Chloride intracellular channel protein 3 (CLIC3) is associated with poor prognosis, immune infiltration, and malignant phenotypes in ovarian cancer

Chloride intracellular channel protein 3 (CLIC3) is associated with poor prognosis, immune infiltration, and malignant phenotypes in 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 Chloride intracellular channel protein 3 (CLIC3) is associated with poor prognosis, immune infiltration, and malignant phenotypes in ovarian cancer Qiaoling Huang, Zhui Ke, Dongfang Cao, Che Huang, Qin Yu, Guoxin Wu, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9359311/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 12 You are reading this latest preprint version Abstract Objective To investigate the impact of CLIC3 expression on immune infiltration and prognosis in ovarian cancer and to assess the biological functions that CLIC3 may influence in the proliferation of ovarian cancer cells. Methods Various databases were utilized to compare CLIC3 expression in ovarian cancer, and the findings were validated using immunohistochemistry, Western blotting, and qPCR on ovarian cancer specimens and cell lines. The correlation between CLIC3 expression and clinicopathological stages was analyzed using logistic regression, while Kaplan-Meier analysis assessed its relation to patient prognosis. R programming language and Gene Set Enrichment Analysis (GSEA) were employed to explore the pathways that CLIC3 might be involved in for ovarian cancer. Furthermore, R was used to analyze the relationship between CLIC3 expression and immune cell infiltration in ovarian cancer tissues. Finally, the effect of knocking down CLIC3 expression on the proliferation of OVCAR3 cells was validated. Results CLIC3 was found to be overexpressed in ovarian cancer, significantly correlating with reduced overall survival and progression-free survival. Enrichment analysis revealed that CLIC3 is predominantly involved in pathways related to extracellular matrix (ECM) receptor interaction, focal adhesion, and cancer-related signaling pathways. Immune infiltration analysis demonstrated that CLIC3 expression in ovarian cancer is associated with mast cells, NK cells, γδ T cells, macrophages, immature dendritic cells (iDCs), NK56 CDdim cells, activated dendritic cells (aDCs), and T helper cells. Knockdown of CLIC3 expression significantly inhibited the proliferation of OVCAR3 cells. Conclusion CLIC3 is highly expressed in ovarian cancer tissues and may influence patient prognosis through interactions with the extracellular matrix, tumor immune infiltration, and cell proliferation. CLIC3 Ovarian cancer Immune infiltration Cell proliferation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Ovarian cancer is the second leading cause of cancer-related mortality among women, following cervical cancer 1 . The most common histological subtype is serous ovarian carcinoma. Although early-stage ovarian cancer can be highly curable, the absence of specific symptoms and effective early diagnostic methods hinders early detection. Consequently, most women are diagnosed at advanced stages (III/IV), which correlates with a poor prognosis; over 75% of patients with advanced ovarian cancer inevitably succumb to the disease prematurely 2 – 4 . Given the high heterogeneity of ovarian cancer, exploring precise and individualized predictive biomarkers at the molecular level is crucial for clinical diagnosis, treatment, and prognosis monitoring in ovarian cancer. Ion channels are considered highly effective pharmacological targets due to their involvement in various essential biological processes, such as oxidative stress, apoptosis, autophagy, and inflammation 5 . The chloride intracellular channel (CLIC) family in vertebrates comprises six evolutionarily conserved protein members (CLIC1-6) 6 . CLICs are widely distributed across different tissues and cell types. They exist in both soluble and membrane-bound forms within cells, exhibiting versatile functionalities: in their membrane-bound form, CLIC proteins act as ion channels, while in their soluble form, they function as redox enzymes involved in cellular protective mechanisms 7 . CLIC3 is primarily localized in the nucleus and, when expressed in cells, stimulates chloride ion conductance, potentially playing a role in the regulation of cell growth 8 . Moreover, CLIC3 exhibits varying degrees of aberrant expression in tumor cells, closely associated with tumor development, malignant progression, and prognosis, highlighting its significant clinical relevance 9 – 11 . However, the mechanistic role of CLIC3 in ovarian cancer (OV) remains unclear. This study aims to conduct a comprehensive bioinformatics analysis of CLIC3, accompanied by experimental validation, to provide a deeper theoretical basis for the diagnosis and treatment of ovarian cancer. Methods Data Sources and Methods Raw data was obtained from the Cancer Genome Atlas (TCGA) ( https://cancergenome.nih.gov/ ) and the Genotype-Tissue Expression (GTEx) database ( https://commonfund.nih.gov/GTEx ), specifically focusing on the TPM format of CLIC3 RNA sequencing data. This study complies with the publication guidelines set forth by TCGA ( https://cancergenome.nih.gov/publications/publicationguidelines ). All data utilized in this research are sourced from TCGA and GTEx, thus eliminating the need for ethical approval and informed consent from patients. Collection and Analysis of RNA Sequencing Data To assess CLIC3 expression levels across various cancers, CLIC3 was inputted into the Tumor Immune Estimation Resource (TIMER2, Ver.2) ( https://cistrome.shinyapps.io/timer ) within the "Gene DE" module. This analysis distinguished expression variations of CLIC3 in tumor tissues compared to adjacent normal tissues across different cancer types or specific cancer subtypes within the TCGA projects. For cancers lacking sufficient normal tissue samples or for which normal tissue supply was limited (including TCGA-OV), we utilized the Gene Expression Profiling Interactive Analysis (GEPIA2) database ( http://gepia2.cancer-pku.cn/#analysis ) to obtain matched normal tissue data from the GTEx dataset. This enabled the analysis of CLIC3 mRNA expression in ovarian cancer patients and its relationship with clinical staging. To evaluate the prognostic value of CLIC3 in predicting outcomes for ovarian cancer patients, we employed the R package “ROC” for analysis and “ggplot2” for visual representation. Collection and Analysis of Protein Expression Data The Human Protein Atlas (HPA) ( https://www.proteinatlas.org/ ) provides information on protein expression levels in normal and tumor tissues. In this study, we selected the immunohistochemistry antibody HPA005963 from the HPA database to compare the expression of CLIC3 protein in normal ovarian tissues and ovarian cancer tissues. Survival Prognosis Analysis To evaluate the prognostic value of CLIC3 in ovarian cancer patients, we used the Kaplan-Meier plotter database ( https://kmplot.com/analysis/ ) to stratify patients into high and low CLIC3 expression groups. We compared survival differences between these two groups to derive overall survival (OS) and progression-free survival (PFS) curves for CLIC3. Gene Enrichment Analysis To elucidate the biological functions of CLIC3, we utilized R programming and Gene Set Enrichment Analysis (GSEA) methodology to perform KEGG pathway enrichment analysis and Gene Ontology (GO) functional enrichment analysis for CLIC3 and its associated genes in ovarian cancer. The functional enrichment analysis covered three main aspects: Molecular Function (MF), Biological Process (BP), and Cellular Component (CC). Immune Infiltration Analysis To assess the correlation between immune cell infiltration and different CLIC3 mRNA expression groups, we employed the ssGSEA algorithm (Single Sample Gene Set Enrichment Analysis) from the R package GSVA. This method integrated the gene expression levels from published gene lists of 24 different immune cell types to quantify the relative level of tumor infiltration by immune cells. Statistical analyses were conducted using the Wilcoxon rank-sum test and Pearson correlation test. Western Blotting Western blot analysis was conducted to evaluate CLIC3 protein expression in ovarian cancer tissues and cell lines. Cells were lysed in a buffer containing protease inhibitors, and protein concentrations were determined using a BCA assay. Equal amounts of protein (30 µg) were separated by SDS-PAGE and transferred to PVDF membranes. After blocking with 5% non-fat milk, membranes were incubated overnight at 4°C with a primary antibody against CLIC3. Following washing, a secondary HRP-conjugated antibody was applied. Protein bands were detected using an ECL detection system, and band intensity was quantified using ImageJ software, normalizing against β-actin. Immunohistochemistry (IHC) Immunohistochemical staining was performed on FFPE ovarian cancer tissue sections. After deparaffinization and antigen retrieval, sections were blocked with hydrogen peroxide and serum. The primary CLIC3 antibody was incubated overnight at 4°C, followed by a biotinylated secondary antibody. Visualization was achieved using a DAB chromogen kit, and sections were counterstained with hematoxylin. CLIC3 expression was evaluated semi quantitatively by two independent pathologists. Quantitative PCR (qPCR) qPCR was used to measure CLIC3 mRNA levels in ovarian cancer samples. Total RNA was extracted using TRIzol, and cDNA was synthesized from 1 µg of RNA. qPCR was performed with SYBR Green Master Mix, following standard cycling conditions. The relative expression of CLIC3 was calculated using the 2^(-ΔΔCt) method, normalizing against GAPDH. Each sample was run in triplicate for accuracy. CLIC3 Knockdown Experiment OVCAR3 cells were cultured in RPMI-1640 medium supplemented with 10% fetal bovine serum and 0.01 mg/mL insulin. CLIC3-specific siRNA (sequence: CCTCAAGGGCGTACCTTTCAC-F1, GTCGCTGTCATAGAGCAGGA-R1, CGCCTCGTTACAGGGAGTC-F2, GGCACCGGGTTCTTGATGA-R2) or scrambled siRNA (control) was transfected into cells (2×10⁵ cells/well, seeded 24 h prior) using Lipofectamine™ RNAiMAX (Thermo Fisher) at 50 nM. Cells were harvested 48–72 h post-transfection. RNA was extracted with TRIzol (Invitrogen). mRNA levels were analyzed via qPCR. Following treatment, the cells were analyzed for proliferative and migratory capacities. For the scratch assay, confluent monolayers in 6-well plates were linearly scratched with a 200 µL sterile pipette tip. Detached cells were removed by PBS washing, and fresh medium was added. Migration progress was monitored at 48 h under a phase-contrast microscope (Nikon Eclipse Ti). Wound closure rates were quantified using ImageJ software (NIH) by measuring residual scratch area relative to initial wound. Data from three independent experiments are expressed as mean ± SD, analyzed by Student’s t-test (*p < 0.05, GraphPad Prism 9.0). Ethics approval and human specimens The analyses based on TCGA, GTEx, GEPIA2, TIMER2, HPA, and Kaplan–Meier Plotter were performed using publicly available datasets and complied with the corresponding database publication guidelines. For the clinical specimen-based experiments, this study was reviewed and approved by the Ethics Committee of Nanhai District People’s Hospital of Foshan, with ethics approval No. 2023366. Human ovarian cancer tissue samples were collected and used in accordance with institutional ethical requirements and the Declaration of Helsinki. Written informed consent was obtained from all participants. Data Processing and Statistical Analysis Data statistical analyses were conducted using GraphPad Prism version 9.4.1. Experimental results are presented as mean ± standard error of the mean (SEM), where n represents the number of independent samples in each experiment. After performing normality tests on the data, comparisons between two groups of counts were analyzed using the independent samples t-test. For comparisons involving multiple groups, one-way analysis of variance (ANOVA) was applied, followed by Bonferroni correction for post-hoc analysis. If the data failed to meet normality assumptions, non-parametric tests were utilized, with the Mann-Whitney U test for two groups and the Kruskal-Wallis test for multiple comparisons. A p-value of < 0.05 was considered statistically significant. Results mRNA expression levels of CLIC3 in different types of human tumors Analysis of CLIC3 mRNA expression across a pan-cancer dataset, derived from The Cancer Genome Atlas (TCGA), comprising 33 different cancer types, revealed aberrant expression of CLIC3 mRNA in numerous tumor tissues (Fig. 1 A). Integrative analysis with the GTEx database further indicated that CLIC3 expression was higher in ovarian cancer tissues compared to normal ovarian tissues (Fig. 1 B-a). Using the GEPIA database, we found that CLIC3 expression was significantly elevated in patients with advanced-stage (stage III/IV) ovarian cancer compared to those in stage II (P < 0.05, Fig. 1 B-b). To assess the diagnostic potential of CLIC3, we employed a receiver operating characteristic (ROC) curve analysis, demonstrating its diagnostic efficacy in differentiating ovarian cancer (OV) with an area under the curve (AUC) of 0.975. This indicates that CLIC3 possesses high sensitivity and specificity for OV diagnosis (Fig. 1 B-c). Additionally, qPCR validation was performed on the ovarian cancer cell line OVCAR3, where it was observed that CLIC3 mRNA levels were upregulated in OVCAR3 cells compared to normal ovarian epithelial cells (Fig. 1 C), corroborating our bioinformatics analysis results. Upregulation of CLIC3 protein in ovarian cancer tissues and OVCAR3 cells The analysis from the Human Protein Atlas (HPA) database shows that CLIC3 protein is predominantly localized in the nuclei of ovarian cancer (OV) cells, with its expression levels significantly higher in ovarian cancer tissues compared to normal ovarian tissues (Fig. 2 A). We collected 38 clinical paraffin-embedded tissue samples for immunohistochemistry (IHC) testing. The results revealed that CLIC3 protein expression is upregulated in ovarian cancer tissues compared to normal ovarian tissues and adjacent non-cancerous ovarian tissues (Fig. 2 B-ab). Additionally, Western blot (WB) analysis confirmed that CLIC3 protein expression is similarly upregulated in OVCAR3 cells compared to IOSE80 cells (Fig. 2 C-ab). Gene enrichment analysis predicts the function of CLIC3 Through Gene Set Enrichment Analysis (GSEA), we identified the signaling pathways associated with CLIC3 enrichment. The analysis revealed that CLIC3 is primarily enriched in pathways related to extracellular matrix (ECM) receptor interactions, focal adhesions, tumor-related pathways, Hedgehog (Hh) signaling, Wnt signaling, and immune-related pathways (Fig. 3 A). Gene Ontology (GO) analysis indicated that CLIC3 plays a significant role in biological processes such as extracellular matrix organization and extracellular structure organization. Its molecular functions are primarily associated with fibronectin binding, ECM structural component interactions, and heparin binding. The cellular components identified include collagen-containing extracellular matrix and the basement membrane (Fig. 3 B). These findings may contribute to a better understanding of the pathophysiological mechanisms underlying ovarian cancer (OV). Relationship between CLIC3 and immune infiltration We utilized the ssGSEA method from R packages and Spearman's statistical approach to investigate the link between CLIC3 expression levels and immune cell infiltration, as defined by 24 immune cell types listed in the Immunity paper 12 . Our analysis revealed that CLIC3 expression is associated with the infiltration of mast cells, NK cells, T gamma delta cells, macrophages, immature dendritic cells (iDC), as well as NK CD56^dim cells, activated dendritic cells (aDC), and T helper cells (Fig. 4 A-a). Further investigation demonstrated a positive correlation between CLIC3 expression and infiltration levels of mast cells (R = 0.259, P < 0.001), NK cells (R = 0.245, P < 0.001), T gamma delta cells (R = 0.201, P < 0.001), macrophages (R = 0.159, P = 0.002), iDC (R = 0.128, P = 0.012), and NK CD56^dim cells (R = 0.105, P = 0.040) (Fig. 4 A-b-g). Conversely, CLIC3 expression was negatively correlated with aDC cells (R=-0.105, P = 0.040) and T helper cells (R=-0.225, P < 0.001) (Fig. 4 A-hi). This prompted us to closely examine the relationship between CLIC3 expression levels and immune infiltration. Interestingly, when stratifying CLIC3 expression into high and low groups, we observed significant differences in immune cell infiltration levels, including mast cells, NK cells, T gamma delta cells, macrophages, aDC cells, and T helper cells (P < 0.05) (Figs. 4 B-a-f). However, no significant differences were detected in the infiltration of iDC cells and NK CD56^dim cells (Figs. 4 B-gh). Association of CLIC3 mRNA expression with poor prognosis in OV patients The Kaplan-Meier analysis revealed that ovarian cancer (OV) patients in the high CLIC3 mRNA expression group had significantly shorter overall survival (OS) compared to those with lower expression levels (P < 0.001, Fig. 5 A-a). Additionally, the progression-free survival (PFS) was also significantly reduced in the high CLIC3 expression group (P = 0.01, Fig. 5 B-b). Knockdown of CLIC3 expression inhibits proliferation and migration of OVCAR3 cells siRNA-mediated CLIC3 silencing achieved 40.4%±7.8% mRNA reduction in OVCAR3 cells at 48h post-transfection (Fig. 6 A). Functional analyses revealed: 1) Concurrent downregulation of proliferation markers, evidenced by 42.6%±4.9% Ki67 mRNA reduction (Fig. 6 B); 2)Impaired migratory capacity with 51.2%±5.3% fewer migrated cell (Fig. 6CD). These results demonstrate that CLIC3 knockdown significantly inhibits OVCAR3 cell proliferation and migration, indicating CLIC3's crucial role in ovarian cancer progression. Discussion Ovarian cancer (OV) is characterized by high malignancy and poor prognosis, primarily due to its subtle early symptoms, which pose significant challenges in diagnosis and treatment. Therefore, it is crucial to identify more accurate biomarkers for early detection and monitoring of disease progression. Fortunately, rapid advancements in genomic sequencing and integrated bioinformatics have paved the way for discovering molecular biomarkers with prognostic value in OV. Previous studies have associated abnormal CLIC3 expression with poor prognosis across various cancer types, highlighting it as a reliable biomarker for prognostic evaluation, and potentially as a therapeutic target. For instance, a study by Tasiopoulou et al. in 2015 utilized gene expression data from microarray datasets to compare expression profiles of CLIC1-6 between malignant pleural mesothelioma and normal tissue, finding significantly increased expression of CLIC3 and CLIC4 in tumors 13 . Other research has linked high expression of CLIC1 and CLIC3 with advanced cancer stages in hepatocellular carcinoma patients 14 . Mechanistically, CLIC3 is overexpressed in salivary gland mucoepidermoid carcinoma, promoting tumor progression 15 . In breast cancer, CLIC3 determines invasiveness and metastasis by controlling late-endosome-associated matrix metalloproteinase MT1-MMP, with high CLIC3 expression indicating poor prognosis in estrogen receptor-negative breast cancer 10 . Moreover, CLIC3 collaborates with Rab25 to enhance integrin recycling in late endosomes/lysosomes, driving cancer progression 9 . Intriguingly, research implications suggest that CLIC3, via glutathione-dependent oxidoreductase activity, drives cancer progression and can be secreted by cancer cells, being abundant in stromal and tumor compartments of aggressive ovarian cancer and correlating with adverse clinical outcomes 16 . These studies indicate that CLIC3 plays a promotive role in tumor progression, consistent with our findings. In our study, both CLIC3 mRNA and protein levels were significantly higher in OV tissues compared to normal tissues (P < 0.05), with ROC curve analysis confirming high diagnostic value. CLIC3 mRNA expression was significantly positively correlated with pathological staging in patients. Further analysis showed that patients with high CLIC3 mRNA expression had reduced overall survival and progression-free survival. These results position CLIC3 as a potential molecular target for prognosis assessment in OV. OV arises from intricate dysregulation of various genetic pathways and interactions with the tumor microenvironment, promoting tumorigenesis. Our Gene Set Enrichment Analysis (GSEA) indicated that high CLIC3 expression samples were primarily enriched in ECM-receptor interaction, focal adhesion, tumor-related, Hedgehog (Hh), Wnt, and immune-related signaling pathways, with ECM-receptor interaction pathway showing the highest enrichment score. Studies suggest that ECM-receptor interaction may play a role in the invasion process of ovarian cancer 17 , while focal adhesion pathways may affect OV initiation and migration 18 . Aberrant Hh signaling promotes OV development 19 , and Wnt signaling is crucial for the proliferation, migration, and invasion of ovarian cancer cells, contributing to the maintenance of ovarian cancer stem cell properties 20 , 21 . CLIC3 might contribute to the malignant behaviors of OV, including proliferation, migration, and invasion, through these pathways, playing a significant role in cancer stem cell maintenance. Nonetheless, the specific biological mechanisms require further experimental validation. Mounting evidence shows that immune cell infiltration influences tumor progression, recurrence, treatment response, and clinical outcomes 12 . One major reason for OV progression and treatment failure is the establishment of a complex immune suppressive network that inhibits anti-tumor immune activity, leading to immune escape and tumor-promotive immune cell activities. Immune escape represents a key phenotype by which tumor cells evade immune attacks, making targeted immunotherapy an emerging research focus in oncology. Thus, immune cells may be crucial participants in tumor pathology and potential therapeutic targets. Given the gaps in understanding the interactions between tumor and immune cells, elucidating these relationships could open new research directions for advanced immunotherapy in OV. Additionally, stromally infiltrating mast cells correlate with immune evasion in OV, resulting in poor prognosis and weak responses to immunotherapy 22 . Macrophage infiltration promotes tumor growth and metastasis through cytokine secretion, impacting OV patient prognosis 23 . Previous studies indicate that CLICs, acting on the potassium efflux-mitochondrial reactive oxygen species (ROS) axis, promote NLRP3 inflammasome activation, regulating inflammation, with dysregulation tied to tumorigenesis 24 . CLIC1's expression in activated macrophages influences inflammation by modulating phagosomal pH and proteolysis 25 , 26 . Research by Kanin Salao et al. has shown that CLIC1 regulates antigen processing and presentation by dendritic cells through phagosome acidification and proteolysis 27 . Yu et al. demonstrated that CLIC1, when fused with Mycobacterium tuberculosis heat shock protein 70, enhances antitumor immunity against OV 28 . CLIC4 possesses innate immune functions 24 , with CLIC4-deficient mice displaying resistance to LPS-induced septic shock 29 . Transcriptomic profiling of CLIC4-deficient hosts showed upregulated inflammatory pathways in primary tumors and premetastatic lung environments 30 . In patients with hepatitis B virus-related acute-on-chronic liver failure, CLIC3 is associated with macrophage polarization 31 . Collectively, these findings suggest that the CLIC family might play key roles in antitumor immunotherapy 32 . Specifically, CLIC3 could be pivotal in antitumor immunotherapeutic strategies. Our results support this hypothesis. Using the TIMER database, we evaluated potential links between CLIC3 expression and infiltration levels of 24 immune cell types. The data indicated correlations between CLIC3 expression and the infiltration of mast cells, NK cells, T gamma delta cells, macrophages, immature dendritic cells, and NK CD56^dim cells in OV. This suggests that CLIC3 overexpression may promote OV progression by affecting immune cell infiltration. CLIC3 knockdown significantly impaired OVCAR3 cell migration (51% reduction) and proliferation (43% Ki67 decrease), confirming its functional importance in ovarian cancer. While CLIC proteins are broadly implicated in membrane dynamics, our findings provide direct experimental evidence for CLIC3's specific role in maintaining malignant phenotypes. The mechanistic basis warrants further investigation through targeted pathway analyses. In conclusion, this study explores the diagnostic and prognostic value of CLIC3 in OV and its relationship with immune infiltration. However, there are limitations, such as the reliance solely on bioinformatics analysis without validation in clinical samples. Further research on CLIC3's biological functions and mechanisms in OV cell lines is warranted as a future research direction. Declarations Ethical approval The analyses based on publicly available datasets and online resources, including TCGA, GTEx, GEPIA2, TIMER2, the Human Protein Atlas, and Kaplan–Meier Plotter, were conducted in accordance with the relevant database guidelines and did not require additional ethical approval. For the clinical specimen-based experiments, this study was reviewed and approved by the Ethics Committee of Nanhai District People’s Hospital of Foshan ( Approval No. 2023366 ), and all procedures were performed in accordance with the Declaration of Helsinki. Consent to participate Written informed consent was obtained from all participants involved in the collection and use of clinical specimens in this study. Consent to publish Not applicable. No identifiable individual participant information is included in this manuscript. Author Contribution Q. Huang, Z. Ke, and D. Cao performed the functional and molecular biological experiments, analyzed the data, and drafted the manuscript. C. Huang, Q. Yu, G. Wu, Y. Ye, Y. Cai, and B. Yang collected ovarian cancer tissue specimens and related clinical data. Y. Huang, Z. Guan, and Q. Lv conceived the study, provided critical suggestions, supervised the project, and revised the manuscript. All authors read and approved of the final manuscript. Acknowledgments This work was supported by grants from Construction Project of Key Clinical Specialties in Guangdong Province: Department of Emergency Medicine (Yuewei Ban Yi Han [2024] No. 110) and Construction Project of High-level Key Medical Specialties during the 14th Five-Year Plan Period in Foshan City (FSGSP145075). Data Availability Data Availability Statement:The public datasets used in this study are available from the following sources: TCGA ovarian serous cystadenocarcinoma (TCGA-OV) at https://portal.gdc.cancer.gov/projects/TCGA-OV (Project ID: TCGA-OV; dbGaP accession: phs000178), and GTEx at https://gtexportal.org/home/gene/CLIC3 and https://gtexportal.org/home/tissue/Ovary (dbGaP accession: phs000424). Protein expression data for CLIC3 were obtained from the Human Protein Atlas at https://www.proteinatlas.org/ENSG00000169583-CLIC3 and https://www.proteinatlas.org/ENSG00000169583-CLIC3/tissue/ovary (gene identifier: ENSG00000169583). 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Supplementary Files CLIC3kDa.jpg actinkDa.png Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 13 May, 2026 Reviews received at journal 07 May, 2026 Reviews received at journal 02 May, 2026 Reviews received at journal 29 Apr, 2026 Reviewers agreed at journal 28 Apr, 2026 Reviewers agreed at journal 27 Apr, 2026 Reviewers agreed at journal 27 Apr, 2026 Reviewers invited by journal 27 Apr, 2026 Editor assigned by journal 27 Apr, 2026 Editor invited by journal 23 Apr, 2026 Submission checks completed at journal 21 Apr, 2026 First submitted to journal 21 Apr, 2026 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-9359311","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":633278320,"identity":"9ca1157d-d90b-4755-b425-590f95299928","order_by":0,"name":"Qiaoling Huang","email":"","orcid":"","institution":"The Second Affiliated Hospital of Guangdong Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qiaoling","middleName":"","lastName":"Huang","suffix":""},{"id":633278323,"identity":"5efd304a-0985-4ca1-9f48-0713c502ec4b","order_by":1,"name":"Zhui Ke","email":"","orcid":"","institution":"Tongji University","correspondingAuthor":false,"prefix":"","firstName":"Zhui","middleName":"","lastName":"Ke","suffix":""},{"id":633278325,"identity":"75aa44ad-eba4-4fd5-b47a-53ae8aa1c2dd","order_by":2,"name":"Dongfang Cao","email":"","orcid":"","institution":"Guangzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Dongfang","middleName":"","lastName":"Cao","suffix":""},{"id":633278326,"identity":"3402cde0-5a51-433a-9af3-c2fe679420cb","order_by":3,"name":"Che Huang","email":"","orcid":"","institution":"Hubei University of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Che","middleName":"","lastName":"Huang","suffix":""},{"id":633278328,"identity":"2d828ab2-f748-4e79-9501-3713a6aa617c","order_by":4,"name":"Qin Yu","email":"","orcid":"","institution":"South China University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Qin","middleName":"","lastName":"Yu","suffix":""},{"id":633278329,"identity":"9f9173d7-500c-4a79-ad8b-855cf297c69c","order_by":5,"name":"Guoxin Wu","email":"","orcid":"","institution":"South China University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Guoxin","middleName":"","lastName":"Wu","suffix":""},{"id":633278330,"identity":"b94fa14b-8b27-4ce8-a5b3-5bdad0e0ba74","order_by":6,"name":"Yi Ye","email":"","orcid":"","institution":"South China University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Yi","middleName":"","lastName":"Ye","suffix":""},{"id":633278331,"identity":"1ed6363e-171b-4758-b1a3-535ea1020936","order_by":7,"name":"Yanglin Cai","email":"","orcid":"","institution":"South China University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Yanglin","middleName":"","lastName":"Cai","suffix":""},{"id":633278332,"identity":"033c8a3e-932d-4c8d-8526-3ddfa9a3cbbe","order_by":8,"name":"Bin Yang","email":"","orcid":"","institution":"South China University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Bin","middleName":"","lastName":"Yang","suffix":""},{"id":633278333,"identity":"fbd94661-02a2-40f4-b717-fdfc7af35628","order_by":9,"name":"Yi Huang","email":"","orcid":"","institution":"South China University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Yi","middleName":"","lastName":"Huang","suffix":""},{"id":633278334,"identity":"fc901092-2188-4ffe-8268-2101412e6f96","order_by":10,"name":"Ziyun Guan","email":"","orcid":"","institution":"South China University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Ziyun","middleName":"","lastName":"Guan","suffix":""},{"id":633278335,"identity":"21427ede-437c-41bb-b62f-ac22815738e9","order_by":11,"name":"Quankun Lv","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwklEQVRIiWNgGAWjYJACxgYGBhkG9sbGhx9I0cLDwHO42ViCNC0S6W0CPMQo57uR/OzhzLY7PAY3H7YxSDDYyek2ENAieSPN3HBj2zMeg9uJbQ8KGJKNzQ4Q0GJwI8FM8mHbYR7J2YntBhIMBxK3EdaS/g2iZebBNgke4rTkmEluBGrhl2AkUovkmTdlkjPOAbXwJAID2YAIv/AdT98m2VN2WI6N/fjDhx8q7OQIamFAVWBASDmmllEwCkbBKBgFWAAA8NFEOdbYFMAAAAAASUVORK5CYII=","orcid":"","institution":"South China University of Technology","correspondingAuthor":true,"prefix":"","firstName":"Quankun","middleName":"","lastName":"Lv","suffix":""}],"badges":[],"createdAt":"2026-04-08 16:10:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9359311/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9359311/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108977249,"identity":"d07bc8e0-da68-44a7-974e-a3cd4fe691a1","added_by":"auto","created_at":"2026-05-11 11:31:04","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1530298,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003emRNA expression of the CLIC3 in various tumor types compared to normal adjacent tissues, with validation specific to ovarian cancer.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExpression levels of CLIC3 mRNA in normal ovarian tissues compared to cancerous tissues (\u003cstrong\u003eA\u003c/strong\u003e). Expression profile of CLIC3 mRNA across different clinical stages of ovarian cancer (\u003cstrong\u003eB\u003c/strong\u003e). ROC curve analysis demonstrating the diagnostic efficacy of CLIC3 for ovarian cancer (\u003cstrong\u003eC\u003c/strong\u003e). qPCR analysis of CLIC3 mRNA expression in OVCAR3 and IOSE80 cell lines (\u003cstrong\u003eD\u003c/strong\u003e).\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9359311/v1/d79a7f82c54de3594c236546.jpg"},{"id":108977559,"identity":"6e3c9c10-c9a5-403d-b380-f1f61531c155","added_by":"auto","created_at":"2026-05-11 11:32:06","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1558055,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExpression of CLIC3 protein in OV tissues and OVCAR3 cell line.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExpression of CLIC3 protein in OV tissues compared to normal ovarian tissues using HPA database (\u003cstrong\u003eA\u003c/strong\u003e). IHC analysis of CLIC3 in OV tissues compared to normal ovarian tissues and adjacent non-tumor tissue (\u003cstrong\u003eB\u003c/strong\u003e). Western blot analysis of CLIC3 expression in OVCAR3 and IOSE80 cell lines (\u003cstrong\u003eC\u003c/strong\u003e).\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9359311/v1/3e6678d3107ed3dc5cda45b0.jpg"},{"id":108978016,"identity":"08ee17ec-cf58-4ac8-aaea-373d675d8631","added_by":"auto","created_at":"2026-05-11 11:33:42","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1064379,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGene enrichment analysis of CLIC3 function.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRelated pathways of CLIC3 in ovarian cancer (\u003cstrong\u003eA\u003c/strong\u003e). GO functional annotation of CLIC3 and related genes (\u003cstrong\u003eB\u003c/strong\u003e).\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9359311/v1/648e7090e51f582881ac0c94.jpg"},{"id":108939373,"identity":"5486e5eb-aac9-43a6-b913-daff2280e8fc","added_by":"auto","created_at":"2026-05-11 05:07:26","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1412206,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of Immune Cell Infiltration Between High and Low CLIC3 Expression Groups.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLollipop plot illustrating CLIC3 expression levels among the 24 immune cell types (A). Positive correlation of CLIC3 with mast cells, NK cells, T gamma delta cells, macrophages, immature dendritic cells (iDC), and NK CD56^dim cells (B-G). Negative correlation of CLIC3 with activated dendritic cells (aDC) and T helper cells (H, I). Immune cell infiltration levels exhibiting significant differences among various cell types, including mast cells, NK cells, T gamma delta cells, macrophages, activated dendritic cells (aDC), and T helper cells (P\u0026lt;0.05) (J-O). No significant differences observed in the expression levels of immature dendritic cells (iDC) and NK CD56^dim cells (P, Q).\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9359311/v1/b77bf86317b24c7161841baa.jpg"},{"id":108978006,"identity":"c370621d-6a17-4949-add4-bd5dc526e964","added_by":"auto","created_at":"2026-05-11 11:33:41","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":247548,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRelationship between CLIC3 gene expression levels and OS and PFS.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9359311/v1/c0f4cd3197fd38c591209f65.jpg"},{"id":108939376,"identity":"9fedf4ac-151e-436f-a021-e18e6a3088a4","added_by":"auto","created_at":"2026-05-11 05:07:26","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1060201,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCLIC3 Knockdown Impacts Ovarian Cancer Cell Phenotype.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQuantitative PCR analysis of CLIC3 mRNA levels in OVCAR3 cells 48h post-transfection with two independent siRNAs (si-CLIC3-1 and si-CLIC3-2) (A). qPCR quantification of Ki67 mRNA levels in OVCAR3 cells 48h post-transfection with CLIC3-targeting siRNAs (si-CLIC3-1 and si-CLIC3-2) (B). Representative phase-contrast images of OVCAR3 scratch wound healing assays at 48h post-scratching. Cells were pre-transfected with si-NC, si-CLIC3-1 and si-CLIC3-2 for 48h prior to scratch creation (C). Quantification of cell-free area 48h post-scratch in OVCAR3 cells transfected with scrambled si-NC, si-CLIC3-1, or si-CLIC3-2 (D). Schematic Illustration of CLIC3 Functional Mechanism in Ovarian Cancer Progression (E).\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9359311/v1/2c7780a8c3dd852474de5afe.jpg"},{"id":108979844,"identity":"d8416551-e36c-4e2f-9852-1fedba93204f","added_by":"auto","created_at":"2026-05-11 12:01:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7115478,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9359311/v1/a9fbd854-89f9-49d5-948c-db19d58fc6e5.pdf"},{"id":108939369,"identity":"26c17c82-8f24-4e41-9986-bc17d244922d","added_by":"auto","created_at":"2026-05-11 05:07:26","extension":"jpg","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":185154,"visible":true,"origin":"","legend":"","description":"","filename":"CLIC3kDa.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9359311/v1/4f499b8beabddc30ac92f12c.jpg"},{"id":108978198,"identity":"714922eb-921a-4cfa-91b0-b633e2f477f7","added_by":"auto","created_at":"2026-05-11 11:34:54","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":747591,"visible":true,"origin":"","legend":"","description":"","filename":"actinkDa.png","url":"https://assets-eu.researchsquare.com/files/rs-9359311/v1/2bb04f3b84b89d8fa03e239b.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Chloride intracellular channel protein 3 (CLIC3) is associated with poor prognosis, immune infiltration, and malignant phenotypes in ovarian cancer","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOvarian cancer is the second leading cause of cancer-related mortality among women, following cervical cancer\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. The most common histological subtype is serous ovarian carcinoma. Although early-stage ovarian cancer can be highly curable, the absence of specific symptoms and effective early diagnostic methods hinders early detection. Consequently, most women are diagnosed at advanced stages (III/IV), which correlates with a poor prognosis; over 75% of patients with advanced ovarian cancer inevitably succumb to the disease prematurely\u003csup\u003e\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Given the high heterogeneity of ovarian cancer, exploring precise and individualized predictive biomarkers at the molecular level is crucial for clinical diagnosis, treatment, and prognosis monitoring in ovarian cancer. Ion channels are considered highly effective pharmacological targets due to their involvement in various essential biological processes, such as oxidative stress, apoptosis, autophagy, and inflammation\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. The chloride intracellular channel (CLIC) family in vertebrates comprises six evolutionarily conserved protein members (CLIC1-6) \u003csup\u003e6\u003c/sup\u003e. CLICs are widely distributed across different tissues and cell types. They exist in both soluble and membrane-bound forms within cells, exhibiting versatile functionalities: in their membrane-bound form, CLIC proteins act as ion channels, while in their soluble form, they function as redox enzymes involved in cellular protective mechanisms\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. CLIC3 is primarily localized in the nucleus and, when expressed in cells, stimulates chloride ion conductance, potentially playing a role in the regulation of cell growth\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Moreover, CLIC3 exhibits varying degrees of aberrant expression in tumor cells, closely associated with tumor development, malignant progression, and prognosis, highlighting its significant clinical relevance\u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. However, the mechanistic role of CLIC3 in ovarian cancer (OV) remains unclear. This study aims to conduct a comprehensive bioinformatics analysis of CLIC3, accompanied by experimental validation, to provide a deeper theoretical basis for the diagnosis and treatment of ovarian cancer.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Sources and Methods\u003c/h2\u003e \u003cp\u003eRaw data was obtained from the Cancer Genome Atlas (TCGA) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cancergenome.nih.gov/\u003c/span\u003e\u003cspan address=\"https://cancergenome.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and the Genotype-Tissue Expression (GTEx) database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://commonfund.nih.gov/GTEx\u003c/span\u003e\u003cspan address=\"https://commonfund.nih.gov/GTEx\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), specifically focusing on the TPM format of CLIC3 RNA sequencing data. This study complies with the publication guidelines set forth by TCGA (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cancergenome.nih.gov/publications/publicationguidelines\u003c/span\u003e\u003cspan address=\"https://cancergenome.nih.gov/publications/publicationguidelines\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). All data utilized in this research are sourced from TCGA and GTEx, thus eliminating the need for ethical approval and informed consent from patients.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCollection and Analysis of RNA Sequencing Data\u003c/h3\u003e\n\u003cp\u003eTo assess CLIC3 expression levels across various cancers, CLIC3 was inputted into the Tumor Immune Estimation Resource (TIMER2, Ver.2) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cistrome.shinyapps.io/timer\u003c/span\u003e\u003cspan address=\"https://cistrome.shinyapps.io/timer\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) within the \"Gene DE\" module. This analysis distinguished expression variations of CLIC3 in tumor tissues compared to adjacent normal tissues across different cancer types or specific cancer subtypes within the TCGA projects. For cancers lacking sufficient normal tissue samples or for which normal tissue supply was limited (including TCGA-OV), we utilized the Gene Expression Profiling Interactive Analysis (GEPIA2) database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://gepia2.cancer-pku.cn/#analysis\u003c/span\u003e\u003cspan address=\"http://gepia2.cancer-pku.cn/#analysis\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to obtain matched normal tissue data from the GTEx dataset. This enabled the analysis of CLIC3 mRNA expression in ovarian cancer patients and its relationship with clinical staging. To evaluate the prognostic value of CLIC3 in predicting outcomes for ovarian cancer patients, we employed the R package \u0026ldquo;ROC\u0026rdquo; for analysis and \u0026ldquo;ggplot2\u0026rdquo; for visual representation.\u003c/p\u003e\n\u003ch3\u003eCollection and Analysis of Protein Expression Data\u003c/h3\u003e\n\u003cp\u003eThe Human Protein Atlas (HPA) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.proteinatlas.org/\u003c/span\u003e\u003cspan address=\"https://www.proteinatlas.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) provides information on protein expression levels in normal and tumor tissues. In this study, we selected the immunohistochemistry antibody HPA005963 from the HPA database to compare the expression of CLIC3 protein in normal ovarian tissues and ovarian cancer tissues.\u003c/p\u003e\n\u003ch3\u003eSurvival Prognosis Analysis\u003c/h3\u003e\n\u003cp\u003eTo evaluate the prognostic value of CLIC3 in ovarian cancer patients, we used the Kaplan-Meier plotter database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://kmplot.com/analysis/\u003c/span\u003e\u003cspan address=\"https://kmplot.com/analysis/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to stratify patients into high and low CLIC3 expression groups. We compared survival differences between these two groups to derive overall survival (OS) and progression-free survival (PFS) curves for CLIC3.\u003c/p\u003e\n\u003ch3\u003eGene Enrichment Analysis\u003c/h3\u003e\n\u003cp\u003eTo elucidate the biological functions of CLIC3, we utilized R programming and Gene Set Enrichment Analysis (GSEA) methodology to perform KEGG pathway enrichment analysis and Gene Ontology (GO) functional enrichment analysis for CLIC3 and its associated genes in ovarian cancer. The functional enrichment analysis covered three main aspects: Molecular Function (MF), Biological Process (BP), and Cellular Component (CC).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eImmune Infiltration Analysis\u003c/h2\u003e \u003cp\u003eTo assess the correlation between immune cell infiltration and different CLIC3 mRNA expression groups, we employed the ssGSEA algorithm (Single Sample Gene Set Enrichment Analysis) from the R package GSVA. This method integrated the gene expression levels from published gene lists of 24 different immune cell types to quantify the relative level of tumor infiltration by immune cells. Statistical analyses were conducted using the Wilcoxon rank-sum test and Pearson correlation test.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eWestern Blotting\u003c/h3\u003e\n\u003cp\u003eWestern blot analysis was conducted to evaluate CLIC3 protein expression in ovarian cancer tissues and cell lines. Cells were lysed in a buffer containing protease inhibitors, and protein concentrations were determined using a BCA assay. Equal amounts of protein (30 \u0026micro;g) were separated by SDS-PAGE and transferred to PVDF membranes. After blocking with 5% non-fat milk, membranes were incubated overnight at 4\u0026deg;C with a primary antibody against CLIC3. Following washing, a secondary HRP-conjugated antibody was applied. Protein bands were detected using an ECL detection system, and band intensity was quantified using ImageJ software, normalizing against β-actin.\u003c/p\u003e\n\u003ch3\u003eImmunohistochemistry (IHC)\u003c/h3\u003e\n\u003cp\u003eImmunohistochemical staining was performed on FFPE ovarian cancer tissue sections. After deparaffinization and antigen retrieval, sections were blocked with hydrogen peroxide and serum. The primary CLIC3 antibody was incubated overnight at 4\u0026deg;C, followed by a biotinylated secondary antibody. Visualization was achieved using a DAB chromogen kit, and sections were counterstained with hematoxylin. CLIC3 expression was evaluated semi quantitatively by two independent pathologists.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eQuantitative PCR (qPCR)\u003c/h2\u003e \u003cp\u003eqPCR was used to measure CLIC3 mRNA levels in ovarian cancer samples. Total RNA was extracted using TRIzol, and cDNA was synthesized from 1 \u0026micro;g of RNA. qPCR was performed with SYBR Green Master Mix, following standard cycling conditions. The relative expression of CLIC3 was calculated using the 2^(-ΔΔCt) method, normalizing against GAPDH. Each sample was run in triplicate for accuracy.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eCLIC3 Knockdown Experiment\u003c/h2\u003e \u003cp\u003eOVCAR3 cells were cultured in RPMI-1640 medium supplemented with 10% fetal bovine serum and 0.01 mg/mL insulin. CLIC3-specific siRNA (sequence: CCTCAAGGGCGTACCTTTCAC-F1, GTCGCTGTCATAGAGCAGGA-R1, CGCCTCGTTACAGGGAGTC-F2, GGCACCGGGTTCTTGATGA-R2) or scrambled siRNA (control) was transfected into cells (2\u0026times;10⁵ cells/well, seeded 24 h prior) using Lipofectamine\u0026trade; RNAiMAX (Thermo Fisher) at 50 nM. Cells were harvested 48\u0026ndash;72 h post-transfection. RNA was extracted with TRIzol (Invitrogen). mRNA levels were analyzed via qPCR. Following treatment, the cells were analyzed for proliferative and migratory capacities. For the scratch assay, confluent monolayers in 6-well plates were linearly scratched with a 200 \u0026micro;L sterile pipette tip. Detached cells were removed by PBS washing, and fresh medium was added. Migration progress was monitored at 48 h under a phase-contrast microscope (Nikon Eclipse Ti). Wound closure rates were quantified using ImageJ software (NIH) by measuring residual scratch area relative to initial wound. Data from three independent experiments are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, analyzed by Student\u0026rsquo;s t-test (*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, GraphPad Prism 9.0).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eEthics approval and human specimens\u003c/h2\u003e \u003cp\u003eThe analyses based on TCGA, GTEx, GEPIA2, TIMER2, HPA, and Kaplan\u0026ndash;Meier Plotter were performed using publicly available datasets and complied with the corresponding database publication guidelines. For the clinical specimen-based experiments, this study was reviewed and approved by the Ethics Committee of Nanhai District People\u0026rsquo;s Hospital of Foshan, with ethics approval No. 2023366. Human ovarian cancer tissue samples were collected and used in accordance with institutional ethical requirements and the Declaration of Helsinki. Written informed consent was obtained from all participants.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eData Processing and Statistical Analysis\u003c/h2\u003e \u003cp\u003eData statistical analyses were conducted using GraphPad Prism version 9.4.1. Experimental results are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error of the mean (SEM), where n represents the number of independent samples in each experiment. After performing normality tests on the data, comparisons between two groups of counts were analyzed using the independent samples t-test. For comparisons involving multiple groups, one-way analysis of variance (ANOVA) was applied, followed by Bonferroni correction for post-hoc analysis. If the data failed to meet normality assumptions, non-parametric tests were utilized, with the Mann-Whitney U test for two groups and the Kruskal-Wallis test for multiple comparisons. A p-value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003emRNA expression levels of CLIC3 in different types of human tumors\u003c/h2\u003e \u003cp\u003eAnalysis of CLIC3 mRNA expression across a pan-cancer dataset, derived from The Cancer Genome Atlas (TCGA), comprising 33 different cancer types, revealed aberrant expression of CLIC3 mRNA in numerous tumor tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Integrative analysis with the GTEx database further indicated that CLIC3 expression was higher in ovarian cancer tissues compared to normal ovarian tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB-a). Using the GEPIA database, we found that CLIC3 expression was significantly elevated in patients with advanced-stage (stage III/IV) ovarian cancer compared to those in stage II (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB-b). To assess the diagnostic potential of CLIC3, we employed a receiver operating characteristic (ROC) curve analysis, demonstrating its diagnostic efficacy in differentiating ovarian cancer (OV) with an area under the curve (AUC) of 0.975. This indicates that CLIC3 possesses high sensitivity and specificity for OV diagnosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB-c). Additionally, qPCR validation was performed on the ovarian cancer cell line OVCAR3, where it was observed that CLIC3 mRNA levels were upregulated in OVCAR3 cells compared to normal ovarian epithelial cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC), corroborating our bioinformatics analysis results.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eUpregulation of CLIC3 protein in ovarian cancer tissues and OVCAR3 cells\u003c/h2\u003e \u003cp\u003eThe analysis from the Human Protein Atlas (HPA) database shows that CLIC3 protein is predominantly localized in the nuclei of ovarian cancer (OV) cells, with its expression levels significantly higher in ovarian cancer tissues compared to normal ovarian tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). We collected 38 clinical paraffin-embedded tissue samples for immunohistochemistry (IHC) testing. The results revealed that CLIC3 protein expression is upregulated in ovarian cancer tissues compared to normal ovarian tissues and adjacent non-cancerous ovarian tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB-ab). Additionally, Western blot (WB) analysis confirmed that CLIC3 protein expression is similarly upregulated in OVCAR3 cells compared to IOSE80 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC-ab).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eGene enrichment analysis predicts the function of CLIC3\u003c/h2\u003e \u003cp\u003eThrough Gene Set Enrichment Analysis (GSEA), we identified the signaling pathways associated with CLIC3 enrichment. The analysis revealed that CLIC3 is primarily enriched in pathways related to extracellular matrix (ECM) receptor interactions, focal adhesions, tumor-related pathways, Hedgehog (Hh) signaling, Wnt signaling, and immune-related pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Gene Ontology (GO) analysis indicated that CLIC3 plays a significant role in biological processes such as extracellular matrix organization and extracellular structure organization. Its molecular functions are primarily associated with fibronectin binding, ECM structural component interactions, and heparin binding. The cellular components identified include collagen-containing extracellular matrix and the basement membrane (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). These findings may contribute to a better understanding of the pathophysiological mechanisms underlying ovarian cancer (OV).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eRelationship between CLIC3 and immune infiltration\u003c/h2\u003e \u003cp\u003eWe utilized the ssGSEA method from R packages and Spearman's statistical approach to investigate the link between CLIC3 expression levels and immune cell infiltration, as defined by 24 immune cell types listed in the Immunity paper\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Our analysis revealed that CLIC3 expression is associated with the infiltration of mast cells, NK cells, T gamma delta cells, macrophages, immature dendritic cells (iDC), as well as NK CD56^dim cells, activated dendritic cells (aDC), and T helper cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-a). Further investigation demonstrated a positive correlation between CLIC3 expression and infiltration levels of mast cells (R\u0026thinsp;=\u0026thinsp;0.259, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), NK cells (R\u0026thinsp;=\u0026thinsp;0.245, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), T gamma delta cells (R\u0026thinsp;=\u0026thinsp;0.201, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), macrophages (R\u0026thinsp;=\u0026thinsp;0.159, P\u0026thinsp;=\u0026thinsp;0.002), iDC (R\u0026thinsp;=\u0026thinsp;0.128, P\u0026thinsp;=\u0026thinsp;0.012), and NK CD56^dim cells (R\u0026thinsp;=\u0026thinsp;0.105, P\u0026thinsp;=\u0026thinsp;0.040) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-b-g). Conversely, CLIC3 expression was negatively correlated with aDC cells (R=-0.105, P\u0026thinsp;=\u0026thinsp;0.040) and T helper cells (R=-0.225, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-hi). This prompted us to closely examine the relationship between CLIC3 expression levels and immune infiltration. Interestingly, when stratifying CLIC3 expression into high and low groups, we observed significant differences in immune cell infiltration levels, including mast cells, NK cells, T gamma delta cells, macrophages, aDC cells, and T helper cells (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB-a-f). However, no significant differences were detected in the infiltration of iDC cells and NK CD56^dim cells (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB-gh).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eAssociation of CLIC3 mRNA expression with poor prognosis in OV patients\u003c/h2\u003e \u003cp\u003eThe Kaplan-Meier analysis revealed that ovarian cancer (OV) patients in the high CLIC3 mRNA expression group had significantly shorter overall survival (OS) compared to those with lower expression levels (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-a). Additionally, the progression-free survival (PFS) was also significantly reduced in the high CLIC3 expression group (P\u0026thinsp;=\u0026thinsp;0.01, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB-b).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eKnockdown of CLIC3 expression inhibits proliferation and migration of OVCAR3 cells\u003c/h2\u003e \u003cp\u003esiRNA-mediated CLIC3 silencing achieved 40.4%\u0026plusmn;7.8% mRNA reduction in OVCAR3 cells at 48h post-transfection (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). Functional analyses revealed: 1) Concurrent downregulation of proliferation markers, evidenced by 42.6%\u0026plusmn;4.9% Ki67 mRNA reduction (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB); 2)Impaired migratory capacity with 51.2%\u0026plusmn;5.3% fewer migrated cell (Fig.\u0026nbsp;6CD). These results demonstrate that CLIC3 knockdown significantly inhibits OVCAR3 cell proliferation and migration, indicating CLIC3's crucial role in ovarian cancer progression.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOvarian cancer (OV) is characterized by high malignancy and poor prognosis, primarily due to its subtle early symptoms, which pose significant challenges in diagnosis and treatment. Therefore, it is crucial to identify more accurate biomarkers for early detection and monitoring of disease progression. Fortunately, rapid advancements in genomic sequencing and integrated bioinformatics have paved the way for discovering molecular biomarkers with prognostic value in OV. Previous studies have associated abnormal CLIC3 expression with poor prognosis across various cancer types, highlighting it as a reliable biomarker for prognostic evaluation, and potentially as a therapeutic target. For instance, a study by Tasiopoulou et al. in 2015 utilized gene expression data from microarray datasets to compare expression profiles of CLIC1-6 between malignant pleural mesothelioma and normal tissue, finding significantly increased expression of CLIC3 and CLIC4 in tumors\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Other research has linked high expression of CLIC1 and CLIC3 with advanced cancer stages in hepatocellular carcinoma patients\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Mechanistically, CLIC3 is overexpressed in salivary gland mucoepidermoid carcinoma, promoting tumor progression\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. In breast cancer, CLIC3 determines invasiveness and metastasis by controlling late-endosome-associated matrix metalloproteinase MT1-MMP, with high CLIC3 expression indicating poor prognosis in estrogen receptor-negative breast cancer\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Moreover, CLIC3 collaborates with Rab25 to enhance integrin recycling in late endosomes/lysosomes, driving cancer progression\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Intriguingly, research implications suggest that CLIC3, via glutathione-dependent oxidoreductase activity, drives cancer progression and can be secreted by cancer cells, being abundant in stromal and tumor compartments of aggressive ovarian cancer and correlating with adverse clinical outcomes\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. These studies indicate that CLIC3 plays a promotive role in tumor progression, consistent with our findings.\u003c/p\u003e \u003cp\u003eIn our study, both CLIC3 mRNA and protein levels were significantly higher in OV tissues compared to normal tissues (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with ROC curve analysis confirming high diagnostic value. CLIC3 mRNA expression was significantly positively correlated with pathological staging in patients. Further analysis showed that patients with high CLIC3 mRNA expression had reduced overall survival and progression-free survival. These results position CLIC3 as a potential molecular target for prognosis assessment in OV.\u003c/p\u003e \u003cp\u003eOV arises from intricate dysregulation of various genetic pathways and interactions with the tumor microenvironment, promoting tumorigenesis. Our Gene Set Enrichment Analysis (GSEA) indicated that high CLIC3 expression samples were primarily enriched in ECM-receptor interaction, focal adhesion, tumor-related, Hedgehog (Hh), Wnt, and immune-related signaling pathways, with ECM-receptor interaction pathway showing the highest enrichment score. Studies suggest that ECM-receptor interaction may play a role in the invasion process of ovarian cancer\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, while focal adhesion pathways may affect OV initiation and migration\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Aberrant Hh signaling promotes OV development\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e, and Wnt signaling is crucial for the proliferation, migration, and invasion of ovarian cancer cells, contributing to the maintenance of ovarian cancer stem cell properties\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. CLIC3 might contribute to the malignant behaviors of OV, including proliferation, migration, and invasion, through these pathways, playing a significant role in cancer stem cell maintenance. Nonetheless, the specific biological mechanisms require further experimental validation.\u003c/p\u003e \u003cp\u003eMounting evidence shows that immune cell infiltration influences tumor progression, recurrence, treatment response, and clinical outcomes\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. One major reason for OV progression and treatment failure is the establishment of a complex immune suppressive network that inhibits anti-tumor immune activity, leading to immune escape and tumor-promotive immune cell activities. Immune escape represents a key phenotype by which tumor cells evade immune attacks, making targeted immunotherapy an emerging research focus in oncology. Thus, immune cells may be crucial participants in tumor pathology and potential therapeutic targets. Given the gaps in understanding the interactions between tumor and immune cells, elucidating these relationships could open new research directions for advanced immunotherapy in OV.\u003c/p\u003e \u003cp\u003eAdditionally, stromally infiltrating mast cells correlate with immune evasion in OV, resulting in poor prognosis and weak responses to immunotherapy\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Macrophage infiltration promotes tumor growth and metastasis through cytokine secretion, impacting OV patient prognosis\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Previous studies indicate that CLICs, acting on the potassium efflux-mitochondrial reactive oxygen species (ROS) axis, promote NLRP3 inflammasome activation, regulating inflammation, with dysregulation tied to tumorigenesis\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. CLIC1's expression in activated macrophages influences inflammation by modulating phagosomal pH and proteolysis\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Research by Kanin Salao et al. has shown that CLIC1 regulates antigen processing and presentation by dendritic cells through phagosome acidification and proteolysis\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Yu et al. demonstrated that CLIC1, when fused with Mycobacterium tuberculosis heat shock protein 70, enhances antitumor immunity against OV\u003csup\u003e28\u003c/sup\u003e. CLIC4 possesses innate immune functions\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, with CLIC4-deficient mice displaying resistance to LPS-induced septic shock\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Transcriptomic profiling of CLIC4-deficient hosts showed upregulated inflammatory pathways in primary tumors and premetastatic lung environments\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. In patients with hepatitis B virus-related acute-on-chronic liver failure, CLIC3 is associated with macrophage polarization\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Collectively, these findings suggest that the CLIC family might play key roles in antitumor immunotherapy\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Specifically, CLIC3 could be pivotal in antitumor immunotherapeutic strategies. Our results support this hypothesis. Using the TIMER database, we evaluated potential links between CLIC3 expression and infiltration levels of 24 immune cell types. The data indicated correlations between CLIC3 expression and the infiltration of mast cells, NK cells, T gamma delta cells, macrophages, immature dendritic cells, and NK CD56^dim cells in OV. This suggests that CLIC3 overexpression may promote OV progression by affecting immune cell infiltration. CLIC3 knockdown significantly impaired OVCAR3 cell migration (51% reduction) and proliferation (43% Ki67 decrease), confirming its functional importance in ovarian cancer. While CLIC proteins are broadly implicated in membrane dynamics, our findings provide direct experimental evidence for CLIC3's specific role in maintaining malignant phenotypes. The mechanistic basis warrants further investigation through targeted pathway analyses. In conclusion, this study explores the diagnostic and prognostic value of CLIC3 in OV and its relationship with immune infiltration. However, there are limitations, such as the reliance solely on bioinformatics analysis without validation in clinical samples. Further research on CLIC3's biological functions and mechanisms in OV cell lines is warranted as a future research direction.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eEthical approval\u003c/h2\u003e \u003cp\u003eThe analyses based on publicly available datasets and online resources, including TCGA, GTEx, GEPIA2, TIMER2, the Human Protein Atlas, and Kaplan\u0026ndash;Meier Plotter, were conducted in accordance with the relevant database guidelines and did not require additional ethical approval. For the clinical specimen-based experiments, this study was reviewed and approved by the Ethics Committee of Nanhai District People\u0026rsquo;s Hospital of Foshan (\u003cb\u003eApproval No. 2023366\u003c/b\u003e), and all procedures were performed in accordance with the Declaration of Helsinki.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent to participate\u003c/strong\u003e \u003cp\u003eWritten informed consent was obtained from all participants involved in the collection and use of clinical specimens in this study.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent to publish\u003c/strong\u003e \u003cp\u003eNot applicable. No identifiable individual participant information is included in this manuscript.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eQ. Huang, Z. Ke, and D. Cao performed the functional and molecular biological experiments, analyzed the data, and drafted the manuscript. C. Huang, Q. Yu, G. Wu, Y. Ye, Y. Cai, and B. Yang collected ovarian cancer tissue specimens and related clinical data. Y. Huang, Z. Guan, and Q. Lv conceived the study, provided critical suggestions, supervised the project, and revised the manuscript. All authors read and approved of the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eThis work was supported by grants from Construction Project of Key Clinical Specialties in Guangdong Province: Department of Emergency Medicine (Yuewei Ban Yi Han [2024] No. 110) and Construction Project of High-level Key Medical Specialties during the 14th Five-Year Plan Period in Foshan City (FSGSP145075).\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData Availability Statement:The public datasets used in this study are available from the following sources: TCGA ovarian serous cystadenocarcinoma (TCGA-OV) at https://portal.gdc.cancer.gov/projects/TCGA-OV (Project ID: TCGA-OV; dbGaP accession: phs000178), and GTEx at https://gtexportal.org/home/gene/CLIC3 and https://gtexportal.org/home/tissue/Ovary (dbGaP accession: phs000424). Protein expression data for CLIC3 were obtained from the Human Protein Atlas at https://www.proteinatlas.org/ENSG00000169583-CLIC3 and https://www.proteinatlas.org/ENSG00000169583-CLIC3/tissue/ovary (gene identifier: ENSG00000169583). Public online analysis platforms used in this study included GEPIA2 (https://gepia2.cancer-pku.cn/), TIMER2.0 (https://compbio.cn/timer2/), and Kaplan\u0026ndash;Meier Plotter ovarian cancer module (https://kmplot.com/analysis/index.php?cancer=ovar\u0026amp;p=service); accession numbers are not applicable for these web-based analysis platforms.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLheureux S, Braunstein M, Oza AM. Epithelial ovarian cancer: Evolution of management in the era of precision medicine. 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CLIC1 regulates dendritic cell antigen processing and presentation by modulating phagosome acidification and proteolysis. Biol Open. 2016;5:620\u0026ndash;30. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1242/bio.018119\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1242/bio.018119\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\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":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dion","sideBox":"Learn more about [Discover Oncology](https://www.springer.com/12672)","snPcode":"","submissionUrl":"","title":"Discover Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"CLIC3, Ovarian cancer, Immune infiltration, Cell proliferation","lastPublishedDoi":"10.21203/rs.3.rs-9359311/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9359311/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo investigate the impact of CLIC3 expression on immune infiltration and prognosis in ovarian cancer and to assess the biological functions that CLIC3 may influence in the proliferation of ovarian cancer cells.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eVarious databases were utilized to compare CLIC3 expression in ovarian cancer, and the findings were validated using immunohistochemistry, Western blotting, and qPCR on ovarian cancer specimens and cell lines. The correlation between CLIC3 expression and clinicopathological stages was analyzed using logistic regression, while Kaplan-Meier analysis assessed its relation to patient prognosis. R programming language and Gene Set Enrichment Analysis (GSEA) were employed to explore the pathways that CLIC3 might be involved in for ovarian cancer. Furthermore, R was used to analyze the relationship between CLIC3 expression and immune cell infiltration in ovarian cancer tissues. Finally, the effect of knocking down CLIC3 expression on the proliferation of OVCAR3 cells was validated.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eCLIC3 was found to be overexpressed in ovarian cancer, significantly correlating with reduced overall survival and progression-free survival. Enrichment analysis revealed that CLIC3 is predominantly involved in pathways related to extracellular matrix (ECM) receptor interaction, focal adhesion, and cancer-related signaling pathways. Immune infiltration analysis demonstrated that CLIC3 expression in ovarian cancer is associated with mast cells, NK cells, γδ T cells, macrophages, immature dendritic cells (iDCs), NK56 CDdim cells, activated dendritic cells (aDCs), and T helper cells. Knockdown of CLIC3 expression significantly inhibited the proliferation of OVCAR3 cells.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eCLIC3 is highly expressed in ovarian cancer tissues and may influence patient prognosis through interactions with the extracellular matrix, tumor immune infiltration, and cell proliferation.\u003c/p\u003e","manuscriptTitle":"Chloride intracellular channel protein 3 (CLIC3) is associated with poor prognosis, immune infiltration, and malignant phenotypes in ovarian cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-11 05:07:21","doi":"10.21203/rs.3.rs-9359311/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-13T15:14:42+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-08T03:41:26+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-02T09:01:14+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-29T07:29:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"163173267048402927994829633753064203556","date":"2026-04-29T01:16:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"98856089905075521669133050642227667205","date":"2026-04-27T23:29:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"262656547652463310311017280579084830771","date":"2026-04-27T11:53:50+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-27T11:34:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-27T11:30:48+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-23T08:52:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-22T02:07:16+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Oncology","date":"2026-04-22T01:59:48+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dion","sideBox":"Learn more about [Discover Oncology](https://www.springer.com/12672)","snPcode":"","submissionUrl":"","title":"Discover Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"820b432a-4e64-4867-ac25-14ed5735d4e8","owner":[],"postedDate":"May 11th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-13T15:14:42+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-08T03:41:26+00:00","index":54,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-02T09:01:14+00:00","index":53,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-29T07:29:25+00:00","index":50,"fulltext":""},{"type":"reviewerAgreed","content":"163173267048402927994829633753064203556","date":"2026-04-29T01:16:19+00:00","index":49,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-13T15:28:37+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-11 05:07:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9359311","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9359311","identity":"rs-9359311","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}