Establishment of a prognostic signature for lung adenocarcinoma by integration of 7 pyroptosis-related genes and cross-validation between the TCGA and GEO cohorts: A comprehensive bioinformatics analysis. Issue 29 (22nd July 2022)

• Record Type: Journal Article
• Authors: Zhang, Wei; Wan, Shiqian; Qu, Zhaohui; Ge, Jing; Zhang, Chunxia; Li, Chunfang; Jiang, Yingchun
• Is Part Of: Medicine. Volume 101:Issue 29(2022)
• Page Start: e29710
• Publication Date: 2022-07-22
• Subjects: cox regression analysis -- Kaplan-Meier survival analysis -- lung adenocarcinoma -- prognostic signature -- pyroptosis -- receiver operating characteristic curve analysis; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000029710
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract : 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.