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Screening and Identification of Key Biomarkers in Pancreatic Cancer: Evidence from Bioinformatic Analysis.
Journal of Computational Biology ( IF 1.4 ) Pub Date : 2020-07-09 , DOI: 10.1089/cmb.2019.0189
Meng Zhang 1 , Chen-Yi Di 2 , Peng Guo 3 , Ling-Bing Meng 4 , Meng-Jie Shan 5 , Yong Qiu 6 , Pei-Yuan Guo 7 , Ke-Qin Dong 7 , Qi Xie 8 , Qiang Wang 9
Affiliation  

Pancreatic cancer (PC) whose mortality is comparable to morbidity is a highly fatal disease. Early approaches of diagnosis and treatment for PC are quite limited, so it is of great urgency to figure out the exact tumorigenesis and development mechanism of PC. To identify the related molecular markers of pancreatic oncogenesis, we downloaded three microarray datasets (GSE63111, GSE101448, and GSE107610) from Gene Expression Omnibus (GEO) database. The common differentially expressed genes (DEGs) among them were identified, and the corresponding function enrichment analyses were accomplished. The protein–protein interaction network was conducted by Search Tool for the Retrieval of Interacting Genes (STRING), and the corresponding module analysis was accomplished by Cytoscape. There were 55 DEGs found in total. The molecular function and biological processes (BP) of these DEGs mainly include cytokinesis, mitotic nuclear division, cell division, cell proliferation, microtubule-based movement, and mineral absorption. Among the 55 DEGs, 14 hub genes were further confirmed and it was concluded that they mainly function in mitotic cytokinesis, microtubule-based movement, mitotic chromosome condensation, and mitotic spindle assembly from the BP analysis. The survival analysis showed that all the 14 hub genes, especially nucleolar and spindle associated protein 1 and abnormal spindle microtubule assembly, may involve in the tumorigenesis and development of PC. And they might be used as new biomarkers for auxiliary diagnosis and potential targets for immunotherapy of PC.

中文翻译:

胰腺癌关键生物标志物的筛选和鉴定:来自生物信息学分析的证据。

死亡率与发病率相当的胰腺癌 (PC) 是一种高度致命的疾病。PC的早期诊断和治疗方法十分有限,因此,明确PC的确切肿瘤发生发展机制迫在眉睫。为了鉴定胰腺癌发生的相关分子标记,我们从基因表达综合 (GEO) 数据库下载了三个微阵列数据集 (GSE63111、GSE101448 和 GSE107610)。鉴定了它们之间常见的差异表达基因(DEGs),并完成了相应的功能富集分析。蛋白质-蛋白质相互作用网络由用于检索相互作用基因的搜索工具(STRING)进行,相应的模块分析由Cytoscape完成。总共发现了55个DEG。这些DEG的分子功能和生物学过程(BP)主要包括胞质分裂、有丝分裂核分裂、细胞分裂、细胞增殖、微管运动和矿物质吸收。在55个DEGs中,进一步证实了14个hub基因,BP分析认为它们主要在有丝分裂胞质分裂、微管运动、有丝分裂染色体凝聚和有丝分裂纺锤体组装中起作用。生存分析表明,所有14个枢纽基因,尤其是核仁和纺锤体相关蛋白1和纺锤体微管组装异常,可能参与PC的肿瘤发生发展。并且它们可能被用作辅助诊断的新生物标志物和PC免疫治疗的潜在靶点。细胞分裂、细胞增殖、基于微管的运动和矿物质吸收。在55个DEGs中,进一步证实了14个hub基因,BP分析认为它们主要在有丝分裂胞质分裂、微管运动、有丝分裂染色体凝聚和有丝分裂纺锤体组装中起作用。生存分析表明,所有14个枢纽基因,尤其是核仁和纺锤体相关蛋白1和纺锤体微管组装异常,可能参与PC的肿瘤发生发展。并且它们可能被用作辅助诊断的新生物标志物和PC免疫治疗的潜在靶点。细胞分裂、细胞增殖、基于微管的运动和矿物质吸收。在55个DEGs中,进一步证实了14个hub基因,BP分析认为它们主要在有丝分裂胞质分裂、微管运动、有丝分裂染色体凝聚和有丝分裂纺锤体组装中起作用。生存分析表明,所有14个枢纽基因,尤其是核仁和纺锤体相关蛋白1和纺锤体微管组装异常,可能参与PC的肿瘤发生发展。并且它们可能被用作辅助诊断的新生物标志物和PC免疫治疗的潜在靶点。来自 BP 分析的基于微管的运动、有丝分裂染色体浓缩和有丝分裂纺锤体组装。生存分析表明,所有14个枢纽基因,尤其是核仁和纺锤体相关蛋白1和纺锤体微管组装异常,可能参与PC的肿瘤发生发展。并且它们可能被用作辅助诊断的新生物标志物和PC免疫治疗的潜在靶点。来自 BP 分析的基于微管的运动、有丝分裂染色体浓缩和有丝分裂纺锤体组装。生存分析表明,所有14个枢纽基因,尤其是核仁和纺锤体相关蛋白1和纺锤体微管组装异常,可能参与PC的肿瘤发生发展。并且它们可能被用作辅助诊断的新生物标志物和PC免疫治疗的潜在靶点。
更新日期:2020-07-10
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