Topological integration of RPPA proteomic data with multi-omics data for survival prediction in breast cancer via pathway activity inference

Table 1 Risk-active pathways identified iDRW(GP)

Pathway ID	Pathway name	Total^a	DE genes	DE proteins	Importance score^b
hsa01100	Metabolic pathways	1273	220	0	100.00
hsa04115	p53 signaling pathway	68	17	4	28.86
hsa04621	NOD-like receptor signaling pathway	168	30	6	27.44
hsa04218	Cellular senescence	160	30	16	26.07
hsa05203	Viral carcinogenesis	201	50	8	21.07
hsa04066	HIF-1 signaling pathway	100	27	11	20.75
hsa05200	Pathways in cancer	526	131	20	20.05
hsa04714	Thermogenesis	229	37	4	20.01
hsa05120	Epithelial cell signaling in Helicobacter pylori infection	68	17	3	19.19
hsa04926	Relaxin signaling pathway	130	30	9	17.97

^aTotal: the number of genes mapped to the pathway in the KEGG database
^bImportance score: the importance of a variable measured by out-of-bag (OOB) estimate and it was scaled in 0 to 100
Note that the number of differentially expressed genes (DE genes) and differentially expressed proteins (DE proteins) are also shown (p-value of DESeq2 or t-test < 0.05)

ISSN: 1755-8794