Extracellular matrix modulates sensitivity of hepatocytes to fibroblastoid dedifferentiation and transforming growth factor beta-induced apoptosis

Abstract

Hepatocytes in culture are a valuable tool to investigate mechanisms involved in the response of the liver to cytokines. However, it is well established that hepatocytes cultured on monolayers of dried stiff collagen dedifferentiate, losing specialized liver functions. In this study, we show that hepatocyte dedifferentiation is a reversible consequence of a specific signaling network constellation triggered by the extracellular matrix. A dried stiff collagen activates focal adhesion kinase (FAK) via Src, leading to activation of the Akt and extracellular signal-regulated kinase (ERK) 1/2 pathways. Akt causes resistance to transforming growth factor beta (TGF-beta)-induced apoptosis by antagonizing p38, whereas ERK1/2 signaling opens the route to epithelial-mesenchymal transition (EMT). Apoptosis resistance is reversible by inhibiting Akt or Src, and EMT can be abrogated by blocking the ERK1/2 pathway. In contrast to stiff collagen, a softer collagen gel does not activate FAK, keeping the hepatocytes in a state where they remain sensitive to TGF-beta-induced apoptosis and do not undergo EMT. In this culture system, inhibition of p38 as well as overexpression of constitutively active Akt causes apoptosis resistance, whereas constitutively active Ras induces EMT. Finally, we show that matrix-induced EMT is reversible by replating cells from dried stiff to soft gel collagen. Our results demonstrate that hepatocyte dedifferentiation in vitro is an active process driven by FAK-mediated Akt and ERK1/2 signaling. This leads to similar functional and morphological alterations as observed for regenerating hepatocytes in vivo and is reversible when Akt and/or ERK1/2 signaling pathways are antagonized.

Conclusion: Hepatocytes can exist in a differentiated and a dedifferentiated state that are reversible and can be switched by manipulating the responsible key factors of the signaling network.