{"title":"胃癌的枢纽基因和通路:使用肿瘤附近正常组织和使用健康组织作为校准器的研究之间的比较","authors":"Khadijeh Sadegh, Amirhossein Ahmadi","doi":"10.1049/syb2.12065","DOIUrl":null,"url":null,"abstract":"<p>Several bioinformatics studies have been performed on high-throughput expression data to determine the cellular pathways and hub genes affected by Gastric cancer (GC). However, these studies differ in using a healthy tissue or normal tissue adjacent to the tumour (NAT) as calibrator tissues. This study was designed to find how using healthy or NAT tissues as calibrator tissues could affect pathway enrichment data and hub genes in GC. Two gene expression datasets with NAT tissues (GSE79973 and GSE118916) and one dataset with healthy tissues (GSE54129) were downloaded and processed by the limma package to screen the differentially expressed genes (DEGs). Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) enrichment analysis were performed by the Enrichr online tool. Protein-protein interaction network construction, module analysis, and hub genes selection were performed by Cytoscape software, Molecular Complex Detection plugin, and cytoHubba plugin, respectively. The gene expression profiling interactive analysis web server was used to analyse RNA sequencing expression data from The Cancer Genome Atlas Program. The Kaplan—Meier plotter was used to perform survival analysis. Our results showed that some KEGG and GO pathways were shared between studies with NAT and the study with healthy tissues. However, some terms, especially inflammation-related terms, were missed when NAT tissues were used as calibrator tissues. Also, only <i>FN1</i> and <i>COL1A1</i> are common hub genes between DEGs of the studies with NAT and healthy tissues. Since hub genes are usually extracted and suggested as candidate targets for GC diagnosis, prognosis, or treatment, selecting healthy or NAT tissues may affect the hub genes selection.</p>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":"17 3","pages":"131-141"},"PeriodicalIF":1.9000,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/syb2.12065","citationCount":"0","resultStr":"{\"title\":\"Hub genes and pathways in gastric cancer: A comparison between studies that used normal tissues adjacent to the tumour and studies that used healthy tissues as calibrator\",\"authors\":\"Khadijeh Sadegh, Amirhossein Ahmadi\",\"doi\":\"10.1049/syb2.12065\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Several bioinformatics studies have been performed on high-throughput expression data to determine the cellular pathways and hub genes affected by Gastric cancer (GC). However, these studies differ in using a healthy tissue or normal tissue adjacent to the tumour (NAT) as calibrator tissues. This study was designed to find how using healthy or NAT tissues as calibrator tissues could affect pathway enrichment data and hub genes in GC. Two gene expression datasets with NAT tissues (GSE79973 and GSE118916) and one dataset with healthy tissues (GSE54129) were downloaded and processed by the limma package to screen the differentially expressed genes (DEGs). Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) enrichment analysis were performed by the Enrichr online tool. Protein-protein interaction network construction, module analysis, and hub genes selection were performed by Cytoscape software, Molecular Complex Detection plugin, and cytoHubba plugin, respectively. The gene expression profiling interactive analysis web server was used to analyse RNA sequencing expression data from The Cancer Genome Atlas Program. The Kaplan—Meier plotter was used to perform survival analysis. Our results showed that some KEGG and GO pathways were shared between studies with NAT and the study with healthy tissues. However, some terms, especially inflammation-related terms, were missed when NAT tissues were used as calibrator tissues. Also, only <i>FN1</i> and <i>COL1A1</i> are common hub genes between DEGs of the studies with NAT and healthy tissues. 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引用次数: 0
摘要
一些生物信息学研究已经对高通量表达数据进行了研究,以确定胃癌(GC)影响的细胞途径和中心基因。然而,这些研究在使用健康组织或肿瘤附近的正常组织(NAT)作为校准组织方面有所不同。本研究旨在发现使用健康或NAT组织作为校准组织如何影响GC的途径富集数据和中心基因。下载两个NAT组织的基因表达数据集(GSE79973和GSE118916)和一个健康组织的基因表达数据集(GSE54129),用limma软件包进行处理,筛选差异表达基因(DEGs)。京都基因与基因组百科全书(KEGG)和基因本体(GO)富集分析通过富集在线工具进行。分别使用Cytoscape软件、Molecular Complex Detection插件和cytoHubba插件进行蛋白-蛋白相互作用网络构建、模块分析和枢纽基因选择。基因表达谱交互分析web服务器用于分析来自The Cancer Genome Atlas Program的RNA测序表达数据。使用Kaplan-Meier绘图仪进行生存分析。我们的研究结果表明,在NAT研究和健康组织研究中,一些KEGG和GO通路是共享的。然而,当使用NAT组织作为校准器组织时,遗漏了一些术语,特别是与炎症相关的术语。此外,只有FN1和COL1A1是NAT研究中deg与健康组织之间的共同枢纽基因。由于中心基因通常被提取并建议作为胃癌诊断、预后或治疗的候选靶点,选择健康或NAT组织可能会影响中心基因的选择。
Hub genes and pathways in gastric cancer: A comparison between studies that used normal tissues adjacent to the tumour and studies that used healthy tissues as calibrator
Several bioinformatics studies have been performed on high-throughput expression data to determine the cellular pathways and hub genes affected by Gastric cancer (GC). However, these studies differ in using a healthy tissue or normal tissue adjacent to the tumour (NAT) as calibrator tissues. This study was designed to find how using healthy or NAT tissues as calibrator tissues could affect pathway enrichment data and hub genes in GC. Two gene expression datasets with NAT tissues (GSE79973 and GSE118916) and one dataset with healthy tissues (GSE54129) were downloaded and processed by the limma package to screen the differentially expressed genes (DEGs). Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) enrichment analysis were performed by the Enrichr online tool. Protein-protein interaction network construction, module analysis, and hub genes selection were performed by Cytoscape software, Molecular Complex Detection plugin, and cytoHubba plugin, respectively. The gene expression profiling interactive analysis web server was used to analyse RNA sequencing expression data from The Cancer Genome Atlas Program. The Kaplan—Meier plotter was used to perform survival analysis. Our results showed that some KEGG and GO pathways were shared between studies with NAT and the study with healthy tissues. However, some terms, especially inflammation-related terms, were missed when NAT tissues were used as calibrator tissues. Also, only FN1 and COL1A1 are common hub genes between DEGs of the studies with NAT and healthy tissues. Since hub genes are usually extracted and suggested as candidate targets for GC diagnosis, prognosis, or treatment, selecting healthy or NAT tissues may affect the hub genes selection.
期刊介绍:
IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. Papers that analyse genomic data in order to identify variables and basic relationships between them are considered if the results provide a basis for mathematical modelling and simulation of cellular dynamics. Manuscripts on molecular and cell biological studies are encouraged if the aim is a systems approach to dynamic interactions within and between cells.
The scope includes the following topics:
Genomics, transcriptomics, proteomics, metabolomics, cells, tissue and the physiome; molecular and cellular interaction, gene, cell and protein function; networks and pathways; metabolism and cell signalling; dynamics, regulation and control; systems, signals, and information; experimental data analysis; mathematical modelling, simulation and theoretical analysis; biological modelling, simulation, prediction and control; methodologies, databases, tools and algorithms for modelling and simulation; modelling, analysis and control of biological networks; synthetic biology and bioengineering based on systems biology.