Skip to main content
main-content

Über dieses Buch

This interdisciplinary thesis introduces a systems biology approach to study the cell fate decision mediated by autophagy. A mathematical model of interaction between Autophagy and Apoptosis in mammalian cells is proposed. In this dynamic model autophagy acts as a gradual response to stress (Rheostat) that delays the initiation of bistable switch of apoptosis to give the cells an opportunity to survive. The author shows that his dynamical model is consistent with existing quantitative measurements of time courses of autophagic responses to cisplatin treatment. To understand the function of this response in cancer cells, he has provided a systems biology experimental framework to study quantitative and dynamical aspects of autophagy in single cancer cells using live-cell imaging and quantitative fluorescence microscopy. This framework can provide new insights on function of autophagic response in cancer cells.

Inhaltsverzeichnis

Frontmatter

Chapter 1. Introduction to Autophagy in Physiology and Pathophysiology

Abstract
In this chapter autophagy and cell death pathways in cancer are reviewed and their roles in physiology and pathophysiology are discussed. Network organization of these pathways are explained and a signalling network linking autophagy to programmed cell death is proposed.
Iman Tavassoly

Chapter 2. Mathematical Modeling of the Interplay of Autophagy and Apoptosis

Abstract
In this chapter, we have proposed a theoretical framework for analysis of dynamics of interplay of autophagy and apoptosis in mammalian cells including cancer cells. Because quantitative experimental data on time course of interplay of autophagy and apoptosis is very limited, we have used the observations of interaction of autophagy and apoptosis in different mammalian cell types to design our primary hypothesis. Using ordinary differential equations (ODEs), we have analyzed network dynamics of molecular signaling pathways controlling cell fate at crosstalk of autophagy and apoptosis. We have used time course of autophagy level and cell fates described by Periyasamy-Thandavan et al. [32] to collectively fit the parameters of the ODE system. The mathematical model presented in this chapter can be extended and by estimating more accurate parameter sets from quantitative experimental data, it can be an integrative in silico model of cell fate decision mediated by interplay of autophagy and apoptosis.
Iman Tavassoly

Chapter 3. An Experimental Framework to Study the Dynamics of Autophagic Response

Abstract
In this chapter we present an experimental quantitative framework for measuring kinetic parameters such as autophagy flux, time course of autophagic response, and stress/response dynamics in single cancer cells including endocrine-resistant breast cancer cells. Some primary data are presented in this chapter.
Iman Tavassoly

Chapter 4. Conclusions: Future Directions in Systems Biology of Autophagy

Abstract
In this chapter systems biology of cell death pathways and autophagy in cancer is discussed and based on current knowledge of signalling networks, dynamic model and quantitative data, the future directions in systems biology of autophagy and cell death pathways in cancer are explained.
Iman Tavassoly

Chapter 5. Source Code for Dynamic Model of Interplay Between Autophagy and Apoptosis

Abstract
The Matlab code for solving ODEs used for modeling autophagy and apoptosis pathways is presented in this chapter.
Iman Tavassoly
Weitere Informationen

Premium Partner

    Marktübersichten

    Die im Laufe eines Jahres in der „adhäsion“ veröffentlichten Marktübersichten helfen Anwendern verschiedenster Branchen, sich einen gezielten Überblick über Lieferantenangebote zu verschaffen. 

    Bildnachweise