Systems level modeling and analysis of cell cycle and metabolic network to study proliferative diseases

Abstract

Cell division refers to the process by which cells grow, replicate their genetic material, and divide to form daughter cells. Major biological processes like reproduction, development and tissue regeneration require cell division. Cells switch between quiescence and proliferation to maintain tissue homeostasis and regeneration. The ability to exit or enter quiescence is dysregulated in proliferative and degenerative diseases. Hence, understanding the molecular mechanisms that control reversible transition between quiescence and proliferation is crucial. We adopted a deterministic modeling framework to generate novel mechanistic insights into the cell cycle control system in different physiological and pathological conditions. Metabolic adaptations and redox state contribute to cellular decision-making; metabolism supports the biosynthetic and bioenergetic demands of proliferating cells. Redox imbalance drives oxidative stress and alters the cell cycle progression. We performed genome-scale metabolic characterization of renal cell carcinoma subtypes using network-based approaches to get systems-level insights. The analysis revealed crosstalk between metabolism and cell cycle, heterogeneity in metabolism within cancer, and cancer stage-specific gene modules, which have clinical implications. We also built mathematical models of neurodegeneration that incorporate the crosstalk between cell cycle and redox-sensitive apoptotic signaling mechanism in differentiated neurons. Analysis of transcriptome data obtained from different regions of the Alzheimer s disease brain relates our models with clinical observations. Thus, the models may help in improving the understanding of diseases and development of drug treatment strategies. Overall, we developed a coherent mechanistic model of cell cycle control system in the normal and disease states by bringing together vast literature and proposing hypotheses to fill in the gaps in the literature. Many of the hypotheses have been validated later by independent research gro