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基于失巢凋亡相关基因预测肺腺癌转移及预后模型的构建与验证

薛金丹 梁超 周家伟 刘亚峰 郭建强 韩涛 李芸芸 吴静 胡东

海南医学院学报2024,Vol.30Issue(14):1068-1081,14.
海南医学院学报2024,Vol.30Issue(14):1068-1081,14.DOI:10.13210/j.cnki.jhmu.20240412.002

基于失巢凋亡相关基因预测肺腺癌转移及预后模型的构建与验证

Establishment and validation of a gene signature for predicting metastasis and prognosis of lung adenocarcinoma based on anoikis-related genes

薛金丹 1梁超 1周家伟 1刘亚峰 2郭建强 1韩涛 1李芸芸 1吴静 3胡东3

作者信息

  • 1. 安徽理工大学医学院,安徽 淮南 232000
  • 2. 安徽理工大学医学院,安徽 淮南 232000||安徽理工大学附属肿瘤医院,安徽 淮南 232000
  • 3. 安徽理工大学医学院,安徽 淮南 232000||安徽理工大学安徽省职业健康安全工程实验室,安徽 淮南 232000||安徽理工大学工业粉尘防控与职业安全健康教育重点实验室,安徽 淮南 232000
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摘要

Abstract

Objective:Anoikis is a programmed cell death process that plays a crucial role in tumor metastasis.Lung adenocar-cinoma frequently results in multi-organ metastasis,which significantly impacts patient prognosis.This study aims to identify new anoikis-related gene signature to predict metastasis and prognosis of lung adenocarcinoma.Methods:The study obtained gene ex-pression profiles and clinical data of patients with metastatic and non-metastatic lung adenocarcinoma from the TCGA and GEO da-tabases.Additionally,293 genes related to anoikis were downloaded from the GeneCard database.Unsupervised cluster analysis was used to divide patients with metastatic lung adenocarcinoma into two tumor subtypes.The study assessed immunoinfiltration and immune cell function in two groups using the TIMER database and single sample gene set enrichment analysis(ssGSEA).A prognostic model of genes related to anoikis was constructed using the minimum absolute contraction and selection algorithm(LASSO)and Cox regression model,which was then validated using external data sets.The predictive power of the model was further evaluated using ROC curves and a nomogram.The study evaluated the differences in immunotherapy and drug therapy be-tween high-risk and low-risk groups.Selective gene expression was verified using real-time quantitative fluorescent PCR(qRT-PCR),and immune cell infiltration was verified using multiple immunofluorescence histochemistry.Results:The two mo-lecular subtypes exhibited significant differences in clinicopathological features,prognosis,and immune cell infiltration.Lasso and multivariate Cox regression identified three prognostic genes related to anoikis(TLE1,EIF2AK3 and BIRC3),and a risk model was constructed using these genes.The patients were categorized into high-and low-risk groups based on their median risk scores.The low-risk group exhibited higher overall survival(OS)time,immune activity,tumor mutation burden(TMB),and PD1/PD-L1 expression,which is consistent with a better response to immune checkpoint inhibitors.The nomogram demonstrates the model's superior predictive value.The expression of three prognostic genes was higher in lung adenocarcinoma cell lines and tis-sue,as determined by qRT-PCR.Furthermore,this expression was positively correlated with the degree of immune cell infiltra-tion.Conclusion:This study has established a prognostic risk model characterized by anoikis-related genes.The model has good prognostic value in patients with lung adenocarcinoma and can be used as a potential diagnostic marker and therapeutic target for evaluating patient prognosis.

关键词

肺腺癌/失巢凋亡/肿瘤转移/预后模型/免疫浸润

Key words

Lung adenocarcinoma/Anoikis/Cancer metastasis/Prognostic signature/Immune infiltration

分类

临床医学

引用本文复制引用

薛金丹,梁超,周家伟,刘亚峰,郭建强,韩涛,李芸芸,吴静,胡东..基于失巢凋亡相关基因预测肺腺癌转移及预后模型的构建与验证[J].海南医学院学报,2024,30(14):1068-1081,14.

基金项目

This study was supported by National Natural Science Foundation of China(81971483)国家自然科学基金资助项目(81971483) (81971483)

海南医学院学报

OA北大核心CSTPCD

1007-1237

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