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甲状腺癌中预后性m6A相关lncRNA和mRNA模型的开发与验证

Development and validation of prognostic m6A-related lncRNA and mRNA model in thyroid cancer.

作者信息

Zhu Yu, Yu Tian, Huang Ju, Ma Xitao, Shen Tao, Li Annuo, Yue Rensong

机构信息

Department of Endocrinology, Hospital of Chengdu University of Traditional Chinese Medicine Chengdu 610075, Sichuan, P. R. China.

Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College No. 1 Shuaifuyuan, Wangfujin, Dongcheng District, Beijing 100730, P. R. China.

出版信息

Am J Cancer Res. 2022 Jul 15;12(7):3259-3279. eCollection 2022.

Abstract

Although N6-methyladenosine (m6A) regulators and lncRNAs influence the carcinogenesis of thyroid cancer (THCA), the association between m6A-related lncRNAs and THCA remains unexplored. Therefore, we have developed and validated a prognostic model based on m6A-related lncRNAs and mRNAs in THCA. Data from the Cancer Genome Atlas were used to analyze the expression and prognostic characteristics of m6A-related lncRNAs and mRNAs in THCA. Univariate Cox regression analysis was used to screen out independent prognostic factors, while Lasso Cox regression was performed to construct m6A-related lncRNA and mRNA models. The correlation between the prognostic models and gene mutation, immune cell infiltration, tumor microenvironment score, tumor mutational burden, and microsatellite instability were assessed. The prognostic models showed excellent accuracy in predicting the prognosis of patients with THCA. Our study established an m6A-related nomogram capable of predicting the prognosis of patients with THCA. In addition, the hub lncRNAs and mRNAs provide insight into improving the prognosis of THCA. These findings can improve our understanding of m6A modifications in THCA and the prognosis and treatment strategies of THCA.

摘要

尽管N6-甲基腺苷(m6A)调节剂和长链非编码RNA(lncRNA)影响甲状腺癌(THCA)的致癌作用,但m6A相关lncRNA与THCA之间的关联仍未得到探索。因此,我们开发并验证了一种基于THCA中m6A相关lncRNA和mRNA的预后模型。来自癌症基因组图谱的数据用于分析THCA中m6A相关lncRNA和mRNA的表达及预后特征。单因素Cox回归分析用于筛选出独立的预后因素,同时进行Lasso Cox回归以构建m6A相关lncRNA和mRNA模型。评估了预后模型与基因突变、免疫细胞浸润、肿瘤微环境评分、肿瘤突变负荷和微卫星不稳定性之间的相关性。预后模型在预测THCA患者的预后方面显示出优异的准确性。我们的研究建立了一种能够预测THCA患者预后的m6A相关列线图。此外,核心lncRNA和mRNA为改善THCA的预后提供了见解。这些发现可以增进我们对THCA中m6A修饰以及THCA的预后和治疗策略的理解。

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