Yan Sha, An-Qi Mao, Yuan-Jie Liu, Jie-Pin Li, Ya-Ting Gong, Dong Xiao, Jun Huang, Yan-Wei Gao, Mu-Yao Wu, Hui Shen
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Bioinformatics analysis was performed using R software and several database resources such as Metascape database, Gene Set Cancer Analysis (GSCA) database, and Cytoscape software, etc., to investigate the biological mechanisms that may be related with collagens. Immunofluorescence and immunohistochemical staining were used to validate the expression and localization of Nidogen-2 (NID2).</p><p><strong>Results: </strong>Melanoma patients can be divided into two collagen clusters. Patients with high collagen levels (C1) had a shorter survival than those with low collagen levels (C2) and were less likely to benefit from immunotherapy. We demonstrated that NID2 is a potential key factor in the collagen phenotype, is involved in fibroblast activation in melanoma, and forms a barrier to limit the proximity of CD8+ T cells to tumor cells.</p><p><strong>Conclusion: </strong>We clarified the adverse effects of collagen on melanoma patients and identified NID2 as a potential therapeutic target.</p>","PeriodicalId":56015,"journal":{"name":"Pharmacogenomics & Personalized Medicine","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/f4/b8/pgpm-16-153.PMC9994630.pdf","citationCount":"0","resultStr":"{\"title\":\"Nidogen-2 (NID2) is a Key Factor in Collagen Causing Poor Response to Immunotherapy in Melanoma.\",\"authors\":\"Yan Sha, An-Qi Mao, Yuan-Jie Liu, Jie-Pin Li, Ya-Ting Gong, Dong Xiao, Jun Huang, Yan-Wei Gao, Mu-Yao Wu, Hui Shen\",\"doi\":\"10.2147/PGPM.S399886\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The incidence of cutaneous melanoma continues to rise rapidly and has an extremely poor prognosis. 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引用次数: 0
摘要
背景:皮肤黑色素瘤的发病率持续快速上升,预后极差。免疫治疗策略是转移患者最有效的方法,但并非所有病例都成功,因为黑色素瘤对免疫检查点抑制的反应机制复杂多变。方法:从公共gene expression Omnibus (GEO)和The Cancer Genome Atlas (TCGA)数据库中合成胶原编码基因表达数据(二代和单细胞测序)。利用R软件和metscape数据库、Gene Set Cancer analysis (GSCA)数据库、Cytoscape软件等数据库资源进行生物信息学分析,探讨可能与胶原蛋白相关的生物学机制。采用免疫荧光和免疫组织化学染色验证Nidogen-2 (NID2)的表达和定位。结果:黑色素瘤患者可分为两个胶原蛋白簇。胶原蛋白水平高(C1)的患者比胶原蛋白水平低(C2)的患者生存期短,并且不太可能从免疫治疗中获益。我们证明NID2是胶原表型的潜在关键因子,参与黑色素瘤的成纤维细胞活化,并形成屏障限制CD8+ T细胞接近肿瘤细胞。结论:我们明确了胶原蛋白对黑色素瘤患者的不良影响,并确定了NID2作为潜在的治疗靶点。
Nidogen-2 (NID2) is a Key Factor in Collagen Causing Poor Response to Immunotherapy in Melanoma.
Background: The incidence of cutaneous melanoma continues to rise rapidly and has an extremely poor prognosis. Immunotherapy strategies are the most effective approach for patients who have developed metastases, but not all cases have been successful due to the complex and variable mechanisms of melanoma response to immune checkpoint inhibition.
Methods: We synthesized collagen-coding gene expression data (second-generation and single-cell sequencing) from public Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Bioinformatics analysis was performed using R software and several database resources such as Metascape database, Gene Set Cancer Analysis (GSCA) database, and Cytoscape software, etc., to investigate the biological mechanisms that may be related with collagens. Immunofluorescence and immunohistochemical staining were used to validate the expression and localization of Nidogen-2 (NID2).
Results: Melanoma patients can be divided into two collagen clusters. Patients with high collagen levels (C1) had a shorter survival than those with low collagen levels (C2) and were less likely to benefit from immunotherapy. We demonstrated that NID2 is a potential key factor in the collagen phenotype, is involved in fibroblast activation in melanoma, and forms a barrier to limit the proximity of CD8+ T cells to tumor cells.
Conclusion: We clarified the adverse effects of collagen on melanoma patients and identified NID2 as a potential therapeutic target.
期刊介绍:
Pharmacogenomics and Personalized Medicine is an international, peer-reviewed, open-access journal characterizing the influence of genotype on pharmacology leading to the development of personalized treatment programs and individualized drug selection for improved safety, efficacy and sustainability.
In particular, emphasis will be given to:
Genomic and proteomic profiling
Genetics and drug metabolism
Targeted drug identification and discovery
Optimizing drug selection & dosage based on patient''s genetic profile
Drug related morbidity & mortality intervention
Advanced disease screening and targeted therapeutic intervention
Genetic based vaccine development
Patient satisfaction and preference
Health economic evaluations
Practical and organizational issues in the development and implementation of personalized medicine programs.