Dynamical studies of cellular signaling networks in cancers

Abstract

Cancer, as a conundrum, is currently the biggest killer of human health. The major viewpoint of carcinogenesis is owing to somatic gene mutations. Based on such a viewpoint and the development of gene sequencing technology, extensive genomic alterations in cancer genomes have been identified. How to develop a better understanding of the link between gene mutations and carcinogenesis as well as efficient clinical cancer therapy is therefore a major challenge. Weinberg and Hanahan have suggested 10 hallmarks of cancer. The hallmarks are highly regulated by the corresponding signaling pathways. Thus, cancer itself is also a disease of dysfunction of signal transduction pathways related to multiple fundamental cell processes, including proliferation, differentiation, apoptosis, invasion and so on. Despite the signaling pathways are extremely complex in cancer cells, one can still focus on the signaling networks that govern the corresponding cell processes for modeling to discuss its dynamics and regulation functions quantitatively. Systems biology provides appropriate approach to integrate the experimental data (clinical data) and signaling pathway for a comprehensive analysis, resulting in a further prediction for optimal therapy and drug discovery. In this paper, we review the recent progress of dynamical modeling of signaling networks by using systems biology approaches that help to exploring the mechanisms of carcinogenesis. We first discuss the motif dynamics of the signaling networks. The presented generic circuit model can be decomposed into two loops and the circuit can achieve tristability through four kinds of bifurcation scenarios when parameter values are varied in a wide range. Then, we show the relative well-studied core signaling networks that regulate the cell survival, apoptosis, proliferation, invasion and energy metabolism processes. For each fundamental cell process, we individually review the dynamics of corresponding signaling network based on the systems biology approaches, including the NF-B signaling pathway that regulates the cell survival process, the Ras signaling pathway that governs the cell proliferation process, the EMT and mitochondrial signaling pathway that modulate the cell invasion and apoptosis processes. Furthermore, two coupled signaling networks, i.e., the p53 and TNF- signaling networks are discussed. Lastly, we review the breast cancer and gastric cancer signaling networks which contain several fundamental cell processes. The potential contribution for cancer treatment is also suggested. These dynamical modeling based on the core signaling networks can facilitate the understanding of the mechanisms of carcinogenesis and provide us the possible clues and ideas of the cancer treatment and drug design. We believe more exciting research works in this field will be stimulated in the near future.