A novel investigation into an E2F transcription factor-related prognostic model with seven signatures for colon cancer patients

IF 1.9 4区 生物学 Q4 CELL BIOLOGY
Xiaoyong Shen, Zheng Su, Yan Dou, Xin Song
{"title":"A novel investigation into an E2F transcription factor-related prognostic model with seven signatures for colon cancer patients","authors":"Xiaoyong Shen,&nbsp;Zheng Su,&nbsp;Yan Dou,&nbsp;Xin Song","doi":"10.1049/syb2.12069","DOIUrl":null,"url":null,"abstract":"<p>The pathogenesis of colon cancer, a common gastrointestinal tumour, involves complicated factors, especially a series of cell cycle-related genes. E2F transcription factors during the cell cycle play an essential role in the occurrence of colon cancer. It is meaningful to establish an efficient prognostic model of colon cancer targeting cellular E2F-associated genes. This has not been reported previously. The authors first aimed to explore the links of E2F genes with the clinical outcomes of colon cancer patients by integrating data from the TCGA-COAD (<i>n</i> = 521), GSE17536 (<i>n</i> = 177) and GSE39582 (<i>n</i> = 585) cohorts. The Cox regression and Lasso modelling approach to identify a novel colon cancer prognostic model involving several hub genes (CDKN2A, GSPT1, PNN, POLD3, PPP1R8, PTTG1 and RFC1) were utilised. Moreover, an E2F-related nomogram that efficiently predicted the survival rates of colon cancer patients was created. Additionally, the authors first identified two E2F tumour clusters, which showed distinct prognostic features. Interestingly, the potential links of E2F-based classification and ‘protein secretion’ issues of multiorgans and tumour infiltration of ‘T-cell regulatory (Tregs)’ and ‘CD56dim natural killer cell’ were detected. The authors’ findings are of potential clinical significance for the prognosis assessment and mechanistic exploration of colon cancer.</p>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/b1/ed/SYB2-17-187.PMC10439494.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Systems Biology","FirstCategoryId":"99","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/syb2.12069","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

The pathogenesis of colon cancer, a common gastrointestinal tumour, involves complicated factors, especially a series of cell cycle-related genes. E2F transcription factors during the cell cycle play an essential role in the occurrence of colon cancer. It is meaningful to establish an efficient prognostic model of colon cancer targeting cellular E2F-associated genes. This has not been reported previously. The authors first aimed to explore the links of E2F genes with the clinical outcomes of colon cancer patients by integrating data from the TCGA-COAD (n = 521), GSE17536 (n = 177) and GSE39582 (n = 585) cohorts. The Cox regression and Lasso modelling approach to identify a novel colon cancer prognostic model involving several hub genes (CDKN2A, GSPT1, PNN, POLD3, PPP1R8, PTTG1 and RFC1) were utilised. Moreover, an E2F-related nomogram that efficiently predicted the survival rates of colon cancer patients was created. Additionally, the authors first identified two E2F tumour clusters, which showed distinct prognostic features. Interestingly, the potential links of E2F-based classification and ‘protein secretion’ issues of multiorgans and tumour infiltration of ‘T-cell regulatory (Tregs)’ and ‘CD56dim natural killer cell’ were detected. The authors’ findings are of potential clinical significance for the prognosis assessment and mechanistic exploration of colon cancer.

Abstract Image

对结肠癌患者E2F转录因子相关的七个特征预后模型的新研究
结肠癌是一种常见的胃肠道肿瘤,其发病机制涉及复杂的因素,尤其是一系列细胞周期相关基因。细胞周期中的E2F转录因子在结肠癌的发生中起着至关重要的作用。建立一种有效的以细胞e2f相关基因为靶点的结肠癌预后模型具有重要意义。这在以前没有报道过。作者首先通过整合TCGA-COAD (n = 521)、GSE17536 (n = 177)和GSE39582 (n = 585)队列的数据,探索E2F基因与结肠癌患者临床结局的联系。使用Cox回归和Lasso建模方法来确定涉及多个中心基因(CDKN2A, GSPT1, PNN, POLD3, PPP1R8, PTTG1和RFC1)的新型结肠癌预后模型。此外,还创建了一个e2f相关的nomogram,可以有效地预测结肠癌患者的生存率。此外,作者首先确定了两个E2F肿瘤簇,它们表现出不同的预后特征。有趣的是,基于e2f的分类和多器官的“蛋白质分泌”问题与“t细胞调节(Tregs)”和“CD56dim自然杀伤细胞”的肿瘤浸润之间的潜在联系被检测到。作者的发现对结肠癌的预后评估和机制探索具有潜在的临床意义。
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 求助全文
来源期刊
IET Systems Biology
IET Systems Biology 生物-数学与计算生物学
CiteScore
4.20
自引率
4.30%
发文量
17
审稿时长
>12 weeks
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.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信