Discovery of neighborhood relationships and regulatory patterns between breast cancer and inflammatory genes based on human co-expressed regulatory network

Abstract

One of the greatest challenges is discovering the underlying regulatory mechanisms between cancer and inflammatory genes. Biological network could act as a bridge for connecting these two topics, thus network-based methods might clarify topological relationships and possible regulatory patterns between cancer and inflammatory genes. In this article, we firstly integrated data resources of gene co-expression and human transcriptional regulatory networks. Then a tumor-CRN (breast cancer co-expression regulatory network) and a normal-CRN (normal co-expression regulatory network) were constructed. After that, we calculated centrality measures and identified regulatory patterns for breast cancer and inflammatory genes in the two CRNs. As a result, we declared that these two kinds of genes tended to occupy important positions in both networks. It is interesting that in tumor-CRN, clustering coefficient of inflammatory genes was significant higher, and breast cancer and inflammatory genes had the characteristic of closer connectivity. It may be inferred that inflammatory genes trigger cancer genes in tumor state. What's more, two types of breast cancer specific motifs were found associated with inflammation accumulation and the cancer process. Furthermore, we obtained a breast specific key gene related sub-network through combining the information of centrality and motifs. In the 31 genes of sub-network, 2 genes were known breast cancer genes, 25 genes were highly associated with breast cancer, and the others were confirmed associated with carcinogenic process. Therefore, we have reasons to believe that they were possible underlying breast cancer candidate genes. Meanwhile, novel regulations between cancer and inflammatory genes were mined in cancer pathway, which was a new discovery in KEGG. In conclusion, the network-based approach offers not only clue for the complex relationship between the breast cancer and inflammation, but also provides a new perspective for inflammation and other types of cancer.