Laboratory of Systems Biology and Bioinformatics (LBB), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
Department of Biology, Tabriz Branch, Islamic Azad University, Tabriz, Iran.
Sci Rep. 2022 Apr 7;12(1):5885. doi: 10.1038/s41598-022-09920-4.
Bladder cancer (BC) is one of the most important cancers worldwide, and if it is diagnosed early, its progression in humans can be prevented and long-term survival will be achieved accordingly. This study aimed to identify novel micro-RNA (miRNA) and gene-based biomarkers for diagnosing BC. The microarray dataset of BC tissues (GSE13507) listed in the GEO database was analyzed for this purpose. The gene expression data from three BC tissues including 165 primary bladder cancer (PBC), 58 normal looking-bladder mucosae surrounding cancer (NBMSC), and 23 recurrent non-muscle invasive tumor tissues (RNIT) were used to reconstruct gene co-expression networks. After preprocessing and normalization, deferentially expressed genes (DEGs) were obtained and used to construct the weighted gene co-expression network (WGCNA). Gene co-expression modules and low-preserved modules were extracted among BC tissues using network clustering. Next, the experimentally validated mRNA-miRNA interaction information were used to reconstruct three mRNA-miRNA bipartite networks. Reactome pathway database and Gene ontology (GO) was subsequently performed for the extracted genes of three bipartite networks and miRNAs, respectively. To further analyze the data, ten hub miRNAs (miRNAs with the highest degree) were selected in each bipartite network to reconstruct three bipartite subnetworks. Finally, the obtained biomarkers were comprehensively investigated and discussed in authentic studies. The obtained results from our study indicated a group of genes including PPARD, CST4, CSNK1E, PTPN14, ETV6, and ADRM1 as well as novel miRNAs (e.g., miR-16-5p, miR-335-5p, miR-124-3p, and let-7b-5p) which might be potentially associated with BC and could be a potential biomarker. Afterward, three drug-gene interaction networks were reconstructed to explore candidate drugs for the treatment of BC. The hub miRNAs in the mRNA-miRNA bipartite network played a fundamental role in BC progression; however, these findings need further investigation.
膀胱癌(BC)是全球最重要的癌症之一,如果早期诊断,可预防其在人类中的进展,并相应实现长期生存。本研究旨在鉴定用于诊断 BC 的新型 microRNA(miRNA)和基因基生物标志物。为此,分析了 GEO 数据库中列出的 BC 组织的 microarray 数据集(GSE13507)。使用来自三种 BC 组织的基因表达数据,包括 165 例原发性膀胱癌(PBC)、58 例癌旁正常膀胱黏膜(NBMSC)和 23 例复发性非肌肉浸润性肿瘤组织(RNIT),来重建基因共表达网络。经过预处理和归一化,获得差异表达基因(DEGs),并用于构建加权基因共表达网络(WGCNA)。使用网络聚类从 BC 组织中提取基因共表达模块和低保留模块。接下来,使用实验验证的 mRNA-miRNA 相互作用信息来重建三个 mRNA-miRNA 二部网络。随后对三个二部网络的提取基因和 miRNAs 分别进行 Reactome 途径数据库和基因本体(GO)分析。为了进一步分析数据,在每个二部网络中选择十个枢纽 miRNA(具有最高度的 miRNA)来重建三个二部子网。最后,对获得的生物标志物进行了综合研究和讨论。本研究获得的结果表明,一组基因,包括 PPARD、CST4、CSNK1E、PTPN14、ETV6 和 ADRM1 以及新型 miRNA(例如 miR-16-5p、miR-335-5p、miR-124-3p 和 let-7b-5p)可能与 BC 相关,可作为潜在的生物标志物。之后,构建了三个药物-基因相互作用网络,以探索用于治疗 BC 的候选药物。mRNA-miRNA 二部网络中的枢纽 miRNA 在 BC 进展中起着重要作用,但这些发现需要进一步研究。