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ORIGINAL ARTICLE
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Transcriptomic profiling and classification of skin melanoma based on ultraviolet response


1 Department of Plastic Surgery, Longgang Central Hospital of Shenzhen, Shenzhen, Guangdong, China
2 Longyuan Daguan Community Health Service Center, Shenzhen Longgang Central Hospital, Shenzhen, Guangdong, China
3 Department of Dermatology, Longgang Central Hospital, Shenzhen, Guangdong, China

Correspondence Address:
Dongxing Xiao,
Department of Plastic Surgery, Longgang Central Hospital, Shenzhen, No. 6082 Longgang Avenue, Shenzhen, Guangdong Province
China
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ds.DS-D-22-00178

Background: We aimed to explore the therapeutic biomarker for cutaneous melanoma (CM). Objectives: The objective is to provide a novel direction for improving overall survival (OS) for CM. Methods: We obtained the gene sets related to ultraviolet (UV) reaction from MsigDB database and CM HTSeq-FPKM data from The Cancer Genome Atlas (TCGA). Gene set variation analysis was used to calculate the enrichment scores in each sample. DAVID and Gene Set Enrichment Analysis (GSEA) were used to explore the function of differentially expressed genes (DEGs) between cluster 1 and cluster 2. The ssGSEA was used to analyze the degree of immune infiltration in samples. Weighted gene co-expression network analysis (WGCNA), protein–protein interaction (PPI) network, and mutation analysis were performed to screen the DEGs related to UV response. Results: The samples were divided into the high activity of UV response (cluster 1) and low activity of UV response (cluster 2). We found that cluster 2 was related to poorer OS and had a higher reaction to UV response. Function analysis indicated that the DEGs are involved in angiogenesis, epidermal development, and inflammatory reaction. Furthermore, the cluster 2 had a higher degree of immune infiltration. The results of WGCNA indicated that the genes in the MEyellow module were highly related to UV response, which is involved in the process of angiogenesis, cell migration, and skin development. PPI and mutation analysis indicated that COL5A1 was the risk factor for CM. Conclusion: COL5A1 might be an important biomarker and potential therapeutic target of CM.


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