PLCD1 Expression for Early Detection and Prognosis in High-Grade Serous Ovarian Cancer

PLCD1 Expression for Early Detection and Prognosis in High-Grade Serous Ovarian Cancer | 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 PLCD1 Expression for Early Detection and Prognosis in High-Grade Serous Ovarian Cancer Jue Young Kim, Ha-Yeon Shin, Eun-Suk Kang, Jae-Hoon Kim This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5832774/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 Purpose: High-grade serous ovarian cancer (HGSOC) is a prevalent and aggressive subtype with rapid progression and poor prognosis, often diagnosed at an advanced stage despite treatment advances. Current diagnostic markers, such as CA-125, have limited early detection capability and poorly integrate with treatment decisions. This study explored PLCD1 as potential biomarkers for HGSOC’s early detection. Methods: Immunohistochemistry (IHC) staining was performed to detect PLCD1 expression in tissue microarrays (TMA). The impact of PLCD1 expression on survival outcomes was evaluated via Kaplan-Meier method. PLCD1 expression in HGSOC cells was confirmed through Western blotting. PLCD1 knockdown and overexpression cell lines were established to investigate the functional role of PLCD1 in HGSOC. Colony formation, invasion, and 3D tumor spheroid assay were performed to evaluate cancer cells behavior. An OVCAR3-derived xenograft model was used to determine whether PLCD1 expression influence tumor growth. Results: IHC staining revealed high cytoplasmic expression of PLCD1 in HGSOC tissues compared to normal or borderline tissues, with low PLCD1 expression correlating with worse overall survival and disease-free survival in 101 patients with HGSOC. In vitro studies demonstrated that PLCD1 knockdown increased OVCA429 cells proliferation, whereas PLCD1 overexpression in OVCAR3 cells reduced colony formation. In the OVCAR3-derived xenograft model, PLCD1 overexpression significantly reduced tumor growth compared with that in the control group. Conclusion: The TMA revealed an association between PLCD1 expression and patient prognosis. Furthermore, tumor reduction was observed following PLCD1 overexpression in a xenograft model.These findings establish PLCD1 as a promising prognostic biomarker and therapeutic target for HGSOC. HGSOC PLCD1 prognosis diagnosis TMA xenograft Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction High-grade serous ovarian cancer (HGSOC) is the most common and aggressive subtype of ovarian cancer, and is characterized by rapid progression and poor prognosis [1]. It typically originates from the fallopian tubes or surface epithelium of the ovary and is known for its tendency to metastasize widely within the peritoneal cavity [2]. Despite advances in treatment, including surgical debulking and chemotherapy, most patients experience recurrence, often with resistance to standard therapies [3]. The molecular complexity of HGSOC, including frequent mutations in TP53 and alterations in the BRCA1/2 genes, contributes to its challenging management and poor survival rates [4]. Studies on the mechanisms underlying HGSOC is crucial for developing effective targeted therapies and improving patient outcomes. Additionally, early detection remains a considerable challenge because the disease is often diagnosed at an advanced stage. Therefore, understanding the unique characteristics of HGSOC is essential to advance diagnostic and therapeutic strategies. PLCD1 encodes phospholipase C delta 1, an enzyme involved in cellular signaling through the hydrolysis of phosphatidylinositol 4,5-bisphosphate [5]. In cancer research, PLCD1 has been implicated in various functions, including the modulation of cell proliferation, migration, and apoptosis [6, 7]. Aberrant expression of PLCD1 is associated with cancer progression and metastasis in several cancer types, such as breast and prostate cancers. Recent studies have revealed that PLCD1 exhibits notable antitumor effects, including the inhibition of cell proliferation in breast cancer, colorectal cancer, and esophageal squamous cell carcinoma [6, 8, 9]. Additionally, PLCD1 is thought to influence the sensitivity of cancer cells to chemotherapy and radiation. Functional alterations in cancer highlight their potential as biomarkers and therapeutic targets for personalized cancer treatment. However, its effect on the pathogenesis and biological functions of HGSOC remains unclear. The expression level of PLCD1 in tumor microarrays (TMA) have been investigated in this study. Furthermore, the biological functions of PLCD1 in HGSOC cells were studied in vivo and in vitro . Our results suggest that PLCD1 is a functional tumor suppressor and a potential biomarker for HGSOC. 2. Materials and Methods 2.1 TMA and patient information The TMA was obtained from the Korea Gynecologic Cancer Bank of Gangnam Severance Hospital, Yonsei University College of Medicine (No. HTB-P2021-5). All procedures were approved by the Institutional Review Board of Samsung Medical Center in advance (date of approval: 12th Dec 2019, approval number: SMC 2019-12-013). The TMA consisted of 68 normal, 44 borderline, and 101 high-grade serous ovarian cancer tissues. Clinical findings, treatment, and follow-up information were obtained from patient records. The demographic and clinical characteristics of the patients are shown in Table 1. Table 1. Demographic and clinical characteristics of patients PLCD1_Hs_Cy Variables No. % Mean IHC Score (95% CI) P value All 213 100 Histology <0.0001 Normal 68 31.9 38.63 (30.48 - 46.78) Borderline 44 20.7 55.11 (41.05 - 69.18) HGSOC 101 47.4 73.99 (64.50 - 83.49) Age 0.877 35U/ml) 89 88.1 75.84 (65.62 - 86.06) N.A 2 2.0 Stage 0.183 I/II 17 16.8 88.2 (66.49 - 109.91) III/IV 84 83.2 71.1 (60.50 - 81.74) Grade 0.464 Moderate 47 46.5 77.8 (62.63 - 92.92) Poor 54 53.5 70.7 (58.39 - 83.02) Chemo sensitivity 0.870 Sensitive 78 77.2 74.2 (63.30 - 85.00) Resistant 20 19.8 72.1 (47.86 - 96.42) 2.2 Immunohistochemistry (IHC) staining Paraffin-embedded sections were incubated at 65°C for 20 min, deparaffinized in xylene for 15 min, and then transferred sequentially to 100% ethanol, 90% ethanol, and 70% ethanol for 5 min. Thereafter, the sections were rinsed with deionized water. Sections were pretreated for heat-mediated antigen retrieval with 10 mM citrate buffer (pH 6.0) for 10 min in a microwave. The sections were immersed in methanol containing with 3% hydrogen peroxide for 10 min and incubated with primary antibodies for 120 min. The following primary antibody was used: PLCD1 (#ab154610, Abcam, Cambridge, UK). The secondary EnVision™ Rabbit/Mouse reagent (#K5007, Agilent Technologies, Santa Clara, CA, USA) was then applied for 60 min. Sections were visualized using 3,3-diaminobenzidine tetrachloride (DAB; #K3468, Agilent Technologies, Santa Clara, CA, USA) and counterstained with hematoxylin (#S3309, Agilent Technologies, Santa Clara, CA, USA) for 5 min. All procedures were performed at a room temperature of 25℃. PLCD1 protein expression was assessed by combining relative staining intensity and proportion of positive cells. The intensity of staining on the slides was scored as 0 (negative), 1 (weak), 2 (moderate), or 3 (strong). The proportion of staining was scored 0-100 percent. The final score was calculated by multiplying each score. 2.3 Cell culture YDOV-139, YDOV-157, and YDOV-161, which were established and characterized in our laboratory, were cultured as described previously [10-12]. OVCA429, OVCA433, and DOV13 were maintained in DMEM medium (#10-013-CV, Corning, NY, USA) supplemented with 10% fetal bovine serum (FBS; #12483-020, Gibco, Waltham, MA, USA) and 1% penicillin/streptomycin (#15140, Gibco, Waltham, MA, USA). OVCAR3 and SKOV3 were purchased from American Type Culture Collection (ATCC, Manassas, VA, USA). All purchased cell lines were maintained as recommended. Mycoplasma contamination test against cell lines was checked by a e-Myco TM plus Mycoplasma PCR detection kit (#25237, iNtRON Biotechnology, Seongnam, Korea). 2.4 Protein extraction and western blotting Cell lysates were obtained using a cell lysis buffer (#9803, Cell Signaling Technology, Danvers, MA, USA) supplemented with PMSF (#8553, Cell Signaling Technology, Danvers, MA, USA). Protein concentrations were determined by BCA assay (Sigma-Aldrich, St. Louis, MO, USA). The proteins were separated by SDS-PAGE and transferred onto 0.2 μm nitrocellulose membranes (Pall Corporation, Washington, NY, USA). Protein bands were visualized using western blotting luminol reagent (Santa Cruz Biotechnology, Inc., CA, USA) after incubation with an HRP-conjugated secondary antibody. The primary antibodies used were anti-PLCD1 (ab154610), anti-α-actinin (sc-17829), and anti-β-actin (ab3854). 2.5 siRNA-mediated knockdown OVCA429 cells were seeded one day prior to siRNA transfection in 6-well plate and were allowed to grow up to 50% confluency. PLCD1 (#5333-3) and control (#SN-1002) knockdown were conducted using predesigned siRNA sequences purchased from Bioneer. On the day of siRNA transfection, cells were transfected with siRNA in Opti-MEM (#31985-070, Gibco BRL, Waltham, MA, USA), using Lipofectamine™ RNAiMAX Transfection Reagent (#13778150, Thermo Scientific, Waltham, MA, USA), as per the manufacturer’s instructions. Transfection efficiencies were analyzed 48 h post-transfection. 2.6 Crystal violet staining The cells were seeded in a 24-well plate and allowed to adhere overnight. Then, the cells were fixed in 10% acetic acid solution with 10% methanol, stained with 0.5% crystal violet (#C3886, Sigma-Aldrich, St. Louis, MO, USA) for 1 h, photographed, and extracted using 1% sodium dodecyl sulfate solution. The crystal violet extracted from the cells was measured by determining the absorbance at 595 nm using a VERSA Max™. 2.7 Cell invasion assay Cell invasion assays were performed in an invasion chamber (Neuro Probe 48-well Micro Chemotaxis Chamber, #AP48). The membranes (Neuro Probe, #PFB8) were coated with Matrigel (#354234, BD Biosciences, NY, USA) for 1 h. Cells (1 × 10 5 ) in serum-free medium were seeded into the upper chambers, and a medium containing 10% FBS was placed in the lower chambers. After incubation for 24 h, cells adhering to the upper surface of the membrane were removed. The invading cells attached to the lower surface were stained using a Differential Quik Stain Kit (#38721, Sysmex Corporation, Kobe, Hyogo, Japan). Images of the invading cells were captured using an Axio Imager. M2 (Carl Zeiss, magnification x 200). The invading cells were counted in three randomly selected fields. 2.8 Establishment of stable cell lines. The human PLCD1 lentiviral ORF cDNA expression plasmid with a c-GFP Spark tag (pLV-PLCD1-GFPSpark, #HG18554-ACGLN) and a Lentivirus Control Plasmid (pLV-C-GFPSpark #, # LVCV-35) were purchased from Sino Biological Inc. (Beijing, China). HEK293T cells (1 × 10 6 ) were co-transfected with 2 µg lentiviral vector, 2 µg the viral packaging plasmids composed of pCMV delta and pMDG, and lipofectamin 2000. The crude virus supernatant (total collected viral medium of 10 mL) was collected 48 and 72 h post-transfection. OVCAR3 cells seeded in a 24-well plate was infected with 500 µL of the collected crude viral medium per well, and the medium was changed with fresh ones after 24 h. Positively infected OVCAR3 cells were observed with GFP expression as a selection marker. Positively infected live cells were sorted based on GFP fluorescence by flow cytometry (BD FACSAria TM III). 2.9 3D tumor spheroid assay For 3D cultures, OVCAR3 stable cells (0.1 × 10 3 cells) were suspended in a PBS and Matrigel (#354234, BD Biosciences, NY, USA) mixture (1:1), which was dropped on the cover slide. After solidifying the mixture, the cover slides were moved to a culture dish, and added medium with 10% FBS. The culture medium was refreshed every two days for up to 9 d. Microscopic imaging of the spheroid cells was performed using a microscope (EVOS® FL Cell Imaging System, Life Technologies). Spheroid cells were stained and counted using 5 mg/mL 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium solution. 2.10 In vivo xenograft tumor model. All animal procedures were performed in accordance with a protocol approved by the Institutional Animal Care and Use Committee of Yonsei University (IACUC Approval No. 2024-0266, Seoul, Korea). First, six-week-old female BALB/c nude mice (OrientBio Inc., Seongnam, Korea) were anesthetized by injecting alfaxan (76 mg/kg) with xylazine (10 mg/kg). OVCAR3 stable cells (5 × 10 6 cells/inoculation) were suspended in PBS and Matrigel (#354234, BD Biosciences, NY, USA) mixture (1:1). Mice were subcutaneously injected with the mixture into the left and right flanks. Tumor dimensions were measured using digital calipers, and tumor volume was calculated using the following formula: [tumor volume (mm 3 ) = length × width 2 × 0.5]. Tumors were harvested 35 d after cell inoculation, final tumor volume and weight were measured and then fixed at 10 % formalin (Sigma-Aldrich, St. Louis, MO, USA). 2.11 Statistical analysis GraphPad Prism 10.0 (GraphPad Prism, San Diego, CA, USA) was used for the statistical analysis. Results are expressed as mean ± standard deviation (SD). Method to test distribution was used by Shapiro-Wilk normality test. Unpaired t-tests or Mann-Whitney U test were used to evaluate the differences between the two groups. Survival curve analysis was performed using the Kaplan–Meier method, and statistical significance was calculated using the log-rank test. Differences were considered significant at * P < 0.05 and **** P < 0.0001. A value of P < 0.05 was considered statistically significant. 3. Results 3.1 PLCD 1 expression was increased in HGSOCs by TMA tissue staining. We investigated PLCD1 expression levels in normal, borderline tumor, and HGSOC tissues of TMA by IHC staining. PLCD1 was highly expressed in the cytoplasm of epithelial cells, with significantly increased expression observed in HGSOC tissues compared to that in normal or borderline tissue (Fig. 1A). The patients clinicopathologic variables of TMA are shown in Table 1. PLCD1 expression was positively associated with histology ( P < 0.0001), but not with age, CA125 levels, stage, grade, or chemosensitivity. To investigate whether the expression of PLCD1 affects survival outcomes in 101 patients with HGSOC, the Kaplan-Meier method was used. The median expression levels of PLCD1 were divided into high and low expression group. Patients in the low PLCD1 expression group had significantly worse prognosis in overall survival (OS) and disease-free survival (DFS) than those in the high expression group (Fig. 1B; Log-rank test, P < 0.05). 3.2 HGSOC cell proliferation was regulated by PLCD1 knockdown/overexpression in vitro . PLCD1 expression in HGSOC cell line was confirmed by Western blotting (Fig. 2A). To investigate the functional role of PLCD1 in HGSOC, the PLCD1 knockdown/overexpression cell lines were established using HGSOC cell lines. A PLCD1 knockdown cell line was established based on the OVCA429 cell line (Fig. 2B). The colony formation assay demonstrated that colonies of siPLCD1 were significantly increased than that of the sicontrol group (Fig. 2C). However, no significant difference in cancer invasion ability between the two groups was observed (Fig. 2D). These results indicate that PLCD1 knockdown in HGSOC cells promoted cell proliferation in vitro . For the overexpression studies, OVCAR3 cells were transfected with either PLCD1 or an Empty lentivirus vector. A stable PLCD1 overexpression cell line was established based on the OVCAR3 cell line (Fig. 3A). Colony formation assays in 3D culture demonstrated that PLCD1 overexpression resulted in a reduction of colony number by over 50% compared with the empty vector cell lines (Fig. 3B). No significant difference was observed in cancer invasion ability between the two groups (Fig. 3C). Our results suggest that PLCD1 overexpression inhibits cell proliferation in vitro . 3.3 PLCD1 overexpression reduced tumor growth in the OVCAR3-derived xenograft model. To evaluate whether PLCD1 expression influenced tumor growth, we used an OVCAR3-derived xenograft model. OVCAR3 cells were transfected with either PLCD1 or an Empty lentivirus vector, and these cells were used to establish two groups: the PLCD1 group (N=11) and Empty group (N=4) via intraperitoneally injection. Starting 30 d after the initiation of the experiment, the tumor growth rate in the PLCD1 group was significantly reduced compared to that the Empty group (Fig. 4A, P < 0.05). Tumor size on day 35 of incubation is shown (Fig. 4B). This finding showed that tumor volume decreased according to PLCD1 overexpression. PLCD1 overexpression led to a reduction in final tumor weight, but this decrease was not statistically significant. 4. Discussion Phospholipase C (PLC), part of the phosphoinositide‐specific enzyme superfamily, is essential for various cellular processes, such as intracellular signaling pathways, including growth factor signaling, hormone release, membrane transport, and the regulation of the cytoskeleton [13]. Among the PLC family, PLCD1 has been determined as a novel tumor suppressor gene because of its inactivation through promoter methylation in various cancer, including breast cancer, chronic myeloid leukemia, esophageal squamous cell carcinoma, and gastric cancer [14-17]. However, its effect on the pathogenesis and biological functions of HGSOC remains unclear. Our results presented that PLCD1 was significantly upregulated in HGSOC tissues compared with normal or borderline tissues. This study revealed that PLCD1 expression is a potential marker of cancer detection in HGSOC. Given the previous studies, PLCD1 expression is associated with survival rate in some cancers; a low level of PLCD1 expression is associated with poor survival in renal cell carcinoma, chondrosarcoma, and colorectal cancer [6, 7, 9]. Consistent with these findings, our results indicated that patients with lower PLCD1 expression had worse OS and DFS. Therefore, our study suggests that PLCD1 expression plays a role as a predictive factor for prognosis in HGSOC. To corroborate our in vivo data, we conducted in vitro study using two HGSOC cell lines, OVCA429 and OVCAR3, and obtained corresponding result: knockdown of PLCD1 led to increased OVCA429 cell proliferation. In contrast, PLCD1 overexpression inhibited HGSOC cell proliferation in vitro and reduced tumor size in an in vivo mouse model. Our results demonstrated that PLCD1 expression is associated with cancer cell proliferation and tumor progression. Consistent with our findings, recent studies have shown that PLCD1 inhibits cancer cell proliferation via several mechanisms. PLCD1 is inactivated by promoter methylation and exerts its tumor-suppressive functions by inhibiting WNT/β‐catenin and EGFR‐FAK-ERK signaling pathway [5]. According to another study, DNA damage induced by PLCD1 overexpression leads to cell cycle arrest and apoptosis [7]. The observed anti-proliferative effect of PLCD1 could be linked to its role in intracellular signaling pathways, which is known to influence cell survival and growth. Our study suggests that PLCD1 may function as a tumor suppressor in HGSOC, indicating the need for further research to elucidate its underlying mechanisms. Taken together, these data provide a novel diagnostic and prognostic marker in HGSOC. Declarations Author contributions Eun-Suk Kang, Jae-Hoon Kim contributed to the study conception and design. Jue Young Kim performed in vitro experiment and analyze between TMA IHC and patient information. Ha-Yeon Shin performed in vitro and in vivo experiment. Jue Young Kim and Ha-Yeon Shin contributed to collecting of clinical samples and wrote the manuscript. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Data availability No datasets were generated or analysed during the current study. Competing interests The authors declare no competing interests. Consent for publication All authors agree to submit the article for publication. Funding This research was supported by the National Institute of Health (NIH) research project (project No. #2024ER051700). Ethics approval and consent to participate This study was approved by Institutional Review Board of Samsung Medical Center in advance (date of approval: 12th Dec 2019, approval number: SMC 2019-12-013). All animal procedures in this study were performed under a protocol approved by the Institutional Animal Care and Use Committee at Yonsei University (IACUC Approval No. 2024-0266, Seoul, Korea). TMA were obtained from the Korea Gynaecologic Cancer Bank (KGCB) of Gangnam Severance Hospital, Yonsei University College of Medicine (No. HTB-P2021-5). All patients involved in this article signed informed consent. Acknowledgements Not applicable References Y. Cen, Y. Fang, Y. Ren, S. Hong, W. Lu and J. Xu, Global characterization of extrachromosomal circular DNAs in advanced high grade serous ovarian cancer, Cell Death Dis 13 , 342 (2022). J. Kim, E.Y. Park, O. Kim, et al., Cell Origins of High-Grade Serous Ovarian Cancer, Cancers (Basel) 10 (2018). A. Andrikopoulou, C. Theofanakis, C. Markellos, et al., Optimal Time Interval between Neoadjuvant Platinum-Based Chemotherapy and Interval Debulking Surgery in High-Grade Serous Ovarian Cancer, Cancers (Basel) 15 (2023). U.A. Boyarskikh, L.F. Gulyaeva, A.M. Avdalyan, et al., Spectrum of TP53 Mutations in BRCA1/2 Associated High-Grade Serous Ovarian Cancer, Front Oncol 10 , 1103 (2020). J. Xie, J. Zhou, J. Xia, et al., Phospholipase C delta 1 inhibits WNT/beta-catenin and EGFR-FAK-ERK signaling and is disrupted by promoter CpG methylation in renal cell carcinoma, Clin Epigenetics 15 , 30 (2023). X. He, F. Meng, Z.J. Yu, et al., PLCD1 Suppressed Cellular Proliferation, Invasion, and Migration via Inhibition of Wnt/beta-Catenin Signaling Pathway in Esophageal Squamous Cell Carcinoma, Dig Dis Sci 66 , 442-451 (2021). J. Shen, C. Yu, Z. Wang, H. Mu and Z. Cai, PLCD1-Induced DNA Damage Inhibits the Tumor Growth via Downregulating CDKs in Chondrosarcoma, J Oncol 2022 , 4488640 (2022). M. Shimozawa, S. Anzai, R. Satow and K. Fukami, Phospholipase C delta1 negatively regulates autophagy in colorectal cancer cells, Biochem Biophys Res Commun 488 , 578-583 (2017). Q. Xiang, X. He, J. Mu, et al., The phosphoinositide hydrolase phospholipase C delta1 inhibits epithelial-mesenchymal transition and is silenced in colorectal cancer, J Cell Physiol 234 , 13906-13916 (2019). H. Cho, Y.S. Lee, J. Kim, J.Y. Chung and J.H. Kim, Overexpression of glucose transporter-1 (GLUT-1) predicts poor prognosis in epithelial ovarian cancer, Cancer Invest 31 , 607-615 (2013). H. Cho, B.J. Lim, E.S. Kang, J.S. Choi and J.H. Kim, Molecular characterization of a new ovarian cancer cell line, YDOV-151, established from mucinous cystadenocarcinoma, Tohoku J Exp Med 218 , 129-139 (2009). H. Cho, H.Y. Shin, S. Kim, et al., The role of S100A14 in epithelial ovarian tumors, Oncotarget 5 , 3482-3496 (2014). C.A. Bill and C.M. Vines, Phospholipase C, Adv Exp Med Biol 1131 , 215-242 (2020). L. Fu, Y.R. Qin, D. Xie, et al., Characterization of a novel tumor-suppressor gene PLC delta 1 at 3p22 in esophageal squamous cell carcinoma, Cancer Res 67 , 10720-10726 (2007). J.J. Song, Q. Liu, Y. Li, et al., Epigenetic inactivation of PLCD1 in chronic myeloid leukemia, Int J Mol Med 30 , 179-184 (2012). X.T. Hu, F.B. Zhang, Y.C. Fan, et al., Phospholipase C delta 1 is a novel 3p22.3 tumor suppressor involved in cytoskeleton organization, with its epigenetic silencing correlated with high-stage gastric cancer, Oncogene 28 , 2466-2475 (2009). T. Xiang, L. Li, Y. Fan, et al., PLCD1 is a functional tumor suppressor inducing G(2)/M arrest and frequently methylated in breast cancer, Cancer Biol Ther 10 , 520-527 (2010). 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-5832774","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":409550821,"identity":"8e600909-7afe-418b-97cd-ee3a7e4eb1fe","order_by":0,"name":"Jue Young Kim","email":"","orcid":"","institution":"Yonsei University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jue","middleName":"Young","lastName":"Kim","suffix":""},{"id":409550822,"identity":"01537536-6e8e-4ea1-a164-875a13b13c5e","order_by":1,"name":"Ha-Yeon Shin","email":"","orcid":"","institution":"Yonsei University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Ha-Yeon","middleName":"","lastName":"Shin","suffix":""},{"id":409550823,"identity":"e7e08c39-9f09-4f49-a51d-66f78a008a33","order_by":2,"name":"Eun-Suk Kang","email":"","orcid":"","institution":"Samsung Medical Center, Sungkyunkwan University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Eun-Suk","middleName":"","lastName":"Kang","suffix":""},{"id":409550824,"identity":"3a1fac49-9fbe-4e5e-816c-800a65b66fe9","order_by":3,"name":"Jae-Hoon Kim","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA00lEQVRIiWNgGAWjYBACxgYGNhBtwMbAfADEI0kLWwJxWoAAooWBgceAOC3M7YePPfhQcceYT+zMN2neHXUM/O0HCDisJy3dcMaZZ2Zs0rnbpHnPHGaQOJNAQEtDjpk0b9thG4iWNqANNwg4jLH//TeolpxnQEYdgzxBLTNy2EBagA4DM5gZDAhreWYmOePMYWM26TRjy7lth3kMCfnFsD/5mcSHisOG82cnP7zxtq1OTu74AQJaGhBsFgkgwUPAWQwM8khs5g8ElY+CUTAKRsGIBAC0FT/TtEm3JAAAAABJRU5ErkJggg==","orcid":"","institution":"Yonsei University College of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Jae-Hoon","middleName":"","lastName":"Kim","suffix":""}],"badges":[],"createdAt":"2025-01-15 08:53:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5832774/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5832774/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":75409211,"identity":"9a436056-c876-4edd-83e4-4eff43f5600a","added_by":"auto","created_at":"2025-02-04 09:03:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":212948,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePLCD1 overexpression was observed in HGSOC tissues.\u003c/strong\u003e(A) Representative IHC image of PLCD1 expression levels in normal, borderline, and HGSOC tissues (magnification ×40; scale bar, 50μm). The mean IHC scores are presented as bar graphs for normal (N=68), borderline (N=44), and HGSOC (N=101) tissues. Statistical significance was determined by unpaired t-test (* \u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05, **** \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.0001). (B) Kaplan-Meier survival curves for 101 patients stratified by PLCD1 expression levels. The curves demonstrate difference in OS and DFS between groups with low and high PLCD1 expression levels. Statistical analysis was conducted using log-rank test.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-5832774/v1/901f7bd90fca615d44c9acb2.png"},{"id":75411529,"identity":"73eb93f2-420e-46a8-adc9-50c753924175","added_by":"auto","created_at":"2025-02-04 09:11:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":203713,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHGSOC cell proliferation was regulated by PLCD1 knockdown \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ein vitro\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e (A) PLCD1 expression levels in HGSOC cell lines were measured by Western blotting. ɑ-actinin was used as a loading control. (B) OVCA429 cells were treated with the various concentration of PLCD1-siRNA, and PLCD1 expression was confirmed by Western blotting. PLCD1 protein expression levels were assessed in the OVCA429 cells treated with 200 nM sicontrol (lane 2) and various concentration of PLCD1-siRNA (lanes 3-5, corresponding 50-200 nM) for 48 h, with untreated cell as a control (lane 1). β-actin was used as a loading control. (C) Cell proliferation was determined for OVCA429 cells following the depletion of PLCD1. The images were representative with crystal violet staining. (D) The staining cells were detected the absorbance at 595 nm (left). Cell proliferation was indicated by a fold change of staining cells (right). The results were shown as mean ± SD and analyzed by the Mann-Whitney U test (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) (E) Invasion activity of OVCA429 cells was determined following the depletion of PLCD1. The images were representative with crystal violet staining (left). Invaded cells were counted by light microscopy. The results were shown as mean ± SD and analyzed by the Mann-Whitney U test (right, ns: not significant).\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-5832774/v1/cb4bb1bbce94d3a2299e8f21.png"},{"id":75409212,"identity":"69eee65b-63ab-4f36-ac19-e74e1746ffe8","added_by":"auto","created_at":"2025-02-04 09:03:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":146425,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHGSOC cell proliferation was regulated by PLCD1 overexpression \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ein vitro\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. \u003c/strong\u003e(A) OVCAR3 cells were transfected with a GFP-PLCD1 expression vector, and PLCD1 expression levels were assessed by the Western blotting. ɑ-actinin was used as a loading control. (B) Representative images of spheroids formed from OVCAR3 cells transfected with PLCD1 or an empty vector, captured using an imaging cytometer (scale bar, 200 μm). All spheroids were cultured for up to 9 days. (C) Invasion activity was evaluated for OVCAR3 cells transfected with PLCD1 and empty vector. The images were representative with crystal violet staining (left). Invaded cells were counted by light microscopy. The results were shown as mean ± SE and analyzed by the Mann-Whitney U test (right, ns: not significant).\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-5832774/v1/ffe869b33ef3a0f4a38a9d76.png"},{"id":75409214,"identity":"14149638-a8ec-4c2f-944c-afaf2246084d","added_by":"auto","created_at":"2025-02-04 09:03:02","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":111712,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePLCD1 overexpression inhibited tumor growth in the OVCAR3-derived xenograft model. \u003c/strong\u003e(A) OVCAR3 cells, transfected with either empty or PLCD1 lentivirus vector, were injected subcutaneously into the left and right flank region of nude mice. Tumor volume was measured for 35 d. (B) Tumor size on the 35th day of tumor incubation was displayed for PLCD1 (N=11) and Empty (N=4) group (scale bar, 5 mm). (C) Final tumor volumes were measured using caliper rule. Graph was presented as the mean tumor volumes of mice in both PLCD1 and empty lentivirus vector groups (left, * \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05). Final tumor weight was shown at the end of the experiments (right, ns: not significant).\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-5832774/v1/0861324587b2466df4abb9fe.png"},{"id":75833312,"identity":"15bcaefb-196c-49ee-b628-6c6e2f2c9b19","added_by":"auto","created_at":"2025-02-09 13:31:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1570273,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5832774/v1/9aed4f98-004c-4631-ad77-01a7599e187b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"PLCD1 Expression for Early Detection and Prognosis in High-Grade Serous Ovarian Cancer","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eHigh-grade serous ovarian cancer (HGSOC) is the most common and aggressive subtype of ovarian cancer, and is characterized by rapid progression and poor prognosis\u0026nbsp;[1]. It typically originates from the fallopian tubes or surface epithelium of the ovary and is known for its tendency to metastasize widely within the peritoneal cavity\u0026nbsp;[2]. Despite advances in treatment, including surgical debulking and chemotherapy, most patients experience recurrence, often with resistance to standard therapies\u0026nbsp;[3]. The molecular complexity of HGSOC, including frequent mutations in TP53 and alterations in the BRCA1/2 genes, contributes to its challenging management and poor survival rates\u0026nbsp;[4]. Studies on the mechanisms underlying HGSOC is crucial for developing effective targeted therapies and improving patient outcomes. Additionally, early detection remains a considerable challenge because the disease is often diagnosed at an advanced stage. Therefore, understanding the unique characteristics of HGSOC is essential to advance diagnostic and therapeutic strategies.\u003c/p\u003e\n\u003cp\u003ePLCD1 encodes phospholipase C delta 1, an enzyme involved in cellular signaling through the hydrolysis of phosphatidylinositol 4,5-bisphosphate [5]. In cancer research, PLCD1 has been implicated in various functions, including the modulation of cell proliferation, migration, and apoptosis [6, 7]. Aberrant expression of PLCD1 is associated with cancer progression and metastasis in several cancer types, such as breast and prostate cancers. Recent studies have revealed that PLCD1 exhibits notable antitumor effects, including the inhibition of cell proliferation in breast cancer, colorectal cancer, and esophageal squamous cell carcinoma [6, 8, 9]. Additionally, PLCD1 is thought to influence the sensitivity of cancer cells to chemotherapy and radiation. Functional alterations in cancer highlight their potential as biomarkers and therapeutic targets for personalized cancer treatment. However, its effect on the pathogenesis and biological functions of HGSOC remains unclear.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe expression level of PLCD1 in tumor microarrays (TMA) have been investigated in this study. Furthermore, the biological functions of PLCD1 in HGSOC cells were studied \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e. Our results suggest that PLCD1 is a functional tumor suppressor and a potential biomarker for HGSOC.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 TMA and patient information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe TMA was obtained from the Korea Gynecologic Cancer Bank of Gangnam Severance Hospital, Yonsei University College of Medicine (No. HTB-P2021-5). All procedures were approved by the Institutional Review Board of Samsung Medical Center in advance (date of approval: 12th Dec 2019, approval number: SMC 2019-12-013). The TMA consisted of 68 normal, 44 borderline, and 101 high-grade serous ovarian cancer tissues. Clinical findings, treatment, and follow-up information were obtained from patient records. The demographic and clinical characteristics of the patients are shown in Table 1.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"83%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 100px;\"\u003e\n \u003cp\u003eTable 1. Demographic and clinical characteristics of patients\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003ePLCD1_Hs_Cy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eNo.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003eMean IHC Score (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistology\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e31.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e38.63 (30.48 - 46.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eBorderline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e20.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e55.11 (41.05 - 69.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eHGSOC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e47.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e73.99 (64.50 - 83.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e0.877\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u0026lt; 55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e49.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e73.24 (58.02 - 88.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u0026ge; 55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e50.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e74.73 (62.74 - 86.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCA125\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e0.788\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e9.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e71.55 (43.01 - 100.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003ePositive (\u0026gt;35U/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e88.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e75.84 (65.62 - 86.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eN.A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e0.183\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eI/II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e16.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e88.2 (66.49 - 109.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eIII/IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e83.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e71.1 (60.50 - 81.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrade\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e0.464\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e46.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e77.8 (62.63 - 92.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003ePoor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e53.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e70.7 (58.39 - 83.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChemo sensitivity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e0.870\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eSensitive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e77.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e74.2 (63.30 - 85.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eResistant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e19.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e72.1 (47.86 - 96.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\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\u003cstrong\u003e2.2 Immunohistochemistry (IHC) staining\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParaffin-embedded sections were incubated at 65\u0026deg;C for 20 min, deparaffinized in xylene for 15 min, and then transferred sequentially to 100% ethanol, 90% ethanol, and 70% ethanol for 5 min. Thereafter, the sections were rinsed with deionized water. Sections were pretreated for heat-mediated antigen retrieval with 10 mM citrate buffer (pH 6.0) for 10 min in a microwave. The sections were immersed in methanol containing with 3% hydrogen peroxide for 10 min and incubated with primary antibodies for 120 min. The following primary antibody was used: PLCD1 (#ab154610,\u0026nbsp;Abcam, Cambridge, UK). The secondary EnVision\u0026trade; Rabbit/Mouse reagent (#K5007,\u0026nbsp;Agilent Technologies, Santa Clara, CA, USA) was then applied for 60 min. Sections were visualized using 3,3-diaminobenzidine tetrachloride (DAB; #K3468,\u0026nbsp;Agilent Technologies, Santa Clara, CA, USA) and counterstained with hematoxylin (#S3309,\u0026nbsp;Agilent Technologies, Santa Clara, CA, USA) for 5 min. All procedures\u0026nbsp;were performed at a room temperature of 25℃. PLCD1 protein expression was assessed by combining relative staining intensity and proportion of positive cells. The intensity of staining on the slides was scored as 0 (negative), 1 (weak), 2 (moderate), or 3 (strong). The proportion of staining was scored 0-100 percent. The final score was calculated by multiplying each score.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Cell culture\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYDOV-139, YDOV-157, and YDOV-161, which were established and characterized in our laboratory, were cultured as described previously [10-12]. OVCA429, OVCA433, and DOV13 were maintained in DMEM medium (#10-013-CV, Corning, NY, USA) supplemented with 10% fetal bovine serum (FBS; #12483-020, Gibco,\u0026nbsp;Waltham, MA, USA) and 1% penicillin/streptomycin (#15140, Gibco,\u0026nbsp;Waltham, MA, USA). OVCAR3 and SKOV3 were purchased from American Type Culture Collection (ATCC, Manassas, VA, USA). All purchased cell lines were maintained as recommended. Mycoplasma contamination test against cell lines was checked by a e-Myco\u003csup\u003eTM\u0026nbsp;\u003c/sup\u003eplus Mycoplasma PCR detection kit (#25237, iNtRON Biotechnology, Seongnam, Korea).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Protein extraction and western blotting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCell lysates were obtained using a cell lysis buffer (#9803, Cell Signaling Technology,\u0026nbsp;Danvers, MA, USA) supplemented with PMSF (#8553, Cell Signaling Technology,\u0026nbsp;Danvers, MA, USA). Protein concentrations were determined by BCA assay (Sigma-Aldrich, St. Louis, MO, USA). The proteins were separated by SDS-PAGE and transferred onto 0.2 \u0026mu;m nitrocellulose membranes (Pall Corporation, Washington, NY, USA). Protein bands were visualized using western blotting luminol reagent (Santa Cruz Biotechnology, Inc.,\u0026nbsp;CA, USA) after incubation with an HRP-conjugated secondary antibody. The primary antibodies used were anti-PLCD1 (ab154610), anti-\u0026alpha;-actinin (sc-17829), and anti-\u0026beta;-actin (ab3854).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 siRNA-mediated knockdown\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOVCA429 cells were seeded one day prior to siRNA transfection in 6-well plate and were allowed to grow up to 50% confluency. PLCD1 (#5333-3) and control (#SN-1002) knockdown were conducted using predesigned siRNA sequences purchased from Bioneer. On the day of siRNA transfection, cells were transfected with siRNA in Opti-MEM (#31985-070, Gibco BRL,\u0026nbsp;Waltham, MA, USA), using\u0026nbsp;Lipofectamine\u0026trade; RNAiMAX Transfection Reagent (#13778150, Thermo Scientific,\u0026nbsp;Waltham, MA, USA), as per the manufacturer\u0026rsquo;s instructions.\u0026nbsp;Transfection efficiencies were analyzed 48 h post-transfection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.6 Crystal violet staining\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe cells were seeded in a 24-well plate and allowed to adhere overnight. Then, the cells were fixed in 10% acetic acid solution with 10% methanol, stained with 0.5% crystal violet (#C3886, Sigma-Aldrich, St. Louis, MO, USA) for 1 h, photographed, and extracted using 1% sodium dodecyl sulfate solution. The crystal violet extracted from the cells was measured by determining the absorbance at 595 nm using\u0026nbsp;a VERSA Max\u0026trade;.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.7 Cell invasion assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCell invasion assays were performed in an invasion chamber (Neuro Probe 48-well Micro Chemotaxis Chamber, #AP48). The membranes (Neuro Probe, #PFB8) were coated with Matrigel (#354234, BD\u0026nbsp;Biosciences, NY, USA) for 1 h. Cells (1 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e) in serum-free medium were seeded into the upper chambers, and a medium containing 10% FBS was placed in the lower chambers. After incubation for 24 h, cells adhering to the upper surface of the membrane were removed. The invading cells attached to the lower surface were stained using a Differential Quik Stain Kit (#38721,\u0026nbsp;Sysmex Corporation, Kobe, Hyogo, Japan). Images of the invading cells were captured using an Axio Imager. M2 (Carl Zeiss, magnification x 200). The invading cells were counted in three randomly selected fields.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.8 Establishment of stable cell lines.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe human PLCD1 lentiviral ORF cDNA expression plasmid with a c-GFP Spark tag (pLV-PLCD1-GFPSpark, #HG18554-ACGLN) and a Lentivirus Control Plasmid (pLV-C-GFPSpark #, # LVCV-35) were purchased from Sino Biological Inc. (Beijing, China). HEK293T cells (1 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e) were co-transfected with 2 \u0026micro;g lentiviral vector, 2 \u0026micro;g the viral packaging plasmids composed of pCMV delta and pMDG, and lipofectamin 2000. The crude virus supernatant (total collected viral medium of 10 mL) was collected 48 and 72 h post-transfection. OVCAR3 cells seeded in a 24-well plate was infected with 500 \u0026micro;L of the collected crude viral medium per well, and the medium was changed with fresh ones after 24 h. Positively infected OVCAR3 cells were observed with GFP expression as a selection marker. Positively infected live cells were sorted based on GFP fluorescence by flow cytometry (BD FACSAria\u003csup\u003eTM\u003c/sup\u003e III).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.9 3D tumor spheroid assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor 3D cultures, OVCAR3 stable cells (0.1 \u0026times; 10\u003csup\u003e3\u003c/sup\u003e cells) were suspended in a PBS and Matrigel (#354234, BD Biosciences, NY, USA) mixture (1:1), which was dropped on the cover slide. After solidifying the mixture, the cover slides were moved to a culture dish, and added medium with 10% FBS. The culture medium was refreshed every two days for up to 9 d. Microscopic imaging of the spheroid cells was performed using a microscope (EVOS\u0026reg; FL Cell Imaging System, Life Technologies). Spheroid cells were stained and counted using 5 mg/mL 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium solution.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.10\u003cem\u003e\u0026nbsp;In vivo\u003c/em\u003e xenograft tumor model.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll animal procedures were performed in accordance with a protocol approved by the Institutional Animal Care and Use Committee of Yonsei University (IACUC Approval No. 2024-0266, Seoul, Korea). First, six-week-old female BALB/c nude mice (OrientBio Inc.,\u0026nbsp;Seongnam, Korea) were anesthetized by\u0026nbsp;injecting alfaxan\u0026nbsp;(76 mg/kg) with\u0026nbsp;xylazine\u0026nbsp;(10 mg/kg). OVCAR3 stable cells (5 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cells/inoculation) were suspended in PBS and Matrigel (#354234, BD Biosciences, NY, USA) mixture (1:1). Mice were subcutaneously injected with the mixture into the left and right flanks. Tumor dimensions were measured using digital calipers, and tumor volume was calculated using the following formula: [tumor volume (mm\u003csup\u003e3\u003c/sup\u003e) = length \u0026times; width\u003csup\u003e2\u003c/sup\u003e \u0026times; 0.5]. Tumors were harvested 35 d after cell inoculation, final tumor volume and weight were measured and then fixed at 10 % formalin (Sigma-Aldrich, St. Louis, MO, USA).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.11\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGraphPad Prism 10.0 (GraphPad Prism, San Diego, CA, USA) was used for the statistical analysis. Results are expressed as mean \u0026plusmn; standard deviation (SD). Method to test distribution was used by Shapiro-Wilk normality test. Unpaired t-tests or Mann-Whitney U test were used to evaluate the differences between the two groups. Survival curve analysis was performed using the Kaplan\u0026ndash;Meier method, and statistical significance was calculated using the log-rank test. Differences were considered significant at * \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 and **** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.0001. A value of \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 PLCD 1 expression was increased in HGSOCs by TMA tissue staining.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe investigated PLCD1 expression levels in normal, borderline tumor, and HGSOC tissues of TMA by IHC staining.\u0026nbsp;PLCD1 was highly expressed in the cytoplasm of epithelial cells, with significantly increased expression observed in HGSOC tissues compared to that in normal or borderline tissue (Fig. 1A).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe patients clinicopathologic variables of TMA are shown in Table 1.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ePLCD1 expression was positively associated with histology (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.0001), but not with age, CA125 levels, stage, grade, or chemosensitivity. To investigate whether the expression of PLCD1 affects survival outcomes in 101 patients with HGSOC, the Kaplan-Meier method was used.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe median expression levels of PLCD1 were divided into high and low expression group. Patients in the low PLCD1 expression group had significantly worse prognosis in overall survival (OS) and disease-free survival (DFS) than those in the high expression group (Fig. 1B; Log-rank test, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 HGSOC cell proliferation was regulated by PLCD1 knockdown/overexpression \u003cem\u003ein vitro\u003c/em\u003e.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePLCD1 expression in HGSOC cell line was confirmed by Western blotting (Fig. 2A). To investigate the functional role of PLCD1 in HGSOC, the PLCD1 knockdown/overexpression cell lines were established using HGSOC cell lines. A PLCD1 knockdown cell line was established based on the OVCA429 cell line (Fig. 2B). The colony formation assay demonstrated that colonies of siPLCD1 were significantly increased than that of the sicontrol group (Fig. 2C). However, no significant difference in cancer invasion ability between the two groups was observed (Fig. 2D). These results indicate that PLCD1 knockdown in HGSOC cells promoted cell proliferation \u003cem\u003ein vitro\u003c/em\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor the overexpression studies, OVCAR3 cells were transfected with either PLCD1 or an Empty lentivirus vector. A stable PLCD1 overexpression cell line was established based on the OVCAR3 cell line (Fig. 3A). Colony formation assays in 3D culture demonstrated that PLCD1 overexpression resulted in a reduction of colony number by over 50% compared with the empty vector cell lines (Fig. 3B). No significant difference was observed in cancer invasion ability between the two groups (Fig. 3C). Our results suggest that PLCD1 overexpression inhibits cell proliferation \u003cem\u003ein vitro\u003c/em\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 PLCD1 overexpression reduced tumor growth in the OVCAR3-derived xenograft model.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo evaluate whether PLCD1 expression influenced tumor growth, we used an OVCAR3-derived xenograft model. OVCAR3 cells were transfected with either\u0026nbsp;PLCD1 or an Empty lentivirus vector, and these cells were used to establish two groups: the PLCD1 group (N=11) and Empty group (N=4)\u0026nbsp;\u003cem\u003evia\u003c/em\u003e intraperitoneally injection. Starting\u0026nbsp;30 d after the initiation of the experiment, the\u0026nbsp;tumor growth rate\u0026nbsp;in the\u0026nbsp;PLCD1 group was significantly reduced\u0026nbsp;compared to that the Empty group\u0026nbsp;(Fig. 4A, \u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05). Tumor size on day 35 of incubation is shown (Fig. 4B). This finding showed that tumor volume decreased according to PLCD1 overexpression. PLCD1 overexpression led to a reduction in final tumor weight, but this decrease was not statistically significant.\u0026nbsp;\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003ePhospholipase C (PLC), part of the phosphoinositide‐specific enzyme superfamily, is essential for various cellular processes, such as intracellular signaling pathways, including growth factor signaling, hormone release, membrane transport, and the regulation of the cytoskeleton [13]. Among the PLC family, PLCD1 has been determined as a novel tumor suppressor gene because of its inactivation through promoter methylation in various cancer, including breast cancer, chronic myeloid leukemia, esophageal squamous cell carcinoma, and gastric cancer [14-17]. However, its effect on the pathogenesis and biological functions of HGSOC remains unclear. Our results presented that PLCD1 was significantly upregulated in HGSOC tissues compared with normal or borderline tissues. This study revealed that PLCD1 expression is a potential marker of cancer detection in HGSOC.\u003c/p\u003e\n\u003cp\u003eGiven the previous studies, PLCD1 expression is associated with survival rate in some cancers; a low level of PLCD1 expression is associated with poor survival in renal cell carcinoma, chondrosarcoma, and colorectal cancer [6, 7, 9].\u0026nbsp;Consistent with these findings, our results indicated that patients with\u0026nbsp;lower PLCD1 expression had worse OS and DFS. Therefore, our study suggests that\u0026nbsp;PLCD1 expression plays a role as a predictive factor for prognosis in HGSOC.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo corroborate our \u003cem\u003ein vivo\u003c/em\u003e data, we conducted \u003cem\u003ein vitro\u003c/em\u003e study using two HGSOC cell lines, OVCA429 and OVCAR3, and obtained corresponding result: knockdown of PLCD1 led to increased OVCA429 cell proliferation. In contrast, PLCD1 overexpression inhibited HGSOC cell proliferation \u003cem\u003ein vitro\u003c/em\u003e and reduced tumor size in an \u003cem\u003ein vivo\u003c/em\u003e mouse model. Our results demonstrated that PLCD1 expression is associated with cancer cell proliferation and tumor progression. Consistent with our findings, recent studies have shown that PLCD1 inhibits cancer cell proliferation \u003cem\u003evia\u003c/em\u003e several mechanisms. PLCD1 is inactivated by promoter methylation and exerts its tumor-suppressive functions by inhibiting WNT/\u0026beta;‐catenin and EGFR‐FAK-ERK signaling pathway [5]. According to another study, DNA damage induced by PLCD1 overexpression leads to cell cycle arrest and apoptosis [7]. The observed anti-proliferative effect of PLCD1 could be linked to its role in intracellular signaling pathways, which is known to influence cell survival and growth. Our study suggests that PLCD1 may function as a tumor suppressor in HGSOC, indicating the need for further research to elucidate its underlying mechanisms. Taken together, these data provide a novel diagnostic and prognostic marker in HGSOC.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003eEun-Suk Kang, Jae-Hoon Kim contributed to the study conception and design. Jue Young Kim performed in vitro experiment and analyze between TMA IHC and patient information. Ha-Yeon Shin performed in vitro and in vivo experiment. Jue Young Kim and Ha-Yeon Shin contributed to collecting of clinical samples and wrote the manuscript. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e No datasets were generated or analysed during the current study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e The authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e All authors agree to submit the article for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003eThis research was supported by the National Institute of Health (NIH) research project (project No. #2024ER051700).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003eThis study was approved by Institutional Review Board of Samsung Medical Center in advance (date of approval: 12th Dec 2019, approval number: SMC 2019-12-013). All animal procedures in this study were performed under a protocol approved by the Institutional Animal Care and Use Committee at Yonsei University (IACUC Approval No. 2024-0266, Seoul, Korea). TMA were obtained from the Korea Gynaecologic Cancer Bank (KGCB) of Gangnam Severance Hospital, Yonsei University College of Medicine (No. HTB-P2021-5). All patients involved in this article signed informed consent.\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eY. Cen, Y. Fang, Y. Ren, S. Hong, W. Lu and J. Xu, Global characterization of extrachromosomal circular DNAs in advanced high grade serous ovarian cancer, Cell Death Dis \u003cstrong\u003e13\u003c/strong\u003e, 342 (2022).\u003c/li\u003e\n\u003cli\u003eJ. Kim, E.Y. Park, O. Kim, et al., Cell Origins of High-Grade Serous Ovarian Cancer, Cancers (Basel) \u003cstrong\u003e10\u003c/strong\u003e (2018).\u003c/li\u003e\n\u003cli\u003eA. Andrikopoulou, C. Theofanakis, C. Markellos, et al., Optimal Time Interval between Neoadjuvant Platinum-Based Chemotherapy and Interval Debulking Surgery in High-Grade Serous Ovarian Cancer, Cancers (Basel) \u003cstrong\u003e15\u003c/strong\u003e (2023).\u003c/li\u003e\n\u003cli\u003eU.A. Boyarskikh, L.F. Gulyaeva, A.M. Avdalyan, et al., Spectrum of TP53 Mutations in BRCA1/2 Associated High-Grade Serous Ovarian Cancer, Front Oncol \u003cstrong\u003e10\u003c/strong\u003e, 1103 (2020).\u003c/li\u003e\n\u003cli\u003eJ. Xie, J. Zhou, J. Xia, et al., Phospholipase C delta 1 inhibits WNT/beta-catenin and EGFR-FAK-ERK signaling and is disrupted by promoter CpG methylation in renal cell carcinoma, Clin Epigenetics \u003cstrong\u003e15\u003c/strong\u003e, 30 (2023).\u003c/li\u003e\n\u003cli\u003eX. He, F. Meng, Z.J. Yu, et al., PLCD1 Suppressed Cellular Proliferation, Invasion, and Migration via Inhibition of Wnt/beta-Catenin Signaling Pathway in Esophageal Squamous Cell Carcinoma, Dig Dis Sci \u003cstrong\u003e66\u003c/strong\u003e, 442-451 (2021).\u003c/li\u003e\n\u003cli\u003eJ. Shen, C. Yu, Z. Wang, H. Mu and Z. Cai, PLCD1-Induced DNA Damage Inhibits the Tumor Growth via Downregulating CDKs in Chondrosarcoma, J Oncol \u003cstrong\u003e2022\u003c/strong\u003e, 4488640 (2022).\u003c/li\u003e\n\u003cli\u003eM. Shimozawa, S. Anzai, R. Satow and K. Fukami, Phospholipase C delta1 negatively regulates autophagy in colorectal cancer cells, Biochem Biophys Res Commun \u003cstrong\u003e488\u003c/strong\u003e, 578-583 (2017).\u003c/li\u003e\n\u003cli\u003eQ. Xiang, X. He, J. Mu, et al., The phosphoinositide hydrolase phospholipase C delta1 inhibits epithelial-mesenchymal transition and is silenced in colorectal cancer, J Cell Physiol \u003cstrong\u003e234\u003c/strong\u003e, 13906-13916 (2019).\u003c/li\u003e\n\u003cli\u003eH. Cho, Y.S. Lee, J. Kim, J.Y. Chung and J.H. Kim, Overexpression of glucose transporter-1 (GLUT-1) predicts poor prognosis in epithelial ovarian cancer, Cancer Invest \u003cstrong\u003e31\u003c/strong\u003e, 607-615 (2013).\u003c/li\u003e\n\u003cli\u003eH. Cho, B.J. Lim, E.S. Kang, J.S. Choi and J.H. Kim, Molecular characterization of a new ovarian cancer cell line, YDOV-151, established from mucinous cystadenocarcinoma, Tohoku J Exp Med \u003cstrong\u003e218\u003c/strong\u003e, 129-139 (2009).\u003c/li\u003e\n\u003cli\u003eH. Cho, H.Y. Shin, S. Kim, et al., The role of S100A14 in epithelial ovarian tumors, Oncotarget \u003cstrong\u003e5\u003c/strong\u003e, 3482-3496 (2014).\u003c/li\u003e\n\u003cli\u003eC.A. Bill and C.M. Vines, Phospholipase C, Adv Exp Med Biol \u003cstrong\u003e1131\u003c/strong\u003e, 215-242 (2020).\u003c/li\u003e\n\u003cli\u003eL. Fu, Y.R. Qin, D. Xie, et al., Characterization of a novel tumor-suppressor gene PLC delta 1 at 3p22 in esophageal squamous cell carcinoma, Cancer Res \u003cstrong\u003e67\u003c/strong\u003e, 10720-10726 (2007).\u003c/li\u003e\n\u003cli\u003eJ.J. Song, Q. Liu, Y. Li, et al., Epigenetic inactivation of PLCD1 in chronic myeloid leukemia, Int J Mol Med \u003cstrong\u003e30\u003c/strong\u003e, 179-184 (2012).\u003c/li\u003e\n\u003cli\u003eX.T. Hu, F.B. Zhang, Y.C. Fan, et al., Phospholipase C delta 1 is a novel 3p22.3 tumor suppressor involved in cytoskeleton organization, with its epigenetic silencing correlated with high-stage gastric cancer, Oncogene \u003cstrong\u003e28\u003c/strong\u003e, 2466-2475 (2009).\u003c/li\u003e\n\u003cli\u003eT. Xiang, L. Li, Y. Fan, et al., PLCD1 is a functional tumor suppressor inducing G(2)/M arrest and frequently methylated in breast cancer, Cancer Biol Ther \u003cstrong\u003e10\u003c/strong\u003e, 520-527 (2010).\u003c/li\u003e\n\u003c/ol\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":"HGSOC, PLCD1, prognosis, diagnosis, TMA, xenograft","lastPublishedDoi":"10.21203/rs.3.rs-5832774/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5832774/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose: \u003c/strong\u003eHigh-grade serous ovarian cancer (HGSOC) is a prevalent and aggressive subtype with rapid progression and poor prognosis, often diagnosed at an advanced stage despite treatment advances. Current diagnostic markers, such as CA-125, have limited early detection capability and poorly integrate with treatment decisions. This study explored PLCD1 as potential biomarkers for HGSOC’s early detection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eImmunohistochemistry (IHC) staining was performed to detect PLCD1 expression in tissue microarrays (TMA). The impact of PLCD1 expression on survival outcomes was evaluated via Kaplan-Meier method. PLCD1 expression in HGSOC cells was confirmed through Western blotting. PLCD1 knockdown and overexpression cell lines were established to investigate the functional role of PLCD1 in HGSOC. Colony formation, invasion, and 3D tumor spheroid assay\u003cstrong\u003e \u003c/strong\u003ewere performed to evaluate cancer cells behavior. An OVCAR3-derived xenograft model was used to determine whether PLCD1 expression influence tumor growth.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eIHC staining revealed high cytoplasmic expression of PLCD1 in HGSOC tissues compared to normal or borderline tissues, with low PLCD1 expression correlating with worse overall survival and disease-free survival in 101 patients with HGSOC. \u003cem\u003eIn vitro\u003c/em\u003e studies demonstrated that PLCD1 knockdown increased OVCA429 cells proliferation, whereas PLCD1 overexpression in OVCAR3 cells reduced colony formation. In the OVCAR3-derived xenograft model, PLCD1 overexpression significantly reduced tumor growth compared with that in the control group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eThe TMA revealed an association between PLCD1 expression and patient prognosis. Furthermore, tumor reduction was observed following PLCD1 overexpression in a xenograft model.These findings establish \u003cem\u003ePLCD1\u003c/em\u003e as a promising prognostic biomarker and therapeutic target for HGSOC.\u003c/p\u003e","manuscriptTitle":"PLCD1 Expression for Early Detection and Prognosis in High-Grade Serous Ovarian Cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-04 09:02:57","doi":"10.21203/rs.3.rs-5832774/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":"ed949dcc-ddab-49ac-acd8-540f3674d5ef","owner":[],"postedDate":"February 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-02-09T13:23:29+00:00","versionOfRecord":[],"versionCreatedAt":"2025-02-04 09:02:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5832774","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5832774","identity":"rs-5832774","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}