Asymmetric cell division is essential for stem cells to simultaneously generate new progeny and self- renew. An intricate regulatory network controls asymmetric division in both time and space. Impairments in this network can cause unrestrained replication, leading to dysplasia and tumorigenesis. An integrative systems biology approach is adopted to understand the mechanistic details of asymmetric cell division. Computational models and robustness analysis are combined to generate hypotheses that can be verified by experiments, and the addition of the verified hypotheses into the model will generate more insights into the system. This approach will first help study a bacterial model system, Caulobacter, using a multiscale hybrid model, where reactions are classified into categories based on their rates and regulatory functions and simulated by different numerical techniques, which is essential for modeling a system as complex as asymmetric cell division. The critical factors responsible for switching cell fate during asymmetric division will then be identified by checking the robustness of the model on different levels using a multi-tiered robustness analysis framework. To further characterize and understand the function of asymmetric localization of cell fate determinants, which are essential for causing the bifurcation of cell fates between the daughter cells, modular protein interaction domains and protein scaffolds are developed to perturb them spatially. This is the first demonstration that parts and devices designed from synthetic biology can be used to study systems biology. Colon cancer-initiating cells (CCIC) will then be studied using the same computational approach. CCIC are cancer stem cells that can self-renew and form tumors. An innovative technology enables in vitro CCIC cell lines to maintain their self-renewal and tumor formation capability. It is demonstrated for the first time that the level of the Notch signaling pathway is elevated in CCIC, the inhibition of which causes loss of asymmetry and eventually leads to apoptosis. The cell fate determinant NUMB, a notch inhibitor, is shown to asymmetrically localize during mitosis, indicating that asymmetric division plays a crucial role in cancer morphology. Using computational systems biology, signaling pathways like NOTCH and WNT, and cell fate determinants will be systematically perturbed. Based on the computational analysis of hight-throughput transcriptome changes in their downstream targets, which involves statistical analysis, clustering, utilizing bioinformatics databases and network visualization tools, a multiscale systems model will be built to help understand the CCIC asymmetric division and find novel regulatory functions. The proposed research will lead to a better understanding of cancer initiating cells in order to identify novel targets for cancer therapy. The computational and experimental techniques for the integrative systems biology approach will be readily available to the biomedical community to study other systems.

Public Health Relevance

In this proposal, an integrative approach combining multiscale modeling, robustness analysis, computational analysis of high-throughput transcriptome, and perturbation experiments will be developed to investigate the roles of polar localized cell fate determinants in asymmetric cell division. Starting from a well-established bacterial model system, the computational tools will then help study colon cancer-initiating cells, where asymmetrically localized cell fate determinants have been linked to self-renewal and tumor formation through the Notch pathway. This study can identify potential targets for future cancer therapies.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM095990-03
Application #
8536853
Study Section
Modeling and Analysis of Biological Systems Study Section (MABS)
Program Officer
Lyster, Peter
Project Start
2011-09-19
Project End
2016-08-31
Budget Start
2013-09-01
Budget End
2014-08-31
Support Year
3
Fiscal Year
2013
Total Cost
$287,678
Indirect Cost
$104,328
Name
Cornell University
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
872612445
City
Ithaca
State
NY
Country
United States
Zip Code
14850
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Bu, Pengcheng; Chen, Kai-Yuan; Lipkin, Steven M et al. (2013) Asymmetric division: a marker for cancer stem cells in early stage tumors? Oncotarget 4:950-1
Shin, Yong-Jun; Sayed, Ali H; Shen, Xiling (2012) Adaptive models for gene networks. PLoS One 7:e31657