Network-based approach to understand dynamic behaviour of Wnt signaling pathway regulatory elements in colorectal cancer

Abstract

Systems biology helps to understand the intricate biological processes through the regulatory and metabolic mechanism. Modeling and simulation are the computational approaches to encounter the physiological and disease processes by means of an artificial environment that precisely mimics the conditions inside the cell. A large proportion of colorectal cancers (CRC) display mutational inactivation of the variety of pathways and Wnt-signaling is thought to be one of the major contributors from all the pathways that show progression towards CRC. In our study, we have performed a computational analysis to envisage the role of candidate genes for the Wnt signaling pathway. Quantitative simulations have been performed for the colorectal carcinoma. In addition, network motifs detection was performed so as to decipher the role of crucial components in the pathophysiology of CRC. Based on the standard statistical parameters such as Z score, p value and significance profile candidate genes were recovered from the Wnt pathway. The proposed method revealed statistical significance of five key genes i.e. Axin, APC, β-catenin, Lef1, and Myc reflecting their importance to study disease condition. These genes could prove to be efficient markers for the disease diagnosis and also provide a way to solve the mystery behind the aberrant regulation of Wnt signaling in CRC.