Identification of Hub genes with prognostic values in colorectal cancer by integrated bioinformatics analysis.

IF 2.2 4区 医学 Q3 ONCOLOGY Cancer Biomarkers Pub Date : 2024-01-01 DOI:10.3233/CBM-230113
Shan Li, Ting Li, Yan-Qing Shi, Bin-Jie Xu, Yu-Yong Deng, Xu-Guang Sun
{"title":"Identification of Hub genes with prognostic values in colorectal cancer by integrated bioinformatics analysis.","authors":"Shan Li, Ting Li, Yan-Qing Shi, Bin-Jie Xu, Yu-Yong Deng, Xu-Guang Sun","doi":"10.3233/CBM-230113","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Our study aimed to investigate the Hub genes and their prognostic value in colorectal cancer (CRC) via bioinformatics analysis.</p><p><strong>Methods: </strong>The data set of colorectal cancer was downloaded from the GEO database (GSE21510, GSE110224 and GSE74602) for differential expression analysis using the GEO2R tool. Hub genes were screened by protein-protein interaction (PPI) comprehensive analysis. GEPIA was used to verify the expression of Hub genes and evaluate its prognostic value. The protein expression of Hub gene in CRC was analyzed using the Human Protein Atlas database. The cBioPortal was used to analyze the type and frequency of Hub gene mutations, and the effects of mutation on the patients' prognosis. The TIMER database was used to study the correlation between Hub genes and immune infiltration in CRC. Gene set enrichment analysis (GSEA) was used to explore the biological function and signal pathway of the Hub genes and corresponding co-expressed genes.</p><p><strong>Results: </strong>We identified 346 differentially expressed genes (DEGs), including 117 upregulated and 229 downregulated. Four Hub genes (AURKA, CCNB1, EXO1 and CCNA2) were selected by survival analysis and differential expression validation. The protein and mRNA expression levels of AURKA, CCNB1, EXO1 and CCNA2 were higher in CRC tissues than in adjacent tissues. There were varying degrees of immune cell infiltration and gene mutation of Hub genes, especially B cells and CD8+ T cells. The results of GSEA showed that Hub genes and their co-expressed genes mainly participated in chromosome segregation, DNA replication, translational elongation and cell cycle.</p><p><strong>Conclusion: </strong>Overexpression of AURKA, CCNB1, CCNA2 and EXO1 had a better prognosis for CRC and this effect was correlation with gene mutation and infiltration of immune cells.</p>","PeriodicalId":56320,"journal":{"name":"Cancer Biomarkers","volume":null,"pages":null},"PeriodicalIF":2.2000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11191499/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Biomarkers","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3233/CBM-230113","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Background: Our study aimed to investigate the Hub genes and their prognostic value in colorectal cancer (CRC) via bioinformatics analysis.

Methods: The data set of colorectal cancer was downloaded from the GEO database (GSE21510, GSE110224 and GSE74602) for differential expression analysis using the GEO2R tool. Hub genes were screened by protein-protein interaction (PPI) comprehensive analysis. GEPIA was used to verify the expression of Hub genes and evaluate its prognostic value. The protein expression of Hub gene in CRC was analyzed using the Human Protein Atlas database. The cBioPortal was used to analyze the type and frequency of Hub gene mutations, and the effects of mutation on the patients' prognosis. The TIMER database was used to study the correlation between Hub genes and immune infiltration in CRC. Gene set enrichment analysis (GSEA) was used to explore the biological function and signal pathway of the Hub genes and corresponding co-expressed genes.

Results: We identified 346 differentially expressed genes (DEGs), including 117 upregulated and 229 downregulated. Four Hub genes (AURKA, CCNB1, EXO1 and CCNA2) were selected by survival analysis and differential expression validation. The protein and mRNA expression levels of AURKA, CCNB1, EXO1 and CCNA2 were higher in CRC tissues than in adjacent tissues. There were varying degrees of immune cell infiltration and gene mutation of Hub genes, especially B cells and CD8+ T cells. The results of GSEA showed that Hub genes and their co-expressed genes mainly participated in chromosome segregation, DNA replication, translational elongation and cell cycle.

Conclusion: Overexpression of AURKA, CCNB1, CCNA2 and EXO1 had a better prognosis for CRC and this effect was correlation with gene mutation and infiltration of immune cells.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
通过综合生物信息学分析鉴定具有预后价值的结直肠癌 Hub 基因。
研究背景我们的研究旨在通过生物信息学分析研究结直肠癌(CRC)中的Hub基因及其预后价值:从 GEO 数据库(GSE21510、GSE110224 和 GSE74602)下载结直肠癌数据集,使用 GEO2R 工具进行差异表达分析。通过蛋白质-蛋白质相互作用(PPI)综合分析筛选出枢纽基因。GEPIA 用于验证 Hub 基因的表达并评估其预后价值。利用人类蛋白质图谱数据库分析了 Hub 基因在 CRC 中的蛋白质表达。cBioPortal 用于分析 Hub 基因突变的类型和频率,以及突变对患者预后的影响。TIMER 数据库用于研究 Hub 基因与 CRC 免疫浸润之间的相关性。基因组富集分析(Gene set enrichment analysis,GSEA)用于探索Hub基因及相应共表达基因的生物学功能和信号通路:结果:我们发现了346个差异表达基因(DEGs),包括117个上调基因和229个下调基因。通过生存分析和差异表达验证,筛选出四个中枢基因(AURKA、CCNB1、EXO1和CCNA2)。AURKA、CCNB1、EXO1和CCNA2在CRC组织中的蛋白和mRNA表达水平均高于邻近组织。免疫细胞尤其是 B 细胞和 CD8+ T 细胞对 Hub 基因有不同程度的浸润和基因突变。GSEA结果显示,Hub基因及其共表达基因主要参与染色体分离、DNA复制、翻译延伸和细胞周期:结论:AURKA、CCNB1、CCNA2 和 EXO1 的过表达对 CRC 的预后有较好的影响,这种影响与基因突变和免疫细胞的浸润有关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Cancer Biomarkers
Cancer Biomarkers ONCOLOGY-
CiteScore
5.20
自引率
3.20%
发文量
195
审稿时长
3 months
期刊介绍: Concentrating on molecular biomarkers in cancer research, Cancer Biomarkers publishes original research findings (and reviews solicited by the editor) on the subject of the identification of markers associated with the disease processes whether or not they are an integral part of the pathological lesion. The disease markers may include, but are not limited to, genomic, epigenomic, proteomics, cellular and morphologic, and genetic factors predisposing to the disease or indicating the occurrence of the disease. Manuscripts on these factors or biomarkers, either in altered forms, abnormal concentrations or with abnormal tissue distribution leading to disease causation will be accepted.
期刊最新文献
Vitamin D receptor polymorphisms associate with the efficacy and toxicity of radioiodine-131 therapy in patients with differentiated thyroid cancer. Prognostic impact of invariant natural killer T cells in solid and hematological tumors; systematic review and meta-analysis. Mechanism study of serum extracellular nano-vesicles miR-412-3p targeting regulation of TEAD1 in promoting malignant biological behavior of sub-centimeter lung nodules. Circulating tumor DNA (ctDNA) as a biomarker of response to therapy in advanced Hepatocellular carcinoma treated with Nivolumab. Machine learning identifies a 5-serum cytokine panel for the early detection of chronic atrophy gastritis patients.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1