Screening Of Biomarkers Related To B Cells Infiltration In Endometriosis And Exploration Of Potential Mechanism

Objective(s): Endometriosis is a common gynecological condition associated with dysmenorrhea,pelvic pain,and infertility,and is primarily observed in women of reproductive age.Studies have reported that abnormal B cells immune responses are critical for the adhesion,invasion,and angiogenesis of ectopic endometrial cells.hence,the underlying molecular mechanisms,new diagnostic biomarkers,and therapeutic targets need to be urgently explored.Methods: In the present study,GSE51981 dataset was downloaded from the Gene Expression Omnibus database.We identify differentially expressed genes(DEGs)on the expression profiles of 77 endometriosis samples and 34 nonendometriosis samples in the GSE51981 dataset,and use "limma" package to screen differentially expressed genes with | log2(Fold Change)| value>1,FDR<0.05.The x Cell algorithm is used to determine the types of immune cells enriched in GSE51981 data set,and select B-cell-related phenotypes for further analysis.The weighted gene co-expression network(WGCNA)algorithm was used to analyze and establish the weighted gene co-expression network and identify the core genes related to B cells.Using the "cluster Profiler" package to conduct GO and KEGG enrichment analysis on core genes related to B cells,and the threshold is set to FDR<0.05.The hub genes related to B cells infiltration were screened using the machine learning algorithms,including least absolute shrinkage and selection operator regression method(LASSO)and support vector machine-recursive feature elimination(SVM-RFE).It is verified by the external dataset GSE7305.Finally,Gene Set Enrichment Analysis(GSEA)was used to explore the pathways involved in the regulation of biomarkers.In order to further explore the function of biomarkers,a competitive endogenous RNA(ce RNA)network of biomarkers was constructed and drug prediction was performed.Results: The differential expression analysis of GSE51981 dataset identified4341 DEGs.Among them,2561 DEGs were up and 1780 DEGs were down.The x Cell algorithm was used to analyze the abundance of 64 immune cells and stromal cell infiltration in 77 endometriosis and 34 non-endometriosis samples.The B cells and naive B cells were selected as phenotypes for WGCNA analysis,and hub module related to B cells were identified,including 349 genes.GO enrichment analysis of the genes in the hub module showed that the biological processes were mainly related to lipopolysaccharide reaction,neutrophil activation and immune-mediated regulation.The analysis of cell components mainly focused on secretory granular membrane and extracellular matrix containing collagen.Molecular function analysis is usually concentrated on cytokine activity,immune receptor activity and chemokine receptor binding.The signal pathways of KEGG enrichment analysis mainly includes interleukin-17(IL-17),chemokine and nuclear factor-κB(nuclear factor-kappa B,NF-κB),tumor necrosis factor(TNF),B-cell receptor,C-type lectin receptor signal pathway.Venn map was used to analyze 4341 DEGs and 349 hub module genes,and25 overlapping genes were identified for subsequent analysis.LASSO and SVM-RFE algorithms were used to screen 12 and 21 characteristic genes respectively.Venn map analysis of characteristic genes found 12 overlapping genes as potential hub genes.12 overlapping genes were verified in GSE7305 dataset,CMPK2,NR4A1,MMP2,RASGRP1,TNS1,and ZNF521 showed significant p-values < 0.05.In addition,the receiver operating characteristic curve(ROC)was used to analysis the diagnostic significance of these genes,and found that the area under the ROC curve(AUC)values of CMPK2,NR4A1,TNS1 and ZNF521 were greater than 0.85.Hence,these four hub genes were identified as diagnostic biomarkers associated with B cell infiltration in endometriosis.The expression of these four diagnostic genes was up-regulated in the endometriosis group.Pearson correlation analysis showed that there was a strong correlation between the expression of four diagnostic genes,especially TNS1 and ZNF521,and B cell marker genes.The expression level of diagnostic genes was highly correlated with many immune checkpoint molecules(p <0.05),indicating that diagnostic genes are potential co-regulators of immune checkpoints in endometriosis.GSEA was performed between the high expression group and the low expression group of the four diagnostic genes,and we obtained the pathways significantly related to the high expression group of the four diagnostic genes in endometriosis.The pathways involved in CMPK2 mainly include NK cell-mediated cytotoxicity,antigen processing and presentation,complement and coagulation cascades,and cytokine-cytokine receptor interaction.NR4A1 is mainly involved in IL-17 signaling pathway,rheumatoid arthritis,TNF signaling pathway and NF-κB signaling pathway.The pathways involved in TNS1 are mainly Ig A-producing intestinal immune network,Th1 and Th2 cell differentiation,NK cell-mediated cytotoxicity,and chemokine signaling pathways.The pathways involved in ZNF521 mainly include extracellular matrix receptor interaction,Hippo signaling pathway,focal adhesion,phosphatidylinositol 3 kinase(PI3K)kinase B(AKT)signaling pathway.In order to further study the regulatory mechanism of diagnostic genes,we constructed a ce RNA regulatory network.Finally,we predicted potential drugs targeting diagnostic genes through the Comparative Toxicogenics Database database,providing a new perspective for drug treatment of endometriosis.Conclusion(s): This study identified and validated four potential B-cells related biomarkers in endometriosis,including CMPK2,NR4A1,TNS1,and ZNF521,that were upregulated in endometriosis.The functions of the four biomarkers and the role of B-cell infiltration in endometriosis were determined using bioinformatics analysis,providing new insights into endometriosis at the immune and molecular levels.