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Variable asialoglycoprotein receptor 1 expression in liver disease: Implications for therapeutic intervention
Author(s) -
Witzigmann Dominik,
Quagliata Luca,
Schenk Susanne H.,
Quintavalle Cristina,
Terracciano Luigi M.,
Huwyler Jörg
Publication year - 2016
Publication title -
hepatology research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.123
H-Index - 75
eISSN - 1872-034X
pISSN - 1386-6346
DOI - 10.1111/hepr.12599
Subject(s) - asialoglycoprotein receptor , hepatocellular carcinoma , in vivo , liver cancer , tissue microarray , cancer research , downregulation and upregulation , microarray , messenger rna , receptor , in vitro , liver disease , biology , medicine , pathology , immunohistochemistry , gene expression , hepatocyte , gene , biochemistry , microbiology and biotechnology
Abstract Aim One of the most promising strategies for the treatment of liver diseases is targeted drug delivery via the asialoglycoprotein receptor (ASGPR). The success of this approach heavily depends on the ASGPR expression level on parenchymal liver cells. In this study, we assessed the mRNA and protein expression levels of the major receptor subunit, ASGR1, in hepatocytes both in vitro and in vivo . Methods In vitro , various liver cancer‐derived cell lines were evaluated. In vivo , we screened the ASGR1 mRNA on 59 hepatocellular carcinoma and matched non‐neoplastic tissue using RNA microarray. In addition, 350 human liver specimens of patients with hepatocellular carcinoma or non‐neoplastic liver diseases were screened for ASGR1 protein level using tissue microarray analysis. Results Our data reveal that the ASGR1 mRNA expression directly correlates with the protein level. We demonstrate that the ASGR1 expression is upregulated in cirrhotic specimens and is significantly decreased with increasing hepatocellular carcinoma grade. Conclusion Because the ASGR1 expression levels are variable between patients, our findings suggest that ASGPR‐based targeting strategies should be combined with ASGPR‐companion diagnostics to maximize clinical benefit.