Bioinformatics analysis for identifying hub genes in endometriosis and recurrent implantation failure: molecular pathways to enhanced IVF success

Background Recurrent embryo implantation failure (RIF) poses a considerable obstacle in the management of in vitro fertilization (IVF), as IVF failure has been linked to the presence of endometriosis, the growth of endometrial‑ like tissue outside the uterus. Therefore, this study aimed to reveal the molecular mechanisms connecting endome‑ triosis and RIF, offering valuable knowledge on potential therapeutic targets and biomarkers.

A comprehensive investigation was conducted on gene expression data from the GEO database, focus‑ ing on three datasets related to endometriosis and RIF, which revealed distinct gene expression patterns and facili‑ tated functional enrichment analysis to identify significant biological processes and molecular pathways associated with these differentially expressed genes. Protein–protein interaction networks were also established to identify critical genes.

A total of 43 differentially expressed genes (DEGs) were identified, shared between endometriosis and RIF, with enrichment analysis highlighting pathways related to interleukin‑6 signaling, FOXO‑mediated transcription, smooth muscle contraction, and semaphorin interactions. Gene ontology studies revealed the significance of sig‑ nal transduction and apoptosis regulation. ESR1, SOCS3, MYH11, CYP11A1, and CLU were identified as hub genes with potential as therapeutic targets and diagnostic indicators.

This study advances our understanding of the molecular framework underlying endometriosis and RIF. This presents potential possibilities for tailored treatment approaches and enhanced therapeutic results for individuals experiencing repeated or severe reproductive difficulties.

Recurrent embryo implantation failure, In vitro fertilization, Endometriosis, Bioinformatics, Functional enrichments, Hub gene †Parvin Hakimi and Mahshid Alborzi contributed equally to this work. *Correspondence: Maryam Rezazadeh [email protected] Soudeh Ghafouri‑Fard [email protected] Full list of author information is available at the end of the article Page 2 of 12Hakimi et al. Middle East Fertility Society Journal (2025) 30:32

Recurrent embryo implantation failure (RIF) is a per - plexing syndrome that poses significant obstacles in the realm of in  vitro fertilization (IVF), causing frustration among both patients and professionals [1, 2]. However, it is widely acknowledged that RIF can be defined as the inability to achieve clinical conception following three or more excellent-quality embryo transfers or the trans - fer of ≥ 10 embryos over multiple periods, with the spe - cific number of transfers determined by each individual reproductive medical center [3]. There are varying defini- tions of RIF among IVF centers. It is well acknowledged that the inability to achieve pregnancy after two or more cycles of embryo transfer for people is considered RIF [4, 5]. These failures have the potential to impose sig - nificant psychological and financial burdens on infertile couples [6]. Currently, there is a growing focus on strate - gies to enhance pregnancy outcomes in individuals with RIF, including the development of personalized endome - trial receptivity assays (e.g., the Endometrial Receptivity Array) to guide optimal embryo transfer timing [7]. His - torically, the primary factor attributed to RIF has been the perceived quality of the embryo. Impaired uterine receptivity has been identified as a significant factor con - tributing to treatment failure in cases where high-quality embryos are transplanted [8]. In general, several factors related to structural abnormalities of the uterus, such as congenital disabilities and acquired conditions [9], endo - metrial thickness [10, 11], chronic endometritis [12], endometrial perfusion [13], and uterine peristalsis [14] have the potential to influence endometrial receptivity and subsequently affect embryo implantation. Furthermore, the presence of ectopic endometrial tis - sue, known as endometriosis, has been identified as a probable factor in IVF in some instances [15, 16]. Endo- metriosis represents a significant hurdle for women in their reproductive years, incorporating chronic pain and diminished fertility. The presence of an estrogen-depend- ent stroma and endometrial glands, typically located in the pelvic region but not exclusively, distinguishes this syndrome [17]. Because surgical visualization remains the diagnostic gold standard, prevalence estimates vary widely [18], underscoring the need for non-invasive biomarkers such as circulating microRNAs or cytokine panels. Endometriosis is progressively being accepted as a widespread medical problem associated with infertil - ity and a primary element contributing to the failure of IVF procedures. However, the extent to which endome - triosis adversely affects the outcomes of in vitro fertiliza - tion remains a point of contention [15]. An earlier study has proven that the existence of endometriosis influences the reaction to ovarian stimulation [16]. There is a wide - spread opinion that the presence of endometriotic lesions in the pelvic area creates an unfavorable microenviron - ment that interferes with the steps of oocyte fertilization and the early development of the embryo within the fal - lopian tubes in vivo. With regard to IVF initiatives, ovar - ian endometriosis may affect the ovarian reserve and sensitivity to ovarian stimulation. These outcomes con - tribute to lower incidences of fertilization and pregnancy in patients with endometriosis receiving IVF compared to other patient cohorts [16]. The field of bioinformatics has yielded significant find - ings regarding the correlation between endometrio - sis and IVF failure. A study employed transcriptomic analysis to investigate the underlying biological mecha - nisms associated with endometrial receptivity (ER) in various physiological contexts, specifically focusing on natural cycles [19]. The goal of this study was to dis - cover the unique ER profile associated with regulated ovarian stimulation cycles, which might assist in detect - ing genetic abnormalities in patients with RIF undergo - ing IVF. Through the reanalysis of microarray data, this study revealed a significant downregulation of cell adhe - sion function, indicating potential disruptions in embryo implantation [19]. These bioinformatics-driven inves - tigations highlight the significance of employing com - putational approaches to unravel the complex interplay between endometriosis and IVF failure. By elucidating the molecular mechanisms involved, these studies con - tribute to a deeper understanding of the factors con - tributing to IVF outcomes and may facilitate the design of targeted interventions and personalized treatment modalities for endometriosis. In this study, we integrate multiple microarray datasets to uncover shared differentially expressed genes (DEGs) and pathways between endometriosis and RIF, with the goal of identifying candidate biomarkers and druggable targets for clinical application. By mapping these shared molecular signatures—ranging from inflammatory cytokine networks to oxidative‐stress regulators—we aim to lay the groundwork for future clinical trials testing interventions to enhance endometrial receptivity. Ulti - mately, these insights have the potential to inform preci - sion medicine strategies and improve IVF success rates for patients burdened by RIF and endometriosis.

Microarray data source The gene expression datasets used in this investiga - tion were obtained from the GEO database, accessible at https:// www. ncbi. nlm. nih. gov/ geo/. A total of 2055 records pertaining to endometriosis and 159 datasets pertaining to RIF in Homo sapiens were acquired from the designated database. Datasets were selected based on the following criteria: (1) inclusion of both disease Page 3 of 12 Hakimi et al. Middle East Fertility Society Journal (2025) 30:32 and control samples, (2) availability of raw/processed data, (3) sample size ≥ 5 per group, (4) human endo - metrial tissue focus, and (5) exclusion of low-quality or non-relevant studies (e.g., non-endometrial samples, animal/cell-line studies). After conducting a thorough review, three specific gene expression profiles (GSE7305 [20], GSE11691 [21], and GSE26787 [22]) were selected. Two distinct platforms were used in this study. GSE7305 and GSE26787 used the Affymetrix GPL570 platform, whereas GSE11691 used the Affymetrix GPL96 platform. All data were publicly available via the Internet, and the current research did not include any experiments on either human subjects or animals performed by any of the authors. The identification of shared DEGs The analysis was performed using the GEOexplorer [23] web platform (https:// geoex plorer. rosal ind. kcl. ac. uk) to ensure interactive and reproducible microarray data assessment. Raw CEL files from GSE11691 (18 samples: nine normal endometrium vs. nine endometrium from individuals with endometriosis), GSE7305 (20 samples: ten endometriosis vs. ten normal endometrium), and GSE26787 (10 samples: five RIF vs. five viable endome - trium) were retrieved. All datasets underwent identical preprocessing—

correction, quantile normalization, and log₂-transformation—using the affy R package. Normali - zation success was confirmed by inspecting density plots (Fig. 1). Due to the use of different Affymetrix platforms (GPL96 for GSE11691 vs. GPL570 for GSE7305), the two endometriosis datasets were analyzed independently to avoid cross-platform artifacts. Differential expression analysis was performed with moderated t-tests in limma, applying thresholds of |log₂ fold-change|≥ 1.5 and Benjamini–Hochberg adjusted p-value < 0.01 to define significant DEGs. The |log₂FC|≥ 1.5 cutoff was selected based on precedent in endometriosis transcriptome studies to prioritize the most robust expression changes. All DEGs without valid gene-symbol annotations were excluded. Finally, shared DEGs were identified by intersecting the independent DEG lists from GSE7305 and GSE11691 (endometriosis) with those from GSE26787 (RIF). The overlap of genes was visualized in a Venn diagram (Fig. 2) and used for downstream functional analyses. Gene ontology (GO) and Reactome pathway enrichment analyses of DEGs We implemented the EnrichR library for functional annotation and pathway enrichment analysis to explore the potential biological mechanisms associated with DEGs. Our investigation involved the utilization of GO and Reactome pathway analysis techniques [24]. GO, a valuable bioinformatics tool, allows the annotation of genes and examination of the biological processes associ - ated with these genes [25, 26]. Reactome, an extensively curated online library and knowledge resource, provides comprehensive information on biological pathways and their corresponding interactions [27]. A statistical signifi- cance level of p < 0.05 was considered appropriate. Protein–protein interaction (PPI) network of DEGs and hub genes The Search Tool for the Retrieval of Interacting Genes Database (STRING) is commonly used to assess PPI data [28]. Accessible at https:// string- db. org/, this web-based resource proves valuable in the examination of the func - tional associations between proteins, offering potential insights into the etiology and progression of diseases. In this study, the STRING database was used to probe the identified DEGs from the two datasets to uncover poten - tial interconnections between these genes. Interactions with a cumulative score exceeding 0.4 were deemed sta - tistically significant and included in the construction of the PPI network. To fulfill this objective, Cytoscape, a widely accessible bioinformatics software system devel - oped for the visualization of biological interaction net - works, was used [29]. In addition, we identified hub genes that may play a significant role in the development of endometriosis and RIF by evaluating the Maximal Clique Centrality (MCC) of each protein node in Cytoscape using the CytoHubba plugin [30]. In conclusion, the iden- tification of shared hub genes revealed the top five genes that exhibited significant MCC values in the context of RIF and endometriosis.

Identification of DEGs in endometriosis and RIF We performed differential expression analysis separately for each dataset using the GEOexplorer web tool. Raw CEL files were first background–corrected and quantile- normalized, and probe-level data were collapsed to gene- level using the highest-variance probe per gene. We then applied the limma package’s linear modeling pipeline with empirical Bayes moderation. To control for mul - tiple tests, we used the Benjamini–Hochberg method to adjust the p-values. The inclusion criteria for DEGs were |log₂ fold‐change|≥ 1.5 and adjusted p-value < 0.01. Before analysis, dataset normalization was verified by inspecting the density plots of the log₂‐intensity distribu - tions (Fig. 1). Genes lacking annotations in the final gene list were excluded. Under these criteria, GSE7305 yielded 773 DEGs, GSE11691 yielded 37 DEGs, and GSE26787 yielded 506 DEGs, respectively. Intersection analy - sis identified 43 genes differentially expressed in both Page 4 of 12Hakimi et al. Middle East Fertility Society Journal (2025) 30:32 endometriosis (combined GSE7305 and GSE11691) and RIF (GSE26787) (Fig. 2). Table 1 lists these shared DEGs, including gene symbols, log₂ fold-change, and adjusted p-values in each dataset. Functional enrichment analysis Reactome pathway analysis revealed that “Interleu - kin-6 Family Signaling, ” “FOXO-mediated Transcrip - tion of Oxidative Stress, Metabolic, and Neuronal Genes, ” “Smooth Muscle Contraction, ” “Semaphorin Interactions, ” and “Muscle Contraction” were the top five enriched pathways associated with the DEGs. The top five enriched BPs were “Negative Regulation of Sequestering of Calcium Ion, ” “Release of Sequestered Calcium Ion into Cytosol, ” “Regulation of Apoptotic Process, ” “Response to Organic Cyclic Compound, ” and “Calcium Ion Transmembrane Import into Cytosol. ” A detailed depiction of the functional enrichment net - work is shown in Fig.  3, and more information is pro - vided in Table 2 . Fig. 1 Density plot of gene expression microarray datasets. This density plot illustrates the distribution of gene expression values across three distinct datasets: GSE11691, GSE26787, and GSE7305. The x‑axis represents the density of gene expression values, while the y‑axis represents the intensity. This plot serves as an initial examination of data normalization, providing insights into the distribution and intensity of gene expression values within the analyzed datasets Page 5 of 12 Hakimi et al. Middle East Fertility Society Journal (2025) 30:32 Identification of hub genes and network analysis The PPI network associated with the identified DEGs that are often seen in both endometriosis and RIF was ana - lyzed using the Cytoscape STRING plugin. The top five hub genes were identified based on the MCC using the Cytoscape cytohubba plugin. The genes that were cat - egorized included ESR1, SOCS3, MYH11, CYP11A1, and CLU, as shown in Fig. 4. Table 3 provides a detailed over- view of the hub genes shared between endometriosis and RIF.

The relationship between endometriosis and IVF out - comes has been the subject of ongoing research and debate. Recent research has provided insights into the possible impact of endometriomas, a common manifes - tation of endometriosis, on the success rates of IVF. In this context, Hamdan et  al. highlighted the restricted exploration of the unfavorable consequences linked with endometrioma during IVF/ICSI procedures [31]. This study underlined the significance of consider - ing the risks of surgical intervention and its potential impact on ovarian reserve compared to the complica - tions that arise from the persistence of endometriomas during IVF/ICSI [31]. Moreover, Coccia et  al. investi - gated the function of peritoneal fluid in women with moderate endometriosis and its impact on the efficacy of reproductive interventions. The study’s findings indi - cated that the absence of peritoneal fluid from infer - tile women with moderate endometriosis in the media resulted in an increase in the fertilization capacity of oocytes and enhanced embryo development potential [32]. As research further explores the intricate connec - tion between endometriosis and IVF failure, it becomes imperative to uncover strategies that can enhance the probability of successful conception in women affected by this condition. Such strategies could include the targeted modulation of peritoneal cytokine profiles or Fig. 2 Venn diagram of shared DEGs in endometriosis and RIF. The Venn diagram visually represents the overlap of DEGs identified in three distinct datasets: GSE7305, GSE11691, and GSE26787, each associated with either endometriosis or RIF. Notably, 43 DEGs were found to be shared between the endometriosis datasets and the RIF dataset. This intersection highlights specific genes with potential relevance to both endometriosis and RIF Table 1 Shared genes in endometriosis and RIF Gene symbols of DEGs shared in endometriosis and RIF GALNT15, DAPK1, MYH11, LMOD1, RNASE4, PAPSS2, CLU, DPP6, CYP11A1, PTGER3, ARHGEF28, IGFBP5, CPXM2, PODN, TWIST2, PIGR, TDGF1P3/// TDGF1, ITPR1, CCDC80, SYNPO, EHBP1L1, FBXO32, LAMA4, RPP25, MAN1C1, SOCS3, MIR3671///MIR101‑1, FRZB, MCOLN3, PLCH1, PLXNA4, NSG1, SORBS2, LIFR, MFAP3L, IGKC, HOXB‑AS3, BIRC5, TMEM100, ESR1, ANGPT1, SPDEF, TRH Page 6 of 12Hakimi et al. Middle East Fertility Society Journal (2025) 30:32 refined surgical approaches to balance ovarian reserve preservation with lesion removal. To identify the shared molecular components and pathways implicated in both endometriosis and RIF, a comprehensive bioinformatics analysis was performed to evaluate the association between genes showing dif - ferential expression and the respective conditions. Our study used bioinformatics technologies to identify shared DEGs linked to endometriosis and RIF. The primary goal of this study was to discover previously unknown func - tional genes and pathways that play a role in the devel - opment of both disorders. Following the identification of the top five Reactome pathway enrichments for shared DEGs between endometriosis and RIF, our comprehen - sive bioinformatics analysis aimed to uncover the poten - tial molecular connections and underlying pathways implicated in both conditions. The Reactome pathway enrichment results highlighted significant biological Fig. 3 Functional enrichment network. This comprehensive network diagram illustrates functional enrichment analysis results, encompassing GO biological processes and Reactome pathway enrichment. In the network, nodes represent DEGs, which are key molecular players associated with endometriosis and RIF. These DEGs are interconnected with various functional enrichments, including biological processes and pathways. The connections between DEGs and functional enrichments signify the significant involvement of specific genes in particular biological processes and pathways. This network serves as a valuable resource for understanding the functional relationships between DEGs and functional enrichments, facilitating the identification of potential therapeutic targets and diagnostic markers for endometriosis and RIF Table 2 Functional enrichments of the EC metastasis DEGs Term Library p-value q-value z-score Combined score Regulation of signal transduction (GO: 0009966) GO_Biological_Process 0.00007175 0.03379 13.13 125.3 Negative regulation of cellular amide metabolic process (GO: 0034249) GO_Biological_Process 0.0008951 0.1193 17.52 123 Positive regulation of supramolecular fiber organization (GO: 1,902,905) GO_Biological_Process 0.001054 0.1193 16.52 113.2 Regulation of apoptotic process (GO: 0042981) GO_Biological_Process 0.001088 0.1193 4.947 33.76 Interleukin‑6 Family Signaling R‑HSA‑6783589 Reactome 0.001266 0.1874 43.15 287.9 Cardiac muscle cell development (GO: 0055013) GO_Biological_Process 0.001266 0.1193 43.15 287.9 FOXO‑mediated transcription of oxidative stress, metabolic and neu‑ ronal genes R‑HSA‑9615017 Reactome 0.001849 0.1874 35.15 221.2 Smooth muscle contraction R‑HSA‑445355 Reactome 0.004034 0.1874 23.13 127.5 Semaphorin interactions R‑HSA‑373755 Reactome 0.008746 0.1874 15.28 72.41 FOXO‑mediated transcription R‑HSA‑9614085 Reactome 0.009011 0.1874 15.04 70.81 Page 7 of 12 Hakimi et al. Middle East Fertility Society Journal (2025) 30:32 processes and interactions that may contribute to the pathogenesis of endometriosis and RIF. First, the “Inter - leukin-6 Family Signaling” pathway is a critical regulatory pathway involved in the immune response and inflam - mation [33]. This pathway includes various interleukin-6 family cytokines that play pivotal roles in modulating immune and inflammatory reactions in both RIF and endometriosis. The available data indicate that the func - tional instability of the endometrial immune system is a significant pathophysiological mechanism associated with RIF. During implantation, many types of interleu - kins (ILs) are released by epithelial and stromal endome - trial cells. These interleukins include IL-6, IL-10, IL-12, IL-15, IL-18, and leukemia inhibitory factor [34]. These ILs establish a network that coordinates the growth and development of uterine natural killer cells. Addition - ally, they regulate the activity of regulatory T and B cells, which suppress the production of antibodies that may harm the fetus. Furthermore, ILs facilitate trophoblast invasion and decidua formation [34]. Elevated serum IL-6 concentrations are associated with infertility in patients with endometriosis [35]. The presence of disorders linked to IL-6 and IL-6R has been shown to be associated with the development of endometriosis [36]. Endometriosis growth is facilitated by an elevation in soluble interleu - kin-6 receptor levels within the peritoneal fluid, which subsequently enhances the bioactivity of IL-6 [36]. These findings suggest that targeting IL‐6 signalingusing mono - clonal antibodies [37] and immunotherapy [38] could be explored in clinical trials to improve implantation success in women with endometriosis and RIF. Furthermore, the pathway known as “FOXO-mediated transcription of oxidative stress, metabolic and neuronal genes” plays a crucial role in directing the transcrip - tional regulation of genes associated with oxidative stress and metabolic activities. The regulation of this pathway is governed by the FOXO family of transcription fac - tors, which are involved in the modulation of cellular responses to oxidative stress and metabolic dysfunction [39]. Although the exact mechanisms linking endome - triosis and RIF to abnormalities in the FOXO-mediated transcription pathway are not yet fully understood, based on the shared DEGs enrichment results, aberrant activa - tion or suppression of this pathway may influence cellular responses to oxidative stress and metabolic dysfunction, which have been implicated in both endometriosis and Fig. 4 The construction of PPI networks. A The PPI network was established by utilizing data from the STRING database. B The PPI network was constructed by applying a combined score > 0.4 threshold and subsequently identifying the hub genes. Rectangular shapes are utilized to symbolize genes, while lines are employed to depict the interactions between proteins encoded by those genes. The hub genes are distinguished in the network with a gradient of colors ranging from red to yellow, which includes ESR1, SOCS3, MYH11, CYP11A1, and CLU Table 3 Expression details of shared hub genes in endometriosis and RIF Hub genes RIF Endometriosis adj. p. val logFC adj. p. val logFC ESR1 0.0001 2.5336 3.06E‑10 − 2.9213 SOCS3 0.0005 − 1.5912 0.0007 1.9471 MYH11 0.0021 2.9752 7.55E‑08 2.2143 CYP11A1 0.0016 − 2.0553 0.0025 1.8904 CLU 0.0003 − 2.4571 2.96E‑08 2.3214 Page 8 of 12Hakimi et al. Middle East Fertility Society Journal (2025) 30:32 RIF pathogenesis. Emerging compounds that modulate FOXO function [40], some of which are under investiga - tion in oncology settings, may offer a starting point for future studies aimed at protecting endometrial cells from oxidative injury and potentially improving implantation outcomes. The “Smooth Muscle Contraction” pathway emerged as a significant player in both conditions, indicating the potential involvement of smooth muscle cells in patho - physiology. Research revealed that Smooth muscle cells are often present in endometriotic lesions and have been identified in several types of endometriotic lesions, including peritoneal, ovarian, deep-infiltrating, and adenomyotic lesions [41]. The “Semaphorin Interactions” pathway offers insights into cellular communication and guidance cues during development and tissue homeosta - sis. Semaphorins are a group of proteins that are secreted and connected to the cell membrane. These proteins play crucial roles in regulating several developmental pro - cesses, such as building neural circuits, bone develop - ment, and angiogenesis [42]. Furthermore, it has been shown that they have a significant influence on several stages of immunological responses [43]. The available evidence indicates that the presence of a chronic inflam - matory state in endometriosis may potentially lead to an elevation in semaphorin levels, potentially impacting the innervation in peritoneal endometriosis [44]. Meanwhile, the involvement of semaphorin Interactions in RIF and infertility requires further research. In general, Reactome pathway enrichment analysis provides valuable insights into the common molecular constituents and pathways underlying endometriosis and RIF. Through the identifi - cation of these potential functional pathways, our under - standing of the intricate mechanisms that contribute to the emergence and advancement of these conditions is improved. Enriched GO pathways offer valuable insights into the shared molecular mechanisms underlying endometrio - sis and RIF, with the top five pathways having meaning - ful implications for both conditions. However, several GO enrichments were novel in endometriosis and RIF, which can be a basis for further studies, including the regulation of the cellular amide metabolic process, reg - ulation of supramolecular fiber organization, and car - diac muscle cell development. Among these factors, aberrant signal transduction pathways have emerged as critical contributors to endometriosis development. For instance, a study conducted by Kim et al. found compel - ling evidence linking aberrant signal transduction to this complex gynecological condition. Researchers observed a significant increase in the levels of phospho-signal trans - ducer and activator of transcription-3 (pSTAT3) and its downstream signaling protein, HIF1A, in the eutopic endometrium of women diagnosed with endometrio - sis compared to those who did not have the condition [45]. The aberrant induction of pSTAT3 and HIF1A is hypothesized to have a significant impact on endome - triosis development [45]. These findings suggest that the regulation of signal transduction pathways may be the key to understanding and potentially addressing RIF in individuals with endometriosis. In contrast, the control of the apoptotic process is implicated in the pathogenesis of endometriosis. Apoptosis, also known as programmed cell death, is an intrinsic biological mechanism that contributes to the preservation of tissue homeostasis by eliminating impaired or surplus cells [46, 47]. In the context of endometriosis, the equilibrium between cel - lular proliferation and programmed cell death, known as apoptosis, is disturbed, resulting in the development of endometrial tissue in locations outside the uterus [48]. Research findings indicate that there is a modification in the expression of genes associated with apoptosis in endometriotic tissue, indicating that the disruption of apoptosis may play a role in the initiation and progres - sion of the disease [49]. Current therapeutic interven - tions include a range of hormone-based therapies that target the reduction of circulating estrogen levels to those observed in postmenopausal individuals. GnRH agonist incubation enhances the apoptotic rate in eutopic and ectopic endometrial cells from endometriosis-affected women [50, 51]. The increase in the apoptotic rate may be attributed to changes in the expression of genes asso - ciated with apoptosis subsequent to the administra - tion of a GnRH agonist. Treatment with GnRH agonists influences the expression of various genes, including those encoding apoptotic factors [52]. The combination of GnRH agonist downregulation and hormone replace - ment therapy (HRT) has been shown to enhance repro - ductive outcomes in frozen-thawed embryo transfer cycles among older patients (aged 36–43 years) diag - nosed with idiopathic RIF [53]. Prior research on retro - spective self-control has shown that the use of a protocol combining gonadotropin-releasing hormone agonist and hormone replacement therapy (GnRH agonist–HRT) has the potential to enhance the incidence of successful preg- nancies in frozen embryo transfer cycles among patients who have encountered RIF subsequent to IVF treatment [54]. These enriched GO pathways notably shed light on the shared molecular mechanisms of endometriosis and RIF. The regulation of signal transduction pathways and the role of apoptosis are significant factors. Further inves- tigation of these pathways could provide critical insights for developing targeted therapies for both conditions. In the context of unraveling the intricate molecular landscape underlying endometriosis and RIF, the con - cept of hub genes emerged as a pivotal aspect of our Page 9 of 12 Hakimi et al. Middle East Fertility Society Journal (2025) 30:32 analysis. Hub genes are more inclined to function as master signaling and transcription regulators because of their propensity to participate in several connections and maintain the overall integrity of the network [55]. Conse- quently, hubs have the potential to serve as valuable tar - gets for therapeutic interventions and as biomarkers. Our study identified the top five hub genes with a high degree of connectivity: ESR1, SOCS3, MYH11, CYP11A1, and CLU. Endometriosis is a gynecological disease characterized by inflammation that relies on estrogen [56]. The identi - fication of estrogen receptor 1 gene (ESR1) as an onco - gene for endometrial cancer is a recent development [57]. Multiple signals in the ESR1 area related to endometrio - sis and other reproductive characteristics and diseases have been identified using genome-wide association studies (GWAS) [58]. Previous investigations have dis - proven the indications within the ESR1 gene region that are linked to the possibility of developing endometrio - sis. This discovery emphasizes the potential importance of ESR1 in reproductive health [58]. This study aimed to examine the hormonal and genetic control of genes in the ESR1 area of the human endometrium. The results revealed noteworthy fluctuations in hormone levels and receptor expression throughout the menstrual cycle. In addition, a significant correlation between ESR1 and PGR expression was observed, suggesting the possibility of co- regulation [58]. Genetic variations in the ESR1 gene, spe - cifically the single nucleotide polymorphism (SNP) ESR1 rs9340799, have been associated with infertility related to endometriosis and failure of IVF procedures. Women who possess the GG genotype have been found to have a four-fold higher likelihood of developing endometrio - sis and a three-fold higher likelihood of experiencing IVF failure, even after accounting for age-related factors [59]. Given its central role in estrogen signaling, ESR1 expres - sion levels could be quantified in endometrial biopsies via immunohistochemistry or qPCR as part of a “receptivity panel” to stratify patients before IVF. Moreover, the protein known as suppressor of cytokine signaling 3 (SOCS3) plays a crucial role in the regulation of cytokine signaling [60]. Previous studies have shown the involvement of this factor in the process of human endometrial stromal cell differentiation into decidual cells, a crucial step for successful embryo implantation [61]. The transduction of interleukin 11 (IL-11) signal - ing occurs via the signal transducers and activators of transcription (STAT) proteins. In response to cytokine- induced phosphorylation of STAT, the stimulation of suppressor of cytokine signaling (SOCS) proteins takes place, which serves as a negative feedback mechanism to impede the activation of cytokine receptors [61]. It is worth mentioning that the presence of immunoreactive IL-11 in  vivo is not detectable in the endometrium of some women experiencing primary infertility and endo - metriosis during the fertilization window. Additionally, the synthesis of IL-11 is diminished in the endometrium of women with recurrent miscarriages when compared to women who are fertile without any complications [62, 63]. The study demonstrated that the overexpression of SOCS3 in human endometrial stromal cells resulted in a decrease in IL-11-induced pSTAT3 and hindered the process of decidualization. These findings suggest that SOCS3 plays a crucial role in regulating cellular differen - tiation [61]. Additional research is required to elucidate the precise role of SOCS3 in the pathogenesis of endo - metriosis and RIF, and its possibility to serve as a non- invasive biomarker for implantation competence. The MYH11 gene, which is classified as a protein-cod - ing gene of the myosin heavy chain family, is responsible for encoding smooth muscle myosin [64]. In a research investigation, MYH11 was found to be a distinctive marker associated with a specific subgroup of corneal endothelial cells [65]. Recent research using bioinfor - matics techniques has identified MYH11 as one of the hub genes related to endometriosis [66]. CYP11A1, also referred to as cytochrome P450 side chain cleavage, is an enzyme located in the mitochondria. Its primary func - tion is the catalysis of the cleavage of cholesterol’s side chain, resulting in the production of pregnenolone. Preg - nenolone serves as the shared precursor for many ster - oid hormones [67, 68]. The upregulation of CYP11A1 in ectopic endometrial tissue may lead to elevated amounts of estrogen in the local environment, hence exerting an impact on the physiological activities of embryonic stem cells [69]. Within the realm of endometriosis, a schol - arly investigation has successfully identified CYP11A1 as among the genes exhibiting hypomethylation and displaying heightened expression levels in individu - als affected by ovarian endometriosis [70]. CLU, often called clusterin, is a glycoprotein that exhibits a virtu - ally universal tissue distribution and plays a role in sev - eral biological processes, including neurodegeneration in Alzheimer’s disease and the genesis and development of cancer [71, 72]. In the context of endometriosis, CLU levels were found to have a modest increase in cases with the condition, but interestingly, these levels significantly decreased in patients with endometriosis who were receiving contraception [73]. Furthermore, our analysis revealed a notable distinc - tion in the expression patterns of the identified hub genes between endometriosis and RIF. Specifically, MYH11 was the only gene among the five that demonstrated consistent upregulation in both conditions, as evidenced by positive logFC values in both RIF (logFC = 2.9752) and endometriosis (logFC = 2.2143). This consistency Page 10 of 12Hakimi et al. Middle East Fertility Society Journal (2025) 30:32 suggests that MYH11 may be involved in shared molecu - lar mechanisms underlying both endometriosis and RIF, potentially making it a key player in the pathophysiol - ogy of these reproductive disorders. In contrast, ESR1, SOCS3, CYP11A1, and CLU exhibited opposite direc - tions of expression change between endometriosis and RIF, with upregulation in one condition and downregu - lation in the other (e.g., ESR1: logFC = 2.5336 in RIF vs. −2.9213 in endometriosis). This divergence may reflect the unique molecular landscapes of these conditions and highlights the complexity of their pathogenesis. The dis - tinct behavior of MYH11 warrants further investigation to elucidate its specific role in endometriosis and RIF, which could provide insights into novel therapeutic strat- egies and diagnostic markers. Collectively, our findings provide a roadmap for trans - lating molecular insights into clinical practice: the shared DEGs and enriched pathways may form the basis of novel diagnostic panels (e.g., IL-6 or FOXO pathway signa - tures) and therapeutic approaches (e.g., cytokine inhibi - tors, FOXO modulators). Prospective clinical studies should focus on validating these biomarkers in patient cohorts and exploring targeted interventions to improve IVF success rates in women with endometriosis and RIF.

One of the hurdles of this investigation is its dependence on bioinformatics analysis, which provides a valuable comprehension of molecular pathways but lacks direct biological verification. Further empirical inquiries, clinical trials, and prospective research are imperative to establish the clinical reliability and utility of the identified markers.

In conclusion, this work utilizes bioinformatics analysis to elucidate shared biological pathways and central genes linked to endometriosis and RIF. While these results give insight into possible therapy targets and biomarkers for both ill - nesses, it is critical to recognize the study’s limitations. Vali- dating the clinical utility of the identified genes and pathways and exploring their precise functions in reproductive health requires additional research. The discovery of hub genes, including ESR1, SOCS3, MYH11, CYP11A1, and CLU, estab- lishes a fundamental basis for further inquiries into the com- plex molecular terrain of endometriosis and RIF. It is worth mentioning that several hub genes, including ESR1 and SOCS3, have shown correlations with infertility due to endo- metriosis and the failure of IVF procedures. Nevertheless, the extent of their precise participation in RIF has yet to be com- prehensively clarified. This study emphasizes the need for ongoing research in the realm of reproductive health in order to enhance our comprehension of these diseases and estab- lish more efficacious approaches for diagnosis and treatment. Abbreviations RIF Recurrent embryo implantation failure IVF In vitro fertilization DEGs Differentially expressed genes GO Gene ontology BP Biological processes MF Molecular functions CC Cellular components PPI Protein‑protein interaction STRING Search tool for the retrieval of interacting genes MCC Maximal clique centrality GEO Gene expression omnibus HRT Hormone replacement therapy IL Interleukin pSTAT3 Phospho‑signal transducer and activator of transcription‑3 FOXO Forkhead Box O HIF1A Hypoxia‑inducible factor 1 alpha GnRH Gonadotropin‑releasing hormone ESR1 Estrogen receptor 1 SOCS3 Suppressor of cytokine signaling 3 MYH11 Myosin heavy chain 11 CYP11A1 Cytochrome P450 side chain cleavage CLU Clusterin Authors’ contributions The contributions of the authors are outlined as follows: P .H. and N.A.Z. were responsible for the conceptualization of the study and conducted the investigations. K.P . was tasked with software development, formal analysis, and validation. M.A. contributed to the creation of the original draft, while M.R. and S.G.F played a pivotal role in providing a critical review and conducting comprehensive editing of the manuscript. Additionally, all authors actively participated in supervision and meticulously reviewed the final manuscript. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not‑for‑profit sectors. Data availability No datasets were generated or analysed during the current study. Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Author details 1 Women’s Reproductive Health Research Center, Tabriz University of Medi‑ cal Science, Tabriz, Iran. 2 Department of Gynecology & Obstetrics, Jahrom University of Medical Sciences, Jahrom, Iran. 3 Department of Gynecology, Faculty of Medicine, Tabriz Medical Sciences, Islamic Azad University, Tabriz, Iran. 4 Department of Medical Genetics, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran. 5 Department of Medical Genetics, Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran. Received: 26 March 2025 Accepted: 12 August 2025

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