A Prognostic Nomogram Based on an Immunogenic Cell Death and Endoplasmic Reticulum Stress-Related Gene Signature for Ovarian Cancer.

Purpose: Gene signatures offer superior power on prognosis and survival of patients over traditional single-gene biomarker. This study aimed to develop a nomogram based on an immunogenic cell death (ICD) and endoplasmic reticulum (ER) stress-related gene signature to predict the overall survival (OS) of patients with ovarian cancer (OC). Materials and Methods: ICD- and ER stress-related genes were identified from public datasets and previous publications. Candidate genes were screened through differential expression and survival analyses. A prognostic risk score was established using Cox and LASSO regression. The model's predictive performance was evaluated by Kaplan-Meier and multivariate analyses, and a nomogram was constructed to estimate individual survival probabilities. Results: A seven-gene signature related to ICD and ER stress was developed to generate a prognostic risk score. Patients with low risk scores had significantly longer OS compared to high-risk patients. The signature correlated with immune features and remained an independent prognostic factor for OS in multivariate analysis. The prediction performance was good, with AUC values of 0.61, 0.64, and 0.67 for 1-, 2-, and 3-year OS in the training set, and 0.60, 0.61, and 0.60 in the validation set. The calibration curve showed good consistency between predicted and actual results. Conclusion: We established a clinically applicable nomogram integrating a seven-gene ICD/ER stress signature to provide individualized survival prediction for OC patients. This tool may assist clinicians in risk stratification and personalized treatment planning.