The use of pegylated interferon-α (pegIFN-α) has replaced unmodified recombinant IFN-α for the treatment of chronic viral hepatitis. While the superior antiviral efficacy of pegIFN-α is generally attributed to improved pharmacokinetic properties, the pharmacodynamic effects of pegIFN-α in the liver have not been studied. Here, we analyzed pegIFN-α–induced signaling and gene regulation in paired liver biopsies obtained prior to treatment and during the first week following pegIFN-α injection in 18 patients with chronic hepatitis C. Despite sustained high concentrations of pegIFN-α in serum, the Jak/STAT pathway was activated in hepatocytes only on the first day after pegIFN-α administration. Evaluation of liver biopsies revealed that pegIFN-α induces hundreds of genes that can be classified into four clusters based on different temporal expression profiles. In all clusters, gene transcription was mainly driven by IFN-stimulated gene factor 3 (ISGF3). Compared with conventional IFN-α therapy, pegIFN-α induced a broader spectrum of gene expression, including many genes involved in cellular immunity. IFN-induced secondary transcription factors did not result in additional waves of gene expression. Our data indicate that the superior antiviral efficacy of pegIFN-α is not the result of prolonged Jak/STAT pathway activation in hepatocytes, but rather is due to induction of additional genes that are involved in cellular immune responses.
Michael T. Dill, Zuzanna Makowska, Gaia Trincucci, Andreas J. Gruber, Julia E. Vogt, Magdalena Filipowicz, Diego Calabrese, Ilona Krol, Daryl T. Lau, Luigi Terracciano, Erik van Nimwegen, Volker Roth, Markus H. Heim
This article was first published February 24, 2014. Usage data is cumulative from November 2016 through November 2017.
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.