regulation. Lipin 1 (LPIN1) was recognized to mediate the transcriptional regulatory effect of circRNAs on metabolic pathways. circRNA-miRNA-mRNA network further identified the signaling cascade of circRNA_021412/miR-1972/LPIN1, which was characterized by decreased level of circRNA_021412 and miR-1972-based inhibition of LPIN1. LPIN1-induced downregulation of long chain acyl-CoA synthetases (ACSLs) expression finally resulted in the hepatosteatosis. These findings identify circRNAs to be important regulators of hepatic steatosis. Transcription-dependent modulation of metabolic pathways may underlie their effects, partially by the circRNA_021412/miR-1972/LPIN1 signaling.

miR‑181b‑5p mediates TGF‑β1-induced epithelial-to-mesenchymal transition in non-small cell lung cancer stem-like cells derived from lung adenocarcinoma A549 cells

The ability of non-small cell lung cancer (NSCLC) cells to invade and metastasize is associated with epithelial-to-mesenchymal transition (EMT). The process of EMT is, at least in part, regulated by microRNAs. However, it is unknown whether microRNAs regulate EMT in cancer stem-like cells (CSLCs), or which microRNAs are involved. In the present study, we compared microRNA expression in A549 cells, TGF-β1-treated A549 cells, CSLCs characterized by the CD133⁺/CD326⁺ phenotype, and TGF-β1-treated CSLCs. We found that miR-181b-5p expression was upregulated by TGF-β1. Moreover, the overexpression of the miR-181b-5p in A549 cells and CD133⁺/CD326⁺ cells resulted in the down-regulation of the E-cadherin and increased invasion and metastasis in vitro and in vivo. Accordingly, the knockdown of miR-181b-5p partially restored E-cadherin expression. These results suggest that miR-181b-5p regulates TGF-β1-induced EMT by targeting E-cadherin not only in normal A549 cells but also in CD133⁺/CD326⁺ cells which have characteristics of CSLCs. Thus, miR-181b-5p represents a new therapeutic target in NSCLC.

The Profile of Serum microRNAs Predicts Prognosis for Resected Gastric Cancer Patients Receiving Platinum-Based Chemotherapy

BACKGROUND AND AIM

Adjuvant chemotherapy is an important component in the treatment of gastric cancer (GC) patients; however, some patients do not respond to the drugs. We aimed to develop a practical profile based on serum microRNAs (miRNAs) that can be used to predict patients likely to respond to treatment.

METHODS

Microarrays were used to screen cisplatin-resistant SGC7901/DDP GC cells and the parental SGC7901 cell lines for miRNAs related to chemotherapy sensitivity. The correlation between the expression patterns of identified serum miRNAs and overall survival was confirmed in 68 GC patients. Furthermore, we also validated the signature of the serum miRNAs in an independent cohort of 50 GC patients.

RESULTS

From the screening microarrays, we focused on miR-15a, miR-15b and miR-93 as downregulated miRNAs in the SGC7901/DDP cells and miR-27a, miR-106a and miR-664 as upregulated miRNAs. Only serum miR-106, miR-15a, miR-93 and miR-664 were useful in predicting the prognosis of patients who received adjuvant chemotherapy. We identified a signature of four serum miRNAs (miR-106, miR-15a, miR-93 and miR-664) that, when combined, can be used as a risk score for overall survival. Patients with a higher risk score had worse prognosis (p < 0.05). For the independent cohort of patients, the signature of the four miRNAs predicted prognosis well.

CONCLUSION

Our data showed that the risk score derived from the four serum miRNAs was closely associated with the overall survival in GC patients who received adjuvant chemotherapy.

miRNA-mRNA network involved in folliculogenesis interactome: systems biology approach

At later phases of folliculogenesis, the mammalian ovarian follicle contains layers of granulosa cells surrounding an antral cavity. To better understand the molecular basis of follicular growth and granulosa cell maturation, we study transcriptome profiling of granulosa cells from small (<5 mm) and large (>10 mm) bovine follicles using simultaneous method of Affymetrix microarrays (24,128 probe sets) and RNA-Seq data sets. This study proposes a computational method to discover the functional miRNA-mRNA regulatory modules, that is, groups of miRNAs and their target mRNAs that are believed to take part cooperatively in post-transcriptional gene regulation under specific conditions. The reconstructed network was named Integrated miRNA-mRNA Bipartite Network. 277 genes and 6 key modules were disclosed through clustering for mRNA master list. The 66 genes are among the genes that belong to at least two modules. All these genes, being involved in at least one of the phenomena, namely cell survival, proliferation, metastasis and apoptosis, have an overexpression pattern (P < 0.01). For miRNA master list, a total of 172 sequences were differentially expressed (P < 0.01) between dominant (large) and each of subordinate (small) follicles. Within the follicle, these miRNAs were predominantly expressed in mural granulosa cells. Finally, predicted and validated targets of these miRNAs enriched in dominant (large) follicles were identified, which are mapped to signaling pathways involved in follicular cell proliferation, steroidogenesis, PI3K/AKT/mTOR and Ras/Raf/MEK/ERK. The identification of miRNAs and their target mRNAs and the construction of their regulatory networks may give new insights into biological procedures.

Identification of miRNA-mRNA Modules in Colorectal Cancer Using Rough Hypercuboid Based Supervised Clustering

Differences in the expression profiles of miRNAs and mRNAs have been reported in colorectal cancer. Nevertheless, information on important miRNA-mRNA regulatory modules in colorectal cancer is still lacking. In this regard, this study presents an application of the RH-SAC algorithm on miRNA and mRNA expression data for identification of potential miRNA-mRNA modules. First, a set of miRNA rules was generated using the RH-SAC algorithm. The mRNA targets of the selected miRNAs were identified using the miRTarBase database. Next, the expression values of target mRNAs were used to generate mRNA rules using the RH-SAC. Then all miRNA-mRNA rules have been integrated for generating networks. The RH-SAC algorithm unlike other existing methods selects a group of co-expressed miRNAs and mRNAs that are also differentially expressed. In total 17 miRNAs and 141 mRNAs were selected. The enrichment analysis of selected mRNAs revealed that our method selected mRNAs that are significantly associated with colorectal cancer. We identified novel miRNA/mRNA interactions in colorectal cancer. Through experiment, we could confirm that one of our discovered miRNAs, hsa-miR-93-5p, was significantly up-regulated in 75.8% CRC in comparison to their corresponding non-tumor samples. It could have the potential to examine colorectal cancer subtype specific unique miRNA/mRNA interactions.

Roles of microRNAs in immunopathogenesis of non-alcoholic fatty liver disease revealed by integrated analysis of microRNA and mRNA expression profiles

BACKGROUND

The integrative analysis of microRNA and mRNA expression profiles can elucidate microRNA-targeted gene function. We used this technique to elucidate insights into the immunological pathology of non-alcoholic fatty liver disease (NAFLD).

METHODS

We analyzed differentially expressed microRNA and mRNA expression profiles of CD4+ T lymphocytes from the liver and mesenteric lymph nodes (MLNs) of mice with NAFLD using microarrays and RNA sequencing. Normal mice were used as controls. The target genes of microRNAs were predicted by TargetScan. Integrative analysis showed that the mRNAs were overlapped with microRNAs. Furthermore, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to predict the key genes and pathways. Then, 16 microRNAs and 10 mRNAs were validated by qRT-PCR.

RESULTS

Microarray analysis suggested that 170 microRNAs were significantly de-regulated in CD4+ T lymphocytes from the liver between the two groups. Eighty mRNAs corresponded with microRNA targeted genes. KEGG analysis indicated that the MAPK pathway was consistently augmented in the liver of NAFLD mice. miR-23b, let-7e, miR-128 and miR-130b possibly played significant parts in the MAPK pathways. Furthermore, between the two groups, 237 microRNAs were significantly de-regulated in CD4+ T lymphocytes from MLNs. 38 mRNAs coincided with microRNA target genes. The metabolic pathway was consistently enriched in the MLNs of NAFLD mice. miR-206-3p, miR-181a-5p, miR-29c-3p and miR-30d-5p likely play important roles in the regulation of metabolic pathways.

CONCLUSION

The results of this study presented a new perspective on the application of integrative analysis to identify complex regulation means involved in the immunological pathogenesis of NAFLD.

Tools for Sequence-Based miRNA Target Prediction: What to Choose?

MicroRNAs (miRNAs) are defined as small non-coding RNAs ~22 nt in length. They regulate gene expression at a post-transcriptional level through complementary base pairing with the target mRNA, leading to mRNA degradation and therefore blocking translation. In the last decade, the dysfunction of miRNAs has been related to the development and progression of many diseases. Currently, researchers need a method to identify precisely the miRNA targets, prior to applying experimental approaches that allow a better functional characterization of miRNAs in biological processes and can thus predict their effects. Computational prediction tools provide a rapid method to identify putative miRNA targets. However, since a large number of tools for the prediction of miRNA:mRNA interactions have been developed, all with different algorithms, the biological researcher sometimes does not know which is the best choice for his study and many times does not understand the bioinformatic basis of these tools. This review describes the biological fundamentals of these prediction tools, characterizes the main sequence-based algorithms, and offers some insights into their uses by biologists.

MicroRNA expression profiles and networks in CXCL12‑stimulated human endometrial stromal cells

The chemokine stromal cell-derived factor-1 (C-X-C motif chemokine ligand 12; CXCL12) is important in the recruitment of leukocytes to the peritoneal cavity and the regulation of endometriotic tissue growth in endometriosis patients. However, the alterations in microRNA (miRNA) expression induced by CXCL12 remain to be fully elucidated. The present study evaluated key miRNAs in CXCL12‑stimulated endometrial stromal cells (ESCs), and investigated the underlying cellular regulatory mechanisms of CXCL12 in endometriosis by building networks between miRNAs, genes and gene ontologies (GOs). Differential expression of miRNAs and mRNAs induced by CXCL12 stimulation in ESCs was measured using miRNA and gene chips, and it was observed that 35 miRNAs and 1,671 mRNAs were differentially expressed. Using potential target genes of the 35 miRNAs, intersections of these genes were examined and 63 intersection genes were identified. A total of 39 GOs were obtained for these intersection genes, based on information from GO databases, including immune cell chemoattractants, inflammatory and immune responses, and pathological processes of endometriotic lesions in endometriosis. In addition, miRNA‑gene networks were built according to the GO and Kyoto Encyclopedia of Genes and Genomes databases. The present study, to the best of our knowledge, provides the most complete miRNAome and mRNAome profiles, and the most detailed investigation of the underlying cellular regulatory mechanisms, of the effects of CXCL12 in endometriosis. These results may facilitate the complete elucidation of the role of CXCL12 in endometriosis, and its underlying epigenetic mechanisms.

DMirNet: Inferring direct microRNA-mRNA association networks

Background

MicroRNAs (miRNAs) play important regulatory roles in the wide range of biological processes by inducing target mRNA degradation or translational repression. Based on the correlation between expression profiles of a miRNA and its target mRNA, various computational methods have previously been proposed to identify miRNA-mRNA association networks by incorporating the matched miRNA and mRNA expression profiles. However, there remain three major issues to be resolved in the conventional computation approaches for inferring miRNA-mRNA association networks from expression profiles. 1) Inferred correlations from the observed expression profiles using conventional correlation-based methods include numerous erroneous links or over-estimated edge weight due to the transitive information flow among direct associations. 2) Due to the high-dimension-low-sample-size problem on the microarray dataset, it is difficult to obtain an accurate and reliable estimate of the empirical correlations between all pairs of expression profiles. 3) Because the previously proposed computational methods usually suffer from varying performance across different datasets, a more reliable model that guarantees optimal or suboptimal performance across different datasets is highly needed.

Results

In this paper, we present DMirNet, a new framework for identifying direct miRNA-mRNA association networks. To tackle the aforementioned issues, DMirNet incorporates 1) three direct correlation estimation methods (namely Corpcor, SPACE, Network deconvolution) to infer direct miRNA-mRNA association networks, 2) the bootstrapping method to fully utilize insufficient training expression profiles, and 3) a rank-based Ensemble aggregation to build a reliable and robust model across different datasets.

Our empirical experiments on three datasets demonstrate the combinatorial effects of necessary components in DMirNet. Additional performance comparison experiments show that DMirNet outperforms the state-of-the-art Ensemble-based model [1] which has shown the best performance across the same three datasets, with a factor of up to 1.29. Further, we identify 43 putative novel multi-cancer-related miRNA-mRNA association relationships from an inferred Top 1000 direct miRNA-mRNA association network.

Conclusions

We believe that DMirNet is a promising method to identify novel direct miRNA-mRNA relations and to elucidate the direct miRNA-mRNA association networks. Since DMirNet infers direct relationships from the observed data, DMirNet can contribute to reconstructing various direct regulatory pathways, including, but not limited to, the direct miRNA-mRNA association networks.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-016-0373-1) contains supplementary material, which is available to authorized users.

Identify bilayer modules via pseudo-3D clustering: applications to miRNA-gene bilayer networks

Module identification is a frequently used approach for mining local structures with more significance in global networks. Recently, a wide variety of bilayer networks are emerging to characterize the more complex biological processes. In the light of special topological properties of bilayer networks and the accompanying challenges, there is yet no effective method aiming at bilayer module identification to probe the modular organizations from the more inspiring bilayer networks. To this end, we proposed the pseudo-3D clustering algorithm, which starts from extracting initial non-hierarchically organized modules and then iteratively deciphers the hierarchical organization of modules according to a bottom-up strategy. Specifically, a modularity function for bilayer modules was proposed to facilitate the algorithm reporting the optimal partition that gives the most accurate characterization of the bilayer network. Simulation studies demonstrated its robustness and outperformance against alternative competing methods. Specific applications to both the soybean and human miRNA-gene bilayer networks demonstrated that the pseudo-3D clustering algorithm successfully identified the overlapping, hierarchically organized and highly cohesive bilayer modules. The analyses on topology, functional and human disease enrichment and the bilayer subnetwork involved in soybean fat biosynthesis provided both the theoretical and biological evidence supporting the effectiveness and robustness of pseudo-3D clustering algorithm.

Analysis of altered microRNA expression profiles in the kidney tissues of ethylene glycol-induced hyperoxaluric rats

Calcium oxalate stones account for >80% of urinary stones, however the mechanisms underlying their formation remains to be elucidated. Hyperoxaluria serves an important role in the pathophysiological process of stone formation. In the present study, differences in the miRNA expression profiles between experimental hyperoxaluric rats and normal rats were analyzed, in order to identify target genes and signaling pathways involved in the pathogenesis of hyperoxaluria. Ethylene glycol and ammonium chloride was fed to male hyperoxaluric rats (EXP) and normal age-matched male rats (CON). The oxalate concentration in the urine of each experimental rat was collected every 24 h and measured on day 14. Three rats exhibiting the highest concentrations were selected for microarray analysis. Microarray analysis was performed to evaluate differences in the expression of microRNA (miRNA) in the kidney tissues from EXP and CON groups, and miRNAs that exhibited a >2-fold or a <0.5-fold alteration in expression between these groups were screened for differential expression patterns according to the threshold P-values. Reverse transcription-quantitative polymerase chain reaction analysis was employed to confirm the microarray results. In order to predict the potential role of miRNAs in pathophysiological processes, gene ontology (GO), pathway and target prediction analyses were conducted. A total of 28 miRNAs were observed to be differentially expressed (>2-fold change) between EXP and CON groups. Among these miRNAs, 20 were upregulated and 8 were downregulated. GO and pathway analyses revealed that the insulin resistance and phosphatidylinositol-bisphosphonate 3-kinase/AKT serine threonine kinase signaling pathways were potentially associated with miRNA regulation in this setting. In conclusion, the results of the present study identified differentially expressed miRNAs in hyperoxaluric rats, and provided a novel perspective for the role of miRNAs in the formation of calcium oxalate stones.

Profiling of downregulated blood-circulating miR-150-5p as a novel tumor marker for cholangiocarcinoma

Altered microRNA (miRNA) expression plays a role in cholangiocarcinoma (CCA) development; thus, detection of blood-circulating miRNAs could be useful as CCA markers. This study profiled serum miRNA levels in patients with primary sclerosing cholangitis (PSC) and CCA and then assessed the role of miR-150-5p in CCA progression in vitro. Three samples were randomly selected from each of 50 sera of healthy controls, 30 PSC sera, and 28 CCA sera with matched bile samples for miRNA microarray profiling. The dysregulated miRNAs were confirmed using qRT-PCR, and miR-150-5p was selected for further in vitro and ex vivo studies. The miRNA microarray identified three dysregulated miRNAs in both CCA and PSC samples, while miR-150-5p level was consistently lower in CCA sera, bile, and tissues than in normal control and PSC sera (P < 0.05). Furthermore, levels of miR-150-5p were associated with serum carbohydrate antigen 19-9 (CA19-9) levels and CCA pathological grade. Bioinformatic Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses showed that miR-150-5p could regulate hand-full gene pathways, including cancer pathway (P < 0.01). However, overexpression of miR-150-5p inhibited proliferation, migration, and invasion capability of CCA cells (P < 0.05). Luciferase reporter assay showed that miR-150-5p bound to an oncogene Ets including gene-1 (ELK1), and Western blot data confirmed that miR-150-5p suppressed ELK1 expression in CCA cell lines. These results suggest that reduced miR-150-5p expression could contribute to CCA development and progression due to uncontrolled ELK1 expression. Thus, further study could evaluate miR-150-5p as a novel target and predictor for CCA prevention and treatment.

Anticancer bioactive peptide-3 inhibits human gastric cancer growth by targeting miR-338-5p

BACKGROUND

Cancer incidence and mortality have been increasing in China, making cancer the leading cause of death since 2010 and a major public health concern in the country. Cancer stem cells have been studied in relation to the treatment of different malignancies, including gastric cancer. Anticancer bioactive peptide-3 (ACBP-3) can induce the apoptosis of gastric cancer stem cells (GCSCs) and reduce their tumorigenicity. In the present study, for the first time, we used a miRNA microarray and bioinformatics analysis to identify differentially expressed miRNAs in ACBP-3-treated GCSCs and GCSC-derived tumors in a xenograft model and functionally verified the identified miRNAs. miR-338-5p was selected based on its significant upregulation by ACBP-3 both in cultured GCSCs and in tumor tissues.

RESULTS

miR-338-5p was downregulated in GCSCs compared with normal gastric epithelial cells, and the ectopic restoration of miR-338-5p expression in GCSCs inhibited cell proliferation and induced apoptosis, which correlated with the upregulation of the pro-apoptotic Bcl-2 proteins BAK and BIM. We also found that ACBP-3-treated GCSCs could respond to lower effective doses of cisplatin (DDP) or 5-fluorouracil (5-FU), possibly because ACBP-3 induced the expression of miR-338-5p and the BAK and BIM proteins and promoted GCSC apoptosis.

CONCLUSIONS

Our data indicate that miR-338-5p is part of an important pathway for the inhibition of human gastric cancer stem cell proliferation by ACBP-3 combined with chemotherapeutics. ACBP-3 could suppress GCSC proliferation and lower the required effective dose of cisplatin or 5-fluorouracil. Therefore, this study provides not only further evidence for the remarkable anti-tumor effect of ACBP-3 but also a possible new approach for the development of GCSC-targeting therapies.

miRNA targeted signaling pathway in the early stage of denervated fast and slow muscle atrophy

Denervation often results in skeletal muscle atrophy. Different mechanisms seem to be involved in the determination between denervated slow and fast skeletal muscle atrophy. At the epigenetic level, miRNAs are thought to be highly involved in the pathophysiological progress of denervated muscles. We used miRNA microarrays to determine miRNA expression profiles from a typical slow muscle (soleus muscle) and a typical fast muscle (tibialis anterior muscle) at an early denervation stage in a rat model. Results showed that miR-206, miR-195, miR-23a, and miR-30e might be key factors in the transformation process from slow to fast muscle in denervated slow muscles. Additionally, certain miRNA molecules (miR-214, miR-221, miR-222, miR-152, miR-320, and Let-7e) could be key regulatory factors in the denervated atrophy process involved in fast muscle. Analysis of signaling pathway networks revealed the miRNA molecules that were responsible for regulating certain signaling pathways, which were the final targets (e.g., p38 MAPK pathway; Pax3/Pax7 regulates Utrophin and follistatin by HDAC4; IGF1/PI3K/Akt/mTOR pathway regulates atrogin-1 and MuRF1 expression via FoxO phosphorylation). Our results provide a better understanding of the mechanisms of denervated skeletal muscle pathophysiology.

A Novel Method to Detect Functional microRNA Regulatory Modules by Bicliques Merging

MicroRNAs (miRNAs) are post-transcriptional regulators that repress the expression of their targets. They are known to work cooperatively with genes and play important roles in numerous cellular processes. Identification of miRNA regulatory modules (MRMs) would aid deciphering the combinatorial effects derived from the many-to-many regulatory relationships in complex cellular systems. Here, we develop an effective method called BiCliques Merging (BCM) to predict MRMs based on bicliques merging. By integrating the miRNA/mRNA expression profiles from The Cancer Genome Atlas (TCGA) with the computational target predictions, we construct a weighted miRNA regulatory network for module discovery. The maximal bicliques detected in the network are statistically evaluated and filtered accordingly. We then employed a greedy-based strategy to iteratively merge the remaining bicliques according to their overlaps together with edge weights and the gene-gene interactions. Comparing with existing methods on two cancer datasets from TCGA, we showed that the modules identified by our method are more densely connected and functionally enriched. Moreover, our predicted modules are more enriched for miRNA families and the miRNA-mRNA pairs within the modules are more negatively correlated. Finally, several potential prognostic modules are revealed by Kaplan-Meier survival analysis and breast cancer subtype analysis.

AVAILABILITY

BCM is implemented in Java and available for download in the supplementary materials, which can be found on the Computer Society Digital Library at http://doi.ieeecomputersociety.org/10.1109/ TCBB.2015.2462370.

Long noncoding RNA expression profile analysis of colorectal cancer and metastatic lymph node based on microarray data

Long noncoding RNAs (lncRNAs) are emerging as an important part of biological progress in cancers, yet the aberrant lncRNAs implicated in colorectal cancer (CRC) with lymph node metastasis remain unknown. In this study, a total of 390 lncRNA transcripts and 508 mRNA transcripts were dysregulated in tumor tissues compared with paired metastatic lymph nodes. Functional prediction showed that lots of lncRNAs might be involved in biological pathways related to CRC metastasis by cis-regulation and trans-regulation of coexpressed genes. As a representative, ENST00000430471 was associated with cell proliferation and invasion of CRC cells. These results provided support for further investigations of the metastatic pathogenesis of CRC.

Comprehensive gene and microRNA expression profiling reveals miR-206 inhibits MET in lung cancer metastasis

MiRNAs associated with the metastasis of lung cancer remain largely unexplored. In this study, gene and miRNA expression profiling were performed to analyze the global expression of mRNAs and miRNAs in human high- and low-metastatic lung cancer cell strains. By developing an integrated bioinformatics analysis, six miRNAs (miR-424-3p, miR-450b-5p, miR-335-5p, miR-34a-5p, miR-302b-3p and miR-206) showed higher target gene degrees in the miRNA-gene network and might be potential metastasis-related miRNAs. Using the qRT-PCR method, the six miRNAs were further confirmed to show a significant expression difference between human lung cancer and normal tissue samples. Since miR-206 showed lower expression both in lung cancer tissues and cell lines, it was used as an example for further functional verification. The wound healing assay and transwell invasion assay showed that miR-206 mimics significantly inhibited the cell migration and invasion of the high-metastatic lung cancer 95D cell strain. One of its predicted targets in our miRNA-gene network, MET, was also obviously decreased at the protein level when miR-206 was overexpressed. Instead, miR-206 inhibitors increased MET protein expression, cell migration and invasion of the low-metastatic lung cancer 95C cell strain. Meanwhile, the luciferase assay showed that MET was a direct target of miR-206. Furthermore, MET gene silence showed a similar anti-migration and anti-invasion effect with miR-206 mimics in 95D cells and could partially attenuate the migration- and invasion-promoting effect of miR-206 inhibitors in 95C cells, suggesting that miR-206 targets MET in lung cancer metastasis. Finally, we also demonstrated that miR-206 can significantly inhibit lung cancer proliferation and metastasis in mouse models. In conclusion, our study provided a miRNA-gene regulatory network in lung cancer metastasis and further demonstrated the roles of miR-206 and MET in this process, which enhances the understanding of the regulatory mechanism in lung cancer metastasis.

Integrated Data Set of microRNAs and mRNAs Involved in Severe Intrauterine Adhesion

BACKGROUND

Adhesion tissue is formed following injury to the uterine basal layer. Currently, there is no effective treatment for severe intrauterine adhesion (IUA), which causes loss of reproductive function. Enhanced understanding of the molecular mechanisms driving severe IUA would be beneficial for the treatment.

METHODS

Differentially expressed microRNAs (miRNAs) and messenger RNAs (mRNAs) in severe IUA (n = 3) and normal (n = 3) endometrium were analyzed by high-throughput microarray analysis. Subsequently, the target genes of the differentially expressed miRNAs were predicted and found to overlap with the differentially expressed mRNAs. Gene Ontology and pathway analyses were performed for the intersecting genes. Three of the significantly dysregulated miRNAs and 4 of their target mRNAs were further assessed using quantitative real-time polymerase chain reaction (PCR) in 10 severe IUA and 10 normal endometrium samples.

RESULTS

Microarray analysis indicated that 26 miRNAs and 1180 mRNAs were significantly different between the 2 groups. Of these, 16 miRNAs and 54 mRNAs overlapped with putative miRNA target genes and prediction of target gene. Real-time PCR revealed upregulation of hsa-miR-513a-5p and has-miR-135a-3p and downregulation of hsa-miR-543 and their corresponding target genes, plus downregulation of ADAM9 (a disintegrin-containing and metalloproteinases) and lysyl oxidase and upregulation of CDH2 (N-cadherin) and COL16A1 (collagen 16A1). Both CDH2 and COL16A1 were bioinformatically predicted and confirmed in vitro as target genes of miR-543.

CONCLUSION

This study provides an integrated data set of the miRNA and mRNA profiles in severe IUA, showing involvement of many miRNAs and their target genes. Further analysis of these genes will help in understanding of the molecular mechanism of IUA formation.

Endogenous microRNA sponges: evidence and controversy

The competitive endogenous RNA (ceRNA) hypothesis proposes that transcripts with shared microRNA (miRNA) binding sites compete for post-transcriptional control. This hypothesis has gained substantial attention as a unifying function for long non-coding RNAs, pseudogene transcripts and circular RNAs, as well as an alternative function for messenger RNAs. Empirical evidence supporting the hypothesis is accumulating but not without attracting scepticism. Recent studies that model transcriptome-wide binding-site abundance suggest that physiological changes in expression of most individual transcripts will not compromise miRNA activity. In this Review, we critically evaluate the evidence for and against the ceRNA hypothesis to assess the impact of endogenous miRNA-sponge interactions.

Integrative microRNA-gene expression network analysis in genetic hypercalciuric stone-forming rat kidney

Background. MicroRNAs (miRNAs) influence a variety of biological functions by regulating gene expression post-transcriptionally. Aberrant miRNA expression has been associated with many human diseases. Urolithiasis is a common disease, and idiopathic hypercalciuria (IH) is an important risk factor for calcium urolithiasis. However, miRNA expression patterns and their biological functions in urolithiasis remain unknown.

Methods and Results. A multi-step approach combining microarray miRNA and mRNA expression profile and bioinformatics analysis was adopted to analyze dysregulated miRNAs and genes in genetic hypercalciuric stone-forming (GHS) rat kidneys, using normal Sprague-Dawley (SD) rats as controls. We identified 2418 mRNAs and 19 miRNAs as significantly differentially expressed, over 700 gene ontology (GO) terms and 83 KEGG pathways that were significantly enriched in GHS rats. In addition, we constructed an miRNA-gene network that suggested that rno-miR-674-5p, rno-miR-672-5p, rno-miR-138-5p and rno-miR-21-3p may play important roles in the regulatory network. Furthermore, signal-net analysis suggested that NF-kappa B likely plays a crucial role in hypercalciuria urolithiasis.

Conclusions. This study presents a global view of mRNA and miRNA expression in GHS rat kidneys, and suggests that miRNAs may be important in the regulation of hypercalciuria. The data provide valuable insights for future research, which should aim at validating the role of the genes featured here in the pathophysiology of hypercalciuria.

miR-130b-3p Modulates Epithelial-Mesenchymal Crosstalk in Lung Fibrosis by Targeting IGF-1

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive and usually lethal fibrotic lung disease with largely unknown etiology and pathogenesis. Evidence suggests microRNAs (miRNA) contribute to pathogenesis of IPF. In this study, we sought to identify miRNA expression signatures and determine the role of miR-130b-3p in lung fibrosis. The miRNA expression profile of the lungs from patients with IPF and normal donors was determined by Affymetrix microarray, and transcriptome with Affymetrix array. The functions and signal pathways as well as miRNA-mRNA networks were established by bioinformatics analysis. Luciferase assays and ELISA were used to confirm the miRNA target gene. The effect of miRNA-transfected epithelium on fibroblast activities was assessed using a co-culture system. The fibroblast activities were determined by qRT-PCR, western blotting, Transwell and BrdU assays. Seven miRNAs were significantly decreased in IPF lungs, with miR-130b-3p being the highest in the miRNA-mRNA network. Insulin-like growth factor (IGF-1) was a target gene of miR-130b-3p in the epithelium. miR-130b-3p inhibition in the epithelium induced collagen I expression and enhanced the proliferation and migration ability of fibroblast in co-culture systems, which mimicked the functions of exogenous IGF-1 on fibroblasts. Neutralizing IGF-1 with an antibody significantly reduced the modulatory effects of miR-130b-3p inhibitor-transfected epithelium on the activation of fibroblasts. Our results show that miR-130b-3p was downregulated in IPF lungs. miR-130b-3p downregulation contributed to the activation of fibroblasts and the dysregulated epithelial-mesenchymal crosstalk by promoting IGF-1 secretion from lung epithelium, suggesting a key regulatory role for this miRNA in preventing lung fibrosis.

The modularity and dynamicity of miRNA-mRNA interactions in high-grade serous ovarian carcinomas and the prognostic implication

Ovarian carcinoma is the fifth-leading cause of cancer death among women in the United States. Major reasons for this persistent mortality include the poor understanding of the underlying biology and a lack of reliable biomarkers. Previous studies have shown that aberrantly expressed MicroRNAs (miRNAs) are involved in carcinogenesis and tumor progression by post-transcriptionally regulating gene expression. However, the interference of miRNAs in tumorigenesis is quite complicated and far from being fully understood. In this work, by an integrative analysis of mRNA expression, miRNA expression and clinical data published by The Cancer Genome Atlas (TCGA), we studied the modularity and dynamicity of miRNA-mRNA interactions and the prognostic implications in high-grade serous ovarian carcinomas. With the top transcriptional correlations (Bonferroni-adjusted p-value<0.01) as inputs, we identified five miRNA-mRNA module pairs (MPs), each of which included one positive-connection (correlation) module and one negative-connection (correlation) module. The number of miRNAs or mRNAs in each module varied from 3 to 7 or from 2 to 873. Among the four major negative-connection modules, three fit well with the widely accepted miRNA-mediated post-transcriptional regulation theory. These modules were enriched with the genes relevant to cell cycle and immune response. Moreover, we proposed two novel algorithms to reveal the group or sample specific dynamic regulations between these two RNA classes. The obtained miRNA-mRNA dynamic network contains 3350 interactions captured across different cancer progression stages or tumor grades. We found that those dynamic interactions tended to concentrate on a few miRNAs (e.g. miRNA-936), and were more likely present on the miRNA-mRNA pairs outside the discovered modules. In addition, we also pinpointed a robust prognostic signature consisting of 56 modular protein-coding genes, whose co-expression patterns were predictive for the survival time of ovarian cancer patients in multiple independent cohorts.

Identification of miRNA-mRNA regulatory modules by exploring collective group relationships

Background

microRNAs (miRNAs) play an essential role in the post-transcriptional gene regulation in plants and animals. They regulate a wide range of biological processes by targeting messenger RNAs (mRNAs). Evidence suggests that miRNAs and mRNAs interact collectively in gene regulatory networks. The collective relationships between groups of miRNAs and groups of mRNAs may be more readily interpreted than those between individual miRNAs and mRNAs, and thus are useful for gaining insight into gene regulation and cell functions. Several computational approaches have been developed to discover miRNA-mRNA regulatory modules (MMRMs) with a common aim to elucidate miRNA-mRNA regulatory relationships. However, most existing methods do not consider the collective relationships between a group of miRNAs and the group of targeted mRNAs in the process of discovering MMRMs. Our aim is to develop a framework to discover MMRMs and reveal miRNA-mRNA regulatory relationships from the heterogeneous expression data based on the collective relationships.

Results

We propose DIscovering COllective group RElationships (DICORE), an effective computational framework for revealing miRNA-mRNA regulatory relationships. We utilize the notation of collective group relationships to build the computational framework. The method computes the collaboration scores of the miRNAs and mRNAs on the basis of their interactions with mRNAs and miRNAs, respectively. Then it determines the groups of miRNAs and groups of mRNAs separately based on their respective collaboration scores. Next, it calculates the strength of the collective relationship between each pair of miRNA group and mRNA group using canonical correlation analysis, and the group pairs with significant canonical correlations are considered as the MMRMs. We applied this method to three gene expression datasets, and validated the computational discoveries.

Conclusions

Analysis of the results demonstrates that a large portion of the regulatory relationships discovered by DICORE is consistent with the experimentally confirmed databases. Furthermore, it is observed that the top mRNAs that are regulated by the miRNAs in the identified MMRMs are highly relevant to the biological conditions of the given datasets. It is also shown that the MMRMs identified by DICORE are more biologically significant and functionally enriched.

Electronic supplementary material

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MicroRNA expression profiles and networks in mouse lung infected with H1N1 influenza virus

Influenza A viruses can cause localized outbreaks and worldwide pandemics, owing to their high transmissibility and wide host range. As such, they are among the major diseases that cause human death. However, the molecular changes induced by influenza A virus infection in lung tissue are not entirely clear. Changes in microRNA (miRNA) expression occur in many pathological and physiological processes, and influenza A virus infection has been shown to alter miRNA expression in cultured cells and animal models. In this study, we mined key miRNAs closely related to influenza A virus infection and explored cellular regulatory mechanisms against influenza A virus infection, by building networks among miRNAs and genes, gene ontologies (GOs), and pathways. In this study, miRNAs and mRNAs induced by H1N1 influenza virus infection were measured by gene chips, and we found that 82 miRNAs and 3371 mRNAs were differentially expressed. The 82 miRNAs were further analyzed with the series test of cluster (STC) analysis. Three of the 16 cluster profiles identified by STC, which include 46 miRNAs in the three profiles, changed significantly. Using potential target genes of the 46 miRNAs, we looked for intersections of these genes with 3371 differentially expressed mRNAs; 719 intersection genes were identified. Based on the GO or KEGG databases, we attained GOs or pathways for all of the above intersection genes. Fisher's and χ (2) test were used to calculate p value and false discovery rate (FDR), and according to the standard of p < 0.001, 241 GOs and 76 pathways were filtered. Based on these data, miRNA-gene, miRNA-GO, and miRNA-pathway networks were built. We then extracted three classes of GOs (related to inflammatory and immune response, cell cycle, proliferation and apoptosis, and signal transduction) to build three subgraphs, and pathways strictly related with H1N1 influenza virus infection were filtered to extract a subgraph of the miRNA-pathway network. Last, according to the pathway analysis and miRNA-pathway network analysis, 17 miRNAs were found to be associated with the "influenza A" pathway. This study provides the most complete miRNAome profiles, and the most detailed miRNA regulatory networks to date, and is the first to report the most important 17 miRNAs closely related with the pathway of influenza A. These results are a prelude to advancements in mouse H1N1 influenza virus infection biology and the use of mice as a model for human H1N1 influenza virus infection studies.

PGC-Enriched miRNAs Control Germ Cell Development

Non-coding microRNAs (miRNAs) regulate the translation of target messenger RNAs (mRNAs) involved in the growth and development of a variety of cells, including primordial germ cells (PGCs) which play an essential role in germ cell development. However, the target mRNAs and the regulatory networks influenced by miRNAs in PGCs remain unclear. Here, we demonstrate a novel miRNAs control PGC development through targeting mRNAs involved in various cellular pathways. We reveal the PGC-enriched expression patterns of nine miRNAs, including miR-10b, -18a, -93, -106b, -126-3p, -127, -181a, -181b, and -301, using miRNA expression analysis along with mRNA microarray analysis in PGCs, embryonic gonads, and postnatal testes. These miRNAs are highly expressed in PGCs, as demonstrated by Northern blotting, miRNA in situ hybridization assay, and miRNA qPCR analysis. This integrative study utilizing mRNA microarray analysis and miRNA target prediction demonstrates the regulatory networks through which these miRNAs regulate their potential target genes during PGC development. The elucidated networks of miRNAs disclose a coordinated molecular mechanism by which these miRNAs regulate distinct cellular pathways in PGCs that determine germ cell development.