Transcriptomic-based analysis of endometrial tissues from adenomyosis patients reveals significant inflammation biomarkers: A bioinformatics study

Marni Sianturi, M.H.R. Sianturi, Alauddin Syaifulanwar, Darmawi Darmawi, Wirawan Adikusuma, Lalu Muhammad Irham, Muhammad Yusuf, Renato Fani, Rifia Tiara Fani, Febriani Febriani
International journal of reproductive biomedicine · 2025 · vol. 23(5) , pp. 425–436 · doi:10.18502/ijrm.v23i5.19265 · PMID:40989079 · PMC12413538 · W4413096171
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⚙ AI-generated summary by claude@2026-06, 2026-06-08 ⓘ

This bioinformatics study identified significant inflammation biomarkers, including TNF-α-induced protein 6 and matrix metalloproteinase 7, by comparing gene expression profiles in adenomyosis endometrial tissues and healthy controls.

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⚙ AI-generated deep summary by claude@2026-06, 2026-06-09 ⓘ

This bioinformatics study analyzed transcriptomic data from endometrial tissues obtained from adenomyosis patients to identify inflammatory biomarkers. Using computational differential expression and pathway/biomarker-focused analyses, the authors reported significant inflammation-associated molecular signatures as distinguishing features in the adenomyosis endometrium. A major limitation is that the work is based on transcriptomic analysis rather than direct experimental validation of the biomarkers’ functional roles or causal relevance. This paper is centrally about adenomyosis— it focuses on transcriptomic inflammation biomarkers in endometrial tissues from adenomyosis patients.

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Abstract

Background: Adenomyosis is a gynecological disorder characterized by the presence of endometrial tissue within the myometrium, with incidence rates ranging from 10–65% among women of reproductive age. Objective: This study utilized transcriptomic analysis to identify significant biomarkers associated with inflammation in endometrial tissue from patients with adenomyosis. Materials and Methods: In this bioinformatics study, we utilized publicly available transcriptomic datasets. The research involved the systematic analysis of RNA sequencing data obtained from the NCBI-GEO database. Using a high-throughput RNA sequencing database from GSE190580 and GSE157718, we compared gene expression profiles between endometrium tissues of adenomyosis patients and healthy controls. Subsequently, pathways implicated in adenomyosis were analyzed through the Kyoto Encyclopedia of Genes and Genomes and gene ontology. Results: Pathway analysis revealed the aberration of inflammation-related pathways, including tumor necrosis factor (TNF) and Ras-related protein 1 signaling. Furthermore, gene ontology analysis uncovered key biological processes, such as macrophage differentiation and extracellular matrix organization, which are central to the inflammatory response in adenomyosis. Candidate biomarkers, including transmembrane protein kinases, were identified as potential therapeutic targets. We found the top 5 genes that play a role in inflammation in adenomyosis, including TNF-α-induced protein 6, matrix metalloproteinase 7, TNF-α-induced protein 3, leukemia inhibitory factor, and serum and glucocorticoid-regulated kinase 1. Statistical significance was determined with adjusted p < 0.05. Conclusion: These findings enhance our understanding of the molecular mechanisms of adenomyosis and propose novel biomarkers for more effective diagnostic and therapeutic strategies.

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adenomyosis

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