PSG11 Overexpression Promotes Epithelial Ovarian Cancer Progression via Hedgehog-Mediated Autophagy Regulation

PSG11 Overexpression Promotes Epithelial Ovarian Cancer Progression via Hedgehog-Mediated Autophagy Regulation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article PSG11 Overexpression Promotes Epithelial Ovarian Cancer Progression via Hedgehog-Mediated Autophagy Regulation Suwei Lan, Qian Li, Qing Li, Xingcha Wang, Zhengmao Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7239376/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Epithelial ovarian cancer (EOC) is a highly lethal gynecologic malignancy due to late diagnosis, frequent recurrence, and a lack of effective early biomarkers. This study investigates the role of pregnancy-specific glycoprotein 11 (PSG11) in EOC progression and its potential as a therapeutic target. Methods: PSG11 expression and its prognostic significance in epithelial ovarian cancer were analyzed using The Cancer Genome Atlas data and Gene Expression Omnibus, validated by immunohistochemistry. PSG11 expression in epithelial ovarian cancer cell lines was confirmed via Quantitative Polymerase Chain Reaction and Western blot. PSG11 knockdown was studied using flow cytometry,celigo counting,cloning experiment, scratch assay,transwell assays and tumor models in nude mice, with bioinformatics analyses providing insights into the mechanisms involved. Results: PSG11 was significantly overexpressed in EOC tissues compared to para-cancerous tissues (47.2% vs. 12.5%, P < 0.001). A significant correlation was observed between high PSG11 expression and FIGO stage, distant metastasis, tumor size, and lymph node involvement ( P < 0.001, P = 0.004, P = 0.017, and P = 0.019, respectively). Functional studies demonstrated that PSG11 knockdown reduced cell viability by approximately 40% ( P < 0.001), colony formation by approximately 50%, and migration rates by approximately 60% in vitro, while promoting apoptosis. In vivo, PSG11 knockdown suppressed tumor growth, reducing tumor volume by approximately 55% and tumor weight by approximately 50% by day 30. Mechanistically, PSG11 activated the Hedgehog signaling pathway, promoting epithelial ovarian cancer progression by regulating autophagy. Conclusion: PSG11 drives epithelial ovarian cancer progression by activating Hedgehog signaling to regulate autophagy. These findings identify PSG11 as a potential therapeutic target in EOC. PSG11 Epithelial ovarian cancer Hedgehog signaling Autophagy Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Aggressive and common in women, epithelial ovarian cancer (EOC) often begins subtly and has a high risk of spreading to lymph nodes and distant organs [ 1 ]. A 2022 report identified 61,000 new ovarian cancer cases in China, making it the third most prevalent female reproductive malignancy. Additionally, ovarian cancer accounted for 33,000 deaths, ranking second only to cervical cancer in mortality among gynecologic cancers [ 2 ]. These statistics stress the urgent need for new prognostic and therapeutic markers to enhance disease management. In humans, the pregnancy-specific glycoprotein (PSG) family comprises 11 related glycoproteins with largely unknown functions [ 3 ]. Primarily synthesized by the placenta, these glycoproteins belong to both the immunoglobulin superfamily and the carcinoembryonic antigen (CEA) family. PSG11 is encoded by a gene located at chromosome 19q13.31. Historically, PSG11 expression was believed to be restricted to placental tissue and associated with pregnancy-related conditions [ 4 ]. However, recent evidence has expanded the understanding of PSG gene regulation, revealing that PSG expression, including PSG11, is modulated by the CCCTC-binding factor (CTCF) [ 5 ]. Inhibition of CTCF expression led to changes in the transcription of several PSG genes, with some, like PSG6 and PSG11, downregulated, while others were upregulated. These changes were associated with alterations in CTCF binding and histone modifications at PSG promoters, highlighting the importance of epigenetic regulation in PSG gene expression. Interestingly, emerging studies have begun to uncover a potential link between PSG11 and cancer. Zhen Li et al. identified PSG11 in fusobacterium nucleatum-positive esophageal squamous cell carcinoma, which is linked to a higher metastatic risk [ 6 ]. Similarly, PSG9, related to PSG11, is upregulated in various cancers, such as colorectal and breast cancers [ 7 – 10 ]. Furthermore, splicing mutations in PSG9 have been implicated in parotid gland carcinoma [ 11 ]. The role of PSG11 in cancer is still unclear, and its link to EOC remains unexplored. In this study, we have identified PSG11 as a previously unrecognized biomarker for EOC and systematically demonstrated its carcinogenic effects through comprehensive in vivo and in vitro experiments. Mechanistically, we discovered that PSG11 activates the Hedgehog signaling pathway, thereby regulating EOC progression and autophagy to promote cancer development. These findings not only deepen our understanding of the molecular pathogenesis of EOC but also establish PSG11 as a promising therapeutic target. 2. Methods 2.1 Bioinformatics analysis PSG11 expression in EOC was analyzed via bioinformatics using data (the Gene Expresssion Omnibus database, GEO https://www.ncbi.nlm.nih.gov/gds ). Survival-related gene profiles for PSG11 in EOC were derived from The Cancer Genome Atlas (TCGA). Data were accessed via the cBioPortal platform ( https://www.cbioportal.org/ ), and clinical stage data were retrieved from the GDC TCGA database. All datasets were downloaded on October 10, 2022, followed by data cleaning and collation to ensure reliability for subsequent analyses. 2.2 Immunohistochemistry The EOC tissue microarrays were procured from Shanghai Core Super Technology (HOvaC154Su01-M-118) and comprised 154 EOC tissue samples along with 40 para-carcinoma tissues. During the experimental process, 18 cases were excluded due to tissue loss, nine cases were omitted due to incomplete pathological data, and eight cases lacked adjacent tissue slides in the control group. Immunohistochemistry (IHC) was used to analyze PSG11 expression in the remaining tissue samples. These sections underwent deparaffinization, hydration, and immersion in 3% H2O2 at RT for 20 min. Following this, they were incubated overnight with PSG11-specific antibodies (16352-1-AP, Proteintech, 1:100) at 4°C. On the subsequent day, the sections were treated with biotinylated goat anti-rabbit antibodies for 1 h, stained with diaminobenzidine (DAB; Maixin Biotechnology, Shanghai, China), and then counterstained with hematoxylin (Maixin Biotechnology). Two independent pathologists, blind to the experimental data, evaluated the specimens. Scoring was based on staining intensity and the percentage of positively stained.The total score for each visual field was the product of the percentage and intensity scores. 2.3 Cell lines and lentiviral transduction The Cell Bank of the Institute of Biochemistry and Cell Biology in Shanghai supplied EOC cell lines (A2780, OVCAR3, CAOV3) and IOSE80, which were cultured in RPMI 1640 medium (Corning) with 10% FBS (Invitrogen) at 37°C and 5% CO2. RNA interference and overexpression plasmids were designed by Biological Bioengineering Co. (Shanghai, Bioscienceres). Oligonucleotide DNA was reverse-transcribed, annealed into double-stranded DNA, and cloned into LV-002 plasmids using Fermentas T4 DNA ligase. Transformed TOP10 competent cells were cultured on LB solid medium containing ampicillin, and colonies with recombinant plasmids were inoculated in LB liquid medium for monoclonal culture. Plasmids were extracted using the Enzykang GTC Boto-free plasmid extraction kit for subsequent viral packaging. Lentiviral and helper plasmids were co-transfected into A2780 and CAOV3 cells with Lipofectamine 3000. Transfected cells were incubated at 37°C for 48–72 hours, and lentivirus was concentrated by centrifuging at 4°C for two hours. When the cells reached approximately 80% confluence, they were plated into six-well dishes and exposed to either lentiviral particles or control viral vectors. After 72 hours of incubation, infection efficiency was confirmed via fluorescence microscopy. Stably infected cells were selected using puromycin for downstream experiments. 2.4 qRT-PCR for gene expression RNA was extracted with Trizol (Sigma, MO, USA), and cDNA synthesis was performed using the M-MLV Reverse Transcriptase Kit (Promega, WI, USA). qPCR was conducted with the SYBR Green Mastermix Kit (Vazyme, Nanjing, China), and the 2 −ΔΔCt method was applied to assess relative RNA expression, with GAPDH as the reference. The primer sequences were: PSG11 forward: 5′-TCTATGCTTGCTCTGCTCGT-3′; PSG11 reverse: 5′-AATCCTGGAGGAGCAATGAC-3′; GAPDH forward: 5′-TGACTTCAACAGCGACACCCA-3′; GAPDH reverse: 5′-CACCCTGTTGCTGTAGCCAAA-3′. 2.5 Western blot Proteins were extracted with RIPA buffer and quantified via the BCA Assay Kit (HyClone-Pierce). Following SDS-PAGE separation, proteins were transferred to 0.2 µm PVDF membranes. Blocking was performed with non-fat milk for one hour at room temperature, and membranes were incubated overnight at 4°C with a PSG11 primary antibody (1:1000 dilution, rabbit-derived, Proteintech). The membranes were incubated with a secondary antibody (1:3000, A0208, Beyotime) for one hour at RT the next day. Protein bands were visualized via enhanced chemiluminescence (Immobilon Western HRP Substrate, Millipore). Each experiment was repeated three times to ensure reproducibility. 2.6 CCK-8 assay for evaluating cell viability The CCK-8 kit (Sigma, USA) was employed to assess cell viability, with A2780 and CAOV3 cells seeded at 2,000 cells per well in 96-well plates. Each day, 10 µL of CCK-8 reagent was introduced into the wells over a period of five days. Following an incubation time of 1–4 hours, the absorbance at 450 nm was recorded. 2.7 Wound healing migration assay CAOV3 and A2780 cells were grown in six-well plates to 80–90% confluence. Scratches were made with a 200 µL pipette tip and washed with PBS to clear debris. Scratches were imaged at 50× magnification with an OLYMPUS microscope. Cells were incubated in serum-free medium for 24 hours, and scratch areas were re-imaged to evaluate migration. 2.8 Apoptosis analysis by flow cytometry CAOV3 and A2780 cells were collected and prepared as single-cell suspensions. Annexin V-APC and propidium iodide (PI) staining solutions (Vazyme, Nanjing, China) were used as per the manufacturer’s instructions. After 10 minutes of dark incubation at room temperature, a FACSCalibur flow cytometer (BD Biosciences) was employed to evaluate apoptosis. 2.9 Clonogenic assay CAOV3 and A2780 cells were cultured to confluence in six-well plates. The cells were then scraped, rinsed with PBS, and photographed at the initial time point (0 hours) and after 24 hours to evaluate their ability to form colonies. 2.10 Cell migration analysis via transwell assay Cell migration was assessed with Transwell kits (Corning, USA). CAOV3 and A2780 cells (1.5 × 10 5 per well) were seeded in serum-free medium in the upper Transwell chambers, with 600 µL of 30% FBS medium in the lower chambers. After 24 hours, cells were fixed with 4% PFA, stained with 0.5% crystal violet for 30 minutes, and viewed at 200× magnification (OLYMPUS). Migrated cells were quantified. 2.11 In vivo experiment Animal procedures complied with ethical guidelines and were approved by the Chengde Medical University Animal Ethics Committee (CYFYLL2024312). Four-week-old BALB/c nude mice (16–20 g) were obtained from Shanghai Lingchang Biotechnology Co., Ltd. The mice were housed in specific pathogen-free (SPF) conditions at 22 ± 3°C, 55 ± 5% humidity, and a 12-hour light/dark cycle, with unrestricted access to food and water. The mice were randomly assigned to shPSG11 and shCtrl groups (n = 6 per group) and injected with 0.2 mL of lentivirus-transfected A2780 cells. Tumor volumes, calculated as π/6 × length × width 2 , were monitored for 28 days. Tumors were excised and weighed on the final day. 2.12 Statistical analysis Experiments were all repeated three times, and data are presented as the mean ± standard deviation. Statistical tests included the Student’s t-test, Kaplan-Meier Survival Cures, Multivariate Cox Regression Analysis and one-way ANOVA. The association of PSG11 expression with clinical parameters was analyzed using Chi-square tests. SPSS and GraphPad Prism 8.0 were used for data analysis. 3. Results 3.1 PSG11 is high expressed and linked with prognosis in ovarian cancer To identify prognostic biomarkers in epithelial ovarian cancer (EOC), we analyzed the GEO dataset GSE26712, which includes 185 EOC and 10 normal ovarian samples. Differential expression analysis (Padj 0) revealed 4,951 upregulated and 3,023 downregulated genes. Survival analysis using TCGA data via cBioPortal identified two high-expression genes (PSG11 and QKI) and five low-expression genes (C1orf115, C7orf49, CD38, LRRC4, and NPEPL1) significantly associated with poor overall and progression-free survival (HR > 1.5 or < 0.67, P < 0.01). Intersection analysis of upregulated differentially expressed genes (DEGs) from GSE26712 and high-risk gene signatures from the TCGA cohort identified two overlapping genes, with PSG11 selected for further investigation based on its superior differential overall survival hazard ratio. Subsequent validation in the GSE26712 dataset confirmed significantly elevated PSG11 expression levels in EOC samples, and its expression correlated strongly with poor prognosis (Figure 1A). Kaplan-Meier survival analysis in the TCGA cohort further supported the prognostic value of PSG11 (Figure 1B). To experimentally validate these bioinformatic findings, we performed IHC staining on a separate cohort comprising 127 primary EOC tissues and 32 matched para-cancerous tissues. As shown in Figure 1C and summarized in Table 1, PSG11 protein was markedly overexpressed in EOC tissues compared to adjacent non-tumorous tissues ( P < 0.001). High PSG11 expression was significantly correlated with advanced FIGO stage (P < 0.001), presence of distant metastasis (P = 0.004), larger tumor size (P = 0.017), and lymph node involvement (P = 0.019) (Table 2). Furthermore, survival analysis in this validation cohort reinforced the prognostic significance of PSG11 overexpression (Figure 1D). 3.2 Expression and effect of PSG11 in EOC cells PSG11 mRNA expression was significantly upregulated in EOC cell lines (A2780, CAOV3, OVCAR3) versus the normal IOSE80 cell line (Fig.2A). PSG11 protein expression was markedly higher in EOC cell lines than in IOSE80 (Fig.2B). A2780 and CAOV3 displayed the highest PSG11 mRNA and protein expression among the EOC cell lines, exceeding levels in OVCAR3. A2780 and CAOV3 were selected for further experiments, as the data suggest PSG11’s involvement in EOC progression. PSG11 expression was stably silenced in A2780 cells using a lentiviral system to investigate its role. PSG11 protein levels were markedly lower in cells treated with shPSG11-1, shPSG11-2, and shPSG11-3 than in the shCtrl group. shPSG11-2 and shPSG11-3, showing the strongest knockdown, were used in A2780 and CAOV3 experiments (Fig.2C-D). The functional impact of PSG11 knockdown was then evaluated in A2780 and CAOV3 cells (Fig.2E). After five days, shPSG11 cells showed significantly reduced viability compared to shCtrl cells ( P < 0.001), indicating PSG11 knockdown inhibits EOC proliferation (Fig.3A). Colony formation assays confirmed this, with A2780 and CAOV3 cells forming significantly fewer colonies after PSG11 knockdown (Fig.3B). Flow cytometry revealed that PSG11 knockdown significantly increased apoptosis in A2780 and CAOV3 cells compared to controls (Fig.3C). Transwell and wound-healing assays revealed significantly lower migration rates in A2780 and CAOV3 cells with PSG11 knockdown compared to controls. PSG11 knockdown cells showed significantly slower migration 24 hours after the scratch in the wound-healing assay compared to controls (Fig. 3D and Fig. 3E). PSG11 knockdown reduces viability, proliferation, and migration and triggers apoptosis in EOC cells in vitro. These findings suggest PSG11 may regulate tumor cell behavior in EOC. 3.3 PSG11 activates hedgehog pathway to regulate autophagy in EOC progression We analyzed TCGA ovarian cancer data using Gene Set Enrichment Analysis (GSEA) to examine PSG11's involvement in EOC progression. The Hh signaling pathway was significantly linked to PSG11 expression in the analysis. Among the top 10 gene sets identified in the PID database, the Hh signaling pathway emerged as a prominent candidate, with a normalized enrichment score (NES) of 1.5359 ( P < 0.05). High PSG11 expression appears to activate the Hh pathway, potentially facilitating ovarian cancer progression (Fig.4A). The Hh pathway, regulated by Glioma-associated oncogene homolog 1 (GLI1) and Glioma-associated oncogene homolog 2 (GLI2), is vital for embryonic development and tissue repair [12]. The expression of GLI1 and GLI2 proteins in EOC cells was analyzed to explore PSG11's role in the Hh signaling pathway. Knocking down PSG11 significantly reduced GLI1 and GLI2 levels (Fig.4B), confirming its key role in Hh pathway activation as indicated by GSEA. To advance the exploration of the functional relationship between PSG11 and the Hh signaling pathway, SAG, a potent Smoothened (Smo) receptor agonist, was utilized to activate the pathway [13]. Four experimental groups were established: PSG11 knockdown control (shCtrl), PSG11 knockdown (shPSG11), PSG11 knockdown control with SAG treatment (shCtrl + SAG), and PSG11 knockdown with SAG treatment (shPSG11 + SAG). SAG activation of the Hh pathway significantly boosted EOC cells viability, as shown by CCK8 assays 24 hours post-inoculation (Fig.5A). Moreover, colony formation, Transwell, and wound-healing assays revealed that Hh pathway activation restored the proliferative and migratory capacities of EOC cells, even in the presence of PSG11 knockdown. The shPSG11 + SAG group showed significantly lower apoptosis rates than the shPSG11 group, supporting the Hh pathway’s role in mitigating PSG11 knockdown effects (Fig.5B-E). The Western blot(WB) analysis was used to evaluate if PSG11 regulates autophagy via the Hh signaling pathway. PSG11 knockdown was found to suppress the Hh pathway and significantly enhanced LC3 levels to promote autophagy in EOC cells(Fig.4C). PSG11 appears to drive EOC progression by activating the Hh pathway to regulate autophagy. 3.4 PSG11 inhibits tumor growth of EOC In vivo PSG11's impact on tumor growth was assessed in vivo with a mouse xenograft model. Mice were subcutaneously injected with A2780 cells transfected with shCtrl or shPSG11, and tumor growth was tracked over time. Tumor volumes measured from day 8 post-inoculation showed significantly slower growth in the shPSG11 group versus the shCtrl group. Tumor volume and weight were significantly reduced in the shPSG11 group versus the shCtrl group by day 30 (Fig. 6A). The Immunohistochemistry analysis of tumor tissues provided additional insights into the molecular effects of PSG11 knockdown. Ki67, a proliferation marker, was significantly lower in the shPSG11 group than in the shCtrl group.GLI1, and GLI2 expression was significantly lower in the shPSG11 group, LC3A/B was significantly higher in the shPSG11 group than in the shCtrl group,consistent with in vitro data (Fig. 6B). The PSG11 promotes EOC tumor growth, likely via Hh pathway activation,and regulate autophagy while its knockdown inhibits tumor progression in vivo, making it a potential therapeutic target. 4. Discussion The EOC ranks fifth in cancer-related deaths among women, reflecting its major public health burden. The first seven-year survival data on PARP inhibitors marks a key breakthrough in treating certain ovarian cancer patients [ 14 ]. While progress has been made, maintaining platinum sensitivity and extending progression-free survival with PARP inhibitors remains challenging in recurrent ovarian cancer [ 15 ]. This signals an urgent need for new treatment options. Further research is vital to uncover the ovarian cancer progression’s molecular basis and to explore precise biomarkers. This study demonstrates that PSG11 downregulation inhibits tumor growth, emphasizing its viability as a therapeutic target for EOC. Carcinoembryonic antigen cell adhesion molecule (CEACAM) gene families and PSG are members of the immunoglobulin superfamily [ 16 ]. CEACAMs, including CEA, are now better understood in cancer and are widely used as tumor markers in clinical practice [17–19]. These markers have greatly facilitated the diagnosis and management of malignant tumors. As homologous derivatives of the CEACAM family, the PSG family is hypothesized to perform similar functions. PSG7 plays a pivotal role in papillary thyroid cancer progression [ 20 ], with evidence linking PSG family members to various cancers [ 21 – 24 ]. Bioinformatics analyses reveal, compared to normal tissues, that PSG11 exhibits higher expression levels in ovarian cancer tissues. Nevertheless, this observation had not been experimentally validated [ 25 ]. Using GEO and TCGA datasets, we identified PSG11 as an abnormally expressed gene with poor prognostic relevance in EOC through comparative analysis of gene expression profiles. Consistent with these bioinformatics findings, we confirmed for the first time that PSG11 expression is elevated in EOC cell lines using WB and qPCR analyses. We found that PSG11 downregulation inhibits key processes such as migration, invasion, growth, and proliferation in EOC cells, confirming its role in EOC progression.Although in vitro cell lines and in vivo mouse models provide valuable insights, they may not fully replicate the complexity of human EOC,the next step we will explore PSG11 inhibitor or Hh pathway modulators as potential treatments,and conduct clinical studies with larger and more divers patient cohorts to validate PSG11 as a therapeutic target. The Hh signaling pathway regulates mammalian growth and tissue stability [ 26 ], with its oncogenic role confirmed in cancers like papillary thyroid carcinoma [ 27 ] and colorectal cancer [ 28 ]. To further investigate the mechanisms underlying PSG11’s involvement in EOC, we identified its association with the Hh signaling pathway through the PID database. Elevated PSG11 expression was found to correlate with Hh pathway activation. The Hh pathway is crucial in EOC, with Zhu et al. [ 29 ] showing that TSPAN8 activates ovarian cancer stem cells through this mechanism. Resveratrol counters LPA-driven migration and platinum resistance in ovarian cancer cells by restoring Hh-mediated autophagy [ 30 ]. Hu et al. [ 31 ] showed that gut microbiota dysbiosis drives EOC progression through Hh signaling. We were the first to identify PSG11 as a driver of EOC progression through the Hh signaling pathway in vitro,while further research is needed to map out the complete signaling cascade. What’s more,PSG11 downregulation in vivo inhibited tumor growth in a mouse xenograft model. PSG11 knockdown was found to boost Hh-mediated autophagy, which may inhibit tumor progression. This aligns with previous findings that autophagy can suppress or promote tumors, depending on the biological context[ 32 ]. In conclusion, our study confirms PSG11’s key role in EOC progression. By activating the Hh signaling pathway, PSG11 may regulate autophagy to promote tumor growth and progression. The results suggest PSG11 is a promising new target for EOC therapy, whether PSG11 contributes to chemotherapy resistance in EOC is needed. Future work should examine the clinical impact of targeting PSG11 to improve ovarian cancer treatments. Declarations Funding Statement This study was supported by Hebei Natural Science Foundation (No.H2020206223,H2024406004) Author Contribution Suwei Lan and Zhengmao Zhang designed the conceptualization,Qian Li collected data,Qing Li formaled analysis, Suwei Lan,Zhengmao Zhang,Qian Li and Xingcha Wang provided the fundings,Xingcha Wang investigated the manuscript,Suwei Lan implemented the experiment,wrote the original draft,Zhengmao Zhang editored and reviewed the manuscript,All authors reviewed the manuscript. Data Availability Data is provided within the manuscript or supplementary information files References Wang L, Wang X, Zhu X, et al. Drug resistance in ovarian cancer: from mechanism to clinical trial. Mol Cancer. 2024 Mar 28;23(1):66. Zheng Rongshou, Chen Ru, Han Bingfeng, et al. Analysis of the prevalence of malignant tumors in China in 2022 [J]. Chinese Journal of Oncology, 2024,46 (3): 221-231. Zhou GQ, Baranov V, Zimmermann W,et al. Highly specific monoclonal antibody demonstrates that pregnancy-specific glycoprotein (PSG) is limited to syncytiotrophoblast in human early and term placenta. Placenta. 1997 Sep;18(7):491-501. Zhao L, Triche EW, Walsh KM, et al. Genome-wide association study identifies a maternal copy-number deletion in PSG11 enriched among preeclampsia patients. BMC Pregnancy Childbirth. 2012 Jun 29;12:61. Jeong DS, Kim MH, Lee JY. Depletion of CTCF disrupts PSG gene expression in the human trophoblast cell line Swan 71. FEBS Open Bio. 2021 Mar;11(3):804-812. Li Z, Shi C, Zheng J, et al. Fusobacterium nucleatum predicts a high risk of metastasis for esophageal squamous cell carcinoma. BMC Microbiol. 2021 Oct 30;21(1):301. Xiong Y, Feng Y, Zhao J, et al. TFAP2A potentiates lung adenocarcinoma metastasis by a novel miR-16 family/TFAP2A/PSG9/TGF-β signaling pathway. Cell Death Dis. 2021 Apr 6;12(4):352. Yang L, Hu S, Tan J, et al. Pregnancy-specific glycoprotein 9 (PSG9), a driver for colorectal cancer, enhances angiogenesis via activation of SMAD4. Oncotarget. 2016 Sep 20;7(38):61562-61574. Rong W, Yang L, Yin L, Gao Y, Xiao T, Cheng S. PSG9 promotes angiogenesis by stimulating VEGFA production and is associated with poor prognosis in hepatocellular carcinoma. Sci China Life Sci. 2017 May;60(5):528-535. Liu YY, Zhang S, Yu TJ, et al. Pregnancy-specific glycoprotein 9 acts as both a transcriptional target and a regulator of the canonical TGF-β/Smad signaling to drive breast cancer progression. Clin Transl Med. 2020 Dec;10(8):e245. Ishikawa T, Ogawa T, Nakanome A, et al. Whole exome sequencing and establishment of an organoid culture of the carcinoma showing thymus-like differentiation (CASTLE) of the parotid gland. Virchows Arch. 2021 Jun;478(6):1149-1159. Ingham PW, Nakano Y, Seger C. Mechanisms and functions of Hedgehog signalling across the metazoa. Nat Rev Genet. 2011 Jun;12(6):393-406. Chen JK, Taipale J, Young KE, Maiti T, Beachy PA. Small molecule modulation of Smoothened activity. Proc Natl Acad Sci U S A. 2002 Oct 29;99(22):14071-6. Konstantinopoulos PA, Norquist B, Lacchetti C, et al. Germline and Somatic Tumor Testing in Epithelial Ovarian Cancer: ASCO Guideline. J Clin Oncol. 2020 Apr 10;38(11):1222-1245. Pujade-Lauraine E, Selle F, Scambia G, et al. Maintenance olaparib rechallenge in patients with platinum-sensitive relapsed ovarian cancer previously treated with a PARP inhibitor (OReO/ENGOT-ov38): a phase IIIb trial. Ann Oncol. 2023 Dec;34(12):1152-1164. Kammerer R, Zimmermann W. Coevolution of activating and inhibitory receptors within mammalian carcinoembryonic antigen families. BMC Biol. 2010 Feb 4;8:12. Wautier JL, Wautier MP. Old and New Blood Markers in Human Colorectal Cancer. Int J Mol Sci. 2022 Oct 26;23(21):12968. Tsang KY, Fantini M, Mavroukakis SA, Zaki A, Annunziata CM, Arlen PM. Development and Characterization of an Anti-Cancer Monoclonal Antibody for Treatment of Human Carcinomas. Cancers (Basel). 2022 Jun 21;14(13):3037. Seckinger A, Majocchi S, Moine V, et al. Development and characterization of NILK-2301, a novel CEACAM5xCD3 κλ bispecific antibody for immunotherapy of CEACAM5-expressing cancers. J Hematol Oncol. 2023 Dec 12;16(1):117. Wang H, Shen L, Li Y, Lv J. Integrated characterisation of cancer genes identifies key molecular biomarkers in stomach adenocarcinoma. J Clin Pathol. 2020 Sep;73(9):579-586. Su X, Zhang J, Yang W, et al. Identification of the Prognosis-Related lncRNAs and Genes in Gastric Cancer. Front Genet. 2020 Feb 11;11:27. Dan K, Lee JE, Han D, et al. Proteomic identification of biomarkers in maternal plasma that predict the outcome of rescue cerclage for cervical insufficiency. PLoS One. 2021 Apr 15;16(4):e0250031. Houston A, Williams JM, Rovis TL, et al. Pregnancy-specific glycoprotein expression in normal gastrointestinal tract and in tumors detected with novel monoclonal antibodies. MAbs. 2016;8(3):491-500. Rodríguez-Esquivel M, Romero-Morelos P, Taniguchi-Ponciano K, et al. Expression of Pregnancy Specific β-1 Glycoprotein 1 in Cervical Cancer Cells. Arch Med Res. 2020 Aug;51(6):504-514. Zhang Q, Burdette JE, Wang JP. Integrative network analysis of TCGA data for ovarian cancer. BMC Syst Biol. 2014 Dec 31;8:1338. Briscoe J, Thérond PP. The mechanisms of Hedgehog signalling and its roles in development and disease. Nat Rev Mol Cell Biol. 2013 Jul;14(7):416-29. Xu Y, Ma N, Wei P, Zeng Z, Meng J. Expression of hydrogen sulfide synthases and Hh signaling pathway components correlate with the clinicopathological characteristics of papillary thyroid cancer patients. Int J Clin Exp Pathol. 2018 Mar 1;11(3):1818-1824. Sun Q, Yang H, Liu M, et al. Berberine suppresses colorectal cancer by regulation of Hedgehog signaling pathway activity and gut microbiota. Phytomedicine. 2022 Aug;103:154227. Zhu R, Gires O, Zhu L, et al. TSPAN8 promotes cancer cell stemness via activation of sonic Hedgehog signaling. Nat Commun. 2019 Jun 28;10(1):2863. Ferraresi A, Esposito A, Girone C, et al. Resveratrol Contrasts LPA-Induced Ovarian Cancer Cell Migration and Platinum Resistance by Rescuing Hedgehog-Mediated Autophagy. Cells. 2021 Nov 17;10(11):3213. Hu X, Xu X, Zeng X, et al. Gut microbiota dysbiosis promotes the development of epithelial ovarian cancer via regulating Hedgehog signaling pathway. Gut Microbes. 2023 Jan-Dec;15(1):2221093. Niu X, You Q, Hou K, et al.Autophagy in cancer development, immune evasion, and drug resistance. Drug Resist Updat. 2025 Jan;78:101170. Tables Table 1. Differential expression of PSG11 in EOC and para-cancerous tissues. PSG11 Tumor tissue Para-cancerous tissue P value expression Cases Proportion Cases Proportion Low 67 52.8% 28 87.5% < 0.001 High 60 47.2% 4 12.5% Table 2. Correlation between clinicopathological features and PSG11 expression in EOC patients. Features All patients No. of patients (127) PSG11 expression P value Low (67) High (60) Age (years) ＜53 ≥53 69 58 35 32 34 26 0.618 Stage I II III IV 6 30 63 28 3 24 32 8 3 6 31 20 < 0.001 Tumor size ＜13cm ≥13cm 63 64 40 27 23 37 0.017 T Infiltrate T1 T2 T3 6 30 91 2 24 40 3 6 51 0.003 Lymphatic metastasis (N) N0 N1 91 36 54 13 37 23 0.019 Distant Metastasis (M) M0 M1 99 28 59 8 40 20 0.004 HOvaC1541Su01 EGFR ≤0.5 >0.5 78 49 38 29 40 20 0.252 HOvaC1541Su01 PDL1 ＜0.5 ≥0.5 49 78 28 39 21 39 0.434 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7239376","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":493532229,"identity":"dd723548-b412-4c58-b5e2-7592dcc30f7c","order_by":0,"name":"Suwei Lan","email":"","orcid":"","institution":"Affiliated Hospital of Chengde medical university","correspondingAuthor":false,"prefix":"","firstName":"Suwei","middleName":"","lastName":"Lan","suffix":""},{"id":493532230,"identity":"2966c4fe-eb86-4b12-bdb8-b78901387d4f","order_by":1,"name":"Qian Li","email":"","orcid":"","institution":"Affiliated Hospital of Chengde medical university","correspondingAuthor":false,"prefix":"","firstName":"Qian","middleName":"","lastName":"Li","suffix":""},{"id":493532231,"identity":"bd740b03-88b9-4356-81ba-13a2421b1201","order_by":2,"name":"Qing Li","email":"","orcid":"","institution":"Chengde medical university","correspondingAuthor":false,"prefix":"","firstName":"Qing","middleName":"","lastName":"Li","suffix":""},{"id":493532232,"identity":"43138d4b-67f5-472b-a580-b6a10cdc4344","order_by":3,"name":"Xingcha Wang","email":"","orcid":"","institution":"Affiliated Hospital of Chengde medical university","correspondingAuthor":false,"prefix":"","firstName":"Xingcha","middleName":"","lastName":"Wang","suffix":""},{"id":493532233,"identity":"bad3e9de-2040-4376-b4c9-a6b7262fd1df","order_by":4,"name":"Zhengmao Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIiWNgGAWjYDACCTB5AMqrOJAApnmI13KGZC2MbURokZ/d/Ozhlz935Mz5Vyd++DjvTp7ujATGB2/bcGthnHPM3FiG55mx5Yy3myVnbntWbHYjgdlwLh4tzBIJZtISEocTN9w4u0Gad9vhxG03EtikefFoYZNI/yYtYXC4Hqhl82/eOWAt7L/xaeGRyDGT/JBwOMHgfO82ad4GiC3M+LRISOSUSTMcOGy44QbvNssZxw4Xm5152Cw55xxuLfIz0rdJ/vhzWN7g/NnNNz7UHM4zO5588MObMtxawEEAjgWJBBifsQG/epCSHyCS/wBBhaNgFIyCUTBCAQArtF9hZ0ceggAAAABJRU5ErkJggg==","orcid":"","institution":"Hebei Medical University","correspondingAuthor":true,"prefix":"","firstName":"Zhengmao","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2025-07-29 05:53:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7239376/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7239376/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88328217,"identity":"d86576f8-ed3d-4926-8616-cdbab5487e74","added_by":"auto","created_at":"2025-08-05 10:10:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":662847,"visible":true,"origin":"","legend":"\u003cp\u003eThe high expression of PSG11.(A) The expression and prognostic of PSG11 in GSE26712.(B)The prognostic analysis of PSG11 in TCGA. (C) The expression of PSG11 in OC and paracancerous tissues. (D) The prognostic of PSG11 in specimens.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7239376/v1/72961ab1bd930c21a01c8507.png"},{"id":88328226,"identity":"5946cfe5-ad69-4237-a6e2-cea3c65ba501","added_by":"auto","created_at":"2025-08-05 10:10:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":582594,"visible":true,"origin":"","legend":"\u003cp\u003eThe expression of PSG11in EOC cells.(A-B) The mRNA and protein expression levels of PSG11 in EOC and normal cells.(C) Effective target screening of PSG11 in A2780 cells. GAPDH was detected as a loading control in the WB.(D)The photos of Lentiviral-infected cells.(E)The mRNA and protein expression levels of PSG11 in EOC PSG11-knock down and shCtrl cells.The data were expressed as mean ± SD (n = 3), *\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.1, ** \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.01, *** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7239376/v1/671102189e57176a2efd9403.png"},{"id":88328220,"identity":"bf45097e-7df2-428f-b1b8-db5ed3488a64","added_by":"auto","created_at":"2025-08-05 10:10:46","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":632598,"visible":true,"origin":"","legend":"\u003cp\u003eThe effects of PSG11 on the proliferation and apoptosis of EOC cells. (A-B) CCK-8 and clone formation assay revealed that silencing PSG11 decreased the proliferation rate in A2780 and CAOV3 cells. (C) The effect of PSG11-knockdown on apoptosis of A2780 and CAOV3 cells was examined by FACS. (D)Transwell assay revealed that silencing PSG11 decreased the invasion rate in EOC cells.(E) Cell migration of EOC cells was evaluated by Wound-healing assay following knockdown of PSG11.The data were expressed as mean ± SD (n = 3), *\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.1, ** \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.01, *** \u003cem\u003eP\u003c/em\u003e\u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7239376/v1/40f54ee2e24ca3f1228cb433.png"},{"id":88328218,"identity":"1c62210b-21c8-4500-8e3a-e22e9a01d463","added_by":"auto","created_at":"2025-08-05 10:10:46","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":233506,"visible":true,"origin":"","legend":"\u003cp\u003ePSG11 may activates the Hedgehog Signaling pathway to regulate autophagy in EOC. (A) enrichment analysis of PSG11-related genes in PID pathway. (B) Knocking down PSG11 reduced GLI1 and GLI2 levels in EOC cells. (C)PSG11 knockdown was found to suppress the Hh pathway and enhanced autophagy in EOC cells.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7239376/v1/21574919d4eca38063e15c99.png"},{"id":88328222,"identity":"574f4fbc-15d7-4baa-95b8-737d49e9aa6c","added_by":"auto","created_at":"2025-08-05 10:10:46","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":833706,"visible":true,"origin":"","legend":"\u003cp\u003eThe effects of PSG11 knockdown and Hh pathway activation in EOC cells. (A-B) CCK-8 and clone formation assay revealed that PSG11 knockdown decreased the proliferation rate while Hh activated restored the proliferation rate in EOC cells. (C) Transwell assay revealed that silencing PSG11 decreased the invasion rate while Hh activated restored the invasion in EOC cells.(D)Cell migration of EOC cells was evaluated by Wound-healing assay following knockdown of PSG11 and Hh pathway activation .(E) The effect of PSG11-knockdown and Hh pathway activation on apoptosis of EOC cells were examined by FACS.The data were expressed as mean ± SD (n = 3), *\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.1, ** \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.01, *** \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7239376/v1/3e7de066b3a1f9d3ec7b495d.png"},{"id":88328219,"identity":"440fdfed-b8ed-4abb-a2e1-77abd5d20691","added_by":"auto","created_at":"2025-08-05 10:10:46","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":627014,"visible":true,"origin":"","legend":"\u003cp\u003eKnockdown of PSG11 suppressed tumor growth of EOC.(A)Images of mice and tumors and tumor weight and volume in the shCtrl and PSG11knockdown groups.(B) IHC staining of Ki67,GLI1,GLI2 and LC3A/B,*\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.1, ** \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7239376/v1/a5d818110fa5ed50e0167e0d.png"},{"id":88723669,"identity":"410dbfb6-15e4-40c1-bedd-9d48b498410f","added_by":"auto","created_at":"2025-08-10 14:16:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4026451,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7239376/v1/778b5cc5-a320-4843-ac04-b3be07437c89.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"PSG11 Overexpression Promotes Epithelial Ovarian Cancer Progression via Hedgehog-Mediated Autophagy Regulation","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAggressive and common in women, epithelial ovarian cancer (EOC) often begins subtly and has a high risk of spreading to lymph nodes and distant organs [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. A 2022 report identified 61,000 new ovarian cancer cases in China, making it the third most prevalent female reproductive malignancy. Additionally, ovarian cancer accounted for 33,000 deaths, ranking second only to cervical cancer in mortality among gynecologic cancers [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. These statistics stress the urgent need for new prognostic and therapeutic markers to enhance disease management.\u003c/p\u003e\u003cp\u003eIn humans, the pregnancy-specific glycoprotein (PSG) family comprises 11 related glycoproteins with largely unknown functions [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Primarily synthesized by the placenta, these glycoproteins belong to both the immunoglobulin superfamily and the carcinoembryonic antigen (CEA) family. PSG11 is encoded by a gene located at chromosome 19q13.31. Historically, PSG11 expression was believed to be restricted to placental tissue and associated with pregnancy-related conditions [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. However, recent evidence has expanded the understanding of PSG gene regulation, revealing that PSG expression, including PSG11, is modulated by the CCCTC-binding factor (CTCF) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Inhibition of CTCF expression led to changes in the transcription of several PSG genes, with some, like PSG6 and PSG11, downregulated, while others were upregulated. These changes were associated with alterations in CTCF binding and histone modifications at PSG promoters, highlighting the importance of epigenetic regulation in PSG gene expression. Interestingly, emerging studies have begun to uncover a potential link between PSG11 and cancer. Zhen Li et al. identified PSG11 in fusobacterium nucleatum-positive esophageal squamous cell carcinoma, which is linked to a higher metastatic risk [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Similarly, PSG9, related to PSG11, is upregulated in various cancers, such as colorectal and breast cancers [\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Furthermore, splicing mutations in PSG9 have been implicated in parotid gland carcinoma [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The role of PSG11 in cancer is still unclear, and its link to EOC remains unexplored.\u003c/p\u003e\u003cp\u003eIn this study, we have identified PSG11 as a previously unrecognized biomarker for EOC and systematically demonstrated its carcinogenic effects through comprehensive in vivo and in vitro experiments. Mechanistically, we discovered that PSG11 activates the Hedgehog signaling pathway, thereby regulating EOC progression and autophagy to promote cancer development. These findings not only deepen our understanding of the molecular pathogenesis of EOC but also establish PSG11 as a promising therapeutic target.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Bioinformatics analysis\u003c/h2\u003e\u003cp\u003ePSG11 expression in EOC was analyzed via bioinformatics using data (the Gene Expresssion Omnibus database, GEO \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/gds\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/gds\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Survival-related gene profiles for PSG11 in EOC were derived from The Cancer Genome Atlas (TCGA). Data were accessed via the cBioPortal platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cbioportal.org/\u003c/span\u003e\u003cspan address=\"https://www.cbioportal.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and clinical stage data were retrieved from the GDC TCGA database. All datasets were downloaded on October 10, 2022, followed by data cleaning and collation to ensure reliability for subsequent analyses.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Immunohistochemistry\u003c/h2\u003e\u003cp\u003eThe EOC tissue microarrays were procured from Shanghai Core Super Technology (HOvaC154Su01-M-118) and comprised 154 EOC tissue samples along with 40 para-carcinoma tissues. During the experimental process, 18 cases were excluded due to tissue loss, nine cases were omitted due to incomplete pathological data, and eight cases lacked adjacent tissue slides in the control group. Immunohistochemistry (IHC) was used to analyze PSG11 expression in the remaining tissue samples.\u003c/p\u003e\u003cp\u003eThese sections underwent deparaffinization, hydration, and immersion in 3% H2O2 at RT for 20 min. Following this, they were incubated overnight with PSG11-specific\u003c/p\u003e\u003cp\u003eantibodies (16352-1-AP, Proteintech, 1:100) at 4\u0026deg;C. On the subsequent day, the\u003c/p\u003e\u003cp\u003esections were treated with biotinylated goat anti-rabbit antibodies for 1 h,\u003c/p\u003e\u003cp\u003estained with diaminobenzidine (DAB; Maixin Biotechnology, Shanghai,\u003c/p\u003e\u003cp\u003eChina), and then counterstained with hematoxylin (Maixin Biotechnology).\u003c/p\u003e\u003cp\u003eTwo independent pathologists, blind to the experimental data, evaluated the specimens. Scoring was based on staining intensity and the percentage of positively stained.The total score for each visual field was the product of the percentage and intensity scores.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Cell lines and lentiviral transduction\u003c/h2\u003e\u003cp\u003eThe Cell Bank of the Institute of Biochemistry and Cell Biology in Shanghai supplied EOC cell lines (A2780, OVCAR3, CAOV3) and IOSE80, which were cultured in RPMI 1640 medium (Corning) with 10% FBS (Invitrogen) at 37\u0026deg;C and 5% CO2.\u003c/p\u003e\u003cp\u003eRNA interference and overexpression plasmids were designed by Biological Bioengineering Co. (Shanghai, Bioscienceres). Oligonucleotide DNA was reverse-transcribed, annealed into double-stranded DNA, and cloned into LV-002 plasmids using Fermentas T4 DNA ligase. Transformed TOP10 competent cells were cultured on LB solid medium containing ampicillin, and colonies with recombinant plasmids were inoculated in LB liquid medium for monoclonal culture. Plasmids were extracted using the Enzykang GTC Boto-free plasmid extraction kit for subsequent viral packaging.\u003c/p\u003e\u003cp\u003eLentiviral and helper plasmids were co-transfected into A2780 and CAOV3 cells with Lipofectamine 3000. Transfected cells were incubated at 37\u0026deg;C for 48\u0026ndash;72 hours, and lentivirus was concentrated by centrifuging at 4\u0026deg;C for two hours. When the cells reached approximately 80% confluence, they were plated into six-well dishes and exposed to either lentiviral particles or control viral vectors. After 72 hours of incubation, infection efficiency was confirmed via fluorescence microscopy. Stably infected cells were selected using puromycin for downstream experiments.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 qRT-PCR for gene expression\u003c/h2\u003e\u003cp\u003eRNA was extracted with Trizol (Sigma, MO, USA), and cDNA synthesis was performed using the M-MLV Reverse Transcriptase Kit (Promega, WI, USA). qPCR was conducted with the SYBR Green Mastermix Kit (Vazyme, Nanjing, China), and the 2\u003csup\u003e\u0026minus;ΔΔCt\u003c/sup\u003e method was applied to assess relative RNA expression, with GAPDH as the reference. The primer sequences were:\u003c/p\u003e\u003cp\u003ePSG11 forward: 5\u0026prime;-TCTATGCTTGCTCTGCTCGT-3\u0026prime;;\u003c/p\u003e\u003cp\u003ePSG11 reverse: 5\u0026prime;-AATCCTGGAGGAGCAATGAC-3\u0026prime;;\u003c/p\u003e\u003cp\u003eGAPDH forward: 5\u0026prime;-TGACTTCAACAGCGACACCCA-3\u0026prime;;\u003c/p\u003e\u003cp\u003eGAPDH reverse: 5\u0026prime;-CACCCTGTTGCTGTAGCCAAA-3\u0026prime;.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Western blot\u003c/h2\u003e\u003cp\u003eProteins were extracted with RIPA buffer and quantified via the BCA Assay Kit (HyClone-Pierce). Following SDS-PAGE separation, proteins were transferred to 0.2 \u0026micro;m PVDF membranes. Blocking was performed with non-fat milk for one hour at room temperature, and membranes were incubated overnight at 4\u0026deg;C with a PSG11 primary antibody (1:1000 dilution, rabbit-derived, Proteintech). The membranes were incubated with a secondary antibody (1:3000, A0208, Beyotime) for one hour at RT the next day. Protein bands were visualized via enhanced chemiluminescence (Immobilon Western HRP Substrate, Millipore). Each experiment was repeated three times to ensure reproducibility.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6 CCK-8 assay for evaluating cell viability\u003c/h2\u003e\u003cp\u003eThe CCK-8 kit (Sigma, USA) was employed to assess cell viability, with A2780 and CAOV3 cells seeded at 2,000 cells per well in 96-well plates. Each day, 10 \u0026micro;L of CCK-8 reagent was introduced into the wells over a period of five days. Following an incubation time of 1\u0026ndash;4 hours, the absorbance at 450 nm was recorded.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.7 Wound healing migration assay\u003c/h2\u003e\u003cp\u003eCAOV3 and A2780 cells were grown in six-well plates to 80\u0026ndash;90% confluence. Scratches were made with a 200 \u0026micro;L pipette tip and washed with PBS to clear debris. Scratches were imaged at 50\u0026times; magnification with an OLYMPUS microscope. Cells were incubated in serum-free medium for 24 hours, and scratch areas were re-imaged to evaluate migration.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e2.8 Apoptosis analysis by flow cytometry\u003c/h2\u003e\u003cp\u003eCAOV3 and A2780 cells were collected and prepared as single-cell suspensions. Annexin V-APC and propidium iodide (PI) staining solutions (Vazyme, Nanjing, China) were used as per the manufacturer\u0026rsquo;s instructions. After 10 minutes of dark incubation at room temperature, a FACSCalibur flow cytometer (BD Biosciences) was employed to evaluate apoptosis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e2.9 Clonogenic assay\u003c/h2\u003e\u003cp\u003eCAOV3 and A2780 cells were cultured to confluence in six-well plates. The cells were then scraped, rinsed with PBS, and photographed at the initial time point (0 hours) and after 24 hours to evaluate their ability to form colonies.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003e2.10 Cell migration analysis via transwell assay\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eCell migration was assessed with Transwell kits (Corning, USA). CAOV3 and A2780 cells (1.5 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e per well) were seeded in serum-free medium in the upper Transwell chambers, with 600 \u0026micro;L of 30% FBS medium in the lower chambers. After 24 hours, cells were fixed with 4% PFA, stained with 0.5% crystal violet for 30 minutes, and viewed at 200\u0026times; magnification (OLYMPUS). Migrated cells were quantified.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e2.11 In vivo experiment\u003c/h2\u003e\u003cp\u003e Animal procedures complied with ethical guidelines and were approved by the Chengde Medical University Animal Ethics Committee (CYFYLL2024312). Four-week-old BALB/c nude mice (16\u0026ndash;20 g) were obtained from Shanghai Lingchang Biotechnology Co., Ltd. The mice were housed in specific pathogen-free (SPF) conditions at 22\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u0026deg;C, 55\u0026thinsp;\u0026plusmn;\u0026thinsp;5% humidity, and a 12-hour light/dark cycle, with unrestricted access to food and water.\u003c/p\u003e\u003cp\u003eThe mice were randomly assigned to shPSG11 and shCtrl groups (n\u0026thinsp;=\u0026thinsp;6 per group) and injected with 0.2 mL of lentivirus-transfected A2780 cells. Tumor volumes, calculated as π/6 \u0026times; length \u0026times; width\u003csup\u003e2\u003c/sup\u003e, were monitored for 28 days. Tumors were excised and weighed on the final day.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e2.12 Statistical analysis\u003c/h2\u003e\u003cp\u003eExperiments were all repeated three times, and data are presented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. Statistical tests included the Student\u0026rsquo;s t-test, Kaplan-Meier Survival Cures, Multivariate Cox Regression Analysis and one-way ANOVA. The association of PSG11 expression with clinical parameters was analyzed using Chi-square tests. SPSS and GraphPad Prism 8.0 were used for data analysis.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 PSG11 is high expressed and linked with prognosis in ovarian cancer\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo identify prognostic biomarkers in epithelial ovarian cancer (EOC), we analyzed the GEO dataset GSE26712, which includes 185 EOC and 10 normal ovarian samples. Differential expression analysis (Padj \u0026lt; 0.05, log₂FC \u0026gt; 0) revealed 4,951 upregulated and 3,023 downregulated genes. Survival analysis using TCGA data via cBioPortal identified two high-expression genes (PSG11 and QKI) and five low-expression genes (C1orf115, C7orf49, CD38, LRRC4, and NPEPL1) significantly associated with poor overall and progression-free survival (HR \u0026gt; 1.5 or \u0026lt; 0.67, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01). Intersection analysis of upregulated differentially expressed genes (DEGs) from GSE26712 and high-risk gene signatures from the TCGA cohort identified two overlapping genes, with PSG11 selected for further investigation based on its superior differential overall survival hazard ratio.\u003c/p\u003e\n\u003cp\u003eSubsequent validation in the GSE26712 dataset confirmed significantly elevated PSG11 expression levels in EOC samples, and its expression correlated strongly with poor prognosis (Figure 1A). Kaplan-Meier survival analysis in the TCGA cohort further supported the prognostic value of PSG11 (Figure 1B).\u003c/p\u003e\n\u003cp\u003eTo experimentally validate these bioinformatic findings, we performed IHC staining on a separate cohort comprising 127 primary EOC tissues and 32 matched para-cancerous tissues. As shown in Figure 1C and summarized in Table 1, PSG11 protein was markedly overexpressed in EOC tissues compared to adjacent non-tumorous tissues (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). High PSG11 expression was significantly correlated with advanced FIGO stage (P \u0026lt; 0.001), presence of distant metastasis (P = 0.004), larger tumor size (P = 0.017), and lymph node involvement (P = 0.019) (Table 2). Furthermore, survival analysis in this validation cohort reinforced the prognostic significance of PSG11 overexpression (Figure 1D).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Expression and effect of PSG11 in EOC cells\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePSG11 mRNA expression was significantly upregulated in EOC cell lines (A2780, CAOV3, OVCAR3) versus the normal IOSE80 cell line (Fig.2A). PSG11 protein expression was markedly higher in EOC cell lines than in IOSE80 (Fig.2B). A2780 and CAOV3 displayed the highest PSG11 mRNA and protein expression among the EOC cell lines, exceeding levels in OVCAR3. A2780 and CAOV3 were selected for further experiments, as the data suggest PSG11\u0026rsquo;s involvement in EOC progression.\u003c/p\u003e\n\u003cp\u003ePSG11 expression was stably silenced in A2780 cells using a lentiviral system to investigate its role. PSG11 protein levels were markedly lower in cells treated with shPSG11-1, shPSG11-2, and shPSG11-3 than in the shCtrl group. shPSG11-2 and shPSG11-3, showing the strongest knockdown, were used in A2780 and CAOV3 experiments (Fig.2C-D).\u003c/p\u003e\n\u003cp\u003eThe functional impact of PSG11 knockdown was then evaluated in A2780 and CAOV3 cells (Fig.2E). After five days, shPSG11 cells showed significantly reduced viability compared to shCtrl cells\u0026nbsp;(\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), indicating PSG11 knockdown inhibits EOC proliferation (Fig.3A). Colony formation assays confirmed this, with A2780 and CAOV3 cells forming significantly fewer colonies after PSG11 knockdown (Fig.3B). Flow cytometry revealed that PSG11 knockdown significantly increased apoptosis in A2780 and CAOV3 cells compared to controls (Fig.3C). Transwell and wound-healing assays revealed significantly lower migration rates in A2780 and CAOV3 cells with PSG11 knockdown compared to controls. PSG11 knockdown cells showed significantly slower migration 24 hours after the scratch in the wound-healing assay compared to controls (Fig. 3D and Fig. 3E). PSG11 knockdown reduces viability, proliferation, and migration and triggers apoptosis in EOC cells in vitro. These findings suggest PSG11 may regulate tumor cell behavior in EOC.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 PSG11\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eactivates hedgehog\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;pathway to\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eregulate autophagy in\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;EOC progression\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe analyzed TCGA ovarian cancer data using\u0026nbsp;Gene Set Enrichment Analysis\u0026nbsp;(GSEA) to examine PSG11\u0026apos;s involvement in EOC progression. The Hh signaling pathway was significantly linked to PSG11 expression in the\u0026nbsp;analysis. Among\u0026nbsp;the top 10 gene sets\u0026nbsp;identified\u0026nbsp;in the PID database, the Hh signaling pathway\u0026nbsp;emerged as a prominent candidate, with a normalized enrichment score (NES) of\u0026nbsp;1.5359\u0026nbsp;(\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). High PSG11 expression appears to activate the Hh pathway, potentially facilitating ovarian cancer progression (Fig.4A).\u003c/p\u003e\n\u003cp\u003eThe Hh pathway, regulated by Glioma-associated oncogene homolog 1\u0026nbsp;(GLI1) and Glioma-associated oncogene homolog 2\u0026nbsp;(GLI2), is vital for\u0026nbsp;embryonic development and tissue repair\u0026nbsp;[12]. The expression of GLI1 and GLI2 proteins in EOC cells was analyzed to explore PSG11\u0026apos;s role in the Hh signaling pathway. Knocking down PSG11 significantly reduced GLI1 and GLI2 levels (Fig.4B), confirming its key role in Hh pathway activation as indicated by GSEA.\u003c/p\u003e\n\u003cp\u003eTo advance the exploration of the functional relationship between PSG11 and the Hh signaling pathway, SAG, a potent Smoothened (Smo) receptor agonist, was utilized to activate the pathway [13]. Four experimental groups were established: PSG11 knockdown control (shCtrl), PSG11 knockdown (shPSG11), PSG11 knockdown control with SAG treatment (shCtrl + SAG), and PSG11 knockdown with SAG treatment (shPSG11 + SAG).\u003c/p\u003e\n\u003cp\u003eSAG activation of the Hh pathway significantly boosted EOC cells viability, as shown by CCK8 assays 24 hours post-inoculation (Fig.5A). Moreover, colony formation, Transwell, and wound-healing assays revealed that Hh pathway activation restored the proliferative and migratory capacities of EOC cells, even in the presence of PSG11 knockdown. The shPSG11 + SAG group showed significantly lower apoptosis rates than the shPSG11 group, supporting the Hh pathway\u0026rsquo;s role in mitigating PSG11 knockdown effects (Fig.5B-E).\u003c/p\u003e\n\u003cp\u003eThe Western blot(WB) analysis was used to evaluate if PSG11 regulates autophagy via the Hh signaling pathway. PSG11 knockdown was found to suppress the Hh pathway and significantly enhanced LC3 levels to promote autophagy in EOC cells(Fig.4C). PSG11 appears to drive EOC progression by activating the Hh pathway to regulate autophagy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 PSG11 inhibits tumor growth of EOC In vivo\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePSG11\u0026apos;s impact on tumor growth was assessed in vivo with a mouse xenograft model. Mice were subcutaneously injected with A2780 cells transfected with shCtrl or shPSG11, and tumor growth was tracked over time. Tumor volumes measured from day 8 post-inoculation showed significantly slower growth in the shPSG11 group versus the shCtrl group. Tumor volume and weight were significantly reduced in the shPSG11 group versus the shCtrl group by day 30 (Fig. 6A).\u003c/p\u003e\n\u003cp\u003eThe Immunohistochemistry\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eanalysis of tumor tissues provided additional insights into the molecular effects of PSG11 knockdown. Ki67, a proliferation marker, was significantly lower in the shPSG11 group than in the shCtrl group.GLI1, and GLI2 expression was significantly lower in the shPSG11 group,\u0026nbsp;LC3A/B was significantly higher in the\u0026nbsp;shPSG11 group than in the shCtrl group,consistent with in vitro data (Fig.\u0026nbsp;6B).\u003c/p\u003e\n\u003cp\u003eThe PSG11 promotes EOC tumor growth, likely via Hh pathway activation,and regulate autophagy while its knockdown inhibits tumor progression in vivo, making it a potential therapeutic target.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe EOC ranks fifth in cancer-related deaths among women, reflecting its major public health burden. The first seven-year survival data on PARP inhibitors marks a key breakthrough in treating certain ovarian cancer patients [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. While progress has been made, maintaining platinum sensitivity and extending progression-free survival with PARP inhibitors remains challenging in recurrent ovarian cancer [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. This signals an urgent need for new treatment options. Further research is vital to uncover the ovarian cancer progression\u0026rsquo;s molecular basis and to explore precise biomarkers. This study demonstrates that PSG11 downregulation inhibits tumor growth, emphasizing its viability as a therapeutic target for EOC.\u003c/p\u003e\u003cp\u003eCarcinoembryonic antigen cell adhesion molecule (CEACAM) gene families and PSG are members of the immunoglobulin superfamily [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. CEACAMs, including CEA, are now better understood in cancer and are widely used as tumor markers in clinical practice [17\u0026ndash;19]. These markers have greatly facilitated the diagnosis and management of malignant tumors. As homologous derivatives of the CEACAM family, the PSG family is hypothesized to perform similar functions. PSG7 plays a pivotal role in papillary thyroid cancer progression [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e20\u003c/span\u003e], with evidence linking PSG family members to various cancers [\u003cspan additionalcitationids=\"CR22 CR23\" citationid=\"CR20\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eBioinformatics analyses reveal, compared to normal tissues, that PSG11 exhibits higher expression levels in ovarian cancer tissues. Nevertheless, this observation had not been experimentally validated [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Using GEO and TCGA datasets, we identified PSG11 as an abnormally expressed gene with poor prognostic relevance in EOC through comparative analysis of gene expression profiles. Consistent with these bioinformatics findings, we confirmed for the first time that PSG11 expression is elevated in EOC cell lines using WB and qPCR analyses. We found that PSG11 downregulation inhibits key processes such as migration, invasion, growth, and proliferation in EOC cells, confirming its role in EOC progression.Although in vitro cell lines and in vivo mouse models provide valuable insights, they may not fully replicate the complexity of human EOC,the next step we will explore PSG11 inhibitor or Hh pathway modulators as potential treatments,and conduct clinical studies with larger and more divers patient cohorts to validate PSG11 as a therapeutic target.\u003c/p\u003e\u003cp\u003eThe Hh signaling pathway regulates mammalian growth and tissue stability [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e26\u003c/span\u003e], with its oncogenic role confirmed in cancers like papillary thyroid carcinoma [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e27\u003c/span\u003e] and colorectal cancer [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. To further investigate the mechanisms underlying PSG11\u0026rsquo;s involvement in EOC, we identified its association with the Hh signaling pathway through the PID database. Elevated PSG11 expression was found to correlate with Hh pathway activation.\u003c/p\u003e\u003cp\u003eThe Hh pathway is crucial in EOC, with Zhu et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e29\u003c/span\u003e] showing that TSPAN8 activates ovarian cancer stem cells through this mechanism. Resveratrol counters LPA-driven migration and platinum resistance in ovarian cancer cells by restoring Hh-mediated autophagy [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Hu et al. [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e31\u003c/span\u003e] showed that gut microbiota dysbiosis drives EOC progression through Hh signaling. We were the first to identify PSG11 as a driver of EOC progression through the Hh signaling pathway in vitro,while further research is needed to map out the complete signaling cascade.\u003c/p\u003e\u003cp\u003eWhat\u0026rsquo;s more,PSG11 downregulation in vivo inhibited tumor growth in a mouse xenograft model. PSG11 knockdown was found to boost Hh-mediated autophagy, which may inhibit tumor progression. This aligns with previous findings that autophagy can suppress or promote tumors, depending on the biological context[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn conclusion, our study confirms PSG11\u0026rsquo;s key role in EOC progression. By activating the Hh signaling pathway, PSG11 may regulate autophagy to promote tumor growth and progression. The results suggest PSG11 is a promising new target for EOC therapy, whether PSG11 contributes to chemotherapy resistance in EOC is needed. Future work should examine the clinical impact of targeting PSG11 to improve ovarian cancer treatments.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding Statement\u003c/h2\u003e\u003cp\u003eThis study was supported by Hebei Natural Science Foundation (No.H2020206223,H2024406004)\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eSuwei Lan and Zhengmao Zhang designed the conceptualization,Qian Li collected data,Qing Li formaled analysis, Suwei Lan,Zhengmao Zhang,Qian Li and Xingcha Wang provided the fundings,Xingcha Wang investigated the manuscript,Suwei Lan implemented the experiment,wrote the original draft,Zhengmao Zhang editored and reviewed the manuscript,All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData is provided within the manuscript or supplementary information files\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWang L, Wang X, Zhu X, et al. Drug resistance in ovarian cancer: from mechanism to clinical trial. Mol Cancer. 2024 Mar 28;23(1):66. \u003c/li\u003e\n\u003cli\u003eZheng Rongshou, Chen Ru, Han Bingfeng, et al. Analysis of the prevalence of malignant tumors in China in 2022 [J]. Chinese Journal of Oncology, 2024,46 (3): 221-231.\u003c/li\u003e\n\u003cli\u003eZhou GQ, Baranov V, Zimmermann W,et al. Highly specific monoclonal antibody demonstrates that pregnancy-specific glycoprotein (PSG) is limited to syncytiotrophoblast in human early and term placenta. Placenta. 1997 Sep;18(7):491-501. \u003c/li\u003e\n\u003cli\u003eZhao L, Triche EW, Walsh KM, et al. Genome-wide association study identifies a maternal copy-number deletion in PSG11 enriched among preeclampsia patients. BMC Pregnancy Childbirth. 2012 Jun 29;12:61.\u003c/li\u003e\n\u003cli\u003eJeong DS, Kim MH, Lee JY. Depletion of CTCF disrupts PSG gene expression in the human trophoblast cell line Swan 71. FEBS Open Bio. 2021 Mar;11(3):804-812. \u003c/li\u003e\n\u003cli\u003eLi Z, Shi C, Zheng J, et al. Fusobacterium nucleatum predicts a high risk of metastasis for esophageal squamous cell carcinoma. BMC Microbiol. 2021 Oct 30;21(1):301. \u003c/li\u003e\n\u003cli\u003eXiong Y, Feng Y, Zhao J, et al. TFAP2A potentiates lung adenocarcinoma metastasis by a novel miR-16 family/TFAP2A/PSG9/TGF-\u0026beta; signaling pathway. Cell Death Dis. 2021 Apr 6;12(4):352.\u003c/li\u003e\n\u003cli\u003eYang L, Hu S, Tan J, et al. Pregnancy-specific glycoprotein 9 (PSG9), a driver for colorectal cancer, enhances angiogenesis via activation of SMAD4. Oncotarget. 2016 Sep 20;7(38):61562-61574.\u003c/li\u003e\n\u003cli\u003eRong W, Yang L, Yin L, Gao Y, Xiao T, Cheng S. PSG9 promotes angiogenesis by stimulating VEGFA production and is associated with poor prognosis in hepatocellular carcinoma. Sci China Life Sci. 2017 May;60(5):528-535.\u003c/li\u003e\n\u003cli\u003eLiu YY, Zhang S, Yu TJ, et al. Pregnancy-specific glycoprotein 9 acts as both a transcriptional target and a regulator of the canonical TGF-\u0026beta;/Smad signaling to drive breast cancer progression. Clin Transl Med. 2020 Dec;10(8):e245.\u003c/li\u003e\n\u003cli\u003eIshikawa T, Ogawa T, Nakanome A, et al. Whole exome sequencing and establishment of an organoid culture of the carcinoma showing thymus-like differentiation (CASTLE) of the parotid gland. Virchows Arch. 2021 Jun;478(6):1149-1159.\u003c/li\u003e\n\u003cli\u003eIngham PW, Nakano Y, Seger C. Mechanisms and functions of Hedgehog signalling across the metazoa. Nat Rev Genet. 2011 Jun;12(6):393-406. \u003c/li\u003e\n\u003cli\u003eChen JK, Taipale J, Young KE, Maiti T, Beachy PA. Small molecule modulation of Smoothened activity. Proc Natl Acad Sci U S A. 2002 Oct 29;99(22):14071-6.\u003c/li\u003e\n\u003cli\u003eKonstantinopoulos PA, Norquist B, Lacchetti C, et al. Germline and Somatic Tumor Testing in Epithelial Ovarian Cancer: ASCO Guideline. J Clin Oncol. 2020 Apr 10;38(11):1222-1245.\u003c/li\u003e\n\u003cli\u003ePujade-Lauraine E, Selle F, Scambia G, et al. Maintenance olaparib rechallenge in patients with platinum-sensitive relapsed ovarian cancer previously treated with a PARP inhibitor (OReO/ENGOT-ov38): a phase IIIb trial. Ann Oncol. 2023 Dec;34(12):1152-1164.\u003c/li\u003e\n\u003cli\u003eKammerer R, Zimmermann W. Coevolution of activating and inhibitory receptors within mammalian carcinoembryonic antigen families. BMC Biol. 2010 Feb 4;8:12. \u003c/li\u003e\n\u003cli\u003eWautier JL, Wautier MP. Old and New Blood Markers in Human Colorectal Cancer. Int J Mol Sci. 2022 Oct 26;23(21):12968.\u003c/li\u003e\n\u003cli\u003eTsang KY, Fantini M, Mavroukakis SA, Zaki A, Annunziata CM, Arlen PM. Development and Characterization of an Anti-Cancer Monoclonal Antibody for Treatment of Human Carcinomas. Cancers (Basel). 2022 Jun 21;14(13):3037.\u003c/li\u003e\n\u003cli\u003eSeckinger A, Majocchi S, Moine V, et al. Development and characterization of NILK-2301, a novel CEACAM5xCD3 \u0026kappa;\u0026lambda; bispecific antibody for immunotherapy of CEACAM5-expressing cancers. J Hematol Oncol. 2023 Dec 12;16(1):117.\u003c/li\u003e\n\u003cli\u003eWang H, Shen L, Li Y, Lv J. Integrated characterisation of cancer genes identifies key molecular biomarkers in stomach adenocarcinoma. J Clin Pathol. 2020 Sep;73(9):579-586.\u003c/li\u003e\n\u003cli\u003eSu X, Zhang J, Yang W, et al. Identification of the Prognosis-Related lncRNAs and Genes in Gastric Cancer. Front Genet. 2020 Feb 11;11:27.\u003c/li\u003e\n\u003cli\u003eDan K, Lee JE, Han D, et al. Proteomic identification of biomarkers in maternal plasma that predict the outcome of rescue cerclage for cervical insufficiency. PLoS One. 2021 Apr 15;16(4):e0250031.\u003c/li\u003e\n\u003cli\u003eHouston A, Williams JM, Rovis TL, et al. Pregnancy-specific glycoprotein expression in normal gastrointestinal tract and in tumors detected with novel monoclonal antibodies. MAbs. 2016;8(3):491-500.\u003c/li\u003e\n\u003cli\u003eRodr\u0026iacute;guez-Esquivel M, Romero-Morelos P, Taniguchi-Ponciano K, et al. Expression of Pregnancy Specific \u0026beta;-1 Glycoprotein 1 in Cervical Cancer Cells. Arch Med Res. 2020 Aug;51(6):504-514. \u003c/li\u003e\n\u003cli\u003eZhang Q, Burdette JE, Wang JP. Integrative network analysis of TCGA data for ovarian cancer. BMC Syst Biol. 2014 Dec 31;8:1338.\u003c/li\u003e\n\u003cli\u003eBriscoe J, Th\u0026eacute;rond PP. The mechanisms of Hedgehog signalling and its roles in development and disease. Nat Rev Mol Cell Biol. 2013 Jul;14(7):416-29.\u003c/li\u003e\n\u003cli\u003eXu Y, Ma N, Wei P, Zeng Z, Meng J. Expression of hydrogen sulfide synthases and Hh signaling pathway components correlate with the clinicopathological characteristics of papillary thyroid cancer patients. Int J Clin Exp Pathol. 2018 Mar 1;11(3):1818-1824. \u003c/li\u003e\n\u003cli\u003eSun Q, Yang H, Liu M, et al. Berberine suppresses colorectal cancer by regulation of Hedgehog signaling pathway activity and gut microbiota. Phytomedicine. 2022 Aug;103:154227. \u003c/li\u003e\n\u003cli\u003eZhu R, Gires O, Zhu L, et al. TSPAN8 promotes cancer cell stemness via activation of sonic Hedgehog signaling. Nat Commun. 2019 Jun 28;10(1):2863.\u003c/li\u003e\n\u003cli\u003eFerraresi A, Esposito A, Girone C, et al. Resveratrol Contrasts LPA-Induced Ovarian Cancer Cell Migration and Platinum Resistance by Rescuing Hedgehog-Mediated Autophagy. Cells. 2021 Nov 17;10(11):3213. \u003c/li\u003e\n\u003cli\u003eHu X, Xu X, Zeng X, et al. Gut microbiota dysbiosis promotes the development of epithelial ovarian cancer via regulating Hedgehog signaling pathway. Gut Microbes. 2023 Jan-Dec;15(1):2221093. \u003c/li\u003e\n\u003cli\u003eNiu X, You Q, Hou K, et al.Autophagy in cancer development, immune evasion, and drug resistance. Drug Resist Updat. 2025 Jan;78:101170. \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Differential expression of PSG11 in\u0026nbsp;EOC\u0026nbsp;and\u0026nbsp;para-cancerous\u0026nbsp;tissues.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003ePSG11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 59px;\"\u003e\n \u003cp\u003eTumor tissue \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Para-cancerous\u0026nbsp;tissue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003eexpression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eCases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003eProportion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eCases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003eProportion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e52.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e87.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e47.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e12.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2. Correlation between clinicopathological features and PSG11 expression in EOC patients.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eFeatures\u003c/p\u003e\n \u003cp\u003eAll patients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eNo. of patients\u0026nbsp;(127)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 27px;\"\u003e\n \u003cp\u003ePSG11\u0026nbsp;expression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eLow (67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eHigh (60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003cp\u003e＜53\u003c/p\u003e\n \u003cp\u003e\u0026ge;53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e0.618\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eStage\u003c/p\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003cp\u003eIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eTumor size\u003c/p\u003e\n \u003cp\u003e＜13cm\u003c/p\u003e\n \u003cp\u003e\u0026ge;13cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eT Infiltrate\u003c/p\u003e\n \u003cp\u003eT1\u003c/p\u003e\n \u003cp\u003eT2\u003c/p\u003e\n \u003cp\u003eT3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eLymphatic metastasis\u0026nbsp;(N)\u003c/p\u003e\n \u003cp\u003eN0\u003c/p\u003e\n \u003cp\u003eN1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eDistant Metastasis (M)\u003c/p\u003e\n \u003cp\u003eM0\u003c/p\u003e\n \u003cp\u003eM1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eHOvaC1541Su01\u003c/p\u003e\n \u003cp\u003eEGFR\u003c/p\u003e\n \u003cp\u003e\u0026le;0.5\u003c/p\u003e\n \u003cp\u003e\u0026gt;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e0.252\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eHOvaC1541Su01\u003c/p\u003e\n \u003cp\u003ePDL1\u003c/p\u003e\n \u003cp\u003e＜0.5\u003c/p\u003e\n \u003cp\u003e\u0026ge;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e0.434\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"PSG11, Epithelial ovarian cancer, Hedgehog signaling, Autophagy","lastPublishedDoi":"10.21203/rs.3.rs-7239376/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7239376/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Epithelial ovarian cancer (EOC) is a highly lethal gynecologic malignancy due to late diagnosis, frequent recurrence, and a lack of effective early biomarkers. This study investigates the role of pregnancy-specific glycoprotein 11 (PSG11) in EOC progression and its potential as a therapeutic target.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e PSG11 expression and its prognostic significance in epithelial ovarian cancer were analyzed using The Cancer Genome Atlas data and Gene Expression Omnibus, validated by immunohistochemistry. PSG11 expression in epithelial ovarian cancer cell lines was confirmed via Quantitative Polymerase Chain Reaction and Western blot. PSG11 knockdown was studied using flow cytometry,celigo counting,cloning experiment, scratch assay,transwell assays and tumor models in nude mice, with bioinformatics analyses providing insights into the mechanisms involved.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e PSG11 was significantly overexpressed in EOC tissues compared to para-cancerous tissues (47.2% vs. 12.5%, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). A significant correlation was observed between high PSG11 expression and FIGO stage, distant metastasis, tumor size, and lymph node involvement (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001, \u003cem\u003eP\u003c/em\u003e = 0.004, \u003cem\u003eP\u003c/em\u003e = 0.017, and \u003cem\u003eP\u003c/em\u003e = 0.019, respectively). Functional studies demonstrated that PSG11 knockdown reduced cell viability by approximately 40% (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), colony formation by approximately 50%, and migration rates by approximately 60% in vitro, while promoting apoptosis. In vivo, PSG11 knockdown suppressed tumor growth, reducing tumor volume by approximately 55% and tumor weight by approximately 50% by day 30. Mechanistically, PSG11 activated the Hedgehog signaling pathway, promoting epithelial ovarian cancer progression by regulating autophagy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e PSG11 drives epithelial ovarian cancer progression by activating Hedgehog signaling to regulate autophagy. These findings identify PSG11 as a potential therapeutic target in EOC.\u003c/p\u003e","manuscriptTitle":"PSG11 Overexpression Promotes Epithelial Ovarian Cancer Progression via Hedgehog-Mediated Autophagy Regulation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-05 10:10:41","doi":"10.21203/rs.3.rs-7239376/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"883f96a3-eb53-467b-bd7d-164af4cfcc7e","owner":[],"postedDate":"August 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-18T15:23:32+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-05 10:10:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7239376","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7239376","identity":"rs-7239376","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}