近期，内质网应激相关基因（ERS）标记在预测肿瘤患者预后方面表现出色。从TCGA和GTEx数据库中获取口腔鳞状细胞癌（OSCC）中不同表达的基因。通过最小绝对选择和收缩操作（Lasso）回归，筛选出三个与预后相关且差异表达的ERS，构建预后风险模型。利用受试者操作特征曲线（ROC）、风险图和生存曲线验证模型对预后的准确性。进行多组学分析，探索OSCC的可能机制，包括免疫浸润、基因突变和干细胞特性。最后，从药物敏感性的角度讨论了模型在临床应用价值。确定模型中使用的三个基因（IBSP，RDM1，RBP4）为预后风险因素。通过生物信息学分析、组织和细胞实验充分验证了这三个基因在OSCC中的异常表达。多种验证方法和内外部数据集证实了该模型在预测和鉴别预后方面的出色性能。Cox回归分析确定了风险得分作为预后的独立预测因子。多组学分析发现风险得分与免疫细胞、细胞干性指数和肿瘤突变负荷（TMB）之间存在强相关性。还观察到风险得分与多西他赛、吉非替尼和厄洛替尼的半最大抑制浓度密切相关。通过多种方法验证了诊断模型的出色性能。构建了具有高临床应用价值的预后模型。免疫细胞、细胞干性和TMB可能参与OSCC的进展。

Recently, endoplasmic reticulum stress related gene (ERS) markers have performed very well in predicting the prognosis of tumor patients.The differentially expressed genes in Oral squamous cell carcinoma (OSCC) were obtained from TCGA and GTEx database. Three prognosis-related and differentially expressed ERSs were screened out by Least Absolute Selection and Shrinkage Operator (Lasso) regression to construct a prognostic risk model. Receiver Operating Characteristic Curve (ROC), riskplots and survival curves were used to verify the model's accuracy in predicting prognosis. Multi-omics analysis of immune infiltration, gene mutation, and stem cell characteristics were performed to explore the possible mechanism of OSCC. Finally, we discussed the model's clinical application value from the perspective of drug sensitivity.Three genes used in the model (IBSP, RDM1, RBP4) were identified as prognostic risk factors. Bioinformatics analysis, tissue and cell experiments have fully verified the abnormal expression of these three genes in OSCC. Multiple validation methods and internal and external datasets confirmed the model's excellent performance in predicting and discriminating prognosis. Cox regression analysis identified risk score as an independent predictor of prognosis. Multi-omics analysis found strong correlations between risk scores and immune cells, cell stemness index, and tumor mutational burden (TMB). It was also observed that the risk score was closely related to the half maximal inhibitory concentration of docetaxel, gefitinib and erlotinib. The excellent performance of the nomogram has been verified by various means.A prognostic model with high clinical application value was constructed. Immune cells, cellular stemness, and TMB may be involved in the progression of OSCC.