bioRxiv preprint doi: https://doi.org/10.1101/2019.12.21.885657; this version posted December 23, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

1 Transcriptomic responses to hypoxia in endometrial and decidual stromal cells 2 3 Kalle T. Rytkönen 1,2,3,4, Taija Heinosalo 1, Mehrad Mahmoudian 2,5, Xinghong Ma 3,4, Antti 4 Perheentupa 1,6, Laura L. Elo 2, Matti Poutanen 1 and Günter P. Wagner 3,4,7,8 5 6 1 Institute of Biomedicine, Research Centre for Integrative Physiology and Pharmacology, 7 University of Turku, Kiinamyllynkatu 10, 20014, Finland 8 2 Turku Bioscience Centre, University of Turku and Åbo Akademi University, Tykistökatu 6, 9 20520, Turku, Finland 10 3 Yale Systems Biology Institute, West Haven, Connecticut 06516, USA 11 4 Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06511, 12 USA 13 5 Department of Future Technologies, University of Turku, FI-20014 Turku, Finland 14 6 Department of Obstetrics and Gynecology, Turku University Hospital, Kiinamyllynkatu 4-8, 15 20521, Turku, Finland. 16 7 Department of Obstetrics, Gynecology and Reproductive Sciences, Yale Medical School, New 17 Haven 06510, USA 18 8 Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI- 48201, USA 19 20 Correspondence should be addresses to K T Rytkönen; Email: [email protected]. Address: Institute 21 of Biomedicine, Research Centre for Integrative Physiology and Pharmacology, University of 22 Turku, Kiinamyllynkatu 10, 20014, Finland / Turku Bioscience Centre, University of Turku and 23 Åbo Akademi University, Tykistökatu 6, 20520, Turku, Finland. 24 25 Short title: Hypoxic transcriptome of endometrial stroma. 26 Keywords: Endometrium, Oxygen, Hypoxia, Endometrial stromal fibroblasts, Decidual stromal 27 cells, Transcription, Endometriosis, Promoter, JunD Proto-Oncogene, JUND, CCAAT Enhancer 28 Binding Protein Delta, CEBPD. 29 30 Word count: 5819

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31 Abstract 32 33 Human reproductive success depends on a properly decidualized uterine endometrium that 34 allows implantation and the formation of the placenta. At the core of the decidualization process 35 are endometrial stromal fibroblasts (ESF) that differentiate to decidual stromal cells (DSC). As 36 variations in oxygen levels are functionally relevant in endometrium both upon menstruation and 37 during placentation, we assessed the transcriptomic responses to hypoxia in ESF and DSC. In 38 both cell types hypoxia upregulated genes in classical hypoxia pathways such as glycolysis and 39 the epithelial mesenchymal transition. In DSC hypoxia restored an ESF like transcriptional state 40 for a subset of transcription factors that are known targets of the progesterone receptor, 41 suggesting that hypoxia partially interferes with progesterone signaling. In both cell types 42 hypoxia modified transcription of several inflammatory transcription factors that are known 43 regulators of decidualization, including decreased transcription of STATs and increased 44 transcription of CEBPs. We observed that hypoxia upregulated genes had a significant overlap 45 with genes previously detected to be upregulated in endometriotic stromal cells. Promoter 46 analysis of the genes in this overlap suggested the hypoxia upregulated Jun/Fos and CEBP 47 transcription factors as potential drivers of endometriosis-associated transcription. Using 48 immunohistochemistry we observed increased expression of JUND and CEBPD in endometriosis 49 lesions compared to healthy endometria. Overall the findings suggest that hypoxic stress 50 establishes distinct transcriptional states in ESF and DSC, and that hypoxia influences the 51 expression of genes that contribute to the core gene regulation of endometriotic stromal cells.

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52 Introduction 53 54 Human reproductive success depends on a properly differentiated (decidualized) uterine 55 endometrium that allows implantation, the formation of the placenta and maintenance of the 56 pregnancy (Gellersen and Brosens, 2014; Vinketova et al., 2016). In humans, and other 57 catarrhine primates, decidualization of endometrial stromal fibroblasts (ESF) to endometrial 58 stromal cells (DSC) takes place spontaneously during every menstrual cycle. Decidualization 59 involves substantial transcriptional and cellular remodeling, enabling implantation and placental 60 development as well as menstruation-associated renewal of endometrium (Gellersen and 61 Brosens, 2014). This process is triggered by autocrine and paracrine signaling pathways 62 dependent on progesterone activated progesterone receptor (PGR) and cyclic adenosine 63 monophosphate (cAMP) mediated activation of protein kinase A (PKA) (Pavličev et al., 2017; 64 Wu et al., 2018). These, together with expression of transcription factors (TFs) including 65 forkhead box protein O1 (FOXO1), homeobox (HOX), and signal transducer and activator of 66 transcription (STAT) paralogs contribute to the regulatory programming necessary for 67 decidualization (Gellersen and Brosens, 2014; Vinketova et al., 2016). 68 The endometrium is exposed to hypoxic periods specifically upon menstruation as well as 69 during placentation (Pringle et al., 2010; Maybin and Critchley, 2015), but the associated 70 transcriptional regulation remains poorly characterized. A recent study assessed the role of 71 hypoxia in menstrual repair (Maybin et al., 2018), but the difference in the hypoxia related 72 transcriptional regulation between undifferentiated ESF and differentiated DSC has not been 73 studied. Moreover, it was recently shown that DSC specific gene regulatory network involves 74 factors that are part of the oxidative stress responses (Erkenbrack et al., 2018), placing a specific 75 interest on oxygen dependent gene regulation in the endometrium. 76 Importantly, endometrial responses to hypoxia are also relevant to several aspects of 77 reproductive health. In endometriosis, endometrial cells grow outside of uterus in niches that are 78 often more hypoxic than the highly vascularized uterus (Bishop, 1956; Bourdel et al., 2007; Wu 79 et al., 2019). Endometriosis lesions grow faster in hypoxia (Lu et al., 2014) and associated 80 angiogenesis (Lu et al., 2014) and hormone actions, including regulation of estrogen receptor 81 (Wu et al., 2012), are affected by hypoxia. Additionally, the abnormalities in pregnancy disorder 82 preeclampsia are partly driven by hypoxia signaling (Tal, 2012).

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83 Up to date no whole genome studies are available that describe the transcriptomic 84 responses to hypoxia in the endometrial stromal cells. Here we characterize the transcriptomic

85 responses to severe hypoxia (1% O2, 24h) in cultured ESF and DSC. We assess the hypoxia- 86 regulated pathways by enrichment analysis and specifically focus on hypoxia regulated 87 transcription factors. Further, we show that hypoxia upregulated genes have significant overlap 88 with genes known to be upregulated in endometriosis, and guided by promoter analysis of 89 transcription factor binding sites we select two transcription factors, JunD Proto-Oncogene 90 (JUND) and CCAAT Enhancer Binding Protein Delta (CEBPD), for immunohistochemistry in 91 endometriosis lesions and healthy endometria. 92 93 94 Material and methods 95 96 Cell Culture and hypoxia treatment 97 Human immortalized endometrial stromal fibroblasts (ESF) (T HESC, Mor lab, Yale University,

98 corresponding to ATCC CRL-4003) were grown in normoxia (21% O2) in Dulbecco's Modified 99 Eagle's medium (DMEM) (Sigma-Aldrich, D2906), supplemented with 10% charcoal stripped 100 calf serum (Hyclone), 1% antibiotic/antimycotic (ABAM; Gibco), 1nM sodium pyruvate 101 (Gibco), 0.1% insulin-transferrin-selenium (ITS premix, BD Biosciences), and 0.12% sodium 102 bicarbonate. To generate DSC, ESFs were decidualized by adding of 0.5 mM 8-bromoadenosine 103 3′,5′-cyclic monophosphate (8-Br-cAMP) (Sigma) and 0.5 μM of the synthetic progestin 104 medroxyprogesterone acetate (MPA) in DMEM supplemented with 2% charcoal-stripped calf - 105 serum. 106 For ESF hypoxia exposure was conducted for 24 hours using ProOx C21 nitrogen-

107 induced hypoxia system (BioSpherix, Red Field, NY) at 1% O2, 5% CO2 and compared to 108 normoxic ESF from the same cell batch. For DSC, ESF were first decidualized for 36 hours and 109 then similarly exposed to hypoxia for 24 hours (total decidualization time including the time 110 under hypoxia = 60 hours) and compared to normoxic DCS from the same cell batch that were 111 decidualized for two days. As hypoxia slows down cellular processes we defined that normoxic 112 decidualization of 36 hours followed by 24 hours decidualization in hypoxia represents a

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113 reasonable approximation to be compared to normoxic decidualization of two days. Each of the 114 four sample groups had two biological replicates. 115 116 RNA-seq, differential transcription and visualization 117 Total RNA was extracted with RNeasy Mini or Midi RNA-extraction kits (QIAGEN) followed 118 by on-column DNase I treatment. Total RNA quality was assayed with a Bioanalyzer 2100 119 (Agilent) and 500 ng of RNA samples were sequenced with Illumina Genome Analyzer II 120 platform. For each sample at least 30 million reads were acquired and quality parameters were 121 checked with FastQC (http://www.bioinformatics.babraham.ac.uk/projects/fastqc). Sequencing 122 data are available in NCBI Gene Expression Omnibus (GEO; 123 https://www.ncbi.nlm.nih.gov/geo/) under accession numbers GSE111570 (GSM3034449, 124 GSM3034450, GSM3034451 and GSM3034452) and GSE63733 (GSM1556296, GSM1556297, 125 GSM1556298, GSM1556299). All data is also available from authors upon request. 126 Sequence reads were mapped to the GRCh37 human reference genome using Tophat2 127 (Trapnell et al., 2009) and the gene counts were calculated using HTSeq (Anders et al., 2015) 128 according to Ensembl annotation (GRCh37.69) and normalized as transcripts per million (TPM) 129 (Wagner et al., 2013). Differential transcription was analyzed with edgeR using upper quartile 130 normalization (Robinson et al., 2010) and the following cut-offs: false discovery rate 131 (FDR) < 0.01, absolute fold-change (FC) > 2.0 and TPM > 2. The principal component analysis 132 (PCA) of the four conditions after edgeR upper quartile normalization indicated that the two 133 biological replicates in each condition grouped tightly together (Supplementary Figure 1). 134 For visualization, gene heatmaps were produced from averages of the absolute TPM 135 values using pheatmap_1.0 in R 3.5. Hierarchical clustering of the genes was performed using 136 Euclidean distance and the complete linkage method. TF set was constructed by combining 137 genes in Ingenuity Pathway Analysis (IPA, Qiagen, www.qiagen.com/ingenuity) categories 138 “transcription regulator” and “ligand-dependent nuclear receptor”. Hypoxia regulated 139 transcription factor subsets were intersected with PGR targets that were previously detected 140 using siRNA by Demayo lab (we filtered the originally reported siPGR set using FC > 2) (Mazur 141 et al., 2015). A circos plot was produced in METASCAPE (metascape.org). 142 143 Pathway analysis

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144 For gene ontology (GO) and gene set enrichment analysis and heatmaps, gene lists of 145 differentially transcribed genes (FDR < 0.01, FC > 2.0, TPM > 2) were used as input for 146 METASCAPE, and available pathway databases (GO Biological Processes, Reactome Gene 147 Sets, Canonical Pathways, Biocarta Gene Sets, KEGG Pathway and Hallmark Gene Sets) were 148 selected for analysis. We used “IPA Canonical Pathways” tool to visualize enriched pathways. 149 150 Endometriosis transcriptome data and statistical tests of the overlaps 151 In order to test the significance of our cell culture results in a clinically relevant hypoxic niche 152 we investigated the overlap of hypoxia differentially transcribed genes with most relevant 153 available endometriosis data from literature and databases. Endometriosis data sets included a 154 stromal dataset (FACS isolated with CD10 antibody) of differentially expressed genes between 155 endometriosis lesions versus control healthy endometrium (Rekker et al., 2017, Supplementary 156 Table 1); a heterogeneous tissue dataset of differentially expressed genes in the endometrium of 157 endometriosis patients versus healthy controls (Tamaresis et al., 2014, Supplementary Table 5, 158 endometriosis and abnormal) and endometriosis related genes listed in the DisGeNET v5.0- 159 database (http://www.disgenet.org/) (Piñero et al., 2017). For the first two sets, lists of 160 endometriosis up- and downregulated genes were analyzed separately, whereas for the database 161 one list of all endometriosis-regulated genes was used. Each list was filtered to contain only 162 genes that were expressed in our ESF and DSC cell cultures (TPM > 2). To study the overlaps of 163 the endometriosis differentially transcribed genes and the hypoxia differentially transcribed 164 genes we organized the data using varhandle 2.0.3 and constructed contingency tables in R 3.6.0, 165 conducted Fisher’s exact test (fisher.test) to determine the significance of enrichment and 166 presented the results using pheatmap 1.0.12. Effect size was calculated as odds ratio, which was 167 provided by the fisher.test. The genes of the two most significant overlaps were further analyzed 168 with pathway analysis and transcription factor binding site motif analysis. 169 170 Transcription factor binding site (TFBS) analysis 171 We tested the enrichment of TFBS in the promoters of hypoxia and endometriosis upregulated 172 genes using GeneXplain 4.0 (http://genexplain.com). The endometriosis upregulated subsection 173 of all the hypoxia upregulated genes was set as foreground (yes set) and all hypoxia upregulated 174 genes as the background/control (no set) and “Search for enriched TFBSs (genes)” function was

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175 run with default settings (promoter: -1000 to +100). Two TFBS databases were searched: 176 prediction based TRANSFAC_public_vertebrates and ChIP-seq based GTRD_moderate. Both 177 result lists were ranked with “Site FDR” to inspect the most significantly enriched TFBS motifs. 178 Top 20 enriched motifs were manually examined for corresponding TFs homologs among the 179 top ESF and DSC hypoxia upregulated TFs. As TFBS motif names and TF names do not 180 constitute one-to-one correspondence, corresponding homologs (and synonyms) and were 181 manually defined using https://www.genecards.org/. 182 183 Immunohistochemistry 184 Patient samples were collected and processed as described previously (Heinosalo et al., 2018). 185 Briefly, the Joint Ethics Committee of Turku University and Turku University Hospital approved 186 collections and all study subjects provided written informed consent. Samples of endometriosis 187 (deep infiltrating lesions: sacrouterine ligament and bladder) and eutopic endometrial biopsies 188 were collected from endometriosis patients, and as a control group, endometrial biopsies from 189 healthy, endometriosis-free women undergoing laparoscopic tubal ligation were collected. Tissue 190 samples were fixed in formalin and embedded in paraffin for histological analysis. Antigen 191 retrieval of hydrated 5 μm tick sections was performed in 10 mM sodium citrate buffer (pH 6.0), 192 followed by immunohistochemistry with primary antibodies against JUND (mouse monoclonal, 193 Jun D Antibody (D-9), sc-271938, Santa Cruz Biotechnology, Santa Cruz, CAUSA) with 1:1500 194 dilution and CEBPD (rabbit polyclonal Anti-CEBP Delta antibody ab65081, Abcam, Cambridge, 195 MA, USA) with 1:250 dilution. Three samples in each sample group (endometriosis lesion, 196 patient endometrium, healthy control endometrium) were stained. Sections were scanned for 197 analyses with the panoramic 250 Flash series digital slide scanner (3DHISTECH, Hungary). 198 199 200 Results 201 202 Global transcriptomic effects of hypoxia

203 We performed global RNA-seq from hypoxia treated (1% O2, 24h) immortalized human 204 endometrial stromal fibroblasts ESF (ATCC CRL-4003) and 2 day decidualized (MPA, 8-br- 205 cAMP) endometrial stromal cells (DSC) and compared these to corresponding normoxic

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206 conditions. Hypoxia-related upregulation of transcription (FDR < 0.01, FC > 2 and TPM > 2 in 207 hypoxic condition) involved more shared genes between ESF and DSC compared to hypoxia- 208 related downregulation of transcription (FDR < 0.01, FC < -2 and TPM > 2 in normoxic 209 condition) (Fig. 1A). Specifically, 36% (728) of the genes upregulated were shared in both ESF 210 and DSC whereas 628 and 643 genes, respectively, were upregulated in a cell type specific 211 manner. In contrast, 69% of the genes downregulated in DSC (1304) were DSC specific (901). 212 213 Functional pathways affected by hypoxia 214 Pathway enrichment analysis revealed a clustering pattern of the functional terms that is 215 concordant with the above described gene proportions. In both cell types the most significant 216 cellular functions predicted to be upregulated by hypoxia (“hypoxia” and “epithelial 217 mesenchymal transition”) were clustered together (Fig. 1B). On the other hand hypoxia 218 downregulated genes in ESF and DSC formed distinct enrichments, in ESF the most significant 219 terms being “TNFA signaling via NFKB” and “response to wounding” whereas in DSC these 220 were “E2F targets” (involved in cell cycle regulation) and “regulation of cellular response to 221 stress” that were not detected in ESF. 222 As expected, in both cell types hypoxia upregulated genes included canonical glycolysis 223 pathway (Supplementary Figure 2) and other known target genes of hypoxia inducible factor 1 224 (HIF-1alpha) (Fig. 1C). These genes, which also shared the highest hypoxic increases in both 225 conditions, included insulin-like growth factor binding protein 3 (IGFBP3), macrophage 226 migration inhibitory factor (MIF) and metallothionein genes (MT1E, MT1X). MIF is a cytokine 227 potentially regulating both inflammatory status and angiogenesis (Hahne et al., 2018), and MT1s 228 are involved in the protective responses to oxidative stress (Xue et al., 2012). Upon hypoxia in 229 DSC, of the classic decidualization markers, transcription of prolactin remained on the same 230 level as in normoxia (TPM 7.9 to 5.4), whereas IGFBP1 was markedly downregulated (TPM 17 231 to 0.4) suggesting that hypoxia interferes especially with metabolic aspects of decidualization. 232 Most notably, in hypoxia the TPM for IGFBP3, a paralog of IGFBP1, increased from 38 to 4382 233 TPM in ESF, and from 1216 to 16865 TPM in DSC. IGFBPs bind to and modulate insulin-like 234 growth factors (IGFs) and may affect glucose uptake and proliferation of the cells. Also LDHA 235 was highly transcribed and 8.6-fold upregulated in ESF (to TPM 1645) and 5.3-fold upregulated

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236 in DSC (to TPM 1381) (Supplementary Table 1A) confirming the extensive hypoxic metabolism 237 together with glycolysis pathway. 238 In our study, the top hypoxia upregulated genes with high transcription levels included 239 several extracellular matrix components and their regulators, including several collagens (1A1, 240 6A3, 7A1, 12A1, 4A1, 4A2, 5A1), fibronectin, vimentin, proteases and Lysyl oxidases that are 241 involved in EMT (Fig. 1D) and that are relevant markers of mesenchymal like state in ESF (Yu 242 et al., 2016; Owusu-Akyaw et al., 2019). Thus, knowing that these genes are central for both 243 EMT and the opposite process mesenchymal epithelial transition (MET), these results suggest 244 that hypoxia may repress mesenchymal epithelial transition (MET) -like extracellular 245 modifications typical for early decidualization. 246 In ESF, hypoxia repressed genes connected to inflammation, under the terms such as 247 “TNFA signaling via NFKB” and “response to wounding” (Fig. 1B). This repression included 248 the downregulation of pro-inflammatory cytokines such as IL1B and BMP2, and TFs RELB, 249 F2RL1 and IRF1 (Fig. 1E). These results suggest that hypoxia modifies the pro-inflammatory 250 signaling characteristic for early decidualization (Salker et al., 2012; Rytkönen et al., 2019). In 251 DSC, hypoxia downregulated genes in the “E2F targets” term that includes several regulators of 252 cell cycle, chromosome segregation and nuclear division (Supplementary Table 1B). The DSC 253 downregulated genes within the term “regulation of cellular response to stress” include multitude 254 of genes in intracellular protein kinase signaling such as MAPK and JNK cascades 255 (Supplementary Table 1B). 256 257 Hypoxia regulated transcription factors 258 The TFs upregulated in response to hypoxia included several common mediators of hypoxia- 259 induced gene repression. Of the TFs upregulated in ESF by hypoxia, 60% (66/110) were also 260 upregulated in DSC, whereas of the downregulated TFs only 37% (37/100) were shared (Fig. 261 2A). In both cell types hypoxia upregulated transcriptional repressors, such as Inhibitor Of DNA 262 Binding (ID) genes that repress the expression of other TFs (Fig. 2B). 263 The master hypoxic regulators (HIF-1alpha and EPAS1, a.k.a. HIF-2alpha) were highly 264 transcribed in all conditions, but were downregulated in DSC by hypoxia 5- and 3-fold, 265 respectively (Fig. 2C). Notably, in DSC, BHLHE40 and BHLHE41 were highly upregulated by 266 hypoxia, 17-fold and 11-fold respectively (Fig. 2B). These repress TFs regulating circadian

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267 rhythm, such as PER and CLOCK. In line with this, we observed hypoxic downregulation of 268 PER1/3 in ESF and CLOCK in DSC (Supplementary Table 1A). 269 The effects of hypoxia on core regulators of decidualization were multifaceted. In both 270 cell types, and particularly in DSC, HOXA10, HOXA11, CEBPB and CEBPD were upregulated 271 by hypoxia (Fig. 2B, Supplementary Table 1A), whereas FOXO1, STAT3 and STAT5A were 272 downregulated (Fig. 2C). Of these especially CEBPs and STATs are involved in the initial pro- 273 inflammatory decidualization phase (Wang et al., 2012; Rytkönen et al., 2019). 274 Other notable upregulated groups of TFs included members of Jun/Fos family (JUND 275 and JDP2) and several Kruppel-like factors such as KLF2, KLF4 and KLF7, of which KLF2 was 276 18-fold upregulated in ESF. KFL2 is a known negative regulator of NFKB pathway (Jha and 277 Das, 2017), and potentially participates in the of the observed ESF specific NFKB pathway 278 repression. 279 280 Hypoxia interferes with Progesterone Receptor regulated TF networks 281 In both cell types hypoxia downregulated several genes that were under the GO term “cellular 282 response to hormone stimulus” (Fig. 1B). Signaling via progesterone receptor (PGR) is known to 283 be a main driver of decidualization, and it regulates e.g. the expression of FOXO1, HOXO10, 284 CEBPs, and STATs. We, thus, investigated the effect of hypoxia specifically in PGR regulated 285 TFs by intersecting ChIP-seq detected and PGR regulated (>2-fold) TFs from a previous study 286 (Mazur et al., 2015) with the hypoxia regulated TFs. The data revealed that 8/18 PGR 287 upregulated and 29/50 PGR downregulated TFs were influenced by hypoxia (Fig. 2A). This 288 suggests that primarily TF networks downregulated by PGR are modified by hypoxia. Notably, 289 of the 29 TFs downregulated by PGR, 13 showed similar downregulation by hypoxia in ESF, 290 while 15 were upregulated in DSC by hypoxia (Fig. 2A, D). The data also suggest that in DSC 291 hypoxia partly restores the ESF like transcriptional state for a subset of highly transcribed and 292 PGR downregulated TFs (Fig. 2D). Overall these observations suggest that hypoxia, at least 293 partly, reverses PGR dependent transcriptional changes necessary for early decidualization. 294 295 Relationship between gene sets upregulated by hypoxia and in endometriosis 296 In order to explore the significance of our cell culture results for a clinically relevant hypoxic 297 niche, we investigated the overlap between the genes differentially transcribed in hypoxia with

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298 the data available on endometriosis using Fisher’s exact test (Fig. 3A). The overlap with the 299 highest significance was observed between the ESF hypoxia upregulated genes and the 300 endometriosis upregulated genes (p = 5.8E-27, 3.90-fold) from a dataset comparing isolated 301 endometrial stromal cells from endometriosis lesions to healthy control endometrium (Rekker et 302 al., 2017). In this dataset, also the overlap with DSC hypoxia upregulated genes with 303 endometriosis upregulated genes was highly significant (p = 6.0E-19, 3.25-fold). This extensive 304 overlap of hypoxia upregulated (ESF and DSC) genes of the endometriosis upregulated genes 305 39% (157/402, TPM > 2 in our cell culture) suggests that gene regulatory programs responding 306 to hypoxic conditions contribute to the core gene regulation in the stroma of endometriosis 307 lesions. 308 The overlaps with endometriosis datasets that were not stromal cell specific were not 309 significant or less overlapping compared to the stromal cell specific data (Fig. 3A). For a 310 heterogeneous tissue dataset of differentially expressed genes in the endometrium of 311 endometriosis patients versus healthy controls (Tamaresis et al., 2014), the overlaps of hypoxia 312 and endometriosis upregulated genes were moderately significant (p = 2.5E-11 – 2.2E-5, 2.66- 313 fold – 1.92-fold). Further, the endometriosis related genes in DisGeNET v5.0 database (without 314 the direction of regulation) had moderately significant overlaps (p = 2.2E-13 – 2.0E-4, 2.58-fold 315 – 1.64-fold) in both hypoxia up- and downregulated genes. 316 We then used the detected stromal cell specific 157 genes that were hypoxia and 317 endometriosis upregulated as an input for pathways analysis (Fig. 3B). The most enriched 318 categories included “angiogenesis”, “epithelial mesenchymal transition” and “estrogen response 319 early” (Fig. 3C). The hypoxia and endometriosis regulated “angiogenesis” genes included 320 several highly transcribed and secreted ECM and adhesion molecules such as CCN2 (Cellular 321 Communication Network Factor 2), Serpine1, MCAM (Melanoma Cell Adhesion Molecule), 322 JCAD (Junctional Cadherin 5 Associated) (Fig. 3D). Additionally, the known core endometriosis 323 TF GATA6 was hypoxia upregulated and the previously mentioned KLF2 (Kruppel Like Factor 324 2) was substantially upregulated in hypoxic ESF (Fig. 3D). Of the hypoxia and estrogen 325 regulated genes KRT8 and KRT18 are keratins that dimerize with each other to form 326 intermediate filaments, and SCL7A5 (Solute Carrier Family 7 Member 5, or LAT1) is an amino- 327 acid transporter (Fig. 3E). 328

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329 Promoter transcription factor binding site (TFBS) analysis of hypoxia and endometriosis 330 upregulated genes reveals enrichment for Jun/Fos and CEBP motifs 331 We next analyzed the promoters of these 157 hypoxia and endometriosis upregulated genes (Fig. 332 3B) to find TFs that are both hypoxia upregulated and potential drivers of endometriosis. Using 333 GeneXplain 4.0 we searched two databases, prediction based TRANSFAC and ChIP-seq based 334 GTRD, for TFBS motifs enriched in the promoters (-1000 to +100 of TSS) of these 157 genes 335 (Table 1). Then we manually examined the top 20 ranked (site FDR) motifs for corresponding 336 TFs homologs among the highly hypoxia expressed and upregulated TFs (from Fig. 2B). We 337 discovered that in both TRANSFAC and GTRD databases there were corresponding homolog 338 motifs for the hypoxia upregulated Jun/Fos family members JDP2 and JUND and CEBP family 339 members CEBPB and CEBPD. Of these JUND and CEBPD were selected for protein level 340 validation in endometriosis biopsies due to their higher hypoxic upregulation compared to JDP2 341 and CEBPB (Fig. 2B) in ESF (JUND 3.2-fold, CEBPD 5.0-fold) and in DSC (JUND 4.8-fold, 342 CEBPD 5.2-fold). 343 The top motifs in the TFBS analysis that did not have corresponding hypoxia upregulated 344 TF homolog in our experiment included motifs for TFs such as MEF2 (Myocyte Enhancer Factor 345 2), B-ATF (Basic Leucine Zipper ATF-Like TF), OCT1 (POU2F1, POU Class 2 Homeobox 1) 346 and TBP/TATA (TATA binding protein) (Table 1). Of the homologs of these, MEF2C was 2.6- 347 fold downregulated in ESF, whereas the others were not hypoxia regulated. Notably, B-ATF is 348 AP-1/ATF family TF that dimerizes with JUN paralogs, but BATF genes (BATF1, BATF2, 349 BATF3) were not expressed in our cell cultures (TPM< 2). 350 351 Elevated immunohistochemical staining of JUND and CEBPD in deep endometriosis 352 compared to endometrial biopsies 353 Immunohistochemical staining of JUND and CEBPD was conducted in deep infiltrating 354 endometriosis lesions and compared to endometrial biopsies (patients and healthy controls) (Fig. 355 4). The stromal staining of JUND was considerable stronger in endometriosis compared to 356 control endometrium, however, in both roughly only half of the cells were stained. Strong 357 epithelial staining for JUND was present in all epithelial cells of the lesion whereas in control 358 endometrium epithelial cell staining was weak. For CEBPD we detected staining in most of the

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359 stromal and epithelial cells, and both stromal and epithelial cells had stronger staining in the 360 endometriosis lesions compared to control endometria. 361 362 363 Discussion 364 365 It is known that endometrium is exposed to hypoxic periods specifically upon menstruation as 366 well as during placentation (Pringle et al., 2010; Maybin and Critchley, 2015). Here we 367 conducted a global analysis of the transcriptomic responses to severe hypoxia in cultured ESF

368 and DSC by comparing the hypoxia exposed (1% O2, 24h) cultures to normoxic controls. Overall 369 our findings suggest that hypoxia establishes related but distinct transcriptional states in ESF and 370 DSC. Several upregulated functional pathways, such as glycolysis and EMT, were shared with 371 the two cell types, but many hypoxic responses, such as downregulation NFKB pathway in ESF 372 and downregulation of stress responses as well as core hypoxic response genes in DSC were cell 373 type specific. We also studied the relevance of these findings by intersecting our results with 374 previous studies on endometriosis, endometriosis presenting a clinically relevant condition where 375 stromal cells often inhabit hypoxic niches (Bishop, 1956; Bourdel et al., 2007; Wu et al., 2019), 376 and investigated relevant discovered hypoxia regulated targets in the endometriosis and 377 endometrium using immunohistochemistry. 378 Our results show that hypoxia interferes or modifies several gene regulatory networks 379 necessary for early decidualization. In both ESF and DSC, hypoxia promotes fibroblastic 380 phenotype (EMT), and thus, may interfere with the development of the quasi-epithelial state of 381 DSC. Further, when looking at TFs, the intersection of our results with available PGR 382 knockdown data (Mazur et al., 2015) suggests that hypoxia partly reverses PGR dependent 383 rewiring of transcriptional regulation typical for early decidualization. 384 In both ESF and DSC hypoxia enhanced classical hypoxia pathways including glycolysis 385 and insulin-like growth factor (IGF) mediated signaling by altering the expression of IGF 386 binding proteins (IGFBP1, IGFBP3 etc.). These modulate action of IGFs, and thereby may affect 387 glucose uptake and proliferation of the cells (Ding and Wu, 2018). Substantial hypoxic induction 388 of IGFBP3 has also been observed in other cell types (Natsuizaka et al., 2012; Chang et al., 389 2015) and has been associated with robust hypoxic polysome enrichment of IGFBP3 mRNA that

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390 may permit continuous translation under hypoxia (Natsuizaka et al., 2012). In endometrial 391 stromal cell increased glycolytic metabolism appears to take place also in well oxygenated 392 conditions (Kommagani et al., 2013), and the cells actively shuttle lactate (Zuo et al., 2015). 393 These observations can be also viewed in the context of Warburg effect or “pseudohypoxia” 394 (Russell et al., 2017), i.e. that stromal cells robustly express hypoxia-associated proteins, such as 395 glycolytic enzymes regardless of oxygen levels. Moreover, recent studies on first trimester 396 decidua show that the uterine natural killer cell (uNK) populations that are critical for placental 397 development also drive glycolysis (Vento-Tormo et al., 2018), suggesting that hypoxia (or 398 pseudohypoxia) related metabolic programming including glycolysis is not limited to stromal 399 cells and tumors but may be characteristic also to other cell types of decidualizing endometrium. 400 In our hypoxia experiment, stress responses appeared to be reduced specifically in DSC 401 evidenced by general downregulation of stress response genes and the downregulation of mRNA 402 levels of HIF-1alpha and HIF-2alpha, putatively representing negative feedback regulation via 403 repressors such as upregulated ID genes (Inhibitor Of DNA Binding). Hypoxic downregulation 404 of HIF mRNA in DSC can be viewed as part of general desensitized stress responses in DSC, as 405 previously reported on cells exposed to oxidative stress (Kajihara et al., 2013) and other stress 406 pathways (Muter et al., 2018) and may even be related to the above mentioned Warburg effect in 407 DSC, as glycolysis short cuts the mitochondria which are major players in apoptosis. 408 Transcriptional repression of HIFs do not contradict with the previously reported protein levels 409 showing HIF2 stabilization during early secretory phase (Maybin et al., 2018), because HIFs are 410 mainly regulated by hypoxia on translational level (Bishop and Ratcliffe, 2014). Additionally, in 411 our study, of the several upregulated repressor TFs, DECs (BHLHE40 and BHLHE41) 412 specifically repress CLOCK and PER genes (Sato et al., 2016), which were downregulated in 413 our experiment. These circadian rhythm TFs are involved in synchronizing decidualization 414 associated proliferation (Muter et al., 2015), and our data suggest that also this switch is 415 modified by hypoxia. 416 As early decidualization is partly an inflammatory process, several of the early 417 decidualization factors are also regulators of inflammation, including STAT and CEBP 418 pathways. In both cell types, but especially in DSC, hypoxia downregulated FOXO1, STAT3 419 and STAT5A that are known initiators of decidualization (Gellersen and Brosens, 2014), thus 420 suggesting that hypoxia suppresses the initial pro-inflammatory phase of decidualization.

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421 Hypoxia also upregulated AP1 factors (JUND and JDP2) that often mediate inflammation, but 422 that also are general activators for fibroblast proliferation (Manabe et al., 2002; Florin et al., 423 2004). On the other hand enhancers of decidualization HOXA10, HOXA11, CEBPB and CEBPD 424 (Gellersen and Brosens, 2014) were upregulated by hypoxia, underscoring that hypoxic periods 425 may also have positive effects for decidualization together with the potential to prime stromal 426 cells for stress tolerance (Kajihara et al., 2013) or glycolytic metabolism that is enhancing 427 decidualization (Kommagani et al., 2013; Zuo et al., 2015). 428 Hypoxic modification of decidualization related inflammatory states or progesterone 429 signaling may also be relevant in reproductive disorders including endometriosis, where hypoxia 430 has been show to induce stromal cell migration and lesion growth (Lu et al., 2014; Liu et al., 431 2017). We investigated the relevance of our cell culture results by overlapping those with 432 available transcriptomic data from endometriosis, and discovered a significant overlap of 433 hypoxia upregulated genes with endometriosis upregulated genes. The overlap was most 434 pronounced in a dataset of isolated endometrial stromal cells (Rekker et al., 2017) in which 435 endometriosis lesions were compared to healthy control endometrium. Notably, the high 436 proportion of hypoxia upregulated genes (39%, 157/402) of the intersected endometriosis 437 upregulated genes (Rekker et al., 2017) suggests that hypoxic gene regulatory programs 438 extensively contribute to the core gene regulation in the stroma of endometriotic lesions. 439 The overlap of 157 hypoxia and endometriotic stromal cell upregulated genes was 440 enriched in genes promoting angiogenesis, EMT and estrogen responses. Angiogenesis and 441 estrogen response were not among the most enriched pathways in the primary analysis of 442 hypoxia upregulated genes (Fig. 1B) suggesting for the presence of endometriosis specific 443 hypoxic interactions that are not present in stromal cells originating from healthy endometrium. 444 Our results support previous observations (Wu et al., 2012, 2019) that in endometriosis hypoxia 445 and estrogen may synergistically promote the growth of the lesions. For example, the major 446 angiogenic factor VEGFA was upregulated in our hypoxia experiment, and is known to be 447 regulated by both estrogen and hypoxia (Zhang et al., 2017). Among the angiogenesis enriched 448 genes, we observed substantial hypoxic upregulation of KLF2, a known repressor of T- 449 cells/monocyte activation and NFKB pathway (Jha and Das, 2017). Activation of NFKB 450 pathway has been associated with the initiation of menstruation (Evans and Salamonsen, 2014),

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451 and in the context of endometriotic niche the downregulation of NFKB pathway may contribute 452 to the ability of stromal cells to escape the clearance by immune system. 453 In order to systemically search for hypoxia upregulated TFs that drive endometriosis we 454 conducted promoter analysis of the overlap of 157 hypoxia and endometriosis upregulated genes. 455 We discovered that Jun/Fos family members JDP2 and JUND, and CEBP family members 456 CEBPB and CEBPD were both robustly hypoxia upregulated, and enriched in the promoters of 457 the overlapping genes. Of these, we selected JUND and CEBPD for protein level studies in deep 458 endometriosis and healthy control endometrium and found elevated immunohistochemical 459 staining of JUND and CEBPD in deep endometriosis compared to controls. 460 Our study highlights JunD as a potential hypoxia regulated intervention target in 461 endometriosis. The upregulation of Jun/Fos pathway components in endometriosis has been 462 reported in several studies (Hastings et al., 2006; Tamaresis et al., 2014) and previously C-JUN 463 NH2-terminal kinase inhibitor was reported to reduce endometriosis in baboons (Hussein et al., 464 2016). While cytokine profiling of endometriotic peritoneal aspirates detected Jun/Fos driven 465 cytokine expression was interpreted as a major component of macrophage directed cytokine 466 signature (Beste et al., 2014), our results suggest that endometriotic stromal cells that express 467 Jun/Fos factors contribute to the cytokine signatures of endometriosis. 468 CEBPD, which in our study was 5-fold induced by hypoxia in both ESF and DSC, has 469 been suggested to act as a tumor suppressor that in hypoxia turns into a growth promoter 470 (Balamurugan and Sterneck, 2013). Our immunohistochemical results showed increased CEBPD 471 protein levels in deep endometriosis lesions. This differs from a previous immunohistochemical 472 assessment of CEBPD in extra-ovarian endometriosis (Yang et al., 2002), where no differential 473 staining was reported between endometriosis and controls, potentially due to different types of 474 lesions investigated. Further, CEBPD is a paralog of CEBPB, which is a known core regulator of 475 decidualization (Wang et al., 2012; Tamura et al., 2017), however, both CEBPB and CEBPD 476 target decidual PRL promoter (Pohnke et al., 1999). Recent transcriptomic analysis have 477 indicated that CEBPD is early upregulated and late downregulated during decidualization 478 whereas CEBPB levels are not after the initial upregulation (Rytkönen et al., 2019). Putatively, 479 our observation of stronger hypoxia dependent transcriptomic upregulation of CEBPD together 480 with the promoter analysis suggests that CEBPD may have more pronounced regulatory role in 481 endometriosis compared to CEBPB.

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482 Recently described HIF binding sites provide mechanistic perspective on hypoxia 483 induced changes in the Jun/Fos or CEBP TF activities (Smythies et al., 2019). For example, in 484 HepG2 cells both HIF1 and HIF2 binding sites are enriched with CEBPD motifs (Smythies et 485 al., 2019), and in multiple cell types especially HIF2 binding sites are enriched with Jun/Fos 486 motifs (Smythies et al., 2019). Indirectly this suggests that also in endometrial stromal cells 487 HIF2 is a potential interaction partner for Jun/Fos TFs. On the other hand hypoxia related 488 regulatory interactions are not necessarily HIF mediated, but may proceed through changes in 489 chromatin structure via oxygen dependent histone lysine demethylases (KDM). For example, ER 490 receptor is regulated by KDM3A (Wade et al., 2015), which is an oxygen dependent histone 491 demethylase. Recently several KDMs, such as KDM5s (Batie et al., 2019) and KDM6s 492 (Chakraborty et al., 2019), were reported to direct extensive hypoxia dependent transcriptional 493 changes. Specifically, KDM6 activation has been associated with uterine fibroblast activation 494 (Nancy et al., 2018), which is concordant with our observation that hypoxia promotes 495 fibroblastic phenotype in endometrial stromal cells. 496 In conclusion, the global transcriptome analysis performed in this study suggests that 497 hypoxia enhances glycolytic energy metabolism and promotes fibroblastic phenotype (EMT) 498 and, thus may, interfere with the development of the quasi-epithelial state of DSC. Hypoxia also 499 modifies inflammatory pathways and partly counteracts PGR actions suggesting that hypoxia 500 affects regulatory networks that are essential for decidualization. Hypoxia upregulated genes 501 have significant overlap with previously detected endometriosis upregulated stromal genes 502 (Rekker et al., 2017) and promoter analysis of this overlap revealed that Jun/Fos and CEBP 503 transcription factors are potential hypoxic drivers of transcription in endometriosis. Of these we 504 validated the increased expression of JUND and CEBPD in endometriosis lesions using 505 immunohistochemistry. Overall the findings suggest that hypoxic stress constitutes related but 506 distinct transcriptional states in ESF and DSC, and that hypoxic regulatory programs contribute 507 to the core gene regulation in the stroma of endometriotic lesions. 508 509 Supplementary data 510 511 This is linked to the online version of the paper at XXX. 512

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513 Declaration of interest 514 515 The authors declare that there is no conflict of interest that could be perceived as prejudicing the 516 impartiality of the research reported. 517 518 Funding 519 520 Research reported in this publication was supported by European Commission Horizon 2020, 521 Marie Skłodowska-Curie IF (project 659668 EVOLPREG), Finnish Cultural Foundation, Jane 522 and Aatos Erkko Foundation, Päivikki and Sakari Sohlberg Foundation, Eemil Aaltonen 523 Foundation and Sigrid Juselius Foundation, as well as Turku Graduate School (UTUGS), 524 Biocenter Finland, and ELIXIR Finland. Work in the Wagner lab is supported by National 525 Cancer Institute Center Grant U54-CA209992. 526 527 Author contribution statement 528 529 KTR conceived and designed the study, conducted the cell cultures and RNA work, analyzed the 530 data and wrote the manuscript. TH participated in the laboratory work and analysis. MM 531 participated in the data analysis and writing of the manuscript. XM participated in the writing of 532 the manuscript. AP contributed in the sampling and participated in the writing. LLE provided 533 resources for the work and participated in the writing. MP and GPW participated in the design of 534 the work, writing of the manuscript and provided resources for the work. 535 536 Acknowledgements 537 538 We are grateful to Roger Babbitt and Jordan Pober lab (Yale University) for the help with 539 hypoxia cell culture. We thank Erica Nyman and Sinikka Collanus from the University of Turku 540 Histology core facility and Satu Orasniemi from the Institute of Biomedicine for their 541 contribution in immunohistochemistry. 542 543 References

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699 164. 700 Wang W, Taylor RN, Bagchi IC and Bagchi MK (2012) Regulation of human endometrial 701 stromal proliferation and differentiation by C/EBPβ involves cyclin E-cdk2 and STAT3. 702 Molecular Endocrinology (Baltimore, Md.) 26 2016–2030. 703 Wu M-H, Lu C-W, Chang F-M and Tsai S-J (2012) Estrogen receptor expression affected by 704 hypoxia inducible factor-1α in stromal cells from patients with endometriosis. Taiwanese 705 Journal of Obstetrics and Gynecology 51 50–54. 706 Wu S-P, Li R and DeMayo FJ (2018) Progesterone Receptor Regulation of Uterine Adaptation 707 for Pregnancy. Trends in Endocrinology & Metabolism. 708 Wu M-H, Hsiao K-Y and Tsai S-J (2019) Hypoxia: The force of endometriosis. The Journal of 709 Obstetrics and Gynaecology Research 45 532–541. 710 Xue W, Liu Y, Zhao J, Cai L, Li X and Feng W (2012) Activation of HIF-1 by 711 metallothionein contributes to cardiac protection in the diabetic heart. American Journal of 712 Physiology-Heart and Circulatory Physiology 302 H2528–H2535. 713 Yang S, Fang Z, Suzuki T, Sasano H, Zhou J, Gurates B, Tamura M, Ferrer K and Bulun 714 S (2002) Regulation of Aromatase P450 Expression in Endometriotic and Endometrial 715 Stromal Cells by CCAAT/Enhancer Binding Proteins (C/EBPs): Decreased C/EBPβ in 716 Endometriosis Is Associated with Overexpression of Aromatase. The Journal of Clinical 717 Endocrinology & Metabolism 87 2336–2345. 718 Yu J, Berga SL, Johnston-MacAnanny EB, Sidell N, Bagchi IC, Bagchi MK and Taylor RN 719 (2016) Endometrial Stromal Decidualization Responds Reversibly to Hormone Stimulation 720 and Withdrawal. Endocrinology 157 2432–2446. 721 Zhang L, Xiong W, Li N, Liu H, He H, Du Y, Zhang Z and Liu Y (2017) Estrogen stabilizes 722 hypoxia-inducible factor 1α through G protein-coupled estrogen receptor 1 in eutopic 723 endometrium of endometriosis. Fertility and Sterility 107 439–447. 724 Zuo R-J, Gu X-W, Qi Q-R, Wang T-S, Zhao X-Y, Liu J-L and Yang Z-M (2015) Warburg- 725 like Glycolysis and Lactate Shuttle in Mouse Decidua during Early Pregnancy. Journal of 726 Biological Chemistry 290 21280–21291. 727 728 729

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730 Tables 731 732 Table 1. Transcription factor binding site (TFBS) enrichment analysis in the promoters of 733 hypoxia (ESF and DSC) and endometriosis upregulated genes. Both prediction based 734 (TRANSFAC) and ChIP-seq based (GTRD) databases were searched for TFBS enrichment using 735 the 157 hypoxia and endometriosis upregulated genes as foreground and all hypoxia upregulated 736 genes as a background. Top enriched TFBS motifs are displayed by “Site FDR” rank and 737 “Hypoxia up” column displays the presence of a TF homologs corresponding to the TFBS motifs 738 among top hypoxia upregulated TFs (from Fig. 2B). Endometriosis upregulated genes are from 739 (Rekker et al., 2017). See Supplementary Table 4 for the input gene lists and full TFBS 740 enrichment lists. 741 TRANSCFAC Site FDR Hypoxia up GTRD Site FDR Hypoxia up OCT1_04 4,1E-49 na MEF-2A.1 7,5E-17 na TATA_01 4,1E-49 na B-ATF.1 7,5E-17 na MEF2_03 3,1E-38 na MEF-2C.1 3,5E-15 na RSRFC4_01 1,7E-32 na CEBPalpha.1 7,5E-13 CEBPB, CEBPD FOXJ2_02 1,5E-28 na TBP.1 5,7E-10 na MEF2_01 1,7E-26 na STAT6.1 1,1E-06 STAT4 PBX1_01 8,4E-26 na SOX-2.1 1,1E-06 SOX12 MEF2_02 2,8E-25 na GATA-2.1 1,1E-06 na GATA2_01 2,4E-24 na c-Jun.1 2,9E-06 JDP2, JUND HNF1_01 5,6E-23 na TCF-7L1.1 6,7E-06 na CDP_01 3,3E-21 na SMAD1.1 9,6E-06 SMAD7 AP1_01 1,5E-20 JDP2, JUND CEBPdelta.1 1,1E-05 CEBPB, CEBPD BRN2_01 1,3E-19 na FOXP2.1 1,4E-05 FOXP4 CEBP_Q2 2,0E-19 CEBPB, CEBPD PBX-1.1 1,6E-05 na AREB6_04 7,0E-19 na IRF-4.1 2,1E-05 na EVI1_05 1,4E-17 na PU1.1 2,3E-05 na PAX4_04 1,6E-17 na STAT5A.1 7,9E-05 STAT4 OCT1_01 4,0E-17 na STAT1.1 2,8E-04 STAT4 EN1_01 6,3E-17 na GATA-3.1 3,0E-04 na MEF2_04 2,0E-16 na PPARgamma 3,2E-04 na 742 743 744 745

25 bioRxiv preprint doi: https://doi.org/10.1101/2019.12.21.885657; this version posted December 23, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

746 Figure Legends 747 748 Figure 1. Hypoxia regulated gene pathways in endometrial stromal fibroblasts (ESF) and

749 endometrial stromal cells (DSC). A) Differentially transcribed genes in hypoxia (1% O2, 5%

750 CO2, 24 hours, FC > 2, FDR < 0.01, TPM > 2). Arrows up mark upregulated genes and arrows 751 down mark downregulated genes. B) Hierarchical clustering of the functional enrichment 752 categories from METASCAPE (P values, default; see Supplemental Table S1) using the genes 753 with significantly increased and decreased transcription as an input. The functional categories are 754 from GO Biological Processes (G), Hallmark gene sets (H) and KEGG (K). Arrows mark the 755 upregulated or downregulated genes in the four conditions. C) Top 40 genes with increased 756 transcription in hypoxic conditions in ESF and DSC (norm = normoxia, hyp = hypoxia), 757 presented using hierarchical clustering (Euclidean, complete) of averages of absolute TPM 758 values (> 20 TPM). D) “Epithelial mesenchymal transition” (EMT) term associated hypoxia 759 upregulated and highly transcribed genes (> 200 TPM). E) All “TNFA signaling via NFKB” 760 term associated genes differentially transcribed under hypoxia (> 20 TPM). TNFA, Tumor 761 Necrosis Factor A; NFKB, Nuclear Factor Kappa B. See Supplementary Table 1 for the full lists 762 of hypoxia regulated genes, the gene lists of detected enrichment categories and TPM values 763 used for the figures. 764 765 Figure 2. Top hypoxia regulated transcription factors (TF) in endometrial stromal fibroblasts 766 (ESF) and endometrial stromal cells (DSC). A) Differentially transcribed TFs in hypoxia (1%

767 O2, 5% CO2, 24 hours, FC > 2, FDR < 0.01, TPM > 2) and TFs regulated by decidualization 768 regulator progesterone receptor (PGR) PGR siRNA (Mazur et al., 2015) (FC > 2). Arrows up 769 mark upregulated genes and arrows down mark downregulated genes. Top 25 TFs with increased 770 (B) or decreased (C) transcription in ESF and DSC under hypoxia (norm = normoxia, hyp = 771 hypoxia) presented using hierarchical clustering (Euclidean, complete) of averages of absolute 772 TPM values (> 20 TPM). D) 29 Hypoxia regulated (ESF and/or DSC) and PGR downregulated 773 (siRNA upregulated) TFs presented using hierarchical clustering (Euclidean, complete) of 774 averages of absolute TPM values (> 20 TPM). * Notes a subset of highly transcribed and PGR 775 downregulated TFs for which hypoxia partly restores the ESF like transcriptional state (FOSL1, 776 KLF6, BHLHE41, HMGA1, ETV5). FOSL1, FOS Like 1, AP-1 Transcription Factor Subunit;

26 bioRxiv preprint doi: https://doi.org/10.1101/2019.12.21.885657; this version posted December 23, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

777 KLF6, Kruppel Like Factor 6; BHLHE41, Basic Helix-Loop-Helix Family Member E41 (DEC2); 778 HMGA1, High Mobility Group AT-Hook 1; ETV5, E26 transformation-specific Variant 5. See 779 Supplementary Table 2 for the lists of hypoxia and PGR regulated TFs and the lists of the 780 specific intersections with corresponding TPM values. 781 782 Figure 3. Overlaps of hypoxia regulated and endometriosis regulated genes. (A) Significance of 783 the overlaps of hypoxia regulated genes and three representative endometriosis datasets 784 determined using Fishers exact test. Overlaps between hypoxia upregulated genes with stroma 785 specific endometriosis upregulated genes (Rekker et al., 2017) were highly significant (blue and 786 green boxes). Other analyzed datasets were a whole tissue (cell type heterogeneous) 787 endometrium dataset of endometriosis patients versus healthy controls (Tamaresis et al., 2014) 788 and endometriosis associated genes from DisGeNET v5.0 database. (B) Venn diagram showing 789 the number of genes in (Rekker et al., 2017) endometriosis upregulated genes (dashed line) with 790 overlapping ESF and DSC hypoxia upregulated genes (unique green and blue, respectively). 791 Total of 157 genes that were hypoxia and endometriosis regulated were then used as an input for 792 pathway enrichment analysis (C) of which the top enrichment categories are displayed. (D) 793 Heatmap of genes in the “Angiogenesis” enrichment term. (E) Heatmap of genes in the 794 “Estrogen response early” enrichment term. The functional categories are from GO Biological 795 Processes (GO), Hallmark gene sets (H) and KEGG (K). See Supplementary Table 3 for the 796 original and overlapping gene lists, enrichment gene lists and corresponding TPM values used 797 for the heatmaps. 798 799 Figure 4. Immunohistochemical staining of JunD Proto-Oncogene (JUND) and CCAAT 800 Enhancer Binding Protein Delta (CEBPD) in deep infiltrating endometriosis lesions and healthy 801 control endometria. (A, B) Representative JUND staining shows increased expression in 802 endometriosis lesions than control endometrium in both stromal cells and epithelial cells. (C, D) 803 Representative CEBPD staining shows that CEBPD is expressed in both stroma and epithelium, 804 and is highly expressed in the stroma of endometriosis lesion. E = epithelium, S = stroma.

27 bioRxiv preprint doi: https://doi.org/10.1101/2019.12.21.885657; this version posted December 23, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Fig. 1 A B -ORg10(3)

0 2 3 4 6 10 20

epithelial mesenchymal transition (H)05930: HALL0A5K (3I7H(LIAL 0(6(1CHY0AL 75A16I7I21 hypoxia (H)05891: HALL0A5K HY32XIA tissue morphogenesis (G)G2:0048729: tLVVXH PRrSKRgHnHVLV vasculature development (G)G2:0001944: YDVFXODtXrH GHYHORSPHnt TNFA signaling via NFKB (H)05890: HALL0A5K 71)A 6IG1ALI1G 9IA 1)KB skeletal system development (G)G2:0001501: VNHOHtDO VyVtHP GHYHORSPHnt regulation of cell adhesion (G)G2:0030155: rHgXODtLRn RI FHOO DGKHVLRn response to oxygen levels (G)G2:0070482: rHVSRnVH tR RxygHn OHYHOV negative regulation of protein modification process (G)G2:0031400: nHgDtLYH rHgXODtLRn RI SrRtHLn PRGLILFDtLRn SrRFHVV response to growth factor (G)G2:0070848: rHVSRnVH tR grRwtK IDFtRr heart development (G)G2:0007507: KHDrt GHYHORSPHnt supramolecular fiber organization (G)G2:0097435: VXSrDPROHFXODr ILEHr RrgDnLzDtLRn response to wounding (G)G2:0009611: rHVSRnVH tR wRXnGLng regulation of protein kinase activity (G)G2:0045859: rHgXODtLRn RI SrRtHLn NLnDVH DFtLYLty pathways in cancer (K)KVD05200: 3DtKwDyV Ln FDnFHr reproductive structure development (G)G2:0048608: rHSrRGXFtLYH VtrXFtXrH GHYHORSPHnt transmembrane receptor protein tyrosine kinase signaling (G)G2:0007169: trDnVPHPErDnH rHFHStRr SrRtHLn tyrRVLnH NLnDVH VLgnDOLng SDtKwDy cellular response to hormone stimulus (G)G2:0032870: FHOOXODr rHVSRnVH tR KRrPRnH VtLPXOXV E2F targets (H)05925: HALL0A5K (2) 7A5G(76 regulation of cellular response to stress (G)G2:0080135: rHgXODtLRn RI FHOOXODr rHVSRnVH tR VtrHVV D6CGRwn (6)GRwn D6CXS (6)XS ESF DSC ESF DSC

Top hypoxia TNFA signaling via NFKB C TPM D Top EMT TPM E TPM 3000 1000 CTGF COL1A1 SERPINE1 HSPB6 THBS1 20000 CYR61 DKK1 2500 IGFBP3 MMP14 SQSTM1 800 ACTA2 2000 TGFBI VEGFA 15000 RARRES2 TFPI2 SGK1 600 MIF 1500 CXCL12 PNRC1 CDC42EP3 CDH11 1000 10000 CEBPB ACTC1 LRP1 POSTN BHLHE40 400 S100A10 500 DCN FOSL1 PPME1 FBN1 5000 PFKFB3 200 COL11A1 0 PDGFRB PPP1R15A ILK COL6A3 JUN MAZ CTGF 0 ITGBL1 PLK2 0 BNIP3 ADAM12 F2RL1 TNFRSF12A OXTR IRF1 CKB MYL9 EGR1 MFAP5 SERPINE2 IL7R ID2 TIMP1 HMOX1 JUNB BHLHE41 CYR61 MAFF MT1X SERPINE1 BMP2 MT1E PPIB IL1B FAM176A THY1 PTGER4 HAPLN1 GPC1 RELB KRT18 BGN CPA4 TRIB1 MAMDC2 PFN2 PLAUR UCP2 EDIL3 TNC SERTAD4 ENO2 ICAM1 OLR1 VEGFA TIPARP KLF2 RHOB PALM CFLAR ANKRD37 NNMT ETS2 HTRA1 SBF2−AS1 PER1 FGF9 ITGB5 NFIL3 C8orf58 ANPEP STAT5A CDKN1C COL7A1 BHLHE40 LDLR COL12A1 ANGPTL4 SPHK1 PCOLCE RP11−48O20.4 PLAU DYSF DKK1 SERPINB2 ASPN SERPINH1 PHLDA1 MGAT2 PLOD1 TPD52L1 PDE4B SPOCK1 OPN3 GFPT2 TPM2 EMC6 NAMPT DEXI COL4A1 F3 TUFT1 LOX CLIC3 LOXL2 ABCA1 PAPPA2 TPM1 SAT1 CYGB TAGLN DUSP1 RPLP0P2 GADD45A HK2 ACTA2 GPR146 FN1 GADD45B SIX5 COL4A2 SLC2A3 LCE2A COL5A1 PDLIM5 ACTG2 FSTL1 RHOB PPP1R14A INHBA DDT VIM AK4 CALD1 ATP2B1 CLEC3B SPARC SOD2 NOG IGFBP3 IL6ST ESFnorm ESFhyp DSCnorm DSChyp ZNF579 ESFnorm ESFhyp DSCnorm DSChyp ESFnorm ESFhyp DSCnorm DSChyp bioRxiv preprint doi: https://doi.org/10.1101/2019.12.21.885657; this version posted December 23, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Fig. 2 A B C siPGR DSC siPGR Top TFs Top TFs 29 /50 TPM TPM CREB3L1 TBX3 PDLIM1 800 PRDM1 800 FHL2 ANKRD10 ID3 KLF13 600 KLF7 600 ELK3 SLC2A4RG PER1 ASB1 TGFB1I1 400 400 PPARA ESF TSC22D3 66/110 ATF7IP MAZ RUNX2 200 LBH 200 MKL2 ID2 TBX2 37 PPP1R13L RELB 0 DSC KLF2 0 NEO1 /100 JDP2 NR1D2 JUND SALL1 EMX2 ETV1 ESF LMCD1 ARNT2 HDAC9 CBX4 EGR1 CEBPB YLPM1 D 29 siPGR & hypoxia SMAD7 TPM SATB1 CITED2 DDIT3 ETS2 500 KLF2 RFX2 BPTF EGR2 FLI1 400 MSC POLR3E ZNF215 HOXA7 RFX5 NR4A3 300 EBF4 CITED4 SIX5 HES6 PHC3 200 ZFPM1 SALL4 SAP30 GCFC2 HEY1 ZBTB16 HES1 100 ZNF224 LEF1 KLF9 FOS 0 SOX12 STAT5A GATA6 MKX VDR FOXO1 MAFF ID1 MYOCD ETV4 KLF4 RUNX2 OSR2 ETV1 DDX20 PBX1 ARNT2 STAT3 HDAC9 BHLHE41 EGR1 BHLHE40 ZBTB38 CDKN2B MXI1 HUWE1 FOSL1 CTNNB1 BHLHE41* HOXA10 ETV5 * HIF1A LBH * CEBPD ESFnorm ESFhyp DSCnorm DSChyp EPAS1 HMGA1 ESFnorm ESFhyp DSCnorm DSChyp KLF6 * ESFnorm ESFhyp DSCnorm DSChyp * bioRxiv preprint doi: https://doi.org/10.1101/2019.12.21.885657; this version posted December 23, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Fig. 3 A B C Pathway enrichment Rekker_2017_UP GO / HALLMARK / KEGG Log10(P)

-Log10(P) Angiogenesis (GO) -12.03 25 ESFup Epithelial mesenchymal transition (H) -8.10 25 7.8e+00 1.3e+01 5.1e+00 3.7e+00 DISGENET 245 56 Estrogen response early (H) -7.92 7.8e+00 1.3e+01 5.1e+00 3.7e+00 DISGENET 20 Hypoxia (H) -6.78 20 62 = 157 15 Apelin signaling pathway (K) -6.51 15 3.8e+00 1.7e+01 2.6e+01 1.8e+01 Rekker_2017_UP 39 endometriosis 3.8e+00 1.7e+01 2.6e+01 1.8e+01 Rekker_2017_UP 10 & hypoxia up Angiogenesis 10 DSCup D TPM KLF2 2.9e+00 2.6e+00 4.2e+00 1.4e+00 5 APLN 1400 2.9e+00 2.6e+00 4.2e+00 1.4e+00 5 Rekker_2017_DOWN Rekker_2017_DOWN ESM1 1200 NOS3 0 0 COL8A2 1000 EDN1 E Estrogen response early 800 3.8e
10 4.8e
05 4.6e+00 1.1e+01 Tamaresis_2014_UP TPM GATA6 3.8e−10 4.8e−05 4.6e+00 1.1e+01 Tamaresis_2014_UP TBXA2R 200 600 HSPB8 FZD8 400 KRT18 ANXA3 SLC7A5 FOXC1 200 SHB 2.9e
03 4.6e
06 8.0e
08 2.9e
13 150 2.9e−03 4.6e−06 8.0e−08 2.9e−13 Tamaresis_2014_DOWN Tamaresis_2014_DOWN FOXC1 ANG 0 INHBB EGFL7

DSCdown ESFdown ESFup DSCup PTK2B

DSCdown ESFdown ESFup DSCup KRT8 TPD52L1 100 NPR1 PLAAT3 DYSF S1PR1 SCARB1 PDGFA SH3BP5 50 HMOX1 ESFnorm ESFhyp DSCnorm DSChyp MCAM JCAD 0 CCN2 SERPINE1 ESFnorm ESFhyp DSCnorm DSChyp bioRxiv preprint doi: https://doi.org/10.1101/2019.12.21.885657; this version posted December 23, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Fig. 4 A E

S JUND endometrium

B

E

S JUND lesion

C

E

S CEBPD endometrium

D E S CEBPD lesion