Shengli Clinical Medical College of Fujian Medical University, Fuzhou, 350001, Fujian, People's Republic of China.
Department of Laboratory Medicine, People's Hospital of Deyang City, Deyang, 618000, Sichuan, People's Republic of China.
Sci Rep. 2022 Jul 1;12(1):11206. doi: 10.1038/s41598-022-15373-6.
Pyroptosis is a type of programmed cell death with an intense inflammatory response. Previous studies have shown that pyroptosis plays an important role in the pathogenesis and progression of lung cancer. However, the prognostic value and drug targets of pyroptosis-related lncRNAs in lung squamous cell carcinoma (LSCC) have never been studied. In the present study, we identified 1468 pyroptosis-related lncRNAs in LSCC by performing Pearson correlation analysis between the pyroptosis-related genes and the lncRNAs from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. The whole set was divided into a training and a test set with a 1:1 ratio. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analyses were conducted to establish an 11 multilncRNA signature in the three sets. The signature divided LSCC patients into the low-risk and the high-risk groups. Kaplan-Meier analysis and receiver operating characteristic (ROC) indicated that the prognostic signature had a promising predictive capability for LSCC patients. Besides, the association of microenvironment and immunotherapy response with signature was also analyzed. Moreover, 28 potential compounds targeting signature were screened as possible drugs to treat LSCC. Finally, a nomogram model was constructed to offer the quantitative prediction and net benefit for the prognosis of LSCC patients. In conclusion, the 11 pyroptosis-related lncRNAs and their signature may be promising prognostic factors and therapeutic targets for patients with LSCC.
细胞焦亡是一种伴有强烈炎症反应的程序性细胞死亡方式。先前的研究表明,细胞焦亡在肺癌的发病机制和进展中起着重要作用。然而,细胞焦亡相关长链非编码 RNA(lncRNA)在肺鳞状细胞癌(LSCC)中的预后价值和药物靶点从未被研究过。在本研究中,我们通过对来自癌症基因组图谱(TCGA)和基因表达综合数据库(GEO)的细胞焦亡相关基因和 lncRNA 进行 Pearson 相关分析,在 LSCC 中鉴定出 1468 个细胞焦亡相关 lncRNA。整个数据集按 1:1 的比例分为训练集和测试集。我们对三个数据集进行了单变量 Cox 回归和最小绝对收缩和选择算子(LASSO)分析,以建立一个由 11 个多 lncRNA 组成的特征。该特征将 LSCC 患者分为低风险和高风险组。Kaplan-Meier 分析和接收者操作特征(ROC)曲线表明,该预后特征对 LSCC 患者具有良好的预测能力。此外,还分析了特征与微环境和免疫治疗反应的相关性。此外,还筛选了 28 种针对特征的潜在化合物作为治疗 LSCC 的候选药物。最后,构建了列线图模型,为 LSCC 患者的预后提供了定量预测和净效益。总之,这 11 个细胞焦亡相关 lncRNA 及其特征可能是 LSCC 患者有前途的预后因素和治疗靶点。