Prognositic value of anoikis and tumor immune microenvironment-related gene in the treatment of osteosarcoma

Anoikis和肿瘤免疫微环境相关基因在骨肉瘤治疗中的预后价值

Objective:Osteosarcoma is a highly aggressive primary malignant bone tumor commonly seen in children and adolescents,with a poor prognosis.Anchorage-dependent cell death(anoikis)has been proven to be indispensable in tumor metastasis,regulating the migration and adhesion of tumor cells at the primary site.However,as a type of programmed cell death,anoikis is rarely studied in osteosarcoma,especially in the tumor immune microenvironment.This study aims to clarify prognostic value of anoikis and tumor immune microenvironment-related gene in the treatment of osteosarcoma.Methods:Anoikis-related genes(ANRGs)were obtained from GeneCards.Clinical information and ANRGs expression profiles of osteosarcoma patients were sourced from the therapeutically applicable research to generate effective therapies and Gene Expression Omnibus(GEO)databases.ANRGs highly associated with tumor immune microenvironment were identified by the estimate package and the weighted gene coexpression network analysis(WGCNA)algorithm.Machine learning algorithms were performed to construct long-term survival predictive strategy,each sample was divided into high-risk and low-risk subgroups,which was further verified in the GEO cohort.Finally,based on single-cell RNA-seq from the GEO database,analysis was done on the function of signature genes in the osteosarcoma tumor microenvironment.Results:A total of 51 hub ANRGs closely associated with the tumor microenvironment were identified,from which 3 genes(MERTK,BNIP3,S100A8)were selected to construct the prognostic model.Significant differences in immune cell activation and immune-related signaling pathways were observed between the high-risk and low-risk groups based on tumor microenvironment analysis(all P<0.05).Additionally,characteristic genes within the osteosarcoma microenvironment were identified in regulation of intercellular crosstalk through the GAS6-MERTK signaling pathway.Conclusion:The prognostic model based on ANRGs and tumor microenvironment demonstrate good predictive power and provide more personalized treatment options for patients with osteosarcoma.

目的:骨肉瘤是一种极具侵袭性的原发性恶性骨肿瘤,多见于儿童和青少年,预后差。矢巢凋亡(anchorage-dependent cell death,anoikis)已被证明在肿瘤转移中具有重要作用,可调节肿瘤细胞在原发部位的迁移和黏附。作为一种程序性细胞死亡的形式,anoikis在骨肉瘤中的研究较少,尤其是在肿瘤免疫微环境中的研究。本研究旨在阐明anoikis和肿瘤免疫微环境相关基因在骨肉瘤治疗中的预后价值。方法:从GeneCards中获得anoikis相关基因(anoikis-related genes,ANRGs);从产生有效疗法的治疗应用研究和基因表达综合(Gene Expression Omnibus,GEO)数据库中获取骨肉瘤患者的临床信息和ANRGs表达状况。利用估计包和加权基因共表达网络分析(weighted gene coexpression network analysis,WGCNA)算法识别出与肿瘤免疫微环境高度相关的ANRGs;采用机器学习算法构建长期生存预测模型,将样本分为高危组和低危组,并在GEO队列中进行进一步验证。最后,基于来自GEO数据库的单细胞RNA测序,分析骨肉瘤肿瘤微环境中特征基因的功能。结果:51个与肿瘤微环境高度相关的枢纽ANRGs被证实,从中选择3个基因(MERTK、BNIP3、S100A8)构建预后模型。根据肿瘤微环境分析,在免疫细胞激活和免疫相关信号通路方面,高危组和低危组之间的差异均具有统计学意义(均P<0.05)。骨肉瘤微环境中的特征基因被证实通过参与GAS6-MERTK信号通路调控细胞间的串扰。结论:基于ANRGs和肿瘤微环境的预后模型具有良好的预测能力,可为骨肉瘤患者提供更多个性化治疗方案。