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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-125a-5p CD276 -0.56 0 1.19 0 miRanda -0.37 0 NA
2 hsa-miR-29a-3p CD276 -0.43 0 1.19 0 miRNAWalker2 validate; miRTarBase; MirTarget; miRNATAP -0.16 0.02171 NA
3 hsa-miR-29c-3p CD276 -0.24 0.01415 1.19 0 MirTarget; miRNATAP -0.25 1.0E-5 24577056 Identifying microRNAs regulating B7 H3 in breast cancer: the clinical impact of microRNA 29c
4 hsa-miR-149-5p FOXM1 -1.96 0 2.58 0 miRNAWalker2 validate; MirTarget -0.27 0 23762558; 25613903; 27415661 miR 149 Inhibits Non Small Cell Lung Cancer Cells EMT by Targeting FOXM1; Overexpression of FOXM1 restored EMT process inhibited by miR-149;MicroRNA 149 suppresses colorectal cancer cell migration and invasion by directly targeting forkhead box transcription factor FOXM1; Gain- and loss - of - function assays indicated that miR-149 significantly inhibited growth migration and invasion of CRC cells by targeting FOXM1; Furthermore FOXM1 was significantly uiregulated in CRC tissues and inversely correlated with miR-149 expression;MicroRNA 149 Increases the Sensitivity of Colorectal Cancer Cells to 5 Fluorouracil by Targeting Forkhead Box Transcription Factor FOXM1; Previously we have shown that microRNA miR-149 suppresses the migration and invasion of colorectal cancer CRC cells by targeting forkhead box transcription factor FOXM1; The aim of this study is to investigate whether miR-149 targets FOXM1 to regulate the 5-FU resistance of CRC; Finally whether miR-149 regulates the 5-FU resistance of CRC cells by targeting the mammalian Forkhead Box M1 FOXM1 was investigated; In addition the luciferase assay indicated that miR-149 could bind to the 3'-UTR sequence of FOXM1 mRNA; The silencing of FOXM1 could mimic the effect of miR-149 upregulation on the 5-FU resistance of 5-FU-resistant CRC cells; Furthermore the expression of miR-149 in the 5-FU-responding CRC tissues was significantly higher than that in the non-responding tissues and inversely correlated with FOXM1 mRNA level; MiR-149 reverses the resistance of CRC cells to 5-FU by directly targeting FOXM1
5 hsa-miR-200b-3p FSCN1 -1.7 0 1.41 0 MirTarget; TargetScan -0.44 0 27356635 miR 200b inhibits migration and invasion in non small cell lung cancer cells via targeting FSCN1
6 hsa-miR-200c-3p FSCN1 -5.4 0 1.41 0 MirTarget -0.21 0 NA
7 hsa-miR-29a-5p FSCN1 -0.52 0 1.41 0 miRNATAP -0.25 0.00084 NA
8 hsa-miR-30a-5p FSCN1 -0.78 0 1.41 0 miRNAWalker2 validate -0.69 0 NA
9 hsa-miR-429 FSCN1 -2.17 0 1.41 0 MirTarget; PITA; miRanda; miRNATAP -0.35 0 27042104 miR 429 functions as a tumor suppressor by targeting FSCN1 in gastric cancer cells; Fascin-1 FSCN1 was identified as one of the targets of miR-429 and knockdown of FSCN1 mimics the function of miR-429 overexpression; In conclusion miR-429 acts as a tumor suppressor by targeting FSCN1 suggesting that miR-429 and FSCN1 can both be potential therapeutic targets of GC
10 hsa-miR-183-5p ITGA5 -1.22 0 2.04 0 miRNAWalker2 validate -0.17 4.0E-5 NA
11 hsa-miR-27b-3p ITGA5 -0.7 0 2.04 0 miRNATAP -0.67 0 NA
12 hsa-miR-3065-3p ITGA5 -1.65 0 2.04 0 miRNATAP -0.34 0 NA
13 hsa-miR-30a-5p ITGA5 -0.78 0 2.04 0 miRNATAP -0.96 0 NA
14 hsa-miR-30c-5p ITGA5 -1.09 0 2.04 0 miRNATAP -0.8 0 NA
15 hsa-miR-30d-5p ITGA5 -0.2 0.00659 2.04 0 miRNATAP -0.83 0 NA
16 hsa-miR-429 ITGA5 -2.17 0 2.04 0 miRNATAP -0.5 0 NA
NumGOOverlapSizeP ValueAdj. P Value
NumGOOverlapSizeP ValueAdj. P Value
NumGOOverlapSizeP ValueAdj. P Value

Over-represented Pathway

NumPathwayPathviewOverlapSizeP ValueAdj. P Value

Quest ID: 1399b871a3db70fa02e75d3a8e0d07b8