Dynamics of Cell Fate Decision Mediated by the Interplay of Autophagy and Apoptosis in Cancer Cells

Mathematical Modeling and Experimental Observations
2015
ISBN: 978-3-319-14961-5
Verlag: Springer International Publishing

Buch, Englisch, 79 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 330 g

Reihe: Springer Theses

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.

Zielgruppe

Research

Autoren/Hrsg.

Tavassoly, Iman

Fachgebiete

• Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik
• Naturwissenschaften Biowissenschaften Zellbiologie
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Bioinformatik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Klinische und Innere Medizin Onkologie, Krebsforschung

Inhaltsverzeichnis

Introduction.- Mathematical Modeling of the Interplay of Autophagy and Apoptosis.- An Experimental Framework to Study the Dynamics of Autophagic Response.- Conclusions.- Source Code.

Über Autor(innen)

Iman Tavassoly (MD, PhD) is a physician-scientist working at Icahn School of Medicine at Mount Sinai and Systems Biology Center New York. His research interests include systems biology of complex diseases and cancer biology. He graduated from medical school in 2007 and received his PhD in Genetics, Bioinformatics and Computational Biology at Virginia Tech where he was awarded as the outstanding interdisciplinary program doctoral student.