Dataset Information

Tissue geometry patterns epithelial-mesenchymal transition via intercellular mechanotransduction.

ABSTRACT: Epithelial-mesenchymal transition (EMT) is a phenotypic change in which epithelial cells detach from their neighbors and become motile. Whereas soluble signals such as growth factors and cytokines are responsible for stimulating EMT, here we show that gradients of mechanical stress define the spatial locations at which EMT occurs. When treated with transforming growth factor (TGF)-beta, cells at the corners and edges of square mammary epithelial sheets expressed EMT markers, whereas those in the center did not. Changing the shape of the epithelial sheet altered the spatial pattern of EMT. Traction force microscopy and finite element modeling demonstrated that EMT-permissive regions experienced the highest mechanical stress. Myocardin-related transcription factor (MRTF)-A was localized to the nuclei of cells located in high-stress regions, and inhibiting cytoskeletal tension or MRTF-A expression abrogated the spatial patterning of EMT. These data suggest a causal role for tissue geometry and endogenous mechanical stresses in the spatial patterning of EMT.

SUBMITTER: Gomez EW

PROVIDER: S-EPMC2858775 | biostudies-literature | 2010 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Tissue geometry patterns epithelial-mesenchymal transition via intercellular mechanotransduction.

Gomez Esther W EW Chen Qike K QK Gjorevski Nikolce N Nelson Celeste M CM

Journal of cellular biochemistry 20100501 1

Epithelial-mesenchymal transition (EMT) is a phenotypic change in which epithelial cells detach from their neighbors and become motile. Whereas soluble signals such as growth factors and cytokines are responsible for stimulating EMT, here we show that gradients of mechanical stress define the spatial locations at which EMT occurs. When treated with transforming growth factor (TGF)-beta, cells at the corners and edges of square mammary epithelial sheets expressed EMT markers, whereas those in the ...[more]

PMID: 20336666

Similar Datasets

Project description:(1) Background: Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with high intra-tumoral heterogeneity. The epithelial-mesenchymal transition (EMT) is one of the inducers of cancer metastasis and migration. However, the description of the EMT process in TNBC using single-cell RNA sequencing (scRNA-seq) remains unclear. (2) Methods: In this study, we analyzed 8938 cellular gene expression profiles from five TNBC patients. We first scored each malignant cell based on functional pathways to determine its EMT characteristics. Then, a pseudo-time trajectory analysis was employed to characterize the cell trajectories. Furthermore, CellChat was used to identify the cellular communications. (3) Results: We identified 888 epithelium-like and 846 mesenchyme-like malignant cells, respectively. A further pseudo-time trajectory analysis indicated the transition trends from epithelium-like to mesenchyme-like in malignant cells. To characterize the potential regulators of the EMT process, we identified 10 dysregulated transcription factors (TFs) between epithelium-like and mesenchyme-like malignant cells, in which overexpressed forkhead box protein A1 (FOXA1) was recognized as a poor prognosis marker of TNBC. Furthermore, we dissected the cell-cell communications via ligand-receptor (L-R) interactions. We observed that tumor-associated macrophages (TAMs) may support the invasion of malignant epithelial cells, based on CXCL-CXCR2 signaling. The tumor necrosis factor (TNF) signaling pathway secreted by TAMs was identified as an outgoing communication pattern, mediating the communications between monocytes/TAMs and malignant epithelial cells. Alternatively, the TNF-related ligand-receptor (L-R) pairs showed promising clinical implications. Some immunotherapy and anti-neoplastic drugs could interact with the L-R pairs as a potential strategy for the treatment of TNBC. In summary, this study enhances the understanding of the EMT process in the TNBC microenvironment, and dissections of EMT-related cell communications also provided us with potential treatment targets.

Dataset Information

Tissue geometry patterns epithelial-mesenchymal transition via intercellular mechanotransduction.

Publications

Tissue geometry patterns epithelial-mesenchymal transition via intercellular mechanotransduction.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets