Yan Zongcai, He Meiling, He Lifeng, Wei Liuxia, Zhang Yumei
Department of Medical Oncology, Guangxi Medical University Cancer Hospital, No. 71 Hedi Road, Nanning, 530021, Guangxi, People's Republic of China.
Department of Thoracic Surgery, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, 530000, Guangxi, People's Republic of China.
Discov Oncol. 2025 Jun 14;16(1):1094. doi: 10.1007/s12672-025-02965-7.
Methylation at the N atom of adenosine (mA) of RNA has been linked to immune responses to various types of tumors. How mA methylation affects tumorigenicity, progression, and tumor microenvironment in hepatocellular carcinoma (HCC) is unclear.
Consensus clustering was used to define mA methylation patterns based on expression of 26 regulatory factors in HCC. The relative abundance of various immune cell types in the tumor microenvironment was quantified using single-sample gene set enrichment analysis. Cox regression with LASSO was used to screen for genes whose expression correlated with survival of patients with HCC.
Two patterns of mA methylation in HCC were identified: pattern C1 was associated with abundant tumor infiltration by activated CD8 T cells and by effector memory CD8 T cells, as well as longer survival; pattern C2 was associated with abundant tumor infiltration by activated CD4 T cells and by type 2 helper T cells, as well as with shorter survival. Cox regression identified a seven-gene signature capable of predicting the characteristics of the tumor microenvironment and overall survival in HCC: patients in the high-risk group had a lower immunophenoscore, higher TIDE score, and worse survival.
Patterns of mA methylation in HCC are related to immune cell characteristics of the tumor microenvironment and to disease progression and prognosis. Analyzing these patterns in detail may clarify when and how the HCC responds to checkpoint inhibitors and guide the personalization of immunotherapy.
RNA中腺苷（mA）的N原子甲基化与对各种类型肿瘤的免疫反应有关。目前尚不清楚mA甲基化如何影响肝细胞癌（HCC）的致瘤性、进展及肿瘤微环境。
基于HCC中26种调控因子的表达，采用一致性聚类来定义mA甲基化模式。使用单样本基因集富集分析对肿瘤微环境中各种免疫细胞类型的相对丰度进行定量。采用带LASSO的Cox回归筛选与HCC患者生存相关的基因表达。
在HCC中鉴定出两种mA甲基化模式：模式C1与活化的CD8 T细胞和效应记忆CD8 T细胞的大量肿瘤浸润以及更长的生存期相关；模式C2与活化的CD4 T细胞和2型辅助性T细胞的大量肿瘤浸润以及较短的生存期相关。Cox回归确定了一个七基因特征，能够预测HCC的肿瘤微环境特征和总生存期：高危组患者的免疫表型评分较低、TIDE评分较高且生存期较差。
HCC中的mA甲基化模式与肿瘤微环境的免疫细胞特征以及疾病进展和预后相关。详细分析这些模式可能会阐明HCC何时以及如何对检查点抑制剂作出反应，并指导免疫治疗的个性化。
