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肝细胞癌mRNA疫苗的肿瘤相关抗原筛选及验证
作者:罗密1  李军伟2  易永祥1 3 
单位:1. 南京医科大学 公共卫生学院, 江苏 南京 211166;
2. 南京市第二医院 传染病科, 江苏 南京 211103;
3. 南京市第二医院 南京医科大学公共卫生学院联合培养基地, 江苏 南京 210008
关键词:肝细胞癌 mRNA疫苗 肿瘤相关抗原筛选 生物信息学 
分类号:R735.7
出版年·卷·期(页码):2026·45·第四期(597-607)
摘要:

目的: 通过生物信息学数据筛选能利用于肝细胞癌(HCC) mRNA疫苗的肿瘤相关抗原(TAAs)。方法: 整合TCGA、cBioPortal数据库分析HCC基因突变与异常表达情况;利用GEPIA 2.0和Kaplan-Meier评估基因过表达对预后的影响;通过TIMER分析基因与抗原递呈细胞(APCs)免疫浸润的相关性;采用TSNAdb预测抗原免疫原性;结合临床转录组数据及人类蛋白质图谱数据库(HPA)进行表达验证与免疫组化分析。结果: 对TCGA-LIHC的数据初步筛选获得1 485个与HCC相关的过表达基因;生存分析发现108个与患者总生存期(OS)和无复发生存期(RFS)相关的基因。两者取交集得到33个潜在TAAs;进一步分析其与APCs免疫浸润的关联性、与HLA Ⅰ类分子的结合能力,确定核转运蛋白α2亚基(KPNA2)、细胞周期蛋白B1(CCNB1)、细胞周期蛋白依赖性激酶1(CDK1)、核糖体生物合成调控因子1(PES1)、极光激酶A(AURKA)和检查点激酶1(CHEK1)6个HCC-TAAs可作为HCC mRNA疫苗的候选靶点;并在免疫组化结果和小样本的临床转录组测序分析中得到较好的一致性验证。结论: 通过多维生物信息学数据能够筛选具有潜力的HCC-TAAs,为后续mRNA疫苗的开发和临床转化应用提供参考依据。

Objective: To screen tumor-associated antigens(TAAs) applicable to mRNA vaccines for hepatocellular carcinoma(HCC) using bioinformatics data. Methods: Gene mutations and abnormal expression in HCC were analyzed by integrating TCGA and cBioPortal databases. The impact of gene overexpression on prognosis was evaluated using GEPIA 2.0 and Kaplan-Meier analysis. The correlation between gene expression and immune infiltration of antigen-presenting cell(APC) was analyzed via TIMER. Antigen immunogenicity was predicted using TSNAdb. Expression validation and immunohistochemical analysis were performed using clinical transcriptomic data and the Human Protein Atlas(HPA). Results: Preliminary screening of TCGA-LIHC data identified 1 485 genes overexpressed in HCC. Survival analysis revealed 108 genes associated with both overall survival(OS) and recurrence-free survival(RFS) of patients. Intersection of these two datasets yielded 33 potential TAAs. Further analysis of their immune infiltration correlation with APCs and their binding affinity to HLA class Ⅰ molecules identified six HCC-TAAs as candidate targets for HCC mRNA vaccines: karyopherin subunit alpha 2(KPNA2), cyclin B1(CCNB1), cyclin-dependent kinase 1(CDK1), pescadillo ribosomal biogenesis factor 1(PES1), aurora kinase A(AURKA), and checkpoint kinase 1(CHEK1). These findings were consistently validated by immunohistochemistry and transcriptomic data. Conclusion: Multi-dimensional bioinformatics data enable the screening of potential HCC-TAAs, providing a reference basis for the development of mRNA vaccines and their clinical translation.

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