Decoupling epithelial-mesenchymal transitions from stromal profiles by integrative expression analysis
Michael Tyler and
Itay Tirosh ()
Additional contact information
Michael Tyler: Department of Molecular Cell Biology, Weizmann Institute of Science
Itay Tirosh: Department of Molecular Cell Biology, Weizmann Institute of Science
Nature Communications, 2021, vol. 12, issue 1, 1-13
Abstract:
Abstract Epithelial-to-mesenchymal transition (EMT) is the most commonly cited mechanism for cancer metastasis, but it is difficult to distinguish from profiles of normal stromal cells in the tumour microenvironment. In this study we use published single cell RNA-seq data to directly compare mesenchymal signatures from cancer and stromal cells. Informed by these comparisons, we developed a computational framework to decouple these two sources of mesenchymal expression profiles using bulk RNA-seq datasets. This deconvolution offers the opportunity to characterise EMT across hundreds of tumours and examine its association with metastasis and other clinical features. With this approach, we find three distinct patterns of EMT, associated with squamous, gynaecological and gastrointestinal cancer types. Surprisingly, in most cancer types, EMT patterns are not associated with increased chance of metastasis, suggesting that other steps in the metastatic cascade may represent the main bottleneck. This work provides a comprehensive evaluation of EMT profiles and their functional significance across hundreds of tumours while circumventing the confounding effect of stromal cells.
Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
https://www.nature.com/articles/s41467-021-22800-1 Abstract (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-22800-1
Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/
DOI: 10.1038/s41467-021-22800-1
Access Statistics for this article
Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie
More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().