利用单细胞测序分析和大量 RNA 测序分析预测皮肤黑色素瘤预后中的坏死现象

IF 3.5 3区 医学 Q1 DERMATOLOGY
Jiaheng Xie, Pengpeng Zhang, Qikai Tang, Chenfeng Ma, Muyang Li, Min Qi
{"title":"利用单细胞测序分析和大量 RNA 测序分析预测皮肤黑色素瘤预后中的坏死现象","authors":"Jiaheng Xie,&nbsp;Pengpeng Zhang,&nbsp;Qikai Tang,&nbsp;Chenfeng Ma,&nbsp;Muyang Li,&nbsp;Min Qi","doi":"10.1111/exd.15148","DOIUrl":null,"url":null,"abstract":"<p>Cutaneous melanoma, a malignancy of melanocytes, presents a significant challenge due to its aggressive nature and rising global incidence. Despite advancements in treatment, the variability in patient responses underscores the need for further research into novel therapeutic targets, including the role of programmed cell death pathways such as necroptosis. The melanoma datasets used for analysis, GSE215120, GSE19234, GSE22153 and GSE65904, were downloaded from the GEO database. The melanoma data from TCGA were downloaded from the UCSC website. Using single-cell sequencing, we assess the heterogeneity of necroptosis in cutaneous melanoma, identifying distinct cell clusters and necroptosis-related gene expression patterns. A combination of 101 machine learning algorithms was employed to construct a necroptosis-related signature (NRS) based on key genes associated with necroptosis. The prognostic value of NRS was evaluated in four cohorts (one TCGA and three GEO cohorts), and the tumour microenvironment (TME) was analysed to understand the relationship between necroptosis, tumour mutation burden (TMB) and immune infiltration. Finally, we focused on the role of key target TSPAN10 in the prognosis, pathogenesis, immunotherapy relevance and drug sensitivity of cutaneous melanoma. Our study revealed significant heterogeneity in necroptosis among melanoma cells, with a higher prevalence in epithelial cells, myeloid cells and fibroblasts. The NRS, developed through rigorous machine learning techniques, demonstrated robust prognostic capabilities, distinguishing high-risk patients with poorer outcomes in all cohorts. Analysis of the TME showed that high NRS scores correlated with lower TMB and reduced immune cell infiltration, indicating a potential mechanism through which necroptosis influences melanoma progression. Finally, TSPAN10 has been identified as a key target for cutaneous melanoma and is highly associated with poor prognosis. The findings highlight the complex role of necroptosis in cutaneous melanoma and introduce the NRS as a novel prognostic tool with potential to guide therapeutic decisions.</p>","PeriodicalId":12243,"journal":{"name":"Experimental Dermatology","volume":"33 7","pages":""},"PeriodicalIF":3.5000,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Leveraging single-cell sequencing analysis and bulk-RNA sequencing analysis to forecast necroptosis in cutaneous melanoma prognosis\",\"authors\":\"Jiaheng Xie,&nbsp;Pengpeng Zhang,&nbsp;Qikai Tang,&nbsp;Chenfeng Ma,&nbsp;Muyang Li,&nbsp;Min Qi\",\"doi\":\"10.1111/exd.15148\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Cutaneous melanoma, a malignancy of melanocytes, presents a significant challenge due to its aggressive nature and rising global incidence. Despite advancements in treatment, the variability in patient responses underscores the need for further research into novel therapeutic targets, including the role of programmed cell death pathways such as necroptosis. The melanoma datasets used for analysis, GSE215120, GSE19234, GSE22153 and GSE65904, were downloaded from the GEO database. The melanoma data from TCGA were downloaded from the UCSC website. Using single-cell sequencing, we assess the heterogeneity of necroptosis in cutaneous melanoma, identifying distinct cell clusters and necroptosis-related gene expression patterns. A combination of 101 machine learning algorithms was employed to construct a necroptosis-related signature (NRS) based on key genes associated with necroptosis. The prognostic value of NRS was evaluated in four cohorts (one TCGA and three GEO cohorts), and the tumour microenvironment (TME) was analysed to understand the relationship between necroptosis, tumour mutation burden (TMB) and immune infiltration. Finally, we focused on the role of key target TSPAN10 in the prognosis, pathogenesis, immunotherapy relevance and drug sensitivity of cutaneous melanoma. Our study revealed significant heterogeneity in necroptosis among melanoma cells, with a higher prevalence in epithelial cells, myeloid cells and fibroblasts. The NRS, developed through rigorous machine learning techniques, demonstrated robust prognostic capabilities, distinguishing high-risk patients with poorer outcomes in all cohorts. Analysis of the TME showed that high NRS scores correlated with lower TMB and reduced immune cell infiltration, indicating a potential mechanism through which necroptosis influences melanoma progression. Finally, TSPAN10 has been identified as a key target for cutaneous melanoma and is highly associated with poor prognosis. The findings highlight the complex role of necroptosis in cutaneous melanoma and introduce the NRS as a novel prognostic tool with potential to guide therapeutic decisions.</p>\",\"PeriodicalId\":12243,\"journal\":{\"name\":\"Experimental Dermatology\",\"volume\":\"33 7\",\"pages\":\"\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-07-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Experimental Dermatology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/exd.15148\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"DERMATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Experimental Dermatology","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/exd.15148","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"DERMATOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

皮肤黑色素瘤是一种黑色素细胞恶性肿瘤,因其侵袭性强和全球发病率不断上升而成为一项重大挑战。尽管在治疗方面取得了进展,但患者反应的差异性突出表明,有必要进一步研究新的治疗靶点,包括坏死等程序性细胞死亡途径的作用。用于分析的黑色素瘤数据集 GSE215120、GSE19234、GSE22153 和 GSE65904 均从 GEO 数据库下载。TCGA的黑色素瘤数据从加州大学洛杉矶分校网站下载。通过单细胞测序,我们评估了皮肤黑色素瘤坏死的异质性,确定了不同的细胞群和坏死相关的基因表达模式。我们采用了101种机器学习算法,根据与坏死相关的关键基因构建了坏死相关特征(NRS)。我们在四个队列(一个 TCGA 队列和三个 GEO 队列)中评估了 NRS 的预后价值,并分析了肿瘤微环境(TME),以了解坏死、肿瘤突变负荷(TMB)和免疫浸润之间的关系。最后,我们重点研究了关键靶点 TSPAN10 在皮肤黑色素瘤的预后、发病机制、免疫治疗相关性和药物敏感性中的作用。我们的研究揭示了黑色素瘤细胞坏死的明显异质性,上皮细胞、髓样细胞和成纤维细胞的坏死发生率较高。通过严格的机器学习技术开发的NRS显示出强大的预后能力,在所有队列中都能区分出预后较差的高危患者。对TME的分析表明,高NRS评分与较低的TMB和较少的免疫细胞浸润相关,这表明坏死影响黑色素瘤进展的潜在机制。最后,TSPAN10已被确定为皮肤黑色素瘤的关键靶点,并与不良预后高度相关。这些研究结果突显了坏死凋亡在皮肤黑色素瘤中的复杂作用,并将 NRS 介绍为一种新型预后工具,具有指导治疗决策的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Leveraging single-cell sequencing analysis and bulk-RNA sequencing analysis to forecast necroptosis in cutaneous melanoma prognosis

Cutaneous melanoma, a malignancy of melanocytes, presents a significant challenge due to its aggressive nature and rising global incidence. Despite advancements in treatment, the variability in patient responses underscores the need for further research into novel therapeutic targets, including the role of programmed cell death pathways such as necroptosis. The melanoma datasets used for analysis, GSE215120, GSE19234, GSE22153 and GSE65904, were downloaded from the GEO database. The melanoma data from TCGA were downloaded from the UCSC website. Using single-cell sequencing, we assess the heterogeneity of necroptosis in cutaneous melanoma, identifying distinct cell clusters and necroptosis-related gene expression patterns. A combination of 101 machine learning algorithms was employed to construct a necroptosis-related signature (NRS) based on key genes associated with necroptosis. The prognostic value of NRS was evaluated in four cohorts (one TCGA and three GEO cohorts), and the tumour microenvironment (TME) was analysed to understand the relationship between necroptosis, tumour mutation burden (TMB) and immune infiltration. Finally, we focused on the role of key target TSPAN10 in the prognosis, pathogenesis, immunotherapy relevance and drug sensitivity of cutaneous melanoma. Our study revealed significant heterogeneity in necroptosis among melanoma cells, with a higher prevalence in epithelial cells, myeloid cells and fibroblasts. The NRS, developed through rigorous machine learning techniques, demonstrated robust prognostic capabilities, distinguishing high-risk patients with poorer outcomes in all cohorts. Analysis of the TME showed that high NRS scores correlated with lower TMB and reduced immune cell infiltration, indicating a potential mechanism through which necroptosis influences melanoma progression. Finally, TSPAN10 has been identified as a key target for cutaneous melanoma and is highly associated with poor prognosis. The findings highlight the complex role of necroptosis in cutaneous melanoma and introduce the NRS as a novel prognostic tool with potential to guide therapeutic decisions.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Experimental Dermatology
Experimental Dermatology 医学-皮肤病学
CiteScore
6.70
自引率
5.60%
发文量
201
审稿时长
2 months
期刊介绍: Experimental Dermatology provides a vehicle for the rapid publication of innovative and definitive reports, letters to the editor and review articles covering all aspects of experimental dermatology. Preference is given to papers of immediate importance to other investigators, either by virtue of their new methodology, experimental data or new ideas. The essential criteria for publication are clarity, experimental soundness and novelty. Letters to the editor related to published reports may also be accepted, provided that they are short and scientifically relevant to the reports mentioned, in order to provide a continuing forum for discussion. Review articles represent a state-of-the-art overview and are invited by the editors.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信