A combined gene signature model for predicting radiotherapy response and relapse-free survival in laryngeal squamous cell carcinoma.

ABSTRACT:

Background

Radioresistance is a major challenge in radiotherapy for laryngeal squamous cell carcinoma (LSCC), and there is currently no effective method to predict radiosensitivity in LSCC patients. This study aimed to establish a prediction model for radiotherapy response based on gene expression.

Methods

The datasets of LSCC were obtained from the ENT department of Shanghai Ruijin Hospital and The Cancer Genome Atlas (TCGA). Lasso regression and Cox regression were used to establish the prediction model based on gene expression. Weighted gene coexpression network analysis (WGCNA) was used to analyze the correlation between gene expression and clinical characteristics. RT-qPCR was used to detect gene expression in tumor tissue to verify the accuracy of the prediction model.

SUBMITTER: Gong S 

PROVIDER: S-EPMC11916850 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature