骨肉瘤（OS）是一种侵袭和转移能力极强的骨肿瘤，严重影响儿童和青少年的健康。许多研究表明 OS 与上皮间质转化 (EMT) 之间存在联系。我们的目的是整合 EMT 相关基因 (EMT-RG) 来预测 OS 患者的预后、免疫浸润和治疗反应。我们使用共识聚类来识别潜在的 EMT 相关 OS 分子亚型。对每个亚型进行体细胞突变、肿瘤免疫微环境和功能富集分析。接下来，我们构建了 EMT 相关风险特征，并通过 Kaplan-Meier (K-M) 分析生存和受试者工作特征 (ROC) 曲线对其进行评估。此外，我们构建了列线图来更准确地预测 OS 患者的临床结果。通过肿瘤免疫功能障碍和排除 (TIDE) 分析来分析 OS 患者免疫治疗的反应效果，同时使用 oncoPredict 来分析化疗药物的敏感性。最后，通过单细胞RNA测序（scRNA-seq）数据分析研究了hub基因的表达模式。总共鉴定了53个与预后相关的EMT-RDG，将OS样本分为两个独立的亚组。 EMT 高亚组表现出良好的总体生存率和更活跃的免疫反应。发现 EMT 相关 DEG 和功能以及与 OS 发展相关的途径之间存在显着相关性。此外，还建立了风险特征，并根据风险评分将 OS 患者分为两类。该签名具有良好的预测性能，可以被认为是操作系统的独立预测因素。此外，风险评分较高的患者对五种药物表现出更好的敏感性，而两个风险亚组之间的免疫治疗反应不存在显着差异。 scRNA-seq数据分析显示了中心基因的不同表达模式。我们开发了一种新的EMT相关风险特征，可以被视为OS的独立预测因子，这可能有助于改善临床结果预测并指导OS患者的个性化治疗。版权所有 © 2024 李龙、刘、龙、高。

Osteosarcoma (OS), a bone tumor with high ability of invasion and metastasis, has seriously affected the health of children and adolescents. Many studies have suggested a connection between OS and the epithelial-mesenchymal transition (EMT). We aimed to integrate EMT-Related genes (EMT-RGs) to predict the prognosis, immune infiltration, and therapeutic response of patients with OS.We used consensus clustering to identify potential EMT-Related OS molecular subtypes. Somatic mutation, tumor immune microenvironment, and functional enrichment analyses were performed for each subtype. We next constructed an EMT-Related risk signature and evaluated it by Kaplan-Meier (K-M) analysis survival and receiver operating characteristic (ROC) curves. Moreover, we constructed a nomogram to more accurately predict OS patients' clinical outcomes. Response effects of immunotherapy in OS patients was analyzed by Tumor Immune Dysfunction and Exclusion (TIDE) analysis, while sensitivity for chemotherapeutic agents was analyzed using oncoPredict. Finally, the expression patterns of hub genes were investigated by single-cell RNA sequencing (scRNA-seq) data analysis.A total of 53 EMT-RDGs related to prognosis were identified, separating OS samples into two separate subgroups. The EMT-high subgroup showed favourable overall survival and more active immune response. Significant correlations were found between EMT-Related DEGs and functions as well as pathways linked to the development of OS. Additionally, a risk signature was established and OS patients were divided into two categories based on the risk scores. The signature presented a good predictive performance and could be recognized as an independent predictive factor for OS. Furthermore, patients with higher risk scores exhibited better sensitivity for five drugs, while no significant difference existed in immunotherapy response between the two risk subgroups. scRNA-seq data analysis displayed different expression patterns of the hub genes.We developed a novel EMT-Related risk signature that can be considered as an independent predictor for OS, which may help improve clinical outcome prediction and guide personalized treatments for patients with OS.Copyright © 2024 Li, Long, Liu, Long and Gao.