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非小细胞肺癌中铁自噬相关基因与预后及调控机制的分析

Analysis of ferritinophagy-related genes associated with the prognosis and regulatory mechanisms in non-small cell lung cancer.

作者信息

Hao Yuan, Wang Xin, Ni Zerong, Ma Yuhui, Wang Jing, Su Wen

机构信息

Clinical Trials Center, Cancer Hospital Affiliated to Shanxi Medical University, Shanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Taiyuan, China.

Department of Cancer Center, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Tongji Medical College Huazhong University Science of and Technology, Taiyuan, China.

出版信息

Front Med (Lausanne). 2025 Mar 7;12:1480169. doi: 10.3389/fmed.2025.1480169. eCollection 2025.

Abstract

Lung cancer remains a major global health issue, with non-small cell lung cancer (NSCLC) constituting approximately 85% of cases. Ferritinophagy, a pivotal autophagic process in ferroptosis, plays an essential role in tumor initiation and progression. However, the specific contributions of ferritinophagy-related genes (FRGs) to NSCLC pathogenesis remain incompletely understood. In this study, weighted gene co-expression network analysis (WGCNA) was employed to identify key modular genes associated with FRG scores. Genes overlapping between these modules and differentially expressed genes (DEGs) were selected for further investigation. Prognostic genes were identified through univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analysis, with subsequent validation using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) on both clinical samples and the TCGA-NSCLC dataset. A nomogram incorporating clinicopathological features and risk scores was developed to predict patient outcomes. Further analyses focused on functional enrichment, drug sensitivity, and the immune microenvironment. Cross-referencing 2,142 key modular genes with 2,764 DEGs revealed 600 candidate genes. Univariate Cox regression and LASSO analysis of these candidates identified eight prognostic genes: KLK8, MFI2, B3GNT3, MYRF, CREG2, GLB1L3, AHNAK2, and NLRP10. Two distinct risk groups exhibited significant survival differences. Both the risk score and pathological N stage were found to be independent prognostic factors, forming the basis for the nomogram. Notable correlations were observed between certain immune cells, prognostic genes, and immune responses, affecting the efficacy of immunotherapy and drug sensitivity. qRT-PCR confirmed that, except for NLRP10, all prognostic genes exhibited expression patterns consistent with TCGA-NSCLC data. This study highlights the significant role of FRGs in NSCLC prognosis and regulation, offering novel insights for personalized treatment strategies.

摘要

肺癌仍然是一个重大的全球健康问题,非小细胞肺癌(NSCLC)约占病例的85%。铁蛋白自噬是铁死亡中的一个关键自噬过程,在肿瘤的发生和发展中起着重要作用。然而,铁蛋白自噬相关基因(FRGs)对NSCLC发病机制的具体贡献仍未完全了解。在本研究中,采用加权基因共表达网络分析(WGCNA)来识别与FRG评分相关的关键模块基因。选择这些模块与差异表达基因(DEGs)之间重叠的基因进行进一步研究。通过单变量Cox回归和最小绝对收缩和选择算子(LASSO)分析确定预后基因,随后在临床样本和TCGA-NSCLC数据集中使用定量逆转录聚合酶链反应(qRT-PCR)进行验证。开发了一个结合临床病理特征和风险评分的列线图来预测患者的预后。进一步的分析集中在功能富集、药物敏感性和免疫微环境上。将2142个关键模块基因与2764个DEGs进行交叉比对,发现了600个候选基因。对这些候选基因进行单变量Cox回归和LASSO分析,确定了8个预后基因:KLK8、MFI2、B3GNT3、MYRF、CREG2、GLB1L3、AHNAK2和NLRP10。两个不同的风险组表现出显著的生存差异。风险评分和病理N分期均为独立的预后因素,构成了列线图的基础。在某些免疫细胞、预后基因和免疫反应之间观察到显著的相关性,影响免疫治疗的疗效和药物敏感性。qRT-PCR证实,除NLRP10外,所有预后基因的表达模式均与TCGA-NSCLC数据一致。本研究强调了FRGs在NSCLC预后和调控中的重要作用,为个性化治疗策略提供了新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73b5/11925780/46333fce6191/fmed-12-1480169-g001.jpg

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