Department of Critical Care Medicine, Wuhan Jinyintan Hospital, Wuhan, Hubei, People's Republic of China.
Department of Infectious Diseases, Wuhan Jinyintan Hospital, Wuhan, Hubei, People's Republic of China.
Medicine (Baltimore). 2022 Jul 22;101(29):e29710. doi: 10.1097/MD.0000000000029710.
Pyroptosis-related genes (PRGs) have been reported to be associated with prognosis of lung adenocarcinoma (LUAD). Until now, the relationship of PRGs to the prognosis of LUAD patients and its underlying mechanisms have been poorly elucidated. Using The Cancer Genome Atlas (TCGA) LUAD cohort, a prior bioinformatics analysis constructed a prognostic signature incorporating 5 PRGs (NLRP7, NLRP1, NLRP2, NOD1, and CASP6) for predicting prognosis of LUAD patients. However, it has not been validated by the Gene Expression Omnibus (GEO) LUAD cohort yet. We implemented a modified bioinformatics analysis to, respectively, construct one prognostic signature with the TCGA cohort and with the GEO cohort and attempted to perform cross-validations by the GEO cohort and the TCGA cohort alternately in turn. Univariate and multivariate Cox regression analysis screened PRGs and constructed 2 prognostic signatures with the TCGA and GEO cohorts. All LUAD samples were classified into high- and low-risk groups according to the median risk score that was generated by regression formula. Kaplan-Meier survival analysis compared the overall survival rate between the 2 risk groups, and receiver operating characteristic curve analysis evaluated predictive performance of the 2 signatures. Additionally, risk score, combined with clinicopathological features, was subjected to multivariate Cox regression analysis, to evaluate independent prognostic value of the 2 signatures. Finally, the 2 signatures received cross-validations by the GEO and TCGA cohorts, alternately. The TCGA cohort yielded a 3-gene signature (PYCARD, NLRP1, and NLRC4), whereas the GEO cohort built a 7-gene signature (SCAF11, NOD1, NLRP2, NLRP1, GPX4, CASP8, and AIM2) for predicting the prognosis of LUAD patients. Multivariate analysis proved independent prognostic value of risk score in the TCGA cohort (hazard ratio, = 1.939,; P = 8.43 × 10-4) and the GEO cohort (hazard ratio, = 2.291,; P = 4.34 × 10-9). Cross-validations confirmed prognostic value for the 7-gene signature from the GEO cohort by the TCGA cohort but not for the 3-gene signature from the TCGA cohort by the GEO cohort. We develop and validate a 7-gene prognostic signature (SCAF11, NOD1, NLRP2, NLRP1, GPX4, CASP8, and AIM2) with independent prognostic value for patients with LUAD.
焦亡相关基因(PRGs)已被报道与肺腺癌(LUAD)的预后相关。迄今为止,PRGs 与 LUAD 患者预后的关系及其潜在机制仍未得到充分阐明。本研究使用癌症基因组图谱(TCGA)LUAD 队列,通过先前的生物信息学分析构建了一个包含 5 个 PRGs(NLRP7、NLRP1、NLRP2、NOD1 和 CASP6)的预后特征,用于预测 LUAD 患者的预后。然而,该特征尚未通过基因表达综合数据库(GEO)LUAD 队列进行验证。我们实施了一项改良的生物信息学分析,分别使用 TCGA 队列和 GEO 队列构建了一个预后特征,并尝试通过 GEO 队列和 TCGA 队列交替进行交叉验证。单因素和多因素 Cox 回归分析筛选 PRGs,并使用 TCGA 和 GEO 队列构建了 2 个预后特征。根据回归公式生成的中位数风险评分,将所有 LUAD 样本分为高风险组和低风险组。Kaplan-Meier 生存分析比较了 2 个风险组的总生存率,受试者工作特征曲线分析评估了 2 个特征的预测性能。此外,风险评分结合临床病理特征,进行多因素 Cox 回归分析,评估 2 个特征的独立预后价值。最后,通过 GEO 和 TCGA 队列交替对 2 个特征进行交叉验证。TCGA 队列产生了一个 3 基因特征(PYCARD、NLRP1 和 NLRC4),而 GEO 队列构建了一个 7 基因特征(SCAF11、NOD1、NLRP2、NLRP1、GPX4、CASP8 和 AIM2),用于预测 LUAD 患者的预后。多因素分析证明了风险评分在 TCGA 队列(危险比,=1.939;P=8.43×10-4)和 GEO 队列(危险比,=2.291;P=4.34×10-9)中的独立预后价值。交叉验证通过 TCGA 队列验证了来自 GEO 队列的 7 基因特征的预后价值,但通过 GEO 队列验证 TCGA 队列的 3 基因特征的预后价值不成立。我们开发并验证了一个具有独立预后价值的 7 基因 LUAD 患者预后特征(SCAF11、NOD1、NLRP2、NLRP1、GPX4、CASP8 和 AIM2)。