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整合单细胞和批量RNA测序分析确定骨肉瘤中乳酸化相关特征。

Integrative single-cell and bulk RNA-seq analysis identifies lactylation-related signature in osteosarcoma.

作者信息

Xie Zhou, Qu Xiao, Zhang Jun, Huang Yanran, Runhan Zhao, Tang Dagang, Li Ningdao, Wang Zhule, Luo Xiaoji

机构信息

Department of Orthopedics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.

Department of Orthopedics, The First Affiliated Hospital of Chongqing Medical and Pharmaceutical College, Chongqing, 400060, China.

出版信息

Funct Integr Genomics. 2025 Mar 12;25(1):60. doi: 10.1007/s10142-025-01559-4.

Abstract

Osteosarcoma is the most common bone tumor and a highly aggressive malignant neoplasm. This study aims to elucidate the role of lactylation-related genes (LRGs) in osteosarcoma, with the goal of improving prognostic accuracy and enhancing the efficacy of immunotherapy. Using public datasets, we integrated differential and correlated genes based on single-cell sequencing AUCell scores and performed enrichment analysis and risk model construction on these genes. A total of 277 genes were found to be intricately linked with lactate metabolism. Using the uni-Cox and LASSO algorithm, nine key genes were identified, demonstrating strong predictive power for the prognosis of Osteosarcoma patients. Notably, changes were observed at the levels of immune checkpoints, the tumor microenvironment (TME), drug sensitivity, and immune cell infiltration. This study paves the way for targeted drug interventions, thereby opening avenues for improving clinical outcomes in osteosarcoma.

摘要

骨肉瘤是最常见的骨肿瘤,也是一种侵袭性很强的恶性肿瘤。本研究旨在阐明乳酸化相关基因(LRGs)在骨肉瘤中的作用,以提高预后准确性并增强免疫治疗效果。利用公共数据集,我们基于单细胞测序AUCell评分整合差异基因和相关基因,并对这些基因进行富集分析和风险模型构建。共发现277个基因与乳酸代谢密切相关。使用单因素Cox和LASSO算法,确定了9个关键基因,对骨肉瘤患者的预后具有很强的预测能力。值得注意的是,在免疫检查点、肿瘤微环境(TME)、药物敏感性和免疫细胞浸润水平上观察到了变化。本研究为靶向药物干预铺平了道路,从而为改善骨肉瘤的临床结局开辟了途径。

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