[1]董雨晴,刘浩然,孙继宏,等.基于生物信息学构建铜代谢相关基因肺腺癌预后模型及免疫分析[J].中国医学物理学杂志,2024,41(10):1296-1306.[doi:DOI:10.3969/j.issn.1005-202X.2024.10.015]
　DONG Yuqing,LIU Haoran,SUN Jihong,et al.Prognostic model and immune analysis of copper metabolism related genes in lung adenocarcinoma based on bioinformatics[J].Chinese Journal of Medical Physics,2024,41(10):1296-1306.[doi:DOI:10.3969/j.issn.1005-202X.2024.10.015]
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基于生物信息学构建铜代谢相关基因肺腺癌预后模型及免疫分析()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
41卷
期数:
2024年第10期
页码:
1296-1306
栏目:
医学生物信息
出版日期:
2024-10-25

文章信息/Info

Title:
Prognostic model and immune analysis of copper metabolism related genes in lung adenocarcinoma based on bioinformatics
文章编号:
1005-202X（2024）10-1296-11
作者:
董雨晴; 刘浩然; 孙继宏; 张瀚文; 王萍玉
滨州医学院公共卫生学院， 山东 烟台 264003
Author(s):
DONG Yuqing;  LIU Haoran;  SUN Jihong;  ZHANG Hanwen;  WANG Pingyu
School of Public Health, Binzhou Medical University, Yantai 264003, China
关键词:
肺腺癌; 铜代谢相关基因; 预后模型; 免疫微环境; 生物信息学
Keywords:
Keywords: lung adenocarcinoma copper metabolism related gene prognostic model immune microenvironment bioinformatics
分类号:
R318
DOI:
DOI:10.3969/j.issn.1005-202X.2024.10.015
文献标志码:
A
摘要:
目的：构建预后风险模型探索铜代谢相关基因在肺腺癌（LUAD）中预后价值，为LUAD患者制定个性化治疗方案提供参考。方法：通过癌症基因组图谱（TCGA）数据库和基因型-组织表达资料库（GTEx）下载LUAD组织和癌旁或正常肺组织的RNA-seq数据，通过单因素Cox回归分析、Lasso分析和多因素Cox回归分析构建风险评分模型，绘制接受者操作特征（ROC）曲线及列线图模型对风险模型进行评价，并利用基因表达综合数据库（GEO）中的LUAD数据、肿瘤免疫单细胞中心（TISCH）单细胞测序分析、人类蛋白质图谱（HPA）免疫组化分析等进行外部验证。此外，对高、低风险组的免疫微环境和药物敏感性进行分析。结果：构建了一个由6个基因组成的风险模型，低风险组的总体生存率高于高风险组（P<0.001），训练集风险模型1、3、5年ROC曲线下的面积分别为0.729、0.749、0.707，C-index曲线的C指数为0.721（95%CI：0.678~0.764），免疫微环境在高、低风险组之间有统计学意义（P<0.001），药物敏感性分析发现高、低风险组患者对吉西他滨、吉非替尼、克唑替尼、沃利替尼等药物有统计学意义（P<0.001）。结论：基于6个铜代谢相关基因构建的风险模型能较为准确地预测LUAD患者预后，免疫微环境在高、低风险组之间有差异，高风险组患者对吉西他滨、吉非替尼、克唑替尼、沃利替尼等药物更为敏感，为LUAD患者的个性化治疗提供参考。
Abstract:
Abstract: Objective To construct a prognostic risk model for exploring the prognostic value of copper metabolism related genes (CMRGs) in lung adenocarcinoma (LUAD), thereby providing a reference for personalized treatment of LUAD patients. Methods The RNA-seq data of LUAD tissues and adjacent or normal lung tissues were downloaded from the Cancer Genome Atlas (TCGA) database and Genotype-tissue Expression (GTEx) database. The risk scoring model was established using univariate Cox regression analysis, Lasso analysis and multivariate Cox regression analysis, and the receiver operating characteristic (ROC) curves and nomogram were used to evaluate the model performance. The LUAD data in the Gene Expression Omnibus (GEO), the Tumor Immune Single-cell Hub (TISCH) single-cell sequencing analysis, and the Human Protein Atlas (HPA) immunohistochemistry analysis were used for external validation. Additionally, the immune microenvironment and drug sensitivity of high- and low-risk groups were analyzed. Results A risk model consisting of 6 genes was constructed. The overall survival rate of low-risk group was higher than that of high-risk group (P<0.001). ROC analysis showed that the area under curve of the risk model in training set reached 0.729, 0.749 and 0.707 at 1-, 3- and 5-year, respectively, and the C index of C-index curve was 0.721 (95%CI: 0.678-0.764). The immune microenvironment differed significantly between high- and low-risk groups (P<0.001), and the drug sensitivity analysis in high- and low-risk groups revealed that there was statistically significant for gemcitabine, gefitinib, crizotinib and savolitinib (P<0.001). Conclusion The risk model constructed with 6 CMRGs enable the prediction of the prognosis of LUAD patients. The immune microenvironment differs in high- and low-risk group, and high-risk patients are more sensitive to drugs such as gemcitabine, gefitinib, crizotinib and savolitinib, which provide a reference for the personalized treatment of LUAD patients.

相似文献/References:

[1]鲁晓腾,龚敬,聂生东. 基于CT图像特征的肺腺癌预后因素分析[J].中国医学物理学杂志,2019,36(3):291.[doi:DOI:10.3969/j.issn.1005-202X.2019.03.009]
　LU Xiaoteng,GONG Jing,NIE Shengdong. CT image feature-based analysis on the prognostic factors of lung adenocarcinoma[J].Chinese Journal of Medical Physics,2019,36(10):291.[doi:DOI:10.3969/j.issn.1005-202X.2019.03.009]
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[3]刘立威,林俊豪,陈逢生.ARHGAP10基因在肺腺癌中的表达及其机制[J].中国医学物理学杂志,2023,40(5):653.[doi:1005-202X（2023）05-0653-08]
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备注/Memo

备注/Memo:
【收稿日期】2024-05-20 【基金项目】国家自然科学基金（81772281）；山东省自然科学基金重点项目（ZR2020KH015） 【作者简介】董雨晴，硕士研究生，研究方向：流行病与卫生统计学方向，E-mail: 15653363613@163.com 【通信作者】王萍玉，博士，教授，研究方向：流行病与卫生统计学方向，E-mail: wpingyugirl@163.com
更新日期/Last Update: 2024-10-29