Identification of novel disulfidptosis-related lncRNA signatures to predict the prognosis and immune microenvironment of skin cutaneous melanoma patients

被引:0
|
作者
Cheng, Shengrong [1 ]
Wang, Xin [2 ]
Yang, Shuhan [3 ]
Liang, Jiahui [3 ,4 ]
Song, Caiying [1 ]
Zhu, Qiuxuan [1 ]
Chen, Wendong [1 ]
Ren, Zhiyao [2 ]
Zhu, Fei [1 ]
机构
[1] Anhui Med Univ, Affiliated Hosp 1, Dept Plast Surg, Hefei 230022, Peoples R China
[2] Univ Ghent, Fac Med & Hlth Sci, B-9000 Ghent, Belgium
[3] Anhui Med Univ, Affiliated Hosp 1, Dept Gen Surg, Hefei, Peoples R China
[4] Anhui Med Univ, Affiliated Hosp 1, Dept Breast Surg, Hefei, Peoples R China
基金
中国国家自然科学基金;
关键词
disulfidptosis-related LncRNA; prognosis; risk model; skin cutaneous melanoma; tumor microenvironment;
D O I
10.1111/srt.13814
中图分类号
R75 [皮肤病学与性病学];
学科分类号
100206 ;
摘要
BackgroundSkin cutaneous melanoma (SKCM) is an aggressive form of malignant melanoma with poor prognosis and high mortality rates. Disulfidptosis is a newly discovered cell death regulatory mechanism caused by the abnormal accumulation of disulfides. This unique pathway is guiding significant new research to understand cancer progression for targeted treatment. However, the correlation between disulfidptosis with long non-coding RNAs (lncRNAs) in SKCM remains unknown at present.MethodsThe Cancer Genome Atlas database furnished lncRNA expression data and clinical information for SKCM patients. Pearson correlation and Cox regression analyses identified disulfidptosis-related lncRNAs associated with SKCM prognosis. ROC curves and a nomogram validated the model. TME, immune infiltration, GSEA analysis, immune checkpoint gene expression profiling, and drug sensitivity were assessed in high and low-risk groups. Consistent clustering categorized SKCM patients for personalized clinical treatment guidance.ResultsA total of twelve disulfidptosis-related lncRNAs were identified for the development of prognosis prediction models. The area under the curve (AUC) values of the ROC curve and the nomogram provided reliable discrimination to evaluate the prognostic potential for SKCM patients. The TME played a crucial role in tumorigenesis, progression and prognosis, and the risk scores were closely related to immune cell infiltration. Meanwhile, the combination of chemotherapy, targeted therapy, and immunotherapy was recommended for low-risk patients based on drug sensitivity and immune efficacy analyses.ConclusionWe identified a risk model of twelve disulfidptosis-related lncRNAs that could be used to predict the prognosis of SKCM patients and help guide immunotherapy and chemotherapy for personalized treatment plans.
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页数:20
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