{"paper_id":"ec91375d-6049-4939-b82c-c251bbb8c822","body_text":"This work is licensed under the Creative Commons Attribution 4.0 International License. 197 \n \n \n \nBulletin of Pioneering Researches of Medical and Clinical Science \n \nAvailable online: https://bprmcs.com \n 2025 | Volume 5 | Issue 1 | Page: 197-209 \n \n \n \n \nMetabolic Reprogramming Mediates Chronic Stress–Induced \nImmune Dysregulation in Endometriosis \nHiroshi Nakamura1*, Yuta Kato1 \n1Department of Clinical and Translational Medicine, Nagoya University, Nagoya, Japan. \nAbstract \nEvidence indicates that the initiation and progression of endometriosis are intimately tied to \npersistent psychological strain. The precise manner in which sustained stress contributes to \nmetabolic alterations in women with endometriosis has not been elucidated. Our objective was \nto expose the mechanistic underpinnings of how sustained stress influences endometriosis \nevolution and, potentially, to formulate candidate biomarkers to gauge the effect of accelerated, \npersistent stress on endometriosis invasiveness. Ectopic tissue was excised surgically from ten \naffected patients, who were then separated into two categories through a psychological \nevaluation. A human mRNA gene expression microarray was used to assess differences in \nmRNA expression patterns betwee n those under continuous stress and their counterparts. The \nreliability of the microarray results was further corroborated by metabolite profiling using liquid \nchromatography–tandem mass spectrometry (LC -MS/MS) and quantitative reverse \ntranscription polyme rase chain reaction (RT –PCR). Microarray analysis of genes that were \nmarkedly overexpressed and differentially expressed between the ongoing stress and \ncomparison groups revealed genes largely belonging to metabolic and immunological pathways, \nincluding im mune response processes, inhibition of T lymphocyte proliferation, leucine \nbreakdown, and L -cysteine processing (P < 0.05). LC -MS profiling demonstrated that the \ndistinguishing metabolites chiefly involved arginine and proline processing, D -glutamine and \nD-glutamate processing, aspartate handling, glycine, serine metabolism, and tyrosine \nmetabolism (P < 0.05). A mechanism may exist in which prolonged stress impairs immune \ndefense in endometriosis via metabolic reconfiguration. Extended stress curtails the p rovision \nof energy substrates such as arginine and serine, suppresses T lymphocyte activation, and \nweakens antineoplastic immunity, thus facilitating the displacement and penetration of \nendometriotic tissue in chronically stressed patients. \nKeywords: Chronic stress, \nEndometriosis, Immune response, \nMetabolic reprogramming \nCorresponding author: Hiroshi \nNakamura \nE-mail: hiroshi.nakamura@outlook.com \n \n \nReceived: 04 December 2024 \nRevised: 26 January 2025 \nAccepted: 01 February 2025 \n \n \nHow to Cite This Article:  Nakamura H, Kato Y . Metabolic Reprogramming Mediates Chronic Stress –Induced Immune Dysregulation in \nEndometriosis. Bull Pioneer Res Med Clin Sci. 2025;5(1):197-209. https://doi.org/10.51847/hEIdBJFZEE \n \nIntroduction \nEndometriosis (EM) is a disorder in which endometrial \ncells and stroma implant and grow in locations outside the \nuterine cavity, affecting 10% –15% of females in their \nchildbearing years [1]. The pathological mechanisms \nencompass amplified cellular attachme nt, new blood \nvessel formation, disrupted programmed cell death, and \ngenetic factors, yet a comprehensive understanding \nremains lacking. From a clinical standpoint, the illness \nmanifests through painful menses, discomfort during \nintercourse, non -menstrual pelvic aching, and reduced \nfecundity, all elements that considerably impair the well -\nbeing of those diagnosed [2 -4]. As a result, women \nbattling endometriosis tend to exist under a persistent \npsychological burden, involving depressive symptoms, \nanxious sta tes, and insufficient social backing [5 -8]. In \nparticular, individuals enduring deep infiltrative \n\nNakamura and Kato  \n \n Bull Pioneer Res Med Clin Sci, 2025, 5(1):197-209 198 \n \ndiscomfort originating from endometriosis may suffer \nexceptionally severe ongoing stress, a condition often \nmitigated after operative removal of the lesions [9]. \nA growing body of evidence has substantiated that \nsustained stress plays a vital role in the progression of \nendometriosis [10 -12]. Still, the particular part that \nchronic stress plays in the pathogenesis of endometriosis \nremains to be entirely mapped out. \nOngoing stress triggers a multifaceted cascade that can \nstimulate the sympathetic nervous system (SNS) and the \nhypothalamic–pituitary–adrenal (HPA) axis [13, 14]. It \ncan unleash a succession of detrimental secondary \nconsequences throughout the organism [15 ]. Epinephrine \n(E) and norepinephrine (NE) reportedly remain \npersistently elevated in subjects experiencing continuous \nstress, whereas dopamine (DA) concentrations drop [16, \n17]. Persistent stress also engages the GC receptor (GCR), \nwhich forms part of the  regulatory loop governing \ninflammatory and immunological activities [18]. \nAppleyard et al. [19] demonstrated that prior exposure to \nswimming-induced stress before the surgical induction of \nendometriosis in rodents resulted in a notable increase in \nthe size and number of endometrial implants [20]. Guo et \nal. [11] asserted that sustained stress accelerates \nendometriosis progression and operates through \nstimulation of Adrenoceptor Beta 2 (ADRB2) and cyclic \nadenosine monophosphate response element -binding \nprotein (CREB) signaling pathways, and that targeting \nADRB2 signaling might rep resent a novel therapeutic \napproach for endometriosis treatment [21]. Much like the \nconnection between sustained psychological burden and \ncancer advancement implicating the SNS and HPA [15], a \nstudy demonstrated that oncology subjects recounting \nelevated degrees of ongoing stress displayed irregular NE \nand cortisol concentrations [7]. Nevertheless, the \nmechanisms of continuous stress in endometriosis \nprogression are not fully understood. \nVirtually every living entity can adapt to its surrounding \nmilieu to modulate metabolic operations. Consequently, \ncells must continually sense environmental shifts and \nadjust their metabolic requirements accordingly. Different \ncell populations, however, ex hibit distinct metabolic \nmodifications. Standard cells predominantly exploit \nglucose breakdown through mitochondrial oxidative \nphosphorylation to synthesize adenosine triphosphate \n(ATP). Malignant cells, in contrast, adopt an alternative \nmetabolic route, namely glycolysis. Even when oxygen is \nplentiful, neoplastic cells continue to employ glycolysis, \nwhich represents a process that is neither resource-sparing \nnor highly efficient relative to other pathways —the \nphenomenon termed aerobic glycolysis (Warburg e ffect) \n[22]. The metabolic profile of cancerous cells impacts not \nonly the malignant cells themselves but also adjacent cells, \nincluding innate and adaptive immune effectors, \nendothelial linings, and neoplasm -associated fibroblasts \nwithin the immunological  network [23]. As neoplastic \ntissue enlarges, immune elements populating the local \nmicroenvironment experience metabolic reconfiguration, \ntriggering phenotypic transformations [23]. The \nfundamental scientific question this work explores is how \nthe metaboli c restructuring program of neoplastic cells \nshapes anti -tumor immunity; this underlies our \ninvestigation into metabolite distinctions, immunological \ndisparities, and their mutual connections. \nIn the present investigation, we conducted an mRNA \nhuman gene expression microarray survey to examine \ndifferences in mRNA transcription patterns between \nchronic stress and control endometriosis patient cohorts. \nMoreover, using metabolite -centered inquiries  based on \nboth LC-MS/MS and quantitative RT–PCR, we validated \nthe reliability of the mRNA human gene expression \nmicroarray approach. Our objective was to expose the \nmechanistic underpinnings of how sustained stress \ninfluences endometriosis evolution and, p otentially, to \nformulate candidate biomarkers to gauge the effect of \naccelerated, persistent stress on endometriosis \ninvasiveness. \nMaterials and Methods \nPatients \nIndividuals whose endometriosis was confirmed by \nintraoperative pathological examination were enrolled \nfrom the Fudan University Affiliated Obstetrics and \nGynecology Hospital. Psychological evaluation \ninstruments, specifically the Patient Health Questionnaire-\n9 (PHQ -9) and the Generalized Anxiety Disorder -7 \n(GAD-7) scales, were administered to assess participants’ \npsychological condition. Our assessment of each \nparticipant’s psychological status was finalized before the \nsurgical procedure, and every patient  was informed \nregarding the purpose of the evaluation. Participants \ncompleted the questionnaires under the supervision of \ntrained instructors. We assigned patients exhibiting mild \nor more pronounced levels (defined as a score of 5 or \nhigher) of both depres sion and anxiety to the persistent \nstress arm, and those presenting with neither anxiety nor \ndepression to the reference arm. Tissue samples were \nobtained during the operation, transferred into sterile \ncontainers, and promptly frozen at −80 °C pending \nsubsequent analyses. \nTranscriptomic profiling: RNA harvesting, library \nconstruction, RNA sequencing, and differential \nexpression assessment \nThe Agilent SurePrint G3 Human Gene Expression v3 \nMicroarray (8x60K, Design ID: 072363) was employed \nfor this investigation, and bioinformatic analysis of the \nentire set of 10 specimens was performed. \n\nNakamura and Kato  \n \n Bull Pioneer Res Med Clin Sci, 2025, 5(1):197-209 199 \n \nWhole RNA from the endometriotic lesions was recovered \nusing TRIzol reagent (Invitrogen, Carlsbad, CA, USA) in \naccordance with the supplier’s recommended procedure. \nRNA quantity was determined using the NanoDrop ND -\n2000 instrument (Thermo Scientific, New Y ork, NY, \nUSA), and RNA integrity was assessed using the Agilent \nBioanalyzer 2100 system (Agilent Technologies, USA). \nThe procedures for sample labeling, chip hybridization, \nand washing steps were performed exactly as stipulated in \nthe manufacturer’s documentation. To summarize, whole \nRNA was reverse-transcribed to generate double-stranded \ncDNA, after which complementary RNA (cRNA) was \nproduced and conjugated with Cyanine -3-CTP dye. The \ndye-coupled cRNA products were then hybridized onto \nthe microarray slide. After the wash steps, the chips were \nimaged using the Agilent Scanner G2505C (Agilent \nTechnologies, Santa Clara, CA, USA). \nFeature Extraction software (version 10.7.1.1, Agilent \nTechnologies, Santa Clara, CA, USA) served to interpret \nthe array images and extract raw signal intensities. \nGeneSpring (version 13.1, Agilent Technologies, Santa \nClara, CA, USA) was used to process th e raw datasets \ninitially. As a first step, the quantile normalization method \nwas enforced on the raw measurements. Probes that \nreceived a “Detected” flag in no fewer than 100% of the \nvalues across any single experimental condition were \nretained and advance d to the subsequent tiers of \nexploration. Thereafter, p -values were derived from \nrepeated variance assessments and t -tests, enabling the \nidentification of genes whose expression differed \nsignificantly. The criteria for classifying transcripts as \neither heightened or diminished were a fold change ≥ 1.5 \npaired with P ≤ 0.05. GO term enrichment evaluation and \npathway assignment were subsequently undertaken to \nelucidate the functional significance of these differentially \nregulated RNA species. As a final step, hierarchical \nclustering was performed to visualize how the expression \npatterns of the discriminatory genes clustered across the \nsample collection. \nMetabolomic evaluations: tissue metabolite recovery \nand metabolite profiling pipeline \nA panel of 30 endometriotic tissue specimens (comprising \n15 from the persistent stress arm and 15 from the \ncomparator arm) was assembled for metabolite \nmeasurement via LC -MS/MS-driven detection. LC -\nMS/MS was conducted on a UHPLC platform (1290, \nAgilent Technologies, Santa Clara, CA, USA) equipped \nwith a UPLC BEH Amide separation column (1.7 μm, 2.1  \n100 mm, Waters, Milford, MA, USA) and coupled to a \nTriple TOF 6600 mass analyzer (Q-TOF, AB Sciex). The \nmobile solvents were constituted by a water -based \nsolution containing 25 mM NH4OAc combined with 25 \nmM NH4OH (pH = 9.75) (solvent A) and acetonitrile \n(solvent B). The elution timetable was arranged according \nto the following profile: 0 min, 5% A; 0.5 min, 5% A; 7 \nmin, 35% A; 8 min, 60% A; 9 min, 60% A; 9.1 min, 5% \nA; and 12 min, 5% A, with a continuous flow setting of \n0.3 mL/min. A 2 μL aliquot was introduced per injection. \nDuring LC/MS acquisitions, MS/MS fra gmentation data \nwere collected using information -dependent acquisition \nlogic on the triple TOF device. I n this operational mode, \nthe controlling software (Analyst TF 1.7, AB Sciex, \nFramingham, MA, USA) continuously monitored the full-\nscan survey MS signal while simultaneously capturing and \ntriggering MS/MS spectral acquisition according to \npredefined inclusi on rules. In every iterative scan, six \nprecursor species exceeding an intensity cutoff of 100 \nwere chosen and dissociated under a collision energy (CE) \nsetting of 35 V (15 MS/MS events, with a 50 msec dwell \nperiod for each fragment ion). The ESI source con ditions \nwere fixed as follows: ion source gases 1 and 2 at 60 psi \neach, curtain gas at 30 Psi, source block heated to 550 °C, \nand ion spray voltage floating (ISVF) set to 5500 V and \n−4500 V for positive and negative ionization, respectively. \nQuantitative real-time polymerase chain reaction \nTotal RNA was purified from cryopreserved tissue pieces \nand converted into complementary DNA using the \nPrimerScript RT Kit (Takara, Shiga, Japan) according to \nthe manufacturer’s instructions. Quantitative real -time \nPCR (qRT-PCR) was performed with SYBR Pre mix Ex \nTaq (Takara, Japan) on a 7500 RT -PCR detection system \n(Applied Biosystems, Foster City, CA, USA). Each \nsample was run in triplicate. Target mRNA abundance \nvalues were standardized to the 18S reference transcript \nand calculated using the 2 −ΔΔCt relative quantification \nmethod. \nStatistical procedures \nThe experimental data are expressed as the mean ± \nstandard deviation. For contrasts involving more than two \ngroup means, one -way ANOVA was applied, while \npairwise group contrasts were evaluated using the shortest \neffective range procedure. The SPSS 20.0 st atistical suite \n(IBM SPSS Statistics, Inc., Chicago, IL, USA) was used \nfor the computational analyses. Graphical outputs were \nproduced using GraphPad Prism 6.0 software (San Diego, \nCA, USA), and between -cohort comparisons relied on \nStudent’s t -tests. Discr epancies between cohorts were \nconsidered statistically significant when p -values were \nbelow 0.05. \nResults and Discussion \nCharacteristics of the study population \nThirty subjects were enrolled in this investigation and \nsubsequently assigned to either a persistent stress cohort \nor a reference cohort according to their scores on \npsychological assessment instruments. Pathological \n\nNakamura and Kato  \n \n Bull Pioneer Res Med Clin Sci, 2025, 5(1):197-209 200 \n \nevaluation confirmed the diagnosis of endometriosis in all \nparticipants in the present study. The depressive and \nanxious symptomatology of the individuals with \nendometriosis was examined by means of the Patient \nHealth Questionnaire -9 (PHQ -9) and the Genera lized \nAnxiety Disorder -7 (GAD -7) psychological scales. Age \nand disease stage, treated as potential confounders, were \nexcluded from consideration (Figures 1a and 1b). \n \na) \n \nb) \nFigure 1. Characteristics of the study population: (a) \nScatter plot comparison of age distribution between the \nreference group and the persistent stress group among \npatients subjected to metabolome profiling; (b) scatter \nplot comparison of stage distribution between  the \nreference group and the persistent stress group among \npatients subjected to metabolome profiling. \nDivergent gene expression patterns in endometriosis \npatients with or without persistent stress \nThe Agilent SurePrint G3 Human Gene Expression v3 \nmicroarray (8 × 60K, Design ID: 072363) was used to \ngenerate mRNA expression signatures. Five tissue \nspecimens from each experimental arm were sent for \ntranscriptomic analysis. The data indicated a considerable \nnumber of genes whose regulation differed between \nendometriosis patients under persistent stress and those \nfree of such stress. Hierarchical clustering revealed that \nendometriotic lesions harvested from stressed subjects \ndisplay a gene expression prof ile clearly distinguishable \nfrom that of unstressed subjects. The accompanying \ndendrogram also shows that many differentially expressed \ntranscripts are either up- or downregulated in the lesional \ntissue of endometriosis patients experiencing stress \n(Figures 2a and 2b). \n \na) \n \nb) \nFigure 2. (a) Heat map illustrating mRNA signatures \nwithin endometriotic tissues of the persistent stress \ngroup relative to matched control endometriotic \ntissues—red coloration: heightened genes; green \ncoloration: diminished genes. mRNA expression values \nare arrange d via hierarchical clustering along the \nvertical axis, while tissue specimens are arranged via \nhierarchical clustering along the horizontal axis (fold \nchange: 2; P < 0.05). Alphanumeric labels correspond \nto five persistent stress endometriotic tissue sampl es \nand five matched control endometriotic tissue samples, \nrespectively. (b) The overlapping sector in the volcano \nplot designates genes that were concordantly \nmodulated, as per the selection criteria of a ≥ 2 -fold \nalteration (P < 0.05), when comparing persistent-stress \nendometriotic tissue with the control. \nCollectively, 34,757 distinct expressed gene products \nwere detected across the endometriotic specimens. From \nthis pool, we identified 1381 mRNAs that showed \ndifferential expression between the persistent stress and \ncontrol cohorts. Among them, 689 mRNA spe cies were \nup-regulated, while 692 were down -regulated in the \npersistent stress group specimens. \nFunctional categorization through Gene Ontology \n(GO) enrichment of differentially expressed genes \n\n\nNakamura and Kato  \n \n Bull Pioneer Res Med Clin Sci, 2025, 5(1):197-209 201 \n \nTo acquire broader mechanistic insights into the biological \nroles of the differentially expressed transcripts, we \nconducted GO enrichment analyses by interrogating each \ndifferentially expressed gene identified between the \npersistent stress and reference co horts. GO evaluation of \nthe prominently up -regulated, differentially expressed \ngene set between the two groups brought to light a \npredominant enrichment of genes linked to immunological \nand metabolic pathways, such as the immune reaction \npathway, the infla mmatory reaction, the immune \napparatus pathway, modulation of immune reaction, \nsuppression of T lymphocyte proliferation, the leucine \nprocessing pathway, and the L -cysteine processing \npathway (P < 0.05) (Figure 3) . The down -regulated \ndifferentially expressed gene cluster was chiefly \nassociated with immune -related processes, whereas the \nup-regulated differentially expressed gene cluster was \npredominantly associated with metabolism -related \nprocesses. \n \na) \n \nb) \nFigure 3.  Gene ontology (GO) categorization of \ndifferentially expressed (DE) genes. The y -axis \nrepresents the GO designation, and the x -axis \nrepresents the −Log10 (p -value) attributed to the \nsignificantly enriched GO designations. Red circular \nmarkers signify corrected p-values below 0.05. (a) The \nseven most significant GO designations (biological \nprocess category) are tied to the detected up -regulated \nDE gene set. (b) The seven most significa nt GO \ndesignations (biological process category) are tied to \nthe detected down-regulated DE gene set. \nPathway-level characterization of differentially \nexpressed genes \nWe consulted the KEGG database to identify the principal \nsignaling pathways involving the differentially expressed \ngenes identified in this study. Our findings demonstrated \nthat 14 pathways were meaningfully enriched among the \ncataloged DEGs. Beyond that, pathway-level inspection \npointed to the involvement of these differentially \nexpressed gene products in complement and coagulation \ncascades; cell adhesion molecules (CAMs); cytokine –\ncytokine receptor interplay; phagosomes; the NF-kappa B \nsignaling route (NF -κB); cysteine and methionine \nprocessing; glycine, serine, and threonine processing; \ntogether with D -Arginine and D -ornithine processing \n(Figures 4a and 4b). \n \na) \n \nb) \nFigure 4.  Pathway-level characterization of \ndifferentially expressed gene sets. The y-axis indicates \n\n\nNakamura and Kato  \n \n Bull Pioneer Res Med Clin Sci, 2025, 5(1):197-209 202 \n \nthe pathway category, and the x -axis indicates the \n−Log10 (p -value) corresponding to the significantly \nenriched pathway designations. Red bars signify \ncorrected p -values below 0.05. (a) The seven most \nsignificant pathways are tied to the detected down -\nregulated differentially expressed gene set. (b) The \nseven most significant pathways are tied to the detected \nup-regulated differentially expressed gene set. \nPathway–act network construction and inspection \nTo acquire a richer understanding of how pathways \ninteract and to isolate those routes likely occupying \ncommanding positions, we assembled a pathway –act \nnetwork grounded in the direct or systemic associations \ndocumented within the KEGG resource (Figure 5) . As \ndepicted in Figure 6, a subset of differentially expressed \ngenes active in essential routes in both the persistent stress \narm and the reference arm was identified, encompassing \nmetabolic circuits such as glutathione, cysteine and \nmethionine, and glycin e, serine, and threonine handling, \neach of which was shown to be transcriptionally enhanced. \nBeyond this, the FoxO signaling circuit, the Jak -STAT \nsignaling circuit, and the NF -kappa B signaling circuit \nsituated within the interaction web were also forecasted to \nexert considerable influence. \n \n \nFigure 5. Pathway–act network construction and inspection. The pathway–act network was compiled based on interactions \nwith routes cataloged in the KEGG database. Circular markers correspond to pathways, while directional links between \nmarkers represent interaction t argets spanning distinct pathways. Markers colored red signal routes that were \ntranscriptionally enhanced, whereas markers colored green signal routes that were transcriptionally suppressed. \n \n\n\nNakamura and Kato  \n \n Bull Pioneer Res Med Clin Sci, 2025, 5(1):197-209 203 \n \n \nFigure 6. Heat map representation of metabolic patterns across endometriotic lesions taken from the persistent stress arm \nversus the matched control arm endometriotic lesions—red: metabolites present at higher levels; green: metabolites present \nat lower levels. Metabolite concentrations are ordered by hierarchical clustering along the vertical dimension, and the tissue \nsamples are ordered by hierarchical clustering along the horizontal dimension (fold change: 2; P < 0.05). Alphanumeric \ndesignations correspond to 15 p ersistent stress endometriotic lesions and 15 matched control endometriotic lesions, \nrespectively. \nDistinctions in metabolic patterns and \naccompanying routes between endometriosis \npatients with and without persistent stress \nAll 30 biological specimens were dispatched for \nmetabolite profiling. A total of 3629 known metabolites \nwere detected, and their concentrations were measured \nthroughout the endometriotic lesions. We resolved which \nmetabolites diverged between women who hav e \nendometriosis who were experiencing persistent stress and \nthose who were not. Of the 3629 metabolites screened, 235 \ndisplayed significant variation between the two study arms \n(P < 0.05). To illustrate how these 235 altered metabolites \ninterrelate, hierar chical clustering was employed to \narrange the compounds based on their relative abundances \nacross the sample set (Figure 6) . Concurrently, route \nmapping showed that these distinguishing metabolites \nwere mostly engaged in glutathione handling; D -\nglutamine and D-glutamate handling; arginine and proline \nhandling; taurine and hypotaurine handling; alanine, \naspartate, and glutamate  handling; glycine, serine, and \nthreonine handling; arachidonic acid handling; tyrosine \nhandling; and purine handling (P < 0.05) (Figure 7). The \noutcomes documented here exhibited near -complete \nconcordance with the shifts observed among divergent \nroutes previously identified through gene expression \nsignature analysis of metabolic variation pathways. \n\n\nNakamura and Kato  \n \n Bull Pioneer Res Med Clin Sci, 2025, 5(1):197-209 204 \n \n \nFigure 7. Bubble graphs outlining the divergent metabolic routes detected inside endometriotic lesions from the persistent \nstress arm compared to the matched control arm. \nVerification through quantitative real-time PCR of \ngene transcripts connected to inflammatory and \nmetabolic circuitry \nTo substantiate the gene expression signature outputs by \nmeans of quantitative real -time PCR, 10 mRNA targets \nsourced from 10 endometriotic specimens (5 belonging to \neach experimental arm) were chosen for expression \nsignature evaluation. The quantitative R T-PCR data \nrevealed that the miRNA signals corresponding to IL -1B, \nCXCR4, GABARAPL1, IL -7R, STAT4, CD14, CCR5, \nGATM, and GSTM2, together with the mRNA signals \ncorresponding to CXCR4, GABARAPL1, IL-7R, STAT4, \nCD14, and CCR5, underwent statistically meaningf ul \nreductions (P < 0.05 for all comparisons) within the \npersistent stress arm specimens relative to those collected \nfrom the reference arm. By contrast, the mRNA signals for \nGATM and GSTM2 displayed statistically meaningful \nelevations (P < 0.05 for all com parisons) within the \npersistent stress arm specimens compared to those from \nthe reference arm (Figure 8). The quantitative RT -PCR \nfindings were fully consistent with those from expression \nsignature profiling, thereby reinforcing the reliability of \nthe expression signature data. \n \n \nFigure 8.  Confirmation of expression signature data via quantitative real -time PCR. Ten mRNA transcripts (IL -1B, \nCXCR4, GABARAPL1, IL-7R, STAT4, CD14, CCR5, GATM, and GSTM2) were chosen and measured with qRT -PCR \nto authenticate their abundance levels. The comparativ e abundance of every target mRNA was normalized. Values \npresented in the column graphs are shown as means ± standard deviation (SD). \n\n\nNakamura and Kato  \n \n Bull Pioneer Res Med Clin Sci, 2025, 5(1):197-209 205 \n \nTo delve into the mechanistic underpinnings of how \nprolonged stress accelerates endometriosis, we cataloged \nmRNA transcripts in lesion specimens from 10 patients, \nsome experiencing and others not experiencing long-term \npsychological strain, using a human g ene expression \nmicroarray. Our analysis uncovered 1381 mRNAs whose \nabundance diverged when the two study arms were \njuxtaposed. Gene Ontology annotation and pathway \nmapping were subsequently undertaken to infer the likely \nbiological contributions of these d ifferentially abundant \ntranscripts; the outcomes revealed that gene products \nexhibiting diminished expression chiefly aggregated \nwithin immunity -associated functions, whereas those \nshowing elevated expression predominantly gathered \nwithin metabolism -associated functions. In addition, we \ninferred the downstream effectors of the differentially \nexpressed gene products by constructing a pathway –act \ninteraction map. Informed by these findings, we projected \nthat metabolic circuits covering the handling of arginin e, \nglycine, serine, and threonine would emerge among those \ndisplaying heightened activity. Alongside these, the FoxO, \nJak-STAT, and NF -kappa B signaling hubs, positioned \nwithin this interaction architecture, were also forecasted to \nassume considerable impo rtance. Metabolic profiling, \ncoupled with qRT-PCR, was then used to corroborate the \ninferences drawn from the computational analyses. \nDiscomfort and reduced fecundity stand as the two \ndominant sources of hardship that fuel depressive and \nanxious moods among women coping with endometriosis \n[24, 25], and such hardships commonly escape the \nindividual’s capacity to manage them and stretch ac ross \nprotracted timeframes. As a result, they stimulate the SNS, \nwhich in turn drives the catecholamine –HPA endocrine \naxis, thereby shaping glucocorticoid output [15]. Within \nthe endometriosis setting, glucocorticoid receptor levels \nare reportedly up -regulated, lending support to proposals \nfor therapeutic glucocorticoid antagonism [26, 27]. Even \nso, the exact routes through which glucocorticoids might \nimpart any influence on the course of endometriosis \ncontinue to elude clarification. The roles of other \nneuroendocrine factors released under persistent stress in \nshaping the endometriosis trajectory are likewise poorly \ndefined, even though their involvement in tumorigenic \nprogression is far better mapped [28, 29]. \nThe mRNA human gene expression microarray evaluation \nidentified discrepancies across both immunity - and \nmetabolism-related circuitries, evident in distinct gene \ncohorts, when comparing patients subjected to sustained \nstrain with those spared it. Yamauchi et al. [30] noted that \ntriggering NF-κB can amplify the synthesis of intercellular \nadhesion molecules (ICAM -1), MCP -1, and E -selectin; \nrender the endothelium more permeable; and ease \ntethering to the extracellular matrix (ECM) —events that \njointly ignite an inflammatory reaction within the \nendothelial lining. NF -κB promoted excessive IL -8 \nproduction, a process that facilitates neovessel formation \nwithin the ectopic endometrial stroma. \nNuclear factor-kappa B (NF -κB) belongs to a family of \nnuclear transcriptional regulators distributed widely \namong numerous cell lineages throughout the organism. It \nmaintains close ties to immunological and inflammatory \nsignaling cascades, as well as to sc heduled cell death, \ntumor establishment, and metastatic spread [31]. The \ninvolvement of NF -κB in EM may coordinate \ninflammatory reactions, cellular adherence, tissue \npenetration, and neovascularization. Wickiewicz et al . \n[32] documented that the IL -6 gene’ s promoter region \nharbors a docking motif for NF -κB, and that NF -κB can \ninitiate IL-6 synthesis, thereby substantially boosting IL-6 \nconcentrations inside the peritoneal fluid of EM patients. \nLi et al . [33] showed that the concerted transcriptional \neffect exerted by NF -κB, p50, p65, VEGF, and COX -2 \nwithin ectopic endometrial stromal cells was markedly \nenhanced, and that the engaged NF-κB axis could heighten \nthe production of VEGF. This molecule promote s \nneovascularization, degrades the adjacent matrix, and \nfacilitates the dissemination and re -establishment of \ndisplaced endometrial tissue. In the context of our \ninvestigation, prolonged psychological strain appears to \nelevate NF-κB expression in e ctopic endometrial lesions, \ncreating a milieu that promotes the adherence, \nengraftment, and vascularization of the aberrantly located \nendometrium. \nThe Janus kinase/signal transducer and activator of \ntranscription (JAK/STAT) pathway is a cytokine-triggered \nintracellular signaling cascade composed of three \ncomponents: a receptor tyrosine kinase, the tyrosine kinase \nJAK, and the transcriptional effector  STAT [34]. This \nsignaling pathway is involved in cellular proliferation, \ndifferentiation, programmed cell death, and immune \nregulation. When the JAK/STAT axis becomes \ndysregulated, genes orchestrating cell division and \nsurvival, among them cyclin D1, survivin, bcl-2, and bcl-\nxl, are up -regulated, a shift that propels pathological \nprogression [35]. George et al. [36] observed that STAT3 \nphosphorylation levels during the secretory stage of the \nnormal endometrium were considerably greater than those \nseen during the proliferative stage. Additionally, STAT3 \nin the ectopic endometrial deposits of EM patients was \nchronically overactive, and its phosphorylation intensity \ndid not oscillate with the menstrual cycle, suggesting that \nthe pathological overactivation of STAT3 in EM patients \nmay stem from an impaired decidualization capacity. \nSTAT3 participates in the balancing act between \nimmunological evasion and destruction; once activated, it \ncan promote the generation of immunosuppressive factors, \nsuch as IL-10 and TGF-β, while curbing the synthesis of \nimmune-stimulatory molecules, such as IL-12, CD80, and \n\nNakamura and Kato  \n \n Bull Pioneer Res Med Clin Sci, 2025, 5(1):197-209 206 \n \nCD86 [37]. Okamoto et al . [38], using gene expression \nchip-based profiling, demonstrated that STAT3 inhibitors \ncan suppress cell proliferation and VEGF secretion while \ninducing apoptotic death, suggesting that STAT3 blockade \nis a potential drug candidate for EM management. In \nparallel, our study established that this signaling circuit \nwas notably muted in individuals who were not \nexperiencing extended psychological strain. \nAn expansive collection of published work also addresses \nhow enduring engagement of the stress response \ninfluences immunological phenomena linked to \nendometriosis pathogenesis [24, 39, 40]. Studies have \nsuggested that the compromised functionality of natur al \nkiller cells, T lymphocytes, macrophages, mast cells, and \nNKT cells can pave the way for the implantation of ectopic \nendometrium; correspondingly, the disordered expression \nof adhesion-related proteins such as integrin ICAM -1, E-\ncadherin, and analogous factors may partake in the \nanchoring and irregular attachment of endometriotic foci. \nDue to the malfunctioning immune system, recruited \nimmune cells release IL, TNF -α, VEGF, and a host of \ncytokines, further intensifying the disruption of immune \nregulation [41-44]. Prolonged psychological stress has a \npropensity to blunt both the innate and the adaptive \nbranches of the immune defense, curtailing processes such \nas antigen presentation, cytotoxic T cell function, NK cell \nexpansion, and the elaboration of pro -inflammatory \ncytokines through pathways involving adrenergic and \nglucocorticoid-mediated mechanisms [45]. Our data \nindicate that several mRNA species and signaling \npathways associated with immunological competence —\nnamely IL -1B, CXCR4, IL -7R, STAT4, CD14, an d \nCCR5, alongside the FoxO, Jak -STAT, and NF -kappa B \nsignaling hubs —show significant associations with \nendometriosis. \nResearch has demonstrated that metabolic processes can \ninfluence the trajectory of endometriosis. Concentrations \nof TGF-1 and lactate are markedly elevated in people with \nendometriosis relative to healthy women, and notably, \ndisease lesions exhibit strong expression of glycolytic -\nassociated transcripts such as HIf -1α, Glut1, Pdk1, and \nLdha; correspondingly, the glycolytic activity within \nectopic endometrium shifts toward the Warburg \nphenotype [46, 47]. Our investigation likewise established \nthat sustained p sychological strain remodels the \nmicroenvironment surrounding endometrial cells and \nalters their capacity for engraftment and tissue penetration \nby modulating numerous metabolic circuits in \nendometriosis lesions. \nNeoplastic cells can adopt alternative metabolic strategies \nto generate ATP and macromolecular building blocks for \ntheir own requirements, depending on the availability and \nconcentration of extrinsic nutrients, including glucose, \nglutamine, serine, arginin e, and fatty acids [22]. Under \nconditions of glucose or glutamine scarcity, cancer cells \ncan engage oncogenes such as cMyc by controlling the \nabundance of metabolic enzymes PHGDHP, SAT1, and \nPSPH within the serine biosynthetic route; they can also \nexploit residual glutamine or glucose to sustain serine \nproduction via endogenous synthesis and preserve redox \nequilibrium, thus enabling tumor cell survival amidst \nnutritional deprivation [48]. The metabolic configurations \nof tumor cells are intricate and plastic, and they select the \nmost favorable metabolic mode for persistence based on \nthe surrounding milieu. Tellingly, such metabolic \nconfigurations are also found within immune cell \npopulations. \nThe immune apparatus comprises diverse immune cell \nlineages: cells that reside in a quiescent or resting \ncondition within the body, and cells that become rapidly \nmobilized and responsive when the organism encounters \ninfection, inflammation, or other foreig n insults [49]. \nAccordingly, distinct metabolic wiring patterns can shape \nthe specialization and effector capabilities of various \nimmune cells, thereby influencing tumor initiation and \nadvancement inside the tumor microenvironment [50]. \nInvestigations in tumor immunology indicate that lactate \nproduction can compromise immune cells’ function, \nthereby fostering neoplastic progression. Early -stage \nclinical studies showed that tumor burden in patients \ncorrelates with significantly elevated se rum lactate \nconcentrations. Subsequent inquiry has demonstrated that \nlactic acid, rather than the lactate ion, enters CTLs \n(cytotoxic T lymphocytes) and acidifies their intracellular \ncompartment. This event does not block CTL expansion, \ncytokine release, or cytotoxicity [51-53]. Within the tumor \nmicroenvironment and in the presence of tumor -\nconditioned macrophages, elevated expression of VEGF \nand ARG1 occurs through HIF-1α upregulation, and lactic \nacid-mediated stabilization of HIF -1α under normoxic \nconditions drives the activation of VEGF and ARG1. This \nultimately steers tumor -associated macrophages (TAMs) \ntoward an M2 polarization state, and the ARG1 released \nby TAM2 cells facilitates tumor growth [54]. \nAmino acids and their metabolic derivatives produced by \nneoplastic tissue also affect immune cells and their \nactivities. Evidence suggests that the arginine taken up by \ntumor cells within the tumor microenvironment is supplied \nmainly by tumor -associated my eloid cells (including \nmacrophages, monocytes, myeloid progenitors, and \nneutrophils, among others) [55]. These immune effectors \nassist tumor cells in withstanding an arginine -depleted \nmicroenvironment. Furthermore, large -scale data \nanalytics in recent stud ies have revealed that T cell \nactivation involves the consumption of considerable \namounts of arginine and the generation of downstream \nmetabolic products, and that exogenous glycine can \naugment intracellular arginine pools and their downstream \n\nNakamura and Kato  \n \n Bull Pioneer Res Med Clin Sci, 2025, 5(1):197-209 207 \n \nderivatives by engaging transcription factor (BAZ1B, \nPSIP1, and TSN) binding protein complexes through a \nmetabolite-driven shift from glycolysis to OXPHOS, \nthereby enhancing T cell viability and the abundance of \nmemory cells and bolstering the anti -tumor i mmune \nresponse [56]. \nResearch has demonstrated that metabolic processes can \ninfluence the trajectory of endometriosis, with TGF-1 and \nlactate concentrations in endometriosis patients \nsignificantly higher than those in healthy females. In \nparticular, disease lesions exhibit prominent expression of \nglycolytic genes, including HIF -1α, Glut1, Pdk1, and \nLdha. Along with the expression of glycolytic genes, the \nectopic endometrium’s glycolytic metabolism transitioned \ntoward the Warburg effect [46]. \nOur investigation likewise established that sustained \npsychological strain remodels the microenvironment \nsurrounding endometrial cells. It also modulates their \ncapacity for engraftment and tissue penetration by \nperturbing numerous metabolic circuits and \nimmunological pathways within the lesions of \nendometriosis patients. \nConclusion \nTo summarize, our work illustrates that prolonged stress \nhastens the progression of endometriosis in affected \nindividuals. It further shows that amino acids such as \narginine and serine accumulated to a greater extent in the \nlesions of the persistent stress  cohort than in those of the \nreference cohort. Concurrently, the activity of multiple \nimmune-associated pathways was diminished, suggesting \nthat ongoing psychological strain may impede \nendometriosis’s immune defense through metabolic \nreconfiguration; the p recise mechanism warrants further \ninvestigation. Considering the current accessibility of \nsupportive interventions like stress management strategies \ndesigned to attenuate the promotional effect of stress on \nendometriosis advancement, it appears that persis tent \nstress constitutes a modifiable risk determinant for \nendometriosis. \nAcknowledgments: None \nConflict of interest: None \nFinancial support:  This work was supported by the \nShanghai Shenkang Hospital Development Center \n(SHDC12020108) and the Shanghai Municipal Health \nCommission (2020YJZX0202). \nEthics statement: The study was conducted in accordance \nwith the Declaration of Helsinki and approved by the \nethical committee of the Obstetrics and Gynecology \nHospital of Fudan University (Number: kyy2019-26). \nInformed consent was obtained from all subjects involved \nin the study. Written informed consent was obtained from \nthe patient to publish this paper. \nReferences \n1. Ye L, Whitaker LHR, Mawson RL, Hickey M. \nEndometriosis. 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