Input your mRNA list and/or miRNA list and discover the miRNA-mRNA regulations and regulatory network. The miRNA-mRNA regulations will be inferred from both interactions and expression correlations. The designated methods (e.g. MirTarget, PITA, and/or TargetSCAN) will be used to infer the miRNA-mRNA interactions. And the public data of selected cancer type will be used in learning the correlation between miRNAs and mRNAs, and in constructing the regulatory network. TCGA RNA-seq data has been applied in this work so far.
Putative lncRNA sponges can be identified by the positive correlated lncRNA-mRNA pairs commonly regulated by the same set of miRNAs (>10 miRNAs). All these findings will be combined and jointly presented in the interactive regulatory network. We identified miRNA-lncRNA and miRNA-mRNA regulation pairs based on evidences from both sequence-based interactions and anti-correlations of expression. For each mRNA, we examine every single lncRNA to search for the common miRNAs that regulate their expression simultaneously. The list of miRNAs shared by the lncRNA-mRNA pairs were generated and counted, as well as the Pearson correlation coefficient between the lncRNA-mRNA pair in expression data. The lncRNA-mRNA pairs with putative sponge regulation were selected by two criteria, including 1. larger than 0.25 for the Pearson correlation coefficient between lncRNA and mRNA pair (user can decide the significance level by set the P-value cutoff), and 2. at least ten different miRNAs shared in the pair. In the result page, the shared miRNA set of lncRNA and gene will be presented, along with the positive correlation between lncRNA and gene and the negative correlation between miRNA sets and their targets.
You can upload your miRNA-mRNA expression matrix here and run the analysis. This data will be used in learning the correlations between miRNAs and mRNAs and constructing the regulatory network. In default settings, all of your differentially expressed mRNAs and miRNAs will be analyzed. You can also input your own mRNA and miRNA list in the advanced options. Please download the example file to see the file format.
"miRNACancerMAP" is also a network visualization tool for user to draw their regulatory network by personal customization. Users can set the complexity of the visualized network by limiting the number of nodes or edges. And the color of the nodes can be defined by different categories of the mRNAs and miRNAs, like mRNA-Ontology, pathway and expression status. User can also select to use network degree or network betweenness to define the node size. And edges can be black or colored by the correlation. Purple edge means negative correlation and blue edge means positive correlation. We can also add the protein-protein interactions (PPI) into the network. This result will show the cluster of mRNAs regulated by some specific miRNAs. Additionally, miRNA-miRNA edges can be added by the "miRNA sponge" button. This result will show some clusters of miRNA are co-regulating the same mRNA.
GAS5-miRNAs-PLXDC1 sponge regulation in TCGA LIHC cohort
GAS5-miRNAs-PLXDC1 sponge regulation in Burchard J.'s liver cancer cohort (GSE22058)
HCG18-miRNAs-PLXDC1 sponge regulation in TCGA LIHC cohort
HCG18-miRNAs-PLXDC1 sponge regulation in Burchard J.'s liver cancer cohort (GSE22058)
PVT1-miRNAs-MAFG sponge regulation in TCGA LIHC cohort
PVT1-miRNAs-MAFG sponge regulation in Burchard J.'s liver cancer cohort (GSE22058)
The data statistics of this database includes comprehensive and vast data.