Development and validation of a lipid metabolism-derived prognostic signature for risk stratification in Ewing sarcoma

Background Ewing sarcoma (ES) is a challenging malignancy, particularly in metastatic cases, with a poor prognosis. Lipid metabolism alterations create a favorable environment for tumor growth, promoting proliferation, invasion, and metastasis. Given the significant dependence of ES cells on lipid metabolism (LM), this study aims to explore the association of lipid metabolism-related genes (LMRGs) with the tumor microenvironment (TME), immunotherapeutic response, and prognosis, and to develop a novel prognostic risk model for improved clinical management. Methods Bioinformatics analysis was used to identify Clusters A and B and six differentially expressed LMRGs, enabling the construction of a novel risk model and nomogram to enhance clinical treatment strategies. We employed a combination of in vitro assays, including cell transfection, RT-qPCR, flow cytometry, Western blot, and assays for cell wound healing, migration, and invasion. Results Our findings demonstrate that Karyopherin Subunit Beta 1 (KPNB1) promotes ES cell migration, proliferation, and invasion through the PPARγ/p65/IκB pathway, while Carnitine Palmitoyltransferase 1A (CPT1A) inhibits this pathway. These insights were integrated into a novel prognostic risk model and nomogram, providing a robust framework for risk stratification. The unique integration of bioinformatics with experimental validation distinguishes this study, offering a comprehensive understanding of LMRGs' roles in ES progression and their potential to modulate the TME and immune responses. Conclusion This study establishes a pioneering prognostic risk model based on LMRGs, highlighting their critical roles in ES progression and their potential as therapeutic targets. By elucidating the interplay between LMRGs, TME, and prognosis, this research enhances risk stratification and opens new avenues for LM-directed therapies, addressing a significant unmet need in ES treatment and advancing personalized oncology.