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

MOTIVATION: MicroRNAs (miRNAs) and mRNAs constitute an important part of gene regulatory networks, influencing diverse biological phenomena. Elucidating closely related miRNAs and mRNAs can be an essential first step towards the discovery of their combinatorial effects on different cellular states. Here, we propose a probabilistic learning method to identify synergistic miRNAs involving regulation of their condition-specific target genes (mRNAs) from multiple information sources, i.e. computationally predicted target genes of miRNAs and their respective expression profiles. RESULTS: We used data sets consisting of miRNA-target gene binding information and expression profiles of miRNAs and mRNAs on human cancer samples. Our method allowed us to detect functionally correlated miRNA-mRNA modules involved in specific biological processes from multiple data sources by using a balanced fitness function and efficient searching over multiple populations. The proposed algorithm found two miRNA-mRNA modules, highly correlated with respect to their expression and biological function. Moreover, the mRNAs included in the same module showed much higher correlations when the related miRNAs were highly expressed, demonstrating our method's ability for finding coherent miRNA-mRNA modules. Most members of these modules have been reported to be closely related with cancer. Consequently, our method can provide a primary source of miRNA and target sets presumed to constitute closely related parts of gene regulatory pathways.     

Genome-wide analysis of aberrantly expressed circulating miRNAs in patients with coal workers’ pneumoconiosis

Emerging evidence indicates that microRNAs (miRNAs), a class of small non-coding regulatory RNAs, have important roles in multiple biological processes. To determine the potential contribution of miRNAs to coal workers’ pneumoconiosis (CWP), we comprehensively surveyed and identified differentially expressed miRNA profiles in patients with CWP by small RNA sequencing and analysis. Mixed serum samples from the different stages of CWP and the control samples were subjected to deep sequencing by applying next-generation sequencing technology. Samples at different disease stages exhibited inconsistent miRNA expression profiles and differentially expressed miRNA profiles. Generally, these miRNAs were dynamically expressed across the different disease stages and showed various relative expression levels. Some miRNAs (such as miR-18a*, 149, 222 and 671-3p) were consistently up-regulated or down-regulated in the different stages of CWP samples. Most of the aberrantly expressed miRNAs showed a down-regulation trend. Differentially expressed miRNAs were also subjected to pairwise comparison between the different stages. Some miRNAs showed significant inconsistent expression trends across the three stages, although they were not significantly dysregulated based on the control sample. Furthermore, a series of special miRNAs organized into miRNA gene clusters and gene families were also surveyed for aberrant expression (such as mir-200 gene family and mir-222 gene cluster). According to experimentally validated target mRNAs of the aberrantly and abundantly expressed miRNAs, functional enrichment analysis suggests that these miRNAs play important roles in various biological processes, including lung tumorigenesis. In summary, we demonstrated that aberrantly expressed circulating miRNAs showed dynamic expression patterns across diseased samples, which suggests that these miRNAs may have critical roles in the occurrence and development of CWP. In addition, some significantly dysregulated miRNAs may be potential non-invasive diagnosis biomarkers based on further study.     

Genome-wide screen for aberrantly expressed miRNAs reveals miRNA profile signature in breast cancer

Dysregulation in the expression of miRNAs contributes to the occurrence and development of many human cancers. We herein attempted to obtain the potential association between miRNA expression profile and breast cancer by applying high-throughput sequencing technology. Small RNAs from seven paired tumor and adjacent normal tissue samples were sequenced. To determine the miRNA expression profiles in tissues and sera, another five equally pooled serum samples from 20 patients and 30 normal women were sequenced. Despite a similar number in abundantly expressed miRNAs across samples, we detected varying miRNA expression profiles. Some miRNAs showed inconsistent or opposite dysregulation trends across different tumor tissues, including some abundantly expressed miRNA gene clusters and gene families. Wilcoxon sign-rank test for paired samples analysis revealed that abnormal miRNAs showed a higher level of variation across the seven tumor samples. We also completely surveyed abnormal miRNAs expressed in tumor and serum tissues in the mixed datasets based on the relative expression levels. Most of these miRNAs were significantly down-regulated in tumor samples, but nine abnormal miRNAs (miR-18a, 19a, 20a, 30a, 103b, 126, 126*, 192, 1287) were consistently expressed in tumor tissues and serum samples. Based on experimentally validated target mRNAs, functional enrichment analysis indicated that these abnormal miRNAs and miRNA groups (miRNA gene clusters and gene families) have important roles in multiple biological processes. Dynamic miRNA expression profiles, various abnormal miRNA profiles and complexity of the miRNA regulatory network reveal that the miRNA expression profile is a potential biomarker for classifying or detecting human disease.     

Retracted: Deep integrative analysis of microRNA-mRNA regulatory networks for biomarker and target discovery in chondrosarcoma

Chondrosarcoma (CHS) is a common malignant bone sarcoma and its occurrence increases with age. microRNAs (miRNAs) are a class of noncoding RNAs that participate in various biological processes and disease pathogenesis by targeting functional messenger RNA (mRNA). However, the modulation of miRNAs in CHS remains largely unknown. In this study, we performed integrative analysis to explore the expression profiles of miRNAs and mRNAs, together with their interaction networks in human CHS tissues and cell lines by RNA-seq (miRNA and mRNA). A total of 133 and 796 differentially expressed miRNAs and mRNAs were identified (|Fold change| ≥ 2 and P-value ≤ 0.5). miRNA-mRNA regulatory interactions between 55 miRNAs and 242 mRNAs were screened by the Pearson correlation analysis and target prediction. mRNAs in the network were enriched to 145 Gene Ontology terms and 35 Kyoto Encyclopedia of Genes and Genomes pathways. Specifically, some key regulators (hub-miRNAs) in the network (miR-622, miR-4539, miR-145, miR-25, and miR-96) were suggested to play important regulatory roles in the pathogenesis of CHS. In addition, functional experiments validated that miR-622 regulated CHS cell proliferation by targeting bone morphogenetic protein 1 (BMP1).     

microRNA调控网络与肿瘤

microRNA(miRNA)是一类长度约为22nt的小分子非编码RNA,对基因表达进行转录后调控。基因调控网络由各种回路,如前馈和反馈回路组成。它通过将外界刺激整合成合适的输出信号,控制细胞从增殖到死亡几乎所有的生命活动。已知基因调控网络的失调与肿瘤的发生发展密切相关。新近的实验证据表明,miRNA广泛参与基因调控网络中的反馈和前馈回路。该文主要介绍miRNA在基因表达调控网络中的作用及其与肿瘤发生发展的关系。     

An integrated analysis of miRNA and mRNA expressions in non-small cell lung cancers

Using DNA microarrays, we generated both mRNA and miRNA expression data from 6 non-small cell lung cancer (NSCLC) tissues and their matching normal control from adjacent tissues to identify potential miRNA markers for diagnostics. We demonstrated that hsa-miR-96 is significantly and consistently up-regulated in all 6 NSCLCs. We validated this result in an independent set of 35 paired tumors and their adjacent normal tissues, as well as their sera that are collected before surgical resection or chemotherapy, and the results suggested that hsa-miR-96 may play an important role in NSCLC development and has great potential to be used as a noninvasive marker for diagnosing NSCLC. We predicted potential miRNA target mRNAs based on different methods (TargetScan and miRanda). Further classification of miRNA regulated genes based on their relationship with miRNAs revealed that hsa-miR-96 and certain other miRNAs tend to down-regulate their target mRNAs in NSCLC development, which have expression levels permissive to direct interaction between miRNAs and their target mRNAs. In addition, we identified a significant correlation of miRNA regulation with genes coincide with high density of CpG islands, which suggests that miRNA may represent a primary regulatory mechanism governing basic cellular functions and cell differentiations, and such mechanism may be complementary to DNA methylation in repressing or activating gene expression.     

Detecting microRNAs of high influence on protein functional interaction networks: a prostate cancer case study

ABSTRACT: BACKGROUND: The use of biological molecular network information for diagnostic and prognostic purposes and elucidation of molecular disease mechanism is a key objective in systems biomedicine. The network of regulatory miRNA-target and functional protein interactions is a rich source of information to elucidate the function and the prognostic value of miRNAs in cancer. The objective of this study is to identify miRNAs that have high influence on target protein complexes in prostate cancer as a case study. This could provide biomarkers or therapeutic targets relevant for prostate cancer treatment. RESULTS: Our findings demonstrate that a miRNA's functional role can be explained by its target protein connectivity within a physical and functional interaction network. To detect miRNAs with high influence on target protein modules, we integrated miRNA and mRNA expression profiles with a sequence based miRNA-target network and human functional and physical protein interactions (FPI). miRNAs with high influence on target protein complexes play a role in prostate cancer progression and are promising diagnostic or prognostic biomarkers. We uncovered several miRNA-regulated protein modules which were enriched in focal adhesion and prostate cancer genes. Several miRNAs such as miR-96, miR-182, and miR-143 demonstrated high influence on their target protein complexes and could explain most of the gene expression changes in our analyzed prostate cancer data set. CONCLUSIONS: We describe a novel method to identify active miRNA-target modules relevant to prostate cancer progression and outcome. miRNAs with high influence on protein networks are valuable biomarkers that can be used in clinical investigations for prostate cancer treatment.