{"paper_id":"cb6c0a11-07b6-4f2d-aaeb-254da59e6ae2","body_text":"Mahmoud et al. \nThe Journal of Basic and Applied Zoology            (2025) 86:1  \nhttps://doi.org/10.1186/s41936-024-00414-5\nRESEARCH\nOverexpression of miR-21-5p as a potential \npathogenesis marker for ovarian endometriosis\nMohamed Mahmoud1†, Amr Ahmed WalyEldeen1†, Mohamed A. Samie2, Ahmed M. Sadek3, Sayed Elakhras4, \nMohamed Samir1, Osama Ahmed1, Rasha Mohamed Samir Sayed5, Ahmed Abdelaziz Baiomy1, \nSherif Abdelaziz Ibrahim1*† and Hebatallah Hassan1*† \nAbstract \nBackground Endometriosis is a benign gynecological disease characterized by the growth of endometrial cells \nbeyond the uterus, forming endometriotic cyst tissues called ovarian endometriomas. MicroRNAs (miRNAs) are small, \nnon-coding RNAs that epigenetically control the physiological and pathological processes of different diseases, \nincluding endometriosis. In this study, we screened the expression levels of 11-selected miRNAs, namely miR-21-5p, \nmiR-200c-3p, miR-19a-3p, miR-203-3p, miR-181b-5p, miR-182-5p, miR-let7a-5p, miR-205-5p, miR-200b-3p, miR-16-5p, \nand miR-222-3p in ovarian endometriomas relative to eutopic endometrial tissues using quantitative real-time \nPCR (qPCR). In addition, the level of mRNA expression of lumican (LUM), an extracellular matrix proteoglycan (PG), \nand a putative target of miR-21-5p was quantified by qPCR.\nResults Our screening qPCR results showed that 9 miRNAs were upregulated (miR-21-5p, miR-200c-3p, miR-\n19a-3p, miR-203-3p, miR-181b-5p, miR-182-5p, miR-let7a-5p, miR-205-5p, and miR-200b-3p), whereas 2 miRNAs \nwere downregulated (miR-16-5p and miR-222-3p) in ovarian endometriomas compared to eutopic endometrium. \nA significant overexpression of miR-21-5p in ovarian endometrioma was further independently verified by qPCR. \nUsing bioinformatics tools, Gene Ontology Kyoto Encyclopedia of Genes and Genomes pathways, and protein–\nprotein interactions, we identified differentially expressed genes and several pathways regulated by miR-21-5p \nthat may contribute to endometriosis progression. Among them, LUM was found to be significantly diminished \nexpressed in ovarian endometriomas compared to eutopic endometrium.\nConclusion In conclusion, this study identified miR-21-5p and LUM as potential factors that may contribute \nto ovarian endometriomas’ pathogenesis.\nKeywords Endometriosis, Ovarian endometriomas, microRNA, miR-21, Lumican\nOpen Access\n© The Author(s) 2025. Open Access  This article is licensed under a Creative Commons Attribution 4.0 International License, which \npermits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the \noriginal author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or \nother third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line \nto the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory \nregulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this \nlicence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.\nThe Journal of Basic\nand Applied Zoology\n†Mohamed Mahmoud, Amr Ahmed WalyEldeen, Sherif Abdelaziz Ibrahim, \nand Hebatallah Hassan contributed equally to this work.\n*Correspondence:\nSherif Abdelaziz Ibrahim\nisherif@sci.cu.edu.eg; isherif@cu.edu.eg\nHebatallah Hassan\naheba@sci.cu.edu.eg\n1 Department of Zoology, Faculty of Science, Cairo University, Giza 12613, \nEgypt\n2 Department of Gynecology and Obstetrics, Faculty of Medicine, Al-\nAzhar University, Cairo 11651, Egypt\n3 Department of Gynecology and Obstetrics, Faculty of Medicine, Benha \nUniversity, Banha 13518, Egypt\n4 Consultant of Obstetrics and Gynecology and Minimally Invasive \nSurgery, Omam Comprehensive Endometriosis Centre, Giza 22311, Egypt\n5 Pathology Department, Faculty of Medicine, Aswan University, \nAswan 81528, Egypt\n\nPage 2 of 15Mahmoud et al. The Journal of Basic and Applied Zoology            (2025) 86:1 \nBackground\nEndometriosis is a gynecological, genetic, and estrogen-\ndependent autoimmune disorder in which endometrial \ncells grow outside the uterus, primarily in the ovaries and \nperitoneum (Chen et al., 2023; Nisolle & Donnez, 1997; \nShao et  al., 2014). Ovarian endometriomas can severely \nimpair ovary reserve and may lead to infertility due to \nlaparoscopic ovarian cystectomies (Bulun, 2019; Gao \net  al., 2023; Kitajima et  al., 2011; Yılmaz Hanege et  al., \n2019). Other clinical complications, besides infertility, \nare substantially associated with endometriosis, such \nas chronic pelvic pain, dyspareunia, and dysmenorrhea. \nConsequently, decreased quality of life and economic \nburden associated with endometriosis therapy repre -\nsent the major challenges for this disease (Rogers et  al., \n2013). Although multiple efforts have been dedicated to \ndiscovering the cause of endometriosis, the fundamental \nmolecular mechanisms underlying the cause of 10% of \nwomen harboring endometriosis have not yet been dis -\ncovered (Hu et al., 2022). The ovarian endometriotic cyst \nis commonly referred to as a chocolate cyst as it is filled \nwith menstruation-like hemorrhagic blood, giving it a \ndark brown appearance. The accumulation of this hem -\norrhagic blood inside the cyst prompts the recruitment \nof the macrophages, which in turn phagocytize and lyse \nthe blood cells, releasing heme and iron, and inducing \nthe secretion of pro-inflammatory cytokines (Guo et al., \n2015; Simoni et  al., 1994; Wyatt et  al., 2023). Because \nof prolonged exposure to inflammation, cysts begin \nto develop fibrosis (Houghton & McCluggage, 2011). \nIntriguingly, it has been reported that many ovarian \nendometriotic cysts may be originated from the meta -\nplastic fallopian tube instead of eutopic endometrium \nsince the specific markers of fallopian tube may be seen \nin ovarian endometriotic lesions, which in turn explains \nthe unresponsive to hormonal treatments in many cases \n(Hill et al., 2020; Wang et al., 2023; Yuan et al., 2014).\nMicroRNAs (miRNAs) are crucial epigenetic regula -\ntors of genes related to the formation and progression of \nendometriotic lesions; consequently, they appear to be \npotentially attractive candidates (Hawkins et  al., 2011). \nmiRNAs can suppress the transcription or translation \nwhen it binds to the 3′ untranslated region (UTR) of the \ntargeted mRNA (Lee et al., 1993; Pasquinelli et al., 2000). \nmiRNAs have been previously demonstrated to regulate \nthe hallmarks of cancer, including proliferation, death, \nangiogenesis, differentiation, and migration (Hu et  al., \n2022; Zhang et  al., 2019). A previous microarray study \nrevealed aberrant expression of miRNA in ectopic endo -\nmetrium compared to eutopic endometrium (Teague \net  al., 2009). However, specific miRNA expression pat -\nterns in women with ovarian endometriomas have not \nyet been fully explored. So, this study aimed to screen \n11-selected dysregulated miRNA expression patterns and \nidentify putative targets, which may have a potential role \nin ovarian endometriomas pathogenesis.\nMethods\nSample collection\nThis study was initiated after obtaining approval from \nthe institutional review board (IRB) at the Faculty of \nMedicine, Al-Azhar University (protocol number: \n0000195) and the local Ethics Committee of the Fac -\nulty of Medicine at Aswan University (Protocol No. \nAsw.U./677/10/22). Aligned with the regulations of the \nDeclaration of Helsinki, all patients with ovarian endo -\nmetriosis enrolled in this study signed consent form to \nparticipate. Females aged 24–49  years diagnosed with \novarian endometriomas through laparoscopy and were \nnot on hormone replacement treatment for at least a \nyear were recruited for this study. Ovarian endometri -\notic cyst tissues (n = 14) and eutopic endometrial tissues \n(n = 8) were collected. The patients with chronic autoim -\nmune disease, infectious conditions, acute inflammation, \nor cancer were excluded. For the RNA extraction, the \ntissue samples were snap-frozen in liquid nitrogen and \nsubsequently stored at − 80  °C until needed for further \nanalysis.\nHistological examination\nEndometrium and ovarian endometriomas were fixed in \nneutral-buffered formalin (10%), followed by dehydration \nsteps through ascending ethanol series. Tissue sections \nwere treated with xylene to eliminate the alcohol, and \nparaffin was used to embed the tissue. Hematoxylin and \neosin were used to stain tissue sections as previously \ndescribed (Fischer et  al., 2008; Velho et  al., 2023) with \na thickness of 5 μm, and a pathologist examined the \nsections in a blind manner.\nRNA isolation and cDNA synthesis\nThe miRNeasy Mini Kit (cat. no.217004, Qiagen, \nHilden, Germany) was used to extract total RNA from \neutopic endometrium and ovarian endometrioma for \nmiRNA and mRNA expression analysis. Tissues were \nfirst homogenized in QIAzol reagent (Qiagen) and \nincubated with 200 µL chloroform to obtain the RNA’s \naqueous phase. Subsequently, ethanol-treated RNA was \ntransferred to the RNeasy mini-column, according to \nthe manufacturer’s instructions. The concentration and \npurity of the eluted RNA were measured at an absorb -\nance of 260 and 280 nm using an Infinite ®200 PRO \nNanoQuant (Tecan, Zürich, Switzerland). Using the \nmiScript II RT kit (catalog no. 218160, Qiagen), 1 μg \nof RNA was reverse-transcribed into cDNA encoding \nmiRNAs in reverse-transcription reaction components \n\nPage 3 of 15\nMahmoud et al. The Journal of Basic and Applied Zoology            (2025) 86:1 \n \nof 5X hi-spec buffer, 10 × miScript Nucleics Mix, and \nmiScript reverse transcriptase mix. The reaction was \nincubated for 60 min at 37 °C in Veriti ™  96-Well Ther-\nmal Cycler (Applied Biosystem, CA, USA) followed \nby 5  min at 95  °C to inactivate miScript reverse tran -\nscriptase mix. To determine the mRNA expression level \nof the LUM gene, the RevertAid First Strand cDNA Kit \n(cat. no. k1622, Thermo Scientific, Vilnius, Lithuania) \nwas used to reverse transcribe total RNA (1 μg) into \ncDNA as we described before (Fahim et al., 2020).\nQuantitative real‑time PCR\nThe relative miRNA expression levels were quanti -\nfied using the miScript SYBR Green PCR Kit (cat. \nno.218073, Qiagen) and miScript Primer Assays \n(Qiagen) for 11-selected miRNAs: hsa-miR-21-5p \n(MS00009079), hsa-miR-200c-3p (MS00003752), \nhsa-miR-19a-3p (MS00003192), hsa-miR-203-3p \n(MS00003766), hsa-miR-181b-5p (MS00006699), \nhsa-miR-182-5p (MS00008855), hsa-miR-let7a-\n5p (MS00031220), hsa-miR-205-5p (MS00003780), \nhsa-miR-200b-3p (MS00009016), hsa-miR-16-5p \n(MS00031493), and hsa-miR-222-3p (MS00007609). \nFor the screening of 11-selected miRNA expression lev -\nels, an equal concentration of the isolated RNA (ovar -\nian endometriomas, n = 10 and eutopic endometrial \ntissues, n = 8) was pooled and reverse transcribed into \ncDNA. For the validation step, RNA isolated from ovar -\nian endometriomas (n = 14) and eutopic endometrial \ntissues (n = 8) was individually reverse transcribed into \ncDNA. Data were normalized to the endogenous ribo -\nnuclear RNA RNU6-2-11 (MS00033740). The cycling \nconditions used for miRNAs were as follows: 15  min \ninitial activation at 95 °C step, then 40 cycles consisting \nof 15 s at 94 °C, 30 s at 55 °C, and 30 s at 70 °C. The rela -\ntive mRNA expression levels of LUM  normalized to the \nendogenous housekeeping gene β-actin (ACTB ) were \nassessed using Maxima SYBR Green qPCR Master Mix \n(2X) (cat. No. k1061, Thermo Scientific, Vilnius, Lithu -\nania) in StepOnePlus ™  Real-Time PCR System (Applied \nBiosystems). The cycling conditions used for mRNAs \nare as follows: A 10 min-initial activation step at 95 °C, \nthen 40 cycles consisting of 15 s at 95 °C, and 1 min at \n60 °C. The  2−ΔΔCt  method was used to express the fold \nchange of miRNA and mRNA expression levels as we \npreviously described (Fahim et  al., 2020). The primer \nsequences used for LUM  were forward primers 5′ -AAC \nATA CCA ACT GTC AAT GAA AAC C-3′, reverse prim -\ners 5′ -TGC CAT CCA AAC GCA AAT GCTTG-3′ and \nfor ACTB were forward primer 5 ′-CAC CAT TGG CAA \nTGA GCG GTTC-3′ and reverse primer 5′ -AGG TCT \nTTG CGG ATG TCC ACGT-3′.\nIn‑silico analysis of miRNA target genes and pathways \nexploration\nTo find the possible targets of the dysregulated miRNA, \nwe utilized the miRbase (miRDB) (http:// mirdb. org/ \nindex. html) (accessed on August 1, 2024) (Pathan et al., \n2015, 2017). The predicted target genes (469 genes) were \nused to analyze the gene ontology (GO) function and \nthe Kyoto Encyclopedia of Genes and Genomes (KEGG) \nusing the online Database for Annotation, Visualization, \nand Integrated Discovery (DAVID) software (https:// \ndavid. ncifc rf. gov/ home. jsp) (accessed on August 1, 2024) \nusing FDR < 0.05 (Huang et al., 2009a, 2009b). Finally, the \nweb platform STRING (https:// string- db. org) (accessed \non August 1, 2024) integrated the protein–protein inter -\naction (PPI) network and identified key candidate genes \n(Hub Genes) and pathways (Szklarczyk et al., 2019).\nEnrichr database (Chen et  al. 2013; Xie et  al., 2021a) \n(https:// maaya nlab. cloud/ Enric hr/) (accessed on Octo -\nber 10, 2024) was used to identify the biological pathways \nassociated with LUM, ST3GAL6, C7, LRRC57, PTPRG, \nMATN2, ADAMTS3, FASLG, TLR4, ANXA1, TGFB2, \nTIMP3, S100A10, COL4A1, and LAMA4 representing \ngenes that are connected with LUM within the miR-\n21-5p target genes. This web-based software contains \nseveral gene set libraries, among which we used the Else -\nvier Pathway Collection analyses (Chen et al., 2013; Kule-\nshov et al., 2016; Xie et al., 2021b).\nStatistical analysis\nThe Statistical Package for Social Science (SPSS) version \n25 was used to analyze data. The normally distributed \ndata were evaluated using parametric tests, and a nor -\nmality test was performed using skewness and kurtosis. \nUsing the Student’s T-test, the statistical significance lev-\nels for the difference between the two groups were used. \nUsing Pearson’s correlation, the correlation between the \ntwo variables was evaluated. A p-value < 0.05 was con -\nsidered significant for all tests, and data are presented \nas mean ± SEM. GraphPad Prism 8 was used to generate \ngraphs.\nResults\nHistopathological examination of the endometria \nand endometriotic cysts\nBiopsies of eutopic endometrium and ovarian \nendometriotic cysts were obtained. Eutopic \nendometrium samples exhibit typical morphological \ncharacteristics of the endometrium (Franco-\nMurillo et  al., 2015), comprising tubular glands and \nendometrial stroma that are associated with blood \nvessels and immune cells (Yamaguchi et  al., 2021). \nOvarian endometriomas specimens were histologically \n\nPage 4 of 15Mahmoud et al. The Journal of Basic and Applied Zoology            (2025) 86:1 \nconfirmed by the presence of glands resembling \nthe endometrium, endometrial-like stroma, and an \naggregation of “hemosiderin-containing macrophages” \nthat is considered a unique histological feature of the \nendometriotic cyst (Fig.  1). Of note, two of the three \nhistological features of endometriosis are sufficient for \ndiagnosing the patient with endometriosis (Houghton \n& McCluggage, 2011).\nDistinct miRNAs expression pattern between ovarian \nendometriomas tissues compared to eutopic endometria \ntissues\nFor screening dysregulated 11-selected miRNAs, we \nperformed qPCR for cDNA from pooled samples of \n10 ovarian endometriomas and 8 eutopic endometrial \ntissue samples. Our qPCR data, as shown in Fig.  2, \nrevealed that miR-21-5p, miR-200c-3p, miR-19a-3p, \nmiR-203a-3p, miR-181b-5p, miR-182-5p, miR-\nlet-7a-5p, miR-205-5p, and miR-200b-3p were \nupregulated, whereas miR-16-5p and miR-222-3p were \ndownregulated in ovarian endometriomas compared to \neutopic endometria as depicted in Table 1 .\nUpregulation of miR‑21‑5p in ovarian endometriomas\nSince miR-21-5p, miR-let7a-5p, and miR-200b-3p were \nthe top upregulated miRNAs in pooled samples of \novarian endometriomas relative to eutopic endometria, \nwe verified the difference in their expression \nindividually. Interestingly, miR-21-5p was significantly \nupregulated (twofold change, P < 0.05) in ovarian \nendometriomas compared to eutopic endometrial \ntissue (Fig.  3A). miR-let7a-5p was downregulated \n(− 1.7-fold change, P > 0.05) (Fig. 3B), and miR-200b-3p \nwas upregulated (threefold change, P  > 0.05) in ovarian \nendometriomas relative to eutopic endometrial tissue. \nHowever, their expression did not reach a significant \nlevel (Fig. 3 C).\nPrediction of miR‑21‑5p target genes, Gene ontology \nfunction, and KEGG pathway analysis\nUsing the miRDB online database, we identified \nLUM as a potential target for miR-21-5p. qPCR \nresults demonstrated a significant downregulation of \nLUM expression (by − 0.75-fold, P < 0.05) in ovarian \nendometriomas compared to eutopic endometria \n(Fig.  4A). A positive correlation was observed between \nFig. 1 Histopathological sections of the normal endometria \nand ovarian endometriotic cysts. A Normal endometria proliferative \ntype showing endometrial glands (red arrow), stroma (blue arrow), \nand blood vessels (green arrow). B Sections of an endometriotic \ncyst of the ovary showing endometrial-type epithelium (red arrow), \nendometrial-type stroma (blue arrow), and hemosiderin-laden \nmacrophages (green arrow). Magnification: 400X\nFig. 2 Differentially expressed miRNAs in ovarian endometriomas \ncompared to eutopic endometrial tissues. The bar graph shows \nthe log2 fold change in expression levels of 11-selected miRNAs \nin ovarian endometriomas tissues (pooled n = 10) and eutopic \nendometrial tissues (pooled n = 8). miR-21-5p, miR-200c-3p, \nmiR-19a-3p, miR-203a-3p, miR-181b-5p, miR-182-5p, miR-let-7a-5p, \nmiR-205-5p, and miR-200b-3p were upregulated, while miR-16-5p \nand miR-222-3p were downregulated in ovarian endometriomas \nrelative to eutopic endometrial tissues\nTable 1 The fold change of differentially expressed miRNAs in \novarian endometriomas compared to eutopic endometrial tissue\nmiRNAs Log2 fold \nchange (2^‑\nΔΔCT)\nUpregulated\n miR-200b-3p 8.40\n miR-let-7a-5p 6.93\n miR-21-5p 5.08\n miR-200c-3p 4.42\n miR-19a-3p 3.37\n miR-203-3p 2.87\n miR-205-5p 2.34\n miR-181b-5p 1.97\n miR-182-5p 1.92\nDownregulated\n miR-16-5p − 1.11\n miR-222-3p − 5.00\n\nPage 5 of 15\nMahmoud et al. The Journal of Basic and Applied Zoology            (2025) 86:1 \n \nmiR-21-5p and LUM  in ovarian endometriomas tissue, \nwhile a negative correlation was found in eutopic \nendometrium. However, neither correlation reached \nstatistical significance (P > 0.05, Fig.  4B). This suggests \nthat miR-21-5p may regulate the expression of LUM  on \na posttranscriptional and/or translational level, but this \nspeculation should be verified in a future mechanistic \nstudy.\nSubsequently, we retrieved 469 target genes for miR-\n21-5p from the miRbase database (miRDB) and performed \na comprehensive analysis using the DAVID tool to explore \ngene ontology and KEGG pathways. The gene ontology \nanalysis, namely biological processes, cellular components, \nand molecular functions linked to the identified target \ngenes for miR-21-5p was performed. Notably, the biological \nprocesses included regulation of transcription, chromatin, \nand signal transduction, with key cellular components \nencompassing nucleus, cytosol, cytoplasm, and \nnucleoplasm. The molecular function category exhibited \nenrichment in protein, DNA, metal ion, zinc ion binding, \nprotein serine/threonine kinase activity, and sequence-\nspecific DNA interaction. All other functional annotations \nrelated to the targets of miR-21-5p are depicted in Table 2.\nMoreover, the KEGG analysis uncovered several path -\nways with a potential to contribute to ovarian endometrio-\nsis, including MAPK, P13K-Akt, RAS, miRNAs in cancer, \nproteoglycans in cancer, polycomb repressive, FoxO, TGF-\nbeta, EGFR, prolactin, and Hippo signaling pathways sign-\naling pathways as depicted in Table 3.\nFig. 3 qPCR for the expression of miR-21-5p, miR-let7a-5p, and miR-200b-3p in ovarian endometriomas and eutopic endometria. The relative \nmiRNA expression levels of miR-21-5p (A), miR-let7a-5p (B), and miR-200b-3p (C) in ovarian endometriomas (n = 10–14) compared to eutopic \nendometrial tissue (n = 8). Bars represent means ± SEM. *P < 0.05 as determined by Student’s t-test\nFig. 4 A The mRNA expression levels of the LUM assessed by qPCR in ovarian endometriomas (n = 14) compared to eutopic endometria tissue \n(n = 8). Bars represent means ± SEM. *P < 0.05 as determined by Student’s t-test. B Pearson’s correlation between miR-21–2-5p and LUM level \nin eutopic endometria (n = 8) and ovarian endometriomas tissues (n = 14)\n\nPage 6 of 15Mahmoud et al. The Journal of Basic and Applied Zoology            (2025) 86:1 \nProtein–protein interaction network of predicted target \ngenes of miR‑21‑5p\nWe employed the String database to explore potential \nprotein–protein interaction networks among the \npredicted target genes (https:// string- db. org/), including \n469 proteins identified as miR-21-5p targets. The \nresulting network unveiled numerous interactions \namong these proteins, forming three distinct clusters. \nThe first cluster, comprising 173 proteins, is associated \nwith molecular function (specifically Glycogen \nbinding), KEGG pathways (such as Cytokine-Cytokine \nreceptor interaction), and subcellular localization in the \nextracellular region. The second cluster, consisting of 140 \nproteins, is linked to pathways involving Ras, NTRK2 \n(TRKB), and regulation of the microtubule cytoskeleton. \nThe third cluster of 153 proteins is associated with various \npathways, including notch, TGF-beta, p53, androgen, \nand prolactin. This comprehensive analysis of protein–\nprotein interaction networks sheds light on the intricate \nrelationships and functional implications of miR-21-5p \ntarget proteins, providing valuable insights into their \nroles in different biological processes and pathways \n(Fig. 5). Within the PPI network, LUM was found to be \ndirectly connected with several proteins, including LUM, \nST3GAL6, C7, LRRC57, PTPRG, MATN2, ADAMTS3, \nFASLG, TLR4, ANXA1, TGFB2, TIMP3, S100A10, \nCOL4A1, and LAMA4 indicating potential interactions \nthat could influence its biological role and involvement \nin various signalling pathways (Fig.  6A). In addition, \nEnrichr database (https:// maaya nlab. cloud/ Enric hr/) was \nemployed to elucidate the functional pathways associated \nwith LUM, ST3GAL6, C7, LRRC57, PTPRG, MATN2, \nADAMTS3, FASLG, TLR4, ANXA1, TGFB2, TIMP3, \nS100A10, COL4A1, and LAMA4 representing genes that \nare connected with LUM within the miR-21-5p target \ngenes. The functional enrichment analysis based on \nElsevier Pathway Collection analyses revealed that these \nproteins are involved in endometriosis (Fig. 6B).\nDiscussion\nIn our study, we screened for 11-selected dysregulated \nmiRNA expressions and their potential targets, which \nmay be involved in the pathogenesis of endometriosis. \nOur qPCR results revealed the overexpression of \ndifferent miRNAs, namely, miR-21-5p, miR-200c-3p, \nmiR-19a-3p, miR-203-3p, miR-181b-5p, miR-182-5p, \nmiR-let7a-5p, and miR-200b-3p, whereas two miRNAs, \nmiR-16-5p and miR-222-3p, were downregulated \nin ovarian endometriomas compared to eutopic \nendometrial tissues. We further verified a significant \noverexpression of miR-21-5p in endometriomas \ncompared to eutopic endometria tissues. Different \nstudies reported miRNA signatures in endometriotic \nlesions and indicated altered levels of miR-1, miR-29c, \nmiR-34c, miR-141, miR-183, miR-196b, miR-145, miR-\n200a, miR-200b, miR-200c, miR-202, miR-100, miR-365, \nand miR-375 (Shantanam & Mueller, 2018). Several of \nthese miRNAs are also known to regulate angiogenesis, \ncell proliferation, invasion, and cell adhesion, in addition \nto epithelial-mesenchymal transition (EMT), unique \nhallmarks associated with endometriosis (Braicu et  al., \n2017; Saare et  al., 2017). Another study underscored \nanother set of dysregulated miRNAs such as miR-20a, \nmiR-15, miR-29c, miR-23a/b, miR-126, miR-142, miR-\n145, miR-183, miR-199a, and miR–451 in endometriotic \nlesions (Nothnick, 2017). These dysregulated miRNAs \nmay act as “drivers” that contributed to events of \nendometriosis pathophysiology or as “passengers” that \nwere altered due to disease pathogenesis (Nothnick, \n2017). miR-21 governs biological processes such as cell \nproliferation, invasion, and angiogenesis (Krichevsky \n& Gabriely, 2009). These processes are crucial for the \nestablishment and progression of endometriosis. In this \ncontext, our finding of elevated miR-21-5p expression \nfurther supports its role in ovarian endometriosis \nand agrees with different studies. For example, a very \nrecent study reported the role played by miR-21-5p in \novarian endometrial cysts, where the exosomal miR-\n21-5p derived from endometrial stromal cells augments \nproliferation, migration, and angiogenesis of human \numbilical vein endothelial cells (HUVECs) via targeting \nTIMP3 (Sun et al., 2024). miR-21-5p is the second most \nupregulated miRNA in women with endometriosis \n(Braza-Boïls et  al., 2014) and in endometrial epithelial \ntissue of porcine and mouse models during embryo \nimplantation, and its inhibition impedes proliferation \nand migration of endometrial cells, via programmed \ncell death 4 (PDCD4) (Hua et  al., 2020). Suppression of \nmiR-21 expression in endometrial stromal cells (HESCs) \nisolated from patients undergoing laparoscopic surgery \ninduces apoptotic cell death via caspase-3 overexpression \n(Park et  al., 2018). Another mechanistic study reported \nthat overexpression of long non-coding RNA (lnRNA) \nMEG3 inhibits endometrial cell proliferation and \ninvasion via downregulation of miR-21-5p (Yang et  al., \n2023), supporting our hypothesis that miR-21-5p may \ncontribute to the pathogenesis of endometriomas.\nInterestingly, a study reported that oncomiR-21 acts \nas a circulating biomarker for mild and severe forms of \nendometriosis (Rozati et  al., 2023), implying its useful -\nness as a future non-invasive biomarker for diagnosis of \npatients with ovarian endometriosis.\nEpithelial-mesenchymal transition (EMT) program \nplays a central role in endometriosis pathogenesis \n(Szymański et  al., 2024). A higher expression of miR-21 \nand lower expression of EMT markers TGF-β1, SMAD3, \n\nPage 7 of 15\nMahmoud et al. The Journal of Basic and Applied Zoology            (2025) 86:1 \n \nTable 2 Gene ontology analysis of miR-21-5p target genes\nCategory Term Count % P‑value\nBiological process Negative regulation of transcription by RNA polymerase II 54 11.6 0.00000\nPositive regulation of transcription by RNA polymerase II 60 12.9 0.00000\nNegative regulation of stem cell differentiation 6 1.3 0.00004\nProteasome-mediated ubiquitin-dependent protein catabolic process 15 3.2 0.00150\nRegulation of transcription by RNA polymerase II 55 11.8 0.00150\nPositive regulation of osteoblast differentiation 8 1.7 0.00190\nHippo signaling 5 1.1 0.00210\nInterleukin-6-mediated signaling pathway 4 0.9 0.00330\nRoof of mouth development 7 1.5 0.00350\nSignal transduction 43 9.2 0.00450\nGlycogen metabolic process 5 1.1 0.00530\nEphrin receptor signaling pathway 6 1.3 0.00540\nPositive regulation of protein phosphorylation 12 2.6 0.00660\nCellular response to cytokine stimulus 5 1.1 0.00660\nNegative regulation of neuron apoptotic process 10 2.1 0.00680\nCellular response to mechanical stimulus 7 1.5 0.00740\nSomatic stem cell population maintenance 6 1.3 0.00740\nRegulation of angiogenesis 5 1.1 0.00810\nProtein transmembrane transport 4 0.9 0.00810\nNegative regulation of transforming growth factor beta receptor signaling pathway 9 1.9 0.00830\nPositive regulation of MAPK cascade 11 2.4 0.00960\nBud elongation involved in lung branching 3 0.6 0.00960\nPositive regulation of epithelial cell migration 5 1.1 0.00980\nVentricular septum morphogenesis 5 1.1 0.00980\nPositive regulation of cell population proliferation 21 4.5 0.00980\nCartilage development 6 1.3 0.01400\nHemopoiesis 6 1.3 0.01400\nPositive regulation of bone mineralization 5 1.1 0.01400\nIntracellular signal transduction 18 3.9 0.01700\nHematopoietic stem cell homeostasis 4 0.9 0.01700\nNegative regulation of Ras protein signal transduction 4 0.9 0.01700\nPositive regulation of myoblast differentiation 5 1.1 0.01900\nProtein K48-linked ubiquitination 7 1.5 0.01900\nNuclear pore complex assembly 3 0.6 0.02000\nRegulation of glycogen biosynthetic process 3 0.6 0.02000\nPositive regulation of canonical Wnt signaling pathway 8 1.7 0.02000\nLung alveolus development 5 1.1 0.02000\nNegative regulation of epithelial to mesenchymal transition 5 1.1 0.02200\nmRNA transcription by RNA polymerase II 5 1.1 0.02300\n\nPage 8 of 15Mahmoud et al. The Journal of Basic and Applied Zoology            (2025) 86:1 \nTable 2 (continued)\nCategory Term Count % P‑value\nGlial cell migration 3 0.6 0.02400\nTransforming growth factor beta receptor signaling pathway 7 1.5 0.02400\nNegative regulation of translation 7 1.5 0.02400\nNegative regulation of BMP signaling pathway 6 1.3 0.02500\nEpithelial cell proliferation 5 1.1 0.02500\nNegative regulation of cell adhesion 5 1.1 0.02700\nNegative regulation of signal transduction 5 1.1 0.02700\nPositive regulation of Notch signaling pathway 5 1.1 0.02700\nOrgan induction 3 0.6 0.02800\nPositive regulation of hepatocyte proliferation 3 0.6 0.02800\nERK1 and ERK2 cascade 5 1.1 0.02800\nPositive regulation of phosphatidylinositol 3-kinase/protein kinase B signal transduction 10 2.1 0.02800\nPositive regulation of DNA-templated transcription 25 5.4 0.03000\nPhosphatidylinositol 3-kinase/protein kinase B signal transduction 6 1.3 0.03000\nOutflow tract morphogenesis 5 1.1 0.03000\nExtrinsic apoptotic signaling pathway 5 1.1 0.03000\nAnimal organ development 4 0.9 0.03100\nPositive regulation of ERK1 and ERK2 cascade 11 2.4 0.03200\nProtein import into nucleus 7 1.5 0.03200\nNegative regulation of DNA-templated transcription 21 4.5 0.03300\nNegative regulation of activin receptor signaling pathway 3 0.6 0.03300\nPositive regulation of nuclear-transcribed mRNA poly(A) tail shortening 3 0.6 0.03300\nPositive regulation of MAP kinase activity 5 1.1 0.03400\nEmbryonic forelimb morphogenesis 4 0.9 0.03600\nPositive regulation of cardiac muscle cell proliferation 4 0.9 0.03600\nFibroblast growth factor receptor signaling pathway 5 1.1 0.04000\nChondrocyte differentiation 5 1.1 0.04000\nOdontogenesis of dentin-containing tooth 5 1.1 0.04200\nRegulation of synaptic transmission, glutamatergic 4 0.9 0.04200\nProtein phosphorylation 15 3.2 0.04300\nRegulation of epithelial to mesenchymal transition 3 0.6 0.04300\nPositive regulation of nuclear-transcribed mRNA catabolic process, deadenylation-dependent decay 3 0.6 0.04300\nBMP signaling pathway 6 1.3 0.04300\nNegative regulation of mesenchymal cell proliferation involved in lung development 2 0.4 0.04400\nAMPA selective glutamate receptor signaling pathway 2 0.4 0.04400\nMuscle cell fate determination 2 0.4 0.04400\nViral RNA genome replication 2 0.4 0.04400\nHepatic stellate cell activation 2 0.4 0.04400\nRegulation of cell migration 7 1.5 0.04500\n\nPage 9 of 15\nMahmoud et al. The Journal of Basic and Applied Zoology            (2025) 86:1 \n \nTable 2 (continued)\nCategory Term Count % P‑value\nRegulation of ERK1 and ERK2 cascade 4 0.9 0.04500\nRegulation of cell population proliferation 8 1.7 0.04600\nPositive regulation of nitric-oxide synthase biosynthetic process 3 0.6 0.04800\nUreteric bud development 4 0.9 0.04900\nOligodendrocyte differentiation 4 0.9 0.04900\nCellular component Nucleoplasm 131 28.1 0.00000\nChromatin 51 10.9 0.00000\nNucleus 177 38 0.00001\nCytosol 161 34.5 0.00004\nCytoplasm 163 35 0.00005\nNuclear matrix 12 2.6 0.00012\nUbiquitin ligase complex 11 2.4 0.00020\nNuclear body 20 4.3 0.00022\nProtein-containing complex 30 6.4 0.00046\nGolgi apparatus 41 8.8 0.00093\nAdherens junction 13 2.8 0.00140\nPostsynaptic density 14 3 0.00260\nCollagen-containing extracellular matrix 19 4.1 0.00350\nSWI/SNF complex 5 1.1 0.00480\nEarly endosome membrane 12 2.6 0.00550\nRNA polymerase II transcription regulator complex 9 1.9 0.00640\nNuclear envelope 11 2.4 0.01700\nTranscription regulator complex 12 2.6 0.01800\nAxon 16 3.4 0.01900\nActin cytoskeleton 13 2.8 0.02000\nDendritic spine 9 1.9 0.02500\nIntracellular membrane-bounded organelle 30 6.4 0.02600\nProtein phosphatase type 1 complex 3 0.6 0.02700\nBRCA1-A complex 3 0.6 0.02700\nCell cortex 9 1.9 0.02900\nSpindle pole 8 1.7 0.03900\nFibrillar center 8 1.7 0.04700\nMolecular Function Protein binding 345 74 0.00000\nDNA-binding transcription factor activity 30 6.4 0.00002\nUbiquitin-protein transferase activity 16 3.4 0.00026\nDNA-binding transcription activator activity, RNA polymerase II-specific 25 5.4 0.00049\nTranscription cis-regulatory region binding 16 3.4 0.00055\nGlycogen binding 4 0.9 0.00092\nSignaling receptor binding 20 4.3 0.00095\nDNA-binding transcription factor activity, RNA polymerase II-specific 49 10.5 0.00200\nMetal ion binding 88 18.9 0.00210\nDNA-binding transcription factor binding 12 2.6 0.00220\nSequence-specific double-stranded DNA binding 25 5.4 0.00280\nRNA polymerase II cis-regulatory region sequence-specific DNA binding 45 9.7 0.00500\nSignaling adaptor activity 7 1.5 0.00510\nSequence-specific DNA binding 15 3.2 0.00640\n\nPage 10 of 15Mahmoud et al. The Journal of Basic and Applied Zoology            (2025) 86:1 \nand ILK genes are associated with loss of the endometrial \nepithelial phenotype and EMT in ovarian endometrioma \ncompared to matched eutopic endometrium (Zubrzycka \net al., 2023), further supporting the role of miR-21-5p in \novarian endometriosis.\nOur findings further revealed a significant \ndownregulation of LUM , a putative target of \nmiR-21-5p, in ovarian endometriomas compared to \neutopic endometrial tissues. LUM is important in \nmaintaining healthy tissue architecture (Chakravarti, \n2002). Additionally, in the tumor biology context, \nLUM expression is linked to signaling events relevant \nto pro- or anti-tumorigenic consequences. Most of its \npro-tumorigenic actions are shown in stomach, liver, \nand bladder cancers and are associated with a poorer \nclinical prognosis. The pro-tumorigenic activities of \nLUM activate FAK, MAPK, and MMP-9 (Appunni \net al., 2021; Chen et al., 2017; De Wit et al., 2017; Hsiao \net  al., 2020; Radwanska et  al., 2012). On the contrary, \nLUM has anticancer actions in breast and pancreatic \ncancers, as well as in melanoma that are linked to \npositive clinical outcomes (Appunni et al., 2021; Brezillon \net  al., 2009; Brézillon et  al., 2007; Stasiak et  al., 2016; \nYang et  al., 2018). The anti-tumor activity of LUM was \nassociated with the reduction of cancer cell invasion and \nmigration. So, increased migration may be associated \nwith decreased LUM expression (Appunni et  al., 2021; \nHsiao et  al., 2020; Yang et  al., 2018). In the context of \nendometriosis, the notion of downregulated LUM in \nour study suggests that LUM may function similarly to \nits role in cancer by influencing cellular behaviors, such \nas invasion and migration. Given its involvement in \nECM remodeling, reduced LUM levels could facilitate a \nmore permissive environment for the invasive capacity \nof ectopic endometrial tissue. Although only a few \nstudies have examined LUM’s role in endometriosis, \nthere are conflicting findings: two studies reported \nTable 2 (continued)\nCategory Term Count % P‑value\nProtein serine/threonine kinase activity 18 3.9 0.00730\nGrowth factor activity 10 2.1 0.01400\nChromatin binding 21 4.5 0.01800\nProtein serine kinase activity 16 3.4 0.02200\nSingle-stranded RNA binding 5 1.1 0.02400\nTranscription coregulator activity 8 1.7 0.02600\nZinc ion binding 31 6.7 0.02600\nlncRNA binding 4 0.9 0.02800\nmRNA 3′-UTR AU-rich region binding 4 0.9 0.02800\nNuclear receptor activity 5 1.1 0.03500\nBeta-catenin binding 7 1.5 0.04200\nChromatin DNA binding 6 1.3 0.04800\nRibonucleoprotein complex binding 4 0.9 0.04900\nCount: the number of target genes associated with each term in gene ontology category.\n%: indicates the proportion of target genes associated with each term in gene ontology category.\nP-value: represents the statistical significance of enrichment for each term.\nTable 3 Kyoto Encyclopedia of Genes and Genomes (KEGG) \npathway analysis of miR-21-5p\nTerm Count % P‑value\nMAPK signaling pathway 19 4.1 0.0004\nPI3K-Akt signaling pathway 17 3.6 0.015\nRas signaling pathway 15 3.2 0.0019\nMicroRNAs in cancer 14 3 0.041\nProteoglycans in cancer 13 2.8 0.0044\nPolycomb repressive complex 10 2.1 0.0002\nFoxO signaling pathway 10 2.1 0.0047\nHepatitis C 10 2.1 0.015\nHepatitis B 10 2.1 0.018\nAmoebiasis 9 1.9 0.0034\nTGF-beta signaling pathway 9 1.9 0.0049\nNeurotrophin signaling pathway 9 1.9 0.0086\nEGFR tyrosine kinase inhibitor resistance 7 1.5 0.013\nInsulin resistance 7 1.5 0.049\nProlactin signaling pathway 6 1.3 0.028\nNon-small cell lung cancer 6 1.3 0.031\nHippo signaling pathway—multiple species 4 0.9 0.033\n\nPage 11 of 15\nMahmoud et al. The Journal of Basic and Applied Zoology            (2025) 86:1 \n \nLUM’s upregulation in endometriosis (Irungu et  al., \n2019; Sahar et  al., 2021), while another report revealed \ndownregulation of LUM in mural granulosa cells from \nwomen with endometriosis (Kedem et  al., 2022). These \ndiscrepancies in the expression of LUM across different \nstudies, including ours, could be due to differences in the \nFig. 5 The protein–protein interactions network for miR-21-5p target genes retrieved from the string database (https:// string- db. org/) shows \nthe three clusters of interconnected proteins\n\nPage 12 of 15Mahmoud et al. The Journal of Basic and Applied Zoology            (2025) 86:1 \ntypes of ectopic endometrial lesions analyzed, staging of \nendometriosis, phases of the uterine cycle (proliferative \nvs. secretory), or methodological variations of detection.\nAlthough the in-silico analysis identified LUM as a \nputative target of miR-21-5p, our results did not reveal \na negative correlation between miR-21-5p and LUM in \novarian endometrioma. Direct regulation of LUM by miR-\n21-5p needs to be elucidated in a future study using an \nin  vitro model of endometrial cells. Our further several \ntarget genes, including LUM, of miR-21-5p are involved in \nmultiple signalling pathways, such as MAPK, P13K-Akt, \nRAS, proteoglycan, TGF-beta, EGFR, and Hippo signal -\ning pathways signalling pathways, known to be implicated \nin several relevant biological processes in endometriosis \npathogenesis, such as the invasion, migration, differen -\ntiation, and adhesion of cells (Ahrenset al., 2020; Glaviano \net  al., 2023; Huang & Chen, 2012; Iozzo & Sanderson, \n2011; Molina & Adjei, 2006; Paplomata & O’regan, 2014; \nWei & Liu, 2002; Zenonos & Kyprianou, 2013).\nThe limitations that could be associated with this study \nare the relatively small sample size and experimental \nvalidation of the direct targeting of LUM by miR-21-5p \nusing an in vitro model. However, some points should be \nconsidered, such as the challenges associated with diag -\nnosing ovarian endometriosis and its low incidence rate \n(Macer & Taylor, 2012; Nnoaham et al., 2011).\nConclusion\nOverall, this study unveiled that miR-21-5p was \nupregulated, while its putative target LUM  was \ndownregulated, and that their dysregulated expressions \nmay be involved in the pathogenesis of ovarian \nFig. 6 A The protein–protein interactions network for LUM with other target genes identified for miR-21-5p was retrieved from the string database \n(https:// string- db. org/). (Accessed on 15 October 2024) B The functional pathway enrichment analysis of the proteins in the PPI network is based \non the Elsevier Pathway Collection using the Enrichr database (https:// maaya nlab. cloud/ Enric hr/) (Accessed on 15 October 2024)\nendometriosis. We suggest that  miR-21-5p and LUM  \ncould be used as potential markers for future validation \nin a large cohort for ovarian endometriosis. Additional \nresearch is required to delineate the exact molecular \nmechanism(s) underlying the dysregulated expression of \nmiR-21-5p and LUM in ovarian endometriosis.\nAbbreviations\nACTB  β-Actin\nAUC   Area under the curve\nDAVID  Database for annotation, visualization, and integrated discovery\nEMT  Epithelial-mesenchymal transition\nFDR  False discovery rate\nGO  Gene ontology\nHESCs  Endometrial stromal cells\nIRB  Institutional review board\nKEGG  Kyoto Encyclopedia of Genes and Genomes\nLUM  Lumican\nmRNA  Messenger RNA\nniRNA  MicroRNA\nPDCD4  Programmed cell death 4\nPPI  Protein-protein interaction\nqPCR  Quantitative real-time PCR\nROC  Receiver operating characteristic\nSEM  Standard error of the mean\nSLRPs  Short leucine-rich proteoglycans\nUTR   Untranslated region\nVMP1  Vacuole membrane protein 1\nAcknowledgements\nThis work has been performed at the Cellular and Molecular Biosciences \nResearch Laboratory at the Department of Zoology, Faculty of Science, Cairo \nUniversity.\nAuthor contributions\nConceptualization: SAI and HH. Data curation: MM, AAW, SAI, and HH. Inves-\ntigation: MM, AAW, RSS, AB, SAI and HH. Methodology: MM, AAW, SE, MS, OA, \nRSS, SAI and HH. Resources: SAI. Supervision: AB, SAI, and HH. Writing – original \ndraft: MM, AAW, RSS, SAI, and HH. Writing – review & editing: MM, AAW, MS, AS, \nSE, MS, OA, RSS, AB, SAI and HH.\nFunding\nNot applicable.\n\nPage 13 of 15\nMahmoud et al. The Journal of Basic and Applied Zoology            (2025) 86:1 \n \nAvailability of data and materials\nThe datasets used and/or analyzed during the current study are available from \nthe corresponding author on reasonable request.\nDeclarations\nEthics approval and consent to participate\nThis study was approved by the institutional review board (IRB) at the Faculty \nof Medicine, Al-Azhar University (protocol number: 0000195) and the local \nEthics Committee of the Faculty of Medicine at Aswan University (Protocol No. \nAsw.U./677/10/22). All patients who participated in the study signed a consent \nform to participate in this study.\nConsent for publication\nAll patients who participated in the study signed a consent form to Publish in \nthis study.\nCompeting interests\nThe authors declare no conflict of interest does exist.\nReceived: 8 September 2024   Accepted: 29 November 2024\nReferences\nAhrens, T. D., Bang-Christensen, S. R., Jørgensen, A. M., Løppke, C., Spliid, C. B., \nSand, N. T., Clausen, T. M., Salanti, A., & Agerbæk, M. Ø. (2020). The role of \nproteoglycans in cancer metastasis and circulating tumor cell analysis. \nFrontiers in Cell and Developmental Biology, 8, 749. https:// doi. org/ 10. 3389/ \nfcell. 2020. 00749\nAppunni, S., Rubens, M., Ramamoorthy, V., Anand, V., Khandelwal, M., Saxena, \nA., McGranaghan, P ., Odia, Y., Kotecha, R., & Sharma, A. (2021). Lumican, \npro-tumorigenic or anti-tumorigenic: A conundrum. 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