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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 eliminatio...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9118874/ https://www.ncbi.nlm.nih.gov/pubmed/35585523 http://dx.doi.org/10.1186/s12905-022-01765-3 |
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author | Xie, Chengmao Lu, Chang Liu, Yong Liu, Zhaohui |
author_facet | Xie, Chengmao Lu, Chang Liu, Yong Liu, Zhaohui |
author_sort | Xie, Chengmao |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9118874 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-91188742022-05-20 Diagnostic gene biomarkers for predicting immune infiltration in endometriosis Xie, Chengmao Lu, Chang Liu, Yong Liu, Zhaohui BMC Womens Health Research 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. BioMed Central 2022-05-18 /pmc/articles/PMC9118874/ /pubmed/35585523 http://dx.doi.org/10.1186/s12905-022-01765-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Xie, Chengmao Lu, Chang Liu, Yong Liu, Zhaohui Diagnostic gene biomarkers for predicting immune infiltration in endometriosis |
title | Diagnostic gene biomarkers for predicting immune infiltration in endometriosis |
title_full | Diagnostic gene biomarkers for predicting immune infiltration in endometriosis |
title_fullStr | Diagnostic gene biomarkers for predicting immune infiltration in endometriosis |
title_full_unstemmed | Diagnostic gene biomarkers for predicting immune infiltration in endometriosis |
title_short | Diagnostic gene biomarkers for predicting immune infiltration in endometriosis |
title_sort | diagnostic gene biomarkers for predicting immune infiltration in endometriosis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9118874/ https://www.ncbi.nlm.nih.gov/pubmed/35585523 http://dx.doi.org/10.1186/s12905-022-01765-3 |
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