Home LiteratureArticle Details
PMID: 41805257 Published · aheadofprint English

Predicting prognosis of oral squamous cell carcinoma based on endoplasmic reticulum stress-associated gene signatures.

Li S, Chen W, Wang M, Shu G, Yin G

Abstract

Endoplasmic Reticulum Stress (ERS), as a core mechanism of cellular response to protein homeostasis imbalance, plays a dual regulatory role in tumorigenesis and development. In this study, we aimed to analyze the regulatory network of endoplasmic reticulum stress-associated genes (ERSAGs) in oral squamous cell carcinoma (OSCC). By screening differentially expressed genes through the TCGA database, we explored the potential associations between ERS and OSCC across various aspects. We constructed an OSCC prognostic risk scoring model based on ERSRGs and validated the model's reliability using the GEO dataset as a validation set. In total, 43 differentially expressed ERSAGs were screened as well as 9 prognostic genes. Six genes (KLHL14, SLC25A4, STC2, TRIB3, ALG3, and CCNA2) were screened by Lasso regression to construct a prognostic risk score model. Further analysis suggested that KLHL14 may suppress OSCC progression by modulating tumor-infiltrating immune cells, specifically activated B cells and mast cells. Concurrently, experimental validation demonstrated that overexpression of CCNA2 significantly promotes the proliferation of OSCC. The results indicated that CCNA2 promotes the proliferation of OSCC cells cultured in vitro. This study is the first to construct a prognostic risk model for OSCC based on ERSAGs, which may assist in predicting prognosis of OSCC patients. The identified ERSAGs may contribute to the development of new therapeutic strategies, highlighting the potential clinical application value of ERS-related genes in predicting OSCC prognosis.

Keywords
differentially expressed genes endoplasmic reticulum stress oral squamous cell carcinoma prognosis prognostic model survival analysis
Article Info
Journal
Journal of investigative medicine : the official publication of the American Federation for Clinical Research
Abbr.
J Investig Med
ISSN
1708-8267
Published
2026-03-10
Language
English
Region
England
NLM ID
9501229
Analysis Services
Analysis Services

Contact

No. 2 Wenbo Road, Zhangqiu District, Jinan, Shandong

Qilu Normal University · Genelibs Bioinformatics Lab

750 Shunhua Rd, Jinan

2F, Bldg F, University Science Park

Tel: 0531-88819269

WeChat Official Account

Follow our WeChat subscription account for real-time updates and the latest in medical and biological research.


Business Email

E-mail: product@genelibs.com