Development and functional validation of a disulfidoptosis-related gene prognostic model for lung adenocarcinoma based on bioinformatics and experimental validation

基于生物信息学和实验验证,构建并功能验证了与二硫键凋亡相关的肺腺癌预后模型。

阅读:3

Abstract

BACKGROUND: Disulfidoptosis is increasingly linked to cancer progression, yet its immunological impacts and prognostic value in lung adenocarcinoma (LUAD) remain poorly understood. This study aims to delineate the predictive significance of disulfidoptosis-related genes (DRGs) in LUAD, their potential as therapeutic targets, and their interaction with the tumor microenvironment. METHODS: We analyzed the expression profiles of 23 DRGs and survival data, performing consensus clustering to identify molecular subtypes. Survival analysis and gene set variation analysis (GSVA) were used to explore cluster differences. Key DRGs were selected for Cox and LASSO regression to develop a prognostic model. Tensin4 (TNS4), a key gene in the model, was further evaluated through immunohistochemistry (IHC) in LUAD and normal tissues and gene knockdown experiments in vitro. RESULTS: Two clusters were identified, with 225 differentially expressed genes. A six-gene signature was developed, which classified LUAD patients into high- and low-risk groups, showing significant survival differences. The risk score independently predicted LUAD prognosis and correlated with immunotherapy responses. IHC showed elevated TNS4 levels in LUAD tissues, while in vitro TNS4 knockdown reduced both cell proliferation and migration. CONCLUSION: This study highlights the role of DRGs in LUAD, with a validated gene signature offering new avenues for targeted therapies, potentially improving LUAD treatment outcomes.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。