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

被引:0
作者
He, Ting [1 ]
Gao, Zhipeng [3 ]
Lin, Ling [4 ]
Zhang, Xu [1 ]
Zou, Quan [2 ]
机构
[1] Southwest Univ, Sch Math & Stat, Chongqing 400715, Peoples R China
[2] Univ Elect Sci & Technol China, Inst Fundamental & Frontier Sci, Chengdu 611730, Peoples R China
[3] Beidahuang Ind Grp Gen Hosp, Harbin, Peoples R China
[4] Yucai Sch Attached Sichuan Chengdu 7 High Sch, Chengdu, Peoples R China
基金
中国国家自然科学基金;
关键词
esophageal cancer; long noncoding RNA; N6-methyladenosine; prognostic signature; biomarker; SQUAMOUS-CELL CARCINOMA; PD-L1; EXPRESSION; NONCODING RNAS; MESSENGER-RNA; PROLIFERATION; JPX; CONSTRUCTION; MIGRATION; INVASION; BIOLOGY;
D O I
10.1093/bfgp/elad028
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
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.
引用
收藏
页码:239 / 248
页数:10
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