[1]操利超,巴 颖,卢晓萍,等.基于TCGA和GEO数据库构建结肠癌预后模型[J].医学信息,2021,34(24):27-32.[doi:10.3969/j.issn.1006-1959.2021.24.006]
　CAO Li-chao,BA Ying,LU Xiao-ping,et al.Prognostic Model of Colon Cancer Based on TCGA and GEO Database[J].Medical Information,2021,34(24):27-32.[doi:10.3969/j.issn.1006-1959.2021.24.006]
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基于TCGA和GEO数据库构建结肠癌预后模型()
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医学信息[ISSN:1006-1959/CN:61-1278/R]

卷:
34卷
期数:
2021年24期
页码:
27-32
栏目:
论著
出版日期:
2021-12-15

文章信息/Info

Title:
Prognostic Model of Colon Cancer Based on TCGA and GEO Database
文章编号:
1006-1959（2021）24-0027-06
作者:
操利超; 巴 颖; 卢晓萍; 等
（深圳市核子基因科技有限公司，广东 深圳 518071）
Author(s):
CAO Li-chao; BA Ying; LU Xiao-ping; et al.
(Shenzhen Nucleus Gene Technology Co., Ltd.,Shenzhen 518071,Guangdong,China)
关键词:
结肠癌; 预后模型; 生物信息学; 病理分期; 复发
Keywords:
Colorectal cancer; Prognostic model; Bioinformatics; Pathological staging; Recurrence
分类号:
R714.24
DOI:
10.3969/j.issn.1006-1959.2021.24.006
文献标志码:
A
摘要:
目的 利用TCGA和GEO数据库中的基因表达数据和临床信息，挖掘结肠癌预后相关的基因，并构建和评估结肠癌预后模型。方法 从GEO数据库中下载结肠癌相关的基因表达矩阵，包括GSE44076、GSE28000和GSE39582，从TCGA数据库中下载结肠癌相关的mRNA表达数据矩阵和临床信息，通过NCBI数据库中在线分析软件GEO2R对三个GEO数据集进行差异基因分析，利用R包limma对TCGA数据集进行差异基因分析，获取共同的差异表达基因。通过单因子回归、LASSO回归和多因子回归分析构建结肠癌相关的预后模型，进一步结合临床特征构建列线图模型，综合评估预后模型的性能。结果 成功构建结肠癌相关的预后模型，构建的预后模型ROC曲线下面积在3年时为0.628，4年时为0.678，5年时为0.730；Wilcoxon检验显示，较高的风险评分与较高的T分期（P=0.049）、N分期（P=0.0015）、M分期（P=0.003）和病理分期（P=0.0019）相关；结合预后风险评分模型、年龄、性别和病理分期等级构建了列线图，模型的C-index从0.63增加至0.74。结论 本次构建的结肠癌预后模型在评估结肠癌患者复发风险分层、肿瘤分期等方面具有潜在意义。
Abstract:
Objective To explore the prognostic genes of colon cancer by using gene expression data and clinical information in TCGA and GEO databases, and to construct and evaluate the prognostic model of colon cancer.Methods The gene expression matrix related to colon cancer was downloaded from the GEO database, including GSE44076, GSE28000 and GSE39582. The mRNA expression data matrix and clinical information related to colon cancer were downloaded from the TCGA database. The differential gene analysis of the three GEO data sets was carried out through the online analysis software GEO2R in the NCBI database. The differential gene analysis of the TCGA data set was carried out R package limma to obtain the common differential expression genes. Prognostic models related to colon cancer were constructed through single factor regression, LASSO regression and multi-factor regression analysis, and the line chart model was further constructed combined with clinical characteristics to comprehensively evaluate the performance of the prognosis model.Results The colon cancer-related prognostic model was successfully constructed. The area under the ROC curve of the prognostic model was 0.628 at 3 years, 0.678 at 4 years and 0.730 at 5 years. Wilcoxon test showed that higher risk scores were correlated with higher T staging (P=0.049), N staging (P=0.0015), M staging (P=0.003) and pathological staging (P=0.0019). Combined with the prognostic risk score model, age, gender and pathological staging level, a line chart was constructed, and the C-index of the model increased from 0.63 to 0.74.Conclusion The constructed colon cancer prognosis model has potential significance in evaluating the recurrence risk stratification and tumor staging of colon cancer patients.

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更新日期/Last Update: 1900-01-01