摘要
甲状腺癌发病率逐年升高,但其发病机制仍不清楚,阐述甲状腺癌的发病机制对改善甲状腺癌患者的预后至关重要。研究表明,m6A甲基化调控因子高度参与癌症发生发展,具有良好的潜在预后价值。因此,本研究通过生物信息学方法分析甲状腺癌中m6A甲基化调控因子的表达并构建基于m6A甲基化调控因子的甲状腺癌预后模型。
从TCGA数据库下载甲状腺癌m6A甲基化调控因子的表达数据和相应的临床病理资料,通过Wilcoxon检验分析20个m6A甲基化调控因子在肿瘤和正常组织的差异表达;用一致性聚类分析将甲状腺癌患者分为两个聚类,比较两个聚类患者临床病理因素和总体生存率的差异;Lasso Cox回归分析构建风险预测模型并用ROC曲线下面积(AUC)评估模型的预测能力。
19个m6A甲基化调控因子在甲状腺癌和正常组织表达具有统计学差异(均P<0.05),其中HNRNPC、IGF2BP2、FMR1在甲状腺癌组织中明显高表达,而其余表达下调。聚类分析示,cluster 1生存期低于cluster 2(P<0.05),颈淋巴结转移发生率明显高于cluster 2(P<0.01)。基于Lasso Cox回归分析筛选的4个基因(IGF2BP2、RBM15、YTHDF1、YTHDF3)构建风险评估模型,相比低风险组患者,高风险患者生存期明显缩短(P=0.007);ROC曲线示,该模型可以预测甲状腺癌患者的预后(AUC=0.731)。
关键词
过去几十年,甲状腺癌的发病率在全世界范围内迅速上
m6A甲基化修饰是指RNA的腺苷酸的第6位N处发生动态可逆的甲基化过程,在调控mRNA的转录、翻译、稳定、剪切、成熟等发挥了重要的生物学作用,其功能主要由甲基转移酶(writer)、去甲基化酶(eraser)和识别蛋白(reader)决
本研究利用癌症基因组图谱(The Cancer Genome Atlas,TCGA)数据库中甲状腺癌RNA-sep数据,系统性分析了20个m6A甲基化调控因子在甲状腺癌中的表达水平,再利用聚类分析和Lasso Cox回归分析筛选出预后相关基因及构建风险预测模型并进行危险分层,为甲状腺癌患者的临床诊疗和预后改善提供了重要的理论参考依据。
从TCGA数据库(https://portal.gdc.cancer.gov)下载了包含510例甲状腺癌组织和58例正常组织样本的RNA-seq数据集及相应临床数据。临床病理信息包括性别、年龄、肿瘤学多灶性、TNM分期、淋巴结转移、组织学类型、肿瘤位置和生存时间等,剔除RNA序列以及临床病理数据不全的样本,共492例癌组织和58例正常组织样本纳入最终分析。所有患者的病理分期按照美国癌症联合委员会(AJCC)2018年1月颁布了第8版甲状腺癌TNM分期。根据之前m6A甲基化在肿瘤中的研
为了从功能上阐明甲状腺癌中m6A调控因子的生物学特性,使用“consensusclusterplus”软件包对甲状腺癌患者进行一致性聚类分析并将患者分成cluster 1和cluster 2组。主成分分析(PCA)检测基于m6A调控因子表达是否能将两组患者明显区分,并探讨不同的临床病理因素和总体生存率在两组聚类中是否存在差异。
为了探讨m6A调控因子在甲状腺癌预后的作用,通过“glmnet”软件包进行Lasso Cox回归分析筛选预后相关的基因,并计算基因的相关回归系数,根据回归系数加权建立甲状腺癌预后风险评估公式,risk score=Coei*Expi, Coei表示回归系数,Expi表示m6A调控因子的表达量。据此公式计算每个患者的风险评分,以风险评分的中位数将患者分为高危组和低危组,比较两组总体生存率是否存在差异,ROC曲线下面积(AUC)评估模型的预测能力。
本研究共纳入492例甲状腺癌患者,平均年龄47.29岁,男女比列1∶2.76;临床病理TNM分期:Ι期276例,II期52例;III期109例,IV期55例;T分期:T1期135例,T2期162例,T3期172例,T4期23例;44.9%的患者出现颈部淋巴结转移;9例患者出现远处转移;228例肿瘤呈现出多灶性,占46.3%;肿瘤位于峡部、左侧、右侧、双侧分别为22、172、214,84例(
19个m6A甲基化调控因子在甲状腺癌和正常组织表达具有统计学差异(P<0.05),其中HNRNPC(P<0.001)、IGF2BP2(P<0.001)、FMR1(P<0.05)在甲状腺癌组织中明显高表达。相反,ALKBH5(P<0.001)、FTO(P<0.001)、METTL3(P<0.001)、METTL14(P<0.001)、METTL16(P<0.05)、WTAP(P<0.001)、YTHDF1(P<0.001)、YTHDF3(P<0.001)、YTHDC2(P<0.001)、YTHDC1(P<0.001)、ZC3H13(P<0.001)、HNRNPA2B1(P<0.001)、RBM15(P<0.001)、IGF2BP1(P<0.001)、IGF2BP3(P<0.001)和LRPPRC(P<0.001)在甲状腺癌标本中表达明显下调(

图1 m6A甲基化调控因子的基因表达及相关性 A:20个m6A甲基化调控因子在甲状腺癌和正常组织表达水平;B:Spearman相关分析m6A甲基化调控因子相关性;C:PPI网络评估m6A甲基化调控因子相互作用关系
Figure 1 Gene expression and correlations of the m6A methylation regulators A: The mRNA levels of the 20 m6A regulators in thyroid cancer; B: Spearman correlation analysis of co-expressions among the m6A regulators; C: PPI network of the m6A regulators
为了确定最佳的聚类数,采用一致性聚类分析对492例甲状腺癌患者进行聚类分组,共识矩阵k值为2时,甲状腺癌样本之间不存在交叉,聚类稳定性好(

图2 一致性聚类分析m6A甲基化调控因子 A:k值为2时,甲状腺癌样本之间不存在交叉,聚类稳定性好;B:主成分分析区分cluster 1和cluster 2;C:不同的聚类与临床病理的关系;D:总体生存率在两组聚类的情况
Figure 2 Consensus clustering analysis of the m6A RNA methylation regulators A: The most appropriate selection with clustering stability when k=2 used; B: Principal component analysis to distinguish cluster 1 and cluster 2; C: Heatmap and clinicopathologic features of the two clusters; D: The overall survival of cluster 1 and cluster 2
Lasso Cox回归分析筛选4个基因(IGF2BP2、RBM15、YTHDF1、YTHDF3),风险评分=(-0.129×IGF2BP2)+(0.308×RBM15)+(0.331×YTHDF1)+(0.813×YTHDF3)(

图3 m6A甲基化调控因子构建风险预后模型及检验 A:Lasso Cox回归模型的m6A基因及相关系数;B:风险评分和生存状态分布;C:高、低危组的生存曲线;D:ROC曲线评估模型的预测效能
Figure 3 Construction od prognostic risk model and validation A: Coefficients calculated by Lasso Cox regression analysis; B: Risk score and survival status distribution; C: Kaplan-Meier analysis of overall survival in high-risk and low-risk groups; D: Assessment of the prediction accuracy by ROC curve
甲状腺癌是一种常见的内分泌恶性肿瘤,发病率在世界范围内呈快速上升趋势,绝大部分甲状腺癌预后良
m6A修饰是近年来的研究热点,其作用主要参与转录后修饰,同时也参与了DNA修复、细胞分化、细胞重编程、细胞应激等生命活
为了从功能上阐明甲状腺癌中m6A调控因子的生物学特性,本研究对492例甲状腺癌患者进行一致性聚类分析后并分成cluster 1和cluster 2,cluster 1生存期低于cluster 2(P<0.05),相反,颈淋巴结转移发生率明显高于cluster 2(P<0.01)。暗示m6A调控因子能预测颈淋巴结转移并影响甲状腺癌患者预后,具有非常重要的临床实际意义。聚类分析在肝
此外,为了探讨m6A调控因子在甲状腺癌预后的作用,应用Lasso Cox回归分析筛选的4个基因(IGF2BP2、RBM15、YTHDF1、YTHDF3)构建风险评估模型,相比IGF2BP2,其余3个基因在甲状腺癌的研究中甚少,RBM15 不具有甲基转移酶的催化功能,但它可以结合METTL3和WTAP,并将这两个蛋白引导到特定的RNA位点进行m6A修
同时,本研究也存在一些缺陷,首先,该研究基于生物信息学构建的预后预测模型,无外部的实验数据验证,临床实际应用价值有限。其次,该研究只是初步探讨了m6A调控因子在甲状腺癌预后作用,不能完整的阐述甲状腺癌发生和演变的分子机制。最后,本研究基于492例甲状腺癌患者,样本量不大,后续需要进行更大的独立队列研究来验证。
综上,本研究基于TCGA数据库分析甲状腺癌m6A调控因子表达水平,通过Lasso Cox回归分析筛选的4个基因(IGF2BP2、RBM15、YTHDF1、YTHDF3)构建风险评估模型,AUC提示该模型具有良好的预测效能,将为甲状腺癌临床诊治提供潜在的理论依据。
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