Back

Nuclear lamin A/C phosphorylation by loss of Androgen Receptor is a global determinant of cancer-associated fibroblast activation.

Ghosh, S.; Isma, J.; Mazzeo, L.; Toniolo, A.; Simon, C.; Dotto, G.-P.

2023-06-28 cancer biology
10.1101/2023.06.28.546870 bioRxiv
Show abstract

Alterations of nuclear structure and function, and associated impact on gene transcription, are a hallmark of cancer cells. Little is known of these alterations in Cancer-Associated Fibroblasts (CAFs), a key component of the tumor stroma. Here we show that loss of androgen receptor (AR), which triggers early steps of CAF activation in human dermal fibroblasts (HDFs), leads to nuclear membrane alterations and increased micronuclei formation, which are unlinked from induction of cellular senescence. Similar alterations occur in fully established CAFs, which are overcome by restored AR function. AR associates with nuclear lamin A/C and loss of AR results in a substantially increased lamin A/C nucleoplasmic redistribution. Mechanistically, AR functions as a bridge between lamin A/C with the protein phosphatase PPP1. In parallel with a decreased lamin-PPP1 association, AR loss results in a marked increase of lamin A/C phosphorylation at Ser 301, which is also a feature of CAFs. Phosphorylated lamin A/C at Ser 301 binds to the transcription promoter regulatory region of several CAF effector genes, which are upregulated due to the loss of AR. More directly, expression of a lamin A/C Ser301 phosphomimetic mutant alone is sufficient to convert normal fibroblasts into tumor-promoting CAFs of the myofibroblast subtype, without an impact on senescence. These findings highlight the pivotal role of the AR-lamin A/C-PPP1 axis and lamin A/C phosphorylation at Ser 301 in driving CAF activation.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.