ArticleOncoTargets and therapy2024
Exploring Potential Biomarkers and Molecular Mechanisms of Cutaneous Squamous Cell Carcinoma Based on Bioinformatics.
Article in OncoTargets and therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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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
1 citing paper in PubMed.
- A symphony of signals: the intricate role of lncRNAs in dermatological disorders.Clinical and experimental medicine · 2025Review
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Cutaneous squamous cell carcinoma (cSCC) ranks as the second most common malignancy in clinical practice and poses a significant threat to public health due to its high malignancy. In this study, we aimed to explore potential biomarkers and molecular mechanisms of cSCC. Methods: Differentially expressed genes (DEGs) from GSE66359 and GSE117247 datasets were identified using R software. We conducted enrichment analyses and screened hub genes through protein-protein interaction (PPI) analysis and weighted gene co-expression network analysis (WGCNA). To assess the diagnostic performance of these genes, we generated ROC curves using both internal and external datasets (GSE45164) and validated the expression levels of these genes in cSCC tissues through immunohistochemistry. Subsequently, we predicted the target miRNAs and lncRNAs for hub genes using online databases and constructed competing endogenous RNA (ceRNA) networks. Results: In total, we identified 505 upregulated DEGs and 522 downregulated DEGs. Through PPI and WGCNA analyses, we identified four hub genes exhibiting robust diagnostic performance in internal and external datasets (AUC > 0.9) and selected three previously unreported genes for further analysis. Immunohistochemistry demonstrated significantly elevated CCNA2, CCNB2, and UBE2C expression in cSCC tissues compared to normal skin tissues. Finally, we constructed three ceRNA networks, namely NEAT1/H19-hsa-miR-148a-3p-CCNA2 and NEAT1-hsa-miR-140-3p-UBE2C. Conclusion: In conclusion, we have identified CCNA2, CCNB2, and UBE2C as novel biomarkers for cSCC, and the NEAT1/H19-hsa-miR-148a-3p-CCNA2 and NEAT1-hsa-miR-140-3p-UBE2C ceRNA networks may represent molecular mechanisms under-lying cSCC progression. The findings of this study offer new diagnostic and therapeutic options for cSCC patients.
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