鉴定肺腺癌患者分子亚群并建立基于对氧化应激反应的风险模型，以预测其总体生存。
Identification of molecular subgroups and establishment of risk model based on the response to oxidative stress to predict overall survival of patients with lung adenocarcinoma.
发表日期：2023 Sep 09
作者：
Linzhuang Liu, Qinghua Hou, Baorong Chen, Xiyi Lai, Hanwen Wang, Haozhen Liu, Liusheng Wu, Sheng Liu, Kelin Luo, Jixian Liu
来源：
MOLECULAR & CELLULAR PROTEOMICS
摘要：
氧化应激与肺癌的发生和发展有关，但肺癌和氧化应激的具体关联尚不清楚。本研究旨在探究氧化应激在肺腺癌（LUAD）进展和预后中的作用。从GEO和TCGA数据库收集了基因表达谱和相应的临床信息。在正常和肿瘤样本之间鉴定了差异表达的氧化应激相关基因（OSRGs）。应用共识聚类方法鉴定了氧化应激相关的分子亚组。进行功能富集分析、GSEA和GSVA以探究潜在机制。使用xCell评估亚组的免疫状态。采用LASSO算法建立风险模型，并使用TCGA-LUAD、GSE13213和GSE30219数据集进行验证。
共鉴定了40个差异表达的OSRGs和两个与氧化应激相关的亚组。富集分析揭示在这两个亚组中，细胞周期、炎症和氧化应激相关的途径存在明显差异。此外，基于OSRGs建立并验证了风险模型，结果表明该模型对LUAD患者具有良好的预测和诊断价值。
基于氧化应激的风险模型可以作为LUAD患者的有效预后工具。我们的发现为预后预测和个体化临床治疗提供了新的遗传标志物。
© 2023 BioMed Central Ltd., Springer Nature的一部分。
Oxidative stress is associated with the occurrence and development of lung cancer. However, the specific association between lung cancer and oxidative stress is unclear. This study aimed to investigate the role of oxidative stress in the progression and prognosis of lung adenocarcinoma (LUAD).The gene expression profiles and corresponding clinical information were collected from GEO and TCGA databases. Differentially expressed oxidative stress-related genes (OSRGs) were identified between normal and tumor samples. Consensus clustering was applied to identify oxidative stress-related molecular subgroups. Functional enrichment analysis, GSEA, and GSVA were performed to investigate the potential mechanisms. xCell was used to assess the immune status of the subgroups. A risk model was developed by the LASSO algorithm and validated using TCGA-LUAD, GSE13213, and GSE30219 datasets.A total of 40 differentially expressed OSRGs and two oxidative stress-associated subgroups were identified. Enrichment analysis revealed that cell cycle-, inflammation- and oxidative stress-related pathways varied significantly in the two subgroups. Furthermore, a risk model was developed and validated based on the OSRGs, and findings indicated that the risk model exhibits good prediction and diagnosis values for LUAD patients.The risk model based on the oxidative stress could act as an effective prognostic tool for LUAD patients. Our findings provided novel genetic biomarkers for prognosis prediction and personalized clinical treatment for LUAD patients.© 2023. BioMed Central Ltd., part of Springer Nature.