Genes Relating to Biological Processes of Endometriosis: Expression Changes Common to a Mouse Model and Patients

Endometriosis is one of the most common gynecological diseases in women of reproductive age, and it is diagnosed in about 5 % to 10 % of women during their reproductive years, which is approxi - mately 176 million women in the world [1]. Endometriosis is de - fined as the presence of endometrial-like lesions outside the uter- us, primarily in the peritoneum, ovaries, bowel, uterosacral liga - ments, and fallopian tubes, which has a great impact on quality of life [2]. The combined oral contraceptive pill and progestogens are widely used as therapies for endometriosis [3]. Although they are effective for some symptoms of endometriosis such as pain, they are not a complete therapy; some patients show recurrence of the disease after withdrawal of the therapy and one-third of patients are non-responders due to progesterone resistance [4]. Thus, new therapeutic options which have a mechanism of action that is dif - ferent from that of hormonal drugs and which act on endometrio- tic lesions are desirable for the treatment of endometriosis. To achieve this goal, the extrapolation of information from ani- mal models to humans is essential; however, extrapolation is com- plicated because rodents do not develop endometriosis spontane- ously [5]. Among the several rodent models available, the synge - neic mouse model is often used because it is considered to mimic Genes Relating to Biological Processes of Endometriosis: Expression Changes Common to a Mouse Model and Patients Authors Shiho Iwasaki1, 2, Katsuyuki Kaneda 1 Affiliations 1 Laboratory of Molecular Pharmacology, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa, Japan 2 Discovery Research Laboratories, Nippon Shinyaku Co., Ltd., Kyoto, Japan Key words endometriosis, mouse syngeneic model, DNA microarray, patients, differentially expressed genes, biological process received 06.01.2022 accepted 05.07.2022 published online 02.09.2022

Drug Res 2022; 72: 523–533 DOI 10.1055/a-1894-6817 ISSN 2194-9379 © 2022. Thieme. All rights reserved. Georg Thieme Verlag, Rüdigerstraße 14, 70469 Stuttgart, Germany Corresponding Shiho Iwasaki Laboratory of Molecular Pharmacology, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University 920-1192 Kanazawa Japan Tel.: + 81-75-321-9179, Fax: + 81-75-314-3269 [email protected] Supplementary Material is available under https://doi.org/ 10.1055/a-1894-6817 Ab Str Act Endometriosis is one of the most common gynecological dis - eases in women of reproductive age. Retrograde menstruation is considered a major reason for the development of endome- triosis. The syngeneic transplantation mouse model is an endo- metriosis animal model that is considered to mimic retrograde menstruation. However, it remains poorly understood which genetic signatures of endometriosis are reflected in this model. Here, we employed an in vivo syngeneic mouse endometriosis model and identified differentially expressed genes (DEGs) be - tween the ectopic and eutopic tissues using microarray analysis. Three gene expression profile datasets, GSE5108, GSE7305, and GSE11691, were downloaded from the Gene Expression Omni - bus database and DEGs between ectopic and eutopic tissues from the same patients were identified. Gene ontology analysis of the DEGs revealed that biological processes including cell ad- hesion, the inflammatory response, the response to mechanical stimulus, cell proliferation, and extracellular matrix organization were enriched in both the model and patients. Of the 195 DEGs common to the model and patients, 154 showed the same ex- pression pattern, and 28 of these 154 DEGs came up when Pub- Med was searched for each gene along with the terms “endome- triosis” and “development”. This is the first comparison of the DEGs of the mouse syngeneic endometriosis model and those of patients, and we identified the biological processes common to the model and patients at the transcriptional level. This mod - el may be useful to evaluate the efficacy of drugs which target these biological processes. 523 This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited. Article published online: 2022-09-02 Iwasaki S, Kaneda K. Genes relating to biological … Drug Res 2022; 72: 523–533 | © 2022. Thieme. All rights reserved. Original Article Thieme retrograde menstruation [6], which is one of the main causes of the development of endometriosis [7]. However, few studies have comprehensively compared the biological processes of endome - triosis in patients and in the model, and the usefulness of this ani- mal model in the interpretation of the pathophysiology of endo - metriosis in humans is not yet fully understood. In recent years, transcriptome analysis has been one of the tech- nologies most utilized to study human diseases at the gene expres- sion level, and it has contributed to the development of data inte- gration approaches to discover molecular biomarkers in human pathologies and targets for new drugs [8]. Therefore, in the present study, we employed a syngeneic mouse endometriosis model and used transcriptome analysis to investigate the differentially ex- pressed genes and the biological processes common to the model and endometriosis patients.

Animals Seven-week-old female BALB/cCrSlc mice (n = 65) were purchased from Japan SLC Inc. (Hamamatsu, Japan). The mice were housed under conditions of controlled temperature (20–26 °C), humidity (35–75 %), and lighting (12-h light/dark cycle) with water and food ad libitum. The study was conducted in compliance with the Inter- nal Regulations on Animal Experiments at Nippon Shinyaku Co., Ltd. (Kyoto, Japan), which are based on the Law for the Humane Treatment and Management of Animals (Law No. 105, October 1, 1973). Ovariectomy and mouse model of endometriosis Eight-week-old mice were anesthetized with Isoflurane Inhalation Solution [Pfizer] (Mylan Inc., Canonsburg, Pennsylvania, USA). The mice were ovariectomized through bilateral paravertebral incisions, and the muscular and skin incisions were closed with 6–0 black silk suture. Butorphanol tartrate (1 mg/kg; Fujifilm Wako Pure Chemi- cal Co., Osaka, Japan) and ampicillin sodium (100 mg/kg; Viccillin; Meiji Seika Pharma Co., Ltd., Tokyo, Japan) were administered sub- cutaneously. At the end of the procedure, estradiol valerate in ses- ame oil (2 μg/animal) was administered intramuscularly every week to all mice. The day of ovariectomy was designated as day 0. On day 7, the mice were divided into three groups by their body weight: 10 mice in the sham group, 14 mice in the donor group, and 28 mice in the recipient group. To construct the syngeneic mouse en- dometriosis model, uterine tissues from the donor mice were har- vested and minced into small cell aggregates in Medium 199 with Hanks’ Balanced Salts (Thermo Fisher Scientific, Inc., Waltham, Massachusetts, USA) supplemented with penicillin-streptomycin mixed solution (Nacalai Tesque Inc., Kyoto, Japan), then equal vol- umes of uterine cell suspension were transferred into the perito - neal cavities of the recipient mice at a ratio of one donor to two re- cipients. For the sham group, the same volume of Medium 199 with Hanks’ Balanced Salts was injected into the peritoneal cavities of the mice. To reduce the local surgical response to trauma, we in - cised the upper right side of mice and transferred the uterine cell suspension into their lower left peritoneal cavities through the in - dwelling needle. The wounds of the mice were closed with 6–0 black silk suture and bupivacaine hydrochloride hydrate (2.5 mg/ kg; Marcaine Injection; Aspen Japan Co., Ltd., Tokyo, Japan) and ampicillin sodium (100 mg/kg) were administered subcutaneous - ly. On day 35, the recipient mice were euthanized and all ectopic cysts and uterine tissues were carefully and exclusively removed from each mouse with a small scissors and forceps, infused with RNAlater solution (Thermo Fisher Scientific, Inc.) and stored at −80 °C for analysis of gene expression. Microarray analysis Total RNA were isolated from the mouse ectopic cystic tissue and eutopic uterus using an RNeasy Lipid Tissue Mini Kit (Qiagen Inc., Hilden, Germany) (n = 5 animals per group). The quality and concen- tration of the RNA was checked using an Agilent 2100 bioanalyzer. The RNA Integrity Number (RIN) was used to evaluate RNA integrity and all samples used for the microarray analysis had RIN ≥ 7.0. Puri- fied RNA was labeled by using the GeneChip WT Plus Reagent Kit (Thermo Fisher Scientific, Inc.), then hybridized to a Clariom S Mouse Array (Thermo Fisher Scientific, Inc.) according to the manufactur- er’s instructions. Experiments from RNA isolation to microarray anal- ysis were conducted at Filgen, Inc. (Nagoya, Japan). Briefly, CEL files were processed using Affymetrix Expression Console software (Ther- mo Fisher Scientific, Inc.) and subjected to normalization using the Signal Space Transformation-Robust Multiarray Analysis (SST-RMA)

for the following analysis. The number of probes detected was 22,206 and genes whose expression changed at least two-fold with p < 0.05 (Student’s t-test) in the ectopic cystic tissue compared to the eutopic tissue in the syngeneic endometriosis mouse model or in the eutopic tissue in the model compared to the sham group were considered to be differentially expressed. Gene ontology (GO) analysis was conducted on the significantly differentially expressed genes (DEGs) using the Database for Annotation, Visualization and Integrated Discovery [9] (DAVID; Laboratory of Human Retrovirol- ogy and Immunoinformatics). GO terms for biological processes with p < 0.05 (Fisher’s exact test with the Benjamini-Hochberg multiple- testing correction) were considered significant. The datasets are available from the National Center for Biotechnology Information/ Gene Expression Omnibus, and can be accessed with GSE190209. Endometriosis patient data collection The BaseSpace Correlation Engine (Illumina, Inc., San Diego, Cali - fornia, USA) bioinformatics database was used to investigate the microarray gene expression profiles of the endometriosis patients, in which data were reanalyzed as determined by NextBio analysis [10]. We found three datasets (GSE5108 [11], GSE7305 [12] and GSE11691 [13]) in which the gene expression in ectopic tissue is compared to that in eutopic tissue from the same patients. Analysis of DEGs from patient datasets The files from the three datasets were individually processed and normalized according to the BaseSpace Correlation Engine plat- form, and genes whose expression changed in ectopic tissue at least two-fold compared to eutopic tissue with p < 0.05 were con- sidered to be the DEGs of each dataset. The genes which showed the same expression pattern (up-regulated or down-regulated) in at least two datasets were defined as the DEGs of the endometrio- sis patients. GO analysis was conducted on the DEGs of patients 524 This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited. Iwasaki S, Kaneda K. Genes relating to biological … Drug Res 2022; 72: 523–533 | © 2022. Thieme. All rights reserved. using DAVID. GO terms for biological processes with p < 0.05 (Fish- er’s exact test with the Benjamini-Hochberg multiple-testing cor- rection) were considered significant. Comparison of data between the syngeneic mouse endometriosis model and patients The data for the GO analysis of the syngeneic mouse endometrio- sis model were combined with those of the patients, then GO terms common to them were identified using TIBCO Spotfire data analy- sis software (TIBCO Software Inc., Palo Alto, California, USA). The DEGs common to the model and patients were identified using the BaseSpace Correlation Engine. To investigate the relationship be - tween each common DEG and endometriosis, PubMed (National Center for Biotechnology Information) was searched for each com- mon DEG along with the terms “endometriosis” or “endometrio - sis” and “development”. Studies on genes which were not shown to be associated with endometriosis in patients (e. g., studies in ani mal models only or on endometriosis-associated ovarian carci - noma) were excluded.

DEGs in the syngeneic mouse endometriosis model We used DNA microarray analysis to identify the changes in gene expression in the syngeneic mouse endometriosis model. Seven - ty-seven out of 22,206 genes were differentially expressed in the eutopic uterus of the model compared to that of sham-operated mice, comprising 54 up-regulated and 23 down-regulated genes, hereinafter referred to as the DEGs in the eutopic uterus (▶Fig. 1a). We then investigated the DEGs in the ectopic cystic tissue of the model mice compared to those in their eutopic uteri. We identified 1,154 out of 22,206 genes as DEGs, comprising 742 up-regulated and 412 down-regulated genes, and these are hereinafter referred to as the DEGs in ectopic tissue (▶Fig. 1b). These results show that the expression of some genes was different between the eutopic and ectopic tissues of the model mice. DEGs in the endometriosis patients of three datasets from NCBI GEO We identified DEGs in the endometriosis patients using three data- sets from NCBI GEO in which the gene expression between eutop- ic and ectopic lesions from the endometriosis patients was com - pared using microarray analysis. We identified 2633 genes in GSE5108, 3787 in GSE7305, and 494 in GSE11691. Of these, 950 genes showed the same expression pattern in at least two datasets and were defined as the DEGs common to the patients. They com- prised 530 up-regulated and 420 down-regulated genes (▶Fig. 2). GO analysis of DEGs in the mouse model and endometriosis patients To find biological processes associated with the DEGs, we used gene ontology (GO) analysis. We found that DEGs in the eutopic uterus of the model mice represented the enrichment of two biological processes, the response to lipopolysaccharide and neutrophil chemotaxis (▶table 1). The DEGs in the ectopic tissue of the model mice represented the enrichment of 75 biological processes, in - cluding muscle contraction, cell adhesion, response to hypoxia, and the inflammatory response ( Supplementary table 1). The DEGs in the patients represented the enrichment of 28 biological pro - cesses, including extracellular matrix organization, cell adhesion, and the inflammatory response (Supplementary table 2). We then matched GO terms which were enriched both in the ectopic tissue of the model mice and in the patients, and found that 12 biologi - cal processes were common to them (▶ table 2 and ▶ Fig. 3), in- cluding cell adhesion, the inflammatory response, the response to mechanical stimulus, cell proliferation and extracellular matrix or- ganization. This result suggests that these biological processes are important in both the model and patients. 525 ▶Fig. 1 Results of DNA microarray analysis in the mouse endometriosis model. The volcano plots represent the DEGs between (a) the eutopic uterus 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 criteria 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- entially expressed genes. This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited. Iwasaki S, Kaneda K. Genes relating to biological … Drug Res 2022; 72: 523–533 | © 2022. Thieme. All rights reserved. Original Article Thieme 526 DEGs common to the syngeneic mouse endometriosis model and endometriosis patients To identify gene-expression changes common to the model and the patients, we compared the DEGs between them. We found that they shared 195 DEGs, of which 154 showed the same expression pattern (that is, 115 genes were up-regulated and 39 were down-regulated in both the model and the patients; ▶table 3 and ▶Fig. 4). We de- fined these 154 genes as the DEGs common to the model and the patients. We then explored the gene annotations of the common DEGs, and found that some of them were annotated by GO terms which were enriched in both the model and patients (▶table 4). The roles of DEGs common to the syngeneic mouse endometriosis model and endometriosis patients in endometriosis To investigate possible roles played by the DEGs common to the model and the patients, we searched for a relationship between ▶Fig. 2 Identification of DEGs in endometriosis patients. Datasets (GSE5108, GSE7305 and GSE11691) from the NCBI GEO database in which the gene expression of ectopic and ectopic tissue is compared were used for analysis. The DEGs of each dataset were displayed in Venn diagrams and the overlapping DEGs, that is, DEGs which showed the same expression pattern (up-regulated or down-regulat- ed) in at least two datasets, were defined as common DEGs in the endometriosis patients. ▶table 1 The significantly enriched biological processes associated with DEGs in the eutopic uterus of the mouse model GO term count p-value GO:0032496 response to lipopolysaccharide 7 0.03 GO:0030593 neutrophil chemotaxis 5 0.03 ▶table 2 GO terms common to the syngeneic mouse endometriosis model and endometriosis patients GO term Mouse model Endometriosis patients Gene c ount p-value Gene c ount p-value GO:0007155 cell adhesion 74 3.2.E-11 60 7.0.E-08 GO:0006954 inflammatory response 51 6.7.E-07 46 1.1.E-04 GO:0009612 response to mechanical stimulus 17 9.9.E-05 12 3.0.E-02 GO:0008285 negative regulation of cell proliferation 47 3.6.E-04 38 3.8.E-02 GO:0030198 extracellular matrix organization 22 3.8.E-04 37 5.1.E-08 GO:0043627 response to estrogen 17 7.7.E-04 12 5.0.E-02 GO:0001525 angiogenesis 33 1.0.E-03 29 3.1.E-03 GO:0045766 positive regulation of angiogenesis 21 1.8.E-03 20 2.2.E-03 GO:0007568 aging 24 1.1.E-02 21 3.8.E-02 GO:0006955 immune response 32 1.4.E-02 45 2.2.E-03 GO:0070098 chemokine-mediated signaling pathway 12 1.8.E-02 13 3.5.E-02 GO:0048247 lymphocyte chemotaxis 9 2.6.E-02 8 5.0.E-02 ▶Fig. 3 Identification of biological processes common to the syn- geneic mouse endometriosis model and endometriosis patients. Gene ontology (GO) analysis was conducted using DEGs in the ec- topic tissue of the model mice and the patients, and biological pro- cesses that were enriched in both were identified. This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited. Iwasaki S, Kaneda K. Genes relating to biological … Drug Res 2022; 72: 523–533 | © 2022. Thieme. All rights reserved. 527 ▶table 3 DEGs common to the syngeneic mouse endometriosis model and endometriosis patients Gene Description Fold changein model Fold change in patients (average of 3 datasets) up-regulated genes Hp Haptoglobin 468.70 9.18 Cfd complement factor D (adipsin) 405.34 6.15 Fabp4 fatty acid binding protein 4, adipocyte 280.26 30.81 Hspb6 heat shock protein, alpha-crystallin-related, B6 144.70 2.31 Serpina3n serine (or cysteine) peptidase inhibitor, clade A, member 3 N 58.06 5.74 Cryab crystallin, alpha B 42.87 3.25 Hsd11b1 hydroxysteroid 11-beta dehydrogenase 1 41.74 20.65 Gpnmb glycoprotein (transmembrane) nmb 39.08 3.53 Ldb3 LIM domain binding 3 33.46 3.86 Cpxm2 carboxypeptidase X 2 (M14 family) 31.13 16.65 Rgs16 regulator of G-protein signaling 16 30.34 2.62 Serpine2 serine (or cysteine) peptidase inhibitor, clade E, member 2 22.80 18.67 Thbs2 thrombospondin 2 20.39 4.11 Lrrc2 leucine rich repeat containing 2 17.94 4.20 Filip1l filamin A interacting protein 1-like 17.62 3.99 Col12a1 collagen, type XII, alpha 1 16.63 5.26 Fmod Fibromodulin 15.29 2.75 Thbs4 thrombospondin 4 12.82 3.89 Mgp matrix Gla protein 12.49 4.65 Timp1 tissue inhibitor of metalloproteinase 1 12.08 5.25 Thbs1 thrombospondin 1 11.39 6.86 C1qtnf7 C1q and tumor necrosis factor related protein 7 10.29 2.27 Itm2a integral membrane protein 2 A 9.54 7.11 Sfrp2 secreted frizzled-related protein 2 8.96 21.75 Il7r interleukin 7 receptor 8.48 5.82 Slit3 slit homolog 3 (Drosophila) 8.08 2.86 Itgbl1 integrin, beta-like 1 7.92 4.05 Angptl1 angiopoietin-like 1 7.46 13.75 Sulf1 sulfatase 1 7.43 3.22 Bgn Biglycan 6.91 3.43 Ghr growth hormone receptor 6.84 2.79 Inhba inhibin beta-A 6.45 8.09 Cd163 CD163 antigen 6.37 5.35 Chl1 cell adhesion molecule with homology to L1CAM 5.96 36.95 Pdgfrl platelet-derived growth factor receptor-like 5.72 3.80 Fhl5 four and a half LIM domains 5 5.64 2.58 Olfml1 olfactomedin-like 1 5.54 2.55 Nupr1 nuclear protein 1 5.43 2.37 Rcan2 regulator of calcineurin 2 5.20 8.91 Frzb frizzled-related protein 5.04 5.21 Scn7a sodium channel, voltage-gated, type VII, alpha 4.81 37.20 Lyz2 lysozyme 2 4.75 4.23 Vgll3 vestigial like 3 (Drosophila) 4.62 3.04 Lhfp lipoma HMGIC fusion partner 4.53 3.59 Lbh limb-bud and heart 4.52 2.50 Wisp2 WNT1 inducible signaling pathway protein 2 4.52 13.38 Gfpt2 glutamine fructose-6-phosphate transaminase 2 4.37 2.24 Msr1 macrophage scavenger receptor 1 4.36 3.90 Ctss cathepsin S 4.01 2.59 This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited. Iwasaki S, Kaneda K. Genes relating to biological … Drug Res 2022; 72: 523–533 | © 2022. Thieme. All rights reserved. Original Article Thieme 528 ▶table 3 DEGs common to the syngeneic mouse endometriosis model and endometriosis patients Gene Description Fold changein model Fold change in patients (average of 3 datasets) C4a complement component 4 A (Rodgers blood group) 3.97 7.01 Rgs5 regulator of G-protein signaling 5 3.85 3.40 Dpysl3 dihydropyrimidinase-like 3 3.84 8.99 Prelp proline arginine-rich end leucine-rich repeat 3.80 7.90 Itgb2 integrin beta 2 3.65 2.42 Aspn aspirin 3.60 4.09 Meox2 mesenchyme homeobox 2 3.55 3.09 Cbs cystathionine beta-synthase 3.53 2.58 Nrp2 neuropilin 2 3.47 8.76 Ccdc80 coiled-coil domain containing 80 3.43 8.69 S100a6 S100 calcium binding protein A6 (calcyclin) 3.42 2.22 Folr2 folate receptor 2 (fetal) 3.42 2.20 Kcnma1 potassium large conductance calcium-activated channel, subfamily M, alpha member 1 3.42 2.55 Pdlim5 PDZ and LIM domain 5 3.36 2.71 Podn Podocan 3.34 4.29 Plxdc2 plexin domain containing 2 3.32 2.78 Steap4 STEAP family member 4 3.32 4.67 Ltbp2 latent transforming growth factor beta binding protein 2 3.08 6.01 Spsb1 splA/ryanodine receptor domain and SOCS box containing 1 3.06 2.45 Eltd1 EGF, latrophilin seven transmembrane domain containing 1 2.99 2.30 Sytl2 synaptotagmin-like 2 2.96 5.78 Gpx3 glutathione peroxidase 3 2.91 10.59 Hmox1 heme oxygenase (decycling) 1 2.90 4.67 Chrdl1 chordin-like 1 2.88 5.43 Ncf4 neutrophil cytosolic factor 4 2.87 3.66 Loxl1 lysyl oxidase-like 1 2.85 2.76 Rarres1 retinoic acid receptor responder (tazarotene induced) 1 2.78 7.20 Rerg RAS-like, estrogen-regulated, growth-inhibitor 2.75 5.45 Sep4 septin 4 2.75 3.94 Pdgfd platelet-derived growth factor, D polypeptide 2.71 5.77 Col14a1 collagen, type XIV, alpha 1 2.69 3.54 Nfasc Neurofascin 2.68 14.96 Tspan7 tetraspanin 7 2.67 2.67 Colec12 collectin sub-family member 12 2.66 3.25 Igsf6 immunoglobulin superfamily, member 6 2.65 2.96 Cdh5 cadherin 5 2.64 2.47 Plvap plasmalemma vesicle associated protein 2.57 2.96 Clu Clusterin 2.55 8.12 Fry furry homolog (Drosophila) 2.55 3.56 Chi3l1 chitinase 3-like 1 2.55 9.68 Fcgr3 Fc receptor, IgG, low affinity III 2.54 5.88 Itga7 integrin alpha 7 2.53 3.01 Man1c1 mannosidase, alpha, class 1 C, member 1 2.52 3.40 Dkk3 dickkopf homolog 3 (Xenopus laevis) 2.51 3.51 Tril TLR4 interactor with leucine-rich repeats 2.50 3.49 Pros1 protein S (alpha) 2.48 6.98 Fcgr2b Fc receptor, IgG, low affinity IIb 2.44 3.29 Jam2 junction adhesion molecule 2 2.44 2.92 Ccr1 chemokine (C-C motif) receptor 1 2.42 2.48 Continued. This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited. Iwasaki S, Kaneda K. Genes relating to biological … Drug Res 2022; 72: 523–533 | © 2022. Thieme. All rights reserved. 529 ▶table 3 DEGs common to the syngeneic mouse endometriosis model and endometriosis patients Gene Description Fold changein model Fold change in patients (average of 3 datasets) Grk5 G protein-coupled receptor kinase 5 2.26 2.93 Pde1a phosphodiesterase 1 A, calmodulin-dependent 2.26 3.38 Npl N-acetylneuraminate pyruvate lyase 2.25 4.02 Ptprb protein tyrosine phosphatase, receptor type, B 2.25 2.54 Serping1 serine (or cysteine) peptidase inhibitor, clade G, member 1 2.20 5.47 Gpr116 G protein-coupled receptor 116 2.14 3.21 Nr4a1 nuclear receptor subfamily 4, group A, member 1 2.13 2.31 Fst Follistatin 2.11 6.28 Cpa3 carboxypeptidase A3, mast cell 2.08 2.87 Aox1 aldehyde oxidase 1 2.08 17.10 Gnb4 guanine nucleotide binding protein (G protein), beta 4 2.08 2.36 Cd22 CD22 antigen 2.07 3.19 Nuak1 NUAK family, SNF1-like kinase, 1 2.05 3.74 Gpc6 glypican 6 2.03 3.29 9430020K01Rik RIKEN cDNA 9430020K01 gene 2.02 3.09 C7 complement component 7 2.02 73.71 Laptm5 lysosomal-associated protein transmembrane 5 2.01 2.94 down-regulated genes Hsd11b2 hydroxysteroid 11-beta dehydrogenase 2 −8.06 −5.61 Mogat1 monoacylglycerol O-acyltransferase 1 −7.94 −4.09 Kcnip4 Kv channel interacting protein 4 −6.37 −4.81 Gcnt3 glucosaminyl (N-acetyl) transferase 3, mucin type −5.21 −2.26 Car12 carbonic anyhydrase 12 −5.21 −6.39 Slc15a2 solute carrier family 15 (H + /peptide transporter), member 2 −4.27 −4.48 Pgbd5 piggyBac transposable element derived 5 −3.38 −4.45 Crabp2 cellular retinoic acid binding protein II −3.28 −6.77 Mme membrane metallo endopeptidase −3.28 −4.71 Ckb creatine kinase, brain −3.27 −3.01 Krt8 keratin 8 −3.23 −3.75 Krt19 keratin 19 −3.19 −3.69 Tfcp2l1 transcription factor CP2-like 1 −3.13 −3.44 Tspan13 tetraspanin 13 −3.01 −3.43 Galnt4 UDP-N-acetyl-alpha-D-galactosamine:polypeptide N-acetylgalactosaminyl - transferase 4 −2.93 −11.19 Agr2 anterior gradient 2 (Xenopus laevis) −2.85 −11.16 Fam174b family with sequence similarity 174, member B −2.71 −2.27 Galnt3 UDP-N-acetyl-alpha-D-galactosamine:polypeptide N-acetylgalactosaminyl - transferase 3 −2.71 −2.45 Rorb RAR-related orphan receptor beta −2.66 −7.46 Tspan1 tetraspanin 1 −2.53 −4.88 Gpsm2 G-protein signalling modulator 2 (AGS3-like, C. elegans) −2.51 −2.90 Aldh1a2 aldehyde dehydrogenase family 1, subfamily A2 −2.49 −9.64 Prr15 proline rich 15 −2.44 −7.56 Rasef RAS and EF hand domain containing −2.36 −2.79 Esr1 estrogen receptor 1 (alpha) −2.34 −7.53 Rev3l REV3-like, catalytic subunit of DNA polymerase zeta RAD54 like (S. cerevisiae) −2.34 −3.11 Ptn Pleiotrophin −2.31 −3.03 Tmem30b transmembrane protein 30B −2.29 −4.84 Cd24a CD24a antigen −2.26 −22.91 Qpct glutaminyl-peptide cyclotransferase (glutaminyl cyclase) −2.25 −4.16 Cndp2 CNDP dipeptidase 2 (metallopeptidase M20 family) −2.20 −3.14 Continued. This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited. Iwasaki S, Kaneda K. Genes relating to biological … Drug Res 2022; 72: 523–533 | © 2022. Thieme. All rights reserved. Original Article Thieme 530 the common DEGs and endometriosis by using PubMed. When we searched for each gene along with the term “endometriosis”, 52 of 154 genes came up (Supplementary table 3 and ▶Fig. 5). When we searched for each gene along with the terms “endometriosis” and “development”, 23 genes came up that had some association with endometriosis in patients (▶ table 5).

In the present study, we found that biological processes including cell adhesion, the inflammatory response, the response to mechani- cal stimulus, cell proliferation, extracellular matrix organization (ECM), and the estrogen response were enriched in both the model and patients. We found that thrombospondin 1 (Thbs1), tissue in- hibitor of metalloproteinase 1 (Timp1), and cell adhesion molecule with homology to L1CAM (Chl1) were up-regulated in both the model and patients. These genes are known to play a role in cell ad- hesion and/or ECM organization, biological processes important for the attachment and invasion of ectopic cells in tissues [14–16]. ▶table 3 DEGs common to the syngeneic mouse endometriosis model and endometriosis patients Gene Description Fold changein model Fold change in patients (average of 3 datasets) Wfdc2 WAP four-disulfide core domain 2 −2.20 −10.44 Stxbp6 syntaxin binding protein 6 (amisyn) −2.16 −9.21 Rab25 RAB25, member RAS oncogene family −2.15 −5.87 Llgl2 lethal giant larvae homolog 2 (Drosophila) −2.14 −2.27 Npr2 natriuretic peptide receptor 2 −2.14 −2.80 Ppap2c phosphatidic acid phosphatase type 2 C −2.08 −4.03 Irf6 interferon regulatory factor 6 −2.04 −5.03 Gjb6 gap junction protein, beta 6 −2.00 −5.75 ▶Fig. 4 Identification of DEGs common to the syngeneic mouse endometriosis model and endometriosis patients. DEGs in the ectopic tissue of the model mice were compared to those in the patients. The DEGs of each dataset were displayed in Venn diagrams and the over- lapping DEGs identified by selecting genes which showed the same expression pattern (up-regulated or down-regulated). ▶table 4 GO terms which were enriched in DEGs common to the synge- neic mouse endometriosis model and endometriosis patients GO term genes cell adhesion 17 Gpnmb, Thbs2, Col12a1, Thbs4, Thbs1, Sulf1, Chl1, Wisp2, Itgb2, Col14a1, Nfasc, Cdh5, Itga7, Cd22, Nuak1, 9430020K01Rik, Cd24a inflammatory response 6 Thbs1, Cd163, C4a, Chi3l1, Tril, Ccr1 response to mechani - cal stimulus 2 Thbs1, Chi3l1 negative regulation of cell proliferation 13 Serpine2, Sfrp2, Slit3, Inhba, Frzb, Wisp2, Podn, Hmox1, Rerg, Cdh5, Aldh1a2, Irf6, Gjb6 extracellular matrix organization 1 Ccdc80 response to estrogen 5 Kcnma1, Hmox1, Krt19, Esr1, Cd24a Angiogenesis 5 Meox2, Nrp2, Ccdc80, Hmox1, Ptprb positive regulation of angiogenesis 5 Thbs1, Sfrp2, Itgb2, Hmox1, Chi3l1 Aging 5 Cryab, Timp1, Itgb2, Serping1, Gjb6 immune response 7 Thbs1, Ctss, Colec12, Fcgr2b, Ccr1, C7, Cd24a chemokine-mediated signaling pathway 1 Ccr1 ▶Fig. 5 Flowchart for Pubmed search. PubMed (National Center for Biotechnology Information) was searched for each common DEG along with the term “endometriosis” or the terms “endometriosis” and “development” Continued. This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited. Iwasaki S, Kaneda K. Genes relating to biological … Drug Res 2022; 72: 523–533 | © 2022. Thieme. All rights reserved. 531 Thus, these genes might be critical for the development of endo - metriosis via cell attachment and invasion in both model and pa - tients. The inflammatory and immune responses are also critical to the development of endometriosis. Single-cell analysis has shown that T cells in endometriosis are less activated, cytotoxic T cell pop- ulations and the proportion of natural killer cells in endometriosis lesions are decreased, and the ratio of monocytes to macrophages is increased in endometriosis cysts whose main population highly expresses CD206 and CD163, which have been described as M2 macrophage markers [17]. In the present study, the gene expres - sion of haptoglobin and CD163 was upregulated in both the model and patients. Haptoglobin is an acidic glycoprotein and ligand of CD163, which is a surface hemoglobin-haptoglobin scavenger re - ceptor, and is related to the development of endometriosis [18]. These results suggest that M2 macrophages might be critical for the development of endometriosis in both model and patients. Fur- thermore, endometriosis is considered to be an estrogen-depend- ent disease. Previous studies have shown that the aberrant expres- sion of hormone receptors in endometriosis lesions, including high estrogen receptor 2 (Esr2) to Esr1 ratios, is related progesterone ▶table 5 The DEGs common to the model and patients along with the terms “endometriosis” and “development” found by searching PubMed Gene Number of publications r eference lists up-regulated genes Hp 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. Hsd11b1 1 Zhen Lin et al., J Food Biochem. 2021 May;45(5):e13717. Timp1 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 23;23(4):649–653. Stilley JA et al., Biol Reprod. 2010 Aug 1;83(2):185–94. Collette T et al.,Hum Reprod. 2006 Dec;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. 2004 Jun;19(6):1257–64. Thbs1 3 Liu Y et al., Am J Reprod Immunol. 2020 Jun;83(6):e13236. Gilabert-Estellés J et al., Hum Reprod. 2007 Aug;22(8):2120–7. Tan XJ et al., Fertil Steril. 2002 Jul;78(1):148–53. Slit3 1 Greaves E et al., Endocrinology. 2014 Oct;155(10):4015–26. Inhba 1 Lin J et al., Mol Hum Reprod. 2011 Oct;17(10):605–11. Cd163 3 Kusunoki M et al., Med Mol Morphol. 2021 Jun;54(2):122–132. Krasnyi AM et al., Biomed Khim. 2019 Aug;65(5):432–436. Itoh F et al., Fertil Steril. 2013 May;99(6):1705–13. Chl1 2 Jiang L et al., Int J Immunopathol Pharmacol. 2020 Jan-Dec;34:2058738420976309. Zhang C et al., Eur J Obstet Gynecol Reprod Biol. 2019 May;236:177–182. Prelp 1 Araujo FM et al., Braz J Med Biol Res. 2017 Jul 3;50(7):e5782. Itgb2 1 Sundqvist J et al., Hum Reprod. 2012 Sep;27(9):2737–46. S100a6 1 Peng Y et al., Gynecol Endocrinol. 2018 Sep;34(9):815–820. Gpx3 1 Mirza Z et al., Diagnostics (Basel) . 2020 Jun 19;10(6):416. Hmox1 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. Fcgr3 1 Mei J et al., Autophagy. 2018;14(8):1376–1397. Ccr1 3 Li T et al., Biomed Pharmacother. 2020 Sep;129:110476. Trummer D et al., Acta Obstet Gynecol Scand. 2017 Jun;96(6):694–701. Kyama CM et al., Curr Med Chem. 2008;15(10):1006–17. Nr4a1 1 Qingdong Z et al., Cell Physiol Biochem. 2018;45(3):1172–1190. Fst 2 Kimber-Trojnar Ż et al., J Clin Med. 2021 Jun 23;10(13):2762. Luisi S et al., Womens Health (Lond). 2015 Aug;11(5):603–10. down-regulated genes Crabp2 1 Sokalska A et al., J Clin Endocrinol Metab. 2013 Mar;98(3):E463–71. Krt19 1 Konrad L et al., Reprod Sci. 2019 Jan;26(1):49–59. Aldh1a2 1 Jiang Y et al., J Endocrinol. 2018 Mar;236(3):R169-R188. Esr1 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 et 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., Cells. 2019 Sep 21;8(10):1123. Yilmaz BD et al., Hum Reprod Update. 2019 Jul 1;25(4):473–485. Osiński M et al., Ginekol Pol. 2018;89(3):125–134. Sapkota Y et al., Nat Commun. 2017 May 24;8:15539. Hamilton KJ et al., Curr Top Dev Biol. 2017;125:109–146. Xiong W et al., Reproduction. 2015 Dec;150(6):507–16 Zhang Q et al., Gynecol Obstet Invest. 2015;80(3):187–92. Huang PC et al., Environ Sci Pollut Res Int. 2014 Dec;21(24):13964–73. Wang W et al., Reprod 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. 2012 Sep;181(3):917–27. Matsuzaka Y et al., Environ Health Prev Med. 2012 Sep;17(5):423–8. Athanasios F et al., Arch Gynecol Obstet. 2012 Apr;285(4):1001–7. Smuc T et al., Mol Cell Endocrinol. 2009 Mar 25;301(1–2):59–64. Cd24a 1 Sundqvist J et al., Hum Reprod. 2012 Sep;27(9):2737–46. Wfdc2 1 Chen T et al., J Clin Lab Anal. 2021 Sep;35(9):e23947. This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited. Iwasaki S, Kaneda K. Genes relating to biological … Drug Res 2022; 72: 523–533 | © 2022. Thieme. All rights reserved. Original Article Thieme 532 resistance [19]. In our study, the gene expression of Esr1 was de - creased in both the model and patients, suggesting that the estro- gen response is also important in the pathogenesis of this model, despite the fact that the rodent model does not exhibit menstrua- tion. Thus, this model partly reflects the pathophysiology of endo- metriosis that occurs in humans as mentioned above, and it might be useful for evaluating the efficacy of new therapeutic agents tar- geting biological processes that include cell adhesion and ECM re- modeling, inflammatory and immune responses, cell proliferation, angiogenesis, and the estrogen response. We found for the first time that gene expression in the eutopic uterus was changed in the model, and the biological processes as- sociated with the genes whose expression was changed were re - sponse to lipopolysaccharide and neutrophil chemotaxis. Previous work has shown that the expression of lipopolysaccharide in the endometrium of endometriosis patients is increased compared to that in healthy controls [20]. These findings suggest that the model reflects the environment not only in ectopic lesions but also in the eutopic endometrium of endometriosis patients. In addition to this model, immunocompromised models, in which human endometrial tissue is injected into mice, are useful for examining the multiple cellular pathways associated with the development of human endometriosis. However, immunocompro- mised models may not mimic the inflammatory or immune re - sponse of endometriosis patients because of the lack of a fully com- petent immune system in such mice [21]. The surgical immuno - competent model reflects the inflammation response, cell proliferation and the estrogen response of patients, yet it may not mimic early events in the development of endometriosis such as retrograde menstruation due to the surgical induction of ectopic growth [21]. There is reported to be no change in the levels of cy- tokeratin or E-cadherin in the epithelial cells of ectopic endometri- um, or in the excessive collagen deposition or alpha-SMA positive myofibroblasts in the ectopic endometrium of the surgical mouse endometriosis model [22]. In the present study, the expression of genes related to the inflammatory or immune response and ECM remodeling was changed in the syngeneic mouse endometriosis model, indicating that this model may be distinct from other mod- els. A limitation of our study is that we did microarray analysis of whole tissues at a specific time point. The model was found not to reflect some biological process in humans, such as endopeptidase activity and platelet degranulation, at least under the present ex- perimental conditions. However, since the level of gene expression would be expected to change with time after construction of the model, or according to the estrous cycle or the component cells, spatiotemporal single-cell RNA sequencing should be more effec- tive for future study. To obtain data on gene expression in endo - metriosis patients, we used the gene expression data of endome - triosis patients from three datasets in which the gene expression in ectopic tissue is compared to that in eutopic tissue, and reana - lyzed them in order to unify the analysis method between the pa - tient datasets. However, similar data would have been reported consecutively, so we should also analyze those new data to increase the sample size. Furthermore, in the future we should confirm the relationship between disease severity and the gene expression of key molecules which seem to be important for the development of the disease. Additionally, it is not clear whether the DEGs common to the model and patients are the cause or the result of the patho- genesis of endometriosis. To resolve this issue, experiments using a suppressor or initiator for each gene are necessary. On the basis of the DEGs identified in this study, further work would be expect- ed to clarify molecular mechanisms underlying the pathogenesis of endometriosis, which may lead to the identification of new bio- markers and/or treatment targets for this disease.

The study was supported in part by Nippon Shinyaku Co., Ltd. We thank Dr. Gerald E. Smyth for English-language editing of the man- uscript. Conflict of interest The authors declare no conflict of interest.

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