Characterization of RNA Processing Genes in Colon Cancer for Predicting Clinical Outcomes.

IF 3.4 Q2 MEDICINE, RESEARCH & EXPERIMENTAL
Biomarker Insights Pub Date : 2024-08-18 eCollection Date: 2024-01-01 DOI:10.1177/11772719241258642
Jianwen Hu, Yingze Ning, Yongchen Ma, Lie Sun, Guowei Chen
{"title":"Characterization of RNA Processing Genes in Colon Cancer for Predicting Clinical Outcomes.","authors":"Jianwen Hu, Yingze Ning, Yongchen Ma, Lie Sun, Guowei Chen","doi":"10.1177/11772719241258642","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Colon cancer is associated with multiple levels of molecular heterogeneity. RNA processing converts primary transcriptional RNA to mature RNA, which drives tumourigenesis and its maintenance. The characterisation of RNA processing genes in colon cancer urgently needs to be elucidated.</p><p><strong>Methods: </strong>In this study, we obtained 1033 relevant samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to explore the heterogeneity of RNA processing phenotypes in colon cancer. Firstly, Unsupervised hierarchical cluster analysis detected 4 subtypes with specific clinical outcomes and biological features via analysis of 485 RNA processing genes. Next, we adopted the least absolute shrinkage and selection operator (LASSO) as well as Cox regression model with penalty to characterise RNA processing-related prognostic features.</p><p><strong>Results: </strong>An RNA processing-related prognostic risk model based on 10 genes including <i>FXR1</i>, <i>MFAP1</i>, <i>RBM17</i>, <i>SAGE1</i>, <i>SNRPA1</i>, <i>SRRM4</i>, <i>ADAD1</i>, <i>DDX52</i>, <i>ERI1</i>, and <i>EXOSC7</i> was identified finally. A composite prognostic nomogram was constructed by combining this feature with the remaining clinical variables including TNM, age, sex, and stage. Genetic variation, pathway activation, and immune heterogeneity with risk signatures were also analysed via bioinformatics methods. The outcomes indicated that the high-risk subgroup was associated with higher genomic instability, increased proliferative and cycle characteristics, decreased tumour killer CD8<sup>+</sup> T cells and poorer clinical prognosis than the low-risk group.</p><p><strong>Conclusion: </strong>This prognostic classifier based on RNA-edited genes facilitates stratification of colon cancer into specific subgroups according to TNM and clinical outcomes, genetic variation, pathway activation, and immune heterogeneity. It can be used for diagnosis, classification and targeted treatment strategies comparable to current standards in precision medicine. It provides a rationale for elucidation of the role of RNA editing genes and their clinical significance in colon cancer as prognostic markers.</p>","PeriodicalId":47060,"journal":{"name":"Biomarker Insights","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2024-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11331464/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biomarker Insights","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/11772719241258642","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
引用次数: 0

Abstract

Objective: Colon cancer is associated with multiple levels of molecular heterogeneity. RNA processing converts primary transcriptional RNA to mature RNA, which drives tumourigenesis and its maintenance. The characterisation of RNA processing genes in colon cancer urgently needs to be elucidated.

Methods: In this study, we obtained 1033 relevant samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to explore the heterogeneity of RNA processing phenotypes in colon cancer. Firstly, Unsupervised hierarchical cluster analysis detected 4 subtypes with specific clinical outcomes and biological features via analysis of 485 RNA processing genes. Next, we adopted the least absolute shrinkage and selection operator (LASSO) as well as Cox regression model with penalty to characterise RNA processing-related prognostic features.

Results: An RNA processing-related prognostic risk model based on 10 genes including FXR1, MFAP1, RBM17, SAGE1, SNRPA1, SRRM4, ADAD1, DDX52, ERI1, and EXOSC7 was identified finally. A composite prognostic nomogram was constructed by combining this feature with the remaining clinical variables including TNM, age, sex, and stage. Genetic variation, pathway activation, and immune heterogeneity with risk signatures were also analysed via bioinformatics methods. The outcomes indicated that the high-risk subgroup was associated with higher genomic instability, increased proliferative and cycle characteristics, decreased tumour killer CD8+ T cells and poorer clinical prognosis than the low-risk group.

Conclusion: This prognostic classifier based on RNA-edited genes facilitates stratification of colon cancer into specific subgroups according to TNM and clinical outcomes, genetic variation, pathway activation, and immune heterogeneity. It can be used for diagnosis, classification and targeted treatment strategies comparable to current standards in precision medicine. It provides a rationale for elucidation of the role of RNA editing genes and their clinical significance in colon cancer as prognostic markers.

表征结肠癌中的 RNA 处理基因,预测临床结果。
目的:结肠癌具有多层次的分子异质性。RNA 加工将初级转录 RNA 转化为成熟 RNA,从而推动肿瘤的发生和维持。结肠癌中 RNA 加工基因的特征亟待阐明:本研究从癌症基因组图谱(The Cancer Genome Atlas,TCGA)和基因表达总库(Gene Expression Omnibus,GEO)数据库中获取了 1033 个相关样本,以探索结肠癌中 RNA 处理表型的异质性。首先,无监督分层聚类分析通过分析 485 个 RNA 处理基因,发现了具有特定临床结果和生物学特征的 4 个亚型。接着,我们采用最小绝对收缩和选择算子(LASSO)以及带惩罚的考克斯回归模型来描述与RNA加工相关的预后特征:结果:最终确定了基于 10 个基因的 RNA 处理相关预后风险模型,包括 FXR1、MFAP1、RBM17、SAGE1、SNRPA1、SRRM4、ADAD1、DDX52、ERI1 和 EXOSC7。通过将这一特征与其余临床变量(包括 TNM、年龄、性别和分期)相结合,构建了综合预后提名图。此外,还通过生物信息学方法分析了风险特征的遗传变异、通路激活和免疫异质性。结果表明,与低风险组相比,高风险亚组与较高的基因组不稳定性、增殖和周期特征增加、肿瘤杀伤CD8+ T细胞减少以及较差的临床预后有关:结论:这种基于 RNA 编辑基因的预后分类器有助于根据 TNM 和临床结果、基因变异、通路激活和免疫异质性将结肠癌分为特定的亚组。它可用于诊断、分类和靶向治疗策略,与目前的精准医学标准相当。它为阐明 RNA 编辑基因作为预后标志物在结肠癌中的作用及其临床意义提供了理论依据。
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
Biomarker Insights
Biomarker Insights MEDICINE, RESEARCH & EXPERIMENTAL-
CiteScore
6.00
自引率
0.00%
发文量
26
审稿时长
8 weeks
期刊介绍: An open access, peer reviewed electronic journal that covers all aspects of biomarker research and clinical applications.
×
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