升结肠癌的转录组学分析揭示了结肠癌特征特征的已知和新的基因和基因集

Anatomy Pub Date : 2021-04-29 DOI:10.2399/ANA.21.852318
Can Türk
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引用次数: 0

摘要

目的:结肠癌在男性和女性中都是一个严重的健康问题。结肠癌根据解剖区域的不同具有不同的基因型和表型。升结肠肿瘤通常诊断较晚,但其恶性程度高于降结肠和横结肠,患者生存率低于其他部位。本研究的目的是通过比较升结肠、横结肠和降结肠肿瘤样本的所有基因组信息,确定升结肠肿瘤中显著高表达或低表达的基因。根据所有这些信息,研究的另一个目的是确定从大肠中获得的结肠基因的途径,确定它们之间的关系,并将它们与癌症特征联系起来。方法:从GEO (Gene expression Omnibus) (GSE41258)中获取结肠癌升、横、降三种亚型的基因表达值。数据包括47例升结肠、18例横结肠和31例降结肠癌患者样本。采用线性回归分析确定差异表达基因。采用基因集群3.0对基因进行分层聚类。除线性回归和分层聚类外,在Cytoscape应用程序3.8.2中使用GeneMANIA进行多变量基因的网络分析。采用GSEA 4.1.0 (Gene Set Enrichment Analysis,基因集富集分析)分析特定群体间的不同基因。结果:通过这些分析,确定在升结肠肿瘤样本中有85个高表达基因和139个低表达基因。已有研究表明,这些基因对升结肠肿瘤样本的分化作用优于其他结肠区域的肿瘤样本。结论:本研究结果对了解升结肠肿瘤基因组具有重要意义;如果这些发现在体外和临床得到证实,可能有可能揭示所鉴定的基因也具有升结肠肿瘤的生物标志物特性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
In silico transcriptomic analysis of ascending colon cancer unearths known and novel genes and gene sets regard to characteristic features of colon cancer
Objectives: Colon cancer emerges as a serious health problem in both men and women. Cancers in the colon have different genotypes and phenotypes according to the anatomical region. Tumors in ascending colon are usually diagnosed later, but it is more malignant than the descending and transverse colon, and the survival rates of patients are lower than other regions. The purpose of this study was to determine significantly high or low expressed genes in the ascending colon tumors by comparing all genome information obtained from cancer samples of ascending, transverse and descending colon. In concordance with all this information, another aim of the study was to identify the pathways to which the genes obtained from the colon in the large intestine and to determine their relationship with each other and to correlate them with the characteristics of cancer. Methods: Gene expression values for three subtypes of colon cancer as ascending, transverse, and descending were obtained from GEO (Gene Expression Omnibus) (GSE41258). Data included a total of 47 ascending, 18 transverse and 31 descending colon cancer patient samples. Linear regression analysis was performed to determine differentially expressed genes. Gene Cluster 3.0 was used in order to cluster the genes hierarchically. In addition to linear regression and hierarchical clustering, network analysis with multivariable genes was performed in Cytoscape application 3.8.2 using GeneMANIA. GSEA 4.1.0 (Gene Set Enrichment Analysis) was performed to understand the different genes among the specified groups. Results: As a result of these analyses, it was determined that there were 85 genes with high expression and 139 genes with low expression in the ascending colon tumor samples. It has been shown that these genes can differentiate tumor samples in the ascending colon better than tumor samples in other colon regions. Conclusion: Our findings are important for understanding the genome of ascending colon tumors; if these findings are confirmed in vitro and clinically, it may have potential to be revealed that the identified genes also have biomarker properties for tumors in the ascending colon.
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