Prognostic Signature in Osteosarcoma Based on Amino Acid Metabolism-Associated Genes.

IF 2.4 4区 医学 Q3 MEDICINE, RESEARCH & EXPERIMENTAL Cancer Biotherapy and Radiopharmaceuticals Pub Date : 2024-09-01 Epub Date: 2024-03-21 DOI:10.1089/cbr.2024.0002
Liwen Feng, Yuting Chen, Xiangping Mei, Lei Wang, Wenjing Zhao, Jiannan Yao
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引用次数: 0

Abstract

Background: Osteosarcoma (OS) is undeniably a formidable bone malignancy characterized by a scarcity of effective treatment options. Reprogramming of amino acid (AA) metabolism has been associated with OS development. The present study was designed to identify metabolism-associated genes (MAGs) that are differentially expressed in OS and to construct a MAG-based prognostic risk signature for this disease. Methods: Expression profiles and clinicopathological data were downloaded from Gene Expression Omnibus (GEO) and UCSC Xena databases. A set of AA MAGs was obtained from the MSigDB database. Differentially expressed genes (DEGs) in GEO dataset were identified using "limma." Prognostic MAGs from UCSC Xena database were determined through univariate Cox regression and used in the prognostic signature development. This signature was validated using another dataset from GEO database. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, single sample gene set enrichment analysis, and GDSC2 analyses were performed to explore the biological functions of the MAGs. A MAG-based nomogram was established to predict 1-, 3-, and 5-year survival. Real-time quantitative polymerase chain reaction, Western blot, and immunohistochemical staining confirmed the expression of MAGs in primary OS and paired adjacent normal tissues. Results: A total of 790 DEGs and 62 prognostic MAGs were identified. A MAG-based signature was constructed based on four MAGs: PIPOX, PSMC2, SMOX, and PSAT1. The prognostic value of this signature was successfully validated, with areas under the receiver operating characteristic curves for 1-, 3-, and 5-year survival of 0.714, 0.719, and 0.715, respectively. This MAG-based signature was correlated with the infiltration of CD56dim natural killer cells and resistance to several antiangiogenic agents. The nomogram was accurate in predictions, with a C-index of 0.77. The expression of MAGs verified by experiment was consistent with the trends observed in GEO database. Conclusion: Four AA MAGs were prognostic of survival in OS patients. This MAG-based signature has the potential to offer valuable insights into the development of treatments for OS.

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基于氨基酸代谢相关基因的骨肉瘤预后特征
背景:骨肉瘤(Osteosarcoma,OS)无疑是一种可怕的骨恶性肿瘤,其特点是缺乏有效的治疗方案。氨基酸(AA)代谢的重编程与骨肉瘤的发展有关。本研究旨在鉴定在OS中差异表达的代谢相关基因(MAGs),并构建基于MAG的该疾病预后风险特征。方法从基因表达总库(GEO)和 UCSC Xena 数据库下载表达谱和临床病理数据。从 MSigDB 数据库中获得了一组 AA MAGs。使用 "limma "鉴定 GEO 数据集中的差异表达基因(DEGs)。通过单变量 Cox 回归确定了 UCSC Xena 数据库中的预后 MAGs,并将其用于预后特征的开发。该特征使用 GEO 数据库中的另一个数据集进行了验证。为了探索MAGs的生物学功能,还进行了基因本体、京都基因和基因组百科全书、单样本基因组富集分析和GDSC2分析。建立了一个基于 MAG 的提名图来预测 1 年、3 年和 5 年的生存率。实时定量聚合酶链反应、Western印迹和免疫组化染色证实了MAGs在原发性OS和配对的邻近正常组织中的表达。结果显示共鉴定出 790 个 DEGs 和 62 个预后 MAGs。基于PIPOX、PSMC2、SMOX和PSAT1四种MAG构建了基于MAG的特征。该特征的预后价值得到了成功验证,1年、3年和5年生存率的接收者操作特征曲线下面积分别为0.714、0.719和0.715。这种基于 MAG 的特征与 CD56dim 自然杀伤细胞的浸润和对几种抗血管生成药物的耐受性相关。提名图预测准确,C 指数为 0.77。实验验证的 MAGs 表达与 GEO 数据库中观察到的趋势一致。结论:四种 AA MAG 可预测 OS 患者的生存期。这种基于 MAG 的特征有望为开发 OS 治疗方法提供有价值的见解。
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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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