Diagnostic gene biomarkers for predicting immune infiltration in endometriosis

Chengmao Xie
In: Research Square · 2022 · doi:10.21203/rs.3.rs-1305846/v1 · W4210446987
preprint OA: green CC0 ⤵ 2 in-corpus citations
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⚙ AI-generated summary by claude@2026-06, 2026-06-07 ⓘ

This study identified Aquaporin 1 (AQP1) and ZW10 binding protein (ZWINT) as diagnostic biomarkers for endometriosis, which are also correlated with specific immune cell infiltrates.

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⚙ AI-generated deep summary by claude@2026-06, 2026-06-07 ⓘ

Xie et al. studied gene-expression differences between ectopic endometrium (endometriosis/EMS) and matched eutopic endometrium using two GEO microarray datasets (GSE7305 and GSE25628), merged after batch-effect correction, and applied differential expression analysis followed by machine-learning feature selection (LASSO and SVM-RFE) to identify diagnostic candidate biomarkers. Enrichment analyses highlighted pathways including arachidonic acid metabolism, cytokine–cytokine receptor interactions, complement/coagulation cascades, chemokine signaling, and systemic lupus erythematosus; the key diagnostic biomarkers were AQP1 and ZWINT, which showed discriminatory performance by ROC/AUC and were validated at mRNA and protein levels (qRT-PCR and western blot) and further validated in GSE5108. Immune infiltration was estimated with CIBERSORT, and expression of AQP1 and ZWINT correlated with multiple immune cell types, particularly M2 macrophages and several lymphocyte and mast cell subsets; a limitation is that biomarker discovery and immune estimates are based on transcriptomic datasets (with estimated immune proportions rather than direct cellular measurements) and the preprint was not peer reviewed. This paper is centrally about endometriosis—identifying AQP1 and ZWINT as diagnostic gene biomarkers linked to immune infiltration patterns in endometriosis.

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Abstract

Abstract Objective To determine the potential diagnostic markers and extent of immune cell infiltration in endometriosis (EMS). Methods From the Gene Expression Omnibus database (GEO), we downloaded two published profiles (GSE7305 and GSE25628 datasets) of human EMS and endometrial specimens. Differential genes between 17 EMS and 19 endometrial samples were compared. Candidate biomarkers were identified by support vector machine recursive feature elimination analysis and a Lasso regression model. The area under the receiver operating characteristic curve value represented the discriminatory biomarkers. The diagnostic value and expression levels of biomarkers in EMS were verified by quantitative reverse transcription polymerase chain reaction (qRT-PCR) and western blotting, then further validated in the GSE5108 dataset that included 11 eutopic and 11 ectopic endometria. On the basis of the merged cohorts, we used CIBERSORT to estimate the composition pattern of immune cell components in EMS. Results Fifty-three genes were identified in cells from benign neoplasms, polycystic ovary syndrome, gallbladder carcinomas, and adenomas. Gene sets related to arachidonic acid metabolism, cytokine–cytokine receptor interactions, complement and coagulation cascades, chemokine signaling pathways, and systemic lupus erythematosus were differentially activated in EMS compared with endometrial samples. Aquaporin 1 (AQP1) and ZW10 binding protein (ZWINT) were identified as diagnostic markers of EMS, which were verified using qRT-PCR and western blotting and validated in the GSE5108 dataset. Immune cell infiltrate analysis showed that AQP1 and ZWINT were correlated with M2 macrophages, NK cells, activated dendritic cells, T follicular helper cells, regulatory T cells, memory B cells, activated mast cells, and plasma cells. Conclusion AQP1 and ZWINT can be regarded as diagnostic markers of EMS and may provide a new direction for the study of EMS pathogenesis in the future.

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endometriosis

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