Abstract
Background
Endometriosis (EMS) is a common and highly recurrent gynecological disease characterized by chronic pain and infertility. There are no definitive therapies for endometriosis since the pathogenesis remains undetermined. This study aimed to identify EMS-related functional modules and hub genes by integrated bioinformatics analysis.
Methods
Three endometriosis expression profiling series (GSE25628, GSE23339, and GSE7305) were obtained from Gene Expression Omnibus (GEO). The EMS-related module was constructed by weighted gene co-expression network analysis (WGCNA), followed by Gene Ontology (GO) enrichment analyses. Cytohubba and the MCODE plug-ins of Cytoscape were used to screen out the hub genes, which were verified via receiver operating characteristic (ROC) curves. Immunohistochemistry was performed to verify the protein expression of the hub genes in ectopic endometrial tissues. Moreover, CIBERSORT was used to analyze the relationship between the abundance of immune cells infiltration and the expression of hub genes.
Results
Among the 18 modules obtained, the darkmagenta module was identified as the EMS-related module, genes of which were significantly enriched to terms referring to cell migration and neurogenesis. NFASC and CHL1 were screened out and prioritized as hub genes through Cytoscape and confirmed to be differentially upregulated in ectopic endometrial samples. Finally, the expression of hub genes was related to the abundance of immune cells infiltration. The higher expression of NFASC or CHL1 correlated with increased M2 macrophages and decreased natural killer (NK) cells in ectopic lesions.
Conclusion
This study provided new insights into the molecular factors underlying the pathogenesis of endometriosis and provided a theoretical basis for the potential that the two hub genes, NFASC and CHL1, might be novel biomarkers and therapeutic targets in the future.
Abbreviations
EMS, endometriosis; GEO, Gene Expression Omnibus; WGCNA, weighted gene co-expression network analysis; GO, Gene Ontology; ROC, receiver operating characteristic; NK, natural killer; DEGs, differentially expressed genes; IHC, immunohistochemistry; NCBI, National Center for Biotechnology Information; PCA, principal component analysis; TOM, topological overlap matrix; ME, module eigengene; GS, gene significance; MM, module membership; MCC, Maximal Clique Centrality; IRS, Immuno-Reactivity Score.
Data Sharing Statement
The endometriosis datasets of expression profiling including GSE25628, GSE23339 and GSE7305 were downloaded from the GEO database (https://www.ncbi.nlm.nih.gov/geo/).
Ethics Approval and Informed Consent
The study was approved by the Ethics Committee of Women’s Hospital, School of Medicine, Zhejiang University (IRB-20200096-R), in accordance with the principles of the Declaration of Helsinki. All clinical samples were obtained with written informed consent from patients.
Acknowledgment
We thank Yanhong Shou for her technical assistance.
Author Contributions
All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.
Disclosure
The authors have declared no conflicts of interest in this work.