Table 2.
Centrality Analysis Gene Results.
| Symbol | Description | Degree (p-value) | Closeness (p-value) | Betweenness (p-value) | Eigenvector (p-value) |
|---|---|---|---|---|---|
| PIK3CA | phosphoinositide-3-kinase, catalytic, alpha polypeptide | 406 (p = 1.8E−08) | 0.00081 (p = 6.4E−01) | 43246.5 (p = 0.0E + 00) | 0.16 (p = 2.9E−03) |
| MAPK8 | mitogen-activated protein kinase 8 | 372 (p = 3.8E−07) | 0.00078 (p = 6.6E−01) | 30937.8 (p = 0.0E + 00) | 0.15 (p = 6.3E−03) |
| CD44 | CD44 molecule (Indian blood group) | 349 (p = 1.3E−08) | 0.00075 (p = 6.6E−01) | 32129.4 (p = 0.0E + 00) | 0.13 (p = 7.3E−03) |
| MAPK1 | mitogen-activated protein kinase 1 | 280 (p = 3.5E−03) | 0.00074 (p = 6.5E−01) | 19719.2 (p = 1.7E−03) | 0.13 (p = 3.9E−02) |
| CREB1 | cAMP responsive element binding protein 1 | 283 (p = 1.2E−08) | 0.00073 (p = 6.4E−01) | 15524.7 (p = 0.0E + 00) | 0.12 (p = 3.0E−03) |
| LEP | leptin | 301 (p = 8.7E−10) | 0.00072 (p = 6.6E−01) | 22639.7 (p = 0.0E + 00) | 0.12 (p = 5.6E−03) |
| CCL2 | chemokine (C-C motif) ligand 2 | 276 (p = 3.3E−03) | 0.00071 (p = 6.9E−01) | 13595.3 (p = 4.5E−03) | 0.12 (p = 1.0E−01) |
| JUN | jun proto-oncogene | 232 (p = 5.9E−03) | 0.00071 (p = 6.7E−01) | 11905.8 (p = 1.2E−02) | 0.12 (p = 4.3E−02) |
| ESR1 | estrogen receptor 1 | 269 (p = 4.7E−09) | 0.00071 (p = 6.6E−01) | 17433.2 (p = 0.0E + 00) | 0.11 (p = 5.8E−03) |
| FOS | FBJ murine osteosarcoma viral oncogene homolog | 229 (p = 3.1E−03) | 0.00070 (p = 6.4E−01) | 21885.2 (p = 2.5E−07) | 0.10 (p = 7.4E−02) |
| CD36 | CD36 molecule (thrombospondin receptor) | 247 (p = 5.0E−07) | 0.00070 (p = 6.5E−01) | 11865.1 (p = 6.5E−13) | 0.11 (p = 7.2E−03) |
| IL1B | interleukin 1, beta | 224 (p = 6.5E−03) | 0.00070 (p = 6.6E−01) | 12492.5 (p = 3.4E−03) | 0.09 (p = 1.6E−02) |
| HGF | hepatocyte growth factor (hepapoietin A; scatter factor) | 213 (p = 9.4E−06) | 0.00069 (p = 6.6E−01) | 8254.8 (p = 2.6E−07) | 0.12 (p = 4.6E−03) |
Centrality analysis was conducted using the Cytoscape plug-in CentiScaPe and four centrality metrics (degree, eigenvector, closeness, and betweenness) to identify the most important nodes (i.e., genes) in the merged transcriptional network. The top 10 ranked genes in each perspective centrality metric is included in the table and indicate the most influential genes within the network. The centrality scores of each node were compared against the background distribution of centrality scores that were obtained from randomly generated 1,000 random merged networks. P-values were calculated using z-test to examine the significant difference between the real and random networks.