Deciphering the role of lipid metabolism and acetylation in osteosarcoma: A comprehensive molecular analysis

• Published in: Environmental toxicology 2024-10, Vol.39 (10), p.4776-4790
• Main Authors: Wen, Yong, Zhang, Xijiang, Zhang, Jin, Lu, Zhisheng
• Format: Article
• Language: English
• Subjects: Acetylation; acetylation genes; Adolescents; Algorithms; Bone cancer; Bone Neoplasms - genetics; Bone Neoplasms - metabolism; Bone Neoplasms - pathology; Cell Line, Tumor; Drug metabolism; drug sensitivity; Gene Expression Regulation, Neoplastic; Genes; Humans; Lipid Metabolism; Lipids; Machine learning; Metabolism; Metastases; Metastasis; Nucleotide sequence; Osteosarcoma; Osteosarcoma - genetics; Osteosarcoma - metabolism; Osteosarcoma - pathology; Pathogenesis; Prediction models; Sensitivity analysis; Survival
• ISSN: 1520-4081; 1522-7278; 1522-7278
• DOI: 10.1002/tox.24325

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.