Chen Ziyi, Hua Yinghui
Department of Sports Medicine, Huashan Hospital, Fudan University, Shanghai, China.
Department of Sports Medicine, Huashan Hospital, Fudan University, Shanghai, China.
Cytokine. 2023 Oct;170:156313. doi: 10.1016/j.cyto.2023.156313. Epub 2023 Aug 5.
Accumulating evidence has shown that aberrant N7-methylguanosine (m7G) RNA methylation played an important role in the occurrence and development of cancer. However, knowledge of m7G modifications in inflammatory diseases is limited. Osteoarthritis (OA) is the most common arthritic disease with poor prognosis. Our research aimed to identify m7G-related hub biomarkers and investigate m7G regulator expression pattern in immune landscape of OA patients.
Gene expression profiles and their clinical information were obtained from the Gene Expression Omnibus (GEO) database, and differential analysis of 14 m7G-related regulators between elective OA and normal samples was performed. M7G-related hub genes for OA were mined based on single-sample gene set enrichment analysis (ssGSEA) and the random forest (RF) algorithm, and qRT-PCR was performed to confirm the abnormal expression of hub genes. Enrichment, protein-protein interaction (PPI), transcription factor (TF)-gene interaction and microRNA (miRNA)-gene coregulatory analysis based on m7G hub genes were performed. Then we predicted several candidate drugs related to m7G hub genes using DSigDB database. Moreover, we comprehensively evaluated m7G methylation patterns in OA samples and systematically correlated these modification patterns with the characteristics of immune cell infiltration. The m7G score was generated to quantify m7G methylation patterns for individual OA patients by the application of principal component analysis (PCA) algorithm.
We constructed an OA predictive model based on 4 m7G hub genes (SNUPN, METTL1, EIF4E2 and CYFIP1). Two m7G methylation patterns in OA were discovered to show distinct biological characteristics, and an m7G score were generated. M7G cluster A and a higher m7G score were found to be related to an inflamed phenotype.
Our study was the first to comprehensively investigate the m7G methylation dysregulations in immune landscape during the progression of OA. These 4 m7G gene-related signatures can be used as novel OA biomarkers to predict the occurrence of OA. Evaluating the m7G methylation patterns of OA individuals will contribute to enhancing our cognition of immune infiltration characterization and guiding more effective immunotherapy strategies.
越来越多的证据表明，异常的N7-甲基鸟苷（m7G）RNA甲基化在癌症的发生和发展中起重要作用。然而，关于m7G修饰在炎症性疾病中的知识有限。骨关节炎（OA）是最常见的关节炎疾病，预后较差。我们的研究旨在鉴定与m7G相关的枢纽生物标志物，并研究OA患者免疫图谱中m7G调节剂的表达模式。
从基因表达综合数据库（GEO）中获取基因表达谱及其临床信息，并对择期OA样本和正常样本之间的14种m7G相关调节剂进行差异分析。基于单样本基因集富集分析（ssGSEA）和随机森林（RF）算法挖掘OA的m7G相关枢纽基因，并进行qRT-PCR以确认枢纽基因的异常表达。基于m7G枢纽基因进行富集、蛋白质-蛋白质相互作用（PPI）、转录因子（TF）-基因相互作用和微小RNA（miRNA）-基因共调节分析。然后，我们使用DSigDB数据库预测了几种与m7G枢纽基因相关的候选药物。此外，我们全面评估了OA样本中的m7G甲基化模式，并系统地将这些修饰模式与免疫细胞浸润特征相关联。通过应用主成分分析（PCA）算法生成m7G评分，以量化个体OA患者的m7G甲基化模式。
我们基于4个m7G枢纽基因（SNUPN、METTL1、EIF4E2和CYFIP1）构建了OA预测模型。发现OA中的两种m7G甲基化模式具有不同的生物学特征，并生成了m7G评分。发现m7G簇A和较高的m7G评分与炎症表型相关。
我们的研究首次全面研究了OA进展过程中免疫图谱中的m7G甲基化失调。这4种与m7G基因相关的特征可作为预测OA发生的新型OA生物标志物。评估OA个体的m7G甲基化模式将有助于增强我们对免疫浸润特征的认识，并指导更有效的免疫治疗策略。
