Identifying squalene epoxidase as a metabolic vulnerability in high‐risk osteosarcoma using an artificial intelligence‐derived prognostic index
Yongjie Wang,
Xiaolong Ma,
Enjie Xu
et al.
Abstract:BackgroundOsteosarcoma (OSA) presents a clinical challenge and has a low 5‐year survival rate. Currently, the lack of advanced stratification models makes personalized therapy difficult. This study aims to identify novel biomarkers to stratify high‐risk OSA patients and guide treatment.MethodsWe combined 10 machine‐learning algorithms into 101 combinations, from which the optimal model was established for predicting overall survival based on transcriptomic profiles for 254 samples. Alterations in transcriptomi… Show more
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