ArticleArchives of dermatological research2024
Identification and analysis of immune cell-related genes in cutaneous squamous cell carcinoma and drug network prediction.
Article in Archives of dermatological research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Identification and Validation of the Potential Key Biomarkers for Atopic Dermatitis Mitochondrion by Learning Algorithms.Journal of inflammation research · 2025Article
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4 authors.
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Abstract
Cutaneous squamous cell carcinoma (CSCC) is a malignant skin tumor characterized by the abnormal proliferation of keratinocytes. Immune cells have a very important role in the development of CSCC. Hence, it was vital to screen the immune cell-related biomarkers for the treatment of CSCC. Gene set variation analysis (GSVA) and immune infiltration analysis were utilised to obtain key immune cells. Weighted gene co-expression network analysis (WGCNA) was conducted to screen key module genes related to immune cell. At the same time, differential analysis was performed to find the differentially expressed genes (DEGs) between CSCC and normal samples. The candidate genes related to immune cell in CSCC patients were certificated by Venn diagram. Protein-protein interaction (PPI) network and receiver operating characteristic (ROC) curves were selected for identifying biomarkers of CSCC. We further performed immunotherapy analysis between two expression subgroups based on single gene. Following by this, the DRUGBANK database was applied to explore the interactions between biomarkers and available therapeutic agents. Finally, the expression of biomarkers was verified through real-time quantitative polymerase chain reaction (RT-qPCR). A total of 4 key immune cells (M0 macrophages, resting dendritic cells, resting mast cells, and activated mast cells) were identified. Furthermore, we obtained 982 key module genes related to immune cell. Meanwhile, 646 differentially expressed genes (DEGs) were identified. Hence, 63 candidate genes related to immune cell were selected by Venn diagram. Then, we identified six biomarkers (SLC27A2, ACOX2, PECR, CRAT, FADS1 and ELOVL5) were screened. High expression group of biomarkers showed relatively high expression of immune checkpoints. Additionally, we found 10 drugs with potential therapeutic value targeting biomarkers. Eventually, the lower expression of biomarkers in tumor group was observed, which was consistent with the result from public databases. Overall, we obtained six immune cell-related biomarkers (SLC27A2, ACOX2, PECR, CRAT, FADS1 and ELOVL5) associated with CSCC, which laid a theoretical foundation for the treatment of CSCC.
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