Tag Archives: Nilotinib

Atrial fibrillation (AF) is a highly prevalent cardiac arrhythmia disease, which

Atrial fibrillation (AF) is a highly prevalent cardiac arrhythmia disease, which widely leads to exacerbate heart failure and ischemic stroke in elder world. pathway analysis were applied to explore the potential lncRNAs functions, some pathways including oxygen transporter activity and protein heterodimerization activity were speculated to be involved in AF pathogenesis. These results shed some light on lncRNAs’ physiologic functions and provide useful information for exploring potential therapeutic treatments for heart rhythm disease. value<0.05 for up- and down-regulated genes. Then, Hierarchical Clustering was employed to calculate the distinguishable lncRNA and mRNA expression patterns. Functional group analysis The functions in biological pathways or GO terms of these closest coding genes were analyzed by Pathway and GO analyses Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis according to the latest KEGG database (http://www.genome.jp/kegg/) was employed to determine the biological roles of these differentially expressed mRNAs. Nilotinib Significance is judged when p value (Hypergeometric-P value) is less than 0.05. Co-expression network construction To discover the potential targets of lncRNA, we analyzed the interaction between lncRNAs and corresponding transcription factors based on hypergeometric cumulative distribution function with the help of MATLAB 2012b (The MathWorks, USA). The graph of the lncRNAs-TFs network was drawn with the help of Cytoscape 3.01 (Agilent and IBS, USA). If the intersection of these two groups is large enough (< 0.01, calculated by hypergeometric cumulative Nilotinib distribution function and FDR < 0.01, under the control of the Benjamini and Hochberg procedure), then we predict that these lncRNAs possibly participate in pathways regulated by these TFs. The recently released ENCODE data on TFs and Nilotinib their regulatory targets were used in our analysis Real-time quantitative reverse transcription PCR A two-step reaction process was used for quantification reverse transcription [21] and PCR. Each RT reaction consisted of 0.5 g RNA, 2 L of Primer Script Buffer, 0.5 L of oligo dT, 0.5 L of random 6 mers, 0.5 L of Primer Script RT Enzyme Mix I (TaKaRa, Japan) and nuclease-free water to reach a volume of 10 L. Reactions were performed in the GeneAmp? PCR System 7500 (Applied Biosystems, USA) for 15 min at 37C, then inactivation of RT by heating at 85C for 5 s. Then the RT mix was diluted by 10-fold with nuclease-free water and stored at ?20C. While running real-time quantitative PCR, melting curve was analyzed to verify the specificity of the aimed PCR product. All experiments were done in triplicate. Glyceraldehyde-3-phosphate dehydrogenase was used as an endogenous control to normalize and using the 2-Ct method for lncRNAs expression calculation. The primer sequences were designed in the laboratory based on the DNA sequences and is shown: NONHSAG007503 (forwards primer GGAGAAGTCTGCCGTTAC; reverse primer TCAAAGAACCTCTGGGTCC) and NONHSAT040387 (forwards primer CTTCAGTAGCTCTGCTATGC; reverse primer AGAGTCTGCGTAGTATATGGTA). Statistical analysis All results were represented as the means SD or proportions. For comparisons, paired t-tests and unpaired t-tests were performed where appropriate. All graphs were plotting using GraphPad Prism 5.0 for Microsoft Windows (GraphPad Software, USA). Two-sided < 0.05. SUPPLEMENTARY MATERIAL FIGURE Click here to view.(348K, pdf) Acknowledgments This work was supported by the Shanghai Committee of Science and Technology (No. 13140903700). Footnotes CONFLICTS OF INTEREST The authors declare no financial conflicts of interest. REFERENCES 1. Luo X, Yang B, Nattel S. MicroRNAs and atrial fibrillation: mechanisms and translational potential. Nature reviews Cardiology. 2014 [PubMed] 2. Dewland TA, Glidden DV, Marcus GM. Healthcare utilization and Nilotinib clinical outcomes after catheter ablation of atrial flutter. PloS one. 2014;9:e100509. [PMC free article] [PubMed] 3. Santulli G, Iaccarino G, De Luca N, Trimarco B, Condorelli G. Atrial fibrillation and microRNAs. Frontiers in physiology. 2014;5:15. [PMC free article] [PubMed] 4. Hung T, Chang HY. Long noncoding RNA in genome regulation: prospects and mechanisms. RNA biology. 2010;7:582C585. [PMC free article] [PubMed] 5. Di FLT4 Gesualdo F, Capaccioli S, Lulli M. A pathophysiological view of the long non-coding RNA world. Oncotarget. 2014;5:10976C10996. doi: 10.18632/oncotarget.2770. [PMC free article] [PubMed] [Cross Ref] 6. Gomes da Silva AM, Silbiger VN. miRNAs as biomarkers of atrial fibrillation. Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals. 2014;19:631C636. [PubMed] 7. Zhao W, Luo J, Jiao S. Comprehensive characterization of cancer subtype associated long non-coding RNAs and their clinical implications. Scientific reports. 2014;4:6591. [PMC free article] [PubMed] 8. Prensner JR, Chinnaiyan AM. The.