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This regulatory network was inferred from the input dataset. The miRNAs and mRNAs are presented as round and rectangle nodes respectively. The numerical value popped up upon mouse over the gene node is the log2 transformed fold-change of the gene expression between the two groups. All of the nodes are clickable, and the detailed information of the miRNAs/mRNAs and related cancer pathway will be displayed in another window. The edges between nodes are supported by both interactions (predicted or experimentally verified) and correlations learnt from cancer dataset. The numerical value popped up upon mouse over the edge is the correlation beat value (effect size) between the two nodes. The experimental evidences of the edges reported in previous cancer studies are highlighted by red/orange color. All of these information can be accessed by the "mouse-over" action. This network shows a full map of the miRNA-mRNA regulation of the input gene list(s), and the hub miRNAs (with the high network degree/betweenness centrality) would be the potential cancer drivers or tumor suppressors. The full result table can be accessed in the "Regulations" tab.

"miRNACancerMAP" is also a network visualization tool for users to draw their regulatory network by personal customization. Users can set the complexity of the 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, such as Gene-Ontology, pathway, and expression status. Users can also select to use network degree or network betweenness centrality to define the node size. And edges can be black or colored by the correlation. Purple edge means negative correlation (mostly found between miRNA and mRNA), and blue edge means positive correlation (found in PPI or miRNA-miRNA sponge effect). We can also add the protein-protein interactions (PPI) into the network. This result will show the cluster of genes regulated by some specific miRNAs. Additionally, miRNA-miRNA edges can be added by the "miRNA sponge" button, presenting some clusters of miRNAs that have the interactions via sponge effect.

miRNA-gene regulations

(Download full result)

Num microRNA           Gene miRNA log2FC miRNA pvalue Gene log2FC Gene pvalue Interaction Correlation beta Correlation P-value PMID Reported in cancer studies
1 hsa-miR-191-5p BDNF 2.3 0 -2.91 0 miRNATAP -0.49 0 NA
2 hsa-miR-191-5p BRMS1L 2.3 0 -0.51 0.00391 miRNATAP -0.19 0 NA
3 hsa-miR-191-5p CBFA2T3 2.3 0 -1.56 2.0E-5 MirTarget -0.22 0.00048 NA
4 hsa-miR-191-5p CCND2 2.3 0 -2.43 0 MirTarget -0.63 0 NA
5 hsa-miR-191-5p CCPG1 2.3 0 -1 0 MirTarget -0.34 0 NA
6 hsa-miR-191-5p CDK6 2.3 0 -0.77 0.06479 miRNAWalker2 validate; miRTarBase -0.71 0 NA
7 hsa-miR-191-5p CEBPB 2.3 0 -0.38 0.12583 MirTarget; miRNATAP -0.3 0 NA
8 hsa-miR-191-5p CUX1 2.3 0 -0.4 0.0025 mirMAP -0.14 0 NA
9 hsa-miR-191-5p EGR1 2.3 0 -3.5 0 miRNATAP -0.59 0 23505378 We demonstrated that miR-191 protects ERĪ± positive breast cancer cells from hormone starvation-induced apoptosis through the suppression of tumor-suppressor EGR1
10 hsa-miR-191-5p ENAH 2.3 0 -0.68 0.00063 miRNAWalker2 validate -0.25 0 NA
11 hsa-miR-191-5p FOXK1 2.3 0 -0.29 0.13213 mirMAP -0.15 1.0E-5 NA
12 hsa-miR-191-5p GAP43 2.3 0 -1.67 0.00774 miRNATAP -0.75 0 NA
13 hsa-miR-191-5p MAPRE2 2.3 0 -1.49 0 MirTarget; miRNATAP -0.42 0 NA
14 hsa-miR-191-5p MCFD2 2.3 0 -0.27 0.08021 miRNAWalker2 validate -0.22 0 NA
15 hsa-miR-191-5p NDST1 2.3 0 -0.25 0.17674 miRTarBase; miRNATAP -0.22 0 21947487 The N-deacetylase/N-sulfotransferase 1 NDST1 was confirmed to be a direct target gene of miR-191 by enhanced green fluorescent protein reporter experiment; The mRNA and protein levels of NDST1 were inversely correlated with miR-191 in MGC803 cells suggesting the negative regulation of NDST1 by miR-191; Our findings suggested that miR-191 could act as an oncogene in MGC803 cells and the cellular function was partially due to its negative regulation of NDST1
16 hsa-miR-191-5p NFIA 2.3 0 -2.1 0 miRNATAP -0.39 0 NA
17 hsa-miR-191-5p PCSK9 2.3 0 0.64 0.37328 MirTarget -0.81 0 NA
18 hsa-miR-191-5p PRDM16 2.3 0 -2.56 0 mirMAP -0.38 2.0E-5 NA
19 hsa-miR-191-5p PSAP 2.3 0 0.07 0.67077 miRNAWalker2 validate -0.13 1.0E-5 NA
20 hsa-miR-191-5p SBDS 2.3 0 -1.01 0 MirTarget -0.22 0 NA
21 hsa-miR-191-5p SLC7A1 2.3 0 0.06 0.83891 MirTarget -0.28 0 NA
22 hsa-miR-191-5p TARS 2.3 0 0.49 0.00684 miRNAWalker2 validate -0.12 0.0001 NA
23 hsa-miR-191-5p TBC1D16 2.3 0 -0 0.99705 mirMAP -0.16 0 NA
24 hsa-miR-191-5p TJP1 2.3 0 -0.7 1.0E-5 MirTarget; miRNATAP -0.13 0 NA
25 hsa-miR-191-5p TMOD2 2.3 0 -1.02 2.0E-5 miRNATAP -0.25 0 NA
26 hsa-miR-191-5p TRIM58 2.3 0 -1.91 0.00041 MirTarget -0.25 0.00575 NA
27 hsa-miR-191-5p ZCCHC24 2.3 0 -2.71 0 miRNATAP -0.66 0 NA
NumGOOverlapSizeP ValueAdj. P Value
NumGOOverlapSizeP ValueAdj. P Value
NumGOOverlapSizeP ValueAdj. P Value

Over-represented Pathway

NumPathwayPathviewOverlapSizeP ValueAdj. P Value
1 p53_signaling_pathway_hsa04115 2 68 0.003784 0.1968
2 PI3K_Akt_signaling_pathway_hsa04151 3 352 0.01156 0.2096
3 Cell_cycle_hsa04110 2 124 0.01209 0.2096
4 Cellular_senescence_hsa04218 2 160 0.01958 0.2546

Quest ID: 0f8b9b5a7d4deca9ed7402f34c820840