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《天津医科大学学报》[ISSN:1006-8147/CN:12-1259/R]

卷:

28卷

期数:

2022年01期

页码:

20-26

栏目:

生物信息学专题

出版日期:

2022-01-20

文章信息/Info

Title:

Identification of a risk score prognostic model of hepatocellular carcinoma based on tumor mutation burden

文章编号:

1006-8147（2022）01-0020-07

作者:

王凤松¹; 朱刘洋¹; 白易²; 张雅敏²

（1.天津医科大学一中心临床学院，天津300192；2.天津市第一中心医院肝胆外科，天津300192）

Author(s):

WANG Feng-song¹; ZHU Liu-yang¹; BAI Yi²; ZHANG Ya-min²

（1.First Central Clinical College，Tianjin Medical University，Tianjin 300192，China；2.Department of Hepatobiliary Surgery，Tianjin First Central Hospital，Tianjin 300192，China）

关键词:

肝细胞癌; TCGA数据库; 肿瘤突变负荷; 预后模型

Keywords:

hepatocellular carcinoma; TCGA database; tumor mutation burden; prognostic model

分类号:

R735.7

DOI:

-

文献标志码:

A

摘要:

目的：通过分析癌症基因组图谱数据库（TCGA）中肿瘤突变负荷（TMB）数据，构建并验证肝细胞癌（HCC）风险评分预后模型。方法：从TCGA数据库下载HCC患者体细胞突变数据、基因表达数据和临床信息。绘制HCC患者基因突变图谱，分析TMB水平与HCC患者预后的关系。利用生物信息学分析筛选预后基因并构建HCC风险评分预后模型，单因素及多因素分析评估模型预测能力。结果：基因突变图谱揭示了HCC患者基因突变特征。Kaplan-Meier分析显示低TMB组HCC患者总体生存率较高（χ2=6.632，P=0.01），且较高的TMB水平与高龄（χ2=10.328，P=0.001 7）、男性（χ2=9.384，P=0.002 9）和N0分期（χ2=4.723，P=0.03）有关。将所有HCC样本随机分为训练集（n=177）和验证集（n=178），在训练集中，生物信息学方法确定了FABP6、PFKP和PROK1 3个预后基因并构建HCC风险评分预后模型：风险评分=（0.132 08 × FABP6表达量）+（0.153 83×PFKP表达量）+（-0.180 47×PROK1表达量）。将训练集及验证集中样本按风险评分分为高风险组和低分险组，训练集中低风险组HCC患者总体生存率较高（χ2=66.725，P<0.000 1），验证集中结果相同（χ2=38.364，P<0.000 1）。单因素及多因素分析显示，风险评分（HR＝2.016，95%CI：1.356～2.997，P<0.001）、病理分期（HR＝1.591，95%CI：1.274～1.987，P<0.001）是HCC独立的预后因素。结论：TMB水平与HCC预后相关，风险评分预后模型具有良好的预后预测能力，是HCC患者的独立预后因素。

Abstract:

Objective： To construct and verify a risk score prognostic model of hepatocellular carcinoma（HCC） based on tumor mutation burden（TMB） data of the Cancer Genome Atlas（TCGA）. Methods： Somatic mutation data，gene expression data and clinical information of HCC patients were downloaded from TCGA database. The gene mutation profiles of HCC patients were made，and the relationship between the level of TMB and the prognosis of HCC was analyzed. Prognostic genes were identified and HCC risk score prognosis model was constructed by bioinformatics analysis.Univariate and multivariate analysis were used to evaluate the predictive ability of the model. Results：The gene mutation profiles revealed the characteristics of gene mutation in patients with HCC. Kaplan-Meier analysis showed that the overall survival rate of HCC patients with low TMB was higher（χ2=6.632，P=0.01），and the higher TMB level was associated with older age（χ2=10.328，P=0.001 7），male（χ2=9.384，P=0.002 9） and N0 stage（χ2=4.723，P=0.03）. All HCC samples were randomly divided into training set （n=177） and verification set（n=178）.Three prognostic genes（FABP6，PFKP and PROK1）were determined by bioinformatics method in the training set，and the risk score prognostic model of HCC was constructed as follows：risk score=（0.132 08×FABP6 expression）+（0.153 83×PFKP expression） +（-0.180 47×PROK1 expression）. The training set and validation set samples were divided into high-risk group and low-risk group according to risk score.In the training set，the overall survival rate of the low-risk group was higher（χ2=66.725，P<0.000 1），and the result was same in the validation set（χ2=38.364，P<0.000 1）. Univariate and multivariate analysis showed that risk score（HR＝2.016，95%CI：1.356-2.997，P<0.001） and pathological stage（HR＝1.591，95%CI：1.274-1.987，P<0.001） were independent prognostic factors of HCC.Conclusion： The level of TMB is related to the prognosis of HCC. The risk score prognostic model has a good ability to predict the prognosis and is an independent prognostic factor for patients with HCC.

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备注/Memo

备注/Memo:

基金项目 天津市科技计划项目（19ZXDBSY00010）
作者简介 王凤松（1981-），男，硕士在读，研究方向：肝胆肿瘤；通信作者：张雅敏，E-mail：13802122219@163.com。

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更新日期/Last Update: 2022-01-20