[1]侯 丽,张 丽,唐 婧,等.基于GEO 对多发性骨髓瘤关键基因生物信息学分析及免疫浸润模式与验证[J].现代检验医学杂志,2023,38(05):23-28.[doi:10.3969/j.issn.1671-7414.2023.05.005]
　HOU Li,ZHANG Li,TANG Jing,et al.Bioinformatics Analysis and Verify Core Genes and Immune Infiltration Patterns in Multiple Myeloma Based on GEO[J].Journal of Modern Laboratory Medicine,2023,38(05):23-28.[doi:10.3969/j.issn.1671-7414.2023.05.005]
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基于GEO 对多发性骨髓瘤关键基因生物信息学分析及免疫浸润模式与验证()
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《现代检验医学杂志》[ISSN:/CN:]

卷:
第38卷
期数:
2023年05期
页码:
23-28
栏目:
论著
出版日期:
2023-09-15

文章信息/Info

Title:
Bioinformatics Analysis and Verify Core Genes and Immune Infiltration Patterns in Multiple Myeloma Based on GEO
文章编号:
1671-7414（2023）05-023-06
作者:
侯 丽1; 张 丽1; 唐 婧1; 牛 瑶1; 张 媛2; 朱有森1
（1. 新疆医科大学第一附属医院医学检验中心，乌鲁木齐 830054；2. 喀什地区第二人民医院检验科，新疆喀什 844000）
Author(s):
HOU Li1;  ZHANG Li1;  TANG Jing1;  NIU Yao1;  ZHANG Yuan2;  ZHU Yousen1
(1. Medical Laboratory Center, the First Affiliated Hospital of Xinjiang Medical University, Urumqi 830054, China; 2. Department of Clinical Laboratory, the Second People’s Hospital of Kashi Prefecture, Xinjiang Kashi 844000, China)
关键词:
生物信息学; 多发性骨髓瘤; 免疫浸润
分类号:
R733.3；Q786
DOI:
10.3969/j.issn.1671-7414.2023.05.005
文献标志码:
A
摘要:
目的 通过生物信息学方法筛选多发性骨髓瘤（multiple myeloma，MM）潜在的关键基因，并分析其免疫浸润模式。方法 从基因表达综合数据库(gene expression omnibus，GEO) 获取与多发性骨髓瘤相关的基因表达谱GSE118985，(GSE133346和GSE146649)，采用生物信息学方法筛选与多发性骨髓瘤相关的差异表达基因(DEGs)并进行基因本体(GO）功能注释和京都基因与基因组百科全书(KEGG) 富集分析、免疫细胞浸润分析。通过蛋白质- 蛋白质相互作用网络筛选出多发性骨髓瘤潜在的关键基因，利用数据GSE7116 验证关键基因在多发性骨髓瘤中的诊断价值并绘制受试者工作特征（receiver operator characteristic，ROC）曲线。结果 共筛选出101 个DEGs。GO 功能注释和KEGG 富集分析显示，DEGs 主要富集在免疫反应过程中，细胞因子受体相互作用、细胞外基质受体相互作用、粘着斑和Hedgehog 信号通路等，单核细胞是多发性骨髓瘤最主要的免疫浸润细胞。最终筛选出5 个关键基因，分别为SDC1，IRF4，CD38，TNFRSF17和CCND1，核心基因对验证模型联合诊断的AUC 为0.933。结论 SDC1，IRF4，CD38，TNFRSF17 和CCND1 在多发性骨髓瘤中均上调，联合诊断的效能较高，可能是多发性骨髓瘤潜在的生物标志物，可为以后治疗提供新的思路。
Abstract:
Objective To screen the potential key genes of multiple myeloma (MM) and analyze its immune infiltration pattern by bioinformatics methods. Methods The gene expression profiles (GSE118985，GSE133346 and GSE146649) related to multiple myeloma were obtained from Gene Expression Omnibus (GEO) database, and the differentially expressed genes (DEGs) related to multiple myeloma were screened by bioinformatics methods. Gene ontology (GO) functional annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and immune cell infiltration analysis were performed. The potential key genes of multiple myeloma were screened by protein-protein interaction network, and the data GSE7116 was used to verify the diagnostic value of key genes in multiple myeloma , and the ROC curve was drawn. Results A total of 101 DEGs were screened. GO functional annotation and KEGG enrichment analysis showed that DEGs were mainly enriched in the process of immune response, cytokine receptor interaction, extracellular matrix receptor interaction, focal adhesion, Hedgehog signaling pathway, etc. Monocytes are the most important immune infiltrating cells in multiple myeloma. Five key genes were selected, namely SDC1,IRF4,CD38,TNFRSF17 and CCND1. The AUC of the core genes for the combined diagnosis of the validation model was 0.933. Conclusion SDC1,IRF4, CD38,TNFRSF17 and CCND1 were up-regulated in multiple myeloma , and the combined diagnosis efficiency was high, which may be potential biomarkers of multiple myeloma , and provide new thoughts for future treatment.

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备注/Memo

备注/Memo:
基金项目：新疆维吾尔自治区科技支疆计划(2022E2056)。
作者简介：侯丽（1988-），女，硕士研究生，主管技师，主要从事临床检验诊断学及生物信息学，E-mail:sjyh135@qq.com。
通讯作者：朱有森（1969-），男，主任技师, 主要从事临床检验诊断学及分子生物学。
更新日期/Last Update: 2023-09-15