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== Signaling Network-Microenvironment Crosstalk in Metastasis ==
== Signaling Network-Microenvironment Crosstalk in Metastasis ==
'''Collaboration with the Shannon Alford Lab at the University of Minnesota'''
''Erinn Dandley and Jaclyn Somadelis''<br>
''Erinn Dandley and Jaclyn Somadelis''<br>
Metastasis is the leading cause of fatality for women diagnosed with breast cancer.  While specific genetic signatures have been correlated with metastatic potential, and, in some cases, prediction of metastatic tissue site, there exists no biophysical explanation for metastatic site determination.  Increasing evidence suggests that the physicochemical factors within the extracellular milieu may regulate tumor growth, morphology, and tumor cell motility.  The overwhelmingly complex nature of the tumor microenvironment in vivo, which includes numerous extracellular matrix proteins, cell types, inflammatory chemokines, and proteolytic enzymes, presents a significant challenge in parsing the role of physicochemical cues involved in regulating metastasis.  There exists a critical need for novel in vitro experimental systems that can mimic the metastatic niche in a well-defined, controllable, and reproducible manner.  We are developing novel biomaterials to systematically measure breast cancer metastasis in response to physiologically relevant physiochemical cues.  We are employing mathematical modeling tools to both describe and predict the relationship between physicochemical cues of the metastatic site and the predetermined signaling network within metastatic breast cancer cell lines.  Within the scope of this project, we will identify components of intracellular signaling pathways involved in metastatic site preference.  These pathways could serve as checkpoints for pharmaceutical intervention, and, in the long term, control of breast cancer metastasis.
Metastasis is the leading cause of fatality for women diagnosed with breast cancer.  While specific genetic signatures have been correlated with metastatic potential, and, in some cases, prediction of metastatic tissue site, there exists no biophysical explanation for metastatic site determination.  Increasing evidence suggests that the physicochemical factors within the extracellular milieu may regulate tumor growth, morphology, and tumor cell motility.  The overwhelmingly complex nature of the tumor microenvironment in vivo, which includes numerous extracellular matrix proteins, cell types, inflammatory chemokines, and proteolytic enzymes, presents a significant challenge in parsing the role of physicochemical cues involved in regulating metastasis.  There exists a critical need for novel in vitro experimental systems that can mimic the metastatic niche in a well-defined, controllable, and reproducible manner.  We are developing novel biomaterials to systematically measure breast cancer metastasis in response to physiologically relevant physiochemical cues.  We are employing mathematical modeling tools to both describe and predict the relationship between physicochemical cues of the metastatic site and the predetermined signaling network within metastatic breast cancer cell lines.  Within the scope of this project, we will identify components of intracellular signaling pathways involved in metastatic site preference.  These pathways could serve as checkpoints for pharmaceutical intervention, and, in the long term, control of breast cancer metastasis.


[[Image:NSF_NCI.jpg|center|300px]]
[[Image:NSF_NCI.jpg|center|300px]]

Revision as of 12:02, 18 November 2010

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Matrix Physicochemical Cues as Chemotherapeutic Protective Agents in Hepatocellular Carcinoma

Thuy Nguyen
It has been widely accepted that inflammatory environments within the liver contain robust changes in matrix protein synthesis and matrix stiffness; however, it remains elusive as to whether or not alterations in these physicochemical properties of the ECM are causative in HCC cell phenotype. This is a critical question, as chemotherapies are traditionally screened in in vitro scenarios that do not contain these physiological properties. We plan to: 1) Determine the role of relevant adhesive matrix proteins in regulating the phenotype of HCC cell lines of varying pre-determined differentiated states; 2) Use engineered biomaterial platforms with tunable stiffness and adhesive ligand density alongside an FDA-approved kinase inhibitor to determine the role of these matrix physicochemical cues in protecting HCC cells from apoptosis; 3) Determine the intracellular signaling mechanism responsible for translating these matrix cues into chemotherapeutic protection. We hypothesize that the physicochemical properties of the ECM (matrix stiffness and ligand identity/density) act as cues to drive HCC signaling pathways. Intracellular signaling pathways activated from these cues may conflict with the kinase activity of the chemotherapeutic, providing a protection from apoptosis.

Inflammatory Feedback Loops in Cardiovascular

Will Herrick


Signaling Network-Microenvironment Crosstalk in Metastasis

Collaboration with the Shannon Alford Lab at the University of Minnesota

Erinn Dandley and Jaclyn Somadelis
Metastasis is the leading cause of fatality for women diagnosed with breast cancer. While specific genetic signatures have been correlated with metastatic potential, and, in some cases, prediction of metastatic tissue site, there exists no biophysical explanation for metastatic site determination. Increasing evidence suggests that the physicochemical factors within the extracellular milieu may regulate tumor growth, morphology, and tumor cell motility. The overwhelmingly complex nature of the tumor microenvironment in vivo, which includes numerous extracellular matrix proteins, cell types, inflammatory chemokines, and proteolytic enzymes, presents a significant challenge in parsing the role of physicochemical cues involved in regulating metastasis. There exists a critical need for novel in vitro experimental systems that can mimic the metastatic niche in a well-defined, controllable, and reproducible manner. We are developing novel biomaterials to systematically measure breast cancer metastasis in response to physiologically relevant physiochemical cues. We are employing mathematical modeling tools to both describe and predict the relationship between physicochemical cues of the metastatic site and the predetermined signaling network within metastatic breast cancer cell lines. Within the scope of this project, we will identify components of intracellular signaling pathways involved in metastatic site preference. These pathways could serve as checkpoints for pharmaceutical intervention, and, in the long term, control of breast cancer metastasis.