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ORIGINAL RESEARCH article

Front. Genet.

Sec. Cancer Genetics and Oncogenomics

Volume 16 - 2025 | doi: 10.3389/fgene.2025.1655262

This article is part of the Research TopicAdvancing Non-small Lung Cancer Management Through Biomarker IntegrationView all 6 articles

Identification and validation of selenium metabolism-related genes in lung adenocarcinoma prognosis using bioinformatics analysis

Provisionally accepted
Yun  ChenYun Chen1Ping  LiPing Li2Yang  WangYang Wang1Shuai  ShenShuai Shen1Ni  ChenNi Chen1Hao  PengHao Peng1Zheyuan  XuZheyuan Xu3*
  • 1The First People's Hospital of Yunnan Province, Kunming, China
  • 2Affiliated Calmette Hospital of Kunming Medical University, Kunming, China
  • 3The First People’s Hospital of Yunnan Province, Kunming, China

The final, formatted version of the article will be published soon.

Background: The disruption of selenium metabolism has been associated with tumor progression. However, the prognostic significance and underlying molecular mechanisms of selenium metabolism in lung adenocarcinoma (LUAD) remain inadequately understood. This study primarily aimed to identify and validate prognostic genes related to selenium metabolism in LUAD patients. Methods: Transcriptomic datasets from patients diagnosed with LUAD were meticulously analyzed to identify differentially expressed genes associated with selenium metabolism. The genes selected for the prognostic risk model were determined through various analyses, including differential gene expression assessment, univariate and multivariate Cox proportional hazards regression analyses, as well as other relevant analytical methods. A systematic approach was employed for functional enrichment analysis, characterization of the immune microenvironment, somatic mutation analysis, and evaluation of drug sensitivity to elucidate the mechanisms linked to prognostic genes and risk categories. Finally, a reverse transcription quantitative PCR(RT-qPCR) assay was conducted to validate the expression levels of the identified prognostic genes. Results: F2, GPX3, KMO, and KYNU were identified as prognostic genes for establishing a risk model. The functions of these LUAD prognostic genes were influenced by DNA replication pathways, cell cycle regulation, and quiescent CD4 memory T cells. In the high-risk group(HRG), KEAP1, TTN, and USH2A exhibited the highest mutation rate at 48%, while TTN had an even higher mutation rate of 52% in the low-risk group (LRG). Within the HRG cohort, both cisplatin and gemcitabine demonstrated significant sensitivity. Ultimately, RT-qPCR findings corroborated results obtained from bioinformatics analyses; specifically compared to normal samples: GPX3, KMO, KYNU showed significant downregulation in LUAD tissues while F2 was found to be upregulated in LUAD. Conclusion: This study identified four prognostic genes in LUAD and examined their associated mechanisms of action, which may contribute to the development of novel treatment strategies. The integration of immune characterization with drug sensitivity analysis offers valuable insights for stratified therapy.

Keywords: Lung Adenocarcinoma, selenium metabolism, Prognostic model, Tumor Microenvironment, Immunotherapy response, drug sensitivity

Received: 12 Jul 2025; Accepted: 06 Oct 2025.

Copyright: © 2025 Chen, Li, Wang, Shen, Chen, Peng and Xu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Zheyuan Xu, 640039365@qq.com

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