Comparative single-cell transcriptomes of dose and time dependent epithelial-mesenchymal spectrums.
Nicholas PanchyKazuhide WatanabeMasataka TakahashiAndrew WillemsTian HongPublished in: NAR genomics and bioinformatics (2022)
Epithelial-mesenchymal transition (EMT) is a cellular process involved in development and disease progression. Intermediate EMT states were observed in tumors and fibrotic tissues, but previous in vitro studies focused on time-dependent responses with single doses of signals; it was unclear whether single-cell transcriptomes support stable intermediates observed in diseases. Here, we performed single-cell RNA-sequencing with human mammary epithelial cells treated with multiple doses of TGF-β. We found that dose-dependent EMT harbors multiple intermediate states at nearly steady state. Comparisons of dose- and time-dependent EMT transcriptomes revealed that the dose-dependent data enable higher sensitivity to detect genes associated with EMT. We identified cell clusters unique to time-dependent EMT, reflecting cells en route to stable states. Combining dose- and time-dependent cell clusters gave rise to accurate prognosis for cancer patients. Our transcriptomic data and analyses uncover a stable EMT continuum at the single-cell resolution, and complementary information of two types of single-cell experiments.
Keyphrases
- single cell
- epithelial mesenchymal transition
- rna seq
- transforming growth factor
- high throughput
- signaling pathway
- endothelial cells
- gene expression
- stem cells
- induced apoptosis
- healthcare
- electronic health record
- oxidative stress
- high resolution
- big data
- systemic sclerosis
- mass spectrometry
- cell proliferation
- data analysis