Project description:This SuperSeries is composed of the following subset Series: GSE26376: Microarray profiling of monocytic differentiaion reveals miRNA-mRNA intrinsic correlation (miRNA) GSE26377: Microarray profiling of monocytic differentiaion reveals miRNA-mRNA intrinsic correlation (gene expression) Refer to individual Series
Project description:Despite advance in interferon-based treatment for chronic hepatitis C, difficult-to-treat patients remain in existence yet. To identify key genes involved in difficult-to-treat characteristics, gene expression patterns of miRNA and RNA were analyzed by profiling pretreatment liver tissues from five sustained virological responders (SVR), three relapsers (R) and four non-responders (NR). Expression levels of miRNA and mRNA were compared between SVR/R and NR groups by using microarray, respectively. Quantitative real-time reverse-transcriptase polymerase chain reaction and statistical analyses validated genes with significantly differential expression levels in 50 liver tissues: proliferation-, inflammation- and anti-apoptosis-related mRNA expression levels increased significantly in NR, compared to SVR/R. Of miRNA with significantly differential expression levels on microarray, several miRNA were correlated inversely with those significant mRNA. In vitro studies by using miRNA inhibitors and mimics verified the inverse correlation between the miRNA and mRNA. These findings enhance our understanding of the difficult-to-treat molecular mechanism and identification of target molecules for novel treatments.
Project description:The aim of our study is to identify miRNAs responsible for bone-cancer pain condition and their target mRNAs. We combined mRNA profiling with Affymetrix microarray and miRNA measurement with a qRT-PCR-based technique. Then, a cross-correlation of these data highlighted miRNA-mRNA pairs that were further characterized with functional experiments.
Project description:A multi-step approach combining microarray profile and bioinformatics analysis was adopted to identify the CRC specific miRNA-mRNA regulatory network. First, differentially expressed miRNAs and mRNAs were found out in CRC samples compared with normal epithelial tissues by miRNA and mRNA microarray respectively. Secondly the target mRNAs of dysregualted miRNA were identified by a combination of Pearson correlation coefficient between the expression level of miRNAs and mRNAs and online miRNA target predicting databases. Thirdly, the biological pathways which the miRNA-mRNA pairs involved in were identified by DAVID. Finally, some of the dysregualted miRNAs and mRNAs were validated by qRT-PCR
