Rho-ROCK signaling regulates tumor-microenvironment interactions
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Updated: Jan 31, 2026

MAME Models for 4D Live-cell Imaging of Tumor: Microenvironment Interactions that Impact Malignant Progression
Published on: February 17, 2012
Mohammad Zahied Johan1, Michael S Samuel2,3
1Centre for Cancer Biology, SA Pathology and University of South Australia, Adelaide, South Australia, Australia.
Abstract:
Reciprocal biochemical and biophysical interactions between tumor cells, stromal cells and the extracellular matrix (ECM) result in a unique tumor microenvironment that determines disease outcome. The cellular component of the tumor microenvironment contributes to tumor growth by providing nutrients, assisting in the infiltration of immune cells and regulating the production and remodeling of the ECM. The ECM is a noncellular component of the tumor microenvironment and provides both physical and biochemical support to the tumor cells. Rho-ROCK signaling is a key regulator of actomyosin contractility and regulates cell shape, cytoskeletal arrangement and thereby cellular functions such as cell proliferation, differentiation, motility and adhesion. Rho-ROCK signaling has been shown to promote cancer cell growth, migration and invasion. However, it is becoming clear that this pathway also regulates key tumor-promoting properties of the cellular and noncellular components of the tumor microenvironment. There is accumulating evidence that Rho-ROCK signaling enhances ECM stiffness, modifies ECM composition, increases the motility of tumor-associated fibroblasts and lymphocytes and promotes trans-endothelial migration of tumor-associated lymphocytes. In this review, we briefly discuss the current state of knowledge on the role of Rho-ROCK signaling in regulating the tumor microenvironment and the implications of this knowledge for therapy, potentially via the development of selective inhibitors of the components of this pathway to permit the tuning of signaling flux, including one example with demonstrated utility in pre-clinical models.
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