ArticleiScience2025
Single-cell transcriptomic landscape of keratinocyte transformation from actinic keratosis to skin carcinoma.
Article in iScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Aberrant mucin expression and keratinization distinguishing severe from mild asthma revealed by interpretable machine learning.JCI insight · 2026Article
- Single-Cell Transcriptomic Mapping of PD-L1/TLR4 Remodeling Informs Topical Immunoprevention Timing in Skin Carcinogenesis.bioRxiv : the preprint server for biology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cutaneous squamous cell carcinoma (cSCC) develops through a stepwise progression from normal skin (NS) to actinic keratosis (AK) and invasive carcinoma. To delineate the cellular and molecular events underlying this transition, we perform single-cell RNA sequencing on 65,485 cells from NS, AK, and cSCC tissues. The analysis revealed dynamic remodeling of keratinocyte, T cell, and B cell populations during disease progression. A progressively expanding
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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.