Department of Orthopedics, The First College of Clinical Medical Science, China Three Gorges University, Yichang Central People's Hospital, Yichang, China.
Department of Geriatrics, The Third Clinical Medical College of China Three Gorges University, Gezhouba Central Hospital of Sinopharm, Yichang, China.
Cancer Biother Radiopharm. 2024 Sep;39(7):502-516. doi: 10.1089/cbr.2023.0103. Epub 2023 Oct 27.
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. 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). 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. 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.
自然杀伤 (NK) 细胞的抗肿瘤功效无需预先致敏,这引起了人们对肿瘤免疫治疗的关注。骨肉瘤 (OS) 的异质性阻碍了基于 NK 细胞的免疫治疗的应用。作者旨在构建一种新的基于 NK 细胞的特征,以鉴定对免疫治疗更敏感的特定 OS 患者。
本研究共纳入 8 个来自 OS 患者的公开数据集。从基因表达综合数据库 (GEO) 数据库中分析单细胞 RNA 测序数据,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 数据集构建基于 NK 细胞的预后特征。评估风险亚组之间的免疫细胞浸润、免疫系统相关元基因和免疫治疗反应的差异。此外,通过逆转录定量实时 PCR (RT-qPCR) 实验验证了该预后特征。
筛选出差异表达的 NK 细胞标记基因,构建了一个基于 5 个基因的 NK 细胞预后特征。通过内部临床亚组和外部 GEO 数据集验证了该特征的预后预测准确性。低风险 OS 患者含有更高丰度的浸润免疫细胞,尤其是 CD8 T 细胞和幼稚 CD4 T 细胞,表明高危 OS 患者存在 T 细胞耗竭状态。相关性分析表明,免疫系统相关元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,基于两种免疫治疗数据集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) 治疗的反应。RT-qPCR 结果表明,这 5 个基因表达与预测结果大致一致。
基于 NK 细胞的特征可能可用于预测 OS 患者的生存和评估免疫治疗反应,这可能为 OS 患者的后续免疫治疗选择提供依据。此外,作者揭示了免疫抑制微环境与 OS 之间的潜在联系。