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A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds
Published on: April 6, 2016
Modeling the response of a tumor-suppressive network to mitogenic and oncogenic signals
Xinyu Tian1,2,3, Bo Huang1,2,3, Xiao-Peng Zhang4
1National Laboratory of Solid State Microstructures, Nanjing University, Nanjing 210093, China.
Abstract:
Intrinsic tumor-suppressive mechanisms protect normal cells against aberrant proliferation. Although cellular signaling pathways engaged in tumor repression have been largely identified, how they are orchestrated to fulfill their function still remains elusive. Here, we built a tumor-suppressive network model composed of three modules responsible for the regulation of cell proliferation, activation of p53, and induction of apoptosis. Numerical simulations show a rich repertoire of network dynamics when normal cells are subject to serum stimulation and adenovirus E1A overexpression. We showed that oncogenic signaling induces ARF and that ARF further promotes p53 activation to inhibit proliferation. Mitogenic signaling activates E2F activators and promotes Akt activation. p53 and E2F1 cooperate to induce apoptosis, whereas Akt phosphorylates p21 to repress caspase activation. These prosurvival and proapoptotic signals compete to dictate the cell fate of proliferation, cell-cycle arrest, or apoptosis. The cellular outcome is also impacted by the kinetic mode (ultrasensitivity or bistability) of p53. When cells are exposed to serum deprivation and recovery under fixed E1A, the shortest starvation time required for apoptosis induction depends on the terminal serum concentration, which was interpreted in terms of the dynamics of caspase-3 activation and cytochrome c release. We discovered that caspase-3 can be maintained active at high serum concentrations and that E1A overexpression sensitizes serum-starved cells to apoptosis. This work elucidates the roles of tumor repressors and prosurvival factors in tumor repression based on a dynamic network analysis and provides a framework for quantitatively exploring tumor-suppressive mechanisms.
Insights
This study models tumor suppression networks, revealing how oncogenic signals, p53 activation, and apoptosis pathways interact to control cell fate. It highlights the balance between pro-survival and pro-apoptotic signals in preventing cancer.
Area of Science:
- Systems Biology
- Cancer Research
- Molecular Biology
Background:
- Tumor-suppressive mechanisms prevent uncontrolled cell growth.
- The orchestration of these mechanisms remains poorly understood.
- Key pathways involved in tumor repression are known but their dynamic interactions are elusive.
Purpose of the Study:
- To build and analyze a dynamic network model of tumor suppression.
- To elucidate the interplay between cell proliferation, p53 activation, and apoptosis.
- To investigate how oncogenic and mitogenic signals influence cell fate decisions.
Main Methods:
- Development of a three-module tumor-suppressive network model.
- Numerical simulations of network dynamics under various stimuli (serum, E1A).
- Analysis of kinetic properties like ultrasensitivity and bistability of p53.
Main Results:
- Oncogenic signaling induces ARF, promoting p53 activation and inhibiting proliferation.
- Mitogenic signaling activates E2F and Akt; p53/E2F1 induce apoptosis, while Akt/p21 repress it.
- Cell fate (proliferation, arrest, apoptosis) depends on competing signals and p53 kinetics; E1A sensitizes cells to apoptosis.
Conclusions:
- The study elucidates the roles of tumor suppressors and prosurvival factors in a dynamic context.
- Network analysis reveals how competing signals dictate cell fate.
- Provides a quantitative framework for exploring tumor suppression and potential therapeutic targets.
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