Table4_m6A-Related lncRNAs Are Potential Biomarkers for the Prognosis of Metastatic Skin Cutaneous Melanoma.XLSX

Background: The incidence of skin cutaneous melanoma (SKCM) has risen more rapidly than any other solid tumor in the past few decades. The median survival for metastatic melanoma is only six to nine months and the 5°years survival rate of patients with conventional therapy is less than 5%. Our aim was to reveal the potential molecular mechanism in m6A modification of lncRNA and provide candidate prognostic biomarkers for metastatic SKCM.
Methods: lncRNAs expression level was obtained by re-annotation in TCGA and CCLE datasets. m6A-related lncRNAs were selected though correlation analysis. Univariate cox regression analysis was used to screen out independent prognostic factors. LASSO Cox regression was performed to construct an m6A-related lncRNA model (m6A-LncM). Univariate survival analysis and ROC curve were used to assess the prognostic efficacy of this model and candidate lncRNAs. Enrichment analysis was used to explore the candidate genes’ functions.
Results: We obtained 1,086 common m6A-related lncRNAs after Pearson correlation analysis in both two datasets. 130 out of the 1,086 lncRNAs are independent prognostic factors. 24 crucial lncRNAs were filtered after LASSO Cox regression analysis. All the m6A-LncM and the 24 lncRNAs were related to overall survival. Stratified survival analysis of m6A-LncM showed that the model retains its prognostic efficacy in recurrence, radiation therapy and other subgroups. Enrichment analysis also found that these lncRNAs were immune associated.
Conclusion: Here, we obtained 24 crucial lncRNAs that may be potential biomarkers to predict survival of metastatic SKCM and may provide a new insight to improve the prognosis of it.

背景：近数十年来，皮肤黑色素瘤（skin cutaneous melanoma, SKCM）的发病率增长速度超过其他所有实体瘤。转移性黑色素瘤患者的中位生存期仅为6至9个月，接受常规治疗的患者5年生存率不足5%。本研究旨在揭示长链非编码RNA（long non-coding RNA, lncRNA）的m6A修饰潜在分子机制，并为转移性皮肤黑色素瘤提供潜在的预后生物标志物。
方法：通过对TCGA与CCLE数据集进行重新注释，获取lncRNA的表达水平。通过相关性分析筛选与m6A修饰相关的lncRNA。采用单变量Cox回归分析筛选独立预后因素。通过LASSO Cox回归构建m6A相关lncRNA模型（m6A-LncM）。使用单变量生存分析与ROC曲线评估该模型及候选lncRNA的预后效能。采用富集分析探究候选基因的功能。
结果：在两个数据集的Pearson相关分析后，共获得1086个共有的m6A相关lncRNA。其中130个lncRNA为独立预后因素。经LASSO Cox回归分析后筛选出24个关键lncRNA。m6A-LncM模型与这24个lncRNA均与总生存期相关。对m6A-LncM进行分层生存分析显示，该模型在复发、放疗等亚组中仍具有预后效能。富集分析还发现这些lncRNA与免疫相关。
结论：本研究筛选出的24个关键lncRNA或可作为预测转移性皮肤黑色素瘤患者生存期的潜在生物标志物，为改善该疾病的预后提供新的研究思路。