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利用表达谱鉴定与多发性骨髓瘤浆细胞相关的关键基因。

Identification of the key genes connected with plasma cells of multiple myeloma using expression profiles.

作者信息

Zhang Kefeng, Xu Zhongyang, Sun Zhaoyun

机构信息

Spinal Surgery, Jining No 1 People's Hospital, Jining, People's Republic of China.

Department of Orthopedics, The People's Hospital of Laiwu City, Laiwu, Shandong Province, People's Republic of China.

出版信息

Onco Targets Ther. 2015 Jul 20;8:1795-803. doi: 10.2147/OTT.S80075. eCollection 2015.

DOI:10.2147/OTT.S80075
PMID:26229487
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4516193/
Abstract

OBJECTIVE

To uncover the potential regulatory mechanisms of the relevant genes that contribute to the prognosis and prevention of multiple myeloma (MM).

METHODS

Microarray data (GSE13591) were downloaded, including five plasma cell samples from normal donors and 133 plasma cell samples from MM patients. Differentially expressed genes (DEGs) were identified by Student's t-test. Functional enrichment analysis was performed for DEGs using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Transcription factors and tumor-associated genes were also explored by mapping genes in the TRANSFAC, the tumor suppressor gene (TSGene), and tumor-associated gene (TAG) databases. A protein-protein interaction (PPI) network and PPI subnetworks were constructed by Cytoscape software using the Search Tool for the Retrieval of Interacting Genes (STRING) database.

RESULTS

A total of 63 DEGs (42 downregulated, 21 upregulated) were identified. Functional enrichment analysis showed that HLA-DRB1 and VCAM1 might be involved in the positive regulation of immune system processes, and HLA-DRB1 might be related to the intestinal immune network for IgA production pathway. The genes CEBPD, JUND, and ATF3 were identified as transcription factors. The top ten nodal genes in the PPI network were revealed including HLA-DRB1, VCAM1, and TFRC. In addition, genes in the PPI subnetwork, such as HLA-DRB1 and VCAM1, were enriched in the cell adhesion molecules pathway, whereas CD4 and TFRC were both enriched in the hematopoietic cell pathway.

CONCLUSION

Several crucial genes correlated to MM were identified, including CD4, HLA-DRB1, TFRC, and VCAM1, which might exert their roles in MM progression via immune-mediated pathways. There might be certain regulatory correlations between HLA-DRB1, CD4, and TFRC.

摘要

目的

揭示与多发性骨髓瘤(MM)预后及预防相关基因的潜在调控机制。

方法

下载微阵列数据(GSE13591),包括来自正常供体的5个浆细胞样本和来自MM患者的133个浆细胞样本。通过学生t检验鉴定差异表达基因(DEG)。使用基因本体论(GO)和京都基因与基因组百科全书(KEGG)数据库对DEG进行功能富集分析。还通过在TRANSFAC、肿瘤抑制基因(TSGene)和肿瘤相关基因(TAG)数据库中映射基因来探索转录因子和肿瘤相关基因。使用Cytoscape软件和检索相互作用基因的搜索工具(STRING)数据库构建蛋白质-蛋白质相互作用(PPI)网络和PPI子网。

结果

共鉴定出63个DEG(42个下调,21个上调)。功能富集分析表明,HLA-DRB1和VCAM1可能参与免疫系统过程的正调控,且HLA-DRB1可能与IgA产生途径的肠道免疫网络有关。基因CEBPD、JUND和ATF3被鉴定为转录因子。揭示了PPI网络中的前十个节点基因,包括HLA-DRB1、VCAM1和TFRC。此外,PPI子网中的基因,如HLA-DRB1和VCAM1,富集在细胞粘附分子途径中,而CD4和TFRC均富集在造血细胞途径中。

结论

鉴定出几个与MM相关的关键基因,包括CD4、HLA-DRB1、TFRC和VCAM1,它们可能通过免疫介导途径在MM进展中发挥作用。HLA-DRB1、CD4和TFRC之间可能存在一定的调控相关性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c646/4516193/e2b521951400/ott-8-1795Fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c646/4516193/e24f1949969f/ott-8-1795Fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c646/4516193/710afb860d1f/ott-8-1795Fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c646/4516193/e2b521951400/ott-8-1795Fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c646/4516193/e24f1949969f/ott-8-1795Fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c646/4516193/710afb860d1f/ott-8-1795Fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c646/4516193/e2b521951400/ott-8-1795Fig3.jpg

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本文引用的文献

1
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2
Identification of a novel HLA-DRB1*11:129 allele in a Chinese individual by sequence-based typing.通过序列分型在中国个体中鉴定出一种新型HLA-DRB1*11:129等位基因。
Tissue Antigens. 2013 Apr;81(4):237-9. doi: 10.1111/tan.12069.
3
In silico identification of oncogenic potential of fyn-related kinase in hepatocellular carcinoma.在肝细胞癌中鉴定与 Fyn 相关激酶的致癌潜能的计算机模拟。
基于生物信息学方法鉴定轻链淀粉样变性的候选基因和治疗药物。
Pharmgenomics Pers Med. 2019 Dec 31;12:387-396. doi: 10.2147/PGPM.S228574. eCollection 2019.
Bioinformatics. 2013 Feb 15;29(4):420-7. doi: 10.1093/bioinformatics/bts715. Epub 2012 Dec 24.
4
STRING v9.1: protein-protein interaction networks, with increased coverage and integration.STRING v9.1:蛋白质-蛋白质相互作用网络,具有更高的覆盖度和集成度。
Nucleic Acids Res. 2013 Jan;41(Database issue):D808-15. doi: 10.1093/nar/gks1094. Epub 2012 Nov 29.
5
A travel guide to Cytoscape plugins. Cytoscape 插件使用指南。
Nat Methods. 2012 Nov;9(11):1069-76. doi: 10.1038/nmeth.2212. Epub 2012 Nov 6.
6
Prediagnosis biomarkers of insulin-like growth factor-1, insulin, and interleukin-6 dysregulation and multiple myeloma risk in the Multiple Myeloma Cohort Consortium.胰岛素样生长因子-1、胰岛素和白细胞介素-6 失调的预测生物标志物与多发性骨髓瘤风险在多发性骨髓瘤队列研究联盟中的关系。
Blood. 2012 Dec 13;120(25):4929-37. doi: 10.1182/blood-2012-03-417253. Epub 2012 Oct 16.
7
TSGene: a web resource for tumor suppressor genes.TSGene:肿瘤抑制基因的网络资源。
Nucleic Acids Res. 2013 Jan;41(Database issue):D970-6. doi: 10.1093/nar/gks937. Epub 2012 Oct 12.
8
Canonical and noncanonical Hedgehog pathway in the pathogenesis of multiple myeloma.经典和非经典 Hedgehog 通路在多发性骨髓瘤发病机制中的作用。
Blood. 2012 Dec 13;120(25):5002-13. doi: 10.1182/blood-2011-07-368142. Epub 2012 Jul 20.
9
Whole-genome sequencing of multiple myeloma from diagnosis to plasma cell leukemia reveals genomic initiating events, evolution, and clonal tides.从多发性骨髓瘤到浆细胞白血病的全基因组测序揭示了基因组起始事件、演变和克隆潮。
Blood. 2012 Aug 2;120(5):1060-6. doi: 10.1182/blood-2012-01-405977. Epub 2012 Apr 23.
10
Overexpression of HOXB7 and homeobox genes characterizes multiple myeloma patients lacking the major primary immunoglobulin heavy chain locus translocations.HOXB7 和同源盒基因的过表达特征是缺乏主要原发性免疫球蛋白重链基因座易位的多发性骨髓瘤患者。
Am J Hematol. 2011 Dec;86(12):E64-6. doi: 10.1002/ajh.22164. Epub 2011 Sep 22.