the 921st Hospital of PLA
目的 结肠癌（Colon adenocarcinoma，COAD）患者预后较差。因此筛选结肠癌预后相关基因，建立结肠癌新的预后风险评估模型。方法 基于癌症基因组图谱（The cancer genome atlas， TCGA）和基因表达综合（Gene Expression Omnibus，GEO）数据库中结肠癌相关数据，分别作为训练集和验证集。采用加权基因共表达网络分析（Weighted correlation network analysis，WGCNA）、Cox回归模型结合最小绝对值选择与收缩算子（Least Absolute Selection and Shrinkage Operator，LASSO）回归分析筛选结肠癌预后相关基因并构建预后模型，受试者工作特征（Receiver Operating Characteristic，ROC）结合生存曲线验证模型的准确性，并建立列线图。根据中位值将患者分为两组，免疫细胞阳性比例分数（Immune cell proportion score，IPS）评估两组患者免疫治疗反应。结果 最终筛选出15个特征基因，以此建立结肠癌患者预后预测模型的ROC曲线下面积（Area Under the Curve，AUC）>0.6，高风险组生存率显著低于低风险组（P<0.05），该模型可较好的区分高低风险组结肠癌患者。低风险组患者拥有较高的免疫细胞阳性比例（Immune cell proportion score ，IPS）评分（P=0.026），对免疫治疗反应效果更好。结论 建立的结肠癌预后模型对结肠癌高风险和低风险人群的生存情况具有较好的预测能力。
Objective Due to the poor prognosis of colon adenocarcinoma (COAD) patients, it is necessary to screen prognosis-related genes in COAD and establish a new prognostic risk assessment model. Methods COAD-related data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were used as the training set and the validation set, respectively. Weighted gene co-expression network analysis (WGCNA)， Cox regression model and Least Absolute Selection and Shrinkage Operator (LASSO) regression analysis were used to screen prognosis-related genes of COAD and construct a prognostic model. Receiver Operating Characteristic (ROC) curve was combined with survival curve to verify the accuracy of the model, and a nomogram was established. The patients were divided into two groups according to the median value of risk score. The immune cell proportion score (IPS) was used to evaluate the immunotherapy response of the two groups. Results A total of 15 feature genes were screened. The area under the ROC curve (AUC) in the predictive model of COAD patients was >0.6, and the survival rate of high-risk group was significantly lower than that of low-risk group (P<0.05, suggesting good distinguishing ability for high- and low-risk COAD patients. Patients in the low-risk group had a higher IPS (P=0.026), indicating a better response to immunotherapy. Conclusions The model developed for COAD in this study has a good ability to predict the survival of people at high and low risk of COAD.