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ARTICLE
Identification of EML4 as a key hub gene for endometriosis and its molecular mechanism and potential drug prediction based on the GEO database
XIANBAO FANG1,#, MINGYAN TANG1,#, ZIYANG YU1,#, JIAQI DING1, CHONG CUI2, HONG ZHANG1,*
1 Reproductive Medicine Center, The Second Affiliated Hospital of Soochow University, Suzhou, 215002, China
2 Imaging Diagnosis Department, The Second Affiliated Hospital of Soochow University, Suzhou, 215002, China
* Corresponding Author: Hong Zhang,
# Equal contribution
(This article belongs to the Special Issue: Bioinformatics Study of Diseases)
BIOCELL 2023, 47(9), 2059-2068. https://doi.org/10.32604/biocell.2023.030565
Received 13 April 2023; Accepted 29 May 2023; Issue published 28 September 2023
Abstract
Objective: Key genes were screened to analyze molecular mechanisms and their drug targets of endometriosis
by applying a bioinformatics approach.
Methods: Gene expression profiles of endometriosis and healthy controls were
obtained from the Gene Expression Omnibus database. Significant differentially expressed genes were screened using
the limma package. Correlation pathways were screened by Spearman correlation analysis on the echinoderm
microtubule-associated protein-like 4 (EML4) and enrichment in endometriosis pathways and estimated by the GSVA
package. Immune characteristics were assessed by the “ESTIMATE” R package. Potential regulatory pathways were
determined by enrichment analysis. The SWISS-MODE website was used in homology modeling with EML4 and
EML4 protein activity was predicted. VarElect was employed in molecular docking for screening potential compound
inhibitors targeting endometriosis.
Results: Ten endometriosis and 10 normal samples were included. EML4 was
significantly upregulated in endometriosis (
p < 0.05). Thirty significantly correlated pathways involving 18 positive
and 12 negative correlations, including GLYCOSAMINOGLYCAN_BIOSYNTHESIS_HEPARAN_SULFATE and
GLYCOSPHINGOLIPID_BIOSYNTHESIS_GANGLIO_SERIES were screened between EML4 and endometriosis.
Immunocorrelation analysis showed a significant difference in immune-related pathways in endometriosis and normal
samples (
p < 0.05). In endometriosis, EML4 was associated with T-cell CD4 resting memory, activated mast cells,
plasma cells, activated NK cells, M2 macrophages, and follicular helper T cells (
p < 0.05). Molecular docking
identified five potential inhibitors of EML4, and compound DB05104 (asimadoline) bound well to EML4 protein to
exert its physiological effects.
Conclusion: Differential gene expression and immune correlation analyses revealed that
EML4 may affect endometriosis through multiple targets and pathways, the mechanism of which involved immune
cell activation and infiltration. Molecular docking and dynamics simulation verified DB05104 as a potential inhibitor
of EML4 and a powerful target for endometriosis treatment.
Graphical Abstract
Keywords
Cite This Article
APA Style
FANG, X., TANG, M., YU, Z., DING, J., CUI, C. et al. (2023). Identification of EML4 as a key hub gene for endometriosis and its molecular mechanism and potential drug prediction based on the GEO database. BIOCELL, 47(9), 2059-2068. https://doi.org/10.32604/biocell.2023.030565
Vancouver Style
FANG X, TANG M, YU Z, DING J, CUI C, ZHANG H. Identification of EML4 as a key hub gene for endometriosis and its molecular mechanism and potential drug prediction based on the GEO database. BIOCELL . 2023;47(9):2059-2068 https://doi.org/10.32604/biocell.2023.030565
IEEE Style
X. FANG, M. TANG, Z. YU, J. DING, C. CUI, and H. ZHANG "Identification of EML4 as a key hub gene for endometriosis and its molecular mechanism and potential drug prediction based on the GEO database," BIOCELL , vol. 47, no. 9, pp. 2059-2068. 2023. https://doi.org/10.32604/biocell.2023.030565