子宫内膜异位症患者细胞外基质相关基因筛选的生物信息学分析

doi:10.13481/j.1671-587X.20220123

Abstract

Abstract: Objective

To screen the differentially expressed genes （DEGs） of endometriosis （EMS） by bioinformatics tools，and to provide theoretical basis for clarifyinng the pathogenesis of EMS， and to find a new research direction for the diagnosis and treatment of EMS.

Methods

The datasets （GSE25628， GSE23339 and GSE7305） including EMS tissue and normal endometrial tisue were downloaded from the Gene Expression Omnibus（GEO） database by searching for endometriosis. The GE02R online analvsis tools were used to screen for the DEGs in the EMS tissue and the normal endometrial tissue. Gene Ontology （GO） enrichment analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） were used to analyze the function and pathway enrichment of DEGs， the STRING database was used to establish the protein-protein interaction （PPI） network. Finally，the PPI network was analyzed and visualized by Cytoscape software， and the top ten core genes were screened.

Results

After the DEGs analysis， a total of 27 up-regulated DEGs and 43 down-regulated DEGs were identified. The GO enrichment analysis results showed that DEGs were mainly enriched in the extracellular matrix， extracellular space， extracellular region and so on. The results of KEGG pathway analysis demonstrated that DEGs were mainly enriched in phosphate inositol metabolic signal pathway.Through STRING and Cytoscape softwares， the top 10 core genes with the highest connectivities in the PPI network were screened out， including DCN， EPCAM， BGN， FABP4， NTRK2， GPC-3， ERBB3， CD24， NID2， and THBS2. Among them， DCN， BGN， NID2， and THBS2 were associated with the biological function of extracellular matrix.

Conclusion

The disorder of extracellular matrix-related genes may play an important role in the occurrence and development of EMS， and the extracellular matrix-related genes may become the biomarkers and for early diagnosis and therapeutic targets of EMS.

Key words: Endometriosis, Bioinformatics, Decorin, Biglycan, Nidogen2, Throm-bospondin 2

CLC Number:

R711.71

Nan LI,Lei CHEN,Tianmin XU,Kun ZHANG. Bioinformatics analysis on screening of extracellular matrix related genes in patients with endometriosis[J].Journal of Jilin University(Medicine Edition), 2022, 48(1): 188-194.

Figures/Tables 4

Fig. 1

Tab.1

Fig. 2

Tab. 2

References 35

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Description	Gene	P
Extracellular matrix	DSP, RARRES2, COL8A2, HTRA1, BGN, LTBP2, AEBP1, THBS2, NID2, LMCD1, DCN	1.39E-07
Extracellular space	PTGIS, CFH, CCL21, HTRA1, LTBP2,AEBP1, DCN, BMP6,ERBB3, SCGB2A1, DPYSL3, GPC3, LMCD1, SCG2	0.001 265
Extracellular region	COL16A1, CFH, CCL21, RARRES2, HTRA1, BGN, PLA2G5, THBS2, NID2, DCN,PDGFRL, BMP6, C7, OLFML1, COL8A2	0.002 173
Proteinaceousm extracellular matrix	COL16A1, CCL21, COL8A2, BGN,GPC3, LTBP2	0.003 247
Wound healing single organismal	DSP, SCARB1, CDH3, ERBB3, DCN	2.91E-04
Cell-cell adhesion	DSP, CDH3, COL8A2, CD24, MPZL	27.07E-04
Kidney development	PAX8, TCF21, DCN, BMP6	0.004 906
Anatomical structure morphogenesis	PAX8, GPC3, LYVE1, MPZL2	0.005 919
Glycosaminoglycan metabolic process	BGN, GPC3, DCN	0.005 939
Extracellular - matrix organization	COL16A1, COL8A2, BGN, NID2, DCN	0.007 783
Cell adhesion	CDH3, COL16A1, THBS2, CD24, GRHL2, NID2, LYVE1	0.009 879

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Bioinformatics analysis on screening of extracellular matrix related genes in patients with endometriosis

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Gene	Description	Degree
DCN	Decorin	22
EPCAM	Epithelial cell adhesion molecule	21
BGN	Biglycan	21
FABP4	Fatty acid binding protein 4	20
NTRK2	Neurotyrosine kinase receptor	20
GPC3	Glypican3	16
ERBB3	Epidermal growth factor receptor 3	16
CD24	Cluster of differentiationprotein 24	14
NID2	Nidogen-2	14
THBS2	Thrombospondin-2	14