A total of 291 patients who were admitted to Zhuzhou Central Hospital for colonoscopy from January 2020 to December 2021 and met the inclusion criteria were selected. Serum samples of the patients were collected, and CST4 was detected by double-antibody sandwich enzyme-linked immunosorbent assay. Simultaneously, CEA and CA19-9 were detected, and the patients were divided into the CRC group, benign lesion group, and healthy control group. An attempt was made to construct a CRC prediction model including CST4 and draw a subject working characteristic curve as a diagnostic threshold for CRC prediction, and evaluate the diagnostic efficacy of the above indicators. At the same time, the expression analysis of CST4, CEA, and CA19-9 was verified by combining the data of CRC in the Tumor Genome Atlas (TCGA).
In this study, the levels of serum CST4, CEA, and CA19-9 in the CRC group were higher than those in the colorectal benign lesion group and healthy control group, with statistical significance (P < .001). The analysis results of the receiver operating characteristic curve showed that the area under the receiver operator characteristic curve (AUC) of CST4 was 0.7739, which was obviously larger than the AUC of CA19-9 and CEA. CRC data from the TCGA expression database showed that CST4 expression and CEA expression were higher in CRC patients than in normal samples. The combined model based on CST4 was successfully constructed, and the AUC for predicting the occurrence of CRC was 0.7851.
CST4 is a novel and improved diagnostic marker for CRC. The combined model based on CST4 has a certain potential value in terms of predicting the occurrence of intestinal cancer.
方法:选择2020年1月至2021年12月在株洲市中心医院行结肠镜检查且符合纳入标准的患者291例。收集患者的血清样本,采用双抗体夹心酶联免疫吸附法检测CST4。同时,检测到CEA和CA19-9,将患者分为CRC组,良性病变组,健康对照组。尝试构建包含CST4的CRC预测模型,并绘制受试者工作特性曲线作为CRC预测的诊断阈值,并评价上述指标的诊断效能。同时,CST4、CEA、通过结合肿瘤基因组图谱(TCGA)中的CRC数据来验证CA19-9。
结果:在这项研究中,血清CST4、CEA、结直肠良性病变组和健康对照组,具有统计学意义(P<.001)。受试者工作特征曲线分析结果显示,CST4的受试者工作特征曲线下面积(AUC)为0.7739,明显大于CA19-9和CEA的AUC。来自TCGA表达数据库的CRC数据显示CRC患者中的CST4表达和CEA表达高于正常样品。成功构建了基于CST4的组合模型,预测CRC发生的AUC为0.7851。
结论:CST4是一种新的、改进的CRC诊断标志物。基于CST4的组合模型在预测肠癌的发生方面具有一定的潜在价值。