生物信息学分析和临床样本鉴定食管鳞状细胞癌性别相关预后基因OA

[Objective]To identify gender-related prognostic genes in esophageal squamous cell carcinoma(ESCC)through bioinformatics analysis,develop a risk scoring model and prognostic nomogram,and analyze the biological characteristics of key genes in clinical samples,thereby providing an effective tool for prognostic assessment in clinical practice.[Methods]Using the GSE53625 dataset,weighted gene co-expression network analysis(WGCNA)was used to screen gender-related module genes,which were intersected with prognostic genes obtained from Kaplan-Meier(K-M)analysis.Gender-related prognostic genes were further identified using least absolute shrinkage and selection operator(LASSO)and multivariable Cox regression analysis,and a risk score model was constructed.A prognostic prediction nomogram was developed by integrating the risk score and independent prognostic factors.The clinical application performance of the model was evaluated using calibration curves,receiver operating characteristic(ROC)analysis,and decision curve analysis(DCA).[Results]Based on the optimal cutoff value of the risk score model,patients were stratified into high-risk and low-risk groups,with significantly different overall survival(OS)between the two groups.The constructed prognostic nomogram,which incorporated patient age,treatment modality,and risk score,demonstrated excellent calibration and discrimination capabilities.Further analysis revealed that patients with high IL5RA expression had relatively better OS,and female patients exhibited superior survival outcomes compared with males.[Conclusion]The identified gender-related prognostic genes hold promise as novel prognostic biomarkers,providing valuable insights for precise treatment and prognosis assessment in ESCC.