Cellular structure and function, in healthy and diseased systems, is regulated by the interaction of cells with the underlying and surrounding three-dimensional extra-cellular matrix. These complex biochemical and biomechanical interactions, independently, are well known to regulate tumor progression, invasion and metastasis. For example, the aberrant response of cells to biochemical and biophysical stimuli in metastatic breast cancer is often initiated by engagement of the cytoskeletal machinery. As such, actin interacting proteins are found at the nexus of signaling network crosstalk between biochemical and adhesion-promoting cues. One such example is Mena, a member of the Ena/VASP family of actin regulatory proteins, which has been characterized for aberrant cell-signaling response during invasion and metastasis. However, how the altered signaling network is translated into the mechanical processes, and how are these sub-cellular mechanical processes then converted into whole cell migration in 3D environments remain largely elusive. Here, based on our preliminary data, we hypothesize that increased tumor cell invasiveness in 3D environments, is governed by coupling aberrant molecular level signaling events to molecular, macromolecular and cellular biomechanical processes. Our primary goal in this proposal is to rigorously test our hypothesis by bridging the knowledge gap between in vitro signaling studies at the molecular level, and molecular mechanical and cellular models in 3D, and test the predictions of our models through quantitative experiments in 3D environments. We plan to develop and validate our cellular models using the following three specific aims:
Aim I : Develop an integrated subcellular model of cytoskeletal viscoelasticity and intracellular signaling in native like 3D matrices.
Aim II : Develop a quantitative model of cell migration, in 3D matrices, utilizing results from the subcellular model of Aim I.
Aim III : Validate results of Aims I and II b quantifying how signaling acts cooperatively with cellular mechanics machinery and extracellular matrix properties to regulate cell migration in 3D. All three aims build upon strong preliminary data in both computation and experimental studies and will provide both fundamental insights into the coupling between mechanical and biochemical pathways and integration of information from sub-cellular structures to the cellular level. At the same time, the focus on 3D environments will create new and physiologically relevant knowledge about cellular systems in native like environments. Finally, novel platforms developed through this work will be able to test clinically relevant hypotheses and help in quantitatively understanding complex multi-scale processes during various stages of cancer progression.

Public Health Relevance

The overall goal of this project is to develop new and hypothesis driven multiscale models of cellular structure, signaling, mechanics and organization that in turn regulate cellular migration in vivo and thereby control tumor invasion and metastasis. Successful completion will have the potential to identify novel pathways and mechanisms to control breast and lung tumor development and metastasis.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01CA177799-03
Application #
8842951
Study Section
Special Emphasis Panel (ZEB1)
Program Officer
Couch, Jennifer A
Project Start
2013-04-16
Project End
2016-03-31
Budget Start
2015-04-01
Budget End
2016-03-31
Support Year
3
Fiscal Year
2015
Total Cost
Indirect Cost
Name
Boston University
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
049435266
City
Boston
State
MA
Country
United States
Zip Code
Andasari, Vivi; Lü, Dongyuan; Swat, Maciej et al. (2018) Computational model of wound healing: EGF secreted by fibroblasts promotes delayed re-epithelialization of epithelial keratinocytes. Integr Biol (Camb) 10:605-634
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Cruz, Roberto de la; Guerrero, Pilar; Spill, Fabian et al. (2016) Stochastic multi-scale models of competition within heterogeneous cellular populations: Simulation methods and mean-field analysis. J Theor Biol 407:161-183
Spill, Fabian; Weinstein, Zohar B; Irani Shemirani, Atena et al. (2016) Controlling uncertainty in aptamer selection. Proc Natl Acad Sci U S A 113:12076-12081
Sun, Meng; Spill, Fabian; Zaman, Muhammad H (2016) A Computational Model of YAP/TAZ Mechanosensing. Biophys J 110:2540-2550

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