Development and validation of stemness associated LncRNA based prognostic model for lung adenocarcinoma patients.

IF 1.9
Annesha Chatterjee, Seema Khadirnaikar, Sudhanshu Shukla
{"title":"Development and validation of stemness associated LncRNA based prognostic model for lung adenocarcinoma patients.","authors":"Annesha Chatterjee,&nbsp;Seema Khadirnaikar,&nbsp;Sudhanshu Shukla","doi":"10.3233/CBM-200687","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>An increasing number of studies are indicating that the stemness phenotype is a critical determinant of the Lung adenocarcinoma (LUAD) patient's response. Thus, it is crucial to identify novel biomarkers for stemness determination.</p><p><strong>Objective: </strong>Here, we aim to develop a robust LncRNAs based prognostic signature with a stemness association for the LUAD patients.</p><p><strong>Methods: </strong>RNA-seq and clinical data were downloaded from the existing database. The data were analysed using Cox regression, KM-plot, GSEA, and T-test.</p><p><strong>Results: </strong>Initially, we used the TCGA dataset to characterize the stemness phenotype in LUAD. The commonly expressed LncRNAs in TCGA and MCTP cohort were then used as input for the Cox-regression analysis. The top three LncRNAs were selected to build a prognostic model, which was the best prognosticator in multivariate analysis with stage and previously published prognosticators. The characterization of poor surviving patients using various analysis showed high stemness properties and low expression of differentiation markers. Furthermore, we validated the prognostic score in an independent MCTP cohort of patients. In the MCTP cohort, prognostic score significantly predicted survival independent of stage and previous prognosticators.</p><p><strong>Conclusion: </strong>Taken together, in this study, we have developed and validated a new prognostic score associated with the stemness phenotype.</p>","PeriodicalId":520578,"journal":{"name":"Cancer biomarkers : section A of Disease markers","volume":" ","pages":"131-142"},"PeriodicalIF":1.9000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer biomarkers : section A of Disease markers","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3233/CBM-200687","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Background: An increasing number of studies are indicating that the stemness phenotype is a critical determinant of the Lung adenocarcinoma (LUAD) patient's response. Thus, it is crucial to identify novel biomarkers for stemness determination.

Objective: Here, we aim to develop a robust LncRNAs based prognostic signature with a stemness association for the LUAD patients.

Methods: RNA-seq and clinical data were downloaded from the existing database. The data were analysed using Cox regression, KM-plot, GSEA, and T-test.

Results: Initially, we used the TCGA dataset to characterize the stemness phenotype in LUAD. The commonly expressed LncRNAs in TCGA and MCTP cohort were then used as input for the Cox-regression analysis. The top three LncRNAs were selected to build a prognostic model, which was the best prognosticator in multivariate analysis with stage and previously published prognosticators. The characterization of poor surviving patients using various analysis showed high stemness properties and low expression of differentiation markers. Furthermore, we validated the prognostic score in an independent MCTP cohort of patients. In the MCTP cohort, prognostic score significantly predicted survival independent of stage and previous prognosticators.

Conclusion: Taken together, in this study, we have developed and validated a new prognostic score associated with the stemness phenotype.

基于干性相关LncRNA的肺腺癌患者预后模型的建立和验证。
背景:越来越多的研究表明,干性表型是肺腺癌(LUAD)患者反应的关键决定因素。因此,鉴定新的生物标志物是至关重要的。目的:在这里,我们的目标是开发一个强大的基于lncrna的预后特征,与LUAD患者的干性相关。方法:从现有数据库中下载RNA-seq和临床资料。采用Cox回归、KM-plot、GSEA和t检验对数据进行分析。结果:最初,我们使用TCGA数据集来表征LUAD的干性表型。然后将TCGA和MCTP队列中常见表达的lncrna作为cox回归分析的输入。选择前三名的lncrna构建预后模型,在多变量分析中以分期和先前发表的预后因子为最佳预后因子。通过各种分析,生存差患者的特征显示出高干性和低分化标志物的表达。此外,我们在一个独立的MCTP患者队列中验证了预后评分。在MCTP队列中,预后评分显著地预测了独立于分期和既往预后者的生存。结论:总的来说,在这项研究中,我们已经开发并验证了一种与干性表型相关的新的预后评分。
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
自引率
0.00%
发文量
0
×
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:604180095
Book学术官方微信