Pathway Crosstalk Network Analysis Provides Insight Into Novel Pathways in Breast Cancer

Breast cancer (BC) is one of the leading causes of cancer-related mortality among females worldwide. There is no effective treatment for it, since the molecular mechanism underlying BC still remains unclear.
The current study aimed at identifying the hub pathways for BC based on pathway crosstalk networks (PCNs), and revealing the molecular mechanisms underlying BC.
The current case-control bioinformatics analysis used the already published microarray data of BC. The current foundation-application study was performed in Moffitt cancer center, USA, in 2010. To begin with, the gene expression profile of BC (access number E-GEOD-10780), which included 185 samples (143 normal controls and 42 BC samples), was recruited from ArrayExpress database. Then, data pretreatment method was used. Next, the original pathways (OPs), original protein-protein interaction (PPI) network (OPPIN), and attract OPs (AOPs) were obtained. Then, the construction of background PCN (BPCN) and cancer PCN (CPCN) was performed, following by the degree analysis of pathways in the BPCN and CPCN to further identify hub pathways. Moreover, the cross-talks for hub pathways were extracted and termed as hub cross-talks.
There were 300 nodes and 42,293 edges in BPCN, and 283 nodes and 25,750 edges in CPCN. According to the degree results, it was found that the degree distribution of pathways for BPCN was concentrated, while that of CPCN was dispersed. Moreover, the degree of original pathways in BPCN was greater than that of the majority of AOPs in CPCN. Based on the threshold of RankProd 240, a total of 4 hub pathways including glycolysis/gluconeogenesis, Alzheimer disease, carbon metabolism, and hepatitis C virus (HCV) infection were identified.
Hub pathways such as glycolysis/gluconeogenesis and Alzheimer disease might be the potential signatures for BC therapy.