BACKGROUND:Numerous studies have demonstrated the existence of stable regulatory RNAs, microRNAs (miRNAs), in the circulation and have shown that the spectrum of these extracellular miRNAs is affected by various pathologic conditions including cancers.CONTENT: Circulating miRNAs have been the focus of numerous cancer biomarker discovery efforts over the past few years; however, a considerable number of these studies have yielded inconsistent and irreproducible findings. Here, we have summarized and compared the results of studies covering 8 different cancer types to address key questions, including the possibility of using circulating miRNA to detect cancers and what factors may affect miRNA signatures. Although identifying circulating miRNA signatures to detect specific types of early stage cancers can be challenging, study results suggest that it may be possible to use miRNAs to detect cancers in general.

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MicroRNAs (miRNAs) are small noncoding RNAs that modulate the cellular transcriptome at the post-transcriptional level. miRNA plays important roles in different disease manifestation, including type 2 diabetes mellitus (T2DM). Many studies have characterized the changes of miRNAs in T2DM, a complex systematic disease; however, few studies have integrated these findings and explored the functional effects of the dysregulated miRNAs identified. To investigate the involvement of miRNAs in T2DM, we obtained and analyzed all relevant studies published prior to 18 October 2016 from various literature databases. From 59 independent studies that met the inclusion criteria, we identified 158 dysregulated miRNAs in seven different major sample types. To understand the functional impact of these deregulated miRNAs, we performed targets prediction and pathway enrichment analysis. Results from our analysis suggested that the altered miRNAs are involved in the core processes associated with T2DM, such as carbohydrate and lipid metabolisms, insulin signaling pathway and the adipocytokine signaling pathway. This systematic survey of dysregulated miRNAs provides molecular insights on the effect of deregulated miRNAs in different tissues during the development of diabetes. Some of these miRNAs and their mRNA targets may have diagnostic and/or therapeutic utilities in T2DM.

Although many tools have been developed to analyze small RNA sequencing (sRNA-Seq) data, it remains challenging to accurately analyze the small RNA population, mainly due to multiple sequence ID assignment caused by short read length. Additional issues in small RNA analysis include low consistency of microRNA (miRNA) measurement results across different platforms, miRNA mapping associated with miRNA sequence variation (isomiR) and RNA editing, and the origin of those unmapped reads after screening against all endogenous reference sequence databases. To address these issues, we built a comprehensive and customizable sRNA-Seq data analysis pipeline—sRNAnalyzer, which enables: (i) comprehensive miRNA profiling strategies to better handle isomiRs and summarization based on each nucleotide position to detect potential SNPs in miRNAs, (ii) different sequence mapping result assignment approaches to simulate results from microarray/qRT-PCR platforms and a local probabilistic model to assign mapping results to the most-likely IDs, (iii) comprehensive ribosomal RNA filtering for accurate mapping of exogenous RNAs and summarization based on taxonomy annotation. We evaluated our pipeline on both artificial samples (including synthetic miRNA and Escherichia coli cultures) and biological samples (human tissue and plasma). sRNAnalyzer is implemented in Perl and available at: http://srnanalyzer.systemsbiology.net/.

BackgroundA comprehensive network-based understanding of molecular pathways abnormally altered in glioblastoma multiforme (GBM) is essential for developing effective therapeutic approaches for this deadly disease.Methodology/Principal FindingsApplying a next generation sequencing technology, massively parallel signature sequencing (MPSS), we identified a total of 4535 genes that are differentially expressed between normal brain and GBM tissue. The expression changes of three up-regulated genes, CHI3L1, CHI3L2, and FOXM1, and two down-regulated genes, neurogranin and L1CAM, were confirmed by quantitative PCR. Pathway analysis revealed that TGF- β pathway related genes were significantly up-regulated in GBM tumor samples. An integrative pathway analysis of the TGF β signaling network identified two alternative TGF−β signaling pathways mediated by SOX4 (sex determining region Y-box 4) and TGFBI (Transforming growth factor beta induced). Quantitative RT-PCR and immunohistochemistry staining demonstrated that SOX4 and TGFBI expression is elevated in GBM tissues compared with normal brain tissues at both the RNA and protein levels. In vitro functional studies confirmed that TGFBI and SOX4 expression is increased by TGF- β stimulation and decreased by a specific inhibitor of TGF- β receptor 1 kinase.Conclusions/SignificanceOur MPSS database for GBM and normal brain tissues provides a useful resource for the scientific community. The identification of non-SMAD mediated TGF−β signaling pathways acting through SOX4 and TGFBI (GENE ID:7045) in GBM indicates that these alternative pathways should be considered, in addition to the canonical SMAD mediated pathway, in the development of new therapeutic strategies targeting TGF−β signaling in GBM. Finally, the construction of an extended TGF- β signaling network with overlaid gene expression changes between GBM and normal brain extends our understanding of the biology of GBM.

Preterm birth (PTB) can lead to lifelong complications and challenges. Identifying and monitoring molecular signals in easily accessible biological samples that can diagnose or predict the risk of preterm labour (PTL) in pregnant women will reduce or prevent PTBs. A number of studies identified putative biomarkers for PTL including protein, miRNA and hormones from various body fluids. However, biomarkers identified from these studies usually lack consistency and reproducibility. Extracellular vesicles (EVs) in circulation have gained significant interest in recent years as these vesicles may be involved in cell‐cell communication. We have used an improved small RNA library construction protocol and a newly developed size exclusion chromatography (SEC)‐based EV purification method to gain a comprehensive view of circulating RNA in plasma and its distribution by analysing RNAs in whole plasma and EV‐associated and EV‐depleted plasma. We identified a number of miRNAs in EVs that can be used as biomarkers for PTL, and these miRNAs may reflect the pathological changes of the placenta during the development of PTL. To our knowledge, this is the first study to report a comprehensive picture of circulating RNA, including RNA in whole plasma, EV and EV‐depleted plasma, in PTL and reveal the usefulness of EV‐associated RNAs in disease diagnosis.

MicroRNAs (miRNAs) are short regulatory RNAs that modulate the transcriptome and proteome at the post-transcriptional level. To obtain a better understanding on the role of miRNAs in the progression of cervical cancer, meta-analysis and gene set enrichment analysis were used to analyze published cervical cancer miRNA studies. From 85 published reports, which include 3,922 cases and 2,099 noncancerous control tissue samples, 63 differentially expressed miRNAs (DEmiRNAs) were identified in different stages of cervical cancer development (CIN 1-3 and CC). It was found that some of the dysregulated miRNAs were associated with specific stages of cervical cancer development. To illustrate the impact of miRNAs on the pathogenesis of cervical cancer, a miRNA-mRNA interaction network on selected pathways was built by integrating viral oncoproteins, dysregulated miRNAs and their predicted/validated targets. The results indicated that the deregulated miRNAs at the different stages of cervical cancer were functionally involved in several key cancer related pathways, such as cell cycle, p53 and Wnt signaling pathways. These dysregulated miRNAs could play an important role in cervical cancer development. Some of the stage-specific miRNAs can also be used as biomarkers for cancer classification and monitoring the progression of cancer development.Cervical cancer is the second leading cause of female cancer deaths worldwide, with an estimated annual global incidence of more than half a million new cases and about 270,000 deaths. 1,2 Most cervical cancers are caused by infection with high risk (HR) human papilloma virus (HPV), which disrupts the normal proliferation and differentiation of cervical squamous epithelium cells via two viral-encoded oncoproteins: E6 and E7. The E6/E7 protein tumorgenesis is mediated through the interaction with cellular tumor suppressor proteins, TP53 and RB1 (Retinoblastoma 1), respectively. 3 Besides the misregulated host proteins, E6 and E7 oncoproteins also interact with host noncoding transcripts such as microRNAs (miRNAs). [4][5][6] MiRNAs are short (19-25 nucleotides in length) regulatory RNAs that modulate gene expression level by partial base pairing with the 3' untranslated region of their target messenger RNAs (mRNAs). 7 There are currently over 2,500 human miRNAs recorded in miRBase (www.mirbase.org), and it has been estimated that roughly two third of human transcripts are regulated by miRNAs. 8 One of the most important features of miRNAs is the partial nucleotide sequence paring between the miRNA and its mRNA target, which results in promiscuous interactions: one miRNA often interacts with more than one mRNAs, and one transcript can be targeted by multiple miRNAs. 9 The first cervical cancer

The web-based software is available at: http://sbm.postech.ac.kr/pna.