Department of Traditional Chinese Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Gene Hospital of Henan Province, Precision Medicine Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Front Immunol. 2022 Mar 24;13:805967. doi: 10.3389/fimmu.2022.805967. eCollection 2022.
RNA methylation plays crucial roles in gene expression and has been indicated to be involved in tumorigenesis, while it is still unclear whether m1A modifications have potential roles in the prognosis of hepatocellular carcinoma (HCC). In this study, we comprehensively analyzed RNA sequencing (RNA-seq) data and clinical information using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We collected 10 m1A regulators and performed consensus clustering to determine m1A modification patterns in HCC. The CIBERSORT method was utilized to evaluate the level of immune cell infiltration. Principal component analysis was used to construct the m1A-score model. In the TCGA-LIHC cohort, the expression of all 10 m1A regulators was higher in tumor tissues than in normal control tissues, and 8 of 10 genes were closely related to the prognosis of HCC patients. Two distinct m1A methylation modification patterns (Clusters C1 and C2) were identified by the 10 regulators and were associated with different overall survival, TNM stage and tumor microenvironment (TME) characteristics. Based on the differentially expressed genes (DEGs) between C1 and C2, we identified three gene clusters (Clusters A, B and C). C1 with a better prognosis was mainly distributed in Cluster C, while Cluster A contained the fewest samples of C1. An m1A-score model was constructed using five m1A regulators related to prognosis. Patients with higher m1A scores showed a poorer prognosis than those with lower scores in the TCGA-LIHC and GSE14520 datasets. In conclusions, our study showed the vital role of m1A modification in the TME and progression of HCC. Quantitative evaluation of the m1A modification patterns of individual patients facilitates the development of more effective biomarkers for predicting the prognosis of patients with HCC.
RNA 甲基化在基因表达中起着至关重要的作用，并且已经表明它参与了肿瘤发生，而 m1A 修饰是否在肝细胞癌 (HCC) 的预后中具有潜在作用仍不清楚。在这项研究中，我们使用癌症基因组图谱 (TCGA) 和基因表达综合 (GEO) 数据库全面分析了 RNA 测序 (RNA-seq) 数据和临床信息。我们收集了 10 个 m1A 调节剂，并进行共识聚类以确定 HCC 中的 m1A 修饰模式。CIBERSORT 方法用于评估免疫细胞浸润水平。主成分分析用于构建 m1A 评分模型。在 TCGA-LIHC 队列中，所有 10 个 m1A 调节剂在肿瘤组织中的表达均高于正常对照组织，其中 8 个基因与 HCC 患者的预后密切相关。通过 10 个调节剂鉴定出两种不同的 m1A 甲基化修饰模式 (簇 C1 和 C2)，它们与不同的总体生存、TNM 分期和肿瘤微环境 (TME) 特征相关。基于 C1 和 C2 之间的差异表达基因 (DEGs)，我们鉴定了三个基因簇 (簇 A、B 和 C)。预后较好的 C1 主要分布在 C 簇中，而 C1 中包含的 A 簇样本最少。使用与预后相关的五个 m1A 调节剂构建了 m1A 评分模型。在 TCGA-LIHC 和 GSE14520 数据集，m1A 评分较高的患者预后比评分较低的患者差。总之，我们的研究表明 m1A 修饰在 HCC 的 TME 和进展中起着至关重要的作用。对个体患者 m1A 修饰模式的定量评估有助于开发更有效的生物标志物，以预测 HCC 患者的预后。
