bioRxivCancer Biology
NFATc acts as a non-canonical phenotypic stability factor for a hybrid epithelial/mesenchymal phenotype
A. R. Subbalakshmi, D. Kundnani, K. Biswas, A. Ghosh, S. Hanash, S. C. Tripathi, M. K. Jolly
Abstract
Metastasis remains the cause of over 90% of cancer-related deaths. Cells undergoing metastasis use phenotypic plasticity to adapt to their changing environmental conditions and avoid therapy and immune response. Reversible transitions between epithelial and mesenchymal phenotypes - Epithelial-Mesenchymal Transition (EMT) and its reverse Mesenchymal-Epithelial Transition (MET) - form a key axis of phenotypic plasticity during metastasis and therapy resistance. Recent studies have shown that the cells undergoing EMT/MET can attain one or more hybrid epithelial/mesenchymal (E/M) phenotypes, the process of which is termed as partial EMT/MET. Cells in hybrid E/M phenotype(s) can be more aggressive than those in either epithelial or mesenchymal state. Thus, it is crucial to identify the factors and regulatory networks enabling such hybrid E/M phenotypes. Here, employing an integrated computational-experimental approach, we show that the transcription factor NFATc can inhibit the process of complete EMT, thus stabilizing the hybrid E/M phenotype. It increases the range of parameters enabling the existence of a hybrid E/M phenotype, thus behaving as a phenotypic stability factor (PSF). However, unlike previously identified PSFs, it does not increase the mean residence time of the cells in hybrid E/M phenotypes, as shown by stochastic simulations; rather it enables the co-existence of epithelial, mesenchymal and hybrid E/M phenotypes and transitions among them. Clinical data suggests the effect of NFATc on patient survival in a tissue-specific or context-dependent manner. Together, our results indicate that NFATc behaves as a non-canonical phenotypic stability factor for a hybrid E/M phenotype.
- organism: human
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- approach: experimental assay
- approach: statistical model
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