Cell migration, which involves acto-myosin dynamics, cell adhesion, membrane trafficking and signal transduction, is a prerequisite for cancer cell metastasis. Here, we report that an actin-dependent molecular motor, unconventional myosin Va, is involved in this process and implicated in cancer metastasis. The mRNA expression of myosin Va is increased in a number of highly metastatic cancer cell lines and metastatic colorectal cancer tissues. Suppressing the expression of myosin Va by lentivirus-based RNA interference in highly metastatic cancer cells impeded their migration and metastasis capabilities both in vitro and in vivo. In addition, the levels of myosin Va in cancer cell lines are positively correlated with the expression of Snail, a transcriptional repressor that triggers epithelial-mesenchymal transition. Repression or overexpression of Snail in cancer cells caused reduced or elevated levels of myosin Va, respectively. Furthermore, Snail can bind to an E-box of the myosin Va promoter and induce its activity, which indicates that Snail might act as a transcriptional activator. These data demonstrate an essential role of myosin Va in cancer cell migration and metastasis, and suggest a novel target for Snail in its regulation of cancer progression.Cancer cell metastasis is a multistep, complex process including migration of detached cells from the primary tumor through the surrounding stroma, invasion of the cells into the circulatory system, extravasation and arresting at distant secondary sites. Many of these steps require cell motility, which is presumably driven by cycles of actin polymerization, cell adhesion and acto-myosin contraction.

Tumour-initiating cells (TICs) are advocated to constitute the sustaining force to maintain and renew fully established malignancy; however, the molecular mechanisms responsible for these properties are elusive. We previously demonstrated that voltage-gated calcium channel a2d1 subunit marks hepatocellular carcinoma (HCC) TICs. Here we confirm directly that a2d1 is a HCC TIC surface marker, and identify let-7c, miR-200b, miR-222 and miR-424 as suppressors of a2d1 þ HCC TICs. Interestingly, all the four miRNAs synergistically target PBX3, which is sufficient and necessary for the acquisition and maintenance of TIC properties. Moreover, PBX3 drives an essential transcriptional programme, activating the expression of genes critical for HCC TIC stemness including CACNA2D1, EpCAM, SOX2 and NOTCH3. In addition, the expression of CACNA2D1 and PBX3 mRNA is predictive of poor prognosis for HCC patients. Collectively, our study identifies an essential signalling pathway that controls the switch of HCC TIC phenotypes.

This review aimed to summarize the current research contents about long noncoding RNAs (lncRNAs) and some related lncRNAs as molecular biomarkers or therapy strategies in human cancer and cardiovascular diseases. Following the development of various kinds of sequencing technologies, lncRNAs have become one of the most unknown areas that need to be explored. First, the definition and classification of lncRNAs were constantly amended and supplemented because of their complexity and diversity. Second, several methods and strategies have been developed to study the characteristic of lncRNAs, including new species identifications, subcellular localization, gain or loss of function, molecular interaction, and bioinformatics analysis. Third, based on the present results from basic researches, the working mechanisms of lncRNAs were proved to be different forms of interactions involving DNAs, RNAs, and proteins. Fourth, lncRNA can play different important roles during the embryogenesis and organ differentiations. Finally, because of the tissue-specific expression of lncRNAs, they could be used as biomarkers or therapy targets and effectively applied in different kinds of diseases, such as human cancer and cardiovascular diseases.

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Background: Circulating microRNA (miRNA) biomarkers have been extensively reported in cardiovascular diseases (CVDs). However, serum exosomal miRNA (exo-miRNA) as biomarker in patients with heart failure (HF) with reduced ejection fraction (HFrEF) remain largely unexplored. We sought to investigate the potential of three types of serum exo-miRNAs as biomarkers for diagnosis in HFrEF patients who were admitted in hospital because of acute heart failure (AHF). Methods: A total of 28 HFrEF patients hospitalized for AHF, including de novo AHF and acute decompensated HF, and 30 volunteers as control group (CG) from 2015 to 2017 were enrolled in this study. Serum exo-miRNAs were extracted and analyzed by NaNOZS-90, electron microscopy, and western blotting. Three types of serum exo-miRNAs (exo-miR-92b-5p,-192-5p, and-320a) were assessed by quantitative real time polymerase chain reaction (qRT-PCR). Results: The particle size was confirmed as 40-150 nm using NaNOZS-90 and transmission electron microscopy. Exosomal biomarkers CD63 and Hsp70 were readily detected. The expression level of serum exo-miRNAs were transformed into log2 −delta CT in the qPCR assay. The data showed that exo-miR-92b-5p was elevated in HFrEF patients compared with controls. Moreover, exo-miR-92b-5p was inversely correlated with the left ventricular fraction shortening (LVFS) and left ventricular ejection fraction (LVEF), whereas it was positively correlated with left atrial diameter (LAD), left ventricular diastolic diameters (LVDD) and systolic diameters (LVSD). A receiver operating characteristic (ROC) curve was generated for discrimination between HFrEF patients and controls based on exo-miR-92b-5p (P<0.001, sensitivity =71.4%, specificity =83.3%). Conclusions: Exo-miR-92b-5p levels in the serum may serve as a marker for HFrEF diagnosis.

Background/Aims: MicroRNAs (miRNAs) can be used as biomarkers for cardiovascular diseases, especially for heart failure. However, there are few reports on serum exosomal miRNA biomarkers in patients with acute heart failure (AHF) due to Dilated cardiomyopathy (DCM). Methods: We analyzed 3 different serum exosomal miRNAs (exo-miR-92b-5p, exo-miR-192-5p, and exo-miR-320a) in 43 patients with DCM-AHF and 34 healthy volunteers as a control group (CG) by using exosome separation followed by a quantitative reverse-transcript PCR assay. Exosomes were identified by electron microscopy, NaNOZS-90, and western blot analyses (CD63 and Hsp70). Results: Serum exo-miR-92b-5p expression was increased in DCM-AHF patients compared to the CG (Mann–Whitney U-test: P < 0.001). Exo-miR-92b-5p was positively related to age and some ultrasound data (Spearman’s correlation: exo-miR-92b-5p vs. age, r = 0.297, P = 0.014; exo-miR-92b-5p vs. left atrial diameter, r = 0.431, P < 0.001; exo-miR-92b-5p vs. left ventricular diastolic diameter, r = 0.419, P < 0.001; exo-miR-92b-5p vs. left ventricular systolic diameter, r = 0.446, P < 0.001). Exo-miR-92b-5p was also negatively related to other ultrasound data (Spearman’s correlation: exo-miR-92b-5p vs. left ventricular fraction shortening, r = -0.497, P < 0.001; exo-miR-92b-5p vs. left ventricular ejection fraction, r = -0.482, P < 0.001). The discrimination of DCM-AHF patients from the CG by exo-miR-92b-5p was demonstrated by a receiver operating characteristic curve (exo-miR-92b-5p: cutoff value = 0.0023, area under the curve = 0.808, P < 0.001, sensitivity = 62.8%, specificity = 85.3%). Conclusion: Serum exo-miR-92b-5p is a potential biomarker for the diagnosis of DCM-AHF.

Derivations under different grammar formalisms allow extraction of various dependency structures. Particularly, bilexical deep dependency structures beyond surface tree representation can be derived from linguistic analysis grounded by CCG, LFG, and HPSG. Traditionally, these dependency structures are obtained as a by-product of grammar-guided parsers. In this article, we study the alternative data-driven, transition-based approach, which has achieved great success for tree parsing, to build general dependency graphs. We integrate existing tree parsing techniques and present two new transition systems that can generate arbitrary directed graphs in an incremental manner. Statistical parsers that are competitive in both accuracy and efficiency can be built upon these transition systems. Furthermore, the heterogeneous design of transition systems yields diversity of the corresponding parsing models and thus greatly benefits parser ensemble. Concerning the disambiguation problem, we introduce two new techniques, namely, transition combination and tree approximation, to improve parsing quality. Transition combination makes every action performed by a parser significantly change configurations. Therefore, more distinct features can be extracted for statistical disambiguation. With the same goal of extracting informative features, tree approximation induces tree backbones from dependency graphs and re-uses tree parsing techniques to produce tree-related features. We conduct experiments on CCG-grounded functor–argument analysis, LFG-grounded grammatical relation analysis, and HPSG-grounded semantic dependency analysis for English and Chinese. Experiments demonstrate that data-driven models with appropriate transition systems can produce high-quality deep dependency analysis, comparable to more complex grammar-driven models. Experiments also indicate the effectiveness of the heterogeneous design of transition systems for parser ensemble, transition combination, as well as tree approximation for statistical disambiguation.

The lncRNA MALAT1 has multiple biological functions, including influencing RNA processing, miRNA sponging, and cancer development. It is acknowledged that miR663a and its targets are inflammation-related genes frequently deregulated in many cancers. The associations between MALAT1 and miR663a and their target genes remain unknown. In this study, it was found that in colon cancer (CC) cells, MALAT1 and miR663a were reciprocally repressed in cDNA array screening and qRT-PCR analysis. However, MALAT1 was significantly upregulated in CC tissues, and miR663a was significantly downregulated relative to the corresponding surgical margin (SM) tissues. An inverse relationship between MALAT1 and miR663a expression was detected among CC tissue samples (n = 172, r = −0.333, p < 0.0001). The RNA-pulldown results showed MALAT1 lncRNA–miR663a binding. The results of luciferase-reporter analysis further revealed that the MALAT1 7038–7059 nt fragment was the miR663a seed sequence. Both miR663a knockdown and MALAT1 activation alone significantly upregulated the expression levels of miR663a targets, including TGFB1, PIK3CD, P53, P21, and JUND, in the CC cell lines HCT116 and SW480. A positive relationship was also observed between the expression levels of MALAT1 and these miR663a targets in the above 172 CC samples and 160 CC samples in publicly available databases. In addition, reciprocal abolishment of the effects of miR663a overexpression and MALAT1 activation on the proliferation, migration, and invasion of cancer cells was also observed, while miR663a upregulation and MALAT1 activation alone inhibited and promoted the behaviors of these CC cell lines, respectively. All these suggested that, as a competing endogenous lncRNA, MALAT1 maybe a dominant protector for the degradation of miR663a targets. miR663a and MALAT1 may consist of a negative feedback loop to determine their roles in CC development.