An epithelial organoid model with Langerhans cells for assessing virus-host interactions. (8th April 2019)

• Record Type: Journal Article
• Authors: Jackson, Robert; Eade, Statton; Zehbe, Ingeborg
• Is Part Of: Philosophical transactions. Volume 374:Number 1773(2019)
• Publication Date: 2019-04-08
• Subjects: human papillomavirus -- host immune surveillance -- keratinocytes and Langerhans cells -- organoids -- pathogen–host interaction -- next-generation sequencing; Biology -- Periodicals; Science -- Periodicals; 570
• DOI: 10.1098/rstb.2018.0288
• Languages: English
• ISSNs: 0962-8436

Abstract

Abstract : Persistent infection with oncogenic human papillomavirus (HPV) may lead to cancer in mucosal and skin tissue. Consequently, HPV must have developed strategies to escape host immune surveillance. Nevertheless, most HPV infections are cleared by the infected host. Our laboratory investigates Langerhans cells (LCs), acting at the interface between innate and adaptive immunity. We hypothesize that this first line of defence is vital for potential HPV elimination. As an alternative to animal models, we use smaller-scale epithelial organoids grown from human primary keratinocytes derived from various anatomical sites. This approach is amenable to large sample sizes—an essential aspect for scientific rigour and statistical power. To evaluate LCs phenotypically and molecularly during the viral life cycle and onset of carcinogenesis, we have included an engineered myeloid cell line with the ability to acquire an LC phenotype. This model is accurately tailored for the crucial time-window of early virus elimination in a complex organism and will shed more light on our long-standing research question of how naturally occurring HPV variants influence disease development. It may also be applied to other microorganism–host interaction research or enquiries of epithelium immunobiology. Finally, our continuously updated pathogen–host analysis tool enables state-of-the-art bioinformatics analyses of next-generation sequencing data. This article is part of the theme issue 'Silent cancer agents: multi-disciplinary modelling of human DNA oncoviruses'.