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Identification of hub genes and therapeutic drugs in esophageal squamous cell carcinoma based on integrated bioinformatics strategy

机译:基于整合生物信息学策略的食管鳞状细胞癌中枢基因和治疗药物的鉴定

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Esophageal squamous cell carcinoma (ESCC) is one of leading malignant cancers of gastrointestinal tract worldwide. Until now, the involved mechanisms during the development of ESCC are largely unknown. This study aims to explore the driven-genes and biological pathways in ESCC. mRNA expression datasets of GSE29001, GSE20347, GSE100942, and GSE38129, containing 63 pairs of ESCC and non-tumor tissues data, were integrated and deeply analyzed. The bioinformatics approaches include identification of differentially expressed genes (DEGs) and hub genes, gene ontology (GO) terms analysis and biological pathway enrichment analysis, construction and analysis of protein–protein interaction (PPI) network, and miRNA–gene network construction. Subsequently, GEPIA2 database and qPCR assay were utilized to validate the expression of hub genes. DGIdb database was performed to search the candidate drugs for ESCC. Finally, 120 upregulated and 26 downregulated DEGs were identified. The functional enrichment of DEGs in ESCC were mainly correlated with cell cycle, DNA replication, deleted in colorectal cancer (DCC) mediated attractive signaling pathway, and Netrin-1 signaling pathway. The PPI network was constructed using STRING software with 146 nodes and 2392 edges. The most significant three modules in PPI were filtered and analyzed. Totally ten genes were selected and considered as the hub genes and nuclear division cycle 80 (NDC80) was closely related to the survival of ESCC patients. DGIdb database predicted 33 small molecules as the possible drugs for treating ESCC. In summary, the data may provide new insights into ESCC pathogenesis and treatments. The candidate drugs may improve the efficiency of personalized therapy in future.
机译:食道鳞状细胞癌(ESCC)是全球胃肠道恶性肿瘤的领先者之一。到目前为止,ESCC开发过程中涉及的机制尚不清楚。这项研究旨在探索ESCC中的驱动基因和生物学途径。整合并深入分析了GSE29001,GSE20347,GSE100942和GSE38129的mRNA表达数据集,其中包含63对ESCC和非肿瘤组织数据。生物信息学方法包括鉴定差异表达基因(DEG)和中枢基因,基因本体论(GO)术语分析和生物途径富集分析,蛋白质与蛋白质相互作用(PPI)网络的构建和分析,以及miRNA-基因网络的构建。随后,利用GEPIA2数据库和qPCR测定法验证轮毂基因的表达。执行DGIdb数据库以搜索ESCC的候选药物。最终,鉴定出120个上调的DEG和26个下调的DEG。在ESCC中DEG的功能富集主要与细胞周期,DNA复制,在结肠直肠癌(DCC)介导的有吸引力的信号传导途径和Netrin-1信号传导途径中缺失有关。使用具有146个节点和2392个边缘的STRING软件构建了PPI网络。对PPI中最重要的三个模块进行了过滤和分析。总共选择了10个基因,并将其视为中心基因,而核分裂周期80(NDC80)与ESCC患者的生存密切相关。 DGIdb数据库预测了33种小分子可能是治疗ESCC的药物。总之,这些数据可能为ESCC的发病机理和治疗提供新的见解。候选药物将来可能会提高个性化治疗的效率。

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