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基于整合生物信息学分析探讨骨肉瘤中年龄相关差异表达基因及潜在分子机制。

Investigating age‑induced differentially expressed genes and potential molecular mechanisms in osteosarcoma based on integrated bioinformatics analysis.

机构信息

Department of Orthopedics Ward II, Shenzhen Children's Hospital, Shenzhen, Guangdong 518038, P.R. China.

Shanxi Institute of Pediatric Diseases, Xi'an Children's Hospital, Xi'an, Shanxi 710043, P.R. China.

出版信息

Mol Med Rep. 2019 Apr;19(4):2729-2739. doi: 10.3892/mmr.2019.9912. Epub 2019 Jan 30.

DOI:10.3892/mmr.2019.9912
PMID:30720085
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6423644/
Abstract

Osteosarcoma (OS) is the most common primary bone malignancy. It predominantly occurs in adolescents, but can develop at any age. The age at diagnosis is a prognostic factor of OS, but the molecular basis of this remains unknown. The current study aimed to identify age‑induced differentially expressed genes (DEGs) and potential molecular mechanisms that contribute to the different outcomes of patients with OS. Microarray data (GSE39058 and GSE39040) obtained from the Gene Expression Omnibus database and used to analyze age‑induced DEGs to reveal molecular mechanism of OS among different age groups (<20 and >20 years old). Differentially expressed mRNAs (DEMs) were divided into up and downregulated DEMs (according to the expression fold change), then Gene Ontology function enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analysis were performed. Furthermore, the interactions among proteins encoded by DEMs were integrated with prediction for microRNA‑mRNA interactions to construct a regulatory network. The key subnetwork was extracted and Kaplan‑Meier survival analysis for a key microRNA was performed. DEMs within the subnetwork were predominantly involved in 'ubiquitin protein ligase binding', 'response to growth factor', 'regulation of type I interferon production', 'response to decreased oxygen levels', 'voltage‑gated potassium channel complex', 'synapse part', 'regulation of stem cell proliferation'. In summary, integrated bioinformatics was applied to analyze the potential molecular mechanisms leading to different outcomes of patients with OS among different age groups. The hub genes within the key subnetwork may have crucial roles in the different outcomes associated with age and require further analysis.

摘要

骨肉瘤(OS)是最常见的原发性骨恶性肿瘤。它主要发生在青少年中,但也可在任何年龄发病。诊断时的年龄是 OS 的预后因素,但这一机制的分子基础尚不清楚。本研究旨在鉴定年龄诱导的差异表达基因(DEGs)和潜在的分子机制,这些机制可能导致不同年龄组 OS 患者的不同结局。从基因表达综合数据库(GEO)中获取的微阵列数据(GSE39058 和 GSE39040),用于分析年龄诱导的 DEGs,以揭示不同年龄组(<20 岁和>20 岁)OS 之间的分子机制。差异表达的 mRNAs(DEMs)根据表达倍数变化分为上调和下调的 DEMs,然后进行基因本体论(GO)功能富集和京都基因与基因组百科全书(KEGG)通路分析。此外,整合预测的 microRNA-mRNA 相互作用,以构建调控网络,来整合由 DEMs 编码的蛋白质之间的相互作用。提取关键子网,并对关键 microRNA 进行 Kaplan-Meier 生存分析。子网内的 DEMs 主要参与“泛素蛋白连接酶结合”、“对生长因子的反应”、“I 型干扰素产生的调节”、“对低氧水平的反应”、“电压门控钾通道复合物”、“突触部分”、“干细胞增殖的调节”。综上所述,应用综合生物信息学方法分析了不同年龄组 OS 患者不同结局的潜在分子机制。关键子网内的枢纽基因可能在与年龄相关的不同结局中发挥关键作用,需要进一步分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9802/6423644/150720949f3c/MMR-19-04-2729-g09.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9802/6423644/92c646dcaedb/MMR-19-04-2729-g00.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9802/6423644/c8d4d0d04936/MMR-19-04-2729-g01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9802/6423644/5f6de6032102/MMR-19-04-2729-g03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9802/6423644/9dcaf5272f55/MMR-19-04-2729-g04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9802/6423644/4c0474ff836e/MMR-19-04-2729-g05.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9802/6423644/4eb15761c0ef/MMR-19-04-2729-g06.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9802/6423644/c8e79bbc9b97/MMR-19-04-2729-g08.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9802/6423644/150720949f3c/MMR-19-04-2729-g09.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9802/6423644/92c646dcaedb/MMR-19-04-2729-g00.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9802/6423644/c8d4d0d04936/MMR-19-04-2729-g01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9802/6423644/5f6de6032102/MMR-19-04-2729-g03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9802/6423644/9dcaf5272f55/MMR-19-04-2729-g04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9802/6423644/4c0474ff836e/MMR-19-04-2729-g05.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9802/6423644/4eb15761c0ef/MMR-19-04-2729-g06.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9802/6423644/c8e79bbc9b97/MMR-19-04-2729-g08.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9802/6423644/150720949f3c/MMR-19-04-2729-g09.jpg

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2
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Cell Mol Immunol. 2017 May 1;14(11):909-23. doi: 10.1038/cmi.2017.12.
3
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Cancers (Basel). 2023 Oct 19;15(20):5044. doi: 10.3390/cancers15205044.
4
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iScience. 2023 Jun 8;26(7):107067. doi: 10.1016/j.isci.2023.107067. eCollection 2023 Jul 21.
5
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6
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Cancer Res. 2015 Nov 15;75(22):4839-51. doi: 10.1158/0008-5472.CAN-15-0711. Epub 2015 Sep 30.
7
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Oncol Lett. 2015 Apr;9(4):1567-1574. doi: 10.3892/ol.2015.2926. Epub 2015 Feb 3.
8
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Chem Biol Interact. 2015 May 5;232:49-57. doi: 10.1016/j.cbi.2015.02.019. Epub 2015 Mar 3.
9
limma powers differential expression analyses for RNA-sequencing and microarray studies.limma为RNA测序和微阵列研究提供差异表达分析的动力。
Nucleic Acids Res. 2015 Apr 20;43(7):e47. doi: 10.1093/nar/gkv007. Epub 2015 Jan 20.
10
The HIF-1α/CXCR4 pathway supports hypoxia-induced metastasis of human osteosarcoma cells.HIF-1α/CXCR4通路支持缺氧诱导的人骨肉瘤细胞转移。
Cancer Lett. 2015 Feb 1;357(1):254-264. doi: 10.1016/j.canlet.2014.11.034. Epub 2014 Nov 18.