Bioinformatics Analysis of Microarray Data in Myelodysplastic Syndrome Based on Gene Expression Omnibus Database.
10.19746/j.cnki.issn.1009-2137.2022.02.031
- Author:
Bing-Jie DING
1
;
Hu ZHOU
2
;
Liu LIU
3
;
Pei-Pei XU
1
;
Jian-Ping LIU
1
;
Yong-Ping SONG
1
Author Information
1. Department of Hematology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou 450008, Henan Province, China.
2. Department of Hematology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou 450008, Henan Province, China,E-mail: tigerzhoupumc@163.com.
3. Department of Hematology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China.
- Publication Type:Journal Article
- Keywords:
bioinformatics;
differentially expressed gene;
gene chip;
myelodysplastic syndrome
- MeSH:
Computational Biology;
Gene Expression;
Gene Expression Profiling;
Humans;
Microarray Analysis;
Myelodysplastic Syndromes/genetics*;
Protein Interaction Maps
- From:
Journal of Experimental Hematology
2022;30(2):511-515
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE:To identify the key genes and explore mechanisms in the development of myelodysplastic syndrome (MDS) by bioinformatics analysis.
METHODS:Two cohorts profile datasets of MDS were downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed gene (DEG) was screened by GEO2R, functional annotation of DEG was gained from GO database, gene ontology (GO) enrichment analysis was performed via Kyoto Encyclopedia of Genes and Genomes (KEGG) database, and key genes were screened by Matthews correlation coefficient (MCC) based on STRING database.
RESULTS:There were 112 DEGs identified, including 85 up-regulated genes and 27 down-regulated genes. GO enrichment analysis showed that biological processes were mainly enriched in immune response, etc, cellular component in cell membrane, etc, and molecular function in protein binding, etc. KEGG signaling pathway analysis showed that main gene enrichment pathways were primary immunodeficiency, hematopoietic cell lineage, B cell receptor signaling pathway, Hippo signaling pathway, and asthma. Three significant modules were screened by Cytoscape software MCODE plug-in, while 10 key node genes (CD19, CD79A, CD79B, EBF1, VPREB1, IRF4, BLNK, RAG1, POU2AF1, IRF8) in protein-protein interaction (PPI) network were screened based on STRING database.
CONCLUSION:These screened key genes and signaling pathways are helpful to better understand molecular mechanism of MDS, and provide theoretical basis for clinical targeted therapy.
