Joshi Kandarp, Yuan Menglang, Katsushima Keisuke, Saulnier Olivier, Ray Animesh, Amankwah Ernest, Stapleton Stacie, Jallo George, Taylor Michael D, Eberhart Charles G, Perera Ranjan J
Johns Hopkins University.
Institut Curie, PSL University.
Res Sq. 2024 Sep 2:rs.3.rs-4810070. doi: 10.21203/rs.3.rs-4810070/v1.
Medulloblastoma, the most common malignant pediatric brain tumor, is classified into four main molecular subgroups, but group 3 and group 4 tumors are difficult to subclassify and have a poor prognosis. Rapid point-of-care diagnostic and prognostic assays are needed to improve medulloblastoma risk stratification and management. N6-methyladenosine (m6A) is a common RNA modification and long non-coding RNAs (lncRNAs) play a central role in tumor progression, but their impact on gene expression and associated clinical outcomes in medulloblastoma are unknown. Here we analyzed 469 medulloblastoma tumor transcriptomes to identify lncRNAs co-expressed with m6A regulators. Using LASSO-Cox analysis, we identified a five-gene m6A-associated lncRNA signature (M6LSig) significantly associated with overall survival, which was combined in a prognostic clinical nomogram. Using expression of the 67 m6A-associated lncRNAs, a subgroup classification model was generated using the XGBoost machine learning algorithm, which had a classification accuracy > 90%, including for group 3 and 4 samples. All M6LSig genes were significantly correlated with at least one immune cell type abundance in the tumor microenvironment, and the risk score was positively correlated with CD4 naïve T cell abundance and negatively correlated with follicular helper T cells and eosinophils. Knockdown of key m6A writer genes and in a group 3 medulloblastoma cell line (D425-Med) decreased cell proliferation and upregulated many M6LSig genes identified in our analysis, suggesting that the signature genes are functional in medulloblastoma. This study highlights a crucial role for m6A-dependent lncRNAs in medulloblastoma prognosis and immune responses and provides the foundation for practical clinical tools that can be rapidly deployed in clinical settings.
髓母细胞瘤是最常见的儿童恶性脑肿瘤,分为四个主要分子亚组,但3组和4组肿瘤难以进一步细分且预后较差。需要快速的即时诊断和预后检测方法来改善髓母细胞瘤的风险分层和管理。N6-甲基腺苷(m6A)是一种常见的RNA修饰,长链非编码RNA(lncRNA)在肿瘤进展中起核心作用,但它们对髓母细胞瘤基因表达及相关临床结果的影响尚不清楚。在此,我们分析了469个髓母细胞瘤肿瘤转录组,以鉴定与m6A调节因子共表达的lncRNA。使用LASSO-Cox分析,我们鉴定出一个与总生存期显著相关的五基因m6A相关lncRNA特征(M6LSig),并将其整合到一个预后临床列线图中。利用67个m6A相关lncRNA的表达,使用XGBoost机器学习算法生成了一个亚组分类模型,其分类准确率>90%,包括对3组和4组样本。所有M6LSig基因均与肿瘤微环境中至少一种免疫细胞类型的丰度显著相关,风险评分与初始CD4 T细胞丰度呈正相关,与滤泡辅助性T细胞和嗜酸性粒细胞呈负相关。在一个3组髓母细胞瘤细胞系(D425-Med)中敲低关键的m6A写入基因和 可降低细胞增殖,并上调我们分析中鉴定的许多M6LSig基因,这表明特征基因在髓母细胞瘤中具有功能。本研究强调了m6A依赖的lncRNA在髓母细胞瘤预后和免疫反应中的关键作用,并为可在临床环境中快速应用的实用临床工具奠定了基础。