Pan-Cancer Analysis and Validation of NT5DC2: Emphasizing Its Prognostic Significance and Immunological Role in TNBC

Pan-Cancer Analysis and Validation of NT5DC2: Emphasizing Its Prognostic Significance and Immunological Role in TNBC | 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 Pan-Cancer Analysis and Validation of NT5DC2: Emphasizing Its Prognostic Significance and Immunological Role in TNBC Qing Luo, Xiandong Xie, Luyao Tian, Xiaomin Gao, Shu Li, Jinqiu Zhang, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6212403/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background 5′-Nucleotidase Domain Containing 2 (NT5DC2), a cNT5-II family member catalyzing nucleotide hydrolysis, plays a crucial role in tumor initiation and progression. This study aims to elucidate NT5DC2’s potential role in multiple cancers and confirm its oncogenic significance in triple-negative breast cancer (TNBC). Methods Multiple databases analyzed NT5DC2 expression patterns and assessed its diagnostic and prognostic value in cancers. Immune correlation analyses were conducted using ESTIMATE and CIBERSORT. KEGG pathway enrichment analysis explored NT5DC2-associated molecular pathways. To further investigate its role in TNBC, comprehensive bioinformatics analyses, including gene expression profiling, single-cell RNA sequencing analysis, immune infiltration assessment, and gene set enrichment analysis (GSEA). Finally, in vitro experiments were conducted to validate NT5DC2’s oncogenic role in TNBC. Results Our findings indicate that high NT5DC2 expression is associated with poor prognosis and holds significant clinical diagnostic value across multiple cancer types. NT5DC2 is highly expressed in TNBC and correlates with unfavorable outcomes. Single-cell RNA sequencing analysis reveals that NT5DC2 is predominantly expressed in epithelial cells, where it regulates immune cells through the MIF signaling pathway. Enrichment and immune infiltration analyses indicate that NT5DC2 is closely linked to an immunosuppressive tumor microenvironment. In vitro experiments demonstrate that NT5DC2 knockdown significantly inhibits TNBC cell growth, underscoring its potential as a therapeutic target. Conclusion Our study demonstrates that NT5DC2 functions as an oncogene in multiple cancer types. It holds considerable clinical diagnostic significance and is intricately linked to an immunosuppressive tumor microenvironment, particularly in TNBC. NT5DC2 Pan-cancer TNBC Biomarker Immune function Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Cancer remains a major global health challenge, ranking among the leading causes of death and significantly impacting quality of life worldwide [ 1 ] . Molecular-targeted therapies have emerged as a promising approach to cancer treatment, demonstrating remarkable clinical success across various cancer types [ 2 ] . The discovery of driver genes such as EGFR, HER2, ALK, and KRAS has paved the way for the development of targeted therapies. This progress has been largely driven by advances in sequencing technologies, which have deepened our understanding of human cancers [ 3 , 4 ] . Bioinformatics plays a vital role in cancer research, encompassing genomics, proteomics, and transcriptomics [ 5 ] . The synergy between sequencing technologies and bioinformatics has accelerated progress in life sciences [ 6 ] . Large-scale bioinformatics datasets have been instrumental in identifying effective biomarkers and therapeutic targets for tumor diagnosis and treatment, ultimately contributing to the advancement of precision oncology. 5′-Nucleotidase Domain Containing 2 (NT5DC2) belongs to the NT5DC family, which includes NT5DC1-4. While these proteins share a halo acid dehalogenase (HAD) motif in their N-terminal regions, their physiological roles remain poorly understood [ 7 ] . Recent studies suggest that NT5DC2 is involved in cancer biology. For instance, Guo et al. reported that NT5DC2 promotes glioma stem cell-like tumorigenicity by upregulating Fyn [ 8 ] . In hepatocellular carcinoma (HCC), NT5DC2 enhances proliferation and colony formation in vitro and facilitates tumor growth in vivo [ 9 ] . Conversely, low NT5DC2 expression in soft tissue sarcomas correlates with a favorable prognosis, with its downregulation inhibiting sarcoma progression via the ECM-receptor interaction pathway [ 10 ] . These findings position NT5DC2 as a promising tumor biomarker. However, despite these insights, a comprehensive pan-cancer analysis of NT5DC2's clinical relevance remains lacking. Its precise role in cancer progression and its impact on the tumor immune microenvironment require further investigation. This study conducted a pan-cancer analysis using multiple data sources to comprehensively assess NT5DC2’s clinical implications across various cancer types. NT5DC2’s diagnostic, prognostic, and immunological significance in TNBC were also examined, leveraging single-cell data analysis, GSEA, and in vitro experiments to validate its oncogenic role. Materials and methods Gene expression analysis Tumor cell line gene expression data were obtained from the Cancer Cell Line Encyclopedia (CCLE) ( https://portals.broadinstitute.org/ccle ). RNA sequencing data and corresponding clinical information for 33 cancers and their matched normal tissues were retrieved from TCGA( https://portal.gdc.cancer.gov/ ). Gene expression data were presented as log 2 (TPM + 1), where TPM refers to transcripts per million mapped reads. Statistical analyses were conducted using R software, and data visualization was performed using the ggplot2 package (version 3.4.2). NT5DC2 protein expression data were collected from the UALCAN portal ( https://ualcan.path.uab.edu ). All data were collected in March 2024. Analysis of the diagnosis Value The diagnostic accuracy of NT5DC2 was evaluated using receiver operating characteristic (ROC) curve analysis, assessing sensitivity and specificity via the pROC package (version 1.18.2). The area under the curve (AUC) ranged from 1.0 (perfect diagnostic value) to 0.5 (no diagnostic value). Immune Cell Infiltration Analysis of Pan-Cancer Using the "estimate" package (version 1.0.13) in R, the stromal and immune scores for each cancer type were calculated. Visualization was conducted with the "ggplot2" package (version 3.4.2). The proportions of immune cells in each tumor sample were estimated using the CIBERSORT algorithm in R. Correlations between NT5DC2 expression levels and immune cell infiltration were assessed using Spearman’s correlation test. TMB scores for each sample were derived from TCGA pan-cancer mutation data, while MSI scores were obtained from previously published studies [ 11 ] . Functional Enrichment Analysis of NT5DC2 Gene Set Enrichment Analysis (GSEA) was performed on the KEGG gene set to explore functional pathways associated with NT5DC2 expression. Differential gene expression analysis was conducted using the "DESeq2" package (version 1.26.0), and visualization was carried out with "ggplot2" (version 3.3.2). Genes with an adjusted p-value < 0.05 and a false discovery rate (FDR) < 0.25 were considered significantly differentially expressed. Single-Cell Analysis in TNBC Single-cell RNA sequencing (scRNA-seq) data were analyzed using the Seurat package in R. To ensure data quality, cells with fewer than 1,000 counts or mitochondrial content exceeding 20% were excluded. After filtering, the data were normalized using the NormalizeData function. Highly variable genes (n = 2,000) were identified with FindVariableGenes. To correct for batch effects, the harmony package was applied, integrating data from different samples. For clustering analysis, Seurat’s graph-based clustering approach was used, and cells were visualized in a two-dimensional space via Uniform Manifold Approximation and Projection (UMAP). Principal Component Analysis (PCA) was performed using the RunPCA function to further explore the variance structure of the data. Cells were annotated based on the expression of well-known marker genes as follows: Epithelial cells: EPCAM; Stromal cells: MME, PECAM1; Mast cells: CD63; Neutrophils: FCGR3A, ITGAM; Conventional dendritic cells (cDCs): FCER1A, CST3; MS4A1, CD79A; Plasma cells: MZB1, IGKC, JCHAIN; Proliferating cells: MKI67, TOP2A, STMN1; Natural killer (NK) cells: GNLY, NKG7, KLRD1; T cells: CD3D, CD3E UMAP plots were generated to visualize NT5DC2 expression across different cell populations. Finally, intercellular communication and key signaling pathways among various cell types were analyzed using the CellChat package, providing insights into cellular interactions and pathways potentially influenced by NT5DC2 expression. Immune Cell Infiltration Analysis in TNBC To examine the association between NT5DC2 expression and immune cell infiltration, multiple computational algorithms, including xCell, TIMER, quanTIseq, EPIC, ConsensusTME, CIBERSORT, and ABIS, were employed. These tools estimated the relative abundance of immune cell populations within the tumor microenvironment based on RNA-seq data. Pearson or Spearman correlation analysis was conducted to evaluate the relationship between NT5DC2 expression and infiltration levels of various immune cell types, including CD4⁺ and CD8⁺ T cells, regulatory T cells (Tregs), B cells, macrophages (M0, M1, M2), dendritic cells, NK cells, neutrophils, eosinophils, and mast cells. Correlation coefficients were calculated and visualized using the ggplot2 package in R. Statistical significance was defined as p < 0.05 after Benjamini-Hochberg correction for multiple testing. GSEA in TNBC To explore the functional pathways associated with differential gene expression, GSEA was performed using the GO and KEGG databases. Patients were classified into high and low NT5DC2 expression groups, and differential gene expression analysis was conducted. A ranked gene list was generated based on the log₂ fold change of differentially expressed genes. GSEA was performed using the clusterProfiler package in R, with 1,000 permutations to assess statistical significance. The enrichment score (ES), NES, and FDR q-values were calculated to identify significantly enriched pathways. A pathway was considered significantly enriched if |NES| > 1 and FDR < 0.05. Immunohistochemistry (IHC) Analysis All tissue samples were fixed, paraffin-embedded, and sectioned. The sections were dried, deparaffinized, rehydrated, and incubated with an anti-NT5DC2 antibody (Invitrogen, Carlsbad, CA, USA), followed by an HRP-conjugated secondary antibody. Staining was visualized using 3,3’-diaminobenzidine (DAB) and counterstained with hematoxylin. Staining positivity was quantified in three high-power fields (HPFs) per section. Cell Lines and Treatment The human TNBC cell line MDA-MB-468 was obtained from the National Cell Bank of China (Shanghai, China). Cells were cultured in Dulbecco's Modified Eagle's Medium (DMEM, high glucose) supplemented with 10% (v/v) fetal bovine serum (FBS) in a humidified incubator at 37°C with 5% CO₂. Cell line authentication was confirmed by short tandem repeat (STR) profiling, and mycoplasma contamination was ruled out. Cell Transfection NT5DC2 knockdown was achieved using NT5DC2 siRNA (Santa Cruz, Dallas, TX, USA). Cell transfection was performed using Lipofectamine 3000 reagent (L3000015, Thermo Fisher) following the manufacturer’s protocol. Cell Viability Assay Transfected cells were seeded into 96-well plates at a density of 1×10⁴ cells per well. At 24, 48, 72, and 96 hours, 20 µL of MTT solution was added to each well, followed by a 4-hour incubation. After removing the medium, 150 µL of DMSO (Beyotime, Shanghai, China) was added to dissolve the formazan crystals for 15 minutes. Optical density (OD) values at 490 nm were measured using an enzyme-linked immunometric meter. Colony Formation Assay A colony formation assay was conducted to assess reproductive cell death. Cells were seeded into 6-well plates and cultured for 7 days in a humidified incubator with 5% CO₂ at 37°C. Cells were then fixed with 4% paraformaldehyde (Beyotime, Shanghai, China) for 15 minutes at room temperature. After washing three times with PBS (Beyotime, Shanghai, China), colonies were stained with crystal violet (Beyotime, Shanghai, China) for 15 minutes at room temperature and washed again. Plates were air-dried, and colony numbers were counted using an inverted phase contrast microscope (Olympus IX53, Tokyo, Japan). Cell Apoptosis Assay Cells were seeded into 24-well plates and cultured at 37°C in a humidified incubator with 5% CO₂ for 24 hours. After incubation, cells were fixed with 4% paraformaldehyde and incubated with the TdT reaction mixture at 37°C. DAPI was used to stain nuclei. Fluorescent signals were detected using a fluorescence microscope (Olympus IX53, Tokyo, Japan). Western Blot Analysis Total protein was extracted using radio-immunoprecipitation assay (RIPA) lysis buffer (Beyotime, Shanghai, China), and protein concentrations were measured using a BCA protein assay kit (Beyotime, Shanghai, China). SDS-PAGE (10% or 15%) was used to separate protein samples, followed by transfer to PVDF membranes. Membranes were blocked and incubated with primary antibodies at 4°C overnight, followed by incubation with HRP-conjugated secondary antibodies at 37°C for 2 hours. Protein bands were visualized using an enhanced chemiluminescence (ECL) assay kit (Beyotime, Shanghai, China). GAPDH served as an endogenous control for normalizing protein expression levels. Statistical Analysis Each experiment was performed at least three times. Statistical analysis was conducted using GraphPad Prism 6.0. Data are presented as mean ± standard deviation (SD). Differences between groups were analyzed using Student’s t-test or ANOVA, with p < 0.05 considered statistically significant. Results Expression Level and Diagnostic Value of NT5DC2 in Human Cancers The expression profile of NT5DC2 in human cancers was analyzed using the CCLE and TCGA databases. According to the CCLE database, NT5DC2 expression varied across different cancer types, generally showing higher levels based on gene expression values (log₂(TPM + 1)) (Fig. 1 A). Analysis of the TCGA database revealed significantly increased NT5DC2 expression in tumor tissues compared to normal tissues across 15 cancer types, including bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), cholangiocarcinoma (CHOL), colon adenocarcinoma (COAD), esophageal carcinoma (ESCA), glioblastoma multiforme (GBM), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), pheochromocytoma and paraganglioma (PCPG), stomach adenocarcinoma (STAD), thyroid carcinoma (THCA), uterine corpus endometrial carcinoma (UCEC), kidney chromophobe (KICH), and prostate adenocarcinoma (PRAD) (Fig. 1 B). As shown in Fig. 1 C, NT5DC2 protein expression was significantly upregulated in colon cancer, clear cell renal cell carcinoma (RCC), UCEC, lung adenocarcinoma, pancreatic adenocarcinoma (PAAD), glioblastoma multiforme, and hepatocellular carcinoma. The ROC curves were used to assess the diagnostic accuracy of the NT5DC2 gene signature. The AUC values indicated high diagnostic accuracy for CHOL (AUC = 0.997), COAD (AUC = 0.940), GBM (AUC = 0.999), LIHC (AUC = 0.932), PCPG (AUC = 0.989), and rectal adenocarcinoma (READ) (AUC = 0.962) (Fig. 1 D). Immune-Related Analysis of NT5DC2 in Human Cancer To further investigate the relationship between NT5DC2 expression and the tumor microenvironment (TME), the ESTIMATE algorithm was used to assess associations between NT5DC2 expression and immune, stromal, and ESTIMATE scores. Regarding immune scores, positive correlations were observed between NT5DC2 expression and immune scores in BRCA and PRAD, whereas negative correlations were found in BLCA, CESC, ESCA, HNSC, GBM, LGG, LUAD, LUSC, MESO, OV, PCPG, SARC, SKCM, STAD, TGCT, and UCEC (Fig. 2 A). To explore the association between NT5DC2 expression and immune cell infiltration across different tumors, the CIBERSORT algorithm was applied. The study focused on tumor-associated macrophages (TAMs), activated dendritic cells, and activated NK cells. The heatmap revealed that NT5DC2 expression was predominantly positively correlated with M2 TAM infiltration in most tumors, while negative correlations were observed with M1 TAMs, dendritic cells, and NK cells (Fig. 2 B). Additionally, correlation analyses between NT5DC2 expression and TMB as well as MSI across various tumors, were performed. NT5DC2 expression was significantly positively associated with TMB in BRCA, TGCT, STAD, SKCM, LUAD, LGG, KICH, GBM, and COAD, whereas a negative correlation was observed in PRAD. For MSI, NT5DC2 expression was positively correlated with MSI in BRCA, TGCT, STAD, SARC, MESO, LIHC, and HNSC, while a negative correlation was found in READ (Fig. 2 C-D). Enrichment Analysis of NT5DC2 in Pan-Cancer To investigate the molecular mechanisms underlying NT5DC2 across different tumor types, GSEA was performed to identify pathways potentially influenced by NT5DC2 in pan-cancer. The six most significant KEGG pathways and generated forest plots across various cancer types were selected. The results indicated that NT5DC2 was significantly associated with multiple immune-related pathways, including antigen processing and presentation, primary immunodeficiency, the B cell receptor signaling pathway, and the intestinal immune network for IgA production. Additionally, NT5DC2 was linked to pathways regulating autophagy in ACC, CHOL, and LUSC. Notably, the most relevant pathway associated with NT5DC2 in pan-cancer was olfactory transduction (Fig. 3A-F). NT5DC2 Exhibits High Diagnostic and Prognostic Value in TNBC The expression of NT5DC2 was significantly higher in TNBC compared to non-TNBC (Fig. 4 A), demonstrating high diagnostic value with an AUC of 0.895 (Fig. 4 B). Additionally, Kaplan-Meier (K-M) survival curves indicated that high NT5DC2 expression was associated with a poorer prognosis (Fig. 4 C). NT5DC2 also exhibited strong predictive value for TNBC patient prognosis at 1, 3, and 5 years (Fig. 4 D). A nomogram based on multivariate analysis revealed that increased NT5DC2 expression significantly impacted age, N stage, T stage, and overall stage, whereas no impact was observed for M stage (Fig. 4 E). Single-Cell Analysis Reveals NT5DC2 Mediates Endothelial Cell-Driven Immune Suppression in TNBC Single-cell analysis showed that NT5DC2 was primarily expressed in epithelial cells, with additional expression observed in stromal and plasma cells (Fig. 5 A). In Fig. 5 B, interactions between specific molecular combinations and target cell types in cell-cell communication were analyzed, revealing a significant enhancement of the MIF-CD74 + CXCR4+/CD44 + signaling pathway in endothelial cells. Further analysis of cell-cell communication between epithelial and other cell types indicated that NT5DC2 primarily regulates endothelial cells, likely influencing macrophages through macrophage migration inhibitory factor (MIF), with multiple immune cell types involved in this regulatory process (Fig. 5 C). Additionally, GSEA analysis revealed suppression of immune-related pathways (Fig. 5 D–E), suggesting that NT5DC2 contributes to the immunosuppressive regulation of endothelial cells in TNBC. Moreover, NT5DC2 expression was negatively correlated with the infiltration of various immune cells across multiple immune infiltration algorithms (Fig. 5 F). NT5DC2 Knockdown Inhibits Cell Viability in TNBC Immunohistochemical analysis revealed that NT5DC2 was highly expressed in TNBC tissues compared to normal tissues (Fig. 6 A). To investigate its oncogenic role, experimental verification in TNBC cells was conducted. NT5DC2 was successfully knocked down in MDA-MB-468 cells using NT5DC2 siRNA (Fig. 6 B). The MTT assay demonstrated that NT5DC2 inhibition significantly reduced the cell viability of MDA-MB-468 cells (Fig. 6 C). Similarly, colony formation assays showed that NT5DC2 downregulation inhibited TNBC cell proliferation (Fig. 6 D). Furthermore, TUNEL staining indicated a significant increase in apoptotic MDA-MB-468 cells upon NT5DC2 knockdown (Fig. 6 E). Discussion This study found that NT5DC2 is highly expressed in multiple types of cancer and holds significant clinical relevance. Its expression correlates with the TME and plays a critical role in immune regulation. Notably, it was discovered that NT5DC2 is highly expressed in TNBC, with higher expression levels associated with poorer prognosis. Our findings indicate that NT5DC2 is closely linked to clinical diagnosis and prognosis, making it a valuable marker for cancer detection and therapeutic decision-making. Using single-cell RNA sequencing data, it was identified that NT5DC2 primarily regulates the immune microenvironment through the MIF signaling pathway, a relationship further supported by GSEA and immune cell infiltration analyses. Additionally, our study revealed a strong association between NT5DC2 expression and immune-related pathways, suggesting its involvement in immunosuppressive regulation. Furthermore, in vitro experiments using TNBC cells confirmed the oncogenic role of NT5DC2. Our analysis showed that NT5DC2 is highly expressed in most tumors, with notable exceptions in KICH, PRAD, and STAD. A model with a high AUC demonstrates high accuracy in distinguishing between cancer patients and healthy individuals or between different cancer types [ 12 ] . This is crucial for early cancer detection, guiding targeted treatment plans, and improving patient survival [ 13 ] . ROC curve analysis revealed the high diagnostic value of NT5DC2, particularly in CHOL, COAD, GBM, LIHC, PCPG, and READ, where AUC values were significantly elevated, underscoring its potential as a sensitive and specific biomarker. NT5DC2 is closely associated with the TME, which plays a critical role in tumor progression and therapy response [ 14 , 15 ] . ESTIMATE score analysis indicated that NT5DC2 expression correlates with immune and stromal cell content across various cancers. NT5DC2 regulate immune responses, potentially affecting immune cell infiltration and immune checkpoint regulation [ 16 ] . Specifically, NT5DC2 was linked to immune cell types such as dendritic cells, CD4⁺ T cells, CD8⁺ T cells, macrophages, and B cells in multiple tumors. The immune signaling pathways associated with KEGG analysis revealed NT5DC2 involvement in various immune pathways, including antigen processing, B cell receptor signaling, and the intestinal immune network for IgA production. The B-cell receptor signaling pathway is crucial for the normal development and adaptive immunity of B-cells, and it also plays a role in the microenvironment of solid tumors, such as squamous cell carcinoma and pancreatic cancer [ 17 ] . These findings strongly implicate NT5DC2 in tumors immune regulation. In TNBC, NT5DC2 not only served as a diagnostic and prognostic biomarker but also played a significant role in the immunosuppressive microenvironment. Single-cell analysis showed that NT5DC2 was primarily expressed in epithelial cells, interacting with immune cells via the MIF-CD74⁺CXCR4⁺/CD44⁺ signaling pathway, a known regulator of macrophage migration and immune suppression. Previous studies have demonstrated that MIF promotes an immunosuppressive microenvironment by enhancing neutrophil and Treg cell infiltration while inhibiting CD8⁺ T cell and M1 macrophage activation [ 18 , 19 ] . Additionally, GO and KEGG pathway analyses of NT5DC2 in TNBC confirmed its potential involvement in immune regulation. This was further supported by multiple immune infiltration algorithms, which showed a negative correlation between NT5DC2 expression and CD8⁺ T cell infiltration, underscoring its role as an immunosuppressive regulator in TNBC. CD8⁺ T cells, particularly those with a tissue-resident memory (TRM) phenotype, play a vital role in local immunity and enhancing responses to immunotherapy [ 20 ] . TRM-like cells expand in response to anti-PD-1 and anti-CTLA-4 immune checkpoint inhibition, providing sustained tissue-protective immunity against TNBC [ 21 ] . In MDA-MB-231 TNBC cells, NT5DC2 knockdown reduced cell proliferation and increased apoptosis, confirming its oncogenic role. Immunohistochemical analysis further validated NT5DC2 overexpression in TNBC tumor tissues, reinforcing its clinical relevance. While our study provides valuable insights into the role of NT5DC2 in pan-cancer and TNBC, several limitations remain. First, although bioinformatics analyses across multiple public databases were conducted, further validation using independent cohorts and experimental models is necessary. Second, while NT5DC2’s potential was identified in TNBC, further investigation of its molecular mechanisms, both in vitro and in vivo , is essential to fully understand its oncogenic role and therapeutic implications. Conclusions In summary, NT5DC2 exhibits potential as a diagnostic and prognostic biomarker in pan-cancer, particularly in TNBC. Our bioinformatics analyses indicate that NT5DC2 overexpression is linked to poor prognosis and plays a key role in the immunosuppressive microenvironment of TNBC. Further research is needed to clarify its molecular mechanisms in cancer progression and to explore its therapeutic potential. Declarations Data Availability Statement The original data can be provided by the corresponding author upon reasonable request. Ethics approval and consent to participate The study was approved by the Medical Ethics Committee of Wuxi Maternal and Child Health Hospital (approval no. 2023-01-0421-06; approval date, April 21, 2023) and was conducted in accordance with The Declaration of Helsinki. The participants provided written informed consent prior to taking part in the study. Acknowledgements Not applicable. Author Contributions Ke Wang and Yongxiang Yin: Writing, review, and/or revision of the manuscript; Qing Luo: Writing and revision of the manuscript, Xiandong Xie and Limei Mo: Data analysis and interpretation; Xiaomin Gao and Shu Li: Formal analysis; Jinqiu Zhang and Luyao Tian: validation; Xue Zhu: Funding acquisition. All authors approved final version of manuscript. Funding This work was supported by Major Project of Wuxi Municipal Health Commission (Z202303), Project of Jiangsu Commission of Health (H2023150) and the Project of Jiangsu Administration of Traditional Chinese Medicine (MS2022145, MS2023166). Patient consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. References Jokhadze N，Das A， and Dizon DS. Global cancer statistics: A healthy population relies on population health[J]. CA Cancer J Clin, 2024, 74(3)： 224-226.https://doi.org/10.3322/caac.21838 Wang M，Herbst RS， and Boshoff C. 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Supplementary Files WB1.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 09 May, 2025 Reviews received at journal 08 May, 2025 Reviewers agreed at journal 08 May, 2025 Reviews received at journal 14 Apr, 2025 Reviewers agreed at journal 06 Apr, 2025 Reviewers agreed at journal 02 Apr, 2025 Reviewers invited by journal 21 Mar, 2025 Editor assigned by journal 18 Mar, 2025 Submission checks completed at journal 17 Mar, 2025 First submitted to journal 17 Mar, 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. 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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-6212403","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":431937280,"identity":"b679d1f1-356a-4c24-80b9-20d658b16ace","order_by":0,"name":"Qing Luo","email":"","orcid":"","institution":"Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Qing","middleName":"","lastName":"Luo","suffix":""},{"id":431937281,"identity":"9f40991c-ef15-4952-9651-98cab6dded4d","order_by":1,"name":"Xiandong Xie","email":"","orcid":"","institution":"Youjiang Medical University for Nationalities","correspondingAuthor":false,"prefix":"","firstName":"Xiandong","middleName":"","lastName":"Xie","suffix":""},{"id":431937282,"identity":"748bceb2-bcbf-4a06-83e3-3d7f11f44ce1","order_by":2,"name":"Luyao Tian","email":"","orcid":"","institution":"Wuxi Maternity and Child Health Care Hospital, Affiliated Women's Hospital of Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Luyao","middleName":"","lastName":"Tian","suffix":""},{"id":431937283,"identity":"48b9059d-c610-40b5-a275-8a5c0709d9ed","order_by":3,"name":"Xiaomin Gao","email":"","orcid":"","institution":"Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Xiaomin","middleName":"","lastName":"Gao","suffix":""},{"id":431937284,"identity":"130251c3-bb15-4171-b539-07cf7ba3b2a7","order_by":4,"name":"Shu Li","email":"","orcid":"","institution":"Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Shu","middleName":"","lastName":"Li","suffix":""},{"id":431937285,"identity":"2c6d8afe-400a-430c-8811-718a606073cb","order_by":5,"name":"Jinqiu Zhang","email":"","orcid":"","institution":"Wuxi Maternity and Child Health Care Hospital, Affiliated Women's Hospital of Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Jinqiu","middleName":"","lastName":"Zhang","suffix":""},{"id":431937286,"identity":"8d0428fb-cd1a-429a-9c45-0ce3e6fe6c52","order_by":6,"name":"Limei Mo","email":"","orcid":"","institution":"Youjiang Medical University for Nationalities","correspondingAuthor":false,"prefix":"","firstName":"Limei","middleName":"","lastName":"Mo","suffix":""},{"id":431937287,"identity":"c057a5cc-9454-4c5b-a94b-121abe73c16f","order_by":7,"name":"Xue Zhu","email":"","orcid":"","institution":"jiangsu institute of nuclear medicine","correspondingAuthor":false,"prefix":"","firstName":"Xue","middleName":"","lastName":"Zhu","suffix":""},{"id":431937288,"identity":"c2535eaa-c64c-40c6-b4b9-2fb32ffd6c04","order_by":8,"name":"Ke Wang","email":"","orcid":"","institution":"jiangsu institute of nuclear medicine","correspondingAuthor":false,"prefix":"","firstName":"Ke","middleName":"","lastName":"Wang","suffix":""},{"id":431937289,"identity":"d2fd3ee9-a594-4820-8427-f3c7a0832e9d","order_by":9,"name":"Yongxiang Yin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA80lEQVRIiWNgGAWjYDACZiBmbLBhZkMIJRClJY0ULQxgLYeRuQS0GBznPSZdueM8Ox/72cOvC2ruMPCz5xgw/NyBR8thvjTJs2duM7Px5KVZzzj2jEGy540BY+8ZfFp4zCQb24BaGHLMjHnYDjMY3MgxYGZsI6jlHDMb/xugln+HGeyJ1HKAmU0ix/gxbxvQFgkCWiQP8xhbNrYlA7W8MWPm7TvMI3HmWcHBXjxa+M6fMbzZ2GaXLN+fY/yZ59thOf725I0PfuLRonCAgUUCSCcDMRuIwQMSPYBbAwODfAMD8wcgbQfEYMYoGAWjYBSMAgwAAKOZS3UVy3CKAAAAAElFTkSuQmCC","orcid":"","institution":"Wuxi Maternity and Child Health Care Hospital, Affiliated Women's Hospital of Jiangnan University","correspondingAuthor":true,"prefix":"","firstName":"Yongxiang","middleName":"","lastName":"Yin","suffix":""}],"badges":[],"createdAt":"2025-03-12 13:23:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6212403/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6212403/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":79576180,"identity":"b2cb21bd-89e9-4f98-905d-50497ac9b72f","added_by":"auto","created_at":"2025-03-31 11:19:26","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":539626,"visible":true,"origin":"","legend":"\u003cp\u003eThe expression and diagnostic characteristics of NT5DC2. (A) NT5DC2 expression in tumor tissues based on the CCLE database. (B) Comparison of NT5DC2 expression in TCGA tumor and adjacent normal tissues. (C) Differential NT5DC2 protein levels in various tumors based on the UALCAN database. (D) AUC of ROC curves validating the diagnostic performance of NT5DC2 in the TCGA cohort. (*p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001).\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6212403/v1/eaf2ca174045eb1ba6dc50f3.png"},{"id":79577779,"identity":"3726ef00-f474-455a-b1af-19cecb38cf35","added_by":"auto","created_at":"2025-03-31 11:27:26","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":472030,"visible":true,"origin":"","legend":"\u003cp\u003eNT5DC2 Immune-Related Analysis in Various Tumors. (A) Relationship between NT5DC2 and stromal, immune, and ESTIMATE scores. (B) Heatmap of the correlation between NT5DC2 expression and immune cell infiltration. (C-D) Correlation of NT5DC2 expression with TMB and MSI. (*p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6212403/v1/9ac7178951ca4f05b69ff2f6.png"},{"id":79576181,"identity":"ae31e5a8-9b98-4e5d-9afd-139429ac36b3","added_by":"auto","created_at":"2025-03-31 11:19:26","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":372328,"visible":true,"origin":"","legend":"\u003cp\u003eKEGG annotations of NT5DC2 in six tumor types. KEGG bubble plots for (A) ACC, (B) CHOL, (C) BRCA, (D) LUAD, (E) SKCM, and (F) LUSC.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6212403/v1/4de1b42384fd24c8e28937ca.png"},{"id":79576188,"identity":"92f45bc0-3751-4ea9-a764-f960704638cd","added_by":"auto","created_at":"2025-03-31 11:19:26","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":198563,"visible":true,"origin":"","legend":"\u003cp\u003eDiagnostic and prognostic analysis of NT5DC2 in TNBC. (A) Differential expression analysis of NT5DC2. (B) ROC curve verifying the diagnostic performance of NT5DC2 in TNBC. (C) Kaplan-Meier analysis of NT5DC2 expression in TNBC. (D) TimeROC analysis of NT5DC2 expression in TNBC. (E) Nomogram predicting 1-, 3-, and 5-year OS in TNBC patients. (*p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001).\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6212403/v1/5aa14acc5f4f0eca876e74d0.png"},{"id":79576183,"identity":"f7bc6c34-157b-45c0-8bbe-0a2a178b1014","added_by":"auto","created_at":"2025-03-31 11:19:26","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":513778,"visible":true,"origin":"","legend":"\u003cp\u003e(A) NT5DC2 expression in TNBC single-cell data. (B) Pathways of communication between epithelial cells and other cell types. (C) Cell-cell communication between epithelial cells and other cell types in the MIF signaling pathway network. (D) GSEA of immune-related GO pathways in TNBC patients grouped by NT5DC2 expression. (E) GSEA of immune-related KEGG pathways in TNBC patients grouped by NT5DC2 expression. (F) Correlation between NT5DC2 expression and immune cell infiltration in TNBC.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-6212403/v1/bfbe6bce4f2c1c49abdd9b46.png"},{"id":79576187,"identity":"efe41318-1e6e-48e9-8c8b-b6b2118ef2d8","added_by":"auto","created_at":"2025-03-31 11:19:26","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":371345,"visible":true,"origin":"","legend":"\u003cp\u003eNT5DC2 knockdown inhibits cell viability in TNBC cells. (A) Immunohistochemical images showing NT5DC2 expression in normal and tumor tissues. (B) Western blot analysis confirming NT5DC2 knockdown in MDA-MB-468 cells transfected with si-NT5DC2. The statistical results are shown on the right. (C) MTT assay assessing MDA-MB-468 cell viability after NT5DC2 knockdown. (D) Colony formation assay results for MDA-MB-468 cells after NT5DC2 knockdown. (E) TUNEL staining results showing apoptotic MDA-MB-468 cells after NT5DC2 knockdown. (*p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001).\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-6212403/v1/0bcc0ea45800bee9a2ee1ffb.png"},{"id":79578504,"identity":"1d4d5105-6437-43a1-94f8-0fc4222c8340","added_by":"auto","created_at":"2025-03-31 11:35:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3275065,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6212403/v1/8f3b5755-7e3a-4695-b2bc-707d14d6d6ae.pdf"},{"id":79577782,"identity":"55b1af9f-6759-4d60-9a65-5fcbf75bedc4","added_by":"auto","created_at":"2025-03-31 11:27:26","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":2096520,"visible":true,"origin":"","legend":"","description":"","filename":"WB1.docx","url":"https://assets-eu.researchsquare.com/files/rs-6212403/v1/cadf1d1f4506ddac7d30a775.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Pan-Cancer Analysis and Validation of NT5DC2: Emphasizing Its Prognostic Significance and Immunological Role in TNBC","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCancer remains a major global health challenge, ranking among the leading causes of death and significantly impacting quality of life worldwide \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Molecular-targeted therapies have emerged as a promising approach to cancer treatment, demonstrating remarkable clinical success across various cancer types \u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. The discovery of driver genes such as EGFR, HER2, ALK, and KRAS has paved the way for the development of targeted therapies. This progress has been largely driven by advances in sequencing technologies, which have deepened our understanding of human cancers \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. Bioinformatics plays a vital role in cancer research, encompassing genomics, proteomics, and transcriptomics \u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. The synergy between sequencing technologies and bioinformatics has accelerated progress in life sciences \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Large-scale bioinformatics datasets have been instrumental in identifying effective biomarkers and therapeutic targets for tumor diagnosis and treatment, ultimately contributing to the advancement of precision oncology.\u003c/p\u003e \u003cp\u003e5\u0026prime;-Nucleotidase Domain Containing 2 (NT5DC2) belongs to the NT5DC family, which includes NT5DC1-4. While these proteins share a halo acid dehalogenase (HAD) motif in their N-terminal regions, their physiological roles remain poorly understood \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Recent studies suggest that NT5DC2 is involved in cancer biology. For instance, Guo et al. reported that NT5DC2 promotes glioma stem cell-like tumorigenicity by upregulating Fyn \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. In hepatocellular carcinoma (HCC), NT5DC2 enhances proliferation and colony formation \u003cem\u003ein vitro\u003c/em\u003e and facilitates tumor growth \u003cem\u003ein vivo\u003c/em\u003e \u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Conversely, low NT5DC2 expression in soft tissue sarcomas correlates with a favorable prognosis, with its downregulation inhibiting sarcoma progression via the ECM-receptor interaction pathway \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. These findings position NT5DC2 as a promising tumor biomarker. However, despite these insights, a comprehensive pan-cancer analysis of NT5DC2's clinical relevance remains lacking. Its precise role in cancer progression and its impact on the tumor immune microenvironment require further investigation.\u003c/p\u003e \u003cp\u003eThis study conducted a pan-cancer analysis using multiple data sources to comprehensively assess NT5DC2\u0026rsquo;s clinical implications across various cancer types. NT5DC2\u0026rsquo;s diagnostic, prognostic, and immunological significance in TNBC were also examined, leveraging single-cell data analysis, GSEA, and \u003cem\u003ein vitro\u003c/em\u003e experiments to validate its oncogenic role.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eGene expression analysis\u003c/h2\u003e \u003cp\u003eTumor cell line gene expression data were obtained from the Cancer Cell Line Encyclopedia (CCLE) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://portals.broadinstitute.org/ccle\u003c/span\u003e\u003cspan address=\"https://portals.broadinstitute.org/ccle\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). RNA sequencing data and corresponding clinical information for 33 cancers and their matched normal tissues were retrieved from TCGA(\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://portal.gdc.cancer.gov/\u003c/span\u003e\u003cspan address=\"https://portal.gdc.cancer.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Gene expression data were presented as log\u003csub\u003e2\u003c/sub\u003e(TPM\u0026thinsp;+\u0026thinsp;1), where TPM refers to transcripts per million mapped reads. Statistical analyses were conducted using R software, and data visualization was performed using the ggplot2 package (version 3.4.2). NT5DC2 protein expression data were collected from the UALCAN portal (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ualcan.path.uab.edu\u003c/span\u003e\u003cspan address=\"https://ualcan.path.uab.edu\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). All data were collected in March 2024.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAnalysis of the diagnosis Value\u003c/h3\u003e\n\u003cp\u003eThe diagnostic accuracy of NT5DC2 was evaluated using receiver operating characteristic (ROC) curve analysis, assessing sensitivity and specificity via the pROC package (version 1.18.2). The area under the curve (AUC) ranged from 1.0 (perfect diagnostic value) to 0.5 (no diagnostic value).\u003c/p\u003e\n\u003ch3\u003eImmune Cell Infiltration Analysis of Pan-Cancer\u003c/h3\u003e\n\u003cp\u003eUsing the \"estimate\" package (version 1.0.13) in R, the stromal and immune scores for each cancer type were calculated. Visualization was conducted with the \"ggplot2\" package (version 3.4.2). The proportions of immune cells in each tumor sample were estimated using the CIBERSORT algorithm in R. Correlations between NT5DC2 expression levels and immune cell infiltration were assessed using Spearman\u0026rsquo;s correlation test. TMB scores for each sample were derived from TCGA pan-cancer mutation data, while MSI scores were obtained from previously published studies\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eFunctional Enrichment Analysis of NT5DC2\u003c/h3\u003e\n\u003cp\u003eGene Set Enrichment Analysis (GSEA) was performed on the KEGG gene set to explore functional pathways associated with NT5DC2 expression. Differential gene expression analysis was conducted using the \"DESeq2\" package (version 1.26.0), and visualization was carried out with \"ggplot2\" (version 3.3.2). Genes with an adjusted p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and a false discovery rate (FDR)\u0026thinsp;\u0026lt;\u0026thinsp;0.25 were considered significantly differentially expressed.\u003c/p\u003e\n\u003ch3\u003eSingle-Cell Analysis in TNBC\u003c/h3\u003e\n\u003cp\u003eSingle-cell RNA sequencing (scRNA-seq) data were analyzed using the Seurat package in R. To ensure data quality, cells with fewer than 1,000 counts or mitochondrial content exceeding 20% were excluded. After filtering, the data were normalized using the NormalizeData function. Highly variable genes (n\u0026thinsp;=\u0026thinsp;2,000) were identified with FindVariableGenes. To correct for batch effects, the harmony package was applied, integrating data from different samples. For clustering analysis, Seurat\u0026rsquo;s graph-based clustering approach was used, and cells were visualized in a two-dimensional space via Uniform Manifold Approximation and Projection (UMAP). Principal Component Analysis (PCA) was performed using the RunPCA function to further explore the variance structure of the data.\u003c/p\u003e \u003cp\u003eCells were annotated based on the expression of well-known marker genes as follows: Epithelial cells: EPCAM; Stromal cells: MME, PECAM1; Mast cells: CD63; Neutrophils: FCGR3A, ITGAM; Conventional dendritic cells (cDCs): FCER1A, CST3; MS4A1, CD79A; Plasma cells: MZB1, IGKC, JCHAIN; Proliferating cells: MKI67, TOP2A, STMN1; Natural killer (NK) cells: GNLY, NKG7, KLRD1; T cells: CD3D, CD3E\u003c/p\u003e \u003cp\u003eUMAP plots were generated to visualize NT5DC2 expression across different cell populations. Finally, intercellular communication and key signaling pathways among various cell types were analyzed using the CellChat package, providing insights into cellular interactions and pathways potentially influenced by NT5DC2 expression.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eImmune Cell Infiltration Analysis in TNBC\u003c/h2\u003e \u003cp\u003eTo examine the association between NT5DC2 expression and immune cell infiltration, multiple computational algorithms, including xCell, TIMER, quanTIseq, EPIC, ConsensusTME, CIBERSORT, and ABIS, were employed. These tools estimated the relative abundance of immune cell populations within the tumor microenvironment based on RNA-seq data. Pearson or Spearman correlation analysis was conducted to evaluate the relationship between NT5DC2 expression and infiltration levels of various immune cell types, including CD4⁺ and CD8⁺ T cells, regulatory T cells (Tregs), B cells, macrophages (M0, M1, M2), dendritic cells, NK cells, neutrophils, eosinophils, and mast cells. Correlation coefficients were calculated and visualized using the ggplot2 package in R. Statistical significance was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 after Benjamini-Hochberg correction for multiple testing.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eGSEA in TNBC\u003c/h3\u003e\n\u003cp\u003eTo explore the functional pathways associated with differential gene expression, GSEA was performed using the GO and KEGG databases. Patients were classified into high and low NT5DC2 expression groups, and differential gene expression analysis was conducted. A ranked gene list was generated based on the log₂ fold change of differentially expressed genes. GSEA was performed using the clusterProfiler package in R, with 1,000 permutations to assess statistical significance. The enrichment score (ES), NES, and FDR q-values were calculated to identify significantly enriched pathways. A pathway was considered significantly enriched if |NES| \u0026gt; 1 and FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\n\u003ch3\u003eImmunohistochemistry (IHC) Analysis\u003c/h3\u003e\n\u003cp\u003eAll tissue samples were fixed, paraffin-embedded, and sectioned. The sections were dried, deparaffinized, rehydrated, and incubated with an anti-NT5DC2 antibody (Invitrogen, Carlsbad, CA, USA), followed by an HRP-conjugated secondary antibody. Staining was visualized using 3,3\u0026rsquo;-diaminobenzidine (DAB) and counterstained with hematoxylin. Staining positivity was quantified in three high-power fields (HPFs) per section.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCell Lines and Treatment\u003c/h2\u003e \u003cp\u003eThe human TNBC cell line MDA-MB-468 was obtained from the National Cell Bank of China (Shanghai, China). Cells were cultured in Dulbecco's Modified Eagle's Medium (DMEM, high glucose) supplemented with 10% (v/v) fetal bovine serum (FBS) in a humidified incubator at 37\u0026deg;C with 5% CO₂. Cell line authentication was confirmed by short tandem repeat (STR) profiling, and mycoplasma contamination was ruled out.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eCell Transfection\u003c/h2\u003e \u003cp\u003eNT5DC2 knockdown was achieved using NT5DC2 siRNA (Santa Cruz, Dallas, TX, USA). Cell transfection was performed using Lipofectamine 3000 reagent (L3000015, Thermo Fisher) following the manufacturer\u0026rsquo;s protocol.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eCell Viability Assay\u003c/h2\u003e \u003cp\u003eTransfected cells were seeded into 96-well plates at a density of 1\u0026times;10⁴ cells per well. At 24, 48, 72, and 96 hours, 20 \u0026micro;L of MTT solution was added to each well, followed by a 4-hour incubation. After removing the medium, 150 \u0026micro;L of DMSO (Beyotime, Shanghai, China) was added to dissolve the formazan crystals for 15 minutes. Optical density (OD) values at 490 nm were measured using an enzyme-linked immunometric meter.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eColony Formation Assay\u003c/h2\u003e \u003cp\u003eA colony formation assay was conducted to assess reproductive cell death. Cells were seeded into 6-well plates and cultured for 7 days in a humidified incubator with 5% CO₂ at 37\u0026deg;C. Cells were then fixed with 4% paraformaldehyde (Beyotime, Shanghai, China) for 15 minutes at room temperature. After washing three times with PBS (Beyotime, Shanghai, China), colonies were stained with crystal violet (Beyotime, Shanghai, China) for 15 minutes at room temperature and washed again. Plates were air-dried, and colony numbers were counted using an inverted phase contrast microscope (Olympus IX53, Tokyo, Japan).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eCell Apoptosis Assay\u003c/h2\u003e \u003cp\u003eCells were seeded into 24-well plates and cultured at 37\u0026deg;C in a humidified incubator with 5% CO₂ for 24 hours. After incubation, cells were fixed with 4% paraformaldehyde and incubated with the TdT reaction mixture at 37\u0026deg;C. DAPI was used to stain nuclei. Fluorescent signals were detected using a fluorescence microscope (Olympus IX53, Tokyo, Japan).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eWestern Blot Analysis\u003c/h2\u003e \u003cp\u003eTotal protein was extracted using radio-immunoprecipitation assay (RIPA) lysis buffer (Beyotime, Shanghai, China), and protein concentrations were measured using a BCA protein assay kit (Beyotime, Shanghai, China). SDS-PAGE (10% or 15%) was used to separate protein samples, followed by transfer to PVDF membranes. Membranes were blocked and incubated with primary antibodies at 4\u0026deg;C overnight, followed by incubation with HRP-conjugated secondary antibodies at 37\u0026deg;C for 2 hours. Protein bands were visualized using an enhanced chemiluminescence (ECL) assay kit (Beyotime, Shanghai, China). GAPDH served as an endogenous control for normalizing protein expression levels.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eEach experiment was performed at least three times. Statistical analysis was conducted using GraphPad Prism 6.0. Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). Differences between groups were analyzed using Student\u0026rsquo;s t-test or ANOVA, with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eExpression Level and Diagnostic Value of NT5DC2 in Human Cancers\u003c/h2\u003e \u003cp\u003eThe expression profile of NT5DC2 in human cancers was analyzed using the CCLE and TCGA databases. According to the CCLE database, NT5DC2 expression varied across different cancer types, generally showing higher levels based on gene expression values (log₂(TPM\u0026thinsp;+\u0026thinsp;1)) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Analysis of the TCGA database revealed significantly increased NT5DC2 expression in tumor tissues compared to normal tissues across 15 cancer types, including bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), cholangiocarcinoma (CHOL), colon adenocarcinoma (COAD), esophageal carcinoma (ESCA), glioblastoma multiforme (GBM), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), pheochromocytoma and paraganglioma (PCPG), stomach adenocarcinoma (STAD), thyroid carcinoma (THCA), uterine corpus endometrial carcinoma (UCEC), kidney chromophobe (KICH), and prostate adenocarcinoma (PRAD) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC, NT5DC2 protein expression was significantly upregulated in colon cancer, clear cell renal cell carcinoma (RCC), UCEC, lung adenocarcinoma, pancreatic adenocarcinoma (PAAD), glioblastoma multiforme, and hepatocellular carcinoma. The ROC curves were used to assess the diagnostic accuracy of the NT5DC2 gene signature. The AUC values indicated high diagnostic accuracy for CHOL (AUC\u0026thinsp;=\u0026thinsp;0.997), COAD (AUC\u0026thinsp;=\u0026thinsp;0.940), GBM (AUC\u0026thinsp;=\u0026thinsp;0.999), LIHC (AUC\u0026thinsp;=\u0026thinsp;0.932), PCPG (AUC\u0026thinsp;=\u0026thinsp;0.989), and rectal adenocarcinoma (READ) (AUC\u0026thinsp;=\u0026thinsp;0.962) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eImmune-Related Analysis of NT5DC2 in Human Cancer\u003c/h2\u003e \u003cp\u003eTo further investigate the relationship between NT5DC2 expression and the tumor microenvironment (TME), the ESTIMATE algorithm was used to assess associations between NT5DC2 expression and immune, stromal, and ESTIMATE scores. Regarding immune scores, positive correlations were observed between NT5DC2 expression and immune scores in BRCA and PRAD, whereas negative correlations were found in BLCA, CESC, ESCA, HNSC, GBM, LGG, LUAD, LUSC, MESO, OV, PCPG, SARC, SKCM, STAD, TGCT, and UCEC (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). To explore the association between NT5DC2 expression and immune cell infiltration across different tumors, the CIBERSORT algorithm was applied. The study focused on tumor-associated macrophages (TAMs), activated dendritic cells, and activated NK cells. The heatmap revealed that NT5DC2 expression was predominantly positively correlated with M2 TAM infiltration in most tumors, while negative correlations were observed with M1 TAMs, dendritic cells, and NK cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Additionally, correlation analyses between NT5DC2 expression and TMB as well as MSI across various tumors, were performed. NT5DC2 expression was significantly positively associated with TMB in BRCA, TGCT, STAD, SKCM, LUAD, LGG, KICH, GBM, and COAD, whereas a negative correlation was observed in PRAD. For MSI, NT5DC2 expression was positively correlated with MSI in BRCA, TGCT, STAD, SARC, MESO, LIHC, and HNSC, while a negative correlation was found in READ (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC-D).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eEnrichment Analysis of NT5DC2 in Pan-Cancer\u003c/h2\u003e \u003cp\u003eTo investigate the molecular mechanisms underlying NT5DC2 across different tumor types, GSEA was performed to identify pathways potentially influenced by NT5DC2 in pan-cancer. The six most significant KEGG pathways and generated forest plots across various cancer types were selected. The results indicated that NT5DC2 was significantly associated with multiple immune-related pathways, including antigen processing and presentation, primary immunodeficiency, the B cell receptor signaling pathway, and the intestinal immune network for IgA production. Additionally, NT5DC2 was linked to pathways regulating autophagy in ACC, CHOL, and LUSC. Notably, the most relevant pathway associated with NT5DC2 in pan-cancer was olfactory transduction (Fig.\u0026nbsp;3A-F).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eNT5DC2 Exhibits High Diagnostic and Prognostic Value in TNBC\u003c/h2\u003e \u003cp\u003eThe expression of NT5DC2 was significantly higher in TNBC compared to non-TNBC (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA), demonstrating high diagnostic value with an AUC of 0.895 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Additionally, Kaplan-Meier (K-M) survival curves indicated that high NT5DC2 expression was associated with a poorer prognosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). NT5DC2 also exhibited strong predictive value for TNBC patient prognosis at 1, 3, and 5 years (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). A nomogram based on multivariate analysis revealed that increased NT5DC2 expression significantly impacted age, N stage, T stage, and overall stage, whereas no impact was observed for M stage (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eSingle-Cell Analysis Reveals NT5DC2 Mediates Endothelial Cell-Driven Immune Suppression in TNBC\u003c/h2\u003e \u003cp\u003eSingle-cell analysis showed that NT5DC2 was primarily expressed in epithelial cells, with additional expression observed in stromal and plasma cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). In Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB, interactions between specific molecular combinations and target cell types in cell-cell communication were analyzed, revealing a significant enhancement of the MIF-CD74\u0026thinsp;+\u0026thinsp;CXCR4+/CD44\u0026thinsp;+\u0026thinsp;signaling pathway in endothelial cells. Further analysis of cell-cell communication between epithelial and other cell types indicated that NT5DC2 primarily regulates endothelial cells, likely influencing macrophages through macrophage migration inhibitory factor (MIF), with multiple immune cell types involved in this regulatory process (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). Additionally, GSEA analysis revealed suppression of immune-related pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD\u0026ndash;E), suggesting that NT5DC2 contributes to the immunosuppressive regulation of endothelial cells in TNBC. Moreover, NT5DC2 expression was negatively correlated with the infiltration of various immune cells across multiple immune infiltration algorithms (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eNT5DC2 Knockdown Inhibits Cell Viability in TNBC\u003c/h2\u003e \u003cp\u003eImmunohistochemical analysis revealed that NT5DC2 was highly expressed in TNBC tissues compared to normal tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). To investigate its oncogenic role, experimental verification in TNBC cells was conducted. NT5DC2 was successfully knocked down in MDA-MB-468 cells using NT5DC2 siRNA (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). The MTT assay demonstrated that NT5DC2 inhibition significantly reduced the cell viability of MDA-MB-468 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). Similarly, colony formation assays showed that NT5DC2 downregulation inhibited TNBC cell proliferation (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e6\u003c/span\u003eD). Furthermore, TUNEL staining indicated a significant increase in apoptotic MDA-MB-468 cells upon NT5DC2 knockdown (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e6\u003c/span\u003eE).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study found that NT5DC2 is highly expressed in multiple types of cancer and holds significant clinical relevance. Its expression correlates with the TME and plays a critical role in immune regulation. Notably, it was discovered that NT5DC2 is highly expressed in TNBC, with higher expression levels associated with poorer prognosis. Our findings indicate that NT5DC2 is closely linked to clinical diagnosis and prognosis, making it a valuable marker for cancer detection and therapeutic decision-making. Using single-cell RNA sequencing data, it was identified that NT5DC2 primarily regulates the immune microenvironment through the MIF signaling pathway, a relationship further supported by GSEA and immune cell infiltration analyses. Additionally, our study revealed a strong association between NT5DC2 expression and immune-related pathways, suggesting its involvement in immunosuppressive regulation. Furthermore, \u003cem\u003ein vitro\u003c/em\u003e experiments using TNBC cells confirmed the oncogenic role of NT5DC2.\u003c/p\u003e \u003cp\u003eOur analysis showed that NT5DC2 is highly expressed in most tumors, with notable exceptions in KICH, PRAD, and STAD. A model with a high AUC demonstrates high accuracy in distinguishing between cancer patients and healthy individuals or between different cancer types \u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. This is crucial for early cancer detection, guiding targeted treatment plans, and improving patient survival \u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. ROC curve analysis revealed the high diagnostic value of NT5DC2, particularly in CHOL, COAD, GBM, LIHC, PCPG, and READ, where AUC values were significantly elevated, underscoring its potential as a sensitive and specific biomarker. NT5DC2 is closely associated with the TME, which plays a critical role in tumor progression and therapy response\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. ESTIMATE score analysis indicated that NT5DC2 expression correlates with immune and stromal cell content across various cancers. NT5DC2 regulate immune responses, potentially affecting immune cell infiltration and immune checkpoint regulation \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. Specifically, NT5DC2 was linked to immune cell types such as dendritic cells, CD4⁺ T cells, CD8⁺ T cells, macrophages, and B cells in multiple tumors. The immune signaling pathways associated with KEGG analysis revealed NT5DC2 involvement in various immune pathways, including antigen processing, B cell receptor signaling, and the intestinal immune network for IgA production. The B-cell receptor signaling pathway is crucial for the normal development and adaptive immunity of B-cells, and it also plays a role in the microenvironment of solid tumors, such as squamous cell carcinoma and pancreatic cancer \u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. These findings strongly implicate NT5DC2 in tumors immune regulation.\u003c/p\u003e \u003cp\u003eIn TNBC, NT5DC2 not only served as a diagnostic and prognostic biomarker but also played a significant role in the immunosuppressive microenvironment. Single-cell analysis showed that NT5DC2 was primarily expressed in epithelial cells, interacting with immune cells via the MIF-CD74⁺CXCR4⁺/CD44⁺ signaling pathway, a known regulator of macrophage migration and immune suppression. Previous studies have demonstrated that MIF promotes an immunosuppressive microenvironment by enhancing neutrophil and Treg cell infiltration while inhibiting CD8⁺ T cell and M1 macrophage activation \u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. Additionally, GO and KEGG pathway analyses of NT5DC2 in TNBC confirmed its potential involvement in immune regulation. This was further supported by multiple immune infiltration algorithms, which showed a negative correlation between NT5DC2 expression and CD8⁺ T cell infiltration, underscoring its role as an immunosuppressive regulator in TNBC. CD8⁺ T cells, particularly those with a tissue-resident memory (TRM) phenotype, play a vital role in local immunity and enhancing responses to immunotherapy \u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. TRM-like cells expand in response to anti-PD-1 and anti-CTLA-4 immune checkpoint inhibition, providing sustained tissue-protective immunity against TNBC \u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn MDA-MB-231 TNBC cells, NT5DC2 knockdown reduced cell proliferation and increased apoptosis, confirming its oncogenic role. Immunohistochemical analysis further validated NT5DC2 overexpression in TNBC tumor tissues, reinforcing its clinical relevance. While our study provides valuable insights into the role of NT5DC2 in pan-cancer and TNBC, several limitations remain. First, although bioinformatics analyses across multiple public databases were conducted, further validation using independent cohorts and experimental models is necessary. Second, while NT5DC2\u0026rsquo;s potential was identified in TNBC, further investigation of its molecular mechanisms, both \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e, is essential to fully understand its oncogenic role and therapeutic implications.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, NT5DC2 exhibits potential as a diagnostic and prognostic biomarker in pan-cancer, particularly in TNBC. Our bioinformatics analyses indicate that NT5DC2 overexpression is linked to poor prognosis and plays a key role in the immunosuppressive microenvironment of TNBC. Further research is needed to clarify its molecular mechanisms in cancer progression and to explore its therapeutic potential.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe original data can be provided by the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Medical Ethics Committee of Wuxi Maternal and Child Health Hospital (approval no. 2023-01-0421-06; approval date, April 21, 2023) and was conducted in accordance with The Declaration of Helsinki. The participants provided written informed consent prior to taking part in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKe Wang and Yongxiang Yin: Writing, review, and/or revision of the manuscript; Qing Luo: Writing and revision of the manuscript, Xiandong Xie and Limei Mo: Data analysis and interpretation; Xiaomin Gao and Shu Li: Formal analysis; Jinqiu Zhang and Luyao Tian: validation; Xue Zhu: Funding acquisition. All authors approved final version of manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Major Project of Wuxi Municipal Health Commission (Z202303), Project of Jiangsu Commission of Health (H2023150) and the Project of Jiangsu Administration of Traditional Chinese Medicine (MS2022145, MS2023166).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient consent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eJokhadze N，Das A， and Dizon DS. Global cancer statistics: A healthy population relies on population health[J]. 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Tumor immune microenvironment analysis of non-small cell lung cancer development through multiplex immunofluorescence[J]. Transl Lung Cancer Res, 2024, 13(9)： 2395-2410.https://doi.org/10.21037/tlcr-24-379\u003c/li\u003e\n\u003cli\u003eWang D，Li S，Yang Z，et al. Single-cell transcriptome analysis deciphers the CD74-mediated immune evasion and tumour growth in lung squamous cell carcinoma with chronic obstructive pulmonary disease[J]. Clin Transl Med, 2024, 14(8)： e1786.https://doi.org/10.1002/ctm2.1786\u003c/li\u003e\n\u003cli\u003eYenyuwadee S，Sanchez-Trincado Lopez JL，Shah R，et al. The evolving role of tissue-resident memory T cells in infections and cancer[J]. Sci Adv, 2022, 8(33)： eabo5871.https://doi.org/10.1126/sciadv.abo5871\u003c/li\u003e\n\u003cli\u003eVirassamy B，Caramia F，Savas P，et al. Intratumoral CD8(+) T cells with a tissue-resident memory phenotype mediate local immunity and immune checkpoint responses in breast cancer[J]. Cancer Cell, 2023, 41(3)： 585-601.e8.https://doi.org/10.1016/j.ccell.2023.01.004\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"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":"NT5DC2, Pan-cancer, TNBC, Biomarker, Immune function","lastPublishedDoi":"10.21203/rs.3.rs-6212403/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6212403/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003e5\u0026prime;-Nucleotidase Domain Containing 2 (NT5DC2), a cNT5-II family member catalyzing nucleotide hydrolysis, plays a crucial role in tumor initiation and progression. This study aims to elucidate NT5DC2\u0026rsquo;s potential role in multiple cancers and confirm its oncogenic significance in triple-negative breast cancer (TNBC).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eMultiple databases analyzed NT5DC2 expression patterns and assessed its diagnostic and prognostic value in cancers. Immune correlation analyses were conducted using ESTIMATE and CIBERSORT. KEGG pathway enrichment analysis explored NT5DC2-associated molecular pathways. To further investigate its role in TNBC, comprehensive bioinformatics analyses, including gene expression profiling, single-cell RNA sequencing analysis, immune infiltration assessment, and gene set enrichment analysis (GSEA). Finally, \u003cem\u003ein vitro\u003c/em\u003e experiments were conducted to validate NT5DC2\u0026rsquo;s oncogenic role in TNBC.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOur findings indicate that high NT5DC2 expression is associated with poor prognosis and holds significant clinical diagnostic value across multiple cancer types. NT5DC2 is highly expressed in TNBC and correlates with unfavorable outcomes. Single-cell RNA sequencing analysis reveals that NT5DC2 is predominantly expressed in epithelial cells, where it regulates immune cells through the MIF signaling pathway. Enrichment and immune infiltration analyses indicate that NT5DC2 is closely linked to an immunosuppressive tumor microenvironment. \u003cem\u003eIn vitro\u003c/em\u003e experiments demonstrate that NT5DC2 knockdown significantly inhibits TNBC cell growth, underscoring its potential as a therapeutic target.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOur study demonstrates that NT5DC2 functions as an oncogene in multiple cancer types. It holds considerable clinical diagnostic significance and is intricately linked to an immunosuppressive tumor microenvironment, particularly in TNBC.\u003c/p\u003e","manuscriptTitle":"Pan-Cancer Analysis and Validation of NT5DC2: Emphasizing Its Prognostic Significance and Immunological Role in TNBC","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-31 11:19:21","doi":"10.21203/rs.3.rs-6212403/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-09T07:18:39+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-09T02:25:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"169288627908112396781180969258299934336","date":"2025-05-08T07:18:15+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-14T14:48:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"71063442699422619952221243296222134863","date":"2025-04-06T11:04:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"43977907552664688973723844846086988247","date":"2025-04-02T12:10:20+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-21T07:10:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-18T06:16:15+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-17T13:45:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Oncology","date":"2025-03-17T13:44:01+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":"31a2231c-57ef-4459-9b44-002262faaf7a","owner":[],"postedDate":"March 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-06-13T12:54:27+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-31 11:19:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6212403","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6212403","identity":"rs-6212403","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}