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单细胞和空间转录组学揭示了RNA甲基化相关的miRNA风险模型与肝细胞癌免疫浸润之间的相关性。

Single-cell and spatial transcriptomics reveal correlation between RNA methylation-related miRNA risk model and immune infiltration in hepatocellular carcinoma.

作者信息

Su Rong, Du Yong, Tian Pan, Ma Weifang, Hui Yongfeng, Yang Shaoqi

机构信息

Department of Gastroenterology, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, China.

Department of Anesthesiology, People's Hospital of Ningxia Hui Autonomous Region, Yinchuan, Ningxia, China.

出版信息

Front Oncol. 2025 May 9;15:1553239. doi: 10.3389/fonc.2025.1553239. eCollection 2025.

Abstract

INTRODUCTION

Increasing evidence highlights the pivotal role of RNA methylation and miRNAs in hepatocellular carcinoma (HCC). However, the risk associated with RNA methylation-related miRNAs (RMRMs) in the HCC immune microenvironment remains largely unknown. Here, we predicted the correlation between RMRM risk and immune cell infiltration in HCC using machine learning.

METHODS

MiRNA sequencing data was used to identify RMRMs. A risk score model of HCC was developed utilizing four RMRMs, including miR-551a, miR-4739, miR-326, and miR-210-3p.

RESULTS

Patients with high-risk scores exhibited poorer prognoses. Single-cell RNA sequencing (scRNA-seq) analysis revealed the high-risk group exhibited increased infiltration levels of several immune cell subtypes, including myeloid-derived suppressor cell (MDSC), macrophage, and T cells. The data integration of scRNA-seq and bulk RNA-seq showed the decreased TIDE score in the high-risk patients and the elevated levels of Macro-secreted phosphoprotein 1 (SPP1), MDSC-meiotic nuclear divisions 1 (MND1), γδ T cells, and Macro-complement C1q C chain (C1QC) predicted adverse prognosis. ScRNA-seq and spatial transcriptomics data integration unveiled the spatial distribution of RMRMs risk scores and their correlation with immune cell subtype localization. Risk model-based clustering of HCC samples revealed that cluster 2, characterized by a higher risk score, correlated with a poorer prognosis and reduced immune and stromal scores. In vitro, the overexpression of miR-4739 in Huh-7 cells significantly induced SPP1 macrophages, and the culture medium derived from SPP1 macrophages further promoted the proliferation and migration of Huh-7 cells. Furthermore, miR-4739 reduced m1A methylation by inhibiting tRNA methyltransferase 61A (TRMT61A) expression.

DISCUSSION

Our study reveals that the RMRM risk model could effectively predict the prognosis of HCC, and SPP1 macrophages regulated by miR-4739-RNA methylation promote the proliferation and migration of HCC cells. These results highlight the potential of RMRMs in predicting the prognosis of HCC.

摘要

引言

越来越多的证据凸显了RNA甲基化和微小RNA(miRNA)在肝细胞癌(HCC)中的关键作用。然而,在HCC免疫微环境中,与RNA甲基化相关的miRNA(RMRM)的风险仍很大程度上未知。在此,我们使用机器学习预测了HCC中RMRM风险与免疫细胞浸润之间的相关性。

方法

使用miRNA测序数据来识别RMRM。利用四个RMRM(包括miR-551a、miR-4739、miR-326和miR-210-3p)建立了HCC风险评分模型。

结果

高风险评分的患者预后较差。单细胞RNA测序(scRNA-seq)分析显示,高风险组中几种免疫细胞亚型的浸润水平增加,包括髓系来源的抑制细胞(MDSC)、巨噬细胞和T细胞。scRNA-seq和批量RNA-seq的数据整合显示,高风险患者的TIDE评分降低,而巨细胞分泌磷蛋白1(SPP1)、MDSC减数分裂核分裂1(MND1)、γδT细胞和巨细胞补体C1q C链(C1QC)水平升高预示着不良预后。scRNA-seq和空间转录组学数据整合揭示了RMRM风险评分的空间分布及其与免疫细胞亚型定位的相关性。基于风险模型的HCC样本聚类显示,以较高风险评分为特征的聚类2与较差的预后以及免疫和基质评分降低相关。在体外,Huh-7细胞中miR-4739的过表达显著诱导了SPP1巨噬细胞,并且来自SPP1巨噬细胞的培养基进一步促进了Huh-7细胞的增殖和迁移。此外,miR-4739通过抑制tRNA甲基转移酶61A(TRMT61A)的表达降低了m1A甲基化。

讨论

我们的研究表明,RMRM风险模型可以有效预测HCC的预后,并且由miR-4739-RNA甲基化调节的SPP1巨噬细胞促进了HCC细胞的增殖和迁移。这些结果凸显了RMRM在预测HCC预后方面的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0147/12098086/9748f38fa1f3/fonc-15-1553239-g001.jpg

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