Department of Orthopedics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Department of Plastic and Burns Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
BMC Cancer. 2023 Aug 14;23(1):752. doi: 10.1186/s12885-023-11246-x.
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.
越来越多的研究推测坏死性凋亡可能是治疗癌症的一种治疗策略。然而，对于皮肤黑色素瘤（SKCM，以下简称黑色素瘤）中与坏死性凋亡相关的长链非编码 RNA（NRL）的预后价值仍了解甚少，需要进一步研究。我们的研究旨在构建一个基于 NRL 的黑色素瘤患者预后模型。
我们从癌症基因组图谱（TCGA）数据库中获取 RNA-seq 和临床数据，并从基因卡片数据库中检索了 86 个与坏死性凋亡相关的基因。通过皮尔逊相关系数鉴定与坏死性凋亡相关的 lncRNAs，并使用 LASSO 回归构建黑色素瘤的预后模型。接下来，我们采用多种方法验证模型的准确性。根据 LASSO 回归的结果，将黑色素瘤患者分为两组（高风险和低风险）。进一步研究风险评分与生存状态、临床病理相关性、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。
该预后模型由 7 个 NRL（EBLN3P、AC093010.2、LINC01871、IRF2-DT、AL162457.2、AC242842.1、HLA-DQB1-AS1）组成，具有较高的诊断效率。高风险组的总生存率明显低于低风险组，风险评分可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。一系列功能细胞检测表明，沉默 AL162457.2 可显著抑制 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，为后续研究黑色素瘤中的坏死性凋亡提供了依据，为黑色素瘤的临床诊断和治疗提供了新的视角。
