构建用于预测肺腺癌预后和肿瘤微环境的线粒体自噬相关预后特征。

Construction of a mitophagy-related prognostic signature for predicting prognosis and tumor microenvironment in lung adenocarcinoma.

作者信息

Liu Wu-Sheng, Li Ru-Mei, Le Yong-Hong, Zhu Zan-Lei

机构信息

Department of Respiratory and Critical Care Medicine, The Affiliated Ganzhou Hospital of Nanchang University, Ganzhou People's Hospital. No. 16, Meiguan Avenue, Zhanggong, Ganzhou, Jiangxi, 341000, PR China.

Department of Endocrinology, The Affiliated Ganzhou Hospital of Nanchang University, Ganzhou People's Hospital. No. 16, Meiguan Avenue, Zhanggong, Ganzhou, Jiangxi, 341000, PR China.

出版信息

Heliyon. 2024 Jul 31;10(15):e35305. doi: 10.1016/j.heliyon.2024.e35305. eCollection 2024 Aug 15.

DOI:10.1016/j.heliyon.2024.e35305

PMID:39170577

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11336613/

Abstract

BACKGROUND

Mitophagy is the selective degradation of mitochondria by autophagy. It becomes increasingly clear that mitophagy pathways are important for cancer cells to adapt to their high-energy needs. However, which genes associated with mitophagy could be used to prognosis cancer is unknown.

METHODS

We created a clinical prognostic model using mitophagy-related genes (MRGs) in lung adenocarcinoma (LUAD) patients for the first time, and we employed bioinformatics methods to search for biomarkers that affect the progression and prognosis of LUAD. Transcriptome data for LUAD were obtained from The Cancer Genome Atlas (TCGA) database, and additional expression data from LUAD patients were sourced from the Gene Expression Omnibus (GEO) database. Furthermore, 25 complete MRGs were identified based on annotations from the MSigDB database.

RESULTS

A comparison of the mitophagy scores between the groups with high and low scores was done using receiver operating characteristic (ROC) curves, which also revealed the differential gene expression patterns between the two groups. Using Kaplan-Meier analysis, two prognostic MRGs from the groups with high and low mitophagy scores were identified: . Using univariate and multivariate Cox regression, the relationship between the expression levels of these two genes and prognostic clinical features of LUAD was examined further.The prognosis of LUAD patients was shown to be significantly correlated (P < 0.05) with the expression levels of these two genes.

CONCLUSIONS

Our prognostic model would improve the prognosis of LUAD and guide clinical treatments.

摘要

背景

线粒体自噬是通过自噬对线粒体进行选择性降解。越来越清楚的是，线粒体自噬途径对于癌细胞适应其高能量需求很重要。然而，哪些与线粒体自噬相关的基因可用于癌症预后尚不清楚。

方法

我们首次使用肺腺癌（LUAD）患者的线粒体自噬相关基因（MRGs）创建了一个临床预后模型，并采用生物信息学方法寻找影响LUAD进展和预后的生物标志物。LUAD的转录组数据从癌症基因组图谱（TCGA）数据库获得，LUAD患者的其他表达数据来自基因表达综合数据库（GEO）。此外，基于MSigDB数据库的注释确定了25个完整的MRGs。

结果

使用受试者工作特征（ROC）曲线对高分组和低分组之间的线粒体自噬评分进行比较，这也揭示了两组之间的差异基因表达模式。使用Kaplan-Meier分析，从高线粒体自噬评分组和低线粒体自噬评分组中确定了两个预后MRGs：。使用单变量和多变量Cox回归，进一步研究了这两个基因的表达水平与LUAD预后临床特征之间的关系。结果显示，LUAD患者的预后与这两个基因的表达水平显著相关（P < 0.05）。