Activation of hepatic stem cells compartment during hepatocarcinogenesis in a HBsAg HBV-transgenic mouse model.
Beatrice AnfusoKorri E El-KhobarSusan I IeClaudio AvelliniOriano RadilloAlan RaseniClaudio TiribelliCaecilia H C SukowatiPublished in: Scientific reports (2018)
Chronic infection of Hepatitis B Virus (HBV) is one of the highest risk factors of hepatocellular carcinoma (HCC). The accumulation of HBV surface antigen (HBsAg) into hepatocytes induces inflammation and oxidative stress, impairing their replicative ability and allowing the activation of the hepatic stem cells (SC) compartment. This study aimed to understand the involvement of SC during hepatocarcinogenesis in HBsAg-related liver damage, from early injury until HCC. HBsAg-transgenic (TG) and wild type (WT) mouse were followed at several stages of the liver damage: inflammation, early hepatocytes damage, dysplasia, and HCC. Serum transaminases, liver histology, and diagnostic data were collected. The expressions of SC and cancer stem cells (CSC) markers was analyzed by RT-qPCR, immunohistochemistry and Western blot. Starting from 3 months, TG animals showed a progressive liver damage characterized by transaminases increase. The up-regulations of SCs markers Cd34 and Sca-1 started from the beginning of the inflammatory stage while progressive increase of Krt19 and Sox9 and CSCs markers Epcam and Cd133 from early hepatic injury. The expressions of Cd133, Cd34, and Afp were significantly higher in HCC compared to paired non-HCC tissue, in contrast to Epcam and Krt19. Western blot and IHC confirmed the positivity of Cd34 and Cd133 in small cells subpopulation.
Keyphrases
- hepatitis b virus
- oxidative stress
- stem cells
- induced apoptosis
- cancer stem cells
- liver failure
- risk factors
- diabetic rats
- dna damage
- mouse model
- multiple sclerosis
- ischemia reperfusion injury
- wild type
- nk cells
- south africa
- cell therapy
- mesenchymal stem cells
- liver injury
- big data
- machine learning
- drug induced
- cell adhesion
- transcription factor
- magnetic resonance imaging
- electronic health record
- cell proliferation
- deep learning
- artificial intelligence
- heat shock