Cui Wenting, Luo Cancan, Zhou Lili, Yu Tiantian, Meng Yongsheng, Yu Qianqian, Lei Zhixiang, Wang Ya, Peng Lijuan, Luo Qingqing, Tang Duozhuang, Sun Ruifang, Yu Li
Department of Hematology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Key Laboratory of Hematology of Jiangxi Province Nanchang, Jiangxi, China.
Department of Hematology, The First People's Hospital of Jiujiang Jiujiang, Jiangxi, China.
Am J Cancer Res. 2024 Apr 15;14(4):1768-1783. doi: 10.62347/NXDR1826. eCollection 2024.
Genetic and epigenetic aberrations display an essential role in the initiation and progression of diffuse large B-cell lymphoma (DLBCL). 5-methylcytosine (mC), a common RNA modification, regulates various cellular processes and contributes to tumorigenesis and cancer progression. However, mC alterations in DLBCL remain unclear. Our research constructed an mC prognostic model utilizing GEO data sets, which can efficiently predict the prognosis of patients with DLBCL, and verified the mC prognostic model genes by immunohistochemistry analysis. This model was constructed using unsupervised consensus clustering analyses, Least Absolute Shrinkage and Selection Operator (LASSO), and multivariate Cox regression analyses. Based on the expression of mC genes in the model, patients with DLBCL could be effectively divided into groups with significant survival time differences. The mC risk-score signature demonstrated a highly significant independent prognostic value. Results from tumor microenvironment analyses revealed that mC genes altered the infiltration of eosinophils, Tregs, and M2 macrophages. Additionally, they regulated T cell activation by modulating the expression of CTLA4, PDL1, B2M, CD8A, ICOS, and other relevant immune checkpoint expressions. In conclusion, our study presents a robust mC prognostic model that effectively predicts prognosis in DLBCL. This model may offer a new approach for prognostic stratification and potential therapeutic interventions for patients with DLBCL.
遗传和表观遗传异常在弥漫性大B细胞淋巴瘤(DLBCL)的发生和发展中起着至关重要的作用。5-甲基胞嘧啶(mC)是一种常见的RNA修饰,可调节多种细胞过程,并促进肿瘤发生和癌症进展。然而,DLBCL中mC的改变仍不清楚。我们的研究利用GEO数据集构建了一个mC预后模型,该模型可以有效地预测DLBCL患者的预后,并通过免疫组织化学分析验证了mC预后模型基因。该模型是使用无监督一致性聚类分析、最小绝对收缩和选择算子(LASSO)以及多变量Cox回归分析构建的。基于模型中mC基因的表达,DLBCL患者可以有效地分为生存时间有显著差异的组。mC风险评分特征显示出高度显著的独立预后价值。肿瘤微环境分析结果表明,mC基因改变了嗜酸性粒细胞、调节性T细胞(Tregs)和M2巨噬细胞的浸润。此外,它们通过调节细胞毒性T淋巴细胞相关抗原4(CTLA4)、程序性死亡受体1(PDL1)、β2微球蛋白(B2M)、CD8α(CD8A)、诱导性共刺激分子(ICOS)和其他相关免疫检查点表达来调节T细胞活化。总之,我们的研究提出了一个强大的mC预后模型,该模型可以有效地预测DLBCL的预后。该模型可能为DLBCL患者的预后分层和潜在治疗干预提供一种新方法。