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基于 N6-甲基腺苷相关长非编码 RNA 的食管癌预后特征分析与生存预测

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

机构信息

School of Mathematics and Statistics, Southwest University, Chongqing 400715, China.

Beidahuang Industry Group General Hospital, Harbin 150000, China.

出版信息

Brief Funct Genomics. 2024 May 15;23(3):239-248. doi: 10.1093/bfgp/elad028.

Abstract

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.

摘要

食管癌(ESCA)预后不良。长链非编码 RNA(lncRNA)影响细胞增殖。然而,N6-甲基腺苷(m6A)相关 lncRNA(m6A-lncRNA)在 ESCA 中的预后功能尚不清楚。采用单因素 Cox 分析探讨与预后相关的 m6A-lncRNA,基于此对样本进行聚类。采用 Wilcoxon 秩和检验和卡方检验比较不同聚类中的临床特征、生存、通路活性和免疫浸润,其中总生存期、临床特征(N 分期)、肿瘤浸润免疫细胞和通路活性存在显著差异。通过最小绝对收缩和选择算子和比例风险(Lasso-Cox)模型,选择了 5 个 m6A-lncRNA 来构建预后特征(m6A-lncSig)和风险评分。为了研究风险评分与临床特征或免疫微环境之间的关系,采用卡方检验和 Spearman 相关分析。风险评分与 N 分期、肿瘤分期、不同聚类、巨噬细胞 M2、B 细胞初始和 T 细胞 CD4 记忆静息有关。风险评分和肿瘤分期被认为是独立的预后变量。所构建的列线图模型在预测预后方面具有较高的准确性。所得的 m6A-lncSig 可作为 ESCA 患者潜在的预后生物标志物。本研究为 ESCA 的临床诊断和预后提供了理论基础。

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