原创论文(Original Article)

基于生物信息学方法的胰腺导管腺癌预后风险标志物筛选

Published at: 2017年第26卷第9期

张志鹏 1 , 陆晔斌 1 , 陈泓西 1 , 夏华 1 , 孙维佳 1
1 中南大学湘雅医院 胆胰外科,湖南 长沙 410008
通讯作者 维佳 孙 Email: sunweijia2009@126.com
DOI: 10.3978/j.issn.1005-6947.10.3978/j.issn.1005-6947.2017.09.004
基金:
湖南省重点研发计划应用基础研究重点项目 2016JC2040

摘要

目的:应用生物信息学方法筛选胰腺导管腺癌的预后风险标志物。方法:从TCGA数据库下载胰腺导管腺癌患者的临床资料、miRNA和基因表达谱数据。然后应用弹性网络Cox比例风险回归(EN-Cox)模型、受试者工作特征(ROC)曲线和生存分析筛选出与胰腺导管腺癌预后风险明显相关的miRNA和基因。最后,对筛选到的预后风险基因与miRNA的潜在靶基因进行文献挖掘及功能分析。结果:经过数据预处理,共得到137例胰腺导管腺癌患者的完整临床资料及797个miRNA和19 969个基因表达谱数据。基于λ=0.107的参数值,EN-Cox分析筛选出了包括54个基因和5个miRNA在内的59个潜在的预后风险因素;根据ROC曲线确定病例分组的截断值,并绘制Kaplan-Meier曲线,最后共筛选出17个胰腺导管腺癌预后风险标志物(均P<0.05),包括16个基因和1个miRNA(miRNA-125a)。在16个预后风险基因中,谷胱甘肽S转移酶μ4(GSTM4)、可诱导T细胞共刺激分子配体(ICOSLG)、精子发生相关2(SPATA2)同时又是miRNA-125a的靶基因;只有GATA结合蛋白1(GATA1)为转录因子编码基因。结论:所筛选的因子在胰腺癌中的作用还有待阐明,并有望成为判断胰腺导管腺癌预后的指标及治疗靶点。


Screening of prognostic risk markers for pancreatic ductal adenocarcinoma based on bioinformatics approaches

Abstract

Objective: To identify the prognostic risk markers for pancreatic ductal adenocarcinoma (PDAC) through bioinformatics approaches. Methods: The clinical information and data of miRNA and gene expression profiles of PDAC patients were downloaded from TCGA website. Then, the miRNAs and genes significantly related to the prognostic risk of PDAC were screened successively by Elastic Net Cox’s proportional risk regression hazards model (EN-Cox), the receiver operating characteristic (ROC) curve and survival analyses. Finally, literature mining and function analyses were conducted on the significant prognostic risk genes and the potential target genes of the significant prognostic risk miRNAs. Results: After data preprocessing, the complete clinical records and data of expression profiles of total of 797 miRNAs and 19 969 genes in 137 PDAC patients were obtained. Based on the parameter λ (0.107), 59 potential prognostic risk factors that included 54 genes and 5 miRNAs were screened via EN-Cox analysis. After grouping of the patients according to the cutoff values derived from the ROC curves and then drawing of Kaplan-Meier curves, 17 significant prognostic risk markers were finally identified (all P<0.05), including 16 genes and 1 miRNA (miRNA-125a). Among the 16 prognostic risk genes, glutathione S-transferase mu 4 (GSTM4), inducible T-cell co-stimulator ligand (ICOSLG) and spermatogenesis associated 2 (SPATA2) were simultaneously the target genes of miRNA-125a; GATA binding protein 1 (GATA1) was the only one transcription factor encoding gene. Conclusion: The functions of these screened candidates in PDAC still need to be elucidated, and they may probably be used as prognostic risk indicators and even therapeutic targets of PDAC.


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引用

引用本文: 志鹏 张, 晔斌 陆, 泓西 陈, 华 夏, 维佳 孙. 基于生物信息学方法的胰腺导管腺癌预后风险标志物筛选[J]. 中国普通外科杂志, 2017, 26(9): 1097-1104.
Cite this article as: ZHANG Zhipeng, LU Yebin, CHEN Hongxi, XIA Hua, SUN Weijia . Screening of prognostic risk markers for pancreatic ductal adenocarcinoma based on bioinformatics approaches [J]. Chin J Gen Surg, 2017, 26(9): 1097-1104.