The impact of matrix stiffness on hepatic cell function, liver fibrosis, and hepatocellular carcinoma-Based on quantitative data.
Kiyoon MinSathish Kumar KaruppannanGiyoong TaePublished in: Biophysics reviews (2024)
Over the past few decades, extensive research has explored the development of supportive scaffold materials for in vitro hepatic cell culture, to effectively mimic in vivo microenvironments. It is crucial for hepatic disease modeling, drug screening, and therapeutic evaluations, considering the ethical concerns and practical challenges associated with in vivo experiments. This review offers a comprehensive perspective on hepatic cell culture using bioscaffolds by encompassing all stages of hepatic diseases-from a healthy liver to fibrosis and hepatocellular carcinoma (HCC)-with a specific focus on matrix stiffness. This review begins by providing physiological and functional overviews of the liver. Subsequently, it explores hepatic cellular behaviors dependent on matrix stiffness from previous reports. For hepatic cell activities, softer matrices showed significant advantages over stiffer ones in terms of cell proliferation, migration, and hepatic functions. Conversely, stiffer matrices induced myofibroblastic activation of hepatic stellate cells, contributing to the further progression of fibrosis. Elevated matrix stiffness also correlates with HCC by increasing proliferation, epithelial-mesenchymal transition, metastasis, and drug resistance of HCC cells. In addition, we provide quantitative information on available data to offer valuable perspectives for refining the preparation and development of matrices for hepatic tissue engineering. We also suggest directions for further research on this topic.
Keyphrases
- epithelial mesenchymal transition
- cell proliferation
- liver fibrosis
- induced apoptosis
- tissue engineering
- emergency department
- signaling pathway
- healthcare
- stem cells
- machine learning
- electronic health record
- transforming growth factor
- health information
- mesenchymal stem cells
- pi k akt
- diabetic rats
- data analysis
- social media