Abstract：
BACKGROUND: The aim of this study was to investigate the common gene signatures and potential molecular mechanisms of bladder urothelial carcinoma (BLCA) and metabolic syndrome (MS).
METHODS: Transcriptome data for BLCA and MS were obtained from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was utilized to identify co-expression networks associated with BLCA and MS, and five hub genes were further screened and validated using logistic least absolute shrinkage and selection operator (LASSO) regression models and receiver operating characteristic (ROC) curve, and external dataset for validation. The relationship between the hub genes and the clinicopathological characteristics and prognosis of BLCA patients was explored in the GEO and The Cancer Genome Atlas (TCGA)-BLCA cohorts, respectively. Differences in the immune microenvironment of BLCA and MS were analyzed using the database CIBERSORT and the R package \"ssGSEA\", and the correlation between hub genes and tumor microenvironment, immune score and targeted drugs was analyzed with the help of the TCGA-BLCA cohort. Finally, BLCA single-cell RNA (scRNA) data were used to analyze the expression levels of the hub genes in various cell types of BLCA and molecular mechanisms.
RESULTS: Five hub genes were screened by WGCNA and LASSO regression analysis, namely AP2-associated protein kinase 1 (AAK1), ATP-binding cassette subfamily F member 2 (ABCF2), Mitochondrial ribosomal protein L42 (MRPL42), La-related protein 3 (SSB) and TATA-box binding protein-associated factor 10 (TAF10). Analyzed in the GEO and TCGA-BLCA cohorts, we found that the hub genes (TAF10 and ABCF2) were closely associated with the clinicopathological characteristics and prognosis of BLCA patients. In CIBERSORT, we discovered that the hub genes are closely linked to the immune microenvironment, immune score, and especially with dendritic cells (DCs). In the single-cell RNA sequencing (scRNA-seq) analysis of BLCA, we identified that SSB was significantly differentially expressed in BLCA and normal bladder tissues and that it plays an important role in the development of BLCA.
CONCLUSIONS: The interaction of BLCA with MS may be associated with several cancer pathways being activated and identified TAF10 and ABCF2 as potential biomarkers and therapeutic targets for patients with BLCA and MS.
METHODS: Transcriptome data for BLCA and MS were obtained from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was utilized to identify co-expression networks associated with BLCA and MS, and five hub genes were further screened and validated using logistic least absolute shrinkage and selection operator (LASSO) regression models and receiver operating characteristic (ROC) curve, and external dataset for validation. The relationship between the hub genes and the clinicopathological characteristics and prognosis of BLCA patients was explored in the GEO and The Cancer Genome Atlas (TCGA)-BLCA cohorts, respectively. Differences in the immune microenvironment of BLCA and MS were analyzed using the database CIBERSORT and the R package \"ssGSEA\", and the correlation between hub genes and tumor microenvironment, immune score and targeted drugs was analyzed with the help of the TCGA-BLCA cohort. Finally, BLCA single-cell RNA (scRNA) data were used to analyze the expression levels of the hub genes in various cell types of BLCA and molecular mechanisms.
RESULTS: Five hub genes were screened by WGCNA and LASSO regression analysis, namely AP2-associated protein kinase 1 (AAK1), ATP-binding cassette subfamily F member 2 (ABCF2), Mitochondrial ribosomal protein L42 (MRPL42), La-related protein 3 (SSB) and TATA-box binding protein-associated factor 10 (TAF10). Analyzed in the GEO and TCGA-BLCA cohorts, we found that the hub genes (TAF10 and ABCF2) were closely associated with the clinicopathological characteristics and prognosis of BLCA patients. In CIBERSORT, we discovered that the hub genes are closely linked to the immune microenvironment, immune score, and especially with dendritic cells (DCs). In the single-cell RNA sequencing (scRNA-seq) analysis of BLCA, we identified that SSB was significantly differentially expressed in BLCA and normal bladder tissues and that it plays an important role in the development of BLCA.
CONCLUSIONS: The interaction of BLCA with MS may be associated with several cancer pathways being activated and identified TAF10 and ABCF2 as potential biomarkers and therapeutic targets for patients with BLCA and MS.
摘要：
背景：本研究的目的是探讨膀胱尿路上皮癌（BLCA）和代谢综合征（MS）的常见基因特征和潜在分子机制。
方法:从基因表达综合(GEO)数据库获得BLCA和MS的转录组数据。加权基因共表达网络分析（WGCNA）用于鉴定与BLCA和MS相关的共表达网络，并使用逻辑最小绝对收缩和选择算子（LASSO）回归模型和受试者工作特征（ROC）曲线进一步筛选和验证了五个中心基因，和外部数据集进行验证。在GEO和癌症基因组图谱（TCGA）-BLCA队列中探讨了hub基因与BLCA患者临床病理特征和预后之间的关系，分别。使用数据库BERSORT和R包“ssGSEA”分析了BLCA和MS的免疫微环境差异，以及hub基因与肿瘤微环境的相关性，免疫评分和靶向药物在TCGA-BLCA队列的帮助下进行分析.最后,BLCA单细胞RNA（scRNA）数据用于分析BLCA的各种细胞类型和分子机制中hub基因的表达水平。
结果：通过WGCNA和LASSO回归分析筛选了5个hub基因，即AP2相关蛋白激酶1（AAK1），ATP结合盒亚家族F成员2（ABCF2），线粒体核糖体蛋白L42(MRPL42),La相关蛋白3（SSB）和TATA盒结合蛋白相关因子10（TAF10）。在GEO和TCGA-BLCA队列中分析，我们发现hub基因(TAF10和ABCF2)与BLCA患者的临床病理特征和预后密切相关。InCIBERSORT,我们发现hub基因与免疫微环境密切相关，免疫评分,尤其是树突状细胞(DC)。在BLCA的单细胞RNA测序（scRNA-seq）分析中，我们发现SSB在BLCA和正常膀胱组织中显著差异表达，并且在BLCA的发生发展中起重要作用。
结论：BLCA与MS的相互作用可能与几种被激活的癌症途径有关，并将TAF10和ABCF2鉴定为BLCA和MS患者的潜在生物标志物和治疗靶标。
方法:从基因表达综合(GEO)数据库获得BLCA和MS的转录组数据。加权基因共表达网络分析（WGCNA）用于鉴定与BLCA和MS相关的共表达网络，并使用逻辑最小绝对收缩和选择算子（LASSO）回归模型和受试者工作特征（ROC）曲线进一步筛选和验证了五个中心基因，和外部数据集进行验证。在GEO和癌症基因组图谱（TCGA）-BLCA队列中探讨了hub基因与BLCA患者临床病理特征和预后之间的关系，分别。使用数据库BERSORT和R包“ssGSEA”分析了BLCA和MS的免疫微环境差异，以及hub基因与肿瘤微环境的相关性，免疫评分和靶向药物在TCGA-BLCA队列的帮助下进行分析.最后,BLCA单细胞RNA（scRNA）数据用于分析BLCA的各种细胞类型和分子机制中hub基因的表达水平。
结果：通过WGCNA和LASSO回归分析筛选了5个hub基因，即AP2相关蛋白激酶1（AAK1），ATP结合盒亚家族F成员2（ABCF2），线粒体核糖体蛋白L42(MRPL42),La相关蛋白3（SSB）和TATA盒结合蛋白相关因子10（TAF10）。在GEO和TCGA-BLCA队列中分析，我们发现hub基因(TAF10和ABCF2)与BLCA患者的临床病理特征和预后密切相关。InCIBERSORT,我们发现hub基因与免疫微环境密切相关，免疫评分,尤其是树突状细胞(DC)。在BLCA的单细胞RNA测序（scRNA-seq）分析中，我们发现SSB在BLCA和正常膀胱组织中显著差异表达，并且在BLCA的发生发展中起重要作用。
结论：BLCA与MS的相互作用可能与几种被激活的癌症途径有关，并将TAF10和ABCF2鉴定为BLCA和MS患者的潜在生物标志物和治疗靶标。
