{"paper_id":"a51f7496-bae4-4d01-8ef0-373fbcca872d","body_text":"Iwasaki S, Kaneda K. Genes relating to biological … Drug Res 2022; 72: 523–533 | © 2022. Thieme. All rights reserved.\nOriginal Article\nThieme\nIntroduction\nEndometriosis is one of the most common gynecological diseases \nin women of reproductive age, and it is diagnosed in about 5 % to \n10 % of women during their reproductive years, which is approxi -\nmately 176 million women in the world [1]. Endometriosis is de -\nfined as the presence of endometrial-like lesions outside the uter-\nus, primarily in the peritoneum, ovaries, bowel, uterosacral liga -\nments, and fallopian tubes, which has a great impact on quality of \nlife [2]. The combined oral contraceptive pill and progestogens are \nwidely used as therapies for endometriosis [3]. Although they are \neffective for some symptoms of endometriosis such as pain, they \nare not a complete therapy; some patients show recurrence of the \ndisease after withdrawal of the therapy and one-third of patients \nare non-responders due to progesterone resistance [4]. Thus, new \ntherapeutic options which have a mechanism of action that is dif -\nferent from that of hormonal drugs and which act on endometrio-\ntic lesions are desirable for the treatment of endometriosis.\nTo achieve this goal, the extrapolation of information from ani-\nmal models to humans is essential; however, extrapolation is com-\nplicated because rodents do not develop endometriosis spontane-\nously [5]. Among the several rodent models available, the synge -\nneic mouse model is often used because it is considered to mimic \nGenes Relating to Biological Processes of Endometriosis: \nExpression Changes Common to a Mouse Model and Patients\n  \nAuthors\nShiho Iwasaki1, 2, Katsuyuki Kaneda 1\nAffiliations\n1 Laboratory of Molecular Pharmacology, Institute of \nMedical, Pharmaceutical and Health Sciences, Kanazawa \nUniversity, Kanazawa, Japan\n2 Discovery Research Laboratories, Nippon Shinyaku Co., \nLtd., Kyoto, Japan\nKey words\nendometriosis, mouse syngeneic model, DNA microarray, \npatients, differentially expressed genes, biological process\nreceived 06.01.2022  \naccepted 05.07.2022  \npublished online 02.09.2022\nBibliography\nDrug Res 2022; 72: 523–533\nDOI 10.1055/a-1894-6817\nISSN 2194-9379\n© 2022. Thieme. All rights reserved.\nGeorg Thieme Verlag, Rüdigerstraße 14,  \n70469 Stuttgart, Germany\nCorresponding\nShiho Iwasaki\nLaboratory of Molecular Pharmacology, Institute of Medical, \nPharmaceutical and Health Sciences, Kanazawa University\n920-1192 Kanazawa\nJapan \nTel.:  + 81-75-321-9179, Fax:  + 81-75-314-3269 \ns.iwasaki@po.nippon-shinyaku.co.jp\nSupplementary Material is available under \nhttps://doi.org/ 10.1055/a-1894-6817\nAb Str Act\nEndometriosis is one of the most common gynecological dis -\neases in women of reproductive age. Retrograde menstruation \nis considered a major reason for the development of endome-\ntriosis. The syngeneic transplantation mouse model is an endo-\nmetriosis animal model that is considered to mimic retrograde \nmenstruation. However, it remains poorly understood which \ngenetic signatures of endometriosis are reflected in this model. \nHere, we employed an in vivo syngeneic mouse endometriosis \nmodel and identified differentially expressed genes (DEGs) be\n-\ntween the ectopic and eutopic tissues using microarray analysis. \nThree gene expression profile datasets, GSE5108, GSE7305, and \nGSE11691, were downloaded from the Gene Expression Omni\n-\nbus database and DEGs between ectopic and eutopic tissues \nfrom the same patients were identified. Gene ontology analysis \nof the DEGs revealed that biological processes including cell ad-\nhesion, the inflammatory response, the response to mechanical \nstimulus, cell proliferation, and extracellular matrix organization \nwere enriched in both the model and patients. Of the 195 DEGs \ncommon to the model and patients, 154 showed the same ex-\npression pattern, and 28 of these 154 DEGs came up when Pub-\nMed was searched for each gene along with the terms “endome-\ntriosis” and “development”. This is the first comparison of the \nDEGs of the mouse syngeneic endometriosis model and those \nof patients, and we identified the biological processes common \nto the model and patients at the transcriptional level. This mod\n-\nel may be useful to evaluate the efficacy of drugs which target \nthese biological processes.\n523\nThis document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.\nArticle published online: 2022-09-02\n\nIwasaki S, Kaneda K. Genes relating to biological … Drug Res 2022; 72: 523–533 | © 2022. Thieme. All rights reserved.\nOriginal Article Thieme\nretrograde menstruation [6], which is one of the main causes of \nthe development of endometriosis [7]. However, few studies have \ncomprehensively compared the biological processes of endome -\ntriosis in patients and in the model, and the usefulness of this ani-\nmal model in the interpretation of the pathophysiology of endo -\nmetriosis in humans is not yet fully understood.\nIn recent years, transcriptome analysis has been one of the tech-\nnologies most utilized to study human diseases at the gene expres-\nsion level, and it has contributed to the development of data inte-\ngration approaches to discover molecular biomarkers in human \npathologies and targets for new drugs [8]. Therefore, in the present \nstudy, we employed a syngeneic mouse endometriosis model and \nused transcriptome analysis to investigate the differentially ex-\npressed genes and the biological processes common to the model \nand endometriosis patients.\nMaterials and Methods\nAnimals\nSeven-week-old female BALB/cCrSlc mice (n = 65) were purchased \nfrom Japan SLC Inc. (Hamamatsu, Japan). The mice were housed \nunder conditions of controlled temperature (20–26 °C), humidity \n(35–75 %), and lighting (12-h light/dark cycle) with water and food \nad libitum. The study was conducted in compliance with the Inter-\nnal Regulations on Animal Experiments at Nippon Shinyaku Co., \nLtd. (Kyoto, Japan), which are based on the Law for the Humane \nTreatment and Management of Animals (Law No. 105, October 1, \n1973).\nOvariectomy and mouse model of endometriosis\nEight-week-old mice were anesthetized with Isoflurane Inhalation \nSolution [Pfizer] (Mylan Inc., Canonsburg, Pennsylvania, USA). The \nmice were ovariectomized through bilateral paravertebral incisions, \nand the muscular and skin incisions were closed with 6–0 black silk \nsuture. Butorphanol tartrate (1 mg/kg; Fujifilm Wako Pure Chemi-\ncal Co., Osaka, Japan) and ampicillin sodium (100 mg/kg; Viccillin; \nMeiji Seika Pharma Co., Ltd., Tokyo, Japan) were administered sub-\ncutaneously. At the end of the procedure, estradiol valerate in ses-\name oil (2 μg/animal) was administered intramuscularly every week \nto all mice. The day of ovariectomy was designated as day 0. On day \n7, the mice were divided into three groups by their body weight: \n10 mice in the sham group, 14 mice in the donor group, and 28 \nmice in the recipient group. To construct the syngeneic mouse en-\ndometriosis model, uterine tissues from the donor mice were har-\nvested and minced into small cell aggregates in Medium 199 with \nHanks’ Balanced Salts (Thermo Fisher Scientific, Inc., Waltham, \nMassachusetts, USA) supplemented with penicillin-streptomycin \nmixed solution (Nacalai Tesque Inc., Kyoto, Japan), then equal vol-\numes of uterine cell suspension were transferred into the perito -\nneal cavities of the recipient mice at a ratio of one donor to two re-\ncipients. For the sham group, the same volume of Medium 199 with \nHanks’ Balanced Salts was injected into the peritoneal cavities of \nthe mice. To reduce the local surgical response to trauma, we in -\ncised the upper right side of mice and transferred the uterine cell \nsuspension into their lower left peritoneal cavities through the in -\ndwelling needle. The wounds of the mice were closed with 6–0 \nblack silk suture and bupivacaine hydrochloride hydrate (2.5 mg/\nkg; Marcaine Injection; Aspen Japan Co., Ltd., Tokyo, Japan) and \nampicillin sodium (100 mg/kg) were administered subcutaneous -\nly. On day 35, the recipient mice were euthanized and all ectopic \ncysts and uterine tissues were carefully and exclusively removed \nfrom each mouse with a small scissors and forceps, infused with \nRNAlater solution (Thermo Fisher Scientific, Inc.) and stored at \n−80 °C for analysis of gene expression.\nMicroarray analysis\nTotal RNA were isolated from the mouse ectopic cystic tissue and \neutopic uterus using an RNeasy Lipid Tissue Mini Kit (Qiagen Inc., \nHilden, Germany) (n = 5 animals per group). The quality and concen-\ntration of the RNA was checked using an Agilent 2100 bioanalyzer. \nThe RNA Integrity Number (RIN) was used to evaluate RNA integrity \nand all samples used for the microarray analysis had RIN  ≥ 7.0. Puri-\nfied RNA was labeled by using the GeneChip WT Plus Reagent Kit \n(Thermo Fisher Scientific, Inc.), then hybridized to a Clariom S Mouse \nArray (Thermo Fisher Scientific, Inc.) according to the manufactur-\ner’s instructions. Experiments from RNA isolation to microarray anal-\nysis were conducted at Filgen, Inc. (Nagoya, Japan). Briefly, CEL files \nwere processed using Affymetrix Expression Console software (Ther-\nmo Fisher Scientific, Inc.) and subjected to normalization using the \nSignal Space Transformation-Robust Multiarray Analysis (SST-RMA) \nmethod for the following analysis. The number of probes detected \nwas 22,206 and genes whose expression changed at least two-fold \nwith p < 0.05 (Student’s t-test) in the ectopic cystic tissue compared \nto the eutopic tissue in the syngeneic endometriosis mouse model \nor in the eutopic tissue in the model compared to the sham group \nwere considered to be differentially expressed. Gene ontology (GO) \nanalysis was conducted on the significantly differentially expressed \ngenes (DEGs) using the Database for Annotation, Visualization and \nIntegrated Discovery [9] (DAVID; Laboratory of Human Retrovirol-\nogy and Immunoinformatics). GO terms for biological processes with \np < 0.05 (Fisher’s exact test with the Benjamini-Hochberg multiple-\ntesting correction) were considered significant. The datasets are \navailable from the National Center for Biotechnology Information/\nGene Expression Omnibus, and can be accessed with GSE190209.\nEndometriosis patient data collection\nThe BaseSpace Correlation Engine (Illumina, Inc., San Diego, Cali -\nfornia, USA) bioinformatics database was used to investigate the \nmicroarray gene expression profiles of the endometriosis patients, \nin which data were reanalyzed as determined by NextBio analysis \n[10]. We found three datasets (GSE5108 [11], GSE7305 [12] and \nGSE11691 [13]) in which the gene expression in ectopic tissue is \ncompared to that in eutopic tissue from the same patients.\nAnalysis of DEGs from patient datasets\nThe files from the three datasets were individually processed and \nnormalized according to the BaseSpace Correlation Engine plat-\nform, and genes whose expression changed in ectopic tissue at \nleast two-fold compared to eutopic tissue with p < 0.05 were con-\nsidered to be the DEGs of each dataset. The genes which showed \nthe same expression pattern (up-regulated or down-regulated) in \nat least two datasets were defined as the DEGs of the endometrio-\nsis patients. GO analysis was conducted on the DEGs of patients \n524\nThis document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.\n\n\nIwasaki S, Kaneda K. Genes relating to biological … Drug Res 2022; 72: 523–533 | © 2022. Thieme. All rights reserved.\nusing DAVID. GO terms for biological processes with p < 0.05 (Fish-\ner’s exact test with the Benjamini-Hochberg multiple-testing cor-\nrection) were considered significant.\nComparison of data between the syngeneic mouse \nendometriosis model and patients\nThe data for the GO analysis of the syngeneic mouse endometrio-\nsis model were combined with those of the patients, then GO terms \ncommon to them were identified using TIBCO Spotfire data analy-\nsis software (TIBCO Software Inc., Palo Alto, California, USA). The \nDEGs common to the model and patients were identified using the \nBaseSpace Correlation Engine. To investigate the relationship be -\ntween each common DEG and endometriosis, PubMed (National \nCenter for Biotechnology Information) was searched for each com-\nmon DEG along with the terms “endometriosis” or “endometrio -\nsis” and “development”. Studies on genes which were not shown \nto be associated with endometriosis in patients (e.  g., studies in \nani mal models only or on endometriosis-associated ovarian carci -\nnoma) were excluded.\nResults\nDEGs in the syngeneic mouse endometriosis model\nWe used DNA microarray analysis to identify the changes in gene \nexpression in the syngeneic mouse endometriosis model. Seven -\nty-seven out of 22,206 genes were differentially expressed in the \neutopic uterus of the model compared to that of sham-operated \nmice, comprising 54 up-regulated and 23 down-regulated genes, \nhereinafter referred to as the DEGs in the eutopic uterus (▶Fig. 1a). \nWe then investigated the DEGs in the ectopic cystic tissue of the \nmodel mice compared to those in their eutopic uteri. We identified \n1,154 out of 22,206 genes as DEGs, comprising 742 up-regulated \nand 412 down-regulated genes, and these are hereinafter referred \nto as the DEGs in ectopic tissue (▶Fig. 1b). These results show that \nthe expression of some genes was different between the eutopic \nand ectopic tissues of the model mice.\nDEGs in the endometriosis patients of three datasets \nfrom NCBI GEO\nWe identified DEGs in the endometriosis patients using three data-\nsets from NCBI GEO in which the gene expression between eutop-\nic and ectopic lesions from the endometriosis patients was com -\npared using microarray analysis. We identified 2633 genes in \nGSE5108, 3787 in GSE7305, and 494 in GSE11691. Of these, 950 \ngenes showed the same expression pattern in at least two datasets \nand were defined as the DEGs common to the patients. They com-\nprised 530 up-regulated and 420 down-regulated genes (▶Fig. 2).\nGO analysis of DEGs in the mouse model and \nendometriosis patients\nTo find biological processes associated with the DEGs, we used gene \nontology (GO) analysis. We found that DEGs in the eutopic uterus \nof the model mice represented the enrichment of two biological \nprocesses, the response to lipopolysaccharide and neutrophil \nchemotaxis (▶table 1). The DEGs in the ectopic tissue of the model \nmice represented the enrichment of 75 biological processes, in -\ncluding muscle contraction, cell adhesion, response to hypoxia, and \nthe inflammatory response ( Supplementary table 1). The DEGs \nin the patients represented the enrichment of 28 biological pro -\ncesses, including extracellular matrix organization, cell adhesion, \nand the inflammatory response (Supplementary table 2). We then \nmatched GO terms which were enriched both in the ectopic tissue \nof the model mice and in the patients, and found that 12 biologi -\ncal processes were common to them (▶ table 2 and ▶ Fig. 3), in-\ncluding cell adhesion, the inflammatory response, the response to \nmechanical stimulus, cell proliferation and extracellular matrix or-\nganization. This result suggests that these biological processes are \nimportant in both the model and patients.\n525\n▶Fig. 1 Results of DNA microarray analysis in the mouse endometriosis model. The volcano plots represent the DEGs between (a) the eutopic \nuterus in the sham mice and in the syngeneic endometriosis mouse model or (b) the eutopic uterus and ectopic tissue in the model. DEGs satisfy the \ncriteria log2(fold change) > 1 or < −1 and p < 0.05 (Student’s t-test). Significantly differentially expressed genes are shown as black dots. DEGs, differ-\nentially expressed genes.\nThis document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.\n\n\nIwasaki S, Kaneda K. Genes relating to biological … Drug Res 2022; 72: 523–533 | © 2022. Thieme. All rights reserved.\nOriginal Article Thieme\n526\nDEGs common to the syngeneic mouse \nendometriosis model and endometriosis patients\nTo identify gene-expression changes common to the model and the \npatients, we compared the DEGs between them. We found that they \nshared 195 DEGs, of which 154 showed the same expression pattern \n(that is, 115 genes were up-regulated and 39 were down-regulated \nin both the model and the patients; ▶table 3 and ▶Fig. 4). We de-\nfined these 154 genes as the DEGs common to the model and the \npatients. We then explored the gene annotations of the common \nDEGs, and found that some of them were annotated by GO terms \nwhich were enriched in both the model and patients (▶table 4).\nThe roles of DEGs common to the syngeneic mouse \nendometriosis model and endometriosis patients in \nendometriosis\nTo investigate possible roles played by the DEGs common to the \nmodel and the patients, we searched for a relationship between \n▶Fig. 2 Identification of DEGs in endometriosis patients. Datasets \n(GSE5108, GSE7305 and GSE11691) from the NCBI GEO database in \nwhich the gene expression of ectopic and ectopic tissue is compared \nwere used for analysis. The DEGs of each dataset were displayed in \nVenn diagrams and the overlapping DEGs, that is, DEGs which \nshowed the same expression pattern (up-regulated or down-regulat-\ned) in at least two datasets, were defined as common DEGs in the \nendometriosis patients.\n▶table 1 The significantly enriched biological processes associated with \nDEGs in the eutopic uterus of the mouse model\nGO term count p-value\nGO:0032496 response to lipopolysaccharide 7 0.03\nGO:0030593 neutrophil chemotaxis 5 0.03\n▶table 2 GO terms common to the syngeneic mouse endometriosis model and endometriosis patients\nGO term Mouse model Endometriosis patients\nGene c ount p-value Gene c ount p-value\nGO:0007155 cell adhesion 74 3.2.E-11 60 7.0.E-08\nGO:0006954 inflammatory response 51 6.7.E-07 46 1.1.E-04\nGO:0009612 response to mechanical stimulus 17 9.9.E-05 12 3.0.E-02\nGO:0008285 negative regulation of cell proliferation 47 3.6.E-04 38 3.8.E-02\nGO:0030198 extracellular matrix organization 22 3.8.E-04 37 5.1.E-08\nGO:0043627 response to estrogen 17 7.7.E-04 12 5.0.E-02\nGO:0001525 angiogenesis 33 1.0.E-03 29 3.1.E-03\nGO:0045766 positive regulation of angiogenesis 21 1.8.E-03 20 2.2.E-03\nGO:0007568 aging 24 1.1.E-02 21 3.8.E-02\nGO:0006955 immune response 32 1.4.E-02 45 2.2.E-03\nGO:0070098 chemokine-mediated signaling pathway 12 1.8.E-02 13 3.5.E-02\nGO:0048247 lymphocyte chemotaxis 9 2.6.E-02 8 5.0.E-02\n▶Fig. 3 Identification of biological processes common to the syn-\ngeneic mouse endometriosis model and endometriosis patients. \nGene ontology (GO) analysis was conducted using DEGs in the ec-\ntopic tissue of the model mice and the patients, and biological pro-\ncesses that were enriched in both were identified.\nThis document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.\n\n\nIwasaki S, Kaneda K. Genes relating to biological … Drug Res 2022; 72: 523–533 | © 2022. Thieme. All rights reserved.\n527\n▶table 3 DEGs common to the syngeneic mouse endometriosis model and endometriosis patients\nGene Description Fold changein \nmodel\nFold change in patients \n(average of 3 datasets)\nup-regulated genes\nHp Haptoglobin 468.70 9.18\nCfd complement factor D (adipsin) 405.34 6.15\nFabp4 fatty acid binding protein 4, adipocyte 280.26 30.81\nHspb6 heat shock protein, alpha-crystallin-related, B6 144.70 2.31\nSerpina3n serine (or cysteine) peptidase inhibitor, clade A, member 3 N 58.06 5.74\nCryab crystallin, alpha B 42.87 3.25\nHsd11b1 hydroxysteroid 11-beta dehydrogenase 1 41.74 20.65\nGpnmb glycoprotein (transmembrane) nmb 39.08 3.53\nLdb3 LIM domain binding 3 33.46 3.86\nCpxm2 carboxypeptidase X 2 (M14 family) 31.13 16.65\nRgs16 regulator of G-protein signaling 16 30.34 2.62\nSerpine2 serine (or cysteine) peptidase inhibitor, clade E, member 2 22.80 18.67\nThbs2 thrombospondin 2 20.39 4.11\nLrrc2 leucine rich repeat containing 2 17.94 4.20\nFilip1l filamin A interacting protein 1-like 17.62 3.99\nCol12a1 collagen, type XII, alpha 1 16.63 5.26\nFmod Fibromodulin 15.29 2.75\nThbs4 thrombospondin 4 12.82 3.89\nMgp matrix Gla protein 12.49 4.65\nTimp1 tissue inhibitor of metalloproteinase 1 12.08 5.25\nThbs1 thrombospondin 1 11.39 6.86\nC1qtnf7 C1q and tumor necrosis factor related protein 7 10.29 2.27\nItm2a integral membrane protein 2 A 9.54 7.11\nSfrp2 secreted frizzled-related protein 2 8.96 21.75\nIl7r interleukin 7 receptor 8.48 5.82\nSlit3 slit homolog 3 (Drosophila) 8.08 2.86\nItgbl1 integrin, beta-like 1 7.92 4.05\nAngptl1 angiopoietin-like 1 7.46 13.75\nSulf1 sulfatase 1 7.43 3.22\nBgn Biglycan 6.91 3.43\nGhr growth hormone receptor 6.84 2.79\nInhba inhibin beta-A 6.45 8.09\nCd163 CD163 antigen 6.37 5.35\nChl1 cell adhesion molecule with homology to L1CAM 5.96 36.95\nPdgfrl platelet-derived growth factor receptor-like 5.72 3.80\nFhl5 four and a half LIM domains 5 5.64 2.58\nOlfml1 olfactomedin-like 1 5.54 2.55\nNupr1 nuclear protein 1 5.43 2.37\nRcan2 regulator of calcineurin 2 5.20 8.91\nFrzb frizzled-related protein 5.04 5.21\nScn7a sodium channel, voltage-gated, type VII, alpha 4.81 37.20\nLyz2 lysozyme 2 4.75 4.23\nVgll3 vestigial like 3 (Drosophila) 4.62 3.04\nLhfp lipoma HMGIC fusion partner 4.53 3.59\nLbh limb-bud and heart 4.52 2.50\nWisp2 WNT1 inducible signaling pathway protein 2 4.52 13.38\nGfpt2 glutamine fructose-6-phosphate transaminase 2 4.37 2.24\nMsr1 macrophage scavenger receptor 1 4.36 3.90\nCtss cathepsin S 4.01 2.59\nThis document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.\n\n\nIwasaki S, Kaneda K. Genes relating to biological … Drug Res 2022; 72: 523–533 | © 2022. Thieme. All rights reserved.\nOriginal Article Thieme\n528\n▶table 3 DEGs common to the syngeneic mouse endometriosis model and endometriosis patients\nGene Description Fold changein \nmodel\nFold change in patients \n(average of 3 datasets)\nC4a complement component 4 A (Rodgers blood group) 3.97 7.01\nRgs5 regulator of G-protein signaling 5 3.85 3.40\nDpysl3 dihydropyrimidinase-like 3 3.84 8.99\nPrelp proline arginine-rich end leucine-rich repeat 3.80 7.90\nItgb2 integrin beta 2 3.65 2.42\nAspn aspirin 3.60 4.09\nMeox2 mesenchyme homeobox 2 3.55 3.09\nCbs cystathionine beta-synthase 3.53 2.58\nNrp2 neuropilin 2 3.47 8.76\nCcdc80 coiled-coil domain containing 80 3.43 8.69\nS100a6 S100 calcium binding protein A6 (calcyclin) 3.42 2.22\nFolr2 folate receptor 2 (fetal) 3.42 2.20\nKcnma1 potassium large conductance calcium-activated channel, subfamily M, alpha \nmember 1\n3.42 2.55\nPdlim5 PDZ and LIM domain 5 3.36 2.71\nPodn Podocan 3.34 4.29\nPlxdc2 plexin domain containing 2 3.32 2.78\nSteap4 STEAP family member 4 3.32 4.67\nLtbp2 latent transforming growth factor beta binding protein 2 3.08 6.01\nSpsb1 splA/ryanodine receptor domain and SOCS box containing 1 3.06 2.45\nEltd1 EGF, latrophilin seven transmembrane domain containing 1 2.99 2.30\nSytl2 synaptotagmin-like 2 2.96 5.78\nGpx3 glutathione peroxidase 3 2.91 10.59\nHmox1 heme oxygenase (decycling) 1 2.90 4.67\nChrdl1 chordin-like 1 2.88 5.43\nNcf4 neutrophil cytosolic factor 4 2.87 3.66\nLoxl1 lysyl oxidase-like 1 2.85 2.76\nRarres1 retinoic acid receptor responder (tazarotene induced) 1 2.78 7.20\nRerg RAS-like, estrogen-regulated, growth-inhibitor 2.75 5.45\nSep4 septin 4 2.75 3.94\nPdgfd platelet-derived growth factor, D polypeptide 2.71 5.77\nCol14a1 collagen, type XIV, alpha 1 2.69 3.54\nNfasc Neurofascin 2.68 14.96\nTspan7 tetraspanin 7 2.67 2.67\nColec12 collectin sub-family member 12 2.66 3.25\nIgsf6 immunoglobulin superfamily, member 6 2.65 2.96\nCdh5 cadherin 5 2.64 2.47\nPlvap plasmalemma vesicle associated protein 2.57 2.96\nClu Clusterin 2.55 8.12\nFry furry homolog (Drosophila) 2.55 3.56\nChi3l1 chitinase 3-like 1 2.55 9.68\nFcgr3 Fc receptor, IgG, low affinity III 2.54 5.88\nItga7 integrin alpha 7 2.53 3.01\nMan1c1 mannosidase, alpha, class 1 C, member 1 2.52 3.40\nDkk3 dickkopf homolog 3 (Xenopus laevis) 2.51 3.51\nTril TLR4 interactor with leucine-rich repeats 2.50 3.49\nPros1 protein S (alpha) 2.48 6.98\nFcgr2b Fc receptor, IgG, low affinity IIb 2.44 3.29\nJam2 junction adhesion molecule 2 2.44 2.92\nCcr1 chemokine (C-C motif) receptor 1 2.42 2.48\nContinued.\nThis document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.\n\n\nIwasaki S, Kaneda K. Genes relating to biological … Drug Res 2022; 72: 523–533 | © 2022. Thieme. All rights reserved.\n529\n▶table 3 DEGs common to the syngeneic mouse endometriosis model and endometriosis patients\nGene Description Fold changein \nmodel\nFold change in patients \n(average of 3 datasets)\nGrk5 G protein-coupled receptor kinase 5 2.26 2.93\nPde1a phosphodiesterase 1 A, calmodulin-dependent 2.26 3.38\nNpl N-acetylneuraminate pyruvate lyase 2.25 4.02\nPtprb protein tyrosine phosphatase, receptor type, B 2.25 2.54\nSerping1 serine (or cysteine) peptidase inhibitor, clade G, member 1 2.20 5.47\nGpr116 G protein-coupled receptor 116 2.14 3.21\nNr4a1 nuclear receptor subfamily 4, group A, member 1 2.13 2.31\nFst Follistatin 2.11 6.28\nCpa3 carboxypeptidase A3, mast cell 2.08 2.87\nAox1 aldehyde oxidase 1 2.08 17.10\nGnb4 guanine nucleotide binding protein (G protein), beta 4 2.08 2.36\nCd22 CD22 antigen 2.07 3.19\nNuak1 NUAK family, SNF1-like kinase, 1 2.05 3.74\nGpc6 glypican 6 2.03 3.29\n9430020K01Rik RIKEN cDNA 9430020K01 gene 2.02 3.09\nC7 complement component 7 2.02 73.71\nLaptm5 lysosomal-associated protein transmembrane 5 2.01 2.94\ndown-regulated genes\nHsd11b2 hydroxysteroid 11-beta dehydrogenase 2 −8.06 −5.61\nMogat1 monoacylglycerol O-acyltransferase 1 −7.94 −4.09\nKcnip4 Kv channel interacting protein 4 −6.37 −4.81\nGcnt3 glucosaminyl (N-acetyl) transferase 3, mucin type −5.21 −2.26\nCar12 carbonic anyhydrase 12 −5.21 −6.39\nSlc15a2 solute carrier family 15 (H + /peptide transporter), member 2 −4.27 −4.48\nPgbd5 piggyBac transposable element derived 5 −3.38 −4.45\nCrabp2 cellular retinoic acid binding protein II −3.28 −6.77\nMme membrane metallo endopeptidase −3.28 −4.71\nCkb creatine kinase, brain −3.27 −3.01\nKrt8 keratin 8 −3.23 −3.75\nKrt19 keratin 19 −3.19 −3.69\nTfcp2l1 transcription factor CP2-like 1 −3.13 −3.44\nTspan13 tetraspanin 13 −3.01 −3.43\nGalnt4 UDP-N-acetyl-alpha-D-galactosamine:polypeptide N-acetylgalactosaminyl\n-\ntransferase 4\n−2.93 −11.19\nAgr2 anterior gradient 2 (Xenopus laevis) −2.85 −11.16\nFam174b family with sequence similarity 174, member B −2.71 −2.27\nGalnt3 UDP-N-acetyl-alpha-D-galactosamine:polypeptide N-acetylgalactosaminyl -\ntransferase 3\n−2.71 −2.45\nRorb RAR-related orphan receptor beta −2.66 −7.46\nTspan1 tetraspanin 1 −2.53 −4.88\nGpsm2 G-protein signalling modulator 2 (AGS3-like, C. elegans) −2.51 −2.90\nAldh1a2 aldehyde dehydrogenase family 1, subfamily A2 −2.49 −9.64\nPrr15 proline rich 15 −2.44 −7.56\nRasef RAS and EF hand domain containing −2.36 −2.79\nEsr1 estrogen receptor 1 (alpha) −2.34 −7.53\nRev3l REV3-like, catalytic subunit of DNA polymerase zeta RAD54 like (S. cerevisiae) −2.34 −3.11\nPtn Pleiotrophin −2.31 −3.03\nTmem30b transmembrane protein 30B −2.29 −4.84\nCd24a CD24a antigen −2.26 −22.91\nQpct glutaminyl-peptide cyclotransferase (glutaminyl cyclase) −2.25 −4.16\nCndp2 CNDP dipeptidase 2 (metallopeptidase M20 family) −2.20 −3.14\nContinued.\nThis document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.\n\n\nIwasaki S, Kaneda K. Genes relating to biological … Drug Res 2022; 72: 523–533 | © 2022. Thieme. All rights reserved.\nOriginal Article Thieme\n530\nthe common DEGs and endometriosis by using PubMed. When we \nsearched for each gene along with the term “endometriosis”, 52 of \n154 genes came up (Supplementary table 3 and ▶Fig. 5). When \nwe searched for each gene along with the terms “endometriosis” \nand “development”, 23 genes came up that had some association \nwith endometriosis in patients (▶ table 5).\nDiscussion\nIn the present study, we found that biological processes including \ncell adhesion, the inflammatory response, the response to mechani-\ncal stimulus, cell proliferation, extracellular matrix organization \n(ECM), and the estrogen response were enriched in both the model \nand patients. We found that thrombospondin 1 (Thbs1), tissue in-\nhibitor of metalloproteinase 1 (Timp1), and cell adhesion molecule \nwith homology to L1CAM (Chl1) were up-regulated in both the \nmodel and patients. These genes are known to play a role in cell ad-\nhesion and/or ECM organization, biological processes important \nfor the attachment and invasion of ectopic cells in tissues [14–16]. \n▶table 3 DEGs common to the syngeneic mouse endometriosis model and endometriosis patients\nGene Description Fold changein \nmodel\nFold change in patients \n(average of 3 datasets)\nWfdc2 WAP four-disulfide core domain 2 −2.20 −10.44\nStxbp6 syntaxin binding protein 6 (amisyn) −2.16 −9.21\nRab25 RAB25, member RAS oncogene family −2.15 −5.87\nLlgl2 lethal giant larvae homolog 2 (Drosophila) −2.14 −2.27\nNpr2 natriuretic peptide receptor 2 −2.14 −2.80\nPpap2c phosphatidic acid phosphatase type 2 C −2.08 −4.03\nIrf6 interferon regulatory factor 6 −2.04 −5.03\nGjb6 gap junction protein, beta 6 −2.00 −5.75\n▶Fig. 4 Identification of DEGs common to the syngeneic mouse \nendometriosis model and endometriosis patients. DEGs in the ectopic \ntissue of the model mice were compared to those in the patients. The \nDEGs of each dataset were displayed in Venn diagrams and the over-\nlapping DEGs identified by selecting genes which showed the same \nexpression pattern (up-regulated or down-regulated).\n▶table 4 GO terms which were enriched in DEGs common to the synge-\nneic mouse endometriosis model and endometriosis patients\nGO term genes\ncell adhesion 17 Gpnmb, Thbs2, Col12a1, Thbs4, \nThbs1, Sulf1, Chl1, Wisp2, Itgb2, \nCol14a1, Nfasc, Cdh5, Itga7, Cd22, \nNuak1, 9430020K01Rik, Cd24a\ninflammatory response 6 Thbs1, Cd163, C4a, Chi3l1, Tril, Ccr1\nresponse to mechani\n-\ncal stimulus\n2 Thbs1, Chi3l1\nnegative regulation of \ncell proliferation\n13 Serpine2, Sfrp2, Slit3, Inhba, Frzb, \nWisp2, Podn, Hmox1, Rerg, Cdh5, \nAldh1a2, Irf6, Gjb6\nextracellular matrix \norganization\n1 Ccdc80\nresponse to estrogen 5 Kcnma1, Hmox1, Krt19, Esr1, Cd24a\nAngiogenesis 5 Meox2, Nrp2, Ccdc80, Hmox1, Ptprb\npositive regulation of \nangiogenesis\n5 Thbs1, Sfrp2, Itgb2, Hmox1, Chi3l1\nAging 5 Cryab, Timp1, Itgb2, Serping1, Gjb6\nimmune response 7 Thbs1, Ctss, Colec12, Fcgr2b, Ccr1, \nC7, Cd24a\nchemokine-mediated \nsignaling pathway\n1 Ccr1\n▶Fig. 5 Flowchart for Pubmed search. PubMed (National Center for \nBiotechnology Information) was searched for each common DEG \nalong with the term “endometriosis” or the terms “endometriosis” \nand “development”\nContinued.\nThis document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.\n\n\nIwasaki S, Kaneda K. Genes relating to biological … Drug Res 2022; 72: 523–533 | © 2022. Thieme. All rights reserved.\n531\nThus, these genes might be critical for the development of endo -\nmetriosis via cell attachment and invasion in both model and pa -\ntients. The inflammatory and immune responses are also critical to \nthe development of endometriosis. Single-cell analysis has shown \nthat T cells in endometriosis are less activated, cytotoxic T cell pop-\nulations and the proportion of natural killer cells in endometriosis \nlesions are decreased, and the ratio of monocytes to macrophages \nis increased in endometriosis cysts whose main population highly \nexpresses CD206 and CD163, which have been described as M2 \nmacrophage markers [17]. In the present study, the gene expres -\nsion of haptoglobin and CD163 was upregulated in both the model \nand patients. Haptoglobin is an acidic glycoprotein and ligand of \nCD163, which is a surface hemoglobin-haptoglobin scavenger re -\nceptor, and is related to the development of endometriosis [18]. \nThese results suggest that M2 macrophages might be critical for \nthe development of endometriosis in both model and patients. Fur-\nthermore, endometriosis is considered to be an estrogen-depend-\nent disease. Previous studies have shown that the aberrant expres-\nsion of hormone receptors in endometriosis lesions, including high \nestrogen receptor 2 (Esr2) to Esr1 ratios, is related progesterone \n▶table 5 The DEGs common to the model and patients along with the terms “endometriosis” and “development” found by searching PubMed\nGene Number of \npublications\nr eference lists\nup-regulated \ngenes\nHp 2 Piva M et al., Glycoconj J. 2002 Jan;19(1):33–41. Sharpe-Timms KL et al., Hum Reprod. 2000 Oct;15(10):2180–5.\nHsd11b1 1 Zhen Lin et al., J Food Biochem. 2021 May;45(5):e13717.\nTimp1 6 Luddi A et al., Int J Mol Sci. 2020 Apr 18;21(8):2840.Szymanowski K et al.,Ann Agric Environ Med. 2016 Dec \n23;23(4):649–653. Stilley JA et al., Biol Reprod. 2010 Aug 1;83(2):185–94. Collette T et al.,Hum Reprod. 2006 \nDec;21(12):3059–67. Li Y et al., Zhonghua Fu Chan Ke Za Zhi. 2006 Jan;41(1):30–3. Collette T et al., Hum Reprod. \n2004 Jun;19(6):1257–64.\nThbs1 3 Liu Y et al., Am J Reprod Immunol. 2020 Jun;83(6):e13236. Gilabert-Estellés J et al., Hum Reprod. 2007 \nAug;22(8):2120–7. Tan XJ et al., Fertil Steril. 2002 Jul;78(1):148–53.\nSlit3 1 Greaves E et al., Endocrinology. 2014 Oct;155(10):4015–26.\nInhba 1 Lin J et al., Mol Hum Reprod. 2011 Oct;17(10):605–11.\nCd163 3 Kusunoki M et al., Med Mol Morphol. 2021 Jun;54(2):122–132. Krasnyi AM et al., Biomed Khim. 2019 \nAug;65(5):432–436. Itoh F et al., Fertil Steril. 2013 May;99(6):1705–13.\nChl1 2 Jiang L et al., Int J Immunopathol Pharmacol. 2020 Jan-Dec;34:2058738420976309. Zhang C et al., Eur J Obstet \nGynecol Reprod Biol. 2019 May;236:177–182.\nPrelp 1 Araujo FM et al., Braz J Med Biol Res. 2017 Jul 3;50(7):e5782.\nItgb2 1 Sundqvist J et al., Hum Reprod. 2012 Sep;27(9):2737–46.\nS100a6 1 Peng Y et al., Gynecol Endocrinol. 2018 Sep;34(9):815–820.\nGpx3 1 Mirza Z et al., Diagnostics (Basel) . 2020 Jun 19;10(6):416.\nHmox1 2 Van LA et al., Fertil Steril. 2002 Mar;77(3):561–70. Imanaka S et al., Arch Med Res. 2021 Aug;52(6):641–647.\nFcgr3 1 Mei J et al., Autophagy. 2018;14(8):1376–1397.\nCcr1 3 Li T et al., Biomed Pharmacother. 2020 Sep;129:110476. Trummer D et al., Acta Obstet Gynecol Scand. 2017 \nJun;96(6):694–701. Kyama CM et al., Curr Med Chem. 2008;15(10):1006–17.\nNr4a1 1 Qingdong Z et al., Cell Physiol Biochem. 2018;45(3):1172–1190.\nFst 2 Kimber-Trojnar Ż et al., J Clin Med. 2021 Jun 23;10(13):2762. Luisi S et al., Womens Health (Lond). 2015 \nAug;11(5):603–10. \ndown-regulated \ngenes\nCrabp2 1 Sokalska A et al., J Clin Endocrinol Metab. 2013 Mar;98(3):E463–71.\nKrt19 1 Konrad L et al., Reprod Sci. 2019 Jan;26(1):49–59.\nAldh1a2 1 Jiang Y et al., J Endocrinol. 2018 Mar;236(3):R169-R188.\nEsr1 18 Wang J etal., Clin Lab. 2020 Aug 1;66(8). Huang ZX et al., J Cell Mol Med. 2020 Sep;24(18):10693–10704. Gibson DA \net al., J Endocrinol. 2020 Sep;246(3):R75-R93. Chantalat E et al., Int J Mol Sci. 2020 Apr 17;21(8):2815. Tang ZR et al., \nCells. 2019 Sep 21;8(10):1123. Yilmaz BD et al., Hum Reprod Update. 2019 Jul 1;25(4):473–485. Osiński M et al., \nGinekol Pol. 2018;89(3):125–134. Sapkota Y et al., Nat Commun. 2017 May 24;8:15539. Hamilton KJ et al., Curr Top \nDev Biol. 2017;125:109–146. Xiong W et al., Reproduction. 2015 Dec;150(6):507–16 Zhang Q et al., Gynecol Obstet \nInvest. 2015;80(3):187–92. Huang PC et al., Environ Sci Pollut Res Int. 2014 Dec;21(24):13964–73. Wang W et al., \nReprod Biomed Online. 2013 Jan;26(1):93–8 Li Y et al., Gene. 2012 Oct 15;508(1):41–8. Veillat V et al., Am J Pathol. \n2012 Sep;181(3):917–27. Matsuzaka Y et al., Environ Health Prev Med. 2012 Sep;17(5):423–8. Athanasios F et al., \nArch Gynecol Obstet. 2012 Apr;285(4):1001–7. Smuc T et al., Mol Cell Endocrinol. 2009 Mar 25;301(1–2):59–64.\nCd24a 1 Sundqvist J et al., Hum Reprod. 2012 Sep;27(9):2737–46.\nWfdc2 1 Chen T et al., J Clin Lab Anal. 2021 Sep;35(9):e23947.\nThis document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.\n\n\nIwasaki S, Kaneda K. Genes relating to biological … Drug Res 2022; 72: 523–533 | © 2022. Thieme. All rights reserved.\nOriginal Article Thieme\n532\nresistance [19]. In our study, the gene expression of Esr1 was de -\ncreased in both the model and patients, suggesting that the estro-\ngen response is also important in the pathogenesis of this model, \ndespite the fact that the rodent model does not exhibit menstrua-\ntion. Thus, this model partly reflects the pathophysiology of endo-\nmetriosis that occurs in humans as mentioned above, and it might \nbe useful for evaluating the efficacy of new therapeutic agents tar-\ngeting biological processes that include cell adhesion and ECM re-\nmodeling, inflammatory and immune responses, cell proliferation, \nangiogenesis, and the estrogen response.\nWe found for the first time that gene expression in the eutopic \nuterus was changed in the model, and the biological processes as-\nsociated with the genes whose expression was changed were re -\nsponse to lipopolysaccharide and neutrophil chemotaxis. Previous \nwork has shown that the expression of lipopolysaccharide in the \nendometrium of endometriosis patients is increased compared to \nthat in healthy controls [20]. These findings suggest that the model \nreflects the environment not only in ectopic lesions but also in the \neutopic endometrium of endometriosis patients.\nIn addition to this model, immunocompromised models, in \nwhich human endometrial tissue is injected into mice, are useful \nfor examining the multiple cellular pathways associated with the \ndevelopment of human endometriosis. However, immunocompro-\nmised models may not mimic the inflammatory or immune re -\nsponse of endometriosis patients because of the lack of a fully com-\npetent immune system in such mice [21]. The surgical immuno -\ncompetent model reflects the inflammation response, cell \nproliferation and the estrogen response of patients, yet it may not \nmimic early events in the development of endometriosis such as \nretrograde menstruation due to the surgical induction of ectopic \ngrowth [21]. There is reported to be no change in the levels of cy-\ntokeratin or E-cadherin in the epithelial cells of ectopic endometri-\num, or in the excessive collagen deposition or alpha-SMA positive \nmyofibroblasts in the ectopic endometrium of the surgical mouse \nendometriosis model [22]. In the present study, the expression of \ngenes related to the inflammatory or immune response and ECM \nremodeling was changed in the syngeneic mouse endometriosis \nmodel, indicating that this model may be distinct from other mod-\nels.\nA limitation of our study is that we did microarray analysis of \nwhole tissues at a specific time point. The model was found not to \nreflect some biological process in humans, such as endopeptidase \nactivity and platelet degranulation, at least under the present ex-\nperimental conditions. However, since the level of gene expression \nwould be expected to change with time after construction of the \nmodel, or according to the estrous cycle or the component cells, \nspatiotemporal single-cell RNA sequencing should be more effec-\ntive for future study. To obtain data on gene expression in endo -\nmetriosis patients, we used the gene expression data of endome -\ntriosis patients from three datasets in which the gene expression \nin ectopic tissue is compared to that in eutopic tissue, and reana -\nlyzed them in order to unify the analysis method between the pa -\ntient datasets. However, similar data would have been reported \nconsecutively, so we should also analyze those new data to increase \nthe sample size. Furthermore, in the future we should confirm the \nrelationship between disease severity and the gene expression of \nkey molecules which seem to be important for the development of \nthe disease. Additionally, it is not clear whether the DEGs common \nto the model and patients are the cause or the result of the patho-\ngenesis of endometriosis. To resolve this issue, experiments using \na suppressor or initiator for each gene are necessary. On the basis \nof the DEGs identified in this study, further work would be expect-\ned to clarify molecular mechanisms underlying the pathogenesis \nof endometriosis, which may lead to the identification of new bio-\nmarkers and/or treatment targets for this disease.\nAcknowledgements\nThe study was supported in part by Nippon Shinyaku Co., Ltd. We \nthank Dr. Gerald E. Smyth for English-language editing of the man-\nuscript.\nConflict of interest\nThe authors declare no conflict of interest.\nReferences\n[1] Giudice LC. Endometriosis. Clinical Practice. N Engl J Med 2010; 362: \n2389–2398\n[2] Nnoaham KE, Hummelshoj L, Webster P et al. World Endometriosis \nResearch Foundation Global Study of Women's Health Consortium. \nImpact of endometriosis on quality of life and work productivity: a \nmulticenter study across ten countries. Fertil Steril 2011; 96: 366–373\n[3] Kalaitzopoulos DR, Samartzis N, Kolovos GN et al. Treatment of \nendometriosis: a review with comparison of 8 guidelines. BMC \nWomen’s Health 2021; 21: 397\n[4] Donnez J, Dolmans MM. Endometriosis and medical therapy: from \nprogestogens to progesterone resistance to GnRH antagonists: a \nreview. J Clin Med 2021; 10: 1085\n[5] Laganà AS, Garzon S, Franchi M et al. Translational animal models for \nendometriosis research: a long and windy road. Ann Transl Med 2018; \nNov 6: 431\n[6] Burns KA, Rodriguez KF, Hewitt SC et al. Role of estrogen receptor \nsignaling required for endometriosis-like lesion establishment in a \nmouse model. Endocrinology. 2012; 153: 3960–39671\n[7] Sampson JA. Peritoneal endometriosis due to the menstrual \ndissemination of endometrial tissue into the peritoneal cavity. Am J \nObstet Gynecol 1927; 14: 422–469\n[8] Goulielmos GN, Matalliotakis M, Matalliotaki C et al. Endometriosis \nresearch in the -omics era. Gene. 2020; 741: 144545\n[9] Huang DW, Sherman BT, Lempicki RA. Systematic and integrative \nanalysis of large gene lists using DAVID Bioinformatics Resources. Nat \nProtoc 2009; 4: 44–57\n[10] Kupershmidt I, Su QJ, Grewal A et al. Ontology-based meta-analysis of \nglobal collections of high-throughput public data. PLoS One 2010; 5: \ne13066\n[11] Eyster KM, Klinkova O, Kennedy V et al. Whole genome \ndeoxyribonucleic acid microarray analysis of gene expression in \nectopic versus eutopic endometrium. Fertil Steril 2007; 88: 1505–\n1533\n[12] Hever A, Roth RB, Hevezi P et al. Human endometriosis is associated \nwith plasma cells and overexpression of B lymphocyte stimulator. Proc \nNat Acad Sci U S A. 2007; 104: 12451–12456\nThis document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.\n\n\nIwasaki S, Kaneda K. Genes relating to biological … Drug Res 2022; 72: 523–533 | © 2022. Thieme. All rights reserved.\n533\n[13] Hull ML, Escareno CR, Godsland JM et al. Endometrial-peritoneal \ninteractions during endometriotic lesion establishment. Am J Pathol \n2008; 173: 700–715\n[14] Ramón LA, Braza-Boïls A, Gilabert-Estellés J et al. microRNAs \nexpression in endometriosis and their relation to angiogenic factors. \nHum Reprod 2011; 26: 1082–1090\n[15] Luddi A, Marrocco C, Governini L et al. Expression of matrix \nmetalloproteinases and their inhibitors in endometrium: high levels in \nendometriotic lesions. Int J Mol Sci 2020; 21: 2840\n[16] Liu T, Liu M, Zheng C et al. Exosomal lncRNA CHL1-AS1 derived from \nperitoneal macrophages promotes the progression of endometriosis \nvia the miR-610/MDM2 axis. Int J Nanomedicine 2021; 16: 5451–5464\n[17] Ma J, Zhang L, Zhan H et al. Single-cell transcriptomic analysis of \nendometriosis provides insights into fibroblast fates and immune cell \nheterogeneity. Cell Biosci 2021; 11: 125\n[18] Zhong Q, Yang F, Chen X et al. Patterns of Immune Infiltration in \nEndometriosis and Their Relationship to r-AFS Stages. Front Genet \n2021; 12: 631715\n[19] Shao R, Cao S, Wang X et al. The elusive and controversial roles of \nestrogen and progesterone receptors in human endometriosis. Am J \nTransl Res 2014; 6: 104–113\n[20] Khan KN, Kitajima M, Hiraki K et al. Escherichia coli contamination of \nmenstrual blood and effect of bacterial endotoxin on endometriosis. \nFertil Steril 2010; 94: 2860–2863\n[21] Greaves E, Critchley HOD, Horne AW et al. Relevant human tissue \nresources and laboratory models for use in endometriosis research. \nActa Obstet Gynecol Scand 2017; 96: 644–658\n[22] Mishra A, Galvankar M, Vaidya S et al. Mouse model for endometriosis \nis characterized by proliferation and inflammation but not epithelial-\nto-mesenchymal transition and fibrosis. J Biosci 2020; 45: 105\nThis document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.","source_license":"CC0","license_restricted":false}