Hong Junfeng, Lin Xiangwu, Hu Xinyu, Wu Xiaolong, Fang Wenzheng
Department of Ultrasound, Fuzhou General Hospital of Fujian Medical University, East Hospital Affiliated to Xiamen University (the 900th Hospital of The Joint Logistics Support Force of Chinese PLA), Dongfang Hospital, Xiamen University, Fuzhou, Fujian, 350025, China.
Department of Oncology, Fuzhou General Hospital of Fujian Medical University, East Hospital Affiliated to Xiamen University (the 900th Hospital of The Joint Logistics Support Force of Chinese PLA), Dongfang Hospital, Xiamen University, Fuzhou, Fujian, 350025, China.
Curr Gene Ther. 2021;21(4):280-289. doi: 10.2174/1566523220666201012151803.
Colorectal cancer (CRC) is a kind of tumor with high incidence and its treatment situation is still very difficult despite the constant renewal and development of treatment methods.
To assist the prognosis, monitoring and survival of CRC patients with a model.
In this study, we established a new prognostic model for CRC. Four groups of CRC data were accessed from the GEO database, and then differential analysis (logFoldChange>1, adjust- P<0.05) was carried out by using the limma package along with the RobustRankAggreg package used to identify the overlapping differentially expressed genes (DEGs). Univariate and multivariate Cox regression analyses were performed on the DEGs to screen the genes related to the patient's prognosis, and a five-gene prognostic prediction model (including RPX, CXCL13, MMP10, FABP4 and CLDN23) was constructed. Then, we further plotted ROC curves to evaluate the predictive performance of the five-gene prognostic signature in the TCGA data sets (the AUC values of 1, 3, 5-year survival were 0.68, 0.632, 0.675, respectively) and an external independent data set GSE2962 (the AUC values of 1, 3, 5-year survival were 0.689, 0.702, 0.631, respectively).
The results showed that the model could effectively predict the prognosis of CRC patients, which provides a robust predictive model for the prognosis of CRC patients.
The model could effectively predict the prognosis of CRC patients, which provides a robust predictive model for the prognosis of CRC patients.
结直肠癌（CRC）是一种高发性肿瘤，尽管治疗方法不断更新和发展，但其治疗情况仍然非常困难。
用一种模型辅助结直肠癌患者的预后、监测和生存情况。
在本研究中，我们建立了一种新的结直肠癌预后模型。从基因表达综合数据库（GEO数据库）获取四组结直肠癌数据，然后使用limma软件包进行差异分析（logFoldChange>1，校正P<0.05），同时使用RobustRankAggreg软件包来识别重叠的差异表达基因（DEGs）。对这些差异表达基因进行单变量和多变量Cox回归分析，以筛选出与患者预后相关的基因，并构建了一个包含五个基因的预后预测模型（包括RPX、CXCL13、MMP10、FABP4和CLDN23）。然后，我们进一步绘制ROC曲线，以评估五基因预后特征在癌症基因组图谱（TCGA）数据集（1、3、5年生存率的AUC值分别为0.68、0.632、0.675）和一个外部独立数据集GSE2962（1、3、5年生存率的AUC值分别为0.689、0.702、0.631）中的预测性能。
结果表明，该模型能够有效预测结直肠癌患者的预后，为结直肠癌患者的预后提供了一个可靠的预测模型。
该模型能够有效预测结直肠癌患者的预后，为结直肠癌患者的预后提供了一个可靠的预测模型。
