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Prognostic signature analysis and survival prediction of esophageal cancer based on N6-methyladenosine associated lncRNAs

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机构: [1]School of Mathematics and Statistics, Southwest University, Chongqing 400715, China. [2]Beidahuang Industry Group General Hospital, Harbin 150000, China. [3]Yucai School Attached to Sichuan Chengdu No. 7 High School, Chengdu 610503, China. [4]Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 611730, China.
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关键词: esophageal cancer long noncoding RNA N6-methyladenosine prognostic signature biomarker

摘要:
Esophageal cancer (ESCA) has a bad prognosis. Long non-coding RNA (lncRNA) impacts on cell proliferation. However, the prognosis function of N6-methyladenosine (m6A)-associated lncRNAs (m6A-lncRNAs) in ESCA remains unknown. Univariate Cox analysis was applied to investigate prognosis related m6A-lncRNAs, based on which the samples were clustered. Wilcoxon rank and Chi-square tests were adopted to compare the clinical traits, survival, pathway activity and immune infiltration in different clusters where overall survival, clinical traits (N stage), tumor-invasive immune cells and pathway activity were found significantly different. Through least absolute shrinkage and selection operator and proportional hazard (Lasso-Cox) model, five m6A-lncRNAs were selected to construct the prognostic signature (m6A-lncSig) and risk score. To investigate the link between risk score and clinical traits or immunological microenvironments, Chi-square test and Spearman correlation analysis were utilized. Risk score was found connected with N stage, tumor stage, different clusters, macrophages M2, B cells naive and T cells CD4 memory resting. Risk score and tumor stage were found as independent prognostic variables. And the constructed nomogram model had high accuracy in predicting prognosis. The obtained m6A-lncSig could be taken as potential prognostic biomarker for ESCA patients. This study offers a theoretical foundation for clinical diagnosis and prognosis of ESCA.© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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出版当年[2023]版
大类 | 3 区 生物学
小类 | 3 区 生物工程与应用微生物 4 区 遗传学
最新[2023]版
大类 | 3 区 生物学
小类 | 3 区 生物工程与应用微生物 4 区 遗传学
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第一作者机构: [1]School of Mathematics and Statistics, Southwest University, Chongqing 400715, China.
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通讯机构: [1]School of Mathematics and Statistics, Southwest University, Chongqing 400715, China. [4]Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 611730, China.
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