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首页> 外文期刊>Frontiers in Cell and Developmental Biology >Comprehensive Analysis of the Immune Infiltrates and PD-L1 of m6A RNA Methylation Regulators in Hepatocellular Carcinoma
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Comprehensive Analysis of the Immune Infiltrates and PD-L1 of m6A RNA Methylation Regulators in Hepatocellular Carcinoma

机译:肝细胞癌M6A RNA甲基化调节剂免疫渗透和PD-L1的综合分析

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摘要

Hepatocellular carcinoma (HCC) is the most common type of liver cancer, which is significantly harmful to human health. Recently, the role of N6‐methyladenosine (m6A) RNA methylation in eukaryotic mRNA in the pathogenesis and prognosis of cancer has become increasingly obvious. Moreover, tumor microenvironment plays an important role in the regulation of tumorigenesis. In this research, the clinical data of 374 tumor and 50 normal patients was downloaded from the Cancer Genome Atlas (TCGA). Then 19 m6A RNA methylation regulators were selected from previous studies. HCC patients were clustered in cluster1 and cluster2, based on consensus clustering for the m6A RNA regulators. The m6A RNA methylation regulators were up-regulated in cluster1. The cluster1 was associated with higher PD-L1 expression level, higher immuescore, worse prognosis and distinct immune cell infiltration compared to cluster2. Furthermore, HCC patients were randomly divided into training dataset (170 patients) and validation dataset (170 patients). Univariate Cox analysis and LASSO regression to identify five risk signatures, including YTHDF1, YTHDF2, HNRNPC, WTAP and METTL3. HCC patients were divided into high-risk group and low-risk group according to riskscore. Similarly, the high-risk group was extremely associated with higher PD-L1 expression level, higher grade and worse overall survival (OS). Also, the cluster1 was mainly enrich in high-risk group. Receiver operating characteristic (ROC) and a nomogram were used to predictive the ability and the probability of 3‐ and 5‐year OS of HCC patients. In training dataset, the time-dependent ROC curve (AUC) reached 0.77, 0.67 and 0.68 at 1- year, 3- year and 5- year. And the 1- year, 3- year and 5- year AUC values were 0.7, 0.63 and 0.55 in validation dataset. The GSEA showed that MTOR signaling pathway and WNT signaling pathway were correlated with the cluster1 and high-risk group. Collectively, the research indicated that the m6A RNA regulators could play a crucial role in TIME in HCC. The m6A regulator-based risk signatures might predict the prognosis of HCC patients and provide new therapeutic targets in improving immunotherapeutic efficacy.
机译:肝细胞癌(HCC)是最常见的肝癌类型,这对人类健康有巨大危害。最近,N6-甲基腺苷(M6A)RNA甲基化在癌症发病机制和预后的真核mRNA中的作用变得越来越明显。此外,肿瘤微环境在肿瘤发生中起着重要作用。在本研究中,从癌症基因组地图集(​​TCGA)下载了374颗肿瘤和50例正常患者的临床资料。然后从先前的研究中选择19M6A RNA甲基化调节剂。基于M6A RNA调节剂的共识聚类,HCC患者在Cluster1和Cluster2中聚集。 M6A RNA甲基化调节剂在Cluster1中上调。与簇2相比,聚簇1与较高的PD-L1表达水平,更高的免疫调节,更差的预后和不同的免疫细胞浸润。此外,HCC患者随机分为训练数据集(170名患者)和验证数据集(170名患者)。单变量的Cox分析和套索回归识别五种风险签名,包括YTHDF1,YTHDF2,HNRNPC,WTAP和METT3。根据Riskscore,HCC患者分为高危组和低风险组。同样,高风险组与较高的PD-L1表达水平,更高的等级和总体存活率(OS)非常相关。此外,聚类主要是丰富的高风险组。接收器操作特征(ROC)和载体图用于预测HCC患者3和5年OS的能力和概率。在培训数据集中,时间依赖的ROC曲线(AUC)达到0.77,0.67和0.68,3年和5年。在验证数据集中为1年,3年,3年和5年的AUC值为0.7,0.63和0.55。 GSEA显示MTOR信号传导途径和WNT信号传导途径与簇1和高风险组相关。共同认为,该研究表明M6A RNA调节剂可以在HCC中发挥至关重要的作用。基于M6A调节剂的风险签名可能预测HCC患者的预后,并提供新的治疗靶标,提高免疫治疗疗效。

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