GREM1 is required to maintain cellular heterogeneity in pancreatic cancer.
Linxiang LanTheodore EvanHuafu LiAasia HussainE Josue RuizMay Zaw ThinRute M M FerreiraHari PsEva M RiisingYoh ZenJorge AlmagroKevin W NgPablo Soro-BarrioJessica NelsonGabriela KoifmanJoana CarvalhoEmma L NyeYulong HeChanghua ZhangAnguraj SadanandamAxel BehrensPublished in: Nature (2022)
Pancreatic ductal adenocarcinoma (PDAC) shows pronounced epithelial and mesenchymal cancer cell populations 1-4 . Cellular heterogeneity in PDAC is an important feature in disease subtype specification 3-5 , but how distinct PDAC subpopulations interact, and the molecular mechanisms that underlie PDAC cell fate decisions, are incompletely understood. Here we identify the BMP inhibitor GREM1 6,7 as a key regulator of cellular heterogeneity in pancreatic cancer in human and mouse. Grem1 inactivation in established PDAC in mice resulted in a direct conversion of epithelial into mesenchymal PDAC cells within days, suggesting that persistent GREM1 activity is required to maintain the epithelial PDAC subpopulations. By contrast, Grem1 overexpression caused an almost complete 'epithelialization' of highly mesenchymal PDAC, indicating that high GREM1 activity is sufficient to revert the mesenchymal fate of PDAC cells. Mechanistically, Grem1 was highly expressed in mesenchymal PDAC cells and inhibited the expression of the epithelial-mesenchymal transition transcription factors Snai1 (also known as Snail) and Snai2 (also known as Slug) in the epithelial cell compartment, therefore restricting epithelial-mesenchymal plasticity. Thus, constant suppression of BMP activity is essential to maintain epithelial PDAC cells, indicating that the maintenance of the cellular heterogeneity of pancreatic cancer requires continuous paracrine signalling elicited by a single soluble factor.
Keyphrases
- induced apoptosis
- epithelial mesenchymal transition
- bone marrow
- stem cells
- cell cycle arrest
- transcription factor
- single cell
- mesenchymal stem cells
- endoplasmic reticulum stress
- cell fate
- type diabetes
- machine learning
- cell death
- adipose tissue
- computed tomography
- deep learning
- metabolic syndrome
- transforming growth factor
- long non coding rna
- high fat diet induced