列线图
比例危险模型
肿瘤科
内科学
医学
免疫系统
生存分析
预测模型
免疫疗法
癌症
回归分析
接收机工作特性
回归
曲线下面积
总体生存率
预后变量
病态的
逐步回归
肿瘤浸润淋巴细胞
训练集
渗透(HVAC)
曲线下面积
阶段(地层学)
试验预测值
作者
Yunjie Wan,Ganshu Xia,Shoumiao Li,Wei Zhang,Yanxin Gong,Xiaolong Liang,Zhiqiang Liu,Baozhong Li
摘要
ABSTRACT Vesicle‐mediated transport plays a role in intercellular communication in tumor microenvironment, affecting tumor development and prognosis. This study attempted to establish risk markers for gastric cancer (GC) based on vesicle‐mediated transport‐related genes, providing a new perspective for evaluating immunotherapeutic response and prognosis in GC patients. We used TCGA‐STAD data set for training set and performed differential analysis and Cox regression analysis to establish a vesicle‐mediated transport‐related GC prognostic risk model to predict survival rate of GC patients. GC prognostic model was verified through TCGA‐STAD and GSE84426 datasets. ROC curve presented that GC prognostic model had reliable prediction results, and the Kaplan‐Meier survival curve presented that high‐risk (HR) GC patients had unfavorable prognoses. The Cox regression analysis results reported that GC prognostic model had independent predictive ability for prognosis. Clinical feature analysis revealed that the majority of HR group patients were male and under 60 years old, with a high degree of malignancy. Using GC prognostic risk scores and clinical factors, we constructed a nomogram. Calibration, ROC, and DCA curves presented that nomogram had excellent predictive ability for patient prognosis. Immune infiltration analysis showed that HR GC patients had a lower overall proportion of immune cell infiltration and poorer immune function. Prediction of immunotherapeutic response showed that low‐risk (LR) GC patients may be prone to benefit from immunotherapy. In conclusion, GC prognostic risk model had potential to forecast prognosis and immunotherapeutic efficacy of GC patients.
科研通智能强力驱动
Strongly Powered by AbleSci AI