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

Table 2 Risk-active pathways identified iDRW(GMP)

Pathway ID	Pathway name	Total^a	DE genes	DM genes	DE proteins	Importance score^b
hsa04137	Mitophagy	65	10	12	3	100.00
hsa03040	Spliceosome	134	10	15	1	94.88
hsa05322	Systemic lupus erythematosus	133	24	15	0	90.26
hsa04218	Cellular senescence	160	30	27	16	87.13
hsa04974	Protein digestion and absorption	90	25	17	1	79.23
hsa04622	RIG-I-like receptor signaling pathway	70	10	5	3	79.02
hsa05145	Toxoplasmosis	113	34	11	10	78.72
hsa05120	Epithelial cell signaling in Helicobacter pylori infection	68	17	11	3	72.59
hsa04621	NOD-like receptor signaling pathway	168	30	26	6	69.23
hsa05230	Central carbon metabolism in cancer	65	12	14	8	68.91

^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), differentially methylated genes (DM genes), and differentially expressed proteins (DE proteins) are also shown (p-value of DESeq2 or t-test < 0.05)

ISSN: 1755-8794