Inferring the perturbed microRNA regulatory networks from gene expression data using a network propagation based method

Network-based drug repurposing for HPV-associated cervical cancer

In women, cervical cancer (CC) is the fourth most common cancer around the world with average cases of 604,000 and 342,000 deaths per year. Approximately 50% of high-grade CC are attributed to human papillomavirus (HPV) types 16 and 18. Chances of CC in HPV-positive patients are 6 times more than HPV-negative patients which demands timely and effective treatment. Repurposing of drugs is considered a viable approach to drug discovery which makes use of existing drugs, thus potentially reducing the time and costs associated with de-novo drug discovery. In this study, we present an integrative drug repurposing framework based on a systems biology-enabled network medicine platform. First, we built an HPV-induced CC protein interaction network named HPV2C following the CC signatures defined by the omics dataset, obtained from GEO database. Second, the drug target interaction (DTI) data obtained from DrugBank, and related databases was used to model the DTI network followed by drug target network proximity analysis of HPV-host associated key targets and DTIs in the human protein interactome. This analysis identified 142 potential anti-HPV repurposable drugs to target HPV induced CC pathways. Third, as per the literature survey 51 of the predicted drugs are already used for CC and 33 of the remaining drugs have anti-viral activity. Gene set enrichment analysis of potential drugs in drug-gene signatures and in HPV-induced CC-specific transcriptomic data in human cell lines additionally validated the predictions. Finally, 13 drug combinations were found using a network based on overlapping exposure. To summarize, the study provides effective network-based technique to quickly identify suitable repurposable drugs and drug combinations that target HPV-associated CC.

Next Generation Sequencing for Potential Regulated Genes and Micro-RNAs of Early Growth Response-1 in the Esophageal Squamous Cell Carcinoma

Esophageal cancer has a poor prognosis due to its aggressiveness and low survival rate. In Ease Asia, esophageal squamous cell carcinoma (ESCC) outnumbers esophageal adenocarcinoma (EAC). The ESCC patients still have high mortality despite modern surgical resection and neoadjuvant treatment. Determining patient and outcome prognostic factors is critical in ESCC treatment. In esophageal cancer, early growth response-1 (Egr-1) is a tumor suppressor gene, but the mechanism and associated genes are unknown. The study utilizes RNA interference method, the platform of Next Generation Sequencing (NGS) and bioinformatics analysis to investigate the influences after the Egr-1 gene slicing on the ESCC cells. The heat maps of differentially expressed mRNA and microRNAs were analyzed using the algorithm, Burrows-Wheller Aligner. The study showed that the expression of 51 mRNA and 26 microRNAs have significant changes in ESCC cells after Egr-1 knockdown. The KEGG enrichment analysis linked Egr-1-regulated genes and microRNAs. Egr-1 interactions with these genes and microRNAs may be important in tumor progression. In conclusions, this study provided the transcriptome patterns and relating pathway analysis for Egr-1 knockdown in ESCC cells. The mRNA and microRNAs altered by Egr-1 gene silencing might provide key information in the treatment of ESCC.

Clinical significance of miRNAs in autoimmunity

MicroRNAs (miRNAs) are evolutionally conserved, single-stranded RNAs that regulate gene expression at the posttranscriptional level by disrupting translation. MiRNAs are key players in variety of biological processes that regulate the differentiation, development and activation of immune cells in both innate and adaptive immunity. The disruption and dysfunction of miRNAs can perturb the immune response, stimulate the release of inflammatory cytokines and initiate the production of autoantibodies, and contribute to the pathogenesis of autoimmune diseases, including systemic lupus erythmatosus (SLE), rheumatoid arthritis (RA), primary biliary cholangitis (PBC), and multiple sclerosis (MS). Accumulating studies demonstrate that miRNAs, which can be collected by noninvasive methods, have the potential to be developed as diagnostic and therapeutic biomarkers, the discovery and validation of which is essential for the improvement of disease diagnosis and clinical monitoring. Recently, with the development of detection tools, such as microarrays and NGS (Next Generation Sequencing), large amounts of miRNAs have been identified and suggest a critical role in the pathogenesis of autoimmune diseases. Several miRNAs associated diagnostic biomarkers have been developed and applied clinically, though the pharmaceutical industry is still facing challenges in commercialization and drug delivery. The development of miRNAs is less advanced for autoimmune diseases compared with cancer. However, drugs that target miRNAs have been introduced as candidates and adopted in clinical trials. This review comprehensively summarizes the differentially expressed miRNAs in several types of autoimmune diseases and discusses the role and the significance of miRNAs in clinical management. The study of miRNAs in autoimmunity promises to provide novel and broad diagnostic and therapeutic strategies for a clinical market that is still in its infancy.

Comprehensive analysis of miRNA-gene regulatory network with clinical significance in human cancers

microRNAs (miRNAs), particularly the exosomal miRNAs have been widely used as biomarkers and promising therapeutic targets in cancer. However, a comprehensive analysis of miRNA-gene regulatory network with clinical significance remains scarce. The emergence of high-throughput multi-omics data over large, well-characterized patient cohorts provides an unprecedented opportunity to address this problem. Herein, we performed a clinic-centered analysis to identify cancer-associated miRNAs, miRNA-target axis. We first calculated the correlation among miRNA, mRNA and 75 unique clinico-pathological characteristics (CPCs) in 26 cancer types, and established an online resource (4CR). Interestingly, we found that the high expression of several DNA methylation-related enzymes was associated with adverse outcomes of cancer patients, and these genes were regulated by a cluster of miRNAs. Furthermore, by integrating exosomal miRNA and mRNA databases, we identified exosomal miRNA biomarkers for non-invasive cancer surveillance and therapy monitoring. Finally, we explored the role of CPC-related miRNAs for therapeutic effect prediction of drugs based on their shared targets. Our analysis pipeline illustrated the significance of clinic-centered analysis in miRNA-gene pair identification and provided helpful clues for future cancer studies.

Integrative microRNA and mRNA deep-sequencing expression profiling in endemic Burkitt lymphoma

BACKGROUND

Burkitt lymphoma (BL) is characterized by overexpression of the c-myc oncogene, which in the vast majority of cases is a consequence of an IGH/MYC translocation. While myc is the seminal event, BL is a complex amalgam of genetic and epigenetic changes causing dysregulation of both coding and non-coding transcripts. Emerging evidence suggest that abnormal modulation of mRNA transcription via miRNAs might be a significant factor in lymphomagenesis. However, the alterations in these miRNAs and their correlations to their putative mRNA targets have not been extensively studied relative to normal germinal center (GC) B cells.

METHODS

Using more sensitive and specific transcriptome deep sequencing, we compared previously published small miRNA and long mRNA of a set of GC B cells and eBL tumors. MiRWalk2.0 was used to identify the validated target genes for the deregulated miRNAs, which would be important for understanding the regulatory networks associated with eBL development.

RESULTS

We found 211 differentially expressed (DE) genes (79 upregulated and 132 downregulated) and 49 DE miRNAs (22 up-regulated and 27 down-regulated). Gene Set enrichment analysis identified the enrichment of a set of MYC regulated genes. Network propagation-based method and correlated miRNA-mRNA expression analysis identified dysregulated miRNAs, including miR-17~95 cluster members and their target genes, which have diverse oncogenic properties to be critical to eBL lymphomagenesis. Central to all these findings, we observed the downregulation of ATM and NLK genes, which represent important regulators in response to DNA damage in eBL tumor cells. These tumor suppressors were targeted by multiple upregulated miRNAs (miR-19b-3p, miR-26a-5p, miR-30b-5p, miR-92a-5p and miR-27b-3p) which could account for their aberrant expression in eBL.

CONCLUSION

Combined loss of p53 induction and function due to miRNA-mediated regulation of ATM and NLK, together with the upregulation of TFAP4, may be a central role for human miRNAs in eBL oncogenesis. This facilitates survival of eBL tumor cells with the IGH/MYC chromosomal translocation and promotes MYC-induced cell cycle progression, initiating eBL lymphomagenesis. This characterization of miRNA-mRNA interactions in eBL relative to GC B cells provides new insights on miRNA-mediated transcript regulation in eBL, which are potentially useful for new improved therapeutic strategies.

MiR-218 targets MeCP2 and inhibits heroin seeking behavior

MicroRNAs (miRNAs) are a class of evolutionarily conserved, 18-25 nucleotide non-coding sequences that post-transcriptionally regulate gene expression. Recent studies implicated their roles in the regulation of neuronal functions, such as learning, cognition and memory formation. Here we report that miR-218 inhibits heroin-induced behavioral plasticity. First, network propagation-based method was used to predict candidate miRNAs that played potential key roles in regulating drug addiction-related genes. Microarray screening was also carried out to identify miRNAs responding to chronic heroin administration in the nucleus accumbens (NAc). Among the collapsed miRNAs, top-ranked miR-218 was decreased after chronic exposure to heroin. Lentiviral overexpression of miR-218 in NAc could inhibit heroin-induced reinforcement in both conditioned place preference (CPP) test and heroin self-administration experiments. Luciferase activity assay indicated that miR-218 could regulate 3' untranslated regions (3' UTR) of multiple neuroplasticity-related genes and directly target methyl CpG binding protein 2 (Mecp2). Consistently, Mecp2^308/y mice exhibited reduced heroin seeking behavior in CPP test. These data reveal a functional role of miR-218 and its target, MeCP2, in the regulation of heroin-induced behavioral plasticity.

Naïve Bayes classifier predicts functional microRNA target interactions in colorectal cancer

Alterations in the expression of miRNAs have been extensively characterized in several cancers, including human colorectal cancer (CRC). Recent publications provide evidence for tissue-specific miRNA target recognition. Several computational methods have been developed to predict miRNA targets; however, all of these methods assume a general pattern underlying these interactions and therefore tolerate reduced prediction accuracy and a significant number of false predictions. The motivation underlying the presented work was to unravel the relationship between miRNAs and their target mRNAs in CRC. We developed a novel computational algorithm for miRNA-target prediction in CRC using a Naïve Bayes classifier. The algorithm, which is referred to as CRCmiRTar, was trained with data from validated miRNA target interactions in CRC and other cancer entities. Furthermore, we identified a set of position-based, sequence, structural, and thermodynamic features that identify CRC-specific miRNA target interactions. Evaluation of the algorithm showed a significant improvement of performance with respect to AUC, and sensitivity, compared to other widely used algorithms based on machine learning. Based on miRNA and gene expression profiles in CRC tissues with similar clinical and pathological features, our classifier predicted 204 functional interactions, which involve 11 miRNAs and 41 mRNAs in this cancer entity. While the approach is here validated for CRC, the implementation of disease-specific miRNA target prediction algorithms can be easily adopted for other applications too. The identification of disease-specific miRNA target interactions may also facilitate the identification of potential drug targets.

miRMOD: a tool for identification and analysis of 5' and 3' miRNA modifications in Next Generation Sequencing small RNA data

In the past decade, the microRNAs (miRNAs) have emerged to be important regulators of gene expression across various species. Several studies have confirmed different types of post-transcriptional modifications at terminal ends of miRNAs. The reports indicate that miRNA modifications are conserved and functionally significant as it may affect miRNA stability and ability to bind mRNA targets, hence affecting target gene repression. Next Generation Sequencing (NGS) of the small RNA (sRNA) provides an efficient and reliable method to explore miRNA modifications. The need for dedicated software, especially for users with little knowledge of computers, to determine and analyze miRNA modifications in sRNA NGS data, motivated us to develop miRMOD. miRMOD is a user-friendly, Microsoft Windows and Graphical User Interface (GUI) based tool for identification and analysis of 5′ and 3′ miRNA modifications (non-templated nucleotide additions and trimming) in sRNA NGS data. In addition to identification of miRNA modifications, the tool also predicts and compares the targets of query and modified miRNAs. In order to compare binding affinities for the same target, miRMOD utilizes minimum free energies of the miRNA:target and modified-miRNA:target interactions. Comparisons of the binding energies may guide experimental exploration of miRNA post-transcriptional modifications. The tool is available as a stand-alone package to overcome large data transfer problems commonly faced in web-based high-throughput (HT) sequencing data analysis tools. miRMOD package is freely available at http://bioinfo.icgeb.res.in/miRMOD.