[1]李 敖,王玉然,王文浩.基于公共数据库分析自噬相关基因在肺腺癌患者中的预后意义[J].医学信息,2022,35(22):17-22.[doi:10.3969/j.issn.1006-1959.2022.22.003]
　LI Ao,WANG Yu-ran,WANG Wen-hao.Prognostic Significance of Autophagy-related Genes in Patients with Lung Adenocarcinoma Based on Public Database Analysis[J].Journal of Medical Information,2022,35(22):17-22.[doi:10.3969/j.issn.1006-1959.2022.22.003]
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基于公共数据库分析自噬相关基因在肺腺癌患者中的预后意义()
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医学信息[ISSN:1006-1959/CN:61-1278/R]

卷:
35卷
期数:
2022年22期
页码:
17-22
栏目:
生物信息学
出版日期:
2022-11-15

文章信息/Info

Title:
Prognostic Significance of Autophagy-related Genes in Patients with Lung Adenocarcinoma Based on Public Database Analysis
文章编号:
1006-1959（2022）22-0017-06
作者:
李 敖; 王玉然; 王文浩
（潍坊医学院附属医院肿瘤科1，放疗科2，山东 潍坊 261041）
Author(s):
LI Ao; WANG Yu-ran; WANG Wen-hao
(Department of Medical Oncology1,Department of Radiotherapy2,Affiliated Hospital of Weifang Medical University,Weifang 261041,Shandong,China)
关键词:
肺腺癌; 自噬相关基因; 预后模型; 生物信息学
Keywords:
Lung adenocarcinoma; Autophagy-related genes; Prognostic model; Bioinformatics
分类号:
R734.2
DOI:
10.3969/j.issn.1006-1959.2022.22.003
文献标志码:
A
摘要:
目的 利用生物信息学技术对自噬相关基因（ATGs）进行分析，并建立预测肺腺癌患者预后的基因表达模型。方法 利用TCGA数据库筛选肿瘤组织和正常组织中差异表达的ATGs，进行GO和KEGG富集分析确定与ATGs相关的信号通路，再进行单变量和多变量Cox回归分析确定与生存率相关的ATGs，最后根据中位风险评分进行生存分析，评价风险评分的预后价值。结果 共筛选出200个ATGs在肺腺癌中差异表达。30个ATGs被筛选出作为与预后相关的基因。GO和KEGG富集分析均显示，ATGs与自噬相关信号通路有关。单因素Cox回归分析显示，从肺腺癌TCGA数据库中获得了21个预后相关ATGs，其中9个ATGs（ATG4A、NLRC4、PRKCD、DAPK2、SIRT2、CCR2、ATG16L2、DLC1、DRAM1）被认为是保护性基因（HR＜1），其余12个ATGs（ITGB4、BIRC5、CTSL、SPHK1、APOL1、ITGA6、ITGB1、GAPDH、ERO1A、EIF2S1、MBTPS2、ST13）被认为是危险性基因（HR＞1）。多因素Cox回归分析显示，低风险组和高风险组中包含的8个ATGs（ATG4A、CCR2、MBTPS2、APOL1、ERO1A、SPHK1、ST13和ITGA6）的表达差异，而高危组患者倾向于表达危险基因，而低危组患者倾向于表达保护基因。风险评分是肺腺癌TCGA的独立预后指标（P＜0.05），风险评分（AUC=0.763）具有更好的预测性能。结论 本研究构建了一个基于8个ATGs的预后特征模型，为肺腺癌患者的预后评估提供了方向，并为治疗方案提供了潜在研究靶点。
Abstract:
Objective To analyze autophagy-related genes (ATGs) by bioinformatics and establish a gene expression model for predicting the prognosis of patients with lung adenocarcinoma.Methods The TCGA database was used to screen differentially expressed ATGs in tumor tissues and normal tissues. GO and KEGG enrichment analysis was performed to determine the signaling pathways associated with ATGs. Univariate and multivariate Cox regression analysis was performed to determine ATGs associated with survival rate. Finally, survival analysis was performed according to the median risk score to evaluate the prognostic value of the risk score.Results A total of 200 ATGs were differentially expressed in lung adenocarcinoma. Thirty ATGs were screened as genes associated with prognosis. GO and KEGG enrichment analysis showed that ATGs were related to autophagy-related signaling pathways. Univariate Cox regression analysis showed that 21 prognostic ATGs were obtained from the TCGA database of lung adenocarcinoma, of which 9 ATGs (ATG4A, NLRC4, PRKCD, DAPK2, SIRT2, CCR2, ATG16L2, DLC1, DRAM1) were considered to be protective genes (HR<1), the remaining 12 ATGs (ITGB4, BIRC5, CTSL, SPHK1, APOL1, ITGA6, ITGB1, GAPDH, ERO1A, EIF2S1, MBTPS2, ST13) were considered as risk genes (HR>1). Multivariate Cox regression analysis showed that the expression of 8 ATGs (ATG4A, CCR2, MBTPS2, APOL1, ERO1A, SPHK1, ST13 and ITGA6) contained in the low-risk group and the high-risk group was different, while the patients in the high-risk group tended to express risk genes, while the patients in the low-risk group tended to express protective genes. Risk score was an independent prognostic indicator of TCGA in lung adenocarcinoma (P<0.05), and risk score (AUC=0.763) had better predictive performance.Conclusion This study constructs a prognostic feature model based on 8 ATGs, which provides a direction for the prognosis evaluation of lung adenocarcinoma patients and a potential target for treatment.

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更新日期/Last Update: 1900-01-01