Identification of Key miRNAs in Endometriosis

Francesca Blandino, Blandino F, Saviana Antonella Barbati, Luca Forlani, Forlani L, Giulia Coppola, Coppola G, Giuseppe Coppola, Meschino N, Noemi Meschino, Ilde Cecchinelli, Cecchinelli I, Mazzuca AC, Antonietta Cosco Mazzuca, Veltri V, Valentina Veltri, Giannico R, Riccardo Giannico, Graziella Calugi
MicroRNA (Shariqah, United Arab Emirates) · 2024 · vol. 14(2) , pp. 170–175 · doi:10.2174/0122115366333556241014115206 · PMID:39473106 · W4403846273
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⚙ AI-generated summary by claude@2026-06, 2026-06-08 ⓘ

This study identified a specific microRNA expression profile in endometriosis patients, suggesting a molecular signature for potential diagnostic screening tools.

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⚙ AI-generated deep summary by claude@2026-07, 2026-07-09 · read from full text ⓘ

This paper studied whether microRNAs (miRNAs) can serve as key markers for endometriosis by comparing miRNA expression profiles between two patient cohorts: 14 with endometriosis and 15 with benign gynecological lesions without endometriosis, using custom microRNA sequencing pipeline methods. The authors identified a distinct miRNA expression profile that clustered disease molecular signatures in endometriosis, indicating specific miRNA patterns associated with the condition’s pathogenesis. A stated limitation is that the findings require further validation and additional exploration to support development of diagnostic tools and potential machine-learning prediction. This paper is centrally about endometriosis — it identifies endometriosis-specific miRNA expression signatures as potential biomarker markers of disease pathogenesis.

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Abstract

INTRODUCTION: Endometriosis, a prevalent gynecological disorder characterized by the presence of endometrial-like tissue outside the uterus, poses significant challenges in diagnosis and management due to its unclear pathogenesis and lack of specific biomarkers. OBJECTIVE: This study investigates the potential use of microRNAs (miRNAs) as key markers in endometriosis by studying two cohorts of patients (14 patients diagnosed with endometriosis and 15 patients with gynecological benign lesions, different from endometriosis). METHODS: MicroRNA sequencing analysis was tested within data management by a custom pipeline designed by Eurofins Genoma Group. RESULTS: We identified a specific miRNA expression profile associated with endometriosis to feature specific disease molecular clusters to further elucidate the underlying mechanisms driving endometriosis pathogenesis. Data from the present study suggest a specific miRNA scar for endometriosis compared to other gynecological diseases to develop screening tools in early diagnosis and to ameliorate the management of the disease itself. CONCLUSION: This study lays the foundation for the identification of key miRNAs involved in the disease pathogenesis to unveil the molecular signatures in the complex scenario of endometriosis. Further validation and exploration of these findings are needed to develop tools to improve molecular diagnosis and to create a machine-learning prediction algorithm in the future.
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Abstract

Introduction: Endometriosis, a prevalent gynecological disorder characterized by the presence of endometrial-like tissue outside the uterus, poses significant challenges in diagnosis and management due to its unclear pathogenesis and lack of specific biomarkers.

Objective

This study investigates the potential use of microRNAs (miRNAs) as key markers in endometriosis by studying two cohorts of patients (14 patients diagnosed with endometriosis and 15 patients with gynecological benign lesions, different from endometriosis).

Methods

MicroRNA sequencing analysis was tested within data management by a custom pipeline designed by Eurofins Genoma Group.

Results

We identified a specific miRNA expression profile associated with endometriosis to feature specific disease molecular clusters to further elucidate the underlying mechanisms driving endometriosis pathogenesis. Data from the present study suggest a specific miRNA scar for endometriosis compared to other gynecological diseases to develop screening tools in early diagnosis and to ameliorate the management of the disease itself.

Conclusion

This study lays the foundation for the identification of key miRNAs involved in the disease pathogenesis to unveil the molecular signatures in the complex scenario of endometriosis. Further validation and exploration of these findings are needed to develop tools to improve molecular diagnosis and to create a machine-learning prediction algorithm in the future.

Keywords

Endometriosis, miRNA, microRNA, gynecology, women, endometrium. [http://dx.doi.org/10.7759/cureus.3361] [PMID: 30510871] [http://dx.doi.org/10.3389/fendo.2022.1020827] [PMID: 36387918] [http://dx.doi.org/10.3390/ijms221910554] [PMID: 34638893] [http://dx.doi.org/10.3390/ijms19020599] [http://dx.doi.org/10.1093/hropen/hoac009] [PMID: 35350465] [http://dx.doi.org/10.1016/j.fertnstert.2018.10.013] [PMID: 30527836] [http://dx.doi.org/10.1016/j.bpobgyn.2018.04.001] [PMID: 29778458] [http://dx.doi.org/10.2741/4431] [PMID: 27100482] [http://dx.doi.org/10.1093/aje/kwx272] [PMID: 28992341] [http://dx.doi.org/10.4172/1948-5956.1000359] [PMID: 26819681] [http://dx.doi.org/10.1111/j.1447-0756.2012.01860.x] [http://dx.doi.org/10.3390/pharmaceutics15061630] [PMID: 37376078] [http://dx.doi.org/10.3390/jcm11030612] [PMID: 35160066] [http://dx.doi.org/10.1002/jcp.27486] [PMID: 30471116] [http://dx.doi.org/10.1016/bs.acc.2018.12.002] [http://dx.doi.org/10.5603/GP.a2022.0078] [PMID: 36165640] [http://dx.doi.org/10.1186/s13054-021-03775-3] [PMID: 34641966] [http://dx.doi.org/10.1177/03000605221147183] [PMID: 36597409] [http://dx.doi.org/10.1186/s12958-017-0319-5] [PMID: 29357938]

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Condition tags

endometriosis

MeSH descriptors

Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis

Citation neighborhood

Papers in the corpus that this work cites (lower rings, blue) and that cite this one (upper rings, green). Dot size scales with the paper's in-corpus citation count — bigger dot = more influential within the endo/adeno field. Click a dot to open that paper. [ expand to 2 hops ] — adds papers reached through this work's immediate citers/citees. Heavier; up to 60 extra dots.

References (19)

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