The impact of the FOXL2 gene on ovarian granulosa cells KGN

The impact of the FOXL2 gene on ovarian granulosa cells KGN | 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 Article The impact of the FOXL2 gene on ovarian granulosa cells KGN Yuzhu Zhang, Yu Wang, Yuan Gu, Yang Liu, Guohua Liu, Jun Wu, Nan Bai This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4469361/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Apr, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Purpose: This study aimed to investigate the impact of JNK regulation on the FOXL2 gene in ovarian granulosa cells KGN. Materials and methods: Bioinformatics methods were employed to identify the main pathogenic gene FOXL2 in ovarian cancer. KGN cells were randomly divided into control and experimental groups, with the experimental group treated with different concentrations of JNK inhibitors (0.1, 1, 5, 10, 50 μM) and the control group receiving an equal volume of DMSO and incubated for 12 hours. The MTT assay was utilized to assess the proliferative capacity of KGN cells treated with JNK inhibitors. A cell scratch test was conducted to evaluate their migration ability. Cell RNA was extracted, reverse transcribed into cDNA, and qRT-PCR was employed to measure the mRNA expression levels of FOXL2. Protein was extracted and Western blot was used to determine the expression levels of FOXL2 protein. Results: JNK inhibitors at concentrations of 1, 5, 10, and 50 μm all led to a decrease in FOXL2 expression. Conclusion: The FOXL2 gene exerts an influence on KGN cells through JNK regulation. Biological sciences/Cancer Biological sciences/Immunology Health sciences/Diseases FOXL2 KGN JNK Granulosa Cells Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Ovarian granulosa cell tumors are related to the increase in ovarian mass, such as abdominal pain and bloating, and often present with endocrine manifestations of estrogen excess, such as increased menstruation or postmenopausal vaginal bleeding. Some patients may also have shown endometrial hyperplasia or malignancy (Barcellini et al. 2023 , Mangili et al. 2013 ). Previous studies by the applicant have suggested that estrogen regulates FOXL2 to promote apoptosis in human ovarian granulosa cell tumors (Rosario et al. 2014 , Wu et al. 2019a ). Mutations in the FOXL2 gene have been found in 95–97% of adult ovarian granulosa cell tumor patients, making FOXL2 gene mutation an important focus of research in ovarian granulosa cell tumors (Guerrieri et al. 2023 , Singh et al. 2014 , Yanagida et al. 2017 ). To date, research has mainly focused on FOXL2 as a transcription factor regulating its downstream target genes, while relatively ignoring its own transcription and translation regulation (Caburet et al. 2012 , Fuller et al. 2022 , Köbel et al. 2009 , Tucker 2022 ), which is a limitation in FOXL2 research. Therefore, this study aims to investigate the regulatory mechanisms of transcription and translation of the FOXL2 gene, incorporating FOXL2 into the overall regulatory network of the human body, enhancing its dual-role functions, and providing new insights for the prevention and treatment of clinically relevant diseases. Methods Materials The KGN granulosa cells were obtained from the Stem Cell Bank, Chinese Academy of Sciences; fetal bovine serum (FBS) and 1640 culture medium were purchased from Gibco; MEM and Trizol were obtained from Shanghai Biotech Co., Ltd.; pancreatin from BBI; rabbit anti-human FOXL2 antibody from Beijing Zhongshan Gold Bridge Biotechnology Co., Ltd.; DAB chromogenic reagent kit from Beijing Zhongshan Gold Bridge Biotechnology Co., Ltd.; RT-PCR kit and related experimental reagents from Takara, Japan; DNA Marker from TIANGEN; RIPA lysis buffer from Pulilai Gene Technology Co., Ltd. Data Analysis In this study, we manually downloaded the matrix and platform files of dataset GSE34526. Using the GEOquery package in R version 4.3.2, we retrieved the expression matrix and clinical information. The matrix data was then subjected to standardization, and probe IDs were converted to gene names based on the platform file. For genes with the same name in the expression matrix, the average expression level was calculated. Batch effects were removed using the removeBatch function in the limma package. Differential expression genes between ovarian cancer and normal ovarian tissues in the training set were identified using the limma package. Selection criteria of |logFC|>1 and adj.P.Value < 0.05 were applied. The pheatmap package was used to construct a hierarchical clustering heatmap of the top 100 differentially expressed genes, while the ggplot2 package was utilized to create a volcano plot of differentially expressed genes, with annotations for the top 20 differentially expressed gene names. Enrichment analysis of differentially expressed genes was conducted using the clusterProfiler package, including Gene Ontology analysis of biological processes, cellular components, and molecular functions. Visualization of the enrichment results was performed using the ggplot2 package. Cells Culture KGN cells (Innovatbio, Beijing, China) were cultured in DMEM containing 10% FBS and 1% penicillin-streptomycin solution, maintained at 37°C in a 5% CO2 humidified cell culture incubator. When the cell confluence reached approximately 80%, cells were passaged using 0.05% Trypsin-EDTA and further utilized for experimental procedures. The detection of FOXL2 mRNA The cells were randomly divided into control and experimental groups. KGN cells were seeded in a 6-well cell culture plate and allowed to grow to a density of 70%-80%. Different concentrations of JNK inhibitor (0.1, 1, 5, 10, 50µM) were applied to the KGN cells for 12 hours, with DMSO used as the solvent control. RNA extraction was performed using Trizol (Solarbio, Beijing, China) from both total cells and ovarian tissue. RNA concentrations were measured by absorbance at 260nm using a micro-spectrophotometer (ThermoScientific, USA). RNA quality was assessed by electrophoresis in a 1% agarose gel. The cDNA was synthesized using a Fast Super RT Kit cDNA (with gDNase) (B002004018, Bioteke, Beijing, China). Primer pairs were designed for GAPDH (forward primer: 5′-AGCCAAAAGGGTCATCATCTCT-3′, reverse primer: 5′-AGGGGCCATCCACAGTCTT-3′) and FOXL2 (forward primer: 5′-TCACGCTGTCCGGCATCTACCA-3′, reverse primer: 5′-GCGGCACCTTGATGAAGCACTC-3′) using Primer version 5.0 software. Taq DNA Polymerase (9618080604, ABclonal, Wuhan, China) was used for PCR amplification. qRT-PCR was performed using the SYBR Green Real-time PCR Master Mix in a real-time PCR system (TOYOBO, Japan) following the manufacturer’s protocol. The qRT-PCR parameters were as follows: 94°C for 3 minutes, followed by 40 cycles of 94°C for 30 seconds, 60°C for 30 seconds, and a final extension at 72°C for 5 minutes. Data analysis was conducted using the formula: R = 2^-[ΔCt sample - ΔCt control], where R represents the relative expression level, ΔCt represents the difference between the Ct of the gene and the average GAPDH in the experimental sample, and ΔCt control represents the difference between the Ct of the gene and the average GAPDH in the control sample. Experiments were carried out in triplicate with independent experimental samples. Protein extraction and Western blotting The KGN cells and tissue utilized for protein extraction underwent grinding in radio-immunoprecipitation assay (RIPA) buffer (Solarbio, Beijing, China) supplemented with 1 mM phenylmethanesulfonyl fluoride (PMSF) and phosphatase inhibitors, symbolizing a meticulous approach to sample preparation. Following centrifugation at 10,000 g at 4℃ for 10 minutes, the protein-enriched supernatant was meticulously collected. The protein concentrations were determined using the Bradford method (Bradford 1976 ), showcasing a commitment to precise quantification. Subsequently, protein samples (30 µg) were meticulously subjected to 10% sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) and precisely electro-transferred onto a 0.22 µM nitrocellulose membrane, illustrating a meticulous technique of protein separation and transfer. The resulting membranes were diligently blocked with a blocking buffer (2% BSA in TBS buffer: 10 mM Tris-HCl, 150 mM NaCl, pH = 7.5) for 1 hour at room temperature, demonstrating a thorough experimental procedure. The membrane was then meticulously incubated with the antiserum anti-FOXL2 against human (Abcam, ab5096, USA) (1:10,000 dilution in blocking buffer) overnight at 4°C, underscoring the meticulous attention to detail in antibody incubation. After being washed twice with TBST buffer (10 mM Tris-HCl, 150 mM NaCl, 0.1% Tween 20, pH = 7.5) for 10 minutes each time, the membrane underwent further incubation with an alkaline phosphatase-conjugated goat anti-rabbit IgG secondary antibody (ABclonal, AS009, Wuhan, China) (1:1000 dilution in blocking buffer) at room temperature for 3 hours, emphasizing a methodical secondary antibody incubation process. Following a thorough washing with TBS buffer three times for 10 minutes, the target protein signal was meticulously visualized using 45 µL of nitroblue tetrazolium (NBT) (Sigma, USA) and 35 µL of 5-bromo-4-chloro-3-indolyl phosphate (BCIP) (Sigma, USA) incubated in 10 mL of TBS in the dark for 10 minutes, highlighting a precise approach. MTT assay for measuring cell proliferation Exponential growth KGN cells were seeded at 3×103 cells per well in a 96-well plate and incubated in a constant temperature incubator for 24 hours. The OD values of each well were recorded at 490nm on the microplate reader. The proliferation curve of cells was plotted with incubation time as the x-axis and OD values as the y-axis, and the cell proliferation rate was calculated. Cell proliferation rate = OD values of experimental groups A and B / OD values of group C. The experiment was repeated three times. Results Differential gene expression screening The data set GSE14407 was selected from the GEO database for analysis, based on the criteria of corrected P-value < 0.05 and |log 2 FC(fold change)|≥1, which were utilized to screen differentially expressed genes. According to the screening criteria, differential analysis was performed on the gene expression levels in ovarian cancer and normal ovarian samples, resulting in a total of 5145 differentially expressed genes, including 4,027 upregulated and 1,118 downregulated genes. Hierarchical clustering and volcano plots of differentially expressed genes were generated (shown in Fig. 1). Upon querying the NCBI database, the gene sequence analysis of FOXL2 revealed that the FOXL2 gene is approximately 2.7 Kb in length, located in the 3q22.3 region of the long arm of chromosome 3 (shown in Fig. 2A). It encodes a forkhead transcription factor consisting of 376 amino acids, with amino acids 52–142 forming a transmembrane structural domain protein (shown in Fig. 2B). cDNA PCR and gel electrophoresis results The total RNA of KGN cells was successfully extracted, and the OD values of each group of cells were measured by ultraviolet spectrophotometer. The OD values of KGN cells were all between 1.8 and 2.0, indicating good RNA purity. Gel imaging results clearly showed two bands of GAPDH and FOXL2, demonstrating the expression of the FOXL2 gene in both cell groups (shown in Fig. 3). Although reverse transcription PCR results indicated the expression of the FOXL2 gene in ovarian cancer cells, the author conducted real-time quantitative PCR to detect the expression of the FOXL2 gene in ovarian cancer cells. Detection of the FOXL2 gene via Real-time fluorescence quantitative PCR The fluorescence quantitative PCR amplification curves of the reference gene and target gene were satisfactory, with single-peaked melting curves indicating the absence of primer dimers. The relative mRNA expression levels of each group were calculated using the 2 −ΔΔCt method. The expression of FOXL2 mRNA in the JNK inhibitor group was lower than that in the reference group, with the lowest mRNA expression level of the FOXL2 gene observed at a final concentration of 1µM in the experimental group. This difference was statistically significant (P < 0.05), (shown in Fig. 4A). These findings suggest that, on the one hand, the FOXL2 gene is regulated by JNK and may be inhibited in its expression by a certain mechanism. The detection of FOXL2 by Western blot After 24 hours of treatment with the JNK inhibitor, protein extraction and gel electrophoresis were conducted on both the control group and the experimental group. The expression of FOXL2 protein was significantly reduced in the JNK inhibitor group. The expression level of FOXL2 protein in the experimental group decreased by 40% compared to the control group, with statistically significant differences ( P < 0.05), (shown in Fig. 4B). Cell scratch assay The two-dimensional migration experiment was conducted by treating cells with DMSO and JNK inhibitor (1µM) for 24 hours. Scratches were made on the culture dish, and the average migration distance of cells was evaluated after 24 hours. The migration ability of the JNK inhibitor group was weaker than that of the control group. JNK inhibits cell migration through FOXL2 (shown in Fig. 5A). The measuring Cell proliferation ability by the MTT assay The proliferation ability of KGN cells was measured at different time points of 24h, 48h, and 72h using optical microscopy and MTT assay. Through microscopic observation, the three groups of cells showed rapid proliferation at 24h, reaching approximately 80% coverage at 48h, with no significant differences observed among the groups at 72h under optical microscopy. The absorbance values measured at 24h were 0.3 ± 0.05 for the control group and 0.31 ± 0.08 for the experimental group, with P = 0.02; at 48h, the absorbance values were 0.70 ± 0.01 and 0.65 ± 0.05, with P = 0.03; at 72h, the absorbance values were 1.01 ± 0.04 and 0.75 ± 0.05, with P = 0.03. The above quantitative data underwent analysis of variance with multiple independent samples, showing a statistically significant difference with P < 0.05. The proliferation curves of KGN cells at different time points indicated that the values of the experimental group were lower than those of the control group, suggesting a lower proliferation capacity compared to the control group. MTT results showed that JNK inhibitor treatment inhibited the proliferation of KGN cells after 72h (shown in Fig. 5B). Discussion FOXL2 is involved in biological processes such as ovarian differentiation, cell apoptosis, stress response, and cell cycle regulation. FOXL2 is associated with sex determination, premature ovarian failure, infertility, and other related conditions (Fryns et al. 1993 ). The human FOXL2 gene is approximately 2.7 Kb long, located in the 3q2.02.3 region of the long arm of chromosome 3, encoding a forkhead transcription factor consisting of 376 amino acids. The amino acids at positions 52–142 form a transmembrane structural domain protein (Herman et al. 2024 , Llano et al. 2023 , Nagy et al. 2024 ). This study has found, through bioinformatics analysis and literature review, that FOXL2 may be regulated by the JNK signaling pathway. The experimental results of this study also indicate that JNK regulates FOXL2, thereby affecting the expression of GCTs. c-Jun N-terminal kinase (JNK) is a crucial member of the mitogen-activated protein kinase (MAPKs) family and serves as a major signaling pathway that induces cell apoptosis in response to cellular stress (Bildik et al. 2018 ). It plays a significant role in the process of apoptosis when cells are subjected to stressful stimuli (Wu et al. 2019b ). The JNK signaling pathway is divided into two parts: the classical pathway and the non-classical pathway. Both pathways activate MAP kinases through kinase phosphorylation cascades. Kinases MKK4 (MAP kinase kinase 4, a JNK kinase) and Hep (Hemipterous, MAPKK7, a JNK kinase) lead to the activation of JNK, a key protein kinase that regulates many physiological factors, including cell differentiation, apoptosis, stress response, and the occurrence and development of various human diseases. JNK plays a crucial role in these processes, making the JNK signaling pathway a critical regulatory target in normal and diseased cellular states (Abdelrahman et al. 2021 , Garg et al. 2021 , Kumar et al. 2015 , Shah et al. 2009 ). In summary, the FOXL2 gene is highly expressed in ovarian granulosa cells. FOXL2 can inhibit the proliferation of ovarian granulosa cells through JNK. It may serve as a novel tumor suppressor, holding potential value in the metastasis and recurrence of ovarian cancer. However, further research is required to deepen our understanding of its mechanisms. Declarations Author Contributions Nan Bai and Jun Wu: conceived and supervised this project Yuzhu Zhang: conducted cell experiments and performed the data extraction Yu Wang: analysis procedures and wrote the original manuscript Yuan Gu: helped with the data analysis and manuscript writing procedures Yang Liu and Guohua Liu: helped the data analysis procedures Statement of Ethics The article does not address ethical issues. Conflict of Interest Statement The authors declare no competing interests. Funding Sources This work was supported by Linyi Natural Science Foundation grant number 2022YX0053. References Abdelrahman KS, Hassan HA, Abdel-Aziz SA, Marzouk AA, Narumi A, Konno H, Abdel-Aziz M (2021) Jnk Signaling as a Target for Anticancer Therapy. Pharmacol Rep 73: 405–434. Barcellini A, Mangili G, Fodor A, Secondino S, Zerbetto F, Charalampopoulou A, Pignata S, Orlandi E, Bergamini A (2023) Granulosa Cell Tumors (Gcts) of the Ovary: What Is the Role of Radiotherapy? 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Cite Share Download PDF Status: Published Journal Publication published 09 Apr, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 29 Jul, 2024 Reviews received at journal 27 Jul, 2024 Reviewers agreed at journal 25 Jul, 2024 Reviews received at journal 09 Jul, 2024 Reviewers agreed at journal 02 Jul, 2024 Reviewers invited by journal 28 May, 2024 Editor assigned by journal 24 May, 2024 Editor invited by journal 24 May, 2024 Submission checks completed at journal 24 May, 2024 First submitted to journal 23 May, 2024 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. 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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-4469361","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":309949065,"identity":"05d70778-68ef-4be5-be4d-7e65016518c0","order_by":0,"name":"Yuzhu Zhang","email":"","orcid":"","institution":"LinYi People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yuzhu","middleName":"","lastName":"Zhang","suffix":""},{"id":309949066,"identity":"ff64ebcd-9bbb-467e-92ff-fb73ef546593","order_by":1,"name":"Yu Wang","email":"","orcid":"","institution":"LinYi People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Wang","suffix":""},{"id":309949067,"identity":"fca2f6fe-3915-4488-9715-cb5590e4dc31","order_by":2,"name":"Yuan Gu","email":"","orcid":"","institution":"LinYi People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yuan","middleName":"","lastName":"Gu","suffix":""},{"id":309949068,"identity":"aff95f01-d466-4016-8957-8771debc2a41","order_by":3,"name":"Yang Liu","email":"","orcid":"","institution":"LinYi People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Liu","suffix":""},{"id":309949069,"identity":"c98df595-bfd3-4a56-bb0d-ab8076cc85aa","order_by":4,"name":"Guohua Liu","email":"","orcid":"","institution":"LinYi People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Guohua","middleName":"","lastName":"Liu","suffix":""},{"id":309949070,"identity":"dd99009b-df78-4017-8859-0ffc82aaf088","order_by":5,"name":"Jun Wu","email":"","orcid":"","institution":"LinYi People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jun","middleName":"","lastName":"Wu","suffix":""},{"id":309949073,"identity":"07e662fd-e46f-4c13-a543-035d6ec6132e","order_by":6,"name":"Nan Bai","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1UlEQVRIiWNgGAWjYDACCQST8UFCRQ1pWpgNHpw5RpoWNsmHLcyEdfDPbj72ubLNLp+//4xZRWIDGwN/e3cCfkvuHEueebYt2XLGgTNmNxJ3yDBInDm7Aa8WA4kcY8bGtgMGDAd7gFrOsAFFcglpyf8M1iJ/mMesILGNmRgtOcxgLQbHeMwYiNIicSPNmLHhXLKB4Rm2YomEM8d4CPqFf0byY8aGMjsDufOHN378UVEjx9/ei18LGDCygUgOAxDJQ1g5GPwBEewPiFQ9CkbBKBgFIw0AAF4nRr16uiEEAAAAAElFTkSuQmCC","orcid":"","institution":"LinYi People's Hospital","correspondingAuthor":true,"prefix":"","firstName":"Nan","middleName":"","lastName":"Bai","suffix":""}],"badges":[],"createdAt":"2024-05-24 01:23:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4469361/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4469361/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-85439-8","type":"published","date":"2025-04-09T16:05:49+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":57849773,"identity":"6bab54ca-cce2-4090-90bf-03ebe539c528","added_by":"auto","created_at":"2024-06-06 11:36:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1578670,"visible":true,"origin":"","legend":"\u003cp\u003escreening of differentially expressed genes in ovarian cancer\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-4469361/v1/03f979aa287ea24b4b30c744.png"},{"id":57849775,"identity":"1c886907-a9df-4bd5-a53d-f61a81d157c2","added_by":"auto","created_at":"2024-06-06 11:36:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":828770,"visible":true,"origin":"","legend":"\u003cp\u003eThe gene sequence and protein structure domains of FOXL2\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-4469361/v1/5e67ec6f558ad7392fd0686f.png"},{"id":57850368,"identity":"406d4fb6-2e71-4254-aa4b-d25722eed9c4","added_by":"auto","created_at":"2024-06-06 11:44:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":438736,"visible":true,"origin":"","legend":"\u003cp\u003eResults of total mRNA 1% agarose gel electrophoresis in two groups of cells\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-4469361/v1/9e85c162403915d205aaac9d.png"},{"id":57849777,"identity":"99c73342-58d1-406d-ac64-248007822eef","added_by":"auto","created_at":"2024-06-06 11:36:44","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":591120,"visible":true,"origin":"","legend":"\u003cp\u003eA. After treatment with JNK inhibitors, the mRNA expression levels of FOXL2 were detected in KGN cells by qRT-PCR. B. Protein expression of FOXL2 After treatment with JNK inhibitors\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-4469361/v1/c40cf22c5966173ab2a6f385.png"},{"id":57850369,"identity":"b269cbaa-5162-4606-96b2-eced3310acd4","added_by":"auto","created_at":"2024-06-06 11:44:43","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1297459,"visible":true,"origin":"","legend":"\u003cp\u003eA. Cell scratch assay. B. Cell proliferation\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-4469361/v1/779563a99e34a1071cffdd31.png"},{"id":80558942,"identity":"0292f67e-4e0b-4120-85b2-a43858654143","added_by":"auto","created_at":"2025-04-14 16:17:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7402287,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4469361/v1/54f04da2-a0f8-4464-8925-fa1550100da5.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The impact of the FOXL2 gene on ovarian granulosa cells KGN","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOvarian granulosa cell tumors are related to the increase in ovarian mass, such as abdominal pain and bloating, and often present with endocrine manifestations of estrogen excess, such as increased menstruation or postmenopausal vaginal bleeding. Some patients may also have shown endometrial hyperplasia or malignancy (Barcellini et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Mangili et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Previous studies by the applicant have suggested that estrogen regulates FOXL2 to promote apoptosis in human ovarian granulosa cell tumors (Rosario et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2014\u003c/span\u003e, Wu et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e). Mutations in the FOXL2 gene have been found in 95\u0026ndash;97% of adult ovarian granulosa cell tumor patients, making FOXL2 gene mutation an important focus of research in ovarian granulosa cell tumors (Guerrieri et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Singh et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2014\u003c/span\u003e, Yanagida et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). To date, research has mainly focused on FOXL2 as a transcription factor regulating its downstream target genes, while relatively ignoring its own transcription and translation regulation (Caburet et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2012\u003c/span\u003e, Fuller et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, K\u0026ouml;bel et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2009\u003c/span\u003e, Tucker \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), which is a limitation in FOXL2 research. Therefore, this study aims to investigate the regulatory mechanisms of transcription and translation of the FOXL2 gene, incorporating FOXL2 into the overall regulatory network of the human body, enhancing its dual-role functions, and providing new insights for the prevention and treatment of clinically relevant diseases.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eMaterials\u003c/p\u003e \u003cp\u003eThe KGN granulosa cells were obtained from the Stem Cell Bank, Chinese Academy of Sciences; fetal bovine serum (FBS) and 1640 culture medium were purchased from Gibco; MEM and Trizol were obtained from Shanghai Biotech Co., Ltd.; pancreatin from BBI; rabbit anti-human FOXL2 antibody from Beijing Zhongshan Gold Bridge Biotechnology Co., Ltd.; DAB chromogenic reagent kit from Beijing Zhongshan Gold Bridge Biotechnology Co., Ltd.; RT-PCR kit and related experimental reagents from Takara, Japan; DNA Marker from TIANGEN; RIPA lysis buffer from Pulilai Gene Technology Co., Ltd.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eIn this study, we manually downloaded the matrix and platform files of dataset GSE34526. Using the GEOquery package in R version 4.3.2, we retrieved the expression matrix and clinical information. The matrix data was then subjected to standardization, and probe IDs were converted to gene names based on the platform file. For genes with the same name in the expression matrix, the average expression level was calculated. Batch effects were removed using the removeBatch function in the limma package. Differential expression genes between ovarian cancer and normal ovarian tissues in the training set were identified using the limma package. Selection criteria of |logFC|\u0026gt;1 and adj.P.Value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were applied. The pheatmap package was used to construct a hierarchical clustering heatmap of the top 100 differentially expressed genes, while the ggplot2 package was utilized to create a volcano plot of differentially expressed genes, with annotations for the top 20 differentially expressed gene names. Enrichment analysis of differentially expressed genes was conducted using the clusterProfiler package, including Gene Ontology analysis of biological processes, cellular components, and molecular functions. Visualization of the enrichment results was performed using the ggplot2 package.\u003c/p\u003e \u003cp\u003eCells Culture\u003c/p\u003e \u003cp\u003eKGN cells (Innovatbio, Beijing, China) were cultured in DMEM containing 10% FBS and 1% penicillin-streptomycin solution, maintained at 37\u0026deg;C in a 5% CO2 humidified cell culture incubator. When the cell confluence reached approximately 80%, cells were passaged using 0.05% Trypsin-EDTA and further utilized for experimental procedures.\u003c/p\u003e \u003cp\u003eThe detection of FOXL2 mRNA\u003c/p\u003e \u003cp\u003eThe cells were randomly divided into control and experimental groups. KGN cells were seeded in a 6-well cell culture plate and allowed to grow to a density of 70%-80%. Different concentrations of JNK inhibitor (0.1, 1, 5, 10, 50\u0026micro;M) were applied to the KGN cells for 12 hours, with DMSO used as the solvent control. RNA extraction was performed using Trizol (Solarbio, Beijing, China) from both total cells and ovarian tissue. RNA concentrations were measured by absorbance at 260nm using a micro-spectrophotometer (ThermoScientific, USA). RNA quality was assessed by electrophoresis in a 1% agarose gel. The cDNA was synthesized using a Fast Super RT Kit cDNA (with gDNase) (B002004018, Bioteke, Beijing, China). Primer pairs were designed for GAPDH (forward primer: 5\u0026prime;-AGCCAAAAGGGTCATCATCTCT-3\u0026prime;, reverse primer: 5\u0026prime;-AGGGGCCATCCACAGTCTT-3\u0026prime;) and FOXL2 (forward primer: 5\u0026prime;-TCACGCTGTCCGGCATCTACCA-3\u0026prime;, reverse primer: 5\u0026prime;-GCGGCACCTTGATGAAGCACTC-3\u0026prime;) using Primer version 5.0 software. Taq DNA Polymerase (9618080604, ABclonal, Wuhan, China) was used for PCR amplification. qRT-PCR was performed using the SYBR Green Real-time PCR Master Mix in a real-time PCR system (TOYOBO, Japan) following the manufacturer\u0026rsquo;s protocol. The qRT-PCR parameters were as follows: 94\u0026deg;C for 3 minutes, followed by 40 cycles of 94\u0026deg;C for 30 seconds, 60\u0026deg;C for 30 seconds, and a final extension at 72\u0026deg;C for 5 minutes. Data analysis was conducted using the formula: R\u0026thinsp;=\u0026thinsp;2^-[ΔCt sample - ΔCt control], where R represents the relative expression level, ΔCt represents the difference between the Ct of the gene and the average GAPDH in the experimental sample, and ΔCt control represents the difference between the Ct of the gene and the average GAPDH in the control sample. Experiments were carried out in triplicate with independent experimental samples.\u003c/p\u003e \u003cp\u003eProtein extraction and Western blotting\u003c/p\u003e \u003cp\u003eThe KGN cells and tissue utilized for protein extraction underwent grinding in radio-immunoprecipitation assay (RIPA) buffer (Solarbio, Beijing, China) supplemented with 1 mM phenylmethanesulfonyl fluoride (PMSF) and phosphatase inhibitors, symbolizing a meticulous approach to sample preparation. Following centrifugation at 10,000 g at 4℃ for 10 minutes, the protein-enriched supernatant was meticulously collected. The protein concentrations were determined using the Bradford method (Bradford \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1976\u003c/span\u003e), showcasing a commitment to precise quantification. Subsequently, protein samples (30 \u0026micro;g) were meticulously subjected to 10% sodium dodecyl sulfate\u0026ndash;polyacrylamide gel electrophoresis (SDS-PAGE) and precisely electro-transferred onto a 0.22 \u0026micro;M nitrocellulose membrane, illustrating a meticulous technique of protein separation and transfer. The resulting membranes were diligently blocked with a blocking buffer (2% BSA in TBS buffer: 10 mM Tris-HCl, 150 mM NaCl, pH\u0026thinsp;=\u0026thinsp;7.5) for 1 hour at room temperature, demonstrating a thorough experimental procedure. The membrane was then meticulously incubated with the antiserum anti-FOXL2 against human (Abcam, ab5096, USA) (1:10,000 dilution in blocking buffer) overnight at 4\u0026deg;C, underscoring the meticulous attention to detail in antibody incubation. After being washed twice with TBST buffer (10 mM Tris-HCl, 150 mM NaCl, 0.1% Tween 20, pH\u0026thinsp;=\u0026thinsp;7.5) for 10 minutes each time, the membrane underwent further incubation with an alkaline phosphatase-conjugated goat anti-rabbit IgG secondary antibody (ABclonal, AS009, Wuhan, China) (1:1000 dilution in blocking buffer) at room temperature for 3 hours, emphasizing a methodical secondary antibody incubation process. Following a thorough washing with TBS buffer three times for 10 minutes, the target protein signal was meticulously visualized using 45 \u0026micro;L of nitroblue tetrazolium (NBT) (Sigma, USA) and 35 \u0026micro;L of 5-bromo-4-chloro-3-indolyl phosphate (BCIP) (Sigma, USA) incubated in 10 mL of TBS in the dark for 10 minutes, highlighting a precise approach.\u003c/p\u003e \u003cp\u003eMTT assay for measuring cell proliferation\u003c/p\u003e \u003cp\u003eExponential growth KGN cells were seeded at 3\u0026times;103 cells per well in a 96-well plate and incubated in a constant temperature incubator for 24 hours. The OD values of each well were recorded at 490nm on the microplate reader. The proliferation curve of cells was plotted with incubation time as the x-axis and OD values as the y-axis, and the cell proliferation rate was calculated. Cell proliferation rate\u0026thinsp;=\u0026thinsp;OD values of experimental groups A and B / OD values of group C. The experiment was repeated three times.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eDifferential gene expression screening\u003c/p\u003e \u003cp\u003eThe data set GSE14407 was selected from the GEO database for analysis, based on the criteria of corrected P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and |log\u003csub\u003e2\u003c/sub\u003e FC(fold change)|\u0026ge;1, which were utilized to screen differentially expressed genes. According to the screening criteria, differential analysis was performed on the gene expression levels in ovarian cancer and normal ovarian samples, resulting in a total of 5145 differentially expressed genes, including 4,027 upregulated and 1,118 downregulated genes. Hierarchical clustering and volcano plots of differentially expressed genes were generated (shown in Fig.\u0026nbsp;1). Upon querying the NCBI database, the gene sequence analysis of FOXL2 revealed that the FOXL2 gene is approximately 2.7 Kb in length, located in the 3q22.3 region of the long arm of chromosome 3 (shown in Fig.\u0026nbsp;2A). It encodes a forkhead transcription factor consisting of 376 amino acids, with amino acids 52\u0026ndash;142 forming a transmembrane structural domain protein (shown in Fig.\u0026nbsp;2B).\u003c/p\u003e \u003cp\u003ecDNA PCR and gel electrophoresis results\u003c/p\u003e \u003cp\u003eThe total RNA of KGN cells was successfully extracted, and the OD values of each group of cells were measured by ultraviolet spectrophotometer. The OD values of KGN cells were all between 1.8 and 2.0, indicating good RNA purity. Gel imaging results clearly showed two bands of GAPDH and FOXL2, demonstrating the expression of the FOXL2 gene in both cell groups (shown in Fig.\u0026nbsp;3). Although reverse transcription PCR results indicated the expression of the FOXL2 gene in ovarian cancer cells, the author conducted real-time quantitative PCR to detect the expression of the FOXL2 gene in ovarian cancer cells.\u003c/p\u003e \u003cp\u003eDetection of the FOXL2 gene via Real-time fluorescence quantitative PCR\u003c/p\u003e \u003cp\u003eThe fluorescence quantitative PCR amplification curves of the reference gene and target gene were satisfactory, with single-peaked melting curves indicating the absence of primer dimers. The relative mRNA expression levels of each group were calculated using the 2\u003csup\u003e\u0026minus;ΔΔCt\u003c/sup\u003e method. The expression of FOXL2 mRNA in the JNK inhibitor group was lower than that in the reference group, with the lowest mRNA expression level of the FOXL2 gene observed at a final concentration of 1\u0026micro;M in the experimental group. This difference was statistically significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), (shown in Fig.\u0026nbsp;4A). These findings suggest that, on the one hand, the FOXL2 gene is regulated by JNK and may be inhibited in its expression by a certain mechanism.\u003c/p\u003e \u003cp\u003eThe detection of FOXL2 by Western blot\u003c/p\u003e \u003cp\u003eAfter 24 hours of treatment with the JNK inhibitor, protein extraction and gel electrophoresis were conducted on both the control group and the experimental group. The expression of FOXL2 protein was significantly reduced in the JNK inhibitor group. The expression level of FOXL2 protein in the experimental group decreased by 40% compared to the control group, with statistically significant differences (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), (shown in Fig.\u0026nbsp;4B).\u003c/p\u003e \u003cp\u003eCell scratch assay\u003c/p\u003e \u003cp\u003eThe two-dimensional migration experiment was conducted by treating cells with DMSO and JNK inhibitor (1\u0026micro;M) for 24 hours. Scratches were made on the culture dish, and the average migration distance of cells was evaluated after 24 hours. The migration ability of the JNK inhibitor group was weaker than that of the control group. JNK inhibits cell migration through FOXL2 (shown in Fig.\u0026nbsp;5A).\u003c/p\u003e \u003cp\u003eThe measuring Cell proliferation ability by the MTT assay\u003c/p\u003e \u003cp\u003eThe proliferation ability of KGN cells was measured at different time points of 24h, 48h, and 72h using optical microscopy and MTT assay. Through microscopic observation, the three groups of cells showed rapid proliferation at 24h, reaching approximately 80% coverage at 48h, with no significant differences observed among the groups at 72h under optical microscopy. The absorbance values measured at 24h were 0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05 for the control group and 0.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08 for the experimental group, with P\u0026thinsp;=\u0026thinsp;0.02; at 48h, the absorbance values were 0.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01 and 0.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05, with P\u0026thinsp;=\u0026thinsp;0.03; at 72h, the absorbance values were 1.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04 and 0.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05, with P\u0026thinsp;=\u0026thinsp;0.03. The above quantitative data underwent analysis of variance with multiple independent samples, showing a statistically significant difference with P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. The proliferation curves of KGN cells at different time points indicated that the values of the experimental group were lower than those of the control group, suggesting a lower proliferation capacity compared to the control group. MTT results showed that JNK inhibitor treatment inhibited the proliferation of KGN cells after 72h (shown in Fig.\u0026nbsp;5B).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eFOXL2 is involved in biological processes such as ovarian differentiation, cell apoptosis, stress response, and cell cycle regulation. FOXL2 is associated with sex determination, premature ovarian failure, infertility, and other related conditions (Fryns et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). The human FOXL2 gene is approximately 2.7 Kb long, located in the 3q2.02.3 region of the long arm of chromosome 3, encoding a forkhead transcription factor consisting of 376 amino acids. The amino acids at positions 52\u0026ndash;142 form a transmembrane structural domain protein (Herman et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, Llano et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Nagy et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study has found, through bioinformatics analysis and literature review, that FOXL2 may be regulated by the JNK signaling pathway. The experimental results of this study also indicate that JNK regulates FOXL2, thereby affecting the expression of GCTs. c-Jun N-terminal kinase (JNK) is a crucial member of the mitogen-activated protein kinase (MAPKs) family and serves as a major signaling pathway that induces cell apoptosis in response to cellular stress (Bildik et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). It plays a significant role in the process of apoptosis when cells are subjected to stressful stimuli (Wu et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019b\u003c/span\u003e). The JNK signaling pathway is divided into two parts: the classical pathway and the non-classical pathway. Both pathways activate MAP kinases through kinase phosphorylation cascades. Kinases MKK4 (MAP kinase kinase 4, a JNK kinase) and Hep (Hemipterous, MAPKK7, a JNK kinase) lead to the activation of JNK, a key protein kinase that regulates many physiological factors, including cell differentiation, apoptosis, stress response, and the occurrence and development of various human diseases. JNK plays a crucial role in these processes, making the JNK signaling pathway a critical regulatory target in normal and diseased cellular states (Abdelrahman et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Garg et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Kumar et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2015\u003c/span\u003e, Shah et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn summary, the FOXL2 gene is highly expressed in ovarian granulosa cells. FOXL2 can inhibit the proliferation of ovarian granulosa cells through JNK. It may serve as a novel tumor suppressor, holding potential value in the metastasis and recurrence of ovarian cancer. However, further research is required to deepen our understanding of its mechanisms.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNan Bai and Jun Wu: conceived and supervised this project\u003c/p\u003e\n\u003cp\u003eYuzhu Zhang: conducted cell experiments and performed the data extraction\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eYu Wang: analysis procedures and wrote the original manuscript\u003c/p\u003e\n\u003cp\u003eYuan Gu: helped with the data analysis and manuscript writing procedures Yang Liu and Guohua Liu: helped the data analysis procedures\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatement of Ethics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe article does not address ethical issues.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Sources\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Linyi Natural Science Foundation grant number 2022YX0053.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbdelrahman KS, Hassan HA, Abdel-Aziz SA, Marzouk AA, Narumi A, Konno H, Abdel-Aziz M (2021) Jnk Signaling as a Target for Anticancer Therapy. Pharmacol Rep 73: 405\u0026ndash;434.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarcellini A, Mangili G, Fodor A, Secondino S, Zerbetto F, Charalampopoulou A, Pignata S, Orlandi E, Bergamini A (2023) Granulosa Cell Tumors (Gcts) of the Ovary: What Is the Role of Radiotherapy? Crit Rev Oncol Hematol 181: 103889.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBildik G, Akin N, Senbabaoglu F, Esmalian Y, Sahin GN, Urman D, Karahuseyinoglu S, Ince U, Palaoglu E, Taskiran C, Arvas M, Guzel Y, Yakin K, Oktem O (2018) Endogenous C-Jun N-Terminal Kinase (Jnk) Activity Marks the Boundary between Normal and Malignant Granulosa Cells. Cell Death Dis 9: 421.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBradford MM (1976) A Rapid and Sensitive Method for the Quantitation of Microgram Quantities of Protein Utilizing the Principle of Protein-Dye Binding. Anal Biochem 72: 248\u0026ndash;254.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCaburet S, Georges A, L'H\u0026ocirc;te D, Todeschini AL, Benayoun BA, Veitia RA (2012) The Transcription Factor Foxl2: At the Crossroads of Ovarian Physiology and Pathology. Mol Cell Endocrinol 356: 55\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFryns JP, Str\u0026oslash;mme P, van den Berghe H (1993) Further Evidence for the Location of the Blepharophimosis Syndrome (Bpes) at 3q22.3-Q23. Clin Genet 44: 149\u0026ndash;151.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFuller PJ, Nguyen T, Alexiadis M, Chu S (2022) Foxl2(C134w): Much Ado About Something!(\u0026dagger;). J Pathol 256: 1\u0026ndash;3.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarg R, Kumariya S, Katekar R, Verma S, Goand UK, Gayen JR (2021) Jnk Signaling Pathway in Metabolic Disorders: An Emerging Therapeutic Target. Eur J Pharmacol 901: 174079.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuerrieri C, Hudacko R, Anderson P (2023) Composite Foxl2 Mutation-Positive Adult Granulosa Cell Tumor and Serous Borderline Tumor of the Ovary. Int J Gynecol Pathol 42: 500\u0026ndash;507.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHerman L, Amo A, Legois B, Di Carlo C, Veitia RA, Todeschini AL (2024) A Cellular Model Provides Insights into the Pathogenicity of the Oncogenic Foxl2 Somatic Variant P.Cys134trp. Br J Cancer.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eK\u0026ouml;bel M, Gilks CB, Huntsman DG (2009) Adult-Type Granulosa Cell Tumors and Foxl2 Mutation. Cancer Res 69: 9160\u0026ndash;9162.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKumar A, Singh UK, Kini SG, Garg V, Agrawal S, Tomar PK, Pathak P, Chaudhary A, Gupta P, Malik A (2015) Jnk Pathway Signaling: A Novel and Smarter Therapeutic Targets for Various Biological Diseases. Future Med Chem 7: 2065\u0026ndash;2086.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLlano E, Todeschini AL, Felipe-Medina N, Corte-Torres MD, Condezo YB, Sanchez-Martin M, L\u0026oacute;pez-Tamargo S, Astudillo A, Puente XS, Pendas AM, Veitia RA (2023) The Oncogenic Foxl2 C134w Mutation Is a Key Driver of Granulosa Cell Tumors. Cancer Res 83: 239\u0026ndash;250.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMangili G, Sigismondi C, Frigerio L, Candiani M, Savarese A, Giorda G, Lauria R, Tamberi S, Greggi S, Lorusso D (2013) Recurrent Granulosa Cell Tumors (Gcts) of the Ovary: A Mito-9 Retrospective Study. Gynecol Oncol 130: 38\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNagy A, Niu N, Ratner E, Hui P, Buza N (2024) Novel Foxl2 Mutation in an Ovarian Adult Granulosa Cell Tumor: Report of a Case with Diagnostic and Clinicopathologic Implications. 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Med Res Rev 39: 2082\u0026ndash;2104.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYanagida S, Anglesio MS, Nazeran TM, Lum A, Inoue M, Iida Y, Takano H, Nikaido T, Okamoto A, Huntsman DG (2017) Clinical and Genetic Analysis of Recurrent Adult-Type Granulosa Cell Tumor of the Ovary: Persistent Preservation of Heterozygous C.402c\u0026thinsp;\u0026gt;\u0026thinsp;G Foxl2 Mutation. PLoS One 12: e0178989.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"FOXL2, KGN, JNK, Granulosa Cells","lastPublishedDoi":"10.21203/rs.3.rs-4469361/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4469361/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose:\u003c/strong\u003e This study aimed to investigate the impact of JNK regulation on the FOXL2 gene in ovarian granulosa cells KGN.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials and methods:\u003c/strong\u003e Bioinformatics methods were employed to identify the main pathogenic gene FOXL2 in ovarian cancer. KGN cells were randomly divided into control and experimental groups, with the experimental group treated with different concentrations of JNK inhibitors (0.1, 1, 5, 10, 50 μM) and the control group receiving an equal volume of DMSO and incubated for 12 hours. The MTT assay was utilized to assess the proliferative capacity of KGN cells treated with JNK inhibitors. A cell scratch test was conducted to evaluate their migration ability. Cell RNA was extracted, reverse transcribed into cDNA, and qRT-PCR was employed to measure the mRNA expression levels of FOXL2. Protein was extracted and Western blot was used to determine the expression levels of FOXL2 protein.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e JNK inhibitors at concentrations of 1, 5, 10, and 50 μm all led to a decrease in FOXL2 expression. Conclusion: The FOXL2 gene exerts an influence on KGN cells through JNK regulation.\u003c/p\u003e","manuscriptTitle":"The impact of the FOXL2 gene on ovarian granulosa cells KGN","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-06 11:36:38","doi":"10.21203/rs.3.rs-4469361/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-29T06:38:15+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-27T17:30:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"198416240571449048511014136733492602797","date":"2024-07-25T14:57:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-09T16:48:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"1577334328744149749111618795441553931","date":"2024-07-02T22:38:28+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-28T13:12:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-24T14:50:41+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-05-24T13:53:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-24T13:52:48+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-05-24T01:20:40+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a6ea7455-680a-4cc5-b184-79ba00bf0b76","owner":[],"postedDate":"June 6th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":32748620,"name":"Biological sciences/Cancer"},{"id":32748621,"name":"Biological sciences/Immunology"},{"id":32748622,"name":"Health sciences/Diseases"}],"tags":[],"updatedAt":"2025-04-14T16:14:06+00:00","versionOfRecord":{"articleIdentity":"rs-4469361","link":"https://doi.org/10.1038/s41598-025-85439-8","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-04-09 16:05:49","publishedOnDateReadable":"April 9th, 2025"},"versionCreatedAt":"2024-06-06 11:36:38","video":"","vorDoi":"10.1038/s41598-025-85439-8","vorDoiUrl":"https://doi.org/10.1038/s41598-025-85439-8","workflowStages":[]},"version":"v1","identity":"rs-4469361","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4469361","identity":"rs-4469361","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}