{"title":"基于紫外线反应的皮肤黑色素瘤转录组学分析和分类","authors":"Dongxing Xiao, Zhaozhao Guo, Yuzhen Xiong, Xinqiang He, Chong Zhao, N. Tang","doi":"10.4103/ds.ds-d-22-00178","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":11107,"journal":{"name":"Dermatologica Sinica","volume":"40 1","pages":"103 - 110"},"PeriodicalIF":2.3000,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Transcriptomic profiling and classification of skin melanoma based on ultraviolet response\",\"authors\":\"Dongxing Xiao, Zhaozhao Guo, Yuzhen Xiong, Xinqiang He, Chong Zhao, N. Tang\",\"doi\":\"10.4103/ds.ds-d-22-00178\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":11107,\"journal\":{\"name\":\"Dermatologica Sinica\",\"volume\":\"40 1\",\"pages\":\"103 - 110\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2023-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Dermatologica Sinica\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.4103/ds.ds-d-22-00178\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"DERMATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Dermatologica Sinica","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.4103/ds.ds-d-22-00178","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"DERMATOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
背景:我们旨在探索皮肤黑色素瘤(CM)的治疗性生物标志物。目的:目的是为提高CM的总生存期(OS)提供一个新的方向。方法:从美国癌症基因组图谱(the Cancer Genome Atlas, TCGA)中获取与紫外线(UV)反应相关的基因集和CM HTSeq-FPKM数据。基因集变异分析用于计算每个样品的富集分数。采用DAVID和基因集富集分析(Gene Set Enrichment Analysis, GSEA)分析了集群1和集群2之间差异表达基因(differential expression genes, DEGs)的功能。采用ssGSEA分析样品免疫浸润程度。通过加权基因共表达网络分析(WGCNA)、蛋白-蛋白相互作用网络(PPI)和突变分析来筛选与紫外线反应相关的基因。结果:将样品分为高活性紫外响应(簇1)和低活性紫外响应(簇2)。我们发现簇2与较差的OS相关,对紫外响应的反应较高。功能分析表明,deg参与血管生成、表皮发育和炎症反应。此外,簇2具有较高的免疫浸润程度。WGCNA结果表明,MEyellow模块中的基因与紫外线反应高度相关,参与血管生成、细胞迁移和皮肤发育过程。PPI和突变分析显示COL5A1是CM的危险因素。结论:COL5A1可能是CM重要的生物标志物和潜在的治疗靶点。
Transcriptomic profiling and classification of skin melanoma based on ultraviolet response
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.
期刊介绍:
Dermatologica Sinica aims to publish high quality scientific research in the field of dermatology, with the goal of promoting and disseminating dermatological-related medical science knowledge to improve global health. Articles on clinical, laboratory, educational, and social research in dermatology and other related fields that are of interest to the medical profession are eligible for consideration. Review articles, original articles, brief reports, case reports and correspondence are accepted.