Development of a Novel Prognostic Model for Lung Adenocarcinoma Utilizing Pyroptosis‐Associated LncRNAs - Bai, Hong-Yan; Li, Tian-Tian; Sun, Li-Na; Zhang, Jing-Hong; Kang, Xiu-He; Qu, Yi-Qing (Analytical cellular pathology (Amsterdam), 2025)
Lung cancer is a highly prevalent and fatal cancer that seriously threatens the safety of people in various regions around the world. Difficulty in early diagnosis and strong drug resistance have always been difficulties in the treatment of lung cancer, so the prognosis of lung cancer has always been the focus of scientific researchers. This study used genotype‐tissue expression (GTEx) and the cancer genome atlas (TCGA) databases to obtain 477 lung adenocarcinoma (LUAD) and 347 healthy individuals’ samples as research subjects and divided LUAD patients into low‐risk and high‐risk groups based on prognostic risk scores. Differentially expressed gene (DEG) analysis was performed on 25 pyroptosis‐related genes obtained from GeneCards and MSigDB databases in cancer tissues of LUAD patients and noncancerous tissues of healthy individuals, and seven genes were significantly different in cancer tissues and noncancerous tissues among them. Coexpression analysis and differential expression analysis of these genes and long noncoding RNAs (lncRNAs) found that three lncRNAs (AC012615.1, AC099850.3, and AO0001453.2) had significant differences in expression between cancer tissues and noncancerous tissues. We used Cox regression and the least absolute shrinkage sum selection operator (LASSO) regression to construct a prognostic model for LUAD patients with these three pyroptosis‐related lncRNAs (pRLs) and analyzed the prognostic value of the pRLs model by the Likaplan–Meier curve and Cox regression. The results show that the risk prediction model has good prediction ability. In addition, we also studied the differences in tumor mutation burden (TMB), tumor immune dysfunction and rejection (TIDE), and immune microenvironment with pRLs risk scores in low‐risk and high‐risk groups. This study successfully established a LUAD prognostic model based on pRLs, which provides new insights into lncRNA‐based LUAD diagnosis and treatment strategies.