Diagnostic gene biomarkers for predicting immune infiltration in endometriosis.
Objective: To determine the potential diagnostic markers and extent of immune cell infiltration in endometriosis (EMS).Methods: Two published profiles (GSE7305 and GSE25628 datasets) were downloaded, and the candidate biomarkers were identified by support vector machine recursive feature elimination...
| Publicado en: | BMC Women's Health Vol. 22; no. 1; pp. 1 - 15 |
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| Autores principales: | , , , |
| Formato: | Journal Article |
| Publicado: |
BioMed Central
5/18/2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=156934001&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 156934001 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 14726874 1CIP jtl: BMC Women's Health issn: 14726874 maglogo: N pubinfo: dt: 5/18/2022 vid: 22 iid: 1 pid: 24147 pub: BioMed Central artinfo: ui: 156934001 156934001 NLM35585523 10.1186/s12905-022-01765-3 NLM35585523 156934001 ppf: 1 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Diagnostic gene biomarkers for predicting immune infiltration in endometriosis. aug: au: Xie, Chengmao Lu, Chang Liu, Yong Liu, Zhaohui affil: Department of Gynecology, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, 100026, Beijing, China sug: subj: Endometriosis Endometriosis Diagnosis Female Endometrium Metabolism Female ab: Objective: To determine the potential diagnostic markers and extent of immune cell infiltration in endometriosis (EMS).Methods: Two published profiles (GSE7305 and GSE25628 datasets) were downloaded, and the candidate biomarkers were identified by support vector machine recursive feature elimination analysis and a Lasso regression model. 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. CIBERSORT was used to estimate the composition pattern of immune cell components in EMS.Results: One hundred and fifty-three differential expression genes (DEGs) were identified between EMS and endometrial with 83 upregulated and 51 downregulated genes. 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 could be regarded as diagnostic markers of EMS and may provide a new direction for the study of EMS pathogenesis in the future. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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