Department of Dermatology, Xiangya Hospital, Central South University, Changsha 410000, China.
School of Computer Science, Hunan First Normal University, Changsha 410205, China.
Life Sci. 2022 Oct 15;307:120832. doi: 10.1016/j.lfs.2022.120832. Epub 2022 Aug 5.
To explore the correlation between the pyroptosis-related lncRNAs (PRlncRNAs) and the prognosis of skin cutaneous melanoma (SKCM), and clarify the effects of the PRlncRNAs on the tumor immune infiltration.
In this study, we utilized RNA-seq and clinical characteristics data obtained from TCGA and GEO database to perform co-expression analysis and LASSO Cox regression analysis to construct a 12-PRlncRNA prognostic prediction model. We also performed functional analysis, immune infiltration analysis and drug sensitivity analysis, as well as correlation analysis with autophagy/ferroptosis genes, tumor mutational burden, and PD-1/PD-L1 genes.
The model based on the 12-PRlncRNA signature could effectively predict the prognosis of SKCM. Low risk group had a higher anti-tumor immune level generally compared with high-risk group. The signature was correlated with the expression of autophagy/ferroptosis-related genes and PD1/PD-L1 genes and tumor mutational burden. Additionally, drug sensitivity analysis indicated potential therapeutic targets.
Our study demonstrated the impact of PRlncRNAs on SKCM. The model established based on the 12-PRlncRNA showed significant prognostic value for SKCM and may be instructive in pyroptosis-related targeted therapy in the clinic.
探讨与细胞焦亡相关的长非编码 RNA(PRlncRNAs)与皮肤黑色素瘤(SKCM)预后的相关性,并阐明 PRlncRNAs 对肿瘤免疫浸润的影响。
本研究利用 TCGA 和 GEO 数据库中的 RNA-seq 和临床特征数据进行共表达分析和 LASSO Cox 回归分析,构建了一个由 12 个 PRlncRNA 组成的预后预测模型。我们还进行了功能分析、免疫浸润分析和药物敏感性分析,并与自噬/铁死亡基因、肿瘤突变负担和 PD-1/PD-L1 基因进行了相关性分析。
基于 12 个 PRlncRNA 特征的模型可以有效地预测 SKCM 的预后。低风险组的抗肿瘤免疫水平普遍高于高风险组。该特征与自噬/铁死亡相关基因和 PD1/PD-L1 基因以及肿瘤突变负担的表达相关。此外,药物敏感性分析表明存在潜在的治疗靶点。
本研究表明 PRlncRNAs 对 SKCM 有影响。基于 12 个 PRlncRNA 的模型对 SKCM 具有显著的预后价值,可能对临床中与细胞焦亡相关的靶向治疗具有指导意义。