Bulk and single-cell sequencing identified a prognostic model based on the macrophage and lipid metabolism related signatures for osteosarcoma patients

通过批量和单细胞测序,我们基于巨噬细胞和脂质代谢相关特征,构建了骨肉瘤患者的预后模型。

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Abstract

The introduction of multidrug combination chemotherapy has significantly advanced the long-term survival prospects for osteosarcoma (OS) patients over the past decades. However, the escalating prevalence of chemoresistance has emerged as a substantial impediment to further advancements, necessitating the formulation of innovative strategies. Our present study leveraged sophisticated bulk and single-cell sequencing techniques to scrutinize the OS immune microenvironment, unveiling a potential association between the differentiation state of macrophages and the efficacy of OS chemotherapy. Notably, we observed that a heightened presence of lipid metabolism genes and pathways in predifferentiated macrophages, constituting the major cluster of OS patients exhibiting a less favorable response to chemotherapy. Subsequently, we developed a robust Macrophage and Lipid Metabolism (MLMR) risk model and a nomogram, both of which demonstrated commendable prognostic predictive performance. Furthermore, a comprehensive investigation into the underlying mechanisms of the risk model revealed intricate associations with variations in the immune response among OS patients. Finally, our meticulous drug sensitivity analysis identified a spectrum of potential therapeutic agents for OS, including AZD2014, Sapitinib, Buparlisib, Afuresertib, MIRA-1, and BIBR-1532. These findings significantly augment the therapeutic arsenal available to clinicians managing OS, presenting a promising avenue for elevating treatment outcomes.

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