VEGF-D and VEGF-C as Biomarkers in Endometrial Cancer: Association with Tumor Grade, Stage and Lymphovascular Invasion

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Endometrial cancer (EC) is the most common gynecologic malignancy in developed countries. While clinicopathological factors such as tumour grade, The International Federation of Gynecology and Obstetrics (FIGO) stage, and lymphovascular invasion (LVI) are established prognostic indicators, reliable preoperative molecular biomarkers remain lacking. Vascular endothelial growth factors C and D (VEGF-C, VEGF-D) regulate lymphangiogenesis, but their circulating levels and prognostic relevance in EC have not been well characterized. Methods. Serum VEGF-C and VEGF-D concentrations were measured using ELISA in 100 patients with histologically confirmed EC. Associations with tumour grade, FIGO stage, and LVI were analyzed using Mann–Whitney U and Kruskal–Wallis tests. Results. Serum VEGF-D levels were significantly elevated in patients with high-grade tumours ( p = 0.0172) and in those with confirmed LVI ( p = 0.0244). The highest VEGF-D concentrations were observed in FIGO stage II, with lower levels in stage IV disease ( p = 0.0205). No significant correlations were observed between VEGF-C levels and any clinicopathological parameters. Conclusions. Elevated VEGF-D levels are associated with unfavorable pathological features in EC, including poor differentiation and lymphovascular invasion, indicating its potential role as a non-invasive biomarker of tumour aggressiveness. Further prospective studies are needed to validate VEGF-D as a prognostic indicator in EC and to explore its clinical utility in risk stratification. endometrial cancer VEGF-C VEGF-D progression prognosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. BACKGROUND Endometrial cancer (EC) is the most common gynecologic malignancy among women, with a steadily rising incidence due to aging populations and the increasing prevalence of obesity and metabolic syndrome [ 1 ]. While most patients are diagnosed at an early stage and have a favorable prognosis, a subset present with or later develop aggressive disease characterized by high-grade histology, advanced stage, and lymphovascular invasion (LVI). All of these features are strongly associated with adverse outcomes [ 2 ]. Established prognostic factors include tumour grade, histological subtype, depth of myometrial invasion, and LVI. The relevance of molecular biomarkers in EC has expanded substantially with the introduction of genomic classification systems such as The Cancer Genome Atlas (TCGA) and the Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE) [ 3 ]. These frameworks provide prognostic information that complements traditional histopathological parameters [ 4 ]. However, current risk stratification continues to rely heavily on postoperative histopathological evaluation. Consequently, there is a critical need for non-invasive biomarkers that could facilitate preoperative risk assessment and guide individualized treatment decisions [ 5 , 6 ]. Among candidate biomarkers, vascular endothelial growth factors (VEGFs) have received particular attention. This family of signaling proteins comprises VEGF-A, VEGF-B, VEGF-C, VEGF-D, VEGF-E, VEGF-F, and placental growth factor, which exert their functions via binding to tyrosine kinase receptors VEGFR-1, VEGFR-2, and VEGFR-3 [ 7 ]. Of these, VEGF-C and VEGF-D are the principal regulators of lymphangiogenesis. VEGF-C primarily acts through VEGFR-3 to drive lymphatic vessel growth and has been implicated in nodal metastasis across multiple solid tumours, including prostate, lung, and ovarian cancer [ 8 , 9 ]. VEGF-D, in contrast, contributes not only to lymphangiogenesis via VEGFR-3 but also to angiogenesis by activating VEGFR-2, thereby influencing both lymphatic and vascular remodeling. Activation of downstream PI3K/Akt and MAPK pathways promotes lymphatic endothelial proliferation and migration. Tumour-derived VEGF-C and VEGF-D further dilate lymphatic vessels, increase lymphatic flow, and remodel draining lymph nodes, creating a permissive environment for regional and distant tumour dissemination [ 10 – 13 ]. Literature data indicate that VEGF-C plays a key role in activating the lymphatic endothelium, thereby promoting the penetration of tumour cells into lymphatic vessels. This occurs through the release of paracrine factors, including proteases and chemotactic agents, tyrosine kinase, which support tumour cell detachment from the primary site and enhance their migration and invasion. [ 14 ] [ 15 ] At the same time, there is a lack of shreds of evidence, proving the involvement of VEGF-D in this process. There is even less evidence of the diagnostic and prognostic value of these factors in EC, especially VEGF-D. Therefore, the aim of this study was to evaluate preoperative serum levels of VEGF-C and VEGF-D in patients with EC and to investigate their association with established clinicopathological features, including tumour grade, FIGO stage, and lymphovascular invasion. We hypothesized that elevated VEGF-D, but not VEGF-C, would correlate with markers of tumor aggressiveness. 2. METHODS 2.1. Study population A total of 100 women with histologically confirmed EC, aged 33–82 years (mean 64.8), were enrolled between 2019 and 2022 at the University Clinical Hospital No. 1 in Lublin, Poland. All patients underwent primary surgical management, including hysterectomy with or without lymphadenectomy and/or omentectomy, according to clinical indications. Inclusion criteria were histologically confirmed, untreated EC, age ≥ 18 years, and availability of preoperative blood samples. Exclusion criteria included history of other malignancies, prior neoadjuvant treatment, systemic inflammatory disorders, or hormone therapy. All participants provided written informed consent. The study was conducted in accordance with the Declaration of Helsinki and approved by the Bioethical Committee of the Medical University of Lublin (approvals KE-0254/139/06/2022 and KE-0254/272/2019). 2.2. Histopathological and clinical analysis Histological subtype, tumour grade, depth of myometrial invasion, LVI, and FIGO 2009 stage were assessed according to WHO and FIGO criteria [ 16 ]. Two independent pathologists reviewed all cases; discrepancies were resolved by consensus. 2.3. Sample collection and ELISA analysis Peripheral blood samples were collected preoperatively under fasting conditions, centrifuged within 2 hours, and serum aliquots were stored at − 80°C until analysis. Each sample was thawed only once before analysis. Serum levels of VEGF-C and VEGF-D were measured using commercially available ELISA kits (Cloud-Clone Corp., Katy, TX, USA; catalog numbers SEA145Hu and SEA146Hu). Each sample was analyzed in duplicate according to the manufacturer’s instructions. The detection limits were 15.6-1,000 pg/mL for both VEGF-C and VEGF-D. 2.4 Bioinformatic analysis Publicly available transcriptomic data were retrieved from the Gene Expression Omnibus (GEO) database ( https://www.ncbi.nlm.nih.gov/geo/ ), a public repository that archives and freely distributes high-throughput functional genomic datasets. The analysis was performed using the GSE17025 dataset, which includes gene expression profiles of normal endometrial tissue and tumor samples obtained from patients with endometrial carcinoma (EC) of early clinical stages (IA–IC). Expression levels of VEGF-C and VEGF-D mRNAs were compared across clinical stages, tumor grades, and histological subtypes of EC. 2.5. Statistical analysis Statistical analyses were performed using Statistica v.13.1 (StatSoft Inc., Tulsa, OK, USA). Continuous variables were tested for normality using the Shapiro–Wilk test and expressed as median (interquartile range) due to non-normal distribution. Group comparisons were performed using the Mann–Whitney U test (two groups) or Kruskal–Wallis test (≥ 3 groups), with post hoc pairwise comparisons when appropriate. A p -value < 0.05 was considered statistically significant. No formal sample size calculation was performed; the study was exploratory in nature and based on available cases. 3. RESULTS The graph shows the distribution of EC patients across different stages according to VEGF-C ( p = 0.695) and VEGF-D (p = 0.0954) expression levels. In both cases, no statistically significant differences were observed; however, a general trend can be noted for VEGF-D. 3.1. GEO analysis of VEGF-C and VEGF-D mRNA expression in tumor tissue samples depending on EC clinical features In this study, we first conducted a bioinformatic analysis of VEGF-C and VEGF-D mRNA expression in EC tissue samples using the GSE17025 dataset obtained from the Gene Expression Omnibus (GEO) database. The analysis demonstrated that lower tumor grade was associated with reduced VEGF-C mRNA expression levels (Fig. 2 ). Furthermore, significantly higher VEGF-C mRNA expression was observed in endometrioid endometrial carcinoma compared with serous endometrial carcinoma (Fig. 1 ). In contrast, the advanced EC stage showed a trend toward increased VEGF-D mRNA expression in tumor tissue; however, this difference did not reach statistical significance. 3.2. Patient characteristics The study cohort included 100 patients with histologically confirmed EC, with a mean age of 64.8 years (range 33–82). The majority of tumours were endometrioid adenocarcinomas (76%), while serous (4%), clear cell (3%), and undifferentiated (2%) subtypes were less frequent; histological subtype data were missing for 15 cases (Table 1 ). Tumour grade was available for 84 patients: G2 tumours predominated (58.3%), followed by G1 (31.0%) and G3 (10.7%). According to the FIGO 2009 classification, most cases were stage I (64%), with 6% stage II, 11% stage III, and 3% stage IV. Lymphovascular invasion (LVI) was present in 17 patients (17%), while myometrial invasion was identified in 75% of evaluable cases. Missing data were excluded from relevant analyses, and effective sample sizes are provided in Table 1 . Table 1 VEGF-C and VEGF-D serum levels depending on endometrial cancer patients’ clinical characteristics Criterion n = 100 VEGF-C VEGF-D Mean ± SEM p Mean ± SEM p Histological type Clear cell 3 473.2 ± 199.4 p = 0.7109 24.97 ± 4.656 p = 0.3048 Endometrial 76 282.3 ± 11.54 20.21 ± 1.175 Serous 4 256.7 ± 44.04 18.47 ± 1.424 Undifferentiated 2 322.7 ± 18,72 25.11 ± 5.458 Grade G1\KM 26 304.3 ± 17.00 p = 0.2975 17.04 ± 0.5543 p = 0.0172 G2 49 279.8 ± 19.41 20.96 ± 1.470 G3 9 300.2 ± 24.68 27.98 ± 5.329 Stage І 64 283.3 ± 12.14 p = 0.8961 19.20 ± 0.9623 p = 0.0205 II 6 281.2 ± 41.95 38.09 ± 11.03 III 11 325.8 ± 63.03 20.21 ± 1.236 IV 3 244.6 ± 42.75 15.60 ± 0.7178 Myometrial invasion No 75 304.7 ± 23.86 p = 0.4867 17.39 ± 1.003 p = 0.5006 Yes 9 285.3 ± 13.91 20.63 ± 1.195 Lymphovascular invasion No 17 300.8 ± 13.23 p = 0.6019 18.03 ± 0.5946 p = 0.0244 Yes 48 322.5 ± 40.88 25.28 ± 3.917 3.3. Serum VEGF levels and clinicopathological parameters The median serum concentration of VEGF-C was 303.1 pg/mL (range: 91.8–869.2 pg/mL), while the median VEGF-D level was 17.5 pg/mL (range: 11.5–101.6 pg/mL). VEGF-D levels were significantly higher in G3 compared to G1 tumours (median: 28.0 vs. 17.0 pg/mL; p = 0.0172), corresponding to an approximately 65% increase (Fig. 4 , Table 1 ). No significant differences in VEGF-C concentrations were observed across tumour grades ( p = 0.2975). VEGF-D levels varied significantly by FIGO stage ( p = 0.0205), with the highest median levels observed in stage II (38.1 pg/mL) and the lowest in stage IV (15.6 pg/mL) (Fig. 5 , Table 1 ). VEGF-C showed no significant variation by stage ( p = 0.8961). Patients with LVI demonstrated nearly 50% higher VEGF-D levels compared with those without LVI (median: 25.3 vs. 18.0 pg/mL; p = 0.0244) (Fig. 6 ). No association was observed for VEGF-C ( p = 0.6019). No significant associations were found between VEGF-D or VEGF-C levels and histological subtype or the presence of myometrial invasion (all p > 0.3). Exploratory analyses did not reveal correlations between VEGF levels and patient age. Taken together, our results demonstrate that serum VEGF-D, but not VEGF-C, is significantly elevated in patients with high-grade tumours, FIGO stage II disease, and in the presence of lymphovascular invasion. In particular, VEGF-D levels were nearly 50% higher in patients with LVI compared to those without, and peaked in stage II disease before declining in stage IV. These findings support the role of VEGF-D as a potential circulating marker of early invasive and aggressive tumour biology. 4. DISCUSSION This study demonstrates a significant association between elevated serum VEGF-D levels and adverse clinicopathological features in EC, including high tumour grade, lymphovascular invasion (LVI), and FIGO stage II disease. In contrast, VEGF-C levels did not correlate with any of the analyzed parameters. To our knowledge, this is the first study to report a statistically significant relationship between circulating VEGF-D and LVI in EC, suggesting a potential role for VEGF-D as a non-invasive biomarker of tumour invasiveness. Given the increasing importance of molecular risk stratification in EC (e.g., ProMisE or TCGA classification), integrating serum biomarkers such as VEGF-D with genomic profiles may improve prognostic accuracy and guide treatment strategies. Several processes enable tumour cells to reach the lymphatic system: progressive enlargement of the tumour mass, activation of lymphangiogenesis by VEGF factors, infiltration of nearby tissues by individual cancer cells, and coordinated migration of tumour cell groups through tissue barriers [ 17 ]. LVI is therefore a key mechanism by which cancer cells penetrate vessel walls, while VEGF-mediated lymphangiogenesis further facilitates dissemination. In EC, LVI is a recognized marker of tumour aggressiveness and is incorporated into modern risk stratification systems [ 18 ]. Indeed, previous studies have demonstrated its impact on progression-free survival [ 19 – 22 ]. Several studies have reported a role for VEGF-C in regional and distant metastasis [ 23 – 24 ], and LVI has been suggested not only as a predictor of locoregional recurrence, but also as a marker of distant metastasis [ 25 – 27 ]. Following VEGF-C/D–induced angiogenesis and lymphangiogenesis, vascular density increases; after epithelial–mesenchymal transition, tumour cells invade lymphatic or blood vessels, enabling further dissemination [ 28 – 29 ]. In our study, serum VEGF-D was significantly associated with LVI, suggesting its dual role in both lymphangiogenesis and angiogenesis. According to Huang et al., VEGF-C mRNA expression correlated with retroperitoneal lymph node metastases [ 30 ], supporting the hypothesis that VEGF-C may mark lymphatic spread in EC. Moreover, some studies have shown that metastatic cells may migrate from lymph nodes to distant organs [ 31 – 32 ], and the concept of a pre-metastatic niche within lymph nodes—first described nearly two decades ago [ 33 – 34 ]—further highlights the biological plausibility of our findings. Lymphovascular invasion, lymphatic vessel density, and VEGF-C expression have all been linked with lymph node metastasis in EC [ 35 ]. However, in our cohort, no association was found between serum VEGF-C and LVI, suggesting that serum VEGF-D may be the more relevant circulating biomarker. VEGF-D expression patterns further support our findings. Girling et al. showed that VEGF-D overexpression enlarged myometrial lymphatic vessels without stimulating new lymphangiogenesis and also promoted enlargement of endometrial blood vessels [ 36 ]. In our study, VEGF-D levels were highest in FIGO stage II disease, which may reflect an early phase of stromal and lymphatic invasion prior to lymph node dissemination. This could represent a clinically relevant window for intervention. Previous studies also support VEGF-D as an independent prognostic factor in EC, with associations to myometrial invasion and nodal metastasis [ 37 ], as well as tumour grade [ 38 ]. Similarly, cohort studies have demonstrated strong correlations between high-grade tumours and LVI [ 39 – 40 ]. The biological plausibility of these findings lies in VEGF-D binding to VEGFR-3, which promotes lymphangiogenesis, vessel dilation, and remodeling [ 41 ]. VEGF-D can also activate VEGFR-2, contributing to angiogenesis and intratumoral vascular permeability [ 42 ]. The discrepancy between VEGF-C and VEGF-D observed in our study may be explained by differences between tissue and serum expression, or by sampling in relation to disease progression [ 43 – 45 ]. From a clinical perspective, serum VEGF-D testing appears feasible, cost-effective, and technically straightforward. As a non-invasive biomarker, it could improve preoperative risk stratification, particularly in centers without access to molecular classification. Identifying patients with elevated VEGF-D may support more aggressive staging or adjuvant therapy decisions. In addition, VEGF-D may represent a future target for therapy in biologically aggressive EC subtypes. Several limitations must be acknowledged. The sample size was relatively small, limiting statistical power and generalizability. Patient heterogeneity, incomplete clinicopathological data, and the retrospective design may have introduced bias. The absence of molecular classification data (e.g., TCGA or ProMisE) precludes integration with genomic risk models, and the lack of survival analysis limits assessment of the prognostic value of VEGF-C and VEGF-D. Prospective, multicenter studies with larger and molecularly stratified cohorts are needed to validate VEGF-D as a prognostic biomarker, clarify its relationship with survival and metastasis, and determine its added value when combined with molecular classifiers. 5. CONCLUSIONS This study demonstrates, for the first time, a significant association between circulating VEGF-D and key pathological features of EC, including FIGO stage, tumour grade, and lymphovascular invasion, while no such associations were observed for VEGF-C. These findings suggest that VEGF-D may serve as a practical, non-invasive biomarker for identifying patients at higher risk of aggressive disease. The observed elevation of VEGF-D in FIGO stage II may represent a biologically active phase of early invasion, offering a potential therapeutic window for intervention. Integration of VEGF-D with existing molecular classifiers could further enhance risk stratification. Larger, prospective, and molecularly stratified studies are warranted to validate its clinical utility and to explore its role as a potential therapeutic target. Abbreviations EC - Endometrial cancer FIGO - The International Federation of Gynecology and Obstetrics VEGF-C, VEGF-D - Vascular endothelial growth factors C and D TCGA The Cancer Genome Atlas ProMisE - Proactive Molecular Risk Classifier for Endometrial Cancer GEO - Gene Expression Omnibus ELISA – Enzyme-linked immunosorbent assay LVI – Lymphovascular invasion Declarations Ethics approval and consent to participate The study was conducted in accordance with the Declaration of Helsinki and approved by the Bioethical Committee of the Medical University of Lublin (approvals KE-0254/139/06/2022 and KE-0254/272/2019). All participants provided written informed consent Consent for publication Not applicable Availability of data and materials The datasets used and analyzed during the current study are available from the corresponding author on reasonable request. Competing Interests The authors declare no competing interests. Funding The study was supported by the Medical University of Lublin, Poland, DS 129 grant for statutory activities and National Centre for Research and Development (NCBiR) PerMed/IV/35/ECLAI/2022. Authors' contributions OK: Writing – original draft, review & editing, Resources, Visualization, Methodology; OM: Writing – original draft, review & editing, Data curation, Methodology; MK: Writing – review & editing, Investigation, Methodology; VA: Writing – review & editing, Data curation, Methodology, Investigation; VM: Writing – review & editing, Data curation, Methodology, Investigation, Validation; MB: Writing – original draft, review & editing, Conceptualization, Formal Analysis; Data curation, Funding acquisition, Project administration, Resources, Supervision; MOL: Writing – original draft, review & editing, Conceptualization, Methodology, Investigation, Project administration; Supervision, Validation. 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Nat Rev Cancer. 2021;21(5):325–38. https://doi.org/10.1038/s41568-021-00332-6 . Hlophe YN, Joubert AM. (2022, December 1). Vascular endothelial growth factor-C in activating vascular endothelial growth factor receptor-3 and chemokine receptor-4 in melanoma adhesion. Journal of Cellular and Molecular Medicine . John Wiley and Sons Inc. https://doi.org/10.1111/jcmm.17571 García-Pérez O, Melgar-Vilaplana L, Sifaoui I, Śmietańska A, Córdoba-Lanús E, Fernández-de-Misa R. VEGFC Gene Expression Is Associated with Tumor Progression and Disease-Free Survival in Cutaneous Squamous Cell Carcinoma. Int J Mol Sci. 2024;25(1). https://doi.org/10.3390/ijms25010379 . Liang B, Li Y. (2014, February 23). Prognostic significance of VEGF-C expression in patients with breast cancer: A meta-analysis. Iranian Journal of Public Health . Iranian Journal of Public Health. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 28 Mar, 2026 Reviewers agreed at journal 03 Mar, 2026 Reviewers invited by journal 24 Feb, 2026 Editor assigned by journal 25 Dec, 2025 Editor invited by journal 22 Dec, 2025 Submission checks completed at journal 19 Dec, 2025 First submitted to journal 19 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8320695","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":596463512,"identity":"56b87e20-414e-4460-858a-c1c67354bef6","order_by":0,"name":"Olha Khoptiana","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA60lEQVRIiWNgGAWjYBACAwSTuY2BoQJZALcWxgYIkxGo5QxUywGitQARYS3m7L3HH/PU3JFnYG9se/Bz3mFj8wbeg48/4NFi2XMusZnn2DPDBp6D7Ya92w6byRzgSzbA67AbOYbNPGyHGRskEtskeLcdtpFg4DGTIKzl32F7kBbJv3PAWsx/ENTC23Y4EaRFmrfhsBnIFvwhduZc4sy5fYeT23gOtknLHEs3lmDmMZY4g0/L8d4DH958O2zbz958TPJNjbXhDPYeww8VeLQwMPAwMPEAKTa4ADNe5RAtjD8IKhoFo2AUjIIRDQCChE9YvpRQhQAAAABJRU5ErkJggg==","orcid":"","institution":"National Cancer Institute","correspondingAuthor":true,"prefix":"","firstName":"Olha","middleName":"","lastName":"Khoptiana","suffix":""},{"id":596463513,"identity":"d7bfa095-5362-44f8-9d52-1dbe77d8a826","order_by":1,"name":"Oleksandr Mushii","email":"","orcid":"","institution":"R.E. Kavetsky Institute of Experimental Pathology, Oncology and Radiobiology","correspondingAuthor":false,"prefix":"","firstName":"Oleksandr","middleName":"","lastName":"Mushii","suffix":""},{"id":596463515,"identity":"38c56bad-fe2e-42ec-bc0a-0f6c68becebf","order_by":2,"name":"Michal Karasek","email":"","orcid":"","institution":"Independent Unit of Medicinal Biology, Department of Toxicology, Medical University of Lublin","correspondingAuthor":false,"prefix":"","firstName":"Michal","middleName":"","lastName":"Karasek","suffix":""},{"id":596463516,"identity":"25dbc7c9-9ea8-4699-8d4a-53cf977b53c1","order_by":3,"name":"Vivek Adhikary","email":"","orcid":"","institution":"Integrative Multiomics Lab, School of Bio Sciences and Technology, Vellore Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Vivek","middleName":"","lastName":"Adhikary","suffix":""},{"id":596463517,"identity":"90524357-84db-43e9-9a21-7300678ccc05","order_by":4,"name":"Vijayachitra Modhukur","email":"","orcid":"","institution":"Department of Obstetrics and Gynecology, Institute of Clinical Medicine, University of Tartu","correspondingAuthor":false,"prefix":"","firstName":"Vijayachitra","middleName":"","lastName":"Modhukur","suffix":""},{"id":596463519,"identity":"6aa58363-44b9-4497-8517-4db4497f6435","order_by":5,"name":"Marcin Bobinski","email":"","orcid":"","institution":"Independent Laboratory of Translational Medicine, Department of Clinical Genetics, Medical University of Lublin","correspondingAuthor":false,"prefix":"","firstName":"Marcin","middleName":"","lastName":"Bobinski","suffix":""},{"id":596463520,"identity":"d6f1c1fd-aea4-491d-85b3-39b939d85ee5","order_by":6,"name":"Marta Ostrowska-Lesko","email":"","orcid":"","institution":"Independent Laboratory of Translational Medicine, Department of Clinical Genetics, Medical University of Lublin","correspondingAuthor":false,"prefix":"","firstName":"Marta","middleName":"","lastName":"Ostrowska-Lesko","suffix":""}],"badges":[],"createdAt":"2025-12-09 18:53:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8320695/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8320695/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104398318,"identity":"b28c3571-cc61-46d1-bd66-7bb13ca8eb72","added_by":"auto","created_at":"2026-03-11 12:01:39","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":99927,"visible":true,"origin":"","legend":"\u003cp\u003eThe distribution of EC patients across different stages according to VEGF-C and VEGF-D expression levels.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8320695/v1/5c5ee756d44ddb14e66bfdde.png"},{"id":103590686,"identity":"a21f589a-cc51-496b-a1bb-d49477518b7b","added_by":"auto","created_at":"2026-02-27 12:06:57","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":325422,"visible":true,"origin":"","legend":"\u003cp\u003eTumor-associated mRNA VEGF-C (A-C) and VEGF-D ( D-F) expression levels depending on clinical stage (A, D), tumor grade (D, E), and histological type (C, F) in endometrial cancer tissue. Data are presented as median with interquartile range. According to the GSE17025 dataset.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8320695/v1/985be1e1588487ca443eb013.png"},{"id":103590681,"identity":"cd76a7cc-b262-4c76-9248-26ae61a784a6","added_by":"auto","created_at":"2026-02-27 12:06:55","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":48853,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 4.\u003c/strong\u003e Serum VEGF-D concentrations according to tumor grade in endometrial cancer patients (\u003cem\u003ep\u003c/em\u003e = 0.0172). Data are presented as median with interquartile range.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8320695/v1/caa43561d8284bbfbc79501f.png"},{"id":103590685,"identity":"37ec0022-6313-4325-a3f6-160594e58c94","added_by":"auto","created_at":"2026-02-27 12:06:56","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":46581,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 5.\u003c/strong\u003e Serum VEGF-D levels according to clinical stage in endometrial cancer patients (\u003cem\u003ep\u003c/em\u003e = 0.0205). Data are presented as median with interquartile range.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8320695/v1/c1eab9259a5758f6c61b6105.png"},{"id":103590683,"identity":"97e6c5cd-47dd-40bd-b841-7dbf796bcc1d","added_by":"auto","created_at":"2026-02-27 12:06:55","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":40771,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 6.\u003c/strong\u003e Serum VEGF-D levels according to lymphovascular invasion in endometrial cancer patients (\u003cem\u003ep \u003c/em\u003e= 0.0244). Data are presented as median with interquartile range.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8320695/v1/f310309486627cf9fee40b7d.png"},{"id":104407477,"identity":"721f217f-4286-487b-b0fc-c149a4f95899","added_by":"auto","created_at":"2026-03-11 12:38:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1261869,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8320695/v1/68fad405-41a7-49cb-a903-af3bc1bb88b1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"VEGF-D and VEGF-C as Biomarkers in Endometrial Cancer: Association with Tumor Grade, Stage and Lymphovascular Invasion","fulltext":[{"header":"1. BACKGROUND","content":"\u003cp\u003eEndometrial cancer (EC) is the most common gynecologic malignancy among women, with a steadily rising incidence due to aging populations and the increasing prevalence of obesity and metabolic syndrome [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. While most patients are diagnosed at an early stage and have a favorable prognosis, a subset present with or later develop aggressive disease characterized by high-grade histology, advanced stage, and lymphovascular invasion (LVI). All of these features are strongly associated with adverse outcomes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Established prognostic factors include tumour grade, histological subtype, depth of myometrial invasion, and LVI.\u003c/p\u003e \u003cp\u003eThe relevance of molecular biomarkers in EC has expanded substantially with the introduction of genomic classification systems such as The Cancer Genome Atlas (TCGA) and the Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. These frameworks provide prognostic information that complements traditional histopathological parameters [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. However, current risk stratification continues to rely heavily on postoperative histopathological evaluation. Consequently, there is a critical need for non-invasive biomarkers that could facilitate preoperative risk assessment and guide individualized treatment decisions [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAmong candidate biomarkers, vascular endothelial growth factors (VEGFs) have received particular attention. This family of signaling proteins comprises VEGF-A, VEGF-B, VEGF-C, VEGF-D, VEGF-E, VEGF-F, and placental growth factor, which exert their functions via binding to tyrosine kinase receptors VEGFR-1, VEGFR-2, and VEGFR-3 [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Of these, VEGF-C and VEGF-D are the principal regulators of lymphangiogenesis. VEGF-C primarily acts through VEGFR-3 to drive lymphatic vessel growth and has been implicated in nodal metastasis across multiple solid tumours, including prostate, lung, and ovarian cancer [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. VEGF-D, in contrast, contributes not only to lymphangiogenesis via VEGFR-3 but also to angiogenesis by activating VEGFR-2, thereby influencing both lymphatic and vascular remodeling. Activation of downstream PI3K/Akt and MAPK pathways promotes lymphatic endothelial proliferation and migration. Tumour-derived VEGF-C and VEGF-D further dilate lymphatic vessels, increase lymphatic flow, and remodel draining lymph nodes, creating a permissive environment for regional and distant tumour dissemination [\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eLiterature data indicate that VEGF-C plays a key role in activating the lymphatic endothelium, thereby promoting the penetration of tumour cells into lymphatic vessels. This occurs through the release of paracrine factors, including proteases and chemotactic agents, tyrosine kinase, which support tumour cell detachment from the primary site and enhance their migration and invasion. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] At the same time, there is a lack of shreds of evidence, proving the involvement of VEGF-D in this process. There is even less evidence of the diagnostic and prognostic value of these factors in EC, especially VEGF-D. Therefore, the aim of this study was to evaluate preoperative serum levels of VEGF-C and VEGF-D in patients with EC and to investigate their association with established clinicopathological features, including tumour grade, FIGO stage, and lymphovascular invasion. We hypothesized that elevated VEGF-D, but not VEGF-C, would correlate with markers of tumor aggressiveness.\u003c/p\u003e"},{"header":"2. METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study population\u003c/h2\u003e \u003cp\u003eA total of 100 women with histologically confirmed EC, aged 33\u0026ndash;82 years (mean 64.8), were enrolled between 2019 and 2022 at the University Clinical Hospital No. 1 in Lublin, Poland. All patients underwent primary surgical management, including hysterectomy with or without lymphadenectomy and/or omentectomy, according to clinical indications. Inclusion criteria were histologically confirmed, untreated EC, age\u0026thinsp;\u0026ge;\u0026thinsp;18 years, and availability of preoperative blood samples. Exclusion criteria included history of other malignancies, prior neoadjuvant treatment, systemic inflammatory disorders, or hormone therapy. All participants provided written informed consent. The study was conducted in accordance with the Declaration of Helsinki and approved by the Bioethical Committee of the Medical University of Lublin (approvals KE-0254/139/06/2022 and KE-0254/272/2019).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Histopathological and clinical analysis\u003c/h2\u003e \u003cp\u003eHistological subtype, tumour grade, depth of myometrial invasion, LVI, and FIGO 2009 stage were assessed according to WHO and FIGO criteria [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Two independent pathologists reviewed all cases; discrepancies were resolved by consensus.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Sample collection and ELISA analysis\u003c/h2\u003e \u003cp\u003ePeripheral blood samples were collected preoperatively under fasting conditions, centrifuged within 2 hours, and serum aliquots were stored at \u0026minus;\u0026thinsp;80\u0026deg;C until analysis. Each sample was thawed only once before analysis. Serum levels of VEGF-C and VEGF-D were measured using commercially available ELISA kits (Cloud-Clone Corp., Katy, TX, USA; catalog numbers SEA145Hu and SEA146Hu). Each sample was analyzed in duplicate according to the manufacturer\u0026rsquo;s instructions. The detection limits were 15.6-1,000 pg/mL for both VEGF-C and VEGF-D.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Bioinformatic analysis\u003c/h2\u003e \u003cp\u003ePublicly available transcriptomic data were retrieved from the Gene Expression Omnibus (GEO) database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/geo/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/geo/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), a public repository that archives and freely distributes high-throughput functional genomic datasets. The analysis was performed using the GSE17025 dataset, which includes gene expression profiles of normal endometrial tissue and tumor samples obtained from patients with endometrial carcinoma (EC) of early clinical stages (IA\u0026ndash;IC). Expression levels of VEGF-C and VEGF-D mRNAs were compared across clinical stages, tumor grades, and histological subtypes of EC.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Statistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using Statistica v.13.1 (StatSoft Inc., Tulsa, OK, USA). Continuous variables were tested for normality using the Shapiro\u0026ndash;Wilk test and expressed as median (interquartile range) due to non-normal distribution. Group comparisons were performed using the Mann\u0026ndash;Whitney U test (two groups) or Kruskal\u0026ndash;Wallis test (\u0026ge;\u0026thinsp;3 groups), with post hoc pairwise comparisons when appropriate. A \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. No formal sample size calculation was performed; the study was exploratory in nature and based on available cases.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. RESULTS","content":"\u003cp\u003eThe graph shows the distribution of EC patients across different stages according to VEGF-C (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.695) and VEGF-D (p\u0026thinsp;=\u0026thinsp;0.0954) expression levels. In both cases, no statistically significant differences were observed; however, a general trend can be noted for VEGF-D.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e3.1. GEO analysis of VEGF-C and VEGF-D mRNA expression in tumor tissue samples depending on EC clinical features\u003c/p\u003e \u003cp\u003eIn this study, we first conducted a bioinformatic analysis of VEGF-C and VEGF-D mRNA expression in EC tissue samples using the GSE17025 dataset obtained from the Gene Expression Omnibus (GEO) database. The analysis demonstrated that lower tumor grade was associated with reduced VEGF-C mRNA expression levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Furthermore, significantly higher VEGF-C mRNA expression was observed in endometrioid endometrial carcinoma compared with serous endometrial carcinoma (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In contrast, the advanced EC stage showed a trend toward increased VEGF-D mRNA expression in tumor tissue; however, this difference did not reach statistical significance.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Patient characteristics\u003c/h2\u003e \u003cp\u003eThe study cohort included 100 patients with histologically confirmed EC, with a mean age of 64.8 years (range 33\u0026ndash;82). The majority of tumours were endometrioid adenocarcinomas (76%), while serous (4%), clear cell (3%), and undifferentiated (2%) subtypes were less frequent; histological subtype data were missing for 15 cases (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTumour grade was available for 84 patients: G2 tumours predominated (58.3%), followed by G1 (31.0%) and G3 (10.7%). According to the FIGO 2009 classification, most cases were stage I (64%), with 6% stage II, 11% stage III, and 3% stage IV. Lymphovascular invasion (LVI) was present in 17 patients (17%), while myometrial invasion was identified in 75% of evaluable cases. Missing data were excluded from relevant analyses, and effective sample sizes are provided in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVEGF-C and VEGF-D serum levels depending on endometrial cancer patients\u0026rsquo; clinical characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eCriterion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eVEGF-C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eVEGF-D\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eHistological type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eClear cell\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e473.2\u0026thinsp;\u0026plusmn;\u0026thinsp;199.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.7109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.97\u0026thinsp;\u0026plusmn;\u0026thinsp;4.656\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.3048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eEndometrial\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e282.3\u0026thinsp;\u0026plusmn;\u0026thinsp;11.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.21\u0026thinsp;\u0026plusmn;\u0026thinsp;1.175\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSerous\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e256.7\u0026thinsp;\u0026plusmn;\u0026thinsp;44.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18.47\u0026thinsp;\u0026plusmn;\u0026thinsp;1.424\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eUndifferentiated\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e322.7\u0026thinsp;\u0026plusmn;\u0026thinsp;18,72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.11\u0026thinsp;\u0026plusmn;\u0026thinsp;5.458\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eGrade\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eG1\\KM\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e304.3\u0026thinsp;\u0026plusmn;\u0026thinsp;17.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.2975\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e17.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5543\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.0172\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eG2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e279.8\u0026thinsp;\u0026plusmn;\u0026thinsp;19.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e20.96\u0026thinsp;\u0026plusmn;\u0026thinsp;1.470\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eG3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e300.2\u0026thinsp;\u0026plusmn;\u0026thinsp;24.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e27.98\u0026thinsp;\u0026plusmn;\u0026thinsp;5.329\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eStage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eІ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e283.3\u0026thinsp;\u0026plusmn;\u0026thinsp;12.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.8961\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e19.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9623\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.0205\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eII\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e281.2\u0026thinsp;\u0026plusmn;\u0026thinsp;41.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e38.09\u0026thinsp;\u0026plusmn;\u0026thinsp;11.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eIII\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e325.8\u0026thinsp;\u0026plusmn;\u0026thinsp;63.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e20.21\u0026thinsp;\u0026plusmn;\u0026thinsp;1.236\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eIV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e244.6\u0026thinsp;\u0026plusmn;\u0026thinsp;42.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e15.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7178\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eMyometrial invasion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e304.7\u0026thinsp;\u0026plusmn;\u0026thinsp;23.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.4867\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.5006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e285.3\u0026thinsp;\u0026plusmn;\u0026thinsp;13.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.195\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eLymphovascular invasion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e300.8\u0026thinsp;\u0026plusmn;\u0026thinsp;13.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.6019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e18.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5946\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.0244\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e322.5\u0026thinsp;\u0026plusmn;\u0026thinsp;40.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e25.28\u0026thinsp;\u0026plusmn;\u0026thinsp;3.917\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Serum VEGF levels and clinicopathological parameters\u003c/h2\u003e \u003cp\u003eThe median serum concentration of VEGF-C was 303.1 pg/mL (range: 91.8\u0026ndash;869.2 pg/mL), while the median VEGF-D level was 17.5 pg/mL (range: 11.5\u0026ndash;101.6 pg/mL).\u003c/p\u003e \u003cp\u003eVEGF-D levels were significantly higher in G3 compared to G1 tumours (median: 28.0 \u003cem\u003evs.\u003c/em\u003e 17.0 pg/mL; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0172), corresponding to an approximately 65% increase (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). No significant differences in VEGF-C concentrations were observed across tumour grades (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.2975).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eVEGF-D levels varied significantly by FIGO stage (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0205), with the highest median levels observed in stage II (38.1 pg/mL) and the lowest in stage IV (15.6 pg/mL) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). VEGF-C showed no significant variation by stage (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.8961).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePatients with LVI demonstrated nearly 50% higher VEGF-D levels compared with those without LVI (median: 25.3 \u003cem\u003evs.\u003c/em\u003e 18.0 pg/mL; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0244) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003e). No association was observed for VEGF-C (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.6019).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eNo significant associations were found between VEGF-D or VEGF-C levels and histological subtype or the presence of myometrial invasion (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.3). Exploratory analyses did not reveal correlations between VEGF levels and patient age.\u003c/p\u003e \u003cp\u003eTaken together, our results demonstrate that serum VEGF-D, but not VEGF-C, is significantly elevated in patients with high-grade tumours, FIGO stage II disease, and in the presence of lymphovascular invasion. In particular, VEGF-D levels were nearly 50% higher in patients with LVI compared to those without, and peaked in stage II disease before declining in stage IV. These findings support the role of VEGF-D as a potential circulating marker of early invasive and aggressive tumour biology.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eThis study demonstrates a significant association between elevated serum VEGF-D levels and adverse clinicopathological features in EC, including high tumour grade, lymphovascular invasion (LVI), and FIGO stage II disease. In contrast, VEGF-C levels did not correlate with any of the analyzed parameters. To our knowledge, this is the first study to report a statistically significant relationship between circulating VEGF-D and LVI in EC, suggesting a potential role for VEGF-D as a non-invasive biomarker of tumour invasiveness. Given the increasing importance of molecular risk stratification in EC (e.g., ProMisE or TCGA classification), integrating serum biomarkers such as VEGF-D with genomic profiles may improve prognostic accuracy and guide treatment strategies.\u003c/p\u003e \u003cp\u003eSeveral processes enable tumour cells to reach the lymphatic system: progressive enlargement of the tumour mass, activation of lymphangiogenesis by VEGF factors, infiltration of nearby tissues by individual cancer cells, and coordinated migration of tumour cell groups through tissue barriers [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. LVI is therefore a key mechanism by which cancer cells penetrate vessel walls, while VEGF-mediated lymphangiogenesis further facilitates dissemination. In EC, LVI is a recognized marker of tumour aggressiveness and is incorporated into modern risk stratification systems [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Indeed, previous studies have demonstrated its impact on progression-free survival [\u003cspan additionalcitationids=\"CR20 CR21\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral studies have reported a role for VEGF-C in regional and distant metastasis [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], and LVI has been suggested not only as a predictor of locoregional recurrence, but also as a marker of distant metastasis [\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Following VEGF-C/D\u0026ndash;induced angiogenesis and lymphangiogenesis, vascular density increases; after epithelial\u0026ndash;mesenchymal transition, tumour cells invade lymphatic or blood vessels, enabling further dissemination [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. In our study, serum VEGF-D was significantly associated with LVI, suggesting its dual role in both lymphangiogenesis and angiogenesis. According to Huang et al., VEGF-C mRNA expression correlated with retroperitoneal lymph node metastases [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], supporting the hypothesis that VEGF-C may mark lymphatic spread in EC. Moreover, some studies have shown that metastatic cells may migrate from lymph nodes to distant organs [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], and the concept of a pre-metastatic niche within lymph nodes\u0026mdash;first described nearly two decades ago [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u0026mdash;further highlights the biological plausibility of our findings. Lymphovascular invasion, lymphatic vessel density, and VEGF-C expression have all been linked with lymph node metastasis in EC [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. However, in our cohort, no association was found between serum VEGF-C and LVI, suggesting that serum VEGF-D may be the more relevant circulating biomarker.\u003c/p\u003e \u003cp\u003eVEGF-D expression patterns further support our findings. Girling et al. showed that VEGF-D overexpression enlarged myometrial lymphatic vessels without stimulating new lymphangiogenesis and also promoted enlargement of endometrial blood vessels [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. In our study, VEGF-D levels were highest in FIGO stage II disease, which may reflect an early phase of stromal and lymphatic invasion prior to lymph node dissemination. This could represent a clinically relevant window for intervention. Previous studies also support VEGF-D as an independent prognostic factor in EC, with associations to myometrial invasion and nodal metastasis [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], as well as tumour grade [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Similarly, cohort studies have demonstrated strong correlations between high-grade tumours and LVI [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The biological plausibility of these findings lies in VEGF-D binding to VEGFR-3, which promotes lymphangiogenesis, vessel dilation, and remodeling [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. VEGF-D can also activate VEGFR-2, contributing to angiogenesis and intratumoral vascular permeability [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. The discrepancy between VEGF-C and VEGF-D observed in our study may be explained by differences between tissue and serum expression, or by sampling in relation to disease progression [\u003cspan additionalcitationids=\"CR44\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFrom a clinical perspective, serum VEGF-D testing appears feasible, cost-effective, and technically straightforward. As a non-invasive biomarker, it could improve preoperative risk stratification, particularly in centers without access to molecular classification. Identifying patients with elevated VEGF-D may support more aggressive staging or adjuvant therapy decisions. In addition, VEGF-D may represent a future target for therapy in biologically aggressive EC subtypes.\u003c/p\u003e \u003cp\u003eSeveral limitations must be acknowledged. The sample size was relatively small, limiting statistical power and generalizability. Patient heterogeneity, incomplete clinicopathological data, and the retrospective design may have introduced bias. The absence of molecular classification data (e.g., TCGA or ProMisE) precludes integration with genomic risk models, and the lack of survival analysis limits assessment of the prognostic value of VEGF-C and VEGF-D. Prospective, multicenter studies with larger and molecularly stratified cohorts are needed to validate VEGF-D as a prognostic biomarker, clarify its relationship with survival and metastasis, and determine its added value when combined with molecular classifiers.\u003c/p\u003e"},{"header":"5. CONCLUSIONS","content":"\u003cp\u003eThis study demonstrates, for the first time, a significant association between circulating VEGF-D and key pathological features of EC, including FIGO stage, tumour grade, and lymphovascular invasion, while no such associations were observed for VEGF-C. These findings suggest that VEGF-D may serve as a practical, non-invasive biomarker for identifying patients at higher risk of aggressive disease. The observed elevation of VEGF-D in FIGO stage II may represent a biologically active phase of early invasion, offering a potential therapeutic window for intervention. Integration of VEGF-D with existing molecular classifiers could further enhance risk stratification. Larger, prospective, and molecularly stratified studies are warranted to validate its clinical utility and to explore its role as a potential therapeutic target.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eEC - Endometrial cancer\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFIGO - The International Federation of Gynecology and Obstetrics\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eVEGF-C, VEGF-D - Vascular endothelial growth factors C and D\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTCGA The Cancer Genome Atlas\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eProMisE - Proactive Molecular Risk Classifier for Endometrial Cancer\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGEO - Gene Expression Omnibus\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eELISA \u0026ndash; Enzyme-linked immunosorbent assay\u003c/p\u003e\n\u003cp\u003eLVI \u0026ndash; Lymphovascular invasion\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki and approved by the Bioethical Committee of the Medical University of Lublin (approvals KE-0254/139/06/2022 and KE-0254/272/2019). All participants provided written informed consent\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was supported by the Medical University of Lublin, Poland, DS 129 grant for statutory activities and \u0026nbsp;National Centre for Research and Development (NCBiR) PerMed/IV/35/ECLAI/2022.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOK: Writing \u0026ndash; original draft, review \u0026amp; editing, Resources, Visualization, Methodology; OM: Writing \u0026ndash; original draft, review \u0026amp; editing, Data curation, Methodology; MK: Writing \u0026ndash; review \u0026amp; editing, Investigation, Methodology; VA: Writing \u0026ndash; review \u0026amp; editing, Data curation, Methodology, Investigation; VM: Writing \u0026ndash; review \u0026amp; editing, Data curation, Methodology, Investigation, Validation; MB: Writing \u0026ndash; original draft, review \u0026amp; editing, Conceptualization, Formal Analysis; Data curation, Funding acquisition, Project administration, Resources, Supervision; MOL: Writing \u0026ndash; original draft, review \u0026amp; editing, Conceptualization, Methodology, Investigation, Project administration; Supervision, Validation.\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the final version of the manuscript and gave consent for submission.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. 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Iranian Journal of Public Health.\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":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"endometrial cancer, VEGF-C, VEGF-D, progression, prognosis","lastPublishedDoi":"10.21203/rs.3.rs-8320695/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8320695/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground.\u003c/h2\u003e \u003cp\u003eEndometrial cancer (EC) is the most common gynecologic malignancy in developed countries. While clinicopathological factors such as tumour grade, The International Federation of Gynecology and Obstetrics (FIGO) stage, and lymphovascular invasion (LVI) are established prognostic indicators, reliable preoperative molecular biomarkers remain lacking. Vascular endothelial growth factors C and D (VEGF-C, VEGF-D) regulate lymphangiogenesis, but their circulating levels and prognostic relevance in EC have not been well characterized.\u003c/p\u003e\u003ch2\u003eMethods.\u003c/h2\u003e \u003cp\u003eSerum VEGF-C and VEGF-D concentrations were measured using ELISA in 100 patients with histologically confirmed EC. Associations with tumour grade, FIGO stage, and LVI were analyzed using Mann\u0026ndash;Whitney U and Kruskal\u0026ndash;Wallis tests.\u003c/p\u003e\u003ch2\u003eResults.\u003c/h2\u003e \u003cp\u003eSerum VEGF-D levels were significantly elevated in patients with high-grade tumours (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0172) and in those with confirmed LVI (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0244). The highest VEGF-D concentrations were observed in FIGO stage II, with lower levels in stage IV disease (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0205). No significant correlations were observed between VEGF-C levels and any clinicopathological parameters.\u003c/p\u003e\u003ch2\u003eConclusions.\u003c/h2\u003e \u003cp\u003eElevated VEGF-D levels are associated with unfavorable pathological features in EC, including poor differentiation and lymphovascular invasion, indicating its potential role as a non-invasive biomarker of tumour aggressiveness. Further prospective studies are needed to validate VEGF-D as a prognostic indicator in EC and to explore its clinical utility in risk stratification.\u003c/p\u003e","manuscriptTitle":"VEGF-D and VEGF-C as Biomarkers in Endometrial Cancer: Association with Tumor Grade, Stage and Lymphovascular Invasion","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-27 12:06:50","doi":"10.21203/rs.3.rs-8320695/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-03-28T11:47:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"146900280237956449061765590997278327276","date":"2026-03-03T17:20:38+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-24T14:05:16+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-25T18:45:58+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-22T05:30:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-19T18:39:44+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2025-12-19T18:34:29+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"eb1e17e3-8f84-43d1-8e27-8be322c43f69","owner":[],"postedDate":"February 27th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-27T12:06:51+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-27 12:06:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8320695","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8320695","identity":"rs-8320695","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}