Single-cell RNA sequencing reveals microenvironment context-specific routes for epithelial-mesenchymal transition in pancreas cancer cells.
Brooke A BrownMatthew J LazzaraPublished in: bioRxiv : the preprint server for biology (2023)
In the PDAC tumor microenvironment, multiple factors initiate the epithelial-mesenchymal transition (EMT) that occurs heterogeneously among transformed ductal cells, but it is unclear if different drivers promote EMT through common or distinct signaling pathways. Here, we use single-cell RNA sequencing (scRNA-seq) to identify the transcriptional basis for EMT in pancreas cancer cells in response to hypoxia or EMT-inducing growth factors. Using clustering and gene set enrichment analysis, we find EMT gene expression patterns that are unique to the hypoxia or growth factor conditions or that are common between them. Among the inferences from the analysis, we find that the FAT1 cell adhesion protein is enriched in epithelial cells and suppresses EMT. Further, the receptor tyrosine kinase AXL is preferentially expressed in hypoxic mesenchymal cells in a manner correlating with YAP nuclear localization, which is suppressed by FAT1 expression. AXL inhibition prevents EMT in response to hypoxia but not growth factors. Relationships between FAT1 or AXL expression with EMT were confirmed through analysis of patient tumor scRNA-seq data. Further exploration of inferences from this unique dataset will reveal additional microenvironment context-specific signaling pathways for EMT that may represent novel drug targets for PDAC combination therapies.
Keyphrases
- epithelial mesenchymal transition
- single cell
- signaling pathway
- tyrosine kinase
- rna seq
- transforming growth factor
- induced apoptosis
- gene expression
- growth factor
- adipose tissue
- pi k akt
- high throughput
- genome wide
- stem cells
- cell cycle arrest
- poor prognosis
- epidermal growth factor receptor
- dna methylation
- cell adhesion
- endothelial cells
- cell death
- binding protein
- bone marrow
- machine learning
- small molecule
- data analysis
- big data
- amino acid
- heat stress