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建立骨肉瘤相关蛋白-蛋白相互作用网络,探索骨肉瘤的发病机制。

Establishing an osteosarcoma associated protein-protein interaction network to explore the pathogenesis of osteosarcoma.

机构信息

Department of Orthopedic Surgery, Shanghai Tenth people's Hospital, Tongji University School of Medicine, No,301 Middle Yan-Chang Road, Zha-Bei District, Shanghai 200072, China.

出版信息

Eur J Med Res. 2013 Dec 14;18(1):57. doi: 10.1186/2047-783X-18-57.

Abstract

BACKGROUND

The aim of this study was to establish an osteosarcoma (OS) associated protein-protein interaction network and explore the pathogenesis of osteosarcoma.

METHODS

The gene expression profile GSE9508 was downloaded from the Gene Expression Omnibus database, including five samples of non-malignant bone (the control), seven samples for non-metastatic patients (six of which were analyzed in duplicate), and 11 samples for metastatic patients (10 of which were analyzed in duplicate). Differentially expressed genes (DEGs) between osteosarcoma and control samples were identified by packages in R with the threshold of |logFC (fold change)| > 1 and false discovery rate < 0.05. Osprey software was used to construct the interaction network of DEGs, and genes at protein-protein interaction (PPI) nodes with high degrees were identified. The Database for Annotation, Visualization and Integrated Discovery and WebGestalt software were then used to perform functional annotation and pathway enrichment analyses for PPI networks, in which P < 0.05 was considered statistically significant.

RESULTS

Compared to the control samples, the expressions of 42 and 341 genes were altered in non-metastatic OS and metastatic OS samples, respectively. A total of 15 significantly enriched functions were obtained with Gene Ontology analysis (P < 0.05). The DEGs were classified and significantly enriched in three pathways, including the tricarboxylic acid cycle, lysosome and axon guidance. Genes such as HRAS, IDH3A, ATP6ap1, ATP6V0D2, SEMA3F and SEMA3A were involved in the enriched pathways.

CONCLUSIONS

The hub genes from metastatic OS samples are not only bio-markers of OS, but also help to improve therapies for OS.

摘要

背景

本研究旨在建立骨肉瘤(OS)相关的蛋白质-蛋白质相互作用网络,探讨骨肉瘤的发病机制。

方法

从基因表达综合数据库中下载基因表达谱 GSE9508,包含 5 例非恶性骨(对照)样本、7 例非转移性患者(其中 6 例重复分析)和 11 例转移性患者样本(其中 10 例重复分析)。使用 R 软件中的包,根据 |logFC(fold change)| > 1 和错误发现率 < 0.05 的阈值,确定骨肉瘤与对照样本之间的差异表达基因(DEGs)。使用 Osprey 软件构建 DEGs 的相互作用网络,并鉴定蛋白质-蛋白质相互作用(PPI)节点中高程度的基因。然后使用数据库注释、可视化和综合发现以及 WebGestalt 软件对 PPI 网络进行功能注释和通路富集分析,其中 P < 0.05 被认为具有统计学意义。

结果

与对照样本相比,非转移性 OS 和转移性 OS 样本中分别有 42 个和 341 个基因的表达发生改变。基因本体论分析获得了 15 个具有显著意义的富集功能(P < 0.05)。DEGs 被分类并在三个途径中显著富集,包括三羧酸循环、溶酶体和轴突导向。参与富集途径的基因包括 HRAS、IDH3A、ATP6AP1、ATP6V0D2、SEMA3F 和 SEMA3A 等。

结论

转移性 OS 样本中的枢纽基因不仅是 OS 的生物标志物,还有助于改善 OS 的治疗方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d36d/3878683/effa34384063/2047-783X-18-57-1.jpg

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