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构建和评估与线粒体自噬相关的基因预后模型:对肺腺癌免疫景观和肿瘤生物学的影响。

Constructing and Evaluating a Mitophagy-Related Gene Prognostic Model: Implications for Immune Landscape and Tumor Biology in Lung Adenocarcinoma.

机构信息

School of Public Health, Suzhou Medical College of Soochow University, Suzhou 215123, China.

出版信息

Biomolecules. 2024 Feb 16;14(2):228. doi: 10.3390/biom14020228.

Abstract

Mitophagy, a conserved cellular mechanism, is crucial for cellular homeostasis through the selective clearance of impaired mitochondria. Its emerging role in cancer development has sparked interest, particularly in lung adenocarcinoma (LUAD). Our study aimed to construct a risk model based on mitophagy-related genes (MRGs) to predict survival outcomes, immune response, and chemotherapy sensitivity in LUAD patients. We mined the GeneCards database to identify MRGs and applied LASSO/Cox regression to formulate a prognostic model. Validation was performed using two independent Gene Expression Omnibus (GEO) cohorts. Patients were divided into high- and low-risk categories according to the median risk score. The high-risk group demonstrated significantly reduced survival. Multivariate Cox analysis confirmed the risk score as an independent predictor of prognosis, and a corresponding nomogram was developed to facilitate clinical assessments. Intriguingly, the risk score correlated with immune infiltration levels, oncogenic expression profiles, and sensitivity to anticancer agents. Enrichment analyses linked the risk score with key oncological pathways and biological processes. Within the model, MTERF3 emerged as a critical regulator of lung cancer progression. Functional studies indicated that the MTERF3 knockdown suppressed the lung cancer cell proliferation and migration, enhanced mitophagy, and increased the mitochondrial superoxide production. Our novel prognostic model, grounded in MRGs, promises to refine therapeutic strategies and prognostication in lung cancer management.

摘要

自噬是一种保守的细胞机制,通过选择性清除受损的线粒体,对于细胞的内稳态至关重要。它在癌症发展中的新兴作用引起了人们的兴趣,特别是在肺腺癌 (LUAD) 中。我们的研究旨在构建基于自噬相关基因 (MRGs) 的风险模型,以预测 LUAD 患者的生存结局、免疫反应和化疗敏感性。我们从 GeneCards 数据库中挖掘 MRGs,并应用 LASSO/Cox 回归构建预后模型。使用两个独立的基因表达综合 (GEO) 队列进行验证。根据中位风险评分将患者分为高风险和低风险类别。高风险组的生存显著降低。多变量 Cox 分析证实风险评分是预后的独立预测因子,并开发了相应的列线图以方便临床评估。有趣的是,风险评分与免疫浸润水平、致癌表达谱和对抗癌药物的敏感性相关。富集分析将风险评分与关键的肿瘤学途径和生物学过程联系起来。在该模型中,MTERF3 作为肺癌进展的关键调节因子。功能研究表明,MTERF3 的敲低抑制了肺癌细胞的增殖和迁移,增强了自噬,并增加了线粒体中超氧化物的产生。我们基于 MRGs 的新型预后模型有望完善肺癌管理中的治疗策略和预后判断。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4dfe/10886790/5666fb6ba898/biomolecules-14-00228-g001.jpg

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