Exploring the relationship between metabolism and immune microenvironment in osteosarcoma based on metabolic pathways.

IF 9 2区 医学 Q1 CELL BIOLOGY
Changwu Wu, Jun Tan, Hong Shen, Chao Deng, Christian Kleber, Georg Osterhoff, Nikolas Schopow
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引用次数: 0

Abstract

Background: Metabolic remodeling and changes in tumor immune microenvironment (TIME) in osteosarcoma are important factors affecting prognosis and treatment. However, the relationship between metabolism and TIME needs to be further explored.

Methods: RNA-Seq data and clinical information of 84 patients with osteosarcoma from the TARGET database and an independent cohort from the GEO database were included in this study. The activity of seven metabolic super-pathways and immune infiltration levels were inferred in osteosarcoma patients. Metabolism-related genes (MRGs) were identified and different metabolic clusters and MRG-related gene clusters were identified using unsupervised clustering. Then the TIME differences between the different clusters were compared. In addition, an MRGs-based risk model was constructed and the role of a key risk gene, ST3GAL4, in osteosarcoma cells was explored using molecular biological experiments.

Results: This study revealed four key metabolic pathways in osteosarcoma, with vitamin and cofactor metabolism being the most relevant to prognosis and to TIME. Two metabolic pathway-related clusters (C1 and C2) were identified, with some differences in immune activating cell infiltration between the two clusters, and C2 was more likely to respond to two chemotherapeutic agents than C1. Three MRG-related gene clusters (GC1-3) were also identified, with significant differences in prognosis among the three clusters. GC2 and GC3 had higher immune cell infiltration than GC1. GC3 is most likely to respond to immune checkpoint blockade and to three commonly used clinical drugs. A metabolism-related risk model was developed and validated. The risk model has strong prognostic predictive power and the low-risk group has a higher level of immune infiltration than the high-risk group. Knockdown of ST3GAL4 significantly inhibited proliferation, migration, invasion and glycolysis of osteosarcoma cells and inhibited the M2 polarization of macrophages.

Conclusion: The metabolism of vitamins and cofactors is an important prognostic regulator of TIME in osteosarcoma, MRG-related gene clusters can well reflect changes in osteosarcoma TIME and predict chemotherapy and immunotherapy response. The metabolism-related risk model may serve as a useful prognostic predictor. ST3GAL4 plays a critical role in the progression, glycolysis, and TIME of osteosarcoma cells.

基于代谢途径探索骨肉瘤代谢与免疫微环境之间的关系
背景:骨肉瘤的代谢重塑和肿瘤免疫微环境(TIME)变化是影响预后和治疗的重要因素。然而,新陈代谢与 TIME 之间的关系还需要进一步探讨:本研究纳入了 TARGET 数据库和 GEO 数据库中一个独立队列的 84 例骨肉瘤患者的 RNA-Seq 数据和临床信息。研究推断了骨肉瘤患者体内七条代谢超通路的活性和免疫浸润水平。通过无监督聚类,确定了代谢相关基因(MRGs),并确定了不同的代谢集群和MRG相关基因集群。然后比较了不同聚类之间的 TIME 差异。此外,还构建了基于MRGs的风险模型,并通过分子生物学实验探讨了关键风险基因ST3GAL4在骨肉瘤细胞中的作用:结果:该研究揭示了骨肉瘤的四个关键代谢通路,其中维生素和辅助因子代谢与预后和TIME最为相关。发现了两个与代谢途径相关的基因簇(C1 和 C2),两个基因簇在免疫激活细胞浸润方面存在一些差异,C2 比 C1 更有可能对两种化疗药物产生反应。此外,还发现了三个与 MRG 相关的基因簇(GC1-3),三个基因簇的预后存在显著差异。与 GC1 相比,GC2 和 GC3 有更高的免疫细胞浸润。GC3最有可能对免疫检查点阻断疗法和三种临床常用药物产生反应。我们开发并验证了一个与代谢相关的风险模型。该风险模型具有很强的预后预测能力,低风险组的免疫细胞浸润水平高于高风险组。敲除 ST3GAL4 能显著抑制骨肉瘤细胞的增殖、迁移、侵袭和糖酵解,并抑制巨噬细胞的 M2 极化:维生素和辅助因子的代谢是骨肉瘤TIME的重要预后调节因子,MRG相关基因簇能很好地反映骨肉瘤TIME的变化,预测化疗和免疫治疗的反应。代谢相关风险模型可作为一种有用的预后预测指标。ST3GAL4在骨肉瘤细胞的进展、糖酵解和TIME中发挥着关键作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Biomedical Science
Journal of Biomedical Science 医学-医学:研究与实验
CiteScore
18.50
自引率
0.90%
发文量
95
审稿时长
1 months
期刊介绍: The Journal of Biomedical Science is an open access, peer-reviewed journal that focuses on fundamental and molecular aspects of basic medical sciences. It emphasizes molecular studies of biomedical problems and mechanisms. The National Science and Technology Council (NSTC), Taiwan supports the journal and covers the publication costs for accepted articles. The journal aims to provide an international platform for interdisciplinary discussions and contribute to the advancement of medicine. It benefits both readers and authors by accelerating the dissemination of research information and providing maximum access to scholarly communication. All articles published in the Journal of Biomedical Science are included in various databases such as Biological Abstracts, BIOSIS, CABI, CAS, Citebase, Current contents, DOAJ, Embase, EmBiology, and Global Health, among others.
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