Abstract
The p53-related transcription factor p63 is required for maintenance of epithelial cell differentiation. We found that activated forms of the Harvey Rat Sarcoma Virus GTPase (H-RAS) and phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) oncogenes strongly repress expression of ΔNp63α, the predominant p63 isoform in basal mammary epithelial cells. This regulation occurs at the transcriptional level, and a short region of the ΔNp63 promoter is sufficient for repression induced by H-RasV12. The suppression of ΔNp63α expression by these oncogenes concomitantly leads to an epithelial-tomesenchymal transition (EMT). In addition, the depletion of ΔNp63α alone is sufficient to induce EMT. Both H-RasV12 expression and ΔNp63α depletion induce individual cell invasion in a 3D collagen gel in vitro system, thereby demonstrating how Ras can drive the mammary epithelial cell state toward greater invasive ability. Together, these results suggest a pathway by which RAS and PIK3CA oncogenes induce EMT through regulation of ΔNp63α.
Original language | English |
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Pages (from-to) | E6107-E6116 |
Journal | Proceedings of the National Academy of Sciences of the United States of America |
Volume | 113 |
Issue number | 41 |
DOIs | |
Publication status | Published - 2016 Oct 11 |
Bibliographical note
Funding Information:We thank Drs. Ella Freulich, Yan Zhu, Wen Zhou, and members of the C.P. and R.P. laboratories for assistance and advice. We thank Dr. Scott Lowe for the pBabepuro, pBabepuro-H-RasV12, and LMP vectors and Phoenix-Ampho cells. We thank Dr. Rosalie Sears for the MCF10A-TR cells and Dr. Kumiko Ui-Tei for the E-cadherin minimal reporter. We thank Dr. Antonio Costanzo for the gift of the -3,000 ΔNp63 promoter construct. We acknowledge the Texas Advanced Computing Center at The University of Texas at Austin for providing access to the high-performance computing system Stampede and the Pittsburgh Supercomputing Center for the Blacklight system. This work was supported by NIH Grant P01 CA87497. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation Grant ACI-1053575. The XSEDE computational grant (to C.P. and K.R.) helped support data analysis carried out on the Stampede and Blacklight supercomputers.
All Science Journal Classification (ASJC) codes
- General