Cargando…

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

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 pat...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Kefeng, Xu, Zhongyang, Sun, Zhaoyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4516193/
https://www.ncbi.nlm.nih.gov/pubmed/26229487
http://dx.doi.org/10.2147/OTT.S80075
_version_ 1782383027411746816
author Zhang, Kefeng
Xu, Zhongyang
Sun, Zhaoyun
author_facet Zhang, Kefeng
Xu, Zhongyang
Sun, Zhaoyun
author_sort Zhang, Kefeng
collection PubMed
description 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.
format Online
Article
Text
id pubmed-4516193
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher Dove Medical Press
record_format MEDLINE/PubMed
spelling pubmed-45161932015-07-30 Identification of the key genes connected with plasma cells of multiple myeloma using expression profiles Zhang, Kefeng Xu, Zhongyang Sun, Zhaoyun Onco Targets Ther Original Research 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. Dove Medical Press 2015-07-20 /pmc/articles/PMC4516193/ /pubmed/26229487 http://dx.doi.org/10.2147/OTT.S80075 Text en © 2015 Zhang et al. This work is published by Dove Medical Press Limited, and licensed under Creative Commons Attribution – Non Commercial (unported, v3.0) License The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.
spellingShingle Original Research
Zhang, Kefeng
Xu, Zhongyang
Sun, Zhaoyun
Identification of the key genes connected with plasma cells of multiple myeloma using expression profiles
title Identification of the key genes connected with plasma cells of multiple myeloma using expression profiles
title_full Identification of the key genes connected with plasma cells of multiple myeloma using expression profiles
title_fullStr Identification of the key genes connected with plasma cells of multiple myeloma using expression profiles
title_full_unstemmed Identification of the key genes connected with plasma cells of multiple myeloma using expression profiles
title_short Identification of the key genes connected with plasma cells of multiple myeloma using expression profiles
title_sort identification of the key genes connected with plasma cells of multiple myeloma using expression profiles
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4516193/
https://www.ncbi.nlm.nih.gov/pubmed/26229487
http://dx.doi.org/10.2147/OTT.S80075
work_keys_str_mv AT zhangkefeng identificationofthekeygenesconnectedwithplasmacellsofmultiplemyelomausingexpressionprofiles
AT xuzhongyang identificationofthekeygenesconnectedwithplasmacellsofmultiplemyelomausingexpressionprofiles
AT sunzhaoyun identificationofthekeygenesconnectedwithplasmacellsofmultiplemyelomausingexpressionprofiles