Background: Natural killer (NK) cells are characterized by their antitumor efficacy without previous sensitization, which have attracted attention in tumor immunotherapy. The heterogeneity of osteosarcoma (OS) has hindered therapeutic application of NK cell-based immunotherapy. The authors aimed to construct a novel NK cell-based signature to identify certain OS patients more responsive to immunotherapy. Materials and Methods: A total of eight publicly available datasets derived from patients with OS were enrolled in this study. Single-cell RNA sequencing data obtained from the Gene Expression Omnibus (GEO) database were analyzed to screen NK cell marker genes. Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis was used to construct an NK cell-based prognostic signature in the TARGET-OS dataset. The differences in immune cell infiltration, immune system-related metagenes, and immunotherapy response were evaluated among risk subgroups. Furthermore, this prognostic signature was experimentally validated by reverse transcription-quantitative real-time PCR (RT-qPCR). Results: With differentially expressed NK cell marker genes screened out, a five-gene NK cell-based prognostic signature was constructed. The prognostic predictive accuracy of the signature was validated through internal clinical subgroups and external GEO datasets. Low-risk OS patients contained higher abundances of infiltrated immune cells, especially CD8 T cells and naive CD4 T cells, indicating that T cell exhaustion states were present in the high-risk OS patients. As indicated from correlation analysis, immune system-related metagenes displayed a negative correlation with risk scores, suggesting the existence of immunosuppressive microenvironment in OS. In addition, based on responses to immune checkpoint inhibitor therapy in two immunotherapy datasets, the signature helped predict the response of OS patients to anti-programmed cell death protein 1 (PD-1) or anti-programmed cell death ligand 1 (PD-L1) therapy. RT-qPCR results demonstrated the roughly consistent relationship of these five gene expressions with predicting outcomes. Conclusions: The NK cell-based signature is likely to be available for the survival prediction and the evaluation of immunotherapy response of OS patients, which may shed light on subsequent immunotherapy choices for OS patients. In addition, the authors revealed a potential link between immunosuppressive microenvironment and OS.

中文翻译：

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利用骨肉瘤中新型自然杀伤细胞标记基因特征预测预后和免疫治疗反应。

背景：自然杀伤（NK）细胞因其无需预先致敏而具有抗肿瘤功效的特点，在肿瘤免疫治疗中引起了人们的关注。骨肉瘤（OS）的异质性阻碍了基于 NK 细胞的免疫疗法的治疗应用。作者旨在构建一种新的基于 NK 细胞的特征，以识别某些对免疫治疗更敏感的 OS 患者。材料和方法：本研究共纳入了八个来自 OS 患者的公开数据集。分析从基因表达综合 (GEO) 数据库获得的单细胞 RNA 测序数据，以筛选 NK 细胞标记基因。使用最小绝对收缩和选择算子 (LASSO) Cox 回归分析在 TARGET-OS 数据集中构建基于 NK 细胞的预后特征。评估了风险亚组之间免疫细胞浸润、免疫系统相关宏基因和免疫治疗反应的差异。此外，这一预后特征还通过逆转录定量实时 PCR (RT-qPCR) 进行了实验验证。结果：筛选出差异表达的NK细胞标记基因，构建了基于五基因NK细胞的预后特征。该特征的预后预测准确性通过内部临床亚组和外部 GEO 数据集进行了验证。低危OS患者含有较高丰度的浸润免疫细胞，尤其是CD8 T细胞和初始CD4 T细胞，表明高危OS患者存在T细胞耗竭状态。相关分析表明，免疫系统相关宏基因与风险评分呈负相关，提示 OS 中存在免疫抑制微环境。此外，根据两个免疫治疗数据集中对免疫检查点抑制剂治疗的反应，该特征有助于预测 OS 患者对抗程序性细胞死亡蛋白 1 (PD-1) 或抗程序性细胞死亡配体 1 (PD-L1) 的反应） 治疗。RT-qPCR 结果表明这五个基因表达与预测结果的关系大致一致。结论：基于 NK 细胞的特征可能可用于 OS 患者的生存预测和免疫治疗反应评估，这可能有助于 OS 患者后续免疫治疗的选择。此外，作者还揭示了免疫抑制微环境与 OS 之间的潜在联系。