Identification and analysis of immune cell-related genes in cutaneous squamous cell carcinoma and drug network prediction

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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Publication Details

Journal
Archives of Dermatological Research
Published
2024-12-30
DOI
https://doi.org/10.1007/s00403-024-03587-9
Citations
1
Primary Topic
Nonmelanoma Skin Cancer Studies
Type
article
Field-Weighted Citation Impact
0.39
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article

Identification and analysis of immune cell-related genes in cutaneous squamous cell carcinoma and drug network prediction

Baoyun Wang, Deyi Zheng, Yang Yang, Jiao Du
1 citations
Archives of Dermatological Research
Nonmelanoma Skin Cancer Studies
0.39
article

Identification and analysis of immune cell-related genes in cutaneous squamous cell carcinoma and drug network prediction

Baoyun Wang, Deyi Zheng, Yang Yang, Jiao Du
article en
1 citations

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.

Archives of Dermatological ResearchVol. 317(1)
Guizhou Provincial People's Hospital (CN)
Zero hunger
Openalex Percentile: Top 31%
Nonmelanoma Skin Cancer Studies
0.39
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