Osteosarcoma is the most common bone tumor and a highly aggressive malignant neoplasm. This study aims to elucidate the role of lactylation-related genes (LRGs) in osteosarcoma, with the goal of improving prognostic accuracy and enhancing the efficacy of immunotherapy. Using public datasets, we integrated differential and correlated genes based on single-cell sequencing AUCell scores and performed enrichment analysis and risk model construction on these genes. A total of 277 genes were found to be intricately linked with lactate metabolism. Using the uni-Cox and LASSO algorithm, nine key genes were identified, demonstrating strong predictive power for the prognosis of Osteosarcoma patients. Notably, changes were observed at the levels of immune checkpoints, the tumor microenvironment (TME), drug sensitivity, and immune cell infiltration. This study paves the way for targeted drug interventions, thereby opening avenues for improving clinical outcomes in osteosarcoma.
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Integrative single-cell and bulk RNA-seq analysis identifies lactylation-related signature in osteosarcoma.
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