机构地区:[1]安徽中医药大学附属芜湖市中医医院专业学位硕士研究生培养基地,安徽芜湖241003 [2]安徽中医药高等专科学校附属医院/芜湖市中医医院泌尿外科,安徽芜湖241001 [3]安徽中医药高等专科学校附属医院/芜湖市中医医院皮肤科,安徽芜湖241001 [4]安徽中医药高等专科学校附属医院/芜湖市中医医院肛肠科,安徽芜湖241001 [5]昆明医科大学海源学院,昆明650106
出 处:《现代检验医学杂志》2024年第1期29-35,66,共8页Journal of Modern Laboratory Medicine
基 金:安徽省高等学校科学研究项目(2022AH052642):个体化预测上尿路结石术后留置双J管致严重LUTS的风险Nomogram模型的构建与验证;芜湖市科技成果转化项目(2021cg07):芜湖市5G+中医治未病健康管理服务云平台的构建与示范研究;芜湖市科技成果转化项目(2022cg37):一期输尿管软镜碎石术临床应用及影响因素分析。
摘 要:目的构建膀胱尿路上皮癌(bladder urothelial carcinoma,BLCA)具有预后价值的内源竞争性核糖核酸(competing endogenous RNA,ceRNA)调控网络,分析关键信使RNA(messenger RNA,mRNA)与免疫功能的关系。方法UCSC Xena数据库下载404例BLCA患者和28例正常人的mRNA表达数据,通过差异分析筛选关键mRNA。ENCORI数据库中查找与关键mRNA结合的微小核糖核酸(micro RNA,miRNA)以及与miRNA结合的长链非编码核糖核酸(long non-coding RNA,LncRNA)。TCGA数据库下载miRNA和LncRNA的表达数据,对关键mRNA与所有miRNA以及mi RNA与所有LncRNA进行共表达分析,筛选出关键的miRNA和LncRNA。根据关键mRNA,miRNA和LncRNA在肿瘤患者和正常人之间表达量的差异进行生存分析,最后构建了ceRNA调控网络。借助TIMER 2.0数据库,分析关键mRNA与免疫细胞、免疫检查点(CD274,PDCD1,CTLA4)以及免疫细胞标记基因(immunomarker genes,IG)的相关性。结果筛选出关键mRNA*共22个,其中差异显著性最高的是脯氨酸3-羟化酶4(proline3-hydroxylase 4,P3H4)。在BLCA中,P3H4表达高,在高表达组患者的生存时间较短。以关键mRNA为中心环节,共筛选出33个miRNA和14个LncRNA。经过共表达分析和生存分析后,筛选出具有预后价值的关键miRNA和关键LncRNA分别为hsa-miR-151a-3p和MIR100HG。上述分析结果差异具有统计学意义(均Ρ<0.05)。综合以上结果,构建了包含1个mRNA,1个miRNA和1个LncRNA的ceRNA调控网络。免疫分析首次在BLCA肿瘤微环境中发现了与P3H4表达量呈显著正相关的双阳性T细胞。此外还有3种免疫细胞(肿瘤相关性中性粒细胞、肿瘤相关巨噬细胞、树突状细胞)、3个免疫检查点(CD274,PDCD1,CTLA4)以及15个IG与P3H4相关度显著,这些差异具有统计学意义(均Ρ<0.01)。结论该研究有助于揭示BLCA的进展机制,构建的ceRNA网络及免疫分析,可为BLCA患者的诊断、治疗、预测提供新的生物学靶点和方向。Objective To construct a regulatory network of competing endogenous RNA(ceRNA)with prognostic value for bladder urothelial carcinoma(BLCA),and analyze the relationship between key messenger RNA(mRNA)and immune function.Methods The UCSC Xena database was used to download mRNA expression data from 404 BLCA patients and 28 normal individuals and key mRNAs were screened by differential analysis.ENCORI database was utilized to search microRNAs(miRNAs)that bind to key mRNAs and all long non-coding RNAs(LncRNAs)that bind to miRNAs.The expression data of miRNA and LncRNA were downloaded from TCGA database,co-expression analysis was performed to identify key mRNA with all miRNAs and miRNA with all LncRNAs,and thus key miRNAs and LncRNAs were screened out.Survival analysis was conducted based on the differences in expression levels of these key mRNAs,miRNAs,and LncRNAs between tumor patients and normal individuals,and finally a ceRNA regulatory network was constructed.The correlation between key mRNAs and immune cells,immune checkpoints(CD274,PDCD1 and CTLA4),and immune cell marker genes(IG)was analyzed using the TIMER 2.0 database.Results A total of 22 key mRNAs were screened,with the most significant difference being proline 3-hydroxylase 4(P3H4).The expression of P3H4 in patients with BLCA was high,and survival time was shorter in patients with high expression.A sum of 33 miRNAs and 14 LncRNAs were screened using the key mRNAs as the central link.Through co-expression analysis and survival analysis,hsa-miR-151a-3p and MIR100 HG were identified as the key miRNA and key LncRNA with prognostic value.The differences in the above analysis results were statistically significant(allΡ<0.05).Based on these findings,a ceRNA regulatory network consisting of 1 mRNA,1 miRNA,and 1 LncRNA was constructed.Immunoassay firstly revealed a significant positive correlation between double positive T cells and P3H4 expression in the tumor microenvironment of BLCA.Moreover,there were 3 types of immune cells(tumor-associated neutrophils,and tu
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...