School of Biological and Pharmaceutical Engineering, Wuhan Huaxia Institute of Technology, Wuhan, 430223, Hubei, China.
BMC Urol. 2023 Aug 10;23(1):135. doi: 10.1186/s12894-023-01307-5.
Bladder cancer (BLCA) is one of the most common malignancies among tumors worldwide. There are no validated biomarkers to facilitate such treatment diagnosis. DNA methylation modification plays important roles in epigenetics. Identifying methylated differentially expressed genes is a common method for the discovery of biomarkers.
Bladder cancer data were obtained from Gene Expression Omnibus (GEO), including the gene expression microarrays GSE37817( 18 patients and 3 normal ), GSE52519 (9 patients and 3 normal) and the gene methylation microarray GSE37816 (18 patients and 3 normal). Aberrantly expressed genes were obtained by GEO2R. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed using the DAVID database and KOBAS. Protein-protein interactions (PPIs) and hub gene networks were constructed by STRING and Cytoscape software. The validation of the results which was confirmed through four online platforms, including Gene Expression Profiling Interactive Analysis (GEPIA), Gene Set Cancer Analysis (GSCA), cBioProtal and MEXPRESS.
In total, 253 and 298 upregulated genes and 674 and 454 downregulated genes were identified for GSE37817 and GSE52519, respectively. For the GSE37816 dataset, hypermethylated and hypomethylated genes involving 778 and 3420 genes, respectively, were observed. Seventeen hypermethylated and low expression genes were enriched in biological processes associated with different organ development and morphogenesis. For molecular function, these genes showed enrichment in extracellular matrix structural constituents. Pathway enrichment showed drug metabolic enzymes and several amino acids metabolism, PI3K-Akt, Hedgehog signaling pathway. The top 3 hub genes screened by Cytoscape software were EFEMP1, SPARCL1 and ABCA8. The research results were verified using the GEPIA, GSCA, cBioProtal and EXPRESS databases, and the hub hypermethylated low expression genes were validated.
This study screened possible aberrantly methylated expression hub genes in BLCA by integrated bioinformatics analysis. The results may provide possible methylation-based biomarkers for the precise diagnosis and treatment of BLCA in the future.
膀胱癌（BLCA）是全球最常见的肿瘤之一。目前尚无经过验证的生物标志物来辅助这种治疗诊断。DNA 甲基化修饰在表观遗传学中发挥重要作用。识别甲基化差异表达基因是发现生物标志物的常用方法。
膀胱癌数据来自基因表达综合数据库（GEO），包括基因表达微阵列 GSE37817（18 例患者和 3 例正常）、GSE52519（9 例患者和 3 例正常）和基因甲基化微阵列 GSE37816（18 例患者和 3 例正常）。通过 GEO2R 获得异常表达基因。使用 DAVID 数据库和 KOBAS 分析基因本体论（GO）和京都基因与基因组百科全书（KEGG）途径。通过 STRING 和 Cytoscape 软件构建蛋白质-蛋白质相互作用（PPI）和枢纽基因网络。通过四个在线平台，包括基因表达谱交互式分析（GEPIA）、基因集癌症分析（GSCA）、cBioPortal 和 MEXPRESS，对结果进行验证。
在 GSE37817 和 GSE52519 中分别鉴定出 253 个和 298 个上调基因，以及 674 个和 454 个下调基因。对于 GSE37816 数据集，观察到涉及 778 个高甲基化基因和 3420 个低甲基化基因的高甲基化和低甲基化基因。17 个高甲基化和低表达基因在不同器官发育和形态发生相关的生物学过程中富集。在分子功能方面，这些基因在细胞外基质结构成分中富集。通路富集显示药物代谢酶和几种氨基酸代谢、PI3K-Akt、Hedgehog 信号通路。通过 Cytoscape 软件筛选出的前 3 个枢纽基因是 EFEMP1、SPARCL1 和 ABCA8。使用 GEPIA、GSCA、cBioPortal 和 EXPRESS 数据库对研究结果进行验证，并验证了枢纽高甲基化低表达基因。
本研究通过整合生物信息学分析筛选膀胱癌中可能存在的异常甲基化表达枢纽基因。这些结果可能为未来膀胱癌的精确诊断和治疗提供基于甲基化的潜在生物标志物。
