基因突变是导致多层玫瑰花结胚胎肿瘤（ETMR）发生的关键因素。本研究旨在通过揭示 ETMR 的遗传驱动因素和免疫浸润来确定改进的治疗方法。 两名患有 ETMR 的兄弟姐妹均在宁夏医科大学总医院接受治疗。诊断涉及 MRI、苏木精和曙红 (HE) 以及免疫组织化学 (IHC) 染色。使用 GSE122077 和 GSE14296 数据集识别 ETMR 中的差异表达基因 (DEG)。 GO 和 KEGG 分析用于确定 ETMR 相关通路。全外显子组测序 (WES) 用于注释 ETMR 中的遗传变异。通过蛋白质-蛋白质相互作用（PPI）鉴定的核心基因形成了通过逻辑回归评估的诊断模型。单样本基因集富集分析 (ssGSEA) 评估了 ETMR 中的免疫浸润，检查免疫细胞和核心基因之间的相关性。两个兄弟姐妹被诊断患有 ETMR。在ETMR中，鉴定出135个DEG，其中25个基因注释有28个突变位点。此外，ETMR 相关途径包括细胞周期、突触功能和神经变性。通过蛋白质-蛋白质相互作用（PPI）筛选了三个 ETMR 相关核心基因（ALB、PSMD1 和 PAK2）。使用这些基因构建的诊断模型在训练集中显示 AUC 值为 0.901（95% CI：0.811-0.991），表明 ETMR 的预测准确。 ETMR 组织中 16 个免疫细胞的 ssGSEA 评分增强表明存在强烈的免疫反应。本研究确定了与 ETMR 中三个核心变异基因（ALB、PSMD1、PAK2）和增强的免疫细胞活性相关的诊断模型。它揭示了 ETMR 中关键的遗传特征和显着的免疫反应。© 2024。作者获得 Springer-Verlag GmbH 德国（Springer Nature 旗下公司）的独家许可。

Genetic mutations stand as pivotal factors leading to the occurrence of embryonal tumor with multilayered rosettes (ETMR). This study aims to identify improved treatment approaches by unraveling the genetic drivers and immune infiltration in ETMR.Two siblings with ETMR, treated at the General Hospital of Ningxia Medical University, were enrolled. Diagnosis involved MRI, Hematoxylin and Eosin (HE), and immunohistochemical (IHC) staining. Differentially expressed genes (DEGs) in ETMR were identified using GSE122077 and GSE14296 datasets. GO and KEGG analyses were used to determine ETMR-related pathways. Whole exome sequencing (WES) was utilized to annotate genetic variations in ETMR. Core genes, identified by protein-protein interaction (PPI), formed a diagnostic model evaluated by Logistic Regression. Single-sample Gene Set Enrichment Analysis (ssGSEA) assessed immune infiltration in ETMR, examining correlations between immune cells and core genes.Two siblings were diagnosed with ETMR. In ETMR, 135 DEGs were identified, of which 25 genes were annotated with 28 mutation sites. Moreover, ETMR-related pathways included cell cycle, synaptic functions, and neurodegeneration. Three ETMR-related core genes (ALB, PSMD1, and PAK2) were screened by protein-protein interaction (PPI). The diagnostic model constructed using these genes demonstrated an AUC value of 0.901 (95% CI: 0.811-0.991) in the training set, indicating accurate predictions in ETMR. Enhanced ssGSEA scores for 16 immune cells in ETMR tissues suggested a strong immune response.This study identifies diagnostic models associated with three core variant genes (ALB, PSMD1, PAK2) and enhanced immune cell activity in ETMR. It reveals crucial genetic features and significant immune responses in ETMR.© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.