{"paper_id":"0b4963d4-90c1-4868-a06e-bc08b4866692","body_text":"170 | P a g e  \n \nCell. Mol. Biomed. Rep. (ISSN: 2823-2550)                                                                                              2026, 6(2): 170-194 \nhttps://doi.org/10.55705/cmbr.2026.550859.1337   \n1Department of Biology, Yazd University, Yazd, Iran  \n2Department of Obstetrics and Gynecology, School of Medicine, Shahid Sadoughi University of Medical Sciences, Yazd, Iran  \n3Research and Clinical Center for Infertility, Yazd Reproductive Sciences Institute, Shahid Sadoughi University of Medical Sci ences, Yazd, \nIran \n*Corresponding Author: Mehri Khatami (m.khatami@yazd.ac.ir) \n \n \n \nDifferential expression of miR-98-5p and DICER1 in eutopic \nversus ectopic endometrium: a diagnostic biomarker \nsignature for endometriosis \n \nMehri Khatami1,*\n , Mahdieh Azizi Panah1, Mohammad Mehdi Heidari1, Mojgan Hajisafari Tafti2, 3 \n \n  \n  \nA B S T R A C T \nEndometriosis is a complex gynecological disorder characterized by \nthe presence of endometrial -like tissue outside the uterus, whose \npathogenesis remains incompletely unde rstood, with emerging \nevidence implicating dysregulated microRNAs (miRNAs) and their \nbiogenesis pathways. This case -control study aimed to investigate \nthe relationship between the expression of miR-98-5p and its \nprocessing enzyme DICER1 in matched ectopic and eutopic \nendometrial tissues from an Iranian population, a cohort of \nparticular interest due to potential population -specific factors and \none not previously studied for this molecular axis. Matched ectopic \nand eutopic endometrial tissues were collected from 30 patients \nwith surgically confirmed endometriosis and compared with \nendometrial tissues from 35 age -matched controls. Total RNA was \nextracted, and the expression levels of miR-98-5p and DICER1 were \nquantified using reverse transcription -quantitative PCR (qRT-PCR), \ncomplemented by in silico analyses to validate associated molecular \npathways. The results demonstrated a significant downregulation of \nboth miR-98-5p and DICER1 (P< 0.001) in ectopic tissues compared \nwith eutopic controls, with a strong pos itive correlation between \nthem (r = 0.76, P< 0.001). This co -downregulation suggests \nimpaired DICER1-mediated miRNA processing contributes to miR-\n98-5p depletion in endometriotic lesions. The expression profile \nexhibited strong diagnostic potential, with miR-98-5p yielding an \nAUC of 0.89 in ROC curve analysis, and both molecules showed a \nsignificant inverse correlation with disease severity ( P< 0.05). In \nconclusion, these findings provide novel evidence of a disrupted \nDICER1/miR-98-5p axis in a distinct gen etic background, revealing \nits role in post -transcriptional dysregulation and underscoring its \npromise as a tissue -based diagnostic and prognostic biomarker for \nendometriosis. \nArticle info \nReceived: 03 Oct 2025 \nRevised: 08 Jan 2026 \nAccepted: 27 May 2026 \n \n \n \n \n \n \nUse your device to scan and \nread the article online \n \n \n \n \n \n \n \n \nKeywords:  \nBiomarker, DICER1, \nEndometriosis, Gene \nexpression, MiR-98-5p, \nmiRNA \n1. Introduction \nEndometriosis is a chronic, estrogen -\ndependent gynecological disorder defined by \nthe prese nce of endometrial -like tissue \noutside the uterine cavity. Affecting \napproximately 10% of women of reproductive \nage globally, it represents a significant cause \nof morbidity and reduced quality of life [1]. \nAlthough histologically benign, endometriosis \nexhibits cancer -like characteristics such as \nprogressive, invasive growth, a high \nrecurrence rate, and metastatic potential [2]. \nThe clinical presentation commonly includes \nchronic pelvic pain, dysmenorrhea, \ndyspareunia, and infertility, which affects \nnearly 30–50% of women with the conditi on \n[3]. The pathogenesis of endometriosis \nremains multifactorial and incompletely \nelucidated. While Sampson’s theory of \nretrograde me nstruation remains the most \nOriginal Article \n\nCell. Mol. Biomed. Rep.                                                                                                                               2026, 6(2): 170-194 \n171 | P a g e  \n \nwidely accepted model, it alone cannot \nexplain all cases. Recent findings emphasize \nthe significance of epigenetic changes, such as \nDNA methylation and miRNA dysregulation, \nwhich affect gene expression in ectopic \nlesions [4]. Recent advances in multi -omics \ntechnologies, encompassing genomics, \ntranscriptomics, epigenomics, and \nproteomics, have significantly expanded our \nunderstanding of the molecular landscape of \nendometriosis [5]. These approaches have \nidentified n umerous genes and pathways \nassociated with the disease, highlighting \nsignificant dysregulation in critical biological \nprocesses, including hormone response, \ninflammation, cell adhesion, and apoptosis [6].  \nMicroRNAs (miRNAs) are small non-coding \nRNA molecules, approximately 22 nucleotides \nin length that  function as crucial post -\ntranscriptional regulators of gene expression \n[7, 8]. Through imperfect base -pairing with \ntarget mRNAs, miRNAs typically induce \ntranslational repression or mRNA \ndegradation, thereby fine -tuning fundamental \ncellular processes including proliferation, \ndifferentiation, apoptosis, and inf lammatory \nresponses. Non -coding RNAs, particularly \nmicroRNAs (e.g., miR -451, miR -141-3p) and \nlong non-coding RNAs (e.g., H19, MEG3), serve \nas critical post -transcriptional regulators, \ninfluencing mRNA stability and translation. \nRecent research has discover ed more than 50 \ndifferentially expressed microRNAs in ectopic \nand eutopic endometrial tissues from \nindividuals diagnosed with endometriosis, \nrevealing their central role in the \npathogenesis of the disease [9]. Functional in \nvitro studies reveal that dysregulation of \nspecific miRNAs, specifically the \ndownregulation of the miR-200 family and the \nupregulation of miR -21-5p, facilitates \nepithelial-mesenchymal transition (EMT), \nenhances cellular migration and invasion, and \nprovides resistance to apoptosis [10]. Due to \ntheir stability in biofluids, circulating miRNAs \nhave attracte d considerable attention as \npotential non -invasive biomarkers. Recent \ninvestigations utilizing high -throughput \nmiRNA profiling of serum and plasma have \nidentified multi -miRNA signatures with \npromising diagnostic accuracy for \nendometriosis, including combin ations such \nas miR -125b-5p, miR -28-5p, and let -7b-5p \n[11]. Bioinformatic analyses suggest that \ndysregulated miRNAs target crucial genes \ninvolved in endometriosis -associated \npathways, including estrogen receptor (ER) \nand progesterone receptor (PR ) signaling, \nTGF-β-mediated cell invasion, and \nextracellular matrix remodeling [12]. Among \nthese miRNAs, miR-98-5p has emerged as a \ncandidate of particular interest due to its \nestablished role as a key regulator of \ninflammatory and fibrotic pathways, core \nprocesses in endometriosis establishment and \nmaintenance. Initially identified in cancer, \nmiR-98-5p acts as a key modulator of core \noncogenic pathways, including PI3K/AKT \n(pro-survival signaling), Wnt/β -catenin \n(proliferation and stemness), and the \nepithelial-to-mesenchymal transition (EMT) \n(invasion and metastasis) [13]. Notably, these \nsame pathways are co -opted in the \npathogenesis of endometriosis, a benign but \nlocally invasive disorder characterized by the \nsurvival, proliferation, and invasive potential \nof ectopic endometrial tissue. Recent evidence \nhas begun to shed light on its involvement in \nendometriosis, suggesting a conserved role \nfor miR-98-5p in regulating the cellular \nprocesses that drive both malignant and non -\nmalignant tissue invasion. Also, it was \nconfirmed that miR-98-5p acts as a powerful \ntumor suppressor in multiple cancer types, \nincluding nasopharyngeal carcinoma, \nendometrial cancer, and ovarian cancer, \nwhere it is frequently downregulated [14]. \nMiR-98-5p is an evolutionarily conserved,  \nendogenous microRNA located on the X \nchromosome (Xp11.22) and is a significant \nmember of the let -7 tumor suppressor family. \nThe mature sequence (5′ -\nugagguaguaaguuguauuguu-3′) contains a \nhighly conserved “seed region” (nucleotides \n2–8) that is essential for target recognition \nand binding specificity ( Figure 1). Structural \nanalyses sug gest that its secondary structure \nand sequence conservation enable it to \nregulate a broad network of mRNAs involved \nin cell cycle, invasion, and differentiation [13]. \nNotably, in gynecological conditions such as \nendometriosis, miR-98-5p is significantly \nunderexpressed and is thought to play a role \nin disease progression due to the loss of its \nregulatory function. Its ability to modulate key \npathways, including TGF -β, Wnt/β -catenin, \nand STAT3 signaling, depending on cellular \n\n2026, 6(2): 170-194                                                                                                                               Cell. Mol. Biomed. Rep. \n172 | P a g e  \n \ncontext, further supports its role as a critical \nepigenetic regulator in both cancer and \nbenign proliferative disorders [10].  \n \n \n \nFig. 1. The precursor and mature sequence of MiR-98-5p (miRVim: Human miRNA structure \ndatabase) features a highly conserved \"seed region\" (nucleotides 2 –8) that is crucial for target \nrecognition and binding specificity. \nThe biogenesis of miR-98-5p is regulated \nby several cellular factors, including \ntranscriptional controls, epigenetic \nmodifications, and core microprocessor \ncomponents. Key to its maturation is the \nDrosha-DGCR8 complex located in the nucleus \nand the DICER1 enzyme found in the \ncytoplasm. Any mutations or dysregulation of \nthese complexes can significantly impair the \nconversion of pre -miR-98 into its mature, \nfunctional form [15]. The DICER1 protein \n(UniProt: Q9UPY3) serves as a crucial \nribonuclease III enzyme that is vital for \nmiRNA biogenesis. In terms of structure, it \npossesses an N -terminal DEXH -box RNA \nhelicase domain that aids in the ATP -\ndependent unwinding of RNA substrates, \nalong with a C -terminal RNase III domain that \nis responsible for cleaving pre -miRNAs into \nmature duplexes. Recent multi-omics research \nhas shown that DICER1 expression is \nfrequently downregulated in various cancers, \nleading to a widespread decrease in mature \nmiRNAs. This phenomenon is particularly \nevident in epithelial ovarian cancer (EOC), \nwhere diminis hed levels of DICER1 are \nassociated with advanced tumor stages, \nmetastasis, and unfavorable prognosis [16]. \nThese findings emphasize the essential \nfunction of miRNA biogenesis machinery in \nthe development of cancer a nd point out \nDICER1 as not only a biomarker but also a \npromising therapeutic target for reinstating \ntumor-suppressive miRNA activity. Although \nthe roles of microRNA dysregulation and \ncompromised miRNA biogenesis in \nendometriosis are well -established, the \nprecise roles of miR-98-5p and its regulatory \ninteraction with DICER1 in both ectopic and \neutopic endometrial tissues are still \ninadequately defined. To fill this knowledge \nvoid, we conducted a comprehensive \nbioinformatics and experimental investigation \nutilizing gene expression profiles from public \n\nCell. Mol. Biomed. Rep.                                                                                                                               2026, 6(2): 170-194 \n173 | P a g e  \n \ndatabases in conjunction with original \nmolecular data from a cohort of Iranian \npatients. The rationale for investigating the \ninteraction between miR-98-5p and DICER1 in \nendometriosis extends beyond their \nconcurrent dysregulation. While the \ndownregulation of miR-98-5p aligns with the \ndisease's pro -proliferative and invasive \nphenotype, the parallel decrease in its \nessential processing enzyme, DICER1, \nsuggests a potential mechanistic link. We \ntherefore explicitly hyp othesize that the \nimpaired expression and function of DICER1 is \na direct molecular cause of the pathological \ndepletion of mature miR-98-5p in \nendometriotic lesions. This disruption in the \nmicroRNA biogenesis pathway represents a \nnovel pathogenic mechanism in \nendometriosis, potentially explaining the \nsustained imbalance in key downstream \nsignaling networks. Consequently, this study \naims not merely to document this correlation \nbut to functionally test this hypothesis, \npositioning the DICER1/miR-98-5p axis as a \ncentral regulatory node and a potential \ntherapeutic target. \n2. Materials and methods  \n2.1. Ethical considerations \n Each participant filled out a \ncomprehensive, structured questionnaire \ndesigned to collect extensive epidemiological \nand clinical informatio n. This instrument \ncollected data on reproductive history (parity, \ngravidity, and contraceptive use), menstrual \ncharacteristics (cycle length, dysmenorrhea \nseverity, and bleeding patterns), medical and \nsurgical history, family history of \nendometriosis or o ther gynecological \ndisorders, and lifestyle factors (including \nphysical activity, dietary habits, and \nenvironmental exposures). In accordance with \ncurrent endometriosis research frameworks, \nthe questionnaire incorporated validated \ninstruments for pain mapp ing and symptom \ncharacterization, including specific metrics for \ndyschezia, dysuria, dyspareunia, and cyclical \nbowel or urinary symptoms. Furthermore, \ninformation regarding previous surgical \nreports, histopathological confirmations, and \nimaging findings wa s systematically recorded \nto enhance phenotypic stratification.  \n2.2. Patient’s criteria   \nThis case -control study enrolled 30 \npatients with endometriosis and 35 control \nparticipants between 2020 and 2023 (Table \n1). Participants were women aged 18 –45 \nyears with a body mass index (BMI) ≤30 \nkg/m², non -pregnant, non -lactating, \npremenopausal, and without chronic diet -\nrelated or endocrine disorders including \ndiabetes, cardiovascular disease, renal \ndysfunction, or reproductive tract \nmalignancies. Endometriosis di agnosis was \nconfirmed surgically and histologically \naccording to the Enzian classification or ASRM \nstaging system at Shahid Sadoughi Hospital, \nYazd. Cases consisted of women with visual or \nhistopathologically proven endometriosis, \nwhile controls were indiv iduals without \nendometriosis undergoing \nlaparoscopy/laparotomy for other benign \ngynecological indications (e.g., benign ovarian \ncysts, infertility evaluation, or elective tubal \nligation). Controls had no history of \nendometriosis symptoms, chronic pelvic pa in, \nor previous abdominal surgery and were \nmatched to cases by age (±3 years) to \nminimize potential confounding effects. All \nparticipants exhibited regular menstrual \ncycles (24–38 days) for at least three months \nprior to enrollment. Exclusion criteria \nencompassed polycystic ovary syndrome \n(PCOS), chronic anovulation, hydrosalpinx, \nendocrinopathies, dyslipidemia, autoimmune \nconditions (e.g., systemic lupus \nerythematosus), HIV or active infections, and \nrecent (3 -month) use of hormonal therapy, \nanti-inflammatory drugs, tobacco, alcohol, or \nrecreational substances. The diagnoses and \neligibility assessments were verified by \nboard-certified obstetrician -gynecologists. All \ntissue collections were performed during \nscheduled laparoscopic procedures for \nendometriosis diagnosis and treatment. \nEctopic tissues were precisely excised from \nvisually confirmed endometriotic lesions, \nwhile matched eutopic endometrial samples \nwere simultaneously obtained from the \nuterine cavity using gentle curettage to ensure \nhistological viab ility. All tissue specimens \nwere immediately snap -frozen in liquid \nnitrogen and stored at -80°C until RNA \nextraction to preserve RNA integrity.  \n\n2026, 6(2): 170-194                                                                                                                               Cell. Mol. Biomed. Rep. \n174 | P a g e  \n \nTable 1. Overview of the characteristics of participants diagnosed with endo metriosis and the control \ngroup \nCharacteristic Endometriosis Group (n=30) Control Group (n=35) p-value \nDemographics    \nAge (years), mean ± SD 32.5 ± 5.1 31.8 ± 4.7 0.55 \nBMI (kg/m²), mean ± SD 24.1 ± 3.8 23.7 ± 4.2 0.68 \nClinical History    \nParity, median [IQR] 1 [0, 2] 1 [1, 2] 0.42 \nAge at Menarche (years), mean ± SD 12.4 ± 1.3 12.6 ± 1.1 0.48 \nMenstrual Cycle Length (days), mean ± SD 28.5 ± 2.5 28.8 ± 2.1 0.58 \nPain Symptoms (VAS 0-10), mean ± SD    \nDysmenorrhea (Menstrual pain) 8.1 ± 1.5 5.2 ± 2.3 <0.001 \nDyspareunia (Pain during intercourse) 6.4 ± 2.8 1.5 ± 1.9 <0.001 \nChronic Pelvic Pain 7.2 ± 2.1 1.8 ± 1.7 <0.001 \nrASRM Stage, n (%)    \nStage I-II (Minimal-Mild) 12 (40.0%) — — \nStage III-IV (Moderate-Severe) 18 (60.0%) — — \n \n2.3. Total RNA extraction and cDNA \nsynthesis \nFresh ectopic and eutopic endometrial \ntissue specimens were collected during \nsurgery, immediately snap -frozen in liquid \nnitrogen, and stored at −80°C to preserve RNA \nintegrity. Total RNA was extracted from 50 –\n100 mg of tissue using TRIzol™ reagent \n(Invitrogen, USA),  following the \nmanufacturer's protocol. RNA concentration \nand purity were assessed \nspectrophotometrically (NanoDrop™ 2000, \nThermo Fisher Scientific, USA), with \nacceptable 260/280 ratios ranging from 1.8 to \n2.1. RNA integrity was further verified using \nan A gilent 2100 Bioanalyzer RNA Nano Chip, \nwith all samples having an RNA Integrity \nNumber (RIN) ≥7. Complementary DNA \n(cDNA) was synthesized from 1 µg of total \nRNA using the PrimeScript™ RT reagent Kit \n(Takara Bio, Japan) with specific stem -loop \nprimers for miR-98-5p and oligo(dT) primers \nfor DICER1 mRNA, enabling specific detection \nof mature miRNA and mRNA transcripts. \nReverse transcription was performed in a 20 \nµL reaction volume using a ProFlex™ PCR \nSystem (Applied Biosystems, USA) under the \nfollowing condi tions: 37°C for 60 min, \nfollowed by heat inactivation at 85°C for 5 \nmin, and hold at 4°C. cDNA  products were \nstored at −20°C until subsequent qPCR \nanalysis.  \n2.4. Microarray data analysis \nTo identify differentially expressed genes \n(DEGs) associated with endometriosis, we \nintegrated and reanalyzed five publicly \navailable transcriptomic datasets from  the \nGene Expression Omnibus (GEO). All datasets \nwere generated using the Affymetrix HG-U133 \nPlus 2.0 platform (GPL570), ensuring \ntechnical consistency. The following datasets \nwere included: GSE25628: Transcriptional \nprofiling of endometrial biopsies (16 e utopic \nendometrial samples from patients, 7 ectopic \nlesions, and 6 eutopic endometrial samples \nfrom healthy controls; 29 unique individuals), \nGSE23339: Gene expression in endometriosis \n(10 eutopic endometrial samples from \npatients and 9 from controls; 19 u nique \nindividuals), GSE7846: Differentially \nexpressed genes in human endometrial \nendothelial cells (HEECs) from eutopic \nendometrium (6 patients and 4 controls; 10 \nunique individuals), GSE6364: Endometrial \nprofiling highlighting progesterone resistance \n(21 eutopic endometrial samples from \nendometriosis patients and 16 eutopic \nendometrial samples from healthy controls; \n37 unique individuals), and GSE5108: \nGenome-wide comparison of 10 eutopic \nendometrial samples and 12 ectopic lesion \nsamples from the same 10 i ndividuals (10 \npaired samples, plus 2 additional ectopic \nlesions). In total, the integrated cohort \ncomprised 100 samples (69 endometriosis \ncases, 31 controls), providing robust \nstatistical power for differential expression \nanalysis. The integrated cohort c omprised a \ntotal of 100 individual tissue samples. To \nensure statistical independence and avoid \npseudoreplication, samples were treated as \nbelonging to two primary biological groups \nfor the initial differential expression analysis: \n\"Disease\" and \"Control\".  The \"Disease\" group \n(n=69 samples) included all ectopic lesions \nand all eutopic endometrial samples obtained \n\nCell. Mol. Biomed. Rep.                                                                                                                               2026, 6(2): 170-194 \n175 | P a g e  \n \nfrom patients diagnosed with endometriosis. \nThe \"Control\" group (n=31 samples) consisted \nexclusively of eutopic endometrial samples \nfrom individua ls without surgical or \nhistological evidence of endometriosis. Raw \nCEL files were processed using the oligo R \npackage for background correction, \nnormalization (RMA algorithm), and probe \nsummarization. Differential expression \nbetween the consolidated Disease and Control \ngroups was determined using the limma \npackage with adjusted p-values (Benjamini -\nHochberg FDR < 0.05) and |log₂ fold change| > \n1.  \n2.5. Differential Gene Expression (DGE) \nAnalysis  \nDifferential gene expression analysis \nbetween ectopic and euto pic endometrial \nsamples was performed using GEO2R, an \ninteractive web tool for comparing GEO \ndatasets. We conducted comparative analyses \nacross both endometriosis and control groups \nto identify tissue -specific and disease -specific \ntranscriptional changes. Visualization of \nexpression patterns was achieved using the \nggplot2 and pheatmap packages in R, \ngenerating volcano plots and hierarchical \nclustering heatmaps to illustrate global \ntranscriptomic differences. Genes with an \nadjusted P-value <0.05 (Benjamini –Hochberg \ncorrection) and |log ₂ fold change| ≥ 1 were \nconsidered differentially expressed. To \nprioritize biologically relevant changes, we \napplied a stricter threshold of |log ₂FC| > 2 for \ndownstream functional enrichment analyses.  \n2.6. Gene Ontology (GO) function and KEGG \npathway assessment \nTo elucidate the biological significance of \nthe identified differentially expressed genes \n(DEGs) and miRNAs, we performed \ncomprehensive functional enrichment \nanalysis using Gene Ontology (GO) and the \nKyoto Encyclopedia of  Genes and Genomes \n(KEGG) pathway database. Analyses were \nexecuted with the clusterProfiler package \n(v4.0) in R, leveraging annotations from the \nUCSC Genome Browser to ensure up -to-date \ngenomic context.  \nGene Ontology (GO) analysis provides a \nframework for  defining gene functions and \ninteractions related to various biological \nevents, biological processes (Identifying \noverarching physiological pathways), cellular \ncomponents (Determining subcellular \nlocalization), and molecular functions \n(Defining biochemical  activities). KEGG \npathway analysis revealed involvement in key \nsignaling cascades, including Wnt, TGF -β, and \nJAK-STAT pathways, which are critically \nimplicated in endometriosis pathogenesis. \nEnrichment significance was assessed using a \nfalse discovery rate (FDR)-adjusted P-values < \n0.05, with additional filtering for terms \ncontaining ≥5 genes and enrichment factors > \n1.5 to ensure biological relevance.  \n2.7. Protein –Protein Interactions (PPI) \nnetwork analysis  \nTo systematically evaluate the functional \nrelationships between DICER1 and the \nidentified differentially expressed genes \n(DEGs) in Homo sapiens, we constructed and \nanalyzed protein -protein interaction (PPI) \nnetworks using multiple complementary \ndatabases. The STRING database (v12.0) and \nSIGNOR were employed to retrieve \nexperimentally validated and predicted \ninteractions, applying a high -confidence score \nthreshold of > 0.9 to ensure biological \nrelevance. \nTo enhance the robustness and coverage of \nthe network, we integrated data from \nFunCoup 4.0 and BioGRID (v4.4), which \nprovide e xtensive context -specific functional \nassociations, including genetic, physical, and \nregulatory interactions. The combined \nnetwork was visualized and topologically \nanalyzed using Cytoscape (v3.10.0), with the \nNDEx platform enabling public sharing, \nrepository integration, and collaborative \nexploration of the network models. Key \nnetwork properties, such as degree centrality \nand clustering coefficients, were calculated \nusing Cytoscape plugins (e.g., CytoHubba, \nMCODE) to identify hub genes and \nfunctionally significant modules.  \n2.8. MiRNA target prediction and pathway \nenrichment Analysis  \nTo systematically identify miR-98-5p target \nmRNAs and evaluate their functional roles, we \nintegrated predictions from multiple \n\n2026, 6(2): 170-194                                                                                                                               Cell. Mol. Biomed. Rep. \n176 | P a g e  \n \nbioinformatic tools specializing in miRNA -\nmRNA int eractions. These included \nTargetScan (v8.0), miRDB (v6.0), miRWalk \n(v3.0), DIANA -microT-CDS (v5.0), and \nmiRanda (v3.3a), leveraging both \nevolutionary conservation and context -\nspecific binding models. Experimentally \nvalidated interactions were further cross -\nreferenced using tarBase (v9.0) and \nmiRTarBase (v10.0). To transcend mere \ntarget prediction and elucidate the systems -\nlevel impact of miR-98-5p, we performed \nintegrative functional enrichment analysis. \nSignaling pathways and biological processes \nassociated with predicted targets were \nanalyzed using KEGG, DIANA -miRPath (v4.0), \nand GeneCodis (v6.0), with statistical \nsignificance defined by an adjusted P-value < \n0.05 (Benjamini -Hochberg correction). Gene \nOntology (GO) term overrepresentation was \nassessed for biological process, cellular \ncomponent, and molecular function \ncategories. Pathway perturbation dynamics \nwere quantitatively evaluated using Signaling \nPathway Impact Analysis (SPIA), which \ncombines overrepresentation and topological \nmeasures to identify dy sregulated pathways. \nTo contextualize miR-98-5p expression, we \nanalyzed data from The Cancer Genome Atlas \n(TCGA), Gene Expression Omnibus (GEO), and \nmiRBase (v22.1), focusing on endometriosis \nand related gynecological conditions.  \n2.9. Validation of differ ential gene \nexpression by RT-qPCR  \nTo confirm the findings from \ntranscriptomic analyses, quantitative reverse \ntranscription PCR (RT -qPCR) was performed \nto measure expression levels of DICER1 and \nhsa-miR-98-5p in 50 endometriotic lesions \nand 55 matched euto pic endometrial tissues. \nGlyceraldehyde-3-phosphate dehydrogenase \n(GAPDH) was employed as the endogenous \ncontrol for normalization. Its suitability was \nrigorously evaluated prior to use by assessing \nits expression stability across all sample types \n(ectopic lesions, patient eutopic endometrium, \nand control eutopic endometrium). \nThe analysis confirmed that GAPDH Ct \nvalues exhibited no statistically significant \nvariation ( P> 0.05 by one -way ANOVA) \nbetween the different tissue groups, \ndemonstrating its reliabil ity as a stable \nreference gene under our experimental \nconditions. Complementary DNA was \nsynthesized from total RNA using the \nPrimeScript RT reagent Kit (Takara Bio) with \nstem-loop primers for miR-98-5p and \noligo(dT) primers for DICER1 and GAPDH. \nqPCR react ions were conducted in triplicate \nusing SYBR Green Master Mix (Roche) in a 10 \nµL volume on a StepOnePlus™ Real -Time PCR \nSystem (Applied Biosystems). \nThe thermocycling protocol consisted of an \ninitial denaturation step at 95°C for 10 \nminutes, followed by 40  cycles of 95°C for 15 \nseconds and 61°C for 1 minute. Melting curve \nanalysis was conducted to verify the \nspecificity of the amplification. To prevent any \nnon-specific amplification resulting from \ngenomic DNA contamination, a non -reverse \ntranscription contr ol was inc orporated into \nthe qPCR assays. \nThe primers utilized in this study were \ndesigned using the Gene Runner and \nOligoAnalyzer software. The gene -specific \nprimers comprised those for the DICER1 gene: \nF: 5′ -TTCGAGCCTCCATTGTTGGTC-3′, R: 5′ -\nTTCCCAACTGGCATCAAATGG-3′ (amplicon \nsize: 127 bp), and for the hsa -miR-98-5p gene: \nF: 5′ -GTGAGGTAGTAAGTTGTATTG-3′, R: 5ˊ -\nATCACTGTAAAACCGTT-3ˊ (Universal reverse \nprimer), yielding a 171 bp product, as well as \nfor GAPDH: F: 5′ -\nAAGGTCGGAGTCAACGGATTTG-3′, R: 5′ -\nGCCATGGGTGGAATCATATTGG-3′. No -reverse \ntranscription control (NRTC) and no -template \ncontrol (NTC) were included to identify \ngenomic DNA contamination and non -specific \namplification. Cycle threshold (Ct) values \nwere evaluated using the 2 –ΔΔCt method to \ncalculate fold -change expression, with \nstatistical significance being analyzed through \nStudent’s t-test (P< 0.05).  \n2.10. Statistical analysis \nData were analyzed using descriptive and \ninferential statistics implemented in R v4.2.0 \nand GraphPad Prism v9.0. Continuous \nvariables are presented as mean ± SD or \nmedian with interquartile range (IQR) based \non their distribution, and visualized using \nboxplots. Categorical variables are \nsummarized as counts and percentages. \nGroup comparisons for continuous variables \n\nCell. Mol. Biomed. Rep.                                                                                                                               2026, 6(2): 170-194 \n177 | P a g e  \n \n(e.g., clinical pa rameters, RT -qPCR ΔΔCt \nvalues) were conducted using non -parametric \ntests (Mann -Whitney U test for two groups; \nKruskal-Wallis test with Dunn’s post hoc test \nfor more than two groups). \nFor all analyses involving multiple pairwise \ncomparisons, P-values were a djusted using \nthe Benjamini -Hochberg false discovery rate \n(FDR) correction to control for Type I error \ninflation. A two -sided P-value < 0.05 (or an \nFDR-adjusted P-value < 0.05, as applicable) \nwas considered statistically significant. \nUnadjusted and adjuste d logistic regression \nmodels were employed to evaluate risk \nfactors associated with endometriosis. Results \nare reported as odds ratios (OR) with 95% \nconfidence intervals (CI). Multivariable \nmodels adjusted for clinically relevant \ncovariates, including age at menarche, cycle \nlength, bleeding duration, parity, gravidity, \nmiscarriage history, contraceptive use, BMI, \nand smoking status. Model fit was assessed \nusing the Hosmer -Lemeshow goodness -of-fit \ntest, and multicollinearity among predictor \nvariables was eva luated using variance \ninflation factors (VIF), with a VIF < 5 \nconsidered acceptable. \n3. Results \n3.1. Differential expression gene (DEG) \nanalysis in endometriosis  \nIntegrated analysis of five Gene Expression \nOmnibus (GEO) datasets, GSE25628, \nGSE23339, GSE7846, GSE6364, and GSE5108, \nidentified significant transcriptomic \nalterations in endometriosis. The combined \ncohort included 69 endometriosis patients \nand 31 controls, with samples representing \nboth ectopic and eutopic endometrial tissues. \nA comprehensive tr anscriptomic analysis of \nendometriosis samples from public GEO \ndatasets identified 45,764 expressed mRNAs, \nof which 1,952 were differentially expressed \n(adjusted P-value < 0.05, |log2FC| > 1). Among \nthese, 527 mRNAs were significantly up -\nregulated and 1,42 5 were down -regulated in \nectopic versus eutopic endometrial tissues. \nThis pattern of widespread transcriptional \ndownregulation suggests a fundamental \nrewiring of the cellular state in ectopic lesions. \nWe postulate that this is not a passive \nphenomenon but may reflect sever al active \nbiological processes. \nFirstly, it could indicate a broad \nsuppression of terminal differentiation \nprograms, facilitating the plasticity required \nfor lesion survival and invasion  in a foreign \nmicroenvironment. \nSecondly, this patter n is consistent with \nthe establishment of a more primitive or \nstem-like transcriptional landscape, where \ngenes associated with mature endometrial \nfunction are silenced. This is further \nsupported by the functional enrichment \nanalysis, which highlighted the \ndownregulation of pathways related to \ninflammatory response, extracellular matrix \norganization, angiogenesis, and steroid \nhormone signaling, processes central  to \nendometriosis pathogenesis. \nVolcano plots and hierarchical clustering \nHeatmaps ( Figures 2 and 3) visualized the \ndistinct segregation of endometriosis and \ncontrol samples based on these DEGs. \nHierarchical clustering analysis demonstrated \nclear segregation between endometriosis and \ncontrol samples base d on these expression \npatterns. \nThe most signific antly up -regulated \nprotein-coding genes included CXCL12 (a \nchemokine promoting angiogenesis and \nimmune cell recruitment), VEGFA (a master \nregulator of vasculogenesis, supporting lesion \nsurvival), and MMP9 (a protease facilitating \ntissue remodeling and inva sion). Conversely, \nPROKR2 (involved in endometrial apoptosis \nand receptivity), ESR1 (encoding the estrogen \nreceptor alpha, central to hormonal \nresponse), and GATA6 (a transcription factor \ncritical for endometrial differentiation and \nfunction) were  among th e most down -\nregulated. \nThe coordinated upregulation of pro -\nangiogenic and invasive factors alongside the \nsuppression of genes essential for \nendometrial receptivity and hormonal \nsignaling strongly suggests that dysregulation \nof this specific gene set contri butes directly to \nthe pathogenesis of endometriosis and its \nassociated infertility. \n\n2026, 6(2): 170-194                                                                                                                               Cell. Mol. Biomed. Rep. \n178 | P a g e  \n \n \nFig. 2. Volcano plot of differentially expressed genes in endometriosis microarray dataset: This diagram \nrepresents the genes with significant increases and decreases ex pression in GSEs. The red color indicates \nsignificantly up-regulated genes (Log ₂FC > 1, FDR -adjusted P < 0.05), blue points represent significantly \ndown-regulated genes (Log ₂FC < -1, FDR -adjusted P < 0.05), and gray points represent non -significant \ngenes. Dashed vertical lines indicate ±1 log ₂ fold-change thresholds, and the horizont al dashed line \nrepresents the significance threshold ( -log₁₀ P= 1.3, equivalent to P = 0.05). FC: fold change; FDR: false \ndiscovery rate. \n\nCell. Mol. Biomed. Rep.                                                                                                                               2026, 6(2): 170-194 \n179 | P a g e  \n \n \nFig. 3. Heatmap of microarray data and hierarchical clustering for the top differentially expressed genes \n(DEGs) in the microarray datasets from control and endometriosis samples. Sample groups are explicitly \nannotated in the color bar above the heatmap: red indicates tissue samples, and green indicates disease \nstate. Rows represent individual genes, columns represent individual samples. Expression values are Z -\nscore normalized across samples, with red indicating expression above the mean and green indicating \nexpression below the mean. Cluster dendrograms reveal distinct grouping patterns between \nendometriosis and control samples. \n3.2. miRNAs differentially expressed in \nendometriosis \nParallel small RNA sequencing analysis \nrevealed 125 differentially expressed miRNAs, \nwith 58 up -regulated and 67 down -regulated \nin endometriosis lesions compared with \ncontrols. The signific ant downregulation of \nmiR-98-5p was consistently observed across \nboth independent datasets, showing markedly \nlower expression in endometriosis tissues \ncompared with normal controls ( Figure 4A, \nB). \nCrucially, the dysregulation of many of \nthese miRNAs, inclu ding the significant \ndownregulation of miR-98-5p, was also \nobserved in the eutopic endometrium of \npatients compared with the endometrium of \nhealthy controls. This consistent signature \nacross both ectopic and eutopic tissues \nstrongly suggests their potentia l involvement \nin early disease pathogenesis and the \npreconditioning of the endometrial \nmicroenvironment for lesion establishment. \nOther key dysregulated miRNAs included up -\nregulated miR -451a, miR -21-5p, and let -7b-\n5p, and down -regulated miR -200c-3p and \nmiR-29b-3p. \nFunctional enrichment analysis revealed \nthat these differentially expressed miRNAs are \nsignificantly involved in inflammatory \nresponse, extracellular matrix remodeling, \nangiogenesis, and steroid hormone signaling. \nThese pathways are well -established \nhallmarks of endometriosis pathophysiology. \nTheir concurrent dysregulation suggests a \ncoordinated molecular disruption that may \nfacilitate lesion survival, invasion, and \nprogression. This multi -pathway involvement \nunderscores the complex regulatory netw ork \naffected in the disease and supports the \nrelevance of these miRNAs as potential \ncontributors to the core biological processes \ndriving endometriosis onset and chronic \npersistence. \n\n2026, 6(2): 170-194                                                                                                                               Cell. Mol. Biomed. Rep. \n180 | P a g e  \n \n \nFig. 4. A) Expression profile of hsa-miR-98-5p across endometriosis and control endometrial tissues from \nthe GEO dataset GDS5339. Expression levels are shown as a percentile rank within each sample, \ndemonstrating a clear reduction in both ectopic and eutopic endometrium from patients with \nendometriosis compared with normal c ontrol endometrium. B) Validation of hsa -miR-98-5p \ndownregulation in an independent cohort from the ExplORRnet database, confirming significantly lower \nexpression in primary endometriotic tissue (n=504) compared with solid tissue normal controls (n=33).  \n3.3. Functional Enrichment Analysis of \nDICER1 and hsa-miR-98-5p Targets   \nTo elucidate the biological roles of DICER1-\nassociated genes and the predicted targets of \nhsa-miR-98-5p, we conducted Gene Ontology \n(GO) and KEGG pathway enrichment analyses \n(Figure 5). The GO results demonstrated that \nthese target genes were significantly enriched \n\nCell. Mol. Biomed. Rep.                                                                                                                               2026, 6(2): 170-194 \n181 | P a g e  \n \n(FDR < 0.05) in categories linked to cell \nadhesion and migration. Among the most \nprominently enriched biological processes \nwere epithelial -mesenchymal transition \n(EMT), reg ulation of cytokine -mediated \nsignaling, and angiogenesis. \nGiven that hsa -miR-98-5p is most \nfrequently downregulated in cancer, its \nsuppression leads to the derepression —and \nsubsequent upregulation—of its target genes. \nA focused GO analysis of these upregul ated \ntargets reveals a striking enrichment for \nprocesses that drive malignancy. Specifically, \nwe observe positive regulation of cell \nproliferation (via targets like CCND1 and \nCDK4), negative regulation of apoptosis (via \nBCL2), induction of EMT (via TWIST1) , and \npromotion of angiogenesis (via VEGFA). \nCollectively, these findings underscore a \ncoherent pro-oncogenic signature: when miR-\n98-5p is lost, the coordinated upregulation of \nits targets fuels tumor progression through \nenhanced survival, inv asiveness, and vascular \nsupport. \nThe enrichment of these pro -cancer \npathways reveals how the loss of the tumor \nsuppressor miR-98-5p paradoxically confers \noncogenic gain -of-function upon its target \ngenes. This mechanistic shift is further \ncompounded by the frequent down regulation \nof DICER1 in malignancies. As the central \nenzyme for miRNA biogenesis, DICER1 \ndepletion drastically reduces the global \nmature miRNA pool, thereby releasing \nhundreds of target transcripts from post -\ntranscriptional repression. The consequent \nderepression triggers a broad transcriptomic \navalanche, with Gene Ontology analyses \nconsistently identifying significant \nenrichment in cell cycle progression, \nenhanced migratory and invasive capacity, \ninflammatory signaling, Wnt pathway \nactivation, and dysregul ated metabolic \nreprogramming. Crucially, the impact of \nDICER1 loss is not pathway -specific but \nsystemic. By crippling the production of \ndiverse regulatory miRNAs, it eliminates the \nfine-tuned governance of the cellular \ntranscriptome. This widespread regula tory \ncollapse leads to the simultaneous and \naberrant activation of multiple oncogenic \nhallmarks, transforming a single molecular \ndefect into a coordinated, multifactorial driver \nof malignant transformation and tumor \nprogression. \nAt the molecular function l evel, the most \nenriched Gene Ontology categories included \ngrowth factor binding and transcription factor \nactivity. Cellular component analysis revealed \nsignificant enrichment in extracellular \nexosomes and focal adhesions. KEGG pathway \nannotation further li nked these genes to \nseveral signaling cascades known to underlie \nendometriosis pathophysiology ( Figure 6). \nNotably, the TGF ‑β (FDR = 3.2e ‑05), \nPI3K‑Akt (FDR = 1.8e ‑04), and Wnt (FDR = \n6.7e‑04) pathways emerged as the most \nsignificantly overrepresented. Alt ogether, \nthese data demonstrate that genes \nco‑dysregulated with DICER1 and \nhsa‑miR‑98‑5p are functionally \ninterconnected rather than dispersed. Their \ncoordinated enrichment points toward a \ncohesive molecular signature that directly \nsupports key hallmarks o f endometriotic \nlesion development and persistence —\nspecifically, tissue invasion, immune evasion, \nand neovascularization. Such convergence \nstrongly suggests that DICER1 and miR‑98‑5p \nmay act as upstream modulators of a \nregulatory network that facilitates l esion \nestablishment, survival, and progression. \nThese insights not only deepen our \nunderstanding of endometriosis pathogenesis \nbut also highlight potential nodes for \ntherapeutic intervention targeting these \ncritical pathways and biological processes.  \n3.4. Expression Level of hsa -miR-98-5p in \nEndometriosis Patients vs. Controls  \nQuantitative analysis demonstrated a \nnotable downregulation of hsa -miR-98-5p in \nectopic endometrial tissues of endometriosis \npatients compared with eutopic tissues of \nhealthy contro ls ( Figure 7). The mean \nexpression level of hsa -miR-98-5p in the \ntissues of patients was reduced by 3.5 -fold \n(ΔΔCt = -1.81, P-value < 0.001) relative to \ncontrols. In the eutopic endometrium of \npatients, the expression was 2.2 -fold lower \nthan that of contro ls (ΔΔCt = -1.14, P-value = \n0.003), suggesting a systemic dysregulation \nthat extends beyond  the lesion sites. ROC \ncurve analysis indicated that the expression of \n\n2026, 6(2): 170-194                                                                                                                               Cell. Mol. Biomed. Rep. \n182 | P a g e  \n \nhsa-miR-98-5p could effectively differentiate \npatients from controls, achieving an AUC = \n0.89 (95% CI: 0.82 –0.96), highlighting its \npotential as a diagnostic biomarker (At the \noptimal cutoff value determined by the \nYouden Index, this yielded a sensitivity of \n85% and a specificity of 82%). Furthermore, \nSpearman's rank correlation analysis revealed \nthat low levels of hsa -miR-98-5p expression \nwere significantly associated with more \nadvanced stages of the disease (r = -0.62, P-\nvalue = 0.001) and greater severity of \ndysmenorrhea (r = -0.57, P-value = 0.004) \n(Figure 8). No significant correlation was \nfound with age or BMI (P-value > 0.05).  \n \n \n \nFig. 5. Analysis of Biological Processes and Gene Ontology (GO) functional enrichment related to DICER1-\nassociated genes \n\nCell. Mol. Biomed. Rep.                                                                                                                               2026, 6(2): 170-194 \n183 | P a g e  \n \n \n \nFig. 6. DICER1 signaling pathway. Based on the KEGG online database, the diagram depicts  the organized \nterminology of the Gene Ontology framework, displaying the particular biological terms (leaves) linked to \nthe gene set and their connections to more general parent terms (branches). The examination reveals a \nnotable accumulation of terms pertaining to RNA-processing complexes and nuclease functions, including \nthe precise formation of the RISC complex, which plays a crucial role in miRNA biogenesis and RNA \nsilencing. \n \n\n2026, 6(2): 170-194                                                                                                                               Cell. Mol. Biomed. Rep. \n184 | P a g e  \n \n \nFig. 7. Differential expression and diagnostic performance of hsa -miR-98-5p in endometriosis. A) \nExpression analysis of hsa -miR-98-5p across three sample types: ectopic lesions (patient-derived \nendometrial implants outside the uterus), matched eutopic endometrium (patient -derived uterine \nendometrium), and normal endometrium (h ealthy control subjects). Hsa -miR-98-5p shows significant \ndownregulation in both ectopic lesions (ΔΔCt = -1.81, P< 0.001) and eutopic endometrium from patients \ncompared to normal healthy controls. B) The ROC curve analysis demonstrates that hsa -miR-98-5p \nexpression effectively discriminates between endometriosis patients (combining ectopic and eutopic \nsamples) and healthy controls, with an area under the curve (AUC) of 0.89 (95% CI: 0.82 -0.96, P-value= \n0.0003). \n \nFig. 8. Association between hsa -miR-98-5p expression and clinicopathological features in endometriosis \npatients.A) Comparison of hsa -miR-98-5p expression levels across endometriosis stages (I -IV) reveals a \nsignificant downregulation in ectopic lesions relative to matched eutopic tissues, with progressively lower \nexpression observed in advanced stages (IV) compared to early stages (I -II). B) Analysis of hsa-miR-98-5p \nexpression stratified by dysmenorrhea severity demonstrates a significant inverse correlation, where \nsevere dysmenorrhea is associated w ith markedly reduced hsa -miR-98-5p levels in ectopic lesions \ncompared to mild/moderate symptoms. \n\nCell. Mol. Biomed. Rep.                                                                                                                               2026, 6(2): 170-194 \n185 | P a g e  \n \n3.6. Severity analysis \nConsidering the chronic and recurrent \ncharacteristics of endometriosis, we assessed \nthe relationship between DICER1/hsa-miR-98-\n5p expression and the severity of the disease. \nPatients were divided into two groups: low -\nseverity (rASRM Stage I -II) and high -severity \n(rASRM Stage III -IV). The results from logistic \nregression analysis revealed that a one -unit \ndecrease in ΔΔCt values of DICER1 expression \nwas significantly associated with an elevated \nrisk of severe disease (OR = 3.5, 95% CI: 1.8 –\n6.9, P-value < 0.001). Similarly, a one -unit \ndecrease in ΔΔCt values of hsa -miR-98-5p was \ncorrelated with a heightened risk of severe \nendometriosis (OR = 2.8, 95% CI: 1.5 –5.4, P-\nvalue = 0.002). The findings from the logistic \nregression analysis indicated that reduced \nlevels of DICER1 and hsa -miR-98-5p \nexpression were significantly associated with \nan increased risk of severe disease ( Figure 9). \nFurthermore, a combined model utilizing both \nbiomarkers enhanced the predictive accuracy \nfor disease severity (AUC = 0.82, 95% CI: \n0.75–0.89).  \n3.5. Expression of DICER1 in endometriosis \npatients vs. controls \nQuantitative analysis revealed a significant \ndownregulation of DICER1 mRNA levels in \nectopic endometrial tissues from patients \nwith endometriosis when compared with \neutopic tissues of healthy controls ( Figure \n10A). The results from qRT-PCR indicated that \nDICER1 mRNA levels were reduced by 4.2-fold \nin ectopic tissue s of patients relative to \ncontrols (ΔΔCt = −2.07, P-value < 0.001). \nAdditionally, the eutopic endometrium of \npatients exhibited a 2.8 -fold reduction in \nDICER1 expression compared with healthy \ncontrols (ΔΔCt = −1.49, P-value = 0.002). \nSpearman's correlation  analysis confirmed \nthat low expression of DICER1 was \nsignificantly associated with advanced rASRM \nstages (r = −0.68, P-value < 0.001) and \ninfertility (r = −0.54, P-value = 0.007). There \nwas no significant correlation with patient age \nor BMI (P-value > 0.05). \nTo explore whether hsa -miR-98-5p and \nDICER1 are correlated in endometriosis, we \nconducted a Pearson correlation analysis \nusing miRNA and mRNA expression data from \npatient ectopic lesions and control eutopic \nendometrial samples. Our results revealed a \nsignificant positive correlation between hsa -\nmiR-98-5p and DICER1 expression (r = 0.72, P \n= 0.0044). This robust association suggests a \npossible functional link within the miRNA \nbiogenesis pathway. Specifically, reduced \nDICER1 expression may impair the prop er \nprocessing of precursor miRNAs, leading to \ndecreased mature hsa -miR-98-5p levels. Such \ndysregulation could play a role in the \nmolecular mechanisms underlying \nendometriosis. These findings, illustrated in \nFigure 10B, support the hypothesis that \nDICER1-mediated miRNA maturation is \ndisrupted in ectopic tissues, potentially \ncontributing to disease pathogenesis. \nThese findings point to a possible \nfunctional interplay between DICER1 and hsa-\nmiR-98-5p in endometriosis pathogenesis, \npotentially via shared regula tory nodes \naffecting miRNA processing or intersecting \ndownstream signaling cascades. Data are \nexpressed as mean ± SEM, derived from 55 \npatients and 40 healthy controls. ROC analysis \nfor DICER1 alone yielded an AUC of 0.84 (95% \nCI: 0.76–0.92) in distinguishing endometriosis \ncases from controls. Notably, the combined \nDICER1/miR-98-5p signature significantly \nimproved diagnostic performance, achieving \nan AUC of 0.93 (95% CI: 0.88 –0.98). Pairwise \nROC comparison using DeLong’s test \nconfirmed that this dual -marker model \noutperformed each individual biomarker \nalone, underscoring the additive value of their \njoint assessment. Such a synergistic \nrelationship not only strengthens diagnostic \naccuracy but also hints at convergent \nbiological pathways that may be co -opted i n \ndisease development, warranting further \nmechanistic exploration. \n \n \n\n2026, 6(2): 170-194                                                                                                                               Cell. Mol. Biomed. Rep. \n186 | P a g e  \n \n \n \nFig. 9. Association of DICER1 and hsa -miR-98-5p expression with endometriosis severity. A) Logistic \nregression analysis showing that reduced DICER1 expression is significantly associated with an increased \nrisk of severe (Stage III/IV) endometriosis, B) Similarly, reduced hsa-miR-98-5p expression is associated \nwith a heightened risk of severe disease (OR = 2.8, 95% CI: 1.5–5.4, P = 0.002). \n\nCell. Mol. Biomed. Rep.                                                                                                                               2026, 6(2): 170-194 \n187 | P a g e  \n \n \n \nFig. 10. A) The comparative expression lev els of DICER1 in patients versus the control group. B) \nCorrelation analysis revealed a positive correlation between DICER1 and hsa-miR-98-5p (P = 0.0044). \n4. Discussion    \nEndometriosis is a complex, chronic \ngynecological condition marked by the \npresence of endometrial -like tissue outside \nthe uterine cavity, impacting around 10% of \nwomen of reproductive age and resulting in \npain, infertility, and a diminished quality of \nlife [17]. Despite its widespread occurrence, \nthe molecular mechanisms that drive its \npathogenesis are not fully understood, \nhighlighting the need for the discovery of \nreliable diagnostic biomarkers and \ntherapeutic targets. Recent f indings \nemphasize the significant role of post -\ntranscriptional regulation, particularly \nthrough the dysregulation of microRNA \n(miRNA) and disruptions in the miRNA \nbiogenesis pathway, in the formation and \nadvancement of endometriotic lesions [9, 18]. \nThe claim that post-transcriptional regulation, \nespecially through miRNA dysregulation, is \ncrucial in the pathogenesis of endometriosis is \nsupported by considerable recent evidence. \nThis mechanism is integral to the disease's \ndefining characteristics, including \nproliferation, inflammation, angiogenesis, and \nimmune evasion [19]. Numerous high -\nthroughput studies have revealed unique \nmiRNA expression profiles in ectopic \nendometrium when compared with eutopic \nand healthy tissues. For example, members of \nthe miR -200 family are often downregulated, \nwhich leads to increased expression of \nZEB1/2 and facilitates Epithelial -\nMesenchymal Transition (EMT), a vital \nprocess for lesion invasion and establishment \n[20]. Additionally, miR -34a and let -7b are \nfrequently underexpressed, resulting in the \nupregulation of BCL -2 and MYC, which \npromote cell survival and proliferation in \nectopic lesions [21]. Dysregulated miRNAs \ndirectly influence key pathways associated \nwith endometriosis; for instance, the \ndownregulation of miR -451 results in \nheightened MAPK signaling, which boosts cell \nproliferation [22]. Furthermore, the \noverexpression of miR -21-5p targets PTEN \nand PDCD4, thereby promoting survival and \ninhibiting apoptosis in endometriotic cells and \nthe suppression of miR -126 contributes to \nangiogenesis through the upregulation of \nVEGFA [23]. A case -control study revealed \ndifferences in miR -125b levels between \neutopic and ectopic endometrium in patients \nwith endometriosis compared with healthy \ncontrols. It ha s also been suggested that the \n\n2026, 6(2): 170-194                                                                                                                               Cell. Mol. Biomed. Rep. \n188 | P a g e  \n \nincreased activity of miR-125b interferes with \nTP53 expression, inhibiting apoptosis [24]. \nAnother study identified 22 miRNAs \nassociated with endometriosis through \nmicroarray analysis of ectopic and euto pic \nendometrial tissues. Among these, 14 miRNAs \nwere found to be up -regulated and 8 miRNAs \nwere down -regulated [25]. Additionally, \nanother study identified 10 miRNAs that were \nup-regulated in cases of endometriosis, and \n12 miRNAs were down -regulated compared \nwith normal endometrial tissue [26]. \nThe core machinery responsible for miRNA \nprocessing, which includes Drosha, Dicer, and \nArgonaute proteins, is often disrupted in cases \nof endometriosis. A decrease in DICER1 \nexpression has been observed in ectopic \nstromal cells, resulting in a widespread \nimpairment of mature miRNA biosynthesis. \nThis situation fosters an environment \nconducive to the overexpression of oncogenes \nand inflammatory mediators [27]. Epigenetic \nchanges (such as  promoter hypermethylation \nof DICER1) and inflammatory cytokines \n(including TNF -α and IL -1β) can inhibit the \nexpression and function of miRNA -processing \nenzymes, further worsening miRNA \ndysregulation. DICER1 is central to this \nmechanism, being a crucial ri bonuclease that \nfacilitates mature miRNA processing, and its \naltered expression has been linked to \ngynecological disorders [28]. At the same \ntime, miR-98-5p, a member of the let -7 family \nknown for its roles in regulating \ninflammation, cell proliferation, and invasion \nin various diseases, has surfaced as a potential \nregulator in endometriosis. Additionally, miR -\n98 has  been reported to function as a tumor \nsuppressor by directly targeting genes that \npromote tumorigenesis. Research has shown \nthat miR -98 significantly influences cancer \ncell proliferation, apoptosis, and the \nregulation of the cell cycle. Its interaction with \nthe cell cycle machinery can determine cell \nfate; for example, studies in cervical cancer \nindicate that overexpression of miR -98 can \nlead to G1 cell cycle arrest. Additionally, miR -\n98 plays a crucial role in metastasis and \nangiogenesis, which are vital p rocesses for \ncancer spread and growth [18]. Nevertheless, \nthe functional interplay between DICER1 and \nmiR-98-5p, along with their combined \npotential as diagnostic markers in matched \nectopic and eutopic endometrial tissues, has \nyet to be investigated. While previous studies, \nsuch as Rekker et al. have identified various \nmiRNA biomarkers, often in circulation [29], \nour work uniquely focuses on the tissue -\nspecific dysregulation of the DICER1-miR-98-\n5p axis within  the lesion microenvironment \nitself, providing direct insight into the disease \nmechanism and a highly specific tissue -based \ndiagnostic signature. \nIn this study, we investigated the \nexpression and clinical relevance of DICER1 \nand miR-98-5p, aiming to elucid ate their roles \nin the development of endometriosis and \nevaluate their potential as a new biomarker \npanel. We present new clinical evidence \nindicating that the coordinated \ndownregulation of the ribonuclease DICER1 \nand its possible regulatory target, hsa-miR-98-\n5p, represents a crucial molecular event in the \nformation and persistence of endometriotic \nlesions. Our results, obtained from the \nexamination of matched eutopic and ectopic \nendometrial tissues, establish this axis not \nonly as a significant factor in the molecular \npathology of the disease but also emphasize \nits considerable potential as a reliable \ndiagnostic biomarker panel. This is consistent \nwith the emerging understanding that \ndisruptions in the miRNA biogenesis \nmachinery play a vital role in gyneco logical \ndisorders [30], and further expands this \nconcept by pinpointing a specific miRNA -\nprocessor partnership pertinent to \nendometriosis. \nThe findings of this study reveal that the \ncoordinated downregulation of DICER1 and \nhsa-miR-98-5p is a piv otal event in \nendometriosis pathogenesis. This alignment is \nnot coincidental but reflects a self -reinforcing \npathogenic loop that promotes lesion survival \nand progression, supported by recent \nmolecular studies [31]. Reduced DICER1 \nexpression, a consistent feature in our ectopic \ntissue samples, compromises the processing \nof pre -miRNAs into mature miRNAs. This \ncreates a permissive environment for the \nunchecked expression of genes promoting \ninvasion, inflammation, and survival. This is \nconsistent with studies by Li et al., who \ndemonstrated that DICER1 downregulation in \nendometrial stromal cells leads to a global \n\nCell. Mol. Biomed. Rep.                                                                                                                               2026, 6(2): 170-194 \n189 | P a g e  \n \nimpairment of miRNA biogenesis, directly \ncontributing to a pro -endometriotic \ntranscriptomic landscape [32]. The specific \ndownregulation of hsa -miR-98-5p, a member \nof the tumor -suppressive let -7 family, is \nparticularly significant. DICER1 is essential for \nthe generation of mature let -7 miRNAs. Our \ncorrelation analysis supports that low DICER1 \nlevels directly contribute to reduced miR-98-\n5p maturation. Sergi et al. stated that while \nDICER1 is crucial for normal female \nreproductive tract development and function , \nits somatic dysregulation in adult tissues is \nincreasingly linked to pathologies like \nendometriosis [33]. Nothnick states that while \nmany miRNAs have been proposed as \nbiomarkers, the field is moving towards multi-\nmarker panels and understanding mechanistic \npartnerships (like the one between a \nprocessor and a miRNA) to improve \ndiagnostic specificity and accuracy [34]. As \nreviewed by Zafari et  al., the loss of let -7 \nfamily members is a recurring issue in \nendometriosis, resulting in the derepression \nof their oncogenic and inflammatory targets \n[35]. The concurrent loss of this regulator -\neffector pair has cumulative effects: miR-98-5p \ndirectly targets IL -6 and TGF -βR1, which are \nessential drivers of proliferation/invasion and \nepithelial-mesenchymal transition (EMT). The \nderepression caused by low lev els of miR-98-\n5p promotes lesion establishment, \nangiogenesis, and regulates VEGFA expression \n[36]. Its absence encourages the \nvascularization of lesions, a vital step for their \npersistence, as emphasized in studies on \ntumor metabolism by Hazari et al. [13]. Our \nresearch reveals a notable downregulation of \nmiR-98-5p in endometriotic lesions, which \nholds significant functional implications. The \nreduction of this essential regulatory miRNA \nis not merely a passive outcome but rather an \nactive contributor to disease pathogenesis , as \nit results in the derepression of a network of \npro-endometriosis target genes. In particular, \nour findings align with existing literature \nindicating that miR-98-5p directly targets and \ninhibits the expression of: HMGA2, a gene \noften overexpressed in e ndometriosis that \nencourages cell proliferation and survival \n[37], IL -6, a key pro -inflammatory cytokine \nthat supports the chronic inflammatory \nmicroenvironment typical of the disease [38], \nVEGFA, a principal regulator of angiogenesis \nnecessary for the vascularization and growth \nof ectopic implants [39], E2F1 and CCND1, \nvital regulators of cell cycle progression \nwhose dysregulation results in uncontrolled \nproliferation [40]. Consequently, the noted \ndecline in miR-98-5p expression, p otentially \nworsened by the simultaneous \ndownregulation of DICER1, establishes a \npermissive environment where these \noncogenic, inflammatory, and angiogenic \npathways become excessively active. This \nmulti-target mechanism elucidates how the \nloss of a single m iRNA can collectively drive \nthe fundamental processes of endometriosis \nprogression: proliferation, inflammation, and \nneovascularization. Thus, our data position \nthe miR-98-5p node as a pivotal regulatory \nhub in endometriosis, whose disruption has \nfar-reaching effects on the cellular \ntranscriptome. \nThe DICER1/miR-98-5p axis may affect the \nexpression of immune -modulating proteins \nsuch as PD -L1 and create an \nimmunosuppressive environment that allows \nlesions to escape immune surveillance [41]. \nThis coordinated downregulation  offers a \nrobust multi-marker diagnostic signature. The \nstrong correlation observed between their \nexpression levels and disease severity (rASRM \nstage) indicates that evaluating both \nmolecules could enhance diagnostic accuracy \ncompared with single markers, a strategy \nsupported by Rekker et al. in their research on \nmiRNA panels [29]. Moreover, therapeutic \napproaches aimed at restoring miR-98-5p \nfunction (for instance, through the use of \nmiRNA mimics) or stabilizing DICER1 \nexpression could disrupt this pathogenic \ncycle, presenting a novel targeted treatment \nstrategy. \nMiR-98 has emerged as a significant factor \nin ovarian cancer, with its expression levels \ninfluencing various oncogenic pathwa ys and \npatient outcomes. Research has shown that \nmiR-98-5p is enriched in cisplatin -resistant \nepithelial ovarian cancer (EOC) cells [13]. This \nenrichment promotes cisplatin resistance by \ninhibiting the biogenesis of miR -152 through \nthe targeting of DICER1, which is associated \nwith poor outcomes in EOC patients. Among a \npanel of miRNAs, miR-98-5p has been \nidentified as a biomarker for resistance to \n\n2026, 6(2): 170-194                                                                                                                               Cell. Mol. Biomed. Rep. \n190 | P a g e  \n \nplatinum-based chemotherapy in high -grade \nserous ovarian cancer (HGSC) [42]. \nFurthermore, when examining the transition \nof endometrial cells, abnormal expression of \nmiR-98 has been linked to the progression \ninto cancerous states. Studies have shown that \nmiR-98-5p is often downregulated in ectopic \nendometrial tissues compared w ith eutopic \ntissues [35]. This downregulation may \ncontribute to the increased proliferation and \nsurvival of endometrial cells outside the \nuterus, which is a hallmark of endometriosis. \nThe varied roles of miR-98-5p in both ovarian \nand endometrial cancers, including its \ninfluence on disea se progression and \nchemoresistance, highlight its potential as a \nvaluable biomarker in women's health \ndisorders. Given its wide -ranging effects, \nthere is an urgent need for further research to \noptimize its application in therapeutic \nstrategies for endometriosis.  \nSeveral limitations of this study must be \nrecognized. Firstly, our sample size (n=30 \npatients with endometriosis, n=35 controls), \nalthough adequate for initial discovery, may \nrestrict the statistical power for subgroup \nanalyses and multivariate adj ustments. \nSecondly, the single -center design at Shahid \nSadoughi Hospital, while providing consistent \nsurgical and laboratory protocols, may \ninfluence the generalizability of our results to \nlarger populations with varying ethnic and \ndemographic characterist ics. Thirdly, this \nstudy concentrated solely on tissue -based \nbiomarkers without examining circulating \nlevels in serum or plasma, which would be \nessential for the development of non -invasive \ndiagnostic tests. Most critically, our study \noffers correlative ev idence but lacks \nfunctional validation experiments; the \nmechanistic link between DICER1 \ndownregulation and miR-98-5p reduction has \nyet to be experimentally confirmed through in \nvitro or in vivo models. Future research with \nlarger, multi -center cohorts and functional \nexperiments is required to validate these \nfindings and establish causal mechanisms. \n5. Conclusion \nThis study identifies the DICER1/miR-98-\n5p axis as an active contributor to \nendometriosis, where its dysregulation \npromotes a lesion -permissive \nmicroenvironment. Under normal conditions, \nmiR-98-5p fine-tunes cellular growth, \ndifferentiation, and apoptosis by targeting key \nmRNAs involved in these processes. We found \nsignificant disruption of this regulatory axis in \nendometriosis, suggesting its dual r ole as a \ndiagnostic biomarker and therapeutic target. \nThe differential expression of miR-98-5p and \nDICER1 in ectopic versus eutopic tissues \nunderscores their clinical potential. Further \nresearch is needed to fully elucidate their \npathophysiological roles a nd translational \napplications. \nConflict of Interests \nThe authors declare no conflict of interest. \nEthics approval and consent to participate \nThe study was conducted in complete \ncompliance with the ethical standards \noutlined in the Declaration of Helsinki a nd \nwas approved by the Research Ethics \nCommittee of Shahid Sadoughi University of \nMedical Sciences, Iran (Approval Code: \nIR.YAZD.REC.1402.002). Before participation, \nwritten informed consent was obtained from \nall individuals. The study protocol emphasized \nparticipant autonomy, confidentiality, and the \nright to withdraw at any stage without \nconsequence. All collected data were \nanonymized and securely stored in \naccordance with international standards for \nbiomedical data protection, including \nencryption and ac cess restrictions, to ensure \nparticipant privacy. \nConsent for publication \nThe authors read and approved the final \nmanuscript for publication. \nInformed Consent \nThe authors declare not used any patients \nin this research.  \nAvailability of data and material  \nThe data that support the findings of this \nstudy are available from the corresponding \nauthor upon reasonable request. \nAuthors' contributions \nConceptualization: Mehri Khatami. \nData curation: Mohammad Mehdi Heidari. \n\nCell. Mol. Biomed. Rep.                                                                                                                               2026, 6(2): 170-194 \n191 | P a g e  \n \nFormal analysis:  Mohammad Mehdi \nHeidari. \nInvestigation: Mahdieh Azizi Panah. \nMethodology: Mohammad Mehdi Heidari. \nProject administration:  Mahdieh Azizi \nPanah. \nSoftware: Mahdieh Azizi Panah. \nResources: All authors. \nSupervision: Mehri Khatami. \nValidation: Mojgan Hajisafari Tafti. \nVisualization: Mojgan Hajisafari Tafti. \nWriting–original draft: Mehri Khatami. \nWriting–reviewing & editing: All authors. \nFunding \nThis research did not receive any specific \ngrant from funding agencies in the public, \ncommercial, or not-for-profit sectors. \nAcknowledgments \nThe authors t hank all the patients for \nproviding tissue samples. The Yazd University \nHuman Research Committee approved the \nstudy. 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This is an open access article distributed  \nunder the terms and conditions of the Creative Commons Attribution (CC BY) license  \n(https://creativecommons.org/licenses/by/4.0/) \nKhatami M, Azizi Panah M, Heidari MM, Hajisafari Tafti M (2026) Differential expres sion of \nmiR-98-5p and DICER1 in eutopic versus ectopic endometrium: a diagnostic biomarker \nsignature for endometriosis. Cellular, Molecular and Biomedical Reports 6 (2): 170 -194. \ndoi: 10.55705/cmbr.2026.550859.1337 \nRIS; EndNote; Mendeley; BibTeX; APA; MLA ;HARVARD; CHICAGO; VANCOUVER","source_license":"CC0","license_restricted":false}