ArticleOncology letters2026
Identification of cancer-associated fibroblast biomarkers in cutaneous squamous cell carcinoma.
Article in Oncology letters, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
Cancer-associated fibroblasts (CAFs) are a key component of the tumor microenvironment and serve key roles in tumor progression, extracellular matrix remodeling and immune modulation. Nevertheless, no consensus has been reached thus far on biomarkers for CAFs in cutaneous squamous cell carcinoma (cSCC), a situation that hinders mechanistic research into this disease. In the present study, large-scale datasets were used to independently screen for candidate CAF biomarkers and subsequently validate their authenticity at the tissue level in cSCC specimens, including those derived from actinic keratosis (AK). Microarray datasets (GSE139505 and GSE191334) from the Gene Expression Omnibus database were analyzed to identify differentially expressed genes (DEGs) in cSCC tissues compared with normal skin tissues. These DEGs were then intersected with cSCC-associated genes retrieved from GeneCards and a set of 50 previously identified CAF marker genes. The expression of candidate genes was further validated in cSCC tissue samples and normal skin samples by immunohistochemistry. To gain further insight into the changes of these candidate genes across different stages of cSCC progression, AK samples were also incorporated during validation using multiplex immunofluorescence technology. Enrichment analysis revealed that the overlapping genes were primarily involved in the MAPK signaling pathway, PI3K-Akt signaling pathway and extracellular matrix organization. A total of five genes, melanoma cell adhesion molecule (MCAM), actin α2, smooth muscle (ACTA2), transgelin (TAGLN), platelet derived growth factor receptor β (PDGFRB) and regulator of G protein signaling 5 (RGS5), were revealed to be significantly upregulated in cSCC compared with normal skin. Among these, MCAM stood out from the cross-analysis pipeline, whereas ACTA2, TAGLN, RGS5 and
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