Prediction of Prognosis and Immunotherapy Response with a Novel Natural Killer Cell Marker Genes Signature in Osteosarcoma.

IF 2.4 4区 医学 Q3 MEDICINE, RESEARCH & EXPERIMENTAL
Cancer Biotherapy and Radiopharmaceuticals Pub Date : 2024-09-01 Epub Date: 2023-10-27 DOI:10.1089/cbr.2023.0103
Qinwen Li, Xiaoyan Huang, Youfang Zhao
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引用次数: 0

Abstract

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.

一种新的自然杀伤细胞标记基因对骨肉瘤预后和免疫治疗反应的预测。
背景:自然杀伤细胞(NK)以其抗肿瘤作用而无致敏性为特点,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细胞的标记,以识别某些对免疫疗法更敏感的OS患者。材料和方法:本研究共纳入了8个来自OS患者的公开数据集。分析从基因表达综合数据库(GEO)获得的单细胞RNA测序数据以筛选NK细胞标记基因。最小绝对收缩和选择算子(LASSO)Cox回归分析用于在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,这种预后标志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细胞标志基因,构建了一个基于5个基因的NK细胞预后标志。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,特别是CD8 T细胞和幼稚CD4 T细胞,表明高风险OS患者存在T细胞耗竭状态。相关性分析表明,免疫系统相关的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,基于两个免疫疗法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)或抗程序性死亡配体1(PD-L1)治疗的反应。RT-qPCR结果表明,这五种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,这可能为OS患者的后续免疫治疗选择提供线索。此外,作者揭示了免疫抑制微环境与OS之间的潜在联系。
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来源期刊
CiteScore
7.80
自引率
2.90%
发文量
87
审稿时长
3 months
期刊介绍: Cancer Biotherapy and Radiopharmaceuticals is the established peer-reviewed journal, with over 25 years of cutting-edge content on innovative therapeutic investigations to ultimately improve cancer management. It is the only journal with the specific focus of cancer biotherapy and is inclusive of monoclonal antibodies, cytokine therapy, cancer gene therapy, cell-based therapies, and other forms of immunotherapies. The Journal includes extensive reporting on advancements in radioimmunotherapy, and the use of radiopharmaceuticals and radiolabeled peptides for the development of new cancer treatments.
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