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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-128-3p A2M 0.78 0 -0.31 0.00047 miRNAWalker2 validate -0.17 0 NA
2 hsa-miR-128-3p ABCA1 0.78 0 0.02 0.83411 MirTarget -0.17 0 NA
3 hsa-miR-128-3p ARID3B 0.78 0 -0.1 0.03142 MirTarget -0.11 0 NA
4 hsa-miR-128-3p ARRDC4 0.78 0 -0.19 0.01538 MirTarget -0.15 0 NA
5 hsa-miR-128-3p B4GALT1 0.78 0 -0.15 0.04686 miRNAWalker2 validate -0.17 0 NA
6 hsa-miR-128-3p BMF 0.78 0 -0.43 1.0E-5 MirTarget -0.39 0 NA
7 hsa-miR-128-3p BOC 0.78 0 -0.23 0.00885 miRNAWalker2 validate -0.13 1.0E-5 NA
8 hsa-miR-128-3p BRCA2 0.78 0 -1.03 0 miRNAWalker2 validate -0.34 0 NA
9 hsa-miR-128-3p CASP3 0.78 0 -0.26 0 miRNAWalker2 validate -0.15 0 NA
10 hsa-miR-128-3p CCL18 0.78 0 0.25 0.29925 MirTarget -0.44 0 NA
11 hsa-miR-128-3p CD276 0.78 0 -0.46 0 MirTarget -0.3 0 NA
12 hsa-miR-128-3p CD2AP 0.78 0 -0.15 0.00191 miRNAWalker2 validate -0.12 0 NA
13 hsa-miR-128-3p CD300A 0.78 0 -0.35 0.00049 miRNAWalker2 validate -0.27 0 NA
14 hsa-miR-128-3p CDCP1 0.78 0 -0.51 1.0E-5 MirTarget -0.31 0 NA
15 hsa-miR-128-3p CDKN2A 0.78 0 -0.02 0.90392 MirTarget -0.26 1.0E-5 NA
16 hsa-miR-128-3p CLIC4 0.78 0 -0.32 4.0E-5 MirTarget -0.22 0 NA
17 hsa-miR-128-3p CLP1 0.78 0 -0.18 0 MirTarget -0.12 0 NA
18 hsa-miR-128-3p CLPP 0.78 0 -0.17 0.00059 miRNAWalker2 validate; MirTarget -0.17 0 NA
19 hsa-miR-128-3p CLSPN 0.78 0 -1.31 0 miRNAWalker2 validate -0.16 0.00691 NA
20 hsa-miR-128-3p CMTM6 0.78 0 -0.33 0 miRNAWalker2 validate -0.19 0 NA
21 hsa-miR-128-3p COL3A1 0.78 0 -1.43 0 MirTarget -0.7 0 NA
22 hsa-miR-128-3p CREB3L2 0.78 0 -0.2 0.00053 MirTarget -0.15 0 NA
23 hsa-miR-128-3p CSF1 0.78 0 0.12 0.20838 MirTarget -0.13 8.0E-5 22909061 By mutations in putative miRNA targets in CSF-1 mRNA 3'UTR we identified a common target for both miR-128 and miR-152; We have also found that both miR-128 and miR-152 down-regulate CSF-1 mRNA and protein expression in ovarian cancer cells leading to decreased cell motility and adhesion in vitro two major aspects of the metastatic potential of cancer cells; Our results provide the evidence for a mechanism by which miR-128 and miR-152 down-regulate CSF-1 an important regulator of ovarian cancer
24 hsa-miR-128-3p CTDSP1 0.78 0 -0.05 0.33671 miRNAWalker2 validate -0.16 0 NA
25 hsa-miR-128-3p CTDSP2 0.78 0 -0.23 0.00019 MirTarget -0.13 0 NA
26 hsa-miR-128-3p CTSZ 0.78 0 -0.25 0.00512 miRNAWalker2 validate -0.17 0 NA
27 hsa-miR-128-3p CTU1 0.78 0 -0.1 0.10104 MirTarget -0.13 0 NA
28 hsa-miR-128-3p DOCK11 0.78 0 -0.34 0 MirTarget -0.18 0 NA
29 hsa-miR-128-3p DOT1L 0.78 0 -0.2 0.00987 MirTarget -0.2 0 NA
30 hsa-miR-128-3p E2F7 0.78 0 -1.47 0 miRNAWalker2 validate -0.48 0 NA
31 hsa-miR-128-3p ECE1 0.78 0 -0.45 0 MirTarget -0.17 0 NA
32 hsa-miR-128-3p EFEMP2 0.78 0 -0.47 7.0E-5 miRNAWalker2 validate -0.14 0.00101 NA
33 hsa-miR-128-3p EGFR 0.78 0 -0.38 0.01555 miRNAWalker2 validate; miRTarBase -0.12 0.02954 NA
34 hsa-miR-128-3p ERCC1 0.78 0 -0.15 0.00613 MirTarget -0.12 0 NA
35 hsa-miR-128-3p ESCO2 0.78 0 -1.34 0 miRNAWalker2 validate -0.41 0 NA
36 hsa-miR-128-3p FAM126A 0.78 0 -0.57 0 MirTarget -0.19 0 NA
37 hsa-miR-128-3p FKBP10 0.78 0 -0.55 0 miRNAWalker2 validate -0.3 0 NA
38 hsa-miR-128-3p G6PC3 0.78 0 -0.14 0.00609 miRNAWalker2 validate -0.12 0 NA
39 hsa-miR-128-3p GAPT 0.78 0 -0.59 0.00024 MirTarget -0.38 0 NA
40 hsa-miR-128-3p GATA6 0.78 0 -0.69 7.0E-5 miRNAWalker2 validate; MirTarget -0.25 0.00014 NA
41 hsa-miR-128-3p GCC1 0.78 0 -0.1 0.0247 MirTarget -0.1 0 NA
42 hsa-miR-128-3p GFPT2 0.78 0 0.13 0.27512 miRNAWalker2 validate -0.11 0.00957 NA
43 hsa-miR-128-3p GLTSCR2 0.78 0 0.05 0.48314 miRNAWalker2 validate -0.12 0 NA
44 hsa-miR-128-3p GYS1 0.78 0 -0.16 0.00181 MirTarget -0.13 0 NA
45 hsa-miR-128-3p HIC1 0.78 0 -0.29 0.00052 MirTarget -0.22 0 NA
46 hsa-miR-128-3p HMOX1 0.78 0 -0.44 2.0E-5 miRNAWalker2 validate -0.36 0 NA
47 hsa-miR-128-3p HOXC6 0.78 0 -1.49 0 miRNAWalker2 validate -0.7 0 NA
48 hsa-miR-128-3p IL13RA1 0.78 0 -0.23 0.01158 MirTarget -0.15 0 NA
49 hsa-miR-128-3p JAG1 0.78 0 -0.59 0 MirTarget -0.29 0 NA
50 hsa-miR-128-3p KCTD14 0.78 0 -0.29 0.00059 miRNAWalker2 validate -0.13 5.0E-5 NA
51 hsa-miR-128-3p KLHDC8A 0.78 0 -0.65 0 MirTarget -0.27 0 NA
52 hsa-miR-128-3p LBR 0.78 0 -0.22 5.0E-5 miRNAWalker2 validate -0.16 0 NA
53 hsa-miR-128-3p LILRB5 0.78 0 0.48 0.00173 miRNAWalker2 validate -0.17 0.0031 NA
54 hsa-miR-128-3p LMNB1 0.78 0 -0.8 0 miRNAWalker2 validate -0.31 0 NA
55 hsa-miR-128-3p LRAT 0.78 0 -0.18 0.28968 MirTarget -0.17 0.00919 NA
56 hsa-miR-128-3p LRRN4CL 0.78 0 -1.13 0 MirTarget -0.45 0 NA
57 hsa-miR-128-3p LTBP1 0.78 0 -0.17 0.10981 MirTarget -0.15 0.0002 NA
58 hsa-miR-128-3p MAP3K8 0.78 0 -0.16 0.05637 MirTarget -0.14 1.0E-5 NA
59 hsa-miR-128-3p MAPKAPK3 0.78 0 -0.07 0.28057 MirTarget -0.13 0 NA
60 hsa-miR-128-3p NEK2 0.78 0 -1.47 0 miRNAWalker2 validate; MirTarget -0.29 0 24046120 In particular we examined miR-128 expression which is thought to target NEK2; We measured NEK2 mRNA and miR-128 levels in clinical samples by quantitative reverse transcription real-time PCR and analyzed the associations between NEK2 levels miR-128 levels clinicopathological factors and prognoses; MiR-128 inhibited NEK2 expression and cancer cell proliferation via cell cycle arrest; Patients with high miR-128 expression had significantly lower NEK2 expression and lower recurrence rates than those with low miR-128 expression; NEK2 may be an independent prognostic factor for CRC and was regulated by miR-128 a microRNA that was subjected to epigenetic regulation
61 hsa-miR-128-3p NFIL3 0.78 0 -0.39 0 MirTarget -0.17 0 NA
62 hsa-miR-128-3p NOP2 0.78 0 -0.22 2.0E-5 miRNAWalker2 validate -0.17 0 NA
63 hsa-miR-128-3p NXT1 0.78 0 -0.33 0 miRNAWalker2 validate -0.25 0 NA
64 hsa-miR-128-3p PDIA5 0.78 0 -0.58 0 MirTarget -0.37 0 NA
65 hsa-miR-128-3p PDPN 0.78 0 -1.01 0 MirTarget -0.47 0 NA
66 hsa-miR-128-3p PHB 0.78 0 -0.1 0.04099 MirTarget -0.1 0 NA
67 hsa-miR-128-3p PHC2 0.78 0 -0.21 0.0006 MirTarget -0.15 0 NA
68 hsa-miR-128-3p PPP4C 0.78 0 -0.21 5.0E-5 MirTarget -0.2 0 NA
69 hsa-miR-128-3p PQLC3 0.78 0 -0.24 7.0E-5 MirTarget -0.17 0 NA
70 hsa-miR-128-3p PRKD1 0.78 0 0.02 0.6922 MirTarget -0.12 0 NA
71 hsa-miR-128-3p PRR11 0.78 0 -0.7 0 miRNAWalker2 validate -0.11 0.03256 NA
72 hsa-miR-128-3p RAB20 0.78 0 -0.05 0.56131 MirTarget -0.23 0 NA
73 hsa-miR-128-3p RAB34 0.78 0 -0.59 0 MirTarget -0.15 0.00061 NA
74 hsa-miR-128-3p RAP1B 0.78 0 -0.14 0.00328 MirTarget -0.15 0 25017996 miR 128 and miR 149 enhance the chemosensitivity of temozolomide by Rap1B mediated cytoskeletal remodeling in glioblastoma
75 hsa-miR-128-3p RDX 0.78 0 -0.09 0.16153 MirTarget -0.12 0 NA
76 hsa-miR-128-3p RPL28 0.78 0 -0.08 0.27539 miRNAWalker2 validate -0.15 0 NA
77 hsa-miR-128-3p SAMD9L 0.78 0 -0.47 1.0E-5 MirTarget -0.25 0 NA
78 hsa-miR-128-3p SEC61A1 0.78 0 -0.27 1.0E-5 miRNAWalker2 validate; MirTarget -0.18 0 NA
79 hsa-miR-128-3p SFXN2 0.78 0 0.09 0.15796 miRNAWalker2 validate -0.12 0 NA
80 hsa-miR-128-3p SKA3 0.78 0 -1.24 0 MirTarget -0.38 0 NA
81 hsa-miR-128-3p SLC16A1 0.78 0 -0.32 0 miRNAWalker2 validate -0.15 0 NA
82 hsa-miR-128-3p SLC39A7 0.78 0 -0.17 0.00058 miRNAWalker2 validate; MirTarget -0.13 0 NA
83 hsa-miR-128-3p SOX11 0.78 0 -0.27 0.02742 miRNAWalker2 validate -0.18 3.0E-5 NA
84 hsa-miR-128-3p SOX2 0.78 0 -0.06 0.49975 miRNAWalker2 validate -0.13 0 NA
85 hsa-miR-128-3p SPG21 0.78 0 -0.06 0.16752 MirTarget -0.12 0 NA
86 hsa-miR-128-3p SSFA2 0.78 0 -0.3 0 miRNAWalker2 validate -0.11 0 NA
87 hsa-miR-128-3p STEAP3 0.78 0 -0.85 0 MirTarget -0.37 0 NA
88 hsa-miR-128-3p STK3 0.78 0 -0.16 0.00329 miRNAWalker2 validate; MirTarget -0.2 0 NA
89 hsa-miR-128-3p STK40 0.78 0 -0.43 0 MirTarget -0.21 0 NA
90 hsa-miR-128-3p SUMF1 0.78 0 -0.19 0.00034 miRNAWalker2 validate -0.12 0 NA
91 hsa-miR-128-3p TAGLN 0.78 0 -0.28 0.00367 miRNAWalker2 validate -0.18 0 NA
92 hsa-miR-128-3p TGFBR1 0.78 0 -0.34 0 miRNAWalker2 validate; miRTarBase -0.21 0 NA
93 hsa-miR-128-3p TIA1 0.78 0 -0.02 0.7735 MirTarget -0.1 0 NA
94 hsa-miR-128-3p TM4SF1 0.78 0 -0.73 0 miRNAWalker2 validate -0.26 0 NA
95 hsa-miR-128-3p TMEM64 0.78 0 -0.16 0.00347 MirTarget -0.12 0 NA
96 hsa-miR-128-3p TMX1 0.78 0 -0.16 0.00337 MirTarget -0.17 0 NA
97 hsa-miR-128-3p TNFAIP8 0.78 0 -0.77 0 MirTarget -0.41 0 NA
98 hsa-miR-128-3p TROVE2 0.78 0 -0.08 0.09467 miRNAWalker2 validate -0.12 0 NA
99 hsa-miR-128-3p TSPAN6 0.78 0 -0.14 0.03739 miRNAWalker2 validate -0.19 0 NA
100 hsa-miR-128-3p TXNDC5 0.78 0 -0.35 0 MirTarget -0.15 0 NA
101 hsa-miR-128-3p TXNIP 0.78 0 0.01 0.92255 miRNAWalker2 validate; MirTarget -0.12 0 NA
102 hsa-miR-128-3p UTP15 0.78 0 -0.22 0 MirTarget -0.13 0 NA
103 hsa-miR-128-3p VANGL2 0.78 0 0.04 0.60519 MirTarget -0.12 0 NA
104 hsa-miR-128-3p VSIG10 0.78 0 -0.06 0.2412 MirTarget -0.12 0 NA
105 hsa-miR-128-3p WEE1 0.78 0 -0.99 0 miRNAWalker2 validate; miRTarBase; MirTarget -0.41 0 NA
106 hsa-miR-128-3p ZNF552 0.78 0 -0.22 0 miRNAWalker2 validate -0.14 0 NA

Over-represented Gene Ontology Biological Process

NumGOOverlapSizeP ValueAdj. P Value
1 POSITIVE REGULATION OF INTRACELLULAR SIGNAL TRANSDUCTION 18 876 7.534e-07 0.001267
2 CARDIOVASCULAR SYSTEM DEVELOPMENT 17 788 8.167e-07 0.001267
3 CIRCULATORY SYSTEM DEVELOPMENT 17 788 8.167e-07 0.001267
4 REGULATION OF INTRACELLULAR SIGNAL TRANSDUCTION 25 1656 1.317e-06 0.001532
5 REGULATION OF CELL CYCLE 18 949 2.356e-06 0.002192
6 TUBE DEVELOPMENT 13 552 7.143e-06 0.005539
NumGOOverlapSizeP ValueAdj. P Value
NumGOOverlapSizeP ValueAdj. P Value

Over-represented Pathway

NumPathwayPathviewOverlapSizeP ValueAdj. P Value
1 MAPK_signaling_pathway_hsa04010 8 295 0.000176 0.007149
2 TNF_signaling_pathway_hsa04668 5 108 0.000275 0.007149
3 p53_signaling_pathway_hsa04115 3 68 0.005649 0.09792
4 Cytokine_cytokine_receptor_interaction_hsa04060 5 270 0.01451 0.1887
5 Ferroptosis_hsa04216 2 40 0.01904 0.1973
6 Rap1_signaling_pathway_hsa04015 4 206 0.02406 0.1973
7 AMPK_signaling_pathway_hsa04152 3 121 0.02656 0.1973
8 FoxO_signaling_pathway_hsa04068 3 132 0.03315 0.205
9 Apoptosis_hsa04210 3 138 0.03707 0.205
10 PI3K_Akt_signaling_pathway_hsa04151 5 352 0.03943 0.205
11 Hippo_signaling_pathway_hsa04390 3 154 0.04864 0.2299
12 Adherens_junction_hsa04520 2 72 0.05596 0.2425
13 TGF_beta_signaling_pathway_hsa04350 2 84 0.07331 0.2932
14 HIF_1_signaling_pathway_hsa04066 2 100 0.09867 0.3665
15 Ras_signaling_pathway_hsa04014 3 232 0.1255 0.3911
16 Lysosome_hsa04142 2 123 0.1386 0.3911
17 Endocytosis_hsa04144 3 244 0.1399 0.3911
18 Cell_cycle_hsa04110 2 124 0.1404 0.3911
19 Apelin_signaling_pathway_hsa04371 2 137 0.1643 0.4069
20 Cellular_senescence_hsa04218 2 160 0.2082 0.4508
21 Jak_STAT_signaling_pathway_hsa04630 2 162 0.2121 0.4508
22 cAMP_signaling_pathway_hsa04024 2 198 0.2825 0.5101
23 Focal_adhesion_hsa04510 2 199 0.2845 0.5101
24 Regulation_of_actin_cytoskeleton_hsa04810 2 208 0.3021 0.5237

Quest ID: 50103f284f807f6924fdf6c55c4643d1