Department of Orthopedics, Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Department of Intensive Care Unit, Taizhou Municipal Hospital, Taizhou, China.
Environ Toxicol. 2024 Oct;39(10):4776-4790. doi: 10.1002/tox.24325. Epub 2024 Aug 20.
Osteosarcoma, known for its rapid progression and high metastatic potential, poses significant challenges in adolescent oncology. This study delves into the roles of lipid metabolism and acetylation genes in the disease's pathogenesis. Utilizing gene set variation analysis, we examined 14 lipid metabolism-related pathways in osteosarcoma patients, identifying significant variances in three pathways between metastatic and primary cases. Additionally, differences in four acetylation genes between these groups were observed. A comprehensive analysis pinpointed 62 lipid metabolism-related genes, with 39 exhibiting significant correlations with acetylation genes, termed lipid metabolism acetylation (LMA) genes. Employing machine learning techniques like Lasso+RSF and GBM, we developed a predictive model for overall survival based on LMA genes. This model, with an average c-index of 0.771, focuses on three key genes: CYP2C8, PAFAH2, and ACOX3, whose prognostic value was confirmed through survival and receiver operating characteristic curve analyses. Quantitative RT-PCR results indicated higher expression levels of ACOX3 and PAFAH2 in OS cells (143B, HOS, MG63) than in osteoblasts (hFOB1.19), while CYP2C8 was lower in OS cells. Furthermore, drug sensitivity analysis through the pRRophetic algorithm suggested potential targeted therapies, revealing drugs with differential sensitivity based on LMA scores and varied treatment responses related to the expression of core genes. This study not only highlights the crucial role of lipid metabolism and acetylation in osteosarcoma but also offers a foundation for personalized treatment strategies, marking a notable advancement in combating this severe form of adolescent cancer.
骨肉瘤以其快速进展和高转移潜能为特征，给青少年肿瘤学带来了重大挑战。本研究深入探讨了脂质代谢和乙酰化基因在疾病发病机制中的作用。我们利用基因集变异分析，研究了骨肉瘤患者 14 条与脂质代谢相关的通路，发现转移和原发病例之间有 3 条通路存在显著差异。此外，这两组之间还观察到 4 个乙酰化基因的差异。综合分析确定了 62 个与脂质代谢相关的基因，其中 39 个与乙酰化基因显著相关，称为脂质代谢乙酰化（LMA）基因。我们采用 Lasso+RSF 和 GBM 等机器学习技术，基于 LMA 基因构建了一个预测总生存期的模型。该模型的平均 c-index 为 0.771，重点关注三个关键基因：CYP2C8、PAFAH2 和 ACOX3，通过生存和接收者操作特征曲线分析验证了它们的预后价值。定量 RT-PCR 结果表明，ACOX3 和 PAFAH2 在骨肉瘤细胞（143B、HOS、MG63）中的表达水平高于成骨细胞（hFOB1.19），而 CYP2C8 在骨肉瘤细胞中的表达水平较低。此外，通过 pRRophetic 算法进行的药物敏感性分析表明存在潜在的靶向治疗方法，根据 LMA 评分和核心基因表达的不同治疗反应揭示了具有差异敏感性的药物。本研究不仅强调了脂质代谢和乙酰化在骨肉瘤中的关键作用，还为个性化治疗策略提供了基础，标志着在对抗这种严重形式的青少年癌症方面取得了显著进展。
