Department of Spine Surgery, Third Xiangya Hospital, Central South University, Changsha 410013.
Shanghai Key Laboratory of Regulatory Biology; Institute of Biomedical Sciences, School of Life Sciences, East China Normal University, Shanghai 200241, China.
Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2024 May 28;49(5):758-774. doi: 10.11817/j.issn.1672-7347.2024.230519.
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.
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.
A total of 51 hub ANRGs closely associated with the tumor microenvironment were identified, from which 3 genes (, , ) 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 <0.05). Additionally, characteristic genes within the osteosarcoma microenvironment were identified in regulation of intercellular crosstalk through the GAS6-MERTK signaling pathway.
The prognostic model based on ANRGs and tumor microenvironment demonstrate good predictive power and provide more personalized treatment options for patients with osteosarcoma.
骨肉瘤是一种常见于儿童和青少年的高度侵袭性原发性恶性骨肿瘤，预后较差。锚定依赖性细胞死亡（失巢凋亡）已被证明在肿瘤转移中不可或缺，调节肿瘤细胞在原发部位的迁移和黏附。然而，作为一种程序性细胞死亡，失巢凋亡在骨肉瘤中很少被研究，特别是在肿瘤免疫微环境中。本研究旨在阐明失巢凋亡和肿瘤免疫微环境相关基因在骨肉瘤治疗中的预后价值。
从 GeneCards 中获取与失巢凋亡相关的基因（ANRGs）。从治疗性应用研究生成有效的治疗方法和基因表达综合数据库（GEO）中获取骨肉瘤患者的临床信息和 ANRGs 表达谱。通过估计包和加权基因共表达网络分析（WGCNA）算法鉴定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策略，将每个样本分为高危和低危亚组，在 GEO 队列中进一步验证。最后，基于 GEO 数据库中的单细胞 RNA-seq，分析特征基因在骨肉瘤肿瘤微环境中的功能。
共鉴定出 51 个与肿瘤微环境密切相关的核心 ANRGs，从中选择 3 个基因（、、）构建预后模型。基于肿瘤微环境分析，高危组和低危组之间在免疫细胞激活和免疫相关信号通路方面存在显著差异（均<0.05）。此外，通过 GAS6-MERTK 信号通路调节细胞间串扰，鉴定出骨肉瘤微环境中的特征基因。
基于 ANRGs 和肿瘤微环境的预后模型具有良好的预测能力，为骨肉瘤患者提供了更个性化的治疗选择。
