A Prognostic Framework Integrating Endoplasmic Reticulum Stress Dynamics Reveals Clinical Stratification and Differential Prognostic Attributes in Osteosarcoma Patients

Zhongming Wu¹Yan Wang²Sina Ahmadi³Mingchao Ding²Yinggang Che⁴Changlong Song²Sijia Na^5*Weiqi Wang²

• ¹The Third Affiliated Hospital of Xi’an Medical University, Xi’an, China
• ²School of Stomatology, The Fourth Military Medical University, Xi'an, Shaanxi Province, China
• ³Xi'an Jiaotong University, Xi'an, China
• ⁴Air Force Hospital of the Western Theater of the Chinese People's Liberation Army, Chengdu, Sichuan Province, China
• ⁵Department of Oral and Maxillofacial Surgery, College of Stomatology, Xi’an Jiaotong University, Xi’an, Shaanxi Province, China

Abstract Background: Endoplasmic reticulum (ER) stress is recognized as a pivotal factor in the initiation and advancement of osteosarcoma; however, its implications for patient prognosis remain poorly understood. Methods: Our objective was to elucidate the prognostic implications and immune infiltration patterns associated with endoplasmic reticulum (ER) stress in osteosarcoma patients through the synthesis of existing osteosarcoma datasets and the application of advanced bioinformatics methodologies. Results: Our findings elucidate distinct and heterogeneous expression patterns of endoplasmic reticulum (ER) stress-related genes in osteosarcoma, contrasting sharply with those identified in osteocytes and mesenchymal stem cells. We developed a robust ER stress model comprising ten ER stress-associated genes specifically tailored for osteosarcoma patients. This model was constructed utilizing univariate analysis and least absolute shrinkage and selection operator (LASSO) regression techniques. The predictive robustness and applicability of the model were ascertained through receiver operating characteristic (ROC) curve analysis and validation against external datasets. Notably, stratification based on the model demonstrated statistically significant correlations with patient survival outcomes. Furthermore, protein-protein interaction network analyses unveiled several pathways pertinent to tumor biology and immune responses. Intriguingly, the low-risk cohort exhibited enhanced immune infiltration, with the density of Th1 cell infiltration showing a positive correlation with increased patient risk, thereby highlighting its potential as a prognostic biomarker. Differential gene clustering analysis further underscored the critical role of ER stress models in prognostic predictions. Finally, our study identifies the IL4 signaling pathway is significantly associated with a good prognosis (p < 0.01), and may play a potential protective role for osteosarcoma, observed at the single-cell level by modulating macrophage polarization. The cause and effect relationship needs to be confirmed IL4 signaling pathway as a promising protective factor for osteosarcoma, observed at the single-cell level. Conclusion: Our findings suggest that evaluating endoplasmic reticulum stress levels and associated models in osteosarcoma patients could inform clinical interventions and enhance patient outcomes.