A molecular portrait of epithelial-mesenchymal plasticity in prostate cancer associated with clinical outcome.
Nataly StylianouMelanie L LehmanChenwei WangAtefeh Taherian FardAnja RockstrohLadan FazliLidija JovanovicMicheal WardMartin C SadowskiAbhishek S KashyapRalph ButtyanMartin E GleaveThomas F WestbrookElizabeth D WilliamsJennifer H GunterColleen C NelsonBrett G HollierPublished in: Oncogene (2018)
The propensity of cancer cells to transition between epithelial and mesenchymal phenotypic states via the epithelial-mesenchymal transition (EMT) program can regulate metastatic processes, cancer progression, and treatment resistance. Transcriptional investigations using reversible models of EMT, revealed the mesenchymal-to-epithelial reverting transition (MErT) to be enriched in clinical samples of metastatic castrate resistant prostate cancer (mCRPC). From this enrichment, a metastasis-derived gene signature was identified that predicted more rapid cancer relapse and reduced survival across multiple human carcinoma types. Additionally, the transcriptional profile of MErT is not a simple mirror image of EMT as tumour cells retain a transcriptional "memory" following a reversible EMT. This memory was also enriched in mCRPC samples. Cumulatively, our studies reveal the transcriptional profile of epithelial-mesenchymal plasticity and highlight the unique transcriptional properties of MErT. Furthermore, our findings provide evidence to support the association of epithelial plasticity with poor clinical outcomes in multiple human carcinoma types.
Keyphrases
- epithelial mesenchymal transition
- prostate cancer
- transcription factor
- gene expression
- bone marrow
- stem cells
- endothelial cells
- transforming growth factor
- papillary thyroid
- squamous cell carcinoma
- signaling pathway
- heat shock
- small cell lung cancer
- radical prostatectomy
- induced apoptosis
- genome wide
- squamous cell
- working memory
- induced pluripotent stem cells
- single cell
- quality improvement
- copy number
- free survival
- cell death
- young adults
- quantum dots
- endoplasmic reticulum stress
- heat stress
- machine learning
- genome wide identification