摘要
背景:结直肠癌(CRC)是一种高发肿瘤,尽管治疗方法不断更新和发展,但其治疗形势仍然十分困难。 目的:为结直肠癌患者的预后、监测和生存提供一个模型。 方法:在本研究中,我们建立了一个新的 CRC 预后模型。从GEO数据库中访问四组CRC数据,然后使用limma包和RobustRankAggreg包进行差异分析(logFoldChange>1,adjust-P<0.05),用于识别重叠差异表达基因(DEGs) )。对DEGs进行单变量和多变量Cox回归分析,筛选与患者预后相关的基因,构建五基因预后预测模型(包括RPX、CXCL13、MMP10、FABP4和CLDN23)。然后,我们进一步绘制了 ROC 曲线以评估 TCGA 数据集中五基因预后特征的预测性能(1、3、5 年生存期的 AUC 值分别为 0.68、0.632、0.675)和外部独立的数据集 GSE2962(1、3、5 年生存期的 AUC 值分别为 0.689、0.702、0.631)。 结果:结果表明,该模型能够有效预测CRC患者的预后,为CRC患者的预后提供了稳健的预测模型。 结论:该模型能够有效预测CRC患者的预后,为CRC患者的预后提供了稳健的预测模型。
关键词: 预后、特征、CRC、预测性、CLDN23、FABP4、MMP10、CXCL13。
Current Gene Therapy
Title:A Five-gene Signature for Predicting the Prognosis of Colorectal Cancer
Volume: 21 Issue: 4
关键词: 预后、特征、CRC、预测性、CLDN23、FABP4、MMP10、CXCL13。
摘要:
Background: 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.
Objective: To assist the prognosis, monitoring and survival of CRC patients with a model.
Methods: 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).
Results: 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.
Conclusion: The model could effectively predict the prognosis of CRC patients, which provides a robust predictive model for the prognosis of CRC patients.
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A Five-gene Signature for Predicting the Prognosis of Colorectal Cancer, Current Gene Therapy 2021; 21 (4) . https://dx.doi.org/10.2174/1566523220666201012151803
DOI https://dx.doi.org/10.2174/1566523220666201012151803 |
Print ISSN 1566-5232 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5631 |
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