越来越多的研究推测坏死相关细胞程序性死亡（necroptosis）可能是治疗癌症的一种治疗策略。然而，目前对于坏死相相关长非编码RNA（NRLs）在皮肤切除性黑色素瘤（SKCM，以下称为黑色素瘤）中的预后价值的理解仍然有限且需要进一步发展。我们的研究旨在基于NRLs构建一个黑色素瘤患者预后的模型。我们从癌症基因组图谱（TCGA）数据库获取了RNA测序和临床数据，并从基因卡（GeneCards）数据库检索了86个坏死相相关基因。通过皮尔逊相关系数鉴定与坏死相相关的长非编码RNA，并使用LASSO回归构建了黑色素瘤的预后模型。接下来，我们采用多种方法验证了该模型的准确性。根据LASSO回归的结果，将黑色素瘤患者分为高风险组和低风险组。进一步研究了风险评分与生存状况、临床病理学相关性、功能富集、免疫浸润、体细胞突变和药物敏感性之间的关系。最后，通过体外实验验证了AL162457.2对黑色素瘤增殖、侵袭和迁移的功能。预后模型包含7个NRLs（EBLN3P、AC093010.2、LINC01871、IRF2-DT、AL162457.2、AC242842.1、HLA-DQB1-AS1），并显示出很高的诊断效率。高风险组的总生存率显著低于低风险组，风险评分可以独立预测黑色素瘤的生存结果。风险组之间在免疫检查点基因表达、免疫浸润、免疫治疗反应和药物敏感性分析方面存在显著差异。一系列的细胞功能实验表明，沉默AL162457.2可以显著抑制A375细胞的增殖、侵袭和迁移。我们的预后模型可以独立预测黑色素瘤患者的生存情况，为进一步研究黑色素瘤中的坏死相提供了基础，也为黑色素瘤的临床诊断和治疗提供了新的视角。© 2023. BioMed Central Ltd., part of Springer Nature.

An increasing amount of research has speculated that necroptosis could be a therapeutic strategy for treating cancer. However, understanding the prognostic value of the necroptosis-related long non-coding RNAs (NRLs) in skin cutaneous melanoma (SKCM, hereafter referred to as melanoma) remains poor and needs to be developed. Our research aims to construct a model based on NRLs for the prognosis of patients with melanoma.We obtained the RNA-seq and clinical data from The Cancer Genome Atlas (TCGA) database and retrieved 86 necroptosis-related genes from the GeneCards database. The lncRNAs associated with necroptosis were identified via the Pearson correlation coefficient, and the prognostic model of melanoma was constructed using LASSO regression. Next, we employed multiple approaches to verify the accuracy of the model. Melanoma patients were categorized into two groups (high-risk and low-risk) according to the results of LASSO regression. The relationships between the risk score and survival status, clinicopathological correlation, functional enrichment, immune infiltration, somatic mutation, and drug sensitivity were further investigated. Finally, the functions of AL162457.2 on melanoma proliferation, invasion, and migration were validated by in vitro experiments.The prognostic model consists of seven NRLs (EBLN3P, AC093010.2, LINC01871, IRF2-DT, AL162457.2, AC242842.1, HLA-DQB1-AS1) and shows high diagnostic efficiency. Overall survival in the high-risk group was significantly lower than in the low-risk group, and risk scores could be used to predict melanoma survival outcomes independently. Significant differences were evident between risk groups regarding the expression of immune checkpoint genes, immune infiltration, immunotherapeutic response and drug sensitivity analysis. A series of functional cell assays indicated that silencing AL162457.2 significantly inhibited cell proliferation, invasion, and migration in A375 cells.Our prognostic model can independently predict the survival of melanoma patients while providing a basis for the subsequent investigation of necroptosis in melanoma and a new perspective on the clinical diagnosis and treatment of melanoma.© 2023. BioMed Central Ltd., part of Springer Nature.