Dynamic transcription factor networks in epithelial-mesenchymal transition in breast cancer models.
The epithelial-mesenchymal transition (EMT) is a complex change in cell differentiation that allows breast carcinoma cells to acquire invasive properties. EMT involves a cascade of regulatory changes that destabilize the epithelial phenotype and allow mesenchymal features to manifest. As transcripti...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2013-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC3620167?pdf=render |
| _version_ | 1818406743483351040 |
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| author | Anaar Siletz Michael Schnabel Ekaterina Kniazeva Andrew J Schumacher Seungjin Shin Jacqueline S Jeruss Lonnie D Shea |
| author_facet | Anaar Siletz Michael Schnabel Ekaterina Kniazeva Andrew J Schumacher Seungjin Shin Jacqueline S Jeruss Lonnie D Shea |
| author_sort | Anaar Siletz |
| collection | DOAJ |
| description | The epithelial-mesenchymal transition (EMT) is a complex change in cell differentiation that allows breast carcinoma cells to acquire invasive properties. EMT involves a cascade of regulatory changes that destabilize the epithelial phenotype and allow mesenchymal features to manifest. As transcription factors (TFs) are upstream effectors of the genome-wide expression changes that result in phenotypic change, understanding the sequential changes in TF activity during EMT provides rich information on the mechanism of this process. Because molecular interactions will vary as cells progress from an epithelial to a mesenchymal differentiation program, dynamic networks are needed to capture the changing context of molecular processes. In this study we applied an emerging high-throughput, dynamic TF activity array to define TF activity network changes in three cell-based models of EMT in breast cancer based on HMLE Twist ER and MCF-7 mammary epithelial cells. The TF array distinguished conserved from model-specific TF activity changes in the three models. Time-dependent data was used to identify pairs of TF activities with significant positive or negative correlation, indicative of interdependent TF activity throughout the six-day study period. Dynamic TF activity patterns were clustered into groups of TFs that change along a time course of gene expression changes and acquisition of invasive capacity. Time-dependent TF activity data was combined with prior knowledge of TF interactions to construct dynamic models of TF activity networks as epithelial cells acquire invasive characteristics. These analyses show EMT from a unique and targetable vantage and may ultimately contribute to diagnosis and therapy. |
| first_indexed | 2024-12-14T09:16:48Z |
| format | Article |
| id | doaj.art-344a221c0d14496fbe7cc500f00cc7a9 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-14T09:16:48Z |
| publishDate | 2013-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-344a221c0d14496fbe7cc500f00cc7a92022-12-21T23:08:26ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-0184e5718010.1371/journal.pone.0057180Dynamic transcription factor networks in epithelial-mesenchymal transition in breast cancer models.Anaar SiletzMichael SchnabelEkaterina KniazevaAndrew J SchumacherSeungjin ShinJacqueline S JerussLonnie D SheaThe epithelial-mesenchymal transition (EMT) is a complex change in cell differentiation that allows breast carcinoma cells to acquire invasive properties. EMT involves a cascade of regulatory changes that destabilize the epithelial phenotype and allow mesenchymal features to manifest. As transcription factors (TFs) are upstream effectors of the genome-wide expression changes that result in phenotypic change, understanding the sequential changes in TF activity during EMT provides rich information on the mechanism of this process. Because molecular interactions will vary as cells progress from an epithelial to a mesenchymal differentiation program, dynamic networks are needed to capture the changing context of molecular processes. In this study we applied an emerging high-throughput, dynamic TF activity array to define TF activity network changes in three cell-based models of EMT in breast cancer based on HMLE Twist ER and MCF-7 mammary epithelial cells. The TF array distinguished conserved from model-specific TF activity changes in the three models. Time-dependent data was used to identify pairs of TF activities with significant positive or negative correlation, indicative of interdependent TF activity throughout the six-day study period. Dynamic TF activity patterns were clustered into groups of TFs that change along a time course of gene expression changes and acquisition of invasive capacity. Time-dependent TF activity data was combined with prior knowledge of TF interactions to construct dynamic models of TF activity networks as epithelial cells acquire invasive characteristics. These analyses show EMT from a unique and targetable vantage and may ultimately contribute to diagnosis and therapy.http://europepmc.org/articles/PMC3620167?pdf=render |
| spellingShingle | Anaar Siletz Michael Schnabel Ekaterina Kniazeva Andrew J Schumacher Seungjin Shin Jacqueline S Jeruss Lonnie D Shea Dynamic transcription factor networks in epithelial-mesenchymal transition in breast cancer models. PLoS ONE |
| title | Dynamic transcription factor networks in epithelial-mesenchymal transition in breast cancer models. |
| title_full | Dynamic transcription factor networks in epithelial-mesenchymal transition in breast cancer models. |
| title_fullStr | Dynamic transcription factor networks in epithelial-mesenchymal transition in breast cancer models. |
| title_full_unstemmed | Dynamic transcription factor networks in epithelial-mesenchymal transition in breast cancer models. |
| title_short | Dynamic transcription factor networks in epithelial-mesenchymal transition in breast cancer models. |
| title_sort | dynamic transcription factor networks in epithelial mesenchymal transition in breast cancer models |
| url | http://europepmc.org/articles/PMC3620167?pdf=render |
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