ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2019
An epithelial organoid model with Langerhans cells for assessing virus-host interactions.
Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 13 citations in OpenAlex.
- Advances in the interrelated nature of vaginal microecology, HPV infection, and cervical lesions.Frontiers in cellular and infection microbiology · 2025Review
- Modeling Innate Antiviral Immunity in Physiological Context.Journal of molecular biology · 2022Review
- Organoids in recapitulating tumorigenesis driven by risk factors: Current trends and future perspectives.International journal of biological sciences · 2022Review
- Potential role of micro ribonucleic acids in screening for anal cancer in human papilloma virus and human immunodeficiency virus related malignancies.World journal of gastrointestinal pathophysiology · 2021Review
- The interplay between the vaginal microbiome and innate immunity in the focus of predictive, preventive, and personalized medical approach to combat HPV-induced cervical cancer.The EPMA journal · 2021Review
- The Potentials and Pitfalls of a Human Cervical Organoid Model Including Langerhans Cells.Viruses · 2020Article
- 3D Oral and Cervical Tissue Models for Studying Papillomavirus Host-Pathogen Interactions.Current protocols in microbiology · 2020Article
- Towards a multi-level and a multi-disciplinary approach to DNA oncovirus virulence.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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'.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.