基于失巢凋亡相关基因的乳腺癌预后模型构建与验证  

Construction and validation of breast cancer prognosis model based on anoikis-related genes

作　　者：唐明政 徐京灏 李晓凤 荣耀 于博[1] 蔡辉[2,3] TANG Mingzheng;XU Jinghao;LI Xiaofeng;RONG Yao;YU Bo;CAI Hui(First Clinical Medical College,Gansu University of Chinese Medicine,Lanzhou 730000,China;Clinical Medical Center for General Surgery,Gansu Provincial Hospital,Lanzhou 730000,China;Key Laboratory of Molecular Diagnostics and Precision Medicine for Surgical Oncology in Gansu Province,Gansu Provincial Hospital,Lanzhou 730000,China)

机构地区：[1]甘肃中医药大学第一临床医学院,兰州730000 [2]甘肃省人民医院普外科临床医学中心,兰州730000 [3]甘肃省人民医院甘肃省外科肿瘤分子诊断与精准医学重点实验室,兰州730000

出　　处：《中国医科大学学报》2024年第4期315-323,共9页Journal of China Medical University

基　　金：国家自然科学基金(82360498);甘肃省联合科研基金重大项目(23JRRA1537);中央引导地方科技发展基金(ZYYDDFFZZJ-1);甘肃中医药大学研究生创新创业基金(38号)。

摘　　要：目的构建乳腺癌(BC)失巢凋亡相关基因(ARGs)预后模型,为临床实践提供更有效的指导。方法采用癌症基因组图谱(TCGA)和基因表达综合数据库(GEO)收集BC患者的转录组和临床数据。将ARGs分为A和B 2个分型,并进行生存分析和通路分析。采用Cox回归和LASSO回归分析生存预后、免疫微环境和肿瘤微环境的差异。构建ARGs相关的预后模型,并通过实时PCR验证预后相关ARGs在BC细胞中的表达。结果共得到10个与BC不良预后相关的ARGs,且这10个ARGs的风险评分均可作为BC患者的独立预后因素。随后将风险评分与BC临床病理特征相结合,构建列线图。决策曲线分析结果表明,该模型患者可以从临床治疗策略中受益。实时PCR分析结果显示,在BC细胞中YAP1、PIK3R1、BAK1、PHLDA2、EDA2R、CD24、SLC2A1和CDC25C表达水平上调,而SLC39A6和LAMB3表达水平下调。结论ARGs可作为生物标志物用于BC患者风险分层和生存预测,为BC患者个体化和精确治疗提供依据。Objective To construct a prognostic model of anoikis-related genes(ARGs)in breast cancer(BC)and provide more effective guidance for clinical practice.Methods The transcriptome and clinical data of patients with BC were collected from The Cancer Genome Atlas(TCGA)and Gene Expression Omnibus(GEO)databases.The ARGs were divided into types A and B,and survival and pathway analyses were performed.Cox regression and least absolute shrinkage and selection operator(LASSO)regression were used to analyze variations in the survival prognosis,immune microenvironment,and tumor microenvironment.The prognostic ARGs were used to construct a prognostic model.Finally,the expression of prognosis-related ARGs in BC cells was verified using real-time polymerase chain reaction(PCR).Results Ten ARGs related to poor prognosis of BC were identified,and the risk scores of these ten ARGs were used as independent prognostic factors for patients with BC.Finally,the risk score was combined with the clinicopathological features of BC to construct a nomogram.The results of the decision curve analysis showed that the patients in this model would benefit from clinical treatment strategies.Real-time PCR analysis showed that the expression levels of YAP1,PIK3R1,BAK1,PHLDA2,EDA2R,CD24,SLC2A1,and CDC25C were upregulated in BC cells,whereas SLC39A6 and LAMB3 in BC cells were downregulated.Conclusion ARGs can be used as biomarkers for risk stratification and survival prediction in patients with BC and provide a basis for individualized and precise treatment of these patients.

关 键 词：乳腺癌 失巢凋亡 免疫 预后 肿瘤微环境 

分 类 号：R737.9[医药卫生—肿瘤]