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, namely reproduction, development, wound healing and tissue regeneration, require cell division. Cells switch between quiescence and proliferation states for maintaining tissue homeostasis and regeneration. The cell division process is regulated by a wide range of extracellular and intracellular cues like growth factors, stress, and reactive oxygen species (ROS). The decision to exit or enter quiescence is dysregulated in proliferative and degenerative diseases. Hence, understanding the molecular mechanisms that control the reversible transition between quiescence and proliferation is crucial. In this thesis, we study the regulatory network involved in this decision-making in normal and disease (cancers and Alzheimer’s Disease) conditions and characterize the metabolic adaptation of cancers using systems biology approach. At the restriction point (R-point), cells become irreversibly committed to the completion of the cell cycle independent of mitogen. The mechanism involving hyperphosphorylation of retinoblastoma (Rb) and activation of transcription factor E2F is linked to the R-point passage. However, stress stimuli trigger exit from the cell cycle back to the mitogen-sensitive quiescent state after Rb hyper-phosphorylation, but only until APC/C-Cdh1 inactivation. In the work presented here, we developed a mathematical model to investigate the reversible transition between quiescence and proliferation in mammalian cells with respect to mitogen and stress signals. The model integrates the current mechanistic knowledge and accounts for the recent experimental observations with cells exiting quiescence and proliferating cells. We show that Cyclin E-Cdk2 couples Rb-E2F and APC/C-Cdh1 bistable switches and temporally segregates the Rpoint and the G1/S transition. A redox-dependent mutual antagonism between APC/CCdh1 and its inhibitor Emi1 makes the inactivation of APC/C-Cdh1 bistable. We show that the levels of Cdk inhibitor (CKI) and mitogen control the reversible transition between quiescence and proliferation. Further, we propose that shifting of the mitogeninduced transcriptional program to G2-phase in proliferating cells might result in an intermediate Cdk2 activity at the mitotic exit and the immediate inactivation of APC/CCdh1. Our study builds a coherent framework and generates hypotheses that have been confirmed by experimental findings. Proliferative diseases like cancer arise due to alterations in the regulation of the cell cycle. An emerging hallmark of cancer is metabolic reprogramming, which presents opportunities for cancer diagnosis and treatment based on metabolism. A comprehensive metabolic network analysis of renal cell carcinoma (RCC) subtypes, including clear cell, papillary, and chromophobe, was performed by integrating transcriptome data with the human genome-scale metabolic model to understand the coordination of metabolic pathways in cancer cells. We identified metabolic alterations of each subtype with respect to tumor-adjacent normal samples and compared them to understand the differences between subtypes. We found that genes of amino acid metabolism and redox homeostasis are significantly altered in RCC subtypes. Chromophobe showed metabolic divergence compared to other subtypes with upregulation of genes involved in glutamine anaplerosis and aspartate biosynthesis. A difference in transcriptional regulation involving HIF1A is observed between subtypes. We identified E2F1 and FOXM1 as other major transcriptional activators of metabolic genes in RCC. These results highlight the crosstalk between metabolism and cell division. Further, the co-expression pattern of metabolic genes in each patient showed variations in metabolism within RCC subtypes. We also found that co-expression modules of each subtype have tumor stage-specific behavior, which may have clinical implications. Intriguingly, cell cycle dysregulation triggers not only proliferative diseases such as cancers but also drives degenerative diseases like Alzheimer's disease (AD). Aberrant production and aggregation of amyloid beta oligomers (Aβ) into plaques is a frequent feature of AD. However, therapeutic approaches targeting Aβ accumulation fail to reverse or inhibit disease progression. The approved cholinesterase inhibitor drugs are also mostly symptomatic treatments. During human brain development, the progenitor cells differentiate into neurons and switch to a postmitotic, resting state. However, cell cycle re-entry often precedes the loss of neurons. In this study, we developed mathematical models of multiple routes leading to cell cycle re-entry in neurons that incorporate the crosstalk between cell cycle, neuronal and apoptotic signaling mechanisms. We show that the integration of multiple feedback loops influences the severity of disease and makes the switch to pathological state irreversible. We observe that the transcriptional changes associated with this transition are also characteristics of the AD brain. We propose targeting multiple arms of the feedback loop may bring about disease-modifying effects in AD. Cell cycle re-entry during infection is also the underlying process of the adaptive immune response. Naïve T cells get activated on antigen priming and proliferate to form effector and memory cells. However, unlike other mammalian cells, these cells go through an extended lag phase followed by rapid division cycles. The cells undergo extensive metabolic reprogramming in the lag phase, which equips them for extensive clonal expansion. Some common regulators of metabolism and cell cycle coordinate cell growth with proliferation. In the final section of the work, we have developed a mathematical model to explore the crosstalk between metabolism and cell cycle in T cell activation and expansion. We demonstrate the interplay of multiple feedback loops in sustaining Myc levels for T cell activation, expansion, and metabolic reprogramming. This proposed model integrates information across literature and high throughput expression data (proteome) to provide systems-level insights. Overall, we studied the regulatory network involved in quiescence versus proliferation decision-making in physiological and pathological conditions. We present a consensus picture that bridges different experimental studies and propose hypotheses that can help in further experimentation. Since proliferation and metabolism go hand in hand, we also characterized the metabolic adaptations of cancer that showed subtype-specific changes. This thesis expands the understanding of multiple pathological states that may aid in developing clinical applications.