{"paper_id":"2e00f4ed-7248-4688-ae9f-be66d65222e4","body_text":"Abstract\nPurpose\nEndometriosis (EMS) is a relatively common gynecological disorder and almost fifty percent of women with EMS suffer from infertility. There are few treatment options for endometriosis, and often recurrences occur following surgery and medication. We aimed to identify potential diagnostic biomarkers for EMS to improve its diagnostic efficiency.\nMethods\nDifferential analysis was utilized to choose EMS-associated abnormal miRNAs (DEMIs) and mRNAs (DEMs). ImmuneAI analysis was to evaluate the levels of immune cells in EMS. Next, the weighted gene co-expression network analysis (WGCNA) was utilized to identify the co-expression modules. Random forest and SVM analyses were used to filter the candidate biomarkers and construct the diagnostic model. qRT-PCR was used to test the expression level of the biomarkers.\nResults\nBased on the different analyses, we obtained 32 DEMIs and 516 DEMs and selected 9 abnormal immune cells whose abundance is abnormal in EMS. Next, we identified five co-expression modules associated with these abnormal immune cells. Then, 176 candidate genes which are both miRNA targets and associated with immune cells and aberrantly expressed in EMS were filtered. Subsequently, random forest analysis selected 11 genes as the diagnostic biomarkers and constructed a diagnostic model by SVM. Finally, we demonstrated that 8 of the 11 genes aberrantly expressed and with better diagnostic efficiency in EMS.\nConclusions\nIn total, we identified 11 crucial genes regulated by 8 miRNAs that could serve as promising diagnostic biomarkers for EMS, potentially enhancing disease diagnosis with novel factors.\nAccess this article\nWe’re sorry, something doesn't seem to be working properly.\nPlease try refreshing the page. If that doesn't work, please contact support so we can address the problem.\nSimilar content being viewed by others\nData availability\nData on the expression of miRNA and mRNA in patients with EMS and their clinical information were obtained from the GEO database under the accession codes GSE153813, GSE105765, GSE51981, and GSE134056 (https://www.ncbi.nlm.nih.gov/geo/).\nReferences\nSachedina A, Todd N. Dysmenorrhea, endometriosis and chronic pelvic pain in adolescents. J Clin Res Pediatr Endocrinol. 2020;12(Suppl 1):7–17.\nBegum MIA, Chuan L, Hong ST, Chae HS. 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FEBS Lett. 2021;595(9):1275–88.\nAcknowledgements\nWe are grateful to the peer reviewers and editors for their valuable feedback and recommendations.\nAuthor information\nAuthors and Affiliations\nCorresponding author\nEthics declarations\nEthics approval\nEthical approval was obtained from the Ethics Committee of the Suzhou Ninth People’s Hospital (KYLW2024-035–01).\nConflict of interest\nThe authors declare no competing interests.\nAdditional information\nPublisher's Note\nSpringer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.\nSupplementary Information\nBelow is the link to the electronic supplementary material.\nRights and permissions\nSpringer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.\nAbout this article\nCite this article\nTu, Q., Zhao, R. & Lu, N. Evaluation of the diagnostic utility of immune microenvironment-related biomarkers in endometriosis using multidimensional transcriptomic data. J Assist Reprod Genet 41, 3213–3223 (2024). https://doi.org/10.1007/s10815-024-03261-z\nReceived:\nAccepted:\nPublished:\nVersion of record:\nIssue date:\nDOI: https://doi.org/10.1007/s10815-024-03261-z","source_license":"CC0","license_restricted":false}