Bai Hong-Yan, Li Tian-Tian, Sun Li-Na, Zhang Jing-Hong, Kang Xiu-He, Qu Yi-Qing
Department of Pulmonary and Critical Care Medicine, Qilu Hospital, Cheeloo College of Medicine, Shandong Key Laboratory of Infectious Respiratory Diseases, Shandong University, Jinan, China.
Anal Cell Pathol (Amst). 2025 Jan 13;2025:4488139. doi: 10.1155/ancp/4488139. eCollection 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.
肺癌是一种高度流行且致命的癌症,严重威胁着世界各地人们的安全。早期诊断困难和强大的耐药性一直是肺癌治疗中的难题,因此肺癌的预后一直是科研人员关注的焦点。本研究利用基因型-组织表达(GTEx)和癌症基因组图谱(TCGA)数据库,获取477例肺腺癌(LUAD)患者和347例健康个体的样本作为研究对象,并根据预后风险评分将LUAD患者分为低风险组和高风险组。对从GeneCards和MSigDB数据库中获得的25个与细胞焦亡相关的基因在LUAD患者癌组织和健康个体非癌组织中进行差异表达基因(DEG)分析,其中7个基因在癌组织和非癌组织中有显著差异。对这些基因与长链非编码RNA(lncRNA)进行共表达分析和差异表达分析,发现3个lncRNA(AC012615.1、AC099850.3和AO0001453.2)在癌组织和非癌组织中的表达存在显著差异。我们使用Cox回归和最小绝对收缩和选择算子(LASSO)回归,以这3个与细胞焦亡相关的lncRNA(pRLs)构建LUAD患者的预后模型,并通过Kaplan-Meier曲线和Cox回归分析pRLs模型的预后价值。结果表明,该风险预测模型具有良好的预测能力。此外,我们还研究了低风险组和高风险组中肿瘤突变负荷(TMB)、肿瘤免疫功能障碍和排斥(TIDE)以及免疫微环境与pRLs风险评分的差异。本研究成功建立了基于pRLs的LUAD预后模型,为基于lncRNA的LUAD诊断和治疗策略提供了新的见解。