[1]巴 颖,操利超,谌 芳,等.m6A相关lncRNA特征对口腔癌预后的预测价值[J].医学信息,2025,38(05):38-48.[doi:10.3969/j.issn.1006-1959.2025.05.006]
 BA Ying,CAO Lichao,CHEN Fang,et al.Predictive Value of m6A-related lncRNA Features for the Prognosis of Oral Cancer[J].Journal of Medical Information,2025,38(05):38-48.[doi:10.3969/j.issn.1006-1959.2025.05.006]
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m6A相关lncRNA特征对口腔癌预后的预测价值()
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医学信息[ISSN:1006-1959/CN:61-1278/R]

卷:
38卷
期数:
2025年05期
页码:
38-48
栏目:
临床信息学
出版日期:
2025-03-01

文章信息/Info

Title:
Predictive Value of m6A-related lncRNA Features for the Prognosis of Oral Cancer
文章编号:
1006-1959(2025)05-0038-11
作者:
巴 颖操利超谌 芳余晨笛卢晓萍张核子
深圳市核子基因科技有限公司研发部,广东 深圳 518071
Author(s):
BA Ying CAO Lichao CHEN Fang YU Chendi LU Xiaoping ZHANG Hezi
R & D Department of Shenzhen Nuclear Gene Technology Co., Ltd., Shenzhen 518071, Guangdong, China
关键词:
口腔癌N6-甲基腺苷非编码RNA预后模型肿瘤微环境
Keywords:
Oral cancer N6-methyladenosine Non-coding RNA Prognosis model Tumor microenvironment
分类号:
R739.8
DOI:
10.3969/j.issn.1006-1959.2025.05.006
文献标志码:
A
摘要:
目的 建立N6-甲基腺苷(m6A)相关的长链非编码RNA(lncRNA)标记预测口腔癌的预后。方法 基于TCGA数据库中HNSC队列的mRNA表达数据、临床信息和已发表文献中的m6A调控基因,通过Pearson相关性评估筛选m6A相关lncRNAs(mrlncRNAs)。通过单因素、LASSO及多因素回归分析构建口腔癌的mrlncRNAs预后模型并进行验证。结合临床特征构建列线图模型,综合评估预后模型的性能。结果 总获得与15个预后相关的mrlncRNAs,在训练数据集中构建的模型ROC曲线下的面积(AUC)发现,3年、4年和5年AUC分别为0.735、0.735和0.806,在测试集和整个数据集中AUC均大于0.6;高风险组的预后差于低风险组(P<0.05);预后风险评分与T分期相关(P<0.05),与病理分期和N分期无关(P>0.05);高风险组中CD8+T细胞、滤泡辅助性T细胞和Treg细胞的比例比低风险组低(P<0.05);较高的TMB与较差的预后相关(P<0.05);高风险组的免疫检查点分子的表达比低风险组低(P<0.05)。结论 基于15个mrlncRNAs特征构建的nomogram模型对于评估口腔癌具有良好的预后价值和预测准确性,而且有助于口腔癌患者的风险分层和预测免疫疗效,对于提高口腔癌患者生存率具有重要意义。
Abstract:
Objective To establish N6-methyladenosine (m6A)-related long non-coding RNA (lncRNA) markers to predict the prognosis of oral cancer. Methods Based on the mRNA expression data, clinical information and m6A regulatory genes in the published literature of the HNSC cohort in the TCGA database, m6A-related lncRNAs (mrlncRNAs) were screened by Pearson correlation evaluation. The prognostic model of mrlncRNAs in oral cancer was constructed and verified by univariate, LASSO and multivariate regression analysis. Combined with clinical features, a nomogram model was constructed to comprehensively evaluate the performance of the prognostic model. Results A total of 15 prognostic-related mrlncRNAs were obtained. The area under the ROC curve (AUC) of the model constructed in the training data set was found to be 0.735,0.735 and 0.806 for 3 years, 4 years and 5 years, respectively, and the AUC in the test set and the entire data set was greater than 0.6; the prognosis of the high-risk group was worse than that of the low-risk group (P<0.05). The prognostic risk score was correlated with T stage (P<0.05), but not with pathological stage and N stage (P>0.05). The proportion of CD8+ T cells, follicular helper T cells and Treg cells in the high-risk group was lower than that in the low-risk group (P<0.05). Higher TMB was associated with poorer prognosis (P<0.05). The expression of immune checkpoint molecules in the high risk group was lower than that in the low risk group (P<0.05). Conclusion The nomogram model based on the characteristics of 15 mrlncRNAs has good prognostic value and predictive accuracy for evaluating oral cancer, and is helpful to predict the risk stratification and immune efficacy of patients with oral cancer, which is of great significance for improving the survival rate of patients with oral cancer.

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更新日期/Last Update: 1900-01-01