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基于内质网应激和肿瘤转移相关基因构建骨肉瘤分子亚型模型

Construction of molecular subtype model of osteosarcoma based on endoplasmic reticulum stress and tumor metastasis-related genes.

作者信息

Wu Wang-Qiang, Zou Cheng-Da, Wu Di, Fu Hou-Xin, Wang Xiao-Dong, Yao Feng

机构信息

Department of Orthopaedics, Children's Hospital of Soochow University, 92# Zhongnan Street, Suzhou, Jiangsu 215025, China.

Children's Hospital of Soochow University, Children's Hospital of Wujiang District, China.

出版信息

Heliyon. 2024 Feb 6;10(3):e25691. doi: 10.1016/j.heliyon.2024.e25691. eCollection 2024 Feb 15.

DOI:10.1016/j.heliyon.2024.e25691
PMID:38371978
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10873750/
Abstract

INTRODUCTION

Osteosarcoma, the prevailing primary bone malignancy among children and adolescents, is frequently associated with treatment failure primarily due to its pronounced metastatic nature.

METHODS

This study aimed to establish potential associations between hub genes and subtypes for the treatment of metastatic osteosarcoma. Differentially expressed genes were extracted from patients diagnosed with metastatic osteosarcoma and a control group of non-metastatic patients, using the publicly available gene expression profile (GSE21257). The intersection of these gene sets was determined by focusing on endoplasmic reticulum (ER) stress-related genes sourced from the GeneCards database. We conducted various analytical techniques, including functional and pathway enrichment analysis, WGCNA analysis, protein-protein interaction (PPI) network construction, and assessment of immune cell infiltration, using the intersecting genes. Through this analysis, we identified potential hub genes.

RESULTS

Osteosarcoma subtype models were developed using molecular consensus clustering analysis, followed by an examination of the associations between each subtype and hub genes. A total of 138 potential differentially expressed genes related to endoplasmic reticulum (ER) stress were identified. These genes were further investigated using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) pathways. Additionally, the PPI interaction network revealed 38 interaction relationships among the top ten hub genes. The findings of the analysis revealed a strong correlation between the extent of immune cell infiltration and both osteosarcoma metastasis and the expression of hub genes. Notably, the differential expression of the top ten hub genes was observed in osteosarcoma clusters 1 and 4, signifying their significant association with the disease.

CONCLUSION

The identification of ten key genes linked to osteosarcoma metastasis and endoplasmic reticulum stress bears potential clinical significance. Additionally, exploring the molecular subtype of osteosarcoma has the capacity to guide clinical treatment decisions, necessitating further investigations and subsequent clinical validations.

摘要

引言

骨肉瘤是儿童和青少年中最常见的原发性骨恶性肿瘤,由于其明显的转移性,常与治疗失败相关。

方法

本研究旨在建立枢纽基因与转移性骨肉瘤治疗亚型之间的潜在关联。使用公开可用的基因表达谱(GSE21257),从诊断为转移性骨肉瘤的患者和非转移性患者的对照组中提取差异表达基因。通过关注来自GeneCards数据库的内质网(ER)应激相关基因,确定这些基因集的交集。我们使用这些相交基因进行了各种分析技术,包括功能和通路富集分析、WGCNA分析、蛋白质-蛋白质相互作用(PPI)网络构建以及免疫细胞浸润评估。通过该分析,我们确定了潜在的枢纽基因。

结果

使用分子共识聚类分析建立骨肉瘤亚型模型,随后检查每个亚型与枢纽基因之间的关联。共鉴定出138个与内质网(ER)应激相关的潜在差异表达基因。使用基因本体论(GO)、京都基因与基因组百科全书(KEGG)和基因集富集分析(GSEA)通路对这些基因进行了进一步研究。此外,PPI相互作用网络揭示了前十个枢纽基因之间的38种相互作用关系。分析结果显示免疫细胞浸润程度与骨肉瘤转移及枢纽基因表达之间存在强相关性。值得注意的是,在前十个枢纽基因的差异表达在骨肉瘤簇1和4中被观察到,表明它们与该疾病有显著关联。

结论

鉴定出与骨肉瘤转移和内质网应激相关的十个关键基因具有潜在的临床意义。此外,探索骨肉瘤的分子亚型有能力指导临床治疗决策,需要进一步研究和后续临床验证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2174/10873750/12508a963512/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2174/10873750/c56fd79e4187/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2174/10873750/045b67e1090f/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2174/10873750/78f642990ab8/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2174/10873750/b5a2902e8351/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2174/10873750/d5062326daba/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2174/10873750/e97f526d1705/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2174/10873750/e0d6a75c7fbb/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2174/10873750/12508a963512/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2174/10873750/c56fd79e4187/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2174/10873750/045b67e1090f/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2174/10873750/78f642990ab8/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2174/10873750/b5a2902e8351/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2174/10873750/d5062326daba/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2174/10873750/e97f526d1705/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2174/10873750/e0d6a75c7fbb/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2174/10873750/12508a963512/gr8.jpg

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