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Regulation of epithelial-mesenchymal transition in breast cancer cells by cell contact and adhesion.

Cichon MA, Nelson CM, Radisky DC - Cancer Inform (2015)

Bottom Line: We show here that EMT-related processes are linked to a broad and conserved program of transcriptional alterations that are influenced by cell contact and adhesion.We further find that treatment of cells with matrix metalloproteinase-3 (MMP-3), an inducer of EMT, interrupts a defined subset of cell contact-regulated genes, including genes encoding a variety of RNA splicing proteins known to regulate the expression of Rac1b, an activated splice isoform of Rac1 known to be a key mediator of MMP-3-induced EMT in breast, lung, and pancreas.These results provide new insights into how MMPs act in cancer progression and how loss of cell-cell interactions is a key step in the earliest stages of cancer development.

View Article: PubMed Central - PubMed

Affiliation: Department of Cancer Biology, Mayo Clinic Cancer Center, Jacksonville, FL USA.

ABSTRACT
Epithelial-mesenchymal transition (EMT) is a physiological program that is activated during cancer cell invasion and metastasis. We show here that EMT-related processes are linked to a broad and conserved program of transcriptional alterations that are influenced by cell contact and adhesion. Using cultured human breast cancer and mouse mammary epithelial cells, we find that reduced cell density, conditions under which cell contact is reduced, leads to reduced expression of genes associated with mammary epithelial cell differentiation and increased expression of genes associated with breast cancer. We further find that treatment of cells with matrix metalloproteinase-3 (MMP-3), an inducer of EMT, interrupts a defined subset of cell contact-regulated genes, including genes encoding a variety of RNA splicing proteins known to regulate the expression of Rac1b, an activated splice isoform of Rac1 known to be a key mediator of MMP-3-induced EMT in breast, lung, and pancreas. These results provide new insights into how MMPs act in cancer progression and how loss of cell-cell interactions is a key step in the earliest stages of cancer development.

No MeSH data available.


Related in: MedlinePlus

Clustering of genes differentially regulated by density and by MMP-3 treatment in SCp2 cells. (A–H) Differentially expressed genes (n = 7056) in the SCp2 dataset were identified as FC > 2 in any of 50K control vs 50K MMP-3, 250K control vs 250K MMP-3, or 50K control vs 250K control. K-means clustering was performed on the SCp2 differentially regulated gene set using eight groups, Pearson-centered similarity measure, and 1000 iterations. The eight-derived clusters could be generally identified as genes upregulated by density and downregulated by MMP-3 (n = 626; A), genes downregulated by density and upregulated by MMP-3 (n = 806; B), genes upregulated by density and little affected by MMP-3 (n = 517; C), genes downregulated by density and little affected by MMP-3 (n = 801; D), genes upregulated by MMP-3 and little affected by density (n = 923; E), genes downregulated by MMP-3 and little affected by density (n = 572; F), genes upregulated by density in the absence of MMP-3 and unregulated by density in the presence of MMP-3 (n = 1528; G), and genes downregulated by density in the absence of MMP-3 and unregulated by density in the presence of MMP-3 (n = 1283; H). For each cluster, the associated genes are shown as a line graph (left panel) and as a box-and-whisker plot (center panel), and expression data for a representative gene from each cluster are shown in the right panel (boxes indicate variation in replicated experiments for 50K, 100K, and 250K).
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f4-cin-suppl.3-2015-001: Clustering of genes differentially regulated by density and by MMP-3 treatment in SCp2 cells. (A–H) Differentially expressed genes (n = 7056) in the SCp2 dataset were identified as FC > 2 in any of 50K control vs 50K MMP-3, 250K control vs 250K MMP-3, or 50K control vs 250K control. K-means clustering was performed on the SCp2 differentially regulated gene set using eight groups, Pearson-centered similarity measure, and 1000 iterations. The eight-derived clusters could be generally identified as genes upregulated by density and downregulated by MMP-3 (n = 626; A), genes downregulated by density and upregulated by MMP-3 (n = 806; B), genes upregulated by density and little affected by MMP-3 (n = 517; C), genes downregulated by density and little affected by MMP-3 (n = 801; D), genes upregulated by MMP-3 and little affected by density (n = 923; E), genes downregulated by MMP-3 and little affected by density (n = 572; F), genes upregulated by density in the absence of MMP-3 and unregulated by density in the presence of MMP-3 (n = 1528; G), and genes downregulated by density in the absence of MMP-3 and unregulated by density in the presence of MMP-3 (n = 1283; H). For each cluster, the associated genes are shown as a line graph (left panel) and as a box-and-whisker plot (center panel), and expression data for a representative gene from each cluster are shown in the right panel (boxes indicate variation in replicated experiments for 50K, 100K, and 250K).

Mentions: To dissect the differential effects of cell density and external stimuli on induction of EMT, we cultured SCp2 mouse mammary epithelial cells at differing densities with MMP-3 (Fig. 3). Because MMP-3-induced EMT requires cell spreading,25 we selected a range of cell densities that would allow for sufficient cell spreading at even the highest seeding density (Fig. 3). Evaluation of transcriptional profiles identified 7056 genes that were more than two-fold differentially expressed in response to MMP-3 (50K control vs 50K MMP-3 and 250K control vs 250K MMP-3) or in response to cell density (250K control vs 50K control). To begin to dissect the differential signaling pathways activated in response to cell density and MMP-3, transcriptional profiles of these differentially expressed genes were clustered using a K-means algorithm into eight groups (Fig. 4). We initially assessed K-means classification into 2, 4, 8, and 12 clusters. One of the endpoints we wished to pursue was the meta-analysis using NextBio, and we found that the classification into eight groups provided the most manageable number of genes for analysis using this utility. In the first two groups (Fig. 4A and B), genes showed regulation by both cell density and by MMP-3. These groups were enriched with genes associated with cell–cell and cell–ECM adhesion and interaction (Table 1, Supplementary Tables 1–3), including the gene encoding C/EBPβ, a key regulator of epithelial cell differentiation and proliferation in mammary branching morphogenesis74,75 and in the morphogenic response to epimorphin in mammary epithelial cells,76–80 as well as the gene encoding the connective tissue growth factor (CTGF), a key regulator of EMT and a mediator of the earliest stages of breast cancer development.81–83 In the second two groups (Fig. 4C and D), gene expression differences were primarily associated with cell density and less affected by the presence or absence of MMP-3. These groups were enriched with genes associated with cellular biogenesis and metabolic processes (Table 1, Supplementary Tables 1–3), including the gene encoding RAB40B, which trafficks MMPs to the invadopodia during breast cancer cell invasion, and the gene encoding SERPINB2/PAI2, which regulates cellular interactions with the ECM.84,85 The third set of gene expression groups included genes that were primarily regulated by MMP-3 (Fig. 4E and F). These groups were enriched with genes associated with cell division and organization (Table 1, Supplementary Tables 1–3), including genes known to be regulated by MMP-3.35 Comparison of the set of genes regulated by density in MCF10A cells showed significant overlap with subgroups A–F, with expected directionality of correlation: positive for clusters A–D and negative for clusters E and F (Supplementary Fig. 2). No significant overlap was found between the genes regulated by density in MCF10A cells and clusters G and H (data not shown).


Regulation of epithelial-mesenchymal transition in breast cancer cells by cell contact and adhesion.

Cichon MA, Nelson CM, Radisky DC - Cancer Inform (2015)

Clustering of genes differentially regulated by density and by MMP-3 treatment in SCp2 cells. (A–H) Differentially expressed genes (n = 7056) in the SCp2 dataset were identified as FC > 2 in any of 50K control vs 50K MMP-3, 250K control vs 250K MMP-3, or 50K control vs 250K control. K-means clustering was performed on the SCp2 differentially regulated gene set using eight groups, Pearson-centered similarity measure, and 1000 iterations. The eight-derived clusters could be generally identified as genes upregulated by density and downregulated by MMP-3 (n = 626; A), genes downregulated by density and upregulated by MMP-3 (n = 806; B), genes upregulated by density and little affected by MMP-3 (n = 517; C), genes downregulated by density and little affected by MMP-3 (n = 801; D), genes upregulated by MMP-3 and little affected by density (n = 923; E), genes downregulated by MMP-3 and little affected by density (n = 572; F), genes upregulated by density in the absence of MMP-3 and unregulated by density in the presence of MMP-3 (n = 1528; G), and genes downregulated by density in the absence of MMP-3 and unregulated by density in the presence of MMP-3 (n = 1283; H). For each cluster, the associated genes are shown as a line graph (left panel) and as a box-and-whisker plot (center panel), and expression data for a representative gene from each cluster are shown in the right panel (boxes indicate variation in replicated experiments for 50K, 100K, and 250K).
© Copyright Policy - open-access
Related In: Results  -  Collection

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f4-cin-suppl.3-2015-001: Clustering of genes differentially regulated by density and by MMP-3 treatment in SCp2 cells. (A–H) Differentially expressed genes (n = 7056) in the SCp2 dataset were identified as FC > 2 in any of 50K control vs 50K MMP-3, 250K control vs 250K MMP-3, or 50K control vs 250K control. K-means clustering was performed on the SCp2 differentially regulated gene set using eight groups, Pearson-centered similarity measure, and 1000 iterations. The eight-derived clusters could be generally identified as genes upregulated by density and downregulated by MMP-3 (n = 626; A), genes downregulated by density and upregulated by MMP-3 (n = 806; B), genes upregulated by density and little affected by MMP-3 (n = 517; C), genes downregulated by density and little affected by MMP-3 (n = 801; D), genes upregulated by MMP-3 and little affected by density (n = 923; E), genes downregulated by MMP-3 and little affected by density (n = 572; F), genes upregulated by density in the absence of MMP-3 and unregulated by density in the presence of MMP-3 (n = 1528; G), and genes downregulated by density in the absence of MMP-3 and unregulated by density in the presence of MMP-3 (n = 1283; H). For each cluster, the associated genes are shown as a line graph (left panel) and as a box-and-whisker plot (center panel), and expression data for a representative gene from each cluster are shown in the right panel (boxes indicate variation in replicated experiments for 50K, 100K, and 250K).
Mentions: To dissect the differential effects of cell density and external stimuli on induction of EMT, we cultured SCp2 mouse mammary epithelial cells at differing densities with MMP-3 (Fig. 3). Because MMP-3-induced EMT requires cell spreading,25 we selected a range of cell densities that would allow for sufficient cell spreading at even the highest seeding density (Fig. 3). Evaluation of transcriptional profiles identified 7056 genes that were more than two-fold differentially expressed in response to MMP-3 (50K control vs 50K MMP-3 and 250K control vs 250K MMP-3) or in response to cell density (250K control vs 50K control). To begin to dissect the differential signaling pathways activated in response to cell density and MMP-3, transcriptional profiles of these differentially expressed genes were clustered using a K-means algorithm into eight groups (Fig. 4). We initially assessed K-means classification into 2, 4, 8, and 12 clusters. One of the endpoints we wished to pursue was the meta-analysis using NextBio, and we found that the classification into eight groups provided the most manageable number of genes for analysis using this utility. In the first two groups (Fig. 4A and B), genes showed regulation by both cell density and by MMP-3. These groups were enriched with genes associated with cell–cell and cell–ECM adhesion and interaction (Table 1, Supplementary Tables 1–3), including the gene encoding C/EBPβ, a key regulator of epithelial cell differentiation and proliferation in mammary branching morphogenesis74,75 and in the morphogenic response to epimorphin in mammary epithelial cells,76–80 as well as the gene encoding the connective tissue growth factor (CTGF), a key regulator of EMT and a mediator of the earliest stages of breast cancer development.81–83 In the second two groups (Fig. 4C and D), gene expression differences were primarily associated with cell density and less affected by the presence or absence of MMP-3. These groups were enriched with genes associated with cellular biogenesis and metabolic processes (Table 1, Supplementary Tables 1–3), including the gene encoding RAB40B, which trafficks MMPs to the invadopodia during breast cancer cell invasion, and the gene encoding SERPINB2/PAI2, which regulates cellular interactions with the ECM.84,85 The third set of gene expression groups included genes that were primarily regulated by MMP-3 (Fig. 4E and F). These groups were enriched with genes associated with cell division and organization (Table 1, Supplementary Tables 1–3), including genes known to be regulated by MMP-3.35 Comparison of the set of genes regulated by density in MCF10A cells showed significant overlap with subgroups A–F, with expected directionality of correlation: positive for clusters A–D and negative for clusters E and F (Supplementary Fig. 2). No significant overlap was found between the genes regulated by density in MCF10A cells and clusters G and H (data not shown).

Bottom Line: We show here that EMT-related processes are linked to a broad and conserved program of transcriptional alterations that are influenced by cell contact and adhesion.We further find that treatment of cells with matrix metalloproteinase-3 (MMP-3), an inducer of EMT, interrupts a defined subset of cell contact-regulated genes, including genes encoding a variety of RNA splicing proteins known to regulate the expression of Rac1b, an activated splice isoform of Rac1 known to be a key mediator of MMP-3-induced EMT in breast, lung, and pancreas.These results provide new insights into how MMPs act in cancer progression and how loss of cell-cell interactions is a key step in the earliest stages of cancer development.

View Article: PubMed Central - PubMed

Affiliation: Department of Cancer Biology, Mayo Clinic Cancer Center, Jacksonville, FL USA.

ABSTRACT
Epithelial-mesenchymal transition (EMT) is a physiological program that is activated during cancer cell invasion and metastasis. We show here that EMT-related processes are linked to a broad and conserved program of transcriptional alterations that are influenced by cell contact and adhesion. Using cultured human breast cancer and mouse mammary epithelial cells, we find that reduced cell density, conditions under which cell contact is reduced, leads to reduced expression of genes associated with mammary epithelial cell differentiation and increased expression of genes associated with breast cancer. We further find that treatment of cells with matrix metalloproteinase-3 (MMP-3), an inducer of EMT, interrupts a defined subset of cell contact-regulated genes, including genes encoding a variety of RNA splicing proteins known to regulate the expression of Rac1b, an activated splice isoform of Rac1 known to be a key mediator of MMP-3-induced EMT in breast, lung, and pancreas. These results provide new insights into how MMPs act in cancer progression and how loss of cell-cell interactions is a key step in the earliest stages of cancer development.

No MeSH data available.


Related in: MedlinePlus