吉林大学学报(医学版) ›› 2023, Vol. 49 ›› Issue (1): 139-149.doi: 10.13481/j.1671-587X.20230118

• 临床研究 • 上一篇    

基于肺腺癌组织中可变剪接数据构建剪接因子-可变剪接调控网络的生物信息学分析

唐吴月1,2,李硕杰1,2,庞丽娟1,2,3()   

  1. 1.石河子大学医学院病理学系,新疆 石河子 832002
    2.石河子大学医学院第一附属医院病理科,新疆 石河子 832002
    3.广东医科大学湛江中心人民医院病理科,广东 湛江 524000
  • 收稿日期:2022-01-03 出版日期:2023-01-28 发布日期:2023-02-03
  • 通讯作者: 庞丽娟 E-mail:ocean123456@shzu.edu.cn
  • 作者简介:唐吴月(1994-),女,山东省德州市人,在读硕士研究生,主要从事分子病理诊断方面的研究。
  • 基金资助:
    国家自然科学基金项目(82060054)

Bioinformatics analysis of splicing factor-alternative splicing regulatory network based on alternative splicing data in lung adenocarcinoma tissue

Wuyue TANG1,2,Shuojie LI1,2,Lijuan PANG1,2,3()   

  1. 1.Department of Pathology, School of Medical Sciences, Shihezi University, Shihezi 832002, China
    2.Department of Pathology, First Affiliated Hospital, School of Medical Sciences, Shihezi University Shihezi 832002, China
    3.Department of Pathology, Central People’s Hospital of Zhanjiang, Guangdong Medical University, Zhanjiang 524000, China
  • Received:2022-01-03 Online:2023-01-28 Published:2023-02-03
  • Contact: Lijuan PANG E-mail:ocean123456@shzu.edu.cn

摘要:

目的 利用生物信息学方法筛选与肺腺癌(LUAD)患者生存相关的可变剪接(AS)事件,构建剪接因子(SF)-AS调控网络,为LUAD患者的预后评价提供新思路。 方法 由癌症基因组图谱(TCGA)数据库中下载LUAD患者转录组数据和临床数据。从SF表达和RNA靶点(SpliceAid2)数据库中下载LUAD患者AS数据。对LUAD患者生存相关AS事件进行单因素Cox回归分析。采用LASSO回归分析和多因素Cox回归分析构建LUAD患者预后风险模型,基于该模型计算每种AS事件的风险评分,采用 Kaplan-Meier(K-M)生存分析和受试者工作特征曲线(ROC)评价模型的可靠性。通过Cox 回归分析风险模型、临床参数与LUAD患者独立预后的关系。采用Pearson检验对SF和与预后相关的AS事件进行相关性分析,并通过Cytoscape软件构建SF-AS互作网络。 结果 筛选获取与生存相关的AS事件43 948个,共7种类型,主要以外显子活跃(ES)事件和可变终止子(AT)事件为主。构建AS事件预后风险模型,基于该模型风险评分将LUAD患者分为高风险组和低风险组,K-M生存分析,高风险组LUAD患者总生存(OS)率较低风险组低(P<0.05)。ROC曲线分析,LUAD患者预后风险模型预测性良好,曲线下面积(AUC)为0.824。SF-AS调控网络,12个与预后相关SFs正向或负向调节AS事件,可预测LUAD患者的不良预后。 结论 筛选了与LUAD患者预后相关的AS事件和上游的调控因子SF,构建了SF-AS网络,为进一步研究AS事件与LUAD患者预后的相关性提供理论依据。

关键词: 生物信息学技术, 肺腺癌, 可变剪接, 剪接因子, 癌症基因组图谱数据库

Abstract:

Objective To screen the survival-associated alternative splicing (AS) events in the lung adenocarcinoma (LUAD) patients using bioinformatics method and construct the splicing factor (SF)-AS regulatory network, and to provide a new approach for the prognostic evaluation of the LUAD patients. Methods The transcriptome data and clinical data of the LUAD patients were downloaded from The Cancer Genome Atlas (TCGA) database, and the AS data of the LUAD patients were downloaded from the SF expression data and RNA target motifs(SpliceAid2)database. The survival-associated AS events of the LUAD patients were analyzed by univariate Cox regression analysis. The prognostic risk model of the LUAD patients was established by LASSO regression analysis and multivariate Cox regression analysis,and the risk score of each AS event was calculated based on the model. Kaplan-Meier (K-M) survival analysis and receiver operating characteristic (ROC) curve were used to evaluate the reliability of the model. The relationships between risk model or clinical parameters and independent prognosis of the LUAD patients were analyzed by using Cox regression analysis. The Pearson test was used to analyze the correlation of SF with AS events associated with prognosis. Cytoscape software was utilized to construct the SF-AS interaction network. Results A total of 43 948 cases of survival-associated AS events were screened, including 7 types of events. Exon skip (ES) events and alternate terminator (AT) events were the main events. The prognostic risk model of AS events was constructed, and the LUAD patients were divided into high and low risk groups based on the risk scores of the model.The K-M survival analysis results showed that the overall survival (OS) rate of the LUAD patients in high risk group was lower than that in low risk group (P<0.05).The ROC curve analysis indicated that prognostic risk model of the LUAD patients had a good predictive effect,and the area under curve (AUC) was 0.824. The SF-AS regulatory network showed that 12 prognosis-related SFs modulated AS events positively or negatively,and they could predict the poor prognosis of the LUAD patients. Conclusion The prognostis-related AS events of LUAD patients and their upstream regulatory factor SF are screened,the SF-AS network is constructed,and the study provides the theoretical basis for further research on the correlation of AS events with prognosis of the LUAD patients.

Key words: Bioinformatics analysis, Lung adenocarcinoma, Alternative splicing, Splicing factor, The Cancer Genome Atlas database

中图分类号: 

  • R738.6