{"title":"解密脂质代谢和乙酰化在骨肉瘤中的作用:全面的分子分析","authors":"Yong Wen, Xijiang Zhang, Jin Zhang, Zhisheng Lu","doi":"10.1002/tox.24325","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":11756,"journal":{"name":"Environmental Toxicology","volume":"39 10","pages":"4776-4790"},"PeriodicalIF":4.4000,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Deciphering the role of lipid metabolism and acetylation in osteosarcoma: A comprehensive molecular analysis\",\"authors\":\"Yong Wen, Xijiang Zhang, Jin Zhang, Zhisheng Lu\",\"doi\":\"10.1002/tox.24325\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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. 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引用次数: 0
摘要
骨肉瘤以其进展迅速和转移潜力大而闻名,给青少年肿瘤学带来了巨大挑战。本研究探讨了脂质代谢和乙酰化基因在该病发病机制中的作用。利用基因组变异分析,我们研究了骨肉瘤患者的 14 个脂质代谢相关通路,发现转移性病例和原发性病例之间有三个通路存在显著差异。此外,我们还观察到这两组患者的四个乙酰化基因存在差异。综合分析确定了 62 个脂质代谢相关基因,其中 39 个与乙酰化基因有显著相关性,称为脂质代谢乙酰化(LMA)基因。利用 Lasso+RSF 和 GBM 等机器学习技术,我们建立了一个基于 LMA 基因的总生存率预测模型。该模型的平均 c 指数为 0.771,重点关注三个关键基因:这些基因的预后价值已通过生存率和接收者操作特征曲线分析得到证实。定量 RT-PCR 结果表明,ACOX3 和 PAFAH2 在 OS 细胞(143B、HOS、MG63)中的表达水平高于成骨细胞(hFOB1.19),而 CYP2C8 在 OS 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提出了潜在的靶向疗法,根据LMA评分揭示了具有不同敏感性的药物,以及与核心基因表达相关的不同治疗反应。这项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奠定了基础,标志着在抗击这种严重的青少年癌症方面取得了显著进展。
Deciphering the role of lipid metabolism and acetylation in osteosarcoma: A comprehensive molecular analysis
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.
期刊介绍:
The journal publishes in the areas of toxicity and toxicology of environmental pollutants in air, dust, sediment, soil and water, and natural toxins in the environment.Of particular interest are:
Toxic or biologically disruptive impacts of anthropogenic chemicals such as pharmaceuticals, industrial organics, agricultural chemicals, and by-products such as chlorinated compounds from water disinfection and waste incineration;
Natural toxins and their impacts;
Biotransformation and metabolism of toxigenic compounds, food chains for toxin accumulation or biodegradation;
Assays of toxicity, endocrine disruption, mutagenicity, carcinogenicity, ecosystem impact and health hazard;
Environmental and public health risk assessment, environmental guidelines, environmental policy for toxicants.