Evidence map›Paper›PMID 40678130›Full record

ArticleFrontiers in medicine2025

A standardizable human-based psoriasis skin model for drug development.

Hanna Glasebach, Steffen Rupp, Anke Burger-Kentischer

Abstract read
In one paragraph

Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Hanna GlasebachFraunhofer Institute for Interfacial Engineering and Biotechnology IGB, Stuttgart, Germany.
Steffen RuppFraunhofer Institute for Interfacial Engineering and Biotechnology IGB, Stuttgart, Germany.
Anke Burger-KentischerFraunhofer Institute for Interfacial Engineering and Biotechnology IGB, Stuttgart, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Psoriasis is a chronic inflammatory autoimmune disease with a prevalence of 2-3% in the western population. For the development of urgently needed new therapeutic options, standardizable and human-relevant disease models are essential. The transcription factor signal transducer and activator of transcription 3 (STAT3) plays a key role in the pro-inflammatory response of psoriatic keratinocytes. In this study, we established STAT3 overexpressing human keratinocytes and combined the cells with our epidermis and immune cell supplemented full-thickness skin model to generate a novel in vitro psoriasis model. In the full-thickness skin models STAT3 overexpression by its own was sufficient to induce enhanced expression of the psoriasis marker S100A7. Both epidermal and full-thickness skin models set up from STAT3 overexpressing keratinocytes showed a stronger psoriasis-like phenotype upon pro-inflammatory stimuli such as treatment with cytokines or integration of T cells compared to skin models set-up from the wild-type keratinocyte cell line. Thus, the STAT3 overexpression in keratinocytes induced a pre-psoriatic like phenotype in untreated skin models and enhanced the sensitivity of the skin models to psoriatic stimuli. This reflects the genetic susceptibility in psoriasis patients, which is responsible for the differences between non-lesional skin in patients and healthy skin. The novel STAT3 overexpressing in vitro skin model mimics many psoriatic hallmarks, is based on well-established immortalized primary keratinocytes and highly reproducible. Therefore, we expect it to be a well-suited psoriasis model for drug screening and validation approaches in a preclinical setting.

Indexed as

in vitro skin modelnon-animal methodpsoriasisSTAT3T cells

Identifiers

PMID40678130
PMCPMC12269714

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Registered trials

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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.