Patients with locally advanced laryngeal and hypopharyngeal squamous cell carcinoma (LA-LHSCC) urgently need precise treatment strategies to improve the prognosis due to severe laryngeal functional impairment following traditional surgery and chemoradiotherapy. This study focuses on the mechanism of sensitivity to induction chemotherapy (IC), integrating the GSE184072 and TCGA-HNSC data sets to screen for differentially expressed genes (DEGs). Combining weighted gene coexpression network analysis (WGCNA) and machine learning methods, including MCC, MCODE, LASSO, SVM-RFE, and Random Forest (RF), the core gene DSC2 (Desmocollin-2) was identified. The results show that DSC2 is significantly highly expressed in the IC-sensitive group with a receiver operating characteristic (ROC) curve area under the curve (AUC) of 0.9111, indicating its high predictive efficacy as a biomarker. Immune infiltration analysis further revealed a significant correlation between DSC2 and the infiltration levels of immune cells such as M1 macrophages, suggesting its potential to influence IC sensitivity by regulating apoptosis and the immune microenvironment. Furthermore, the TCGA clinical data validated the correlation between DSC2 expression and patient survival rates. Our study is the first to establish DSC2 as a pivotal biomarker for IC sensitivity in LA-LHSCC patients, offering a novel avenue for the development of targeted therapeutic strategies and personalized diagnosis and treatment.
No clinical trial protocols linked to this paper
Clinical trials are automatically linked when NCT numbers are found in the paper's title or abstract.PICO Elements
No PICO elements extracted yet. Click "Extract PICO" to analyze this paper.
Paper Details
MeSH Terms
Associated Data
No associated datasets or code repositories found for this paper.
Related Papers
Related paper suggestions will be available in future updates.