DataSheet_1_Pyroptosis-Related LncRNA Signatures Correlate With Lung Adenocarcinoma Prognosis.docx

BackgroundPyroptosis is a new type of programmed cell death, accompanied by an intense inflammatory response. Previous studies have shown that pyroptosis can modify long-chain non-coding RNA (lncRNA), thereby affecting the occurrence and progression of tumors. However, the underlying role of pyroptosis-related lncRNA in lung adenocarcinoma (LUAD) remains to be elucidated. Therefore, the purpose of our study was to evaluate the prognostic value of pyrolysis-related lncRNA in patients with LUAD.
MethodsA total of 454 LUAD samples were downloaded from The Cancer Genome Atlas (TCGA) database. Pearson’s correlation coefficient was used to identify the pyroptosis-related lncRNAs. Unsupervised consensus clustering was used to identify the various LUAD molecular subtypes. A least absolute shrinkage and selection operator (LASSO) analysis was conducted to construct a prognostic signature.
ResultsAn 11-lncRNA prognostic signature out of 19 identified pyroptosis-related prognostic lncRNAs was constructed. The patients with LUAD were divided into low-risk and high-risk groups. Patients in the high-risk group had higher score values and mortality. The immune score, stromal score, and estimate score were lower in the high-risk group. The risk score was an independent predictor for OS in multivariate Cox regression analyses (HR > 1, p < 0.01). BTLA, PD-1, PD-L1, CTLA, and CD47 were lower expressed in the high-risk group.
ConclusionsOur study identified an 11-pyroptosis-related lncRNA signature. These findings could further clarify the role of pyroptosis in LUAD and guide the prognosis and individualized treatment of patients.

背景：焦亡（Pyroptosis）是一种新型程序性细胞死亡类型，伴随强烈的炎症应答。既往研究表明，焦亡可调控长链非编码RNA（long-chain non-coding RNA, lncRNA），进而影响肿瘤的发生与进展。然而，焦亡相关lncRNA在肺腺癌（lung adenocarcinoma, LUAD）中的潜在作用仍有待阐明。因此，本研究旨在评估焦亡相关lncRNA在肺腺癌患者中的预后价值。
方法：本研究从癌症基因组图谱（The Cancer Genome Atlas, TCGA）数据库中下载了454份肺腺癌样本。采用Pearson相关系数筛选焦亡相关lncRNA；采用无监督共识聚类法识别不同的肺腺癌分子亚型；通过最小绝对收缩和选择算子（least absolute shrinkage and selection operator, LASSO）分析构建预后特征模型。
结果：本研究从19个经鉴定的焦亡相关预后lncRNA中，构建了一个包含11个lncRNA的预后特征模型。将肺腺癌患者划分为低风险组与高风险组，高风险组患者的风险评分更高、死亡率也显著升高；高风险组的免疫评分、基质评分及ESTIMATE评分均更低。多因素Cox回归分析显示，风险评分是总生存期（overall survival, OS）的独立预测因子（风险比HR>1，P<0.01）。高风险组中BTLA、PD-1、PD-L1、CTLA及CD47的表达水平均显著降低。
结论：本研究鉴定出一个由11个焦亡相关lncRNA组成的预后特征。本研究结果可进一步阐明焦亡在肺腺癌中的作用，并可为患者的预后评估及个体化治疗提供参考依据。