DCBLD1/CCNB1 Axis Confers Ferroptosis Resistance to Promote Breast Cancer Malignancy

DCBLD1/CCNB1 Axis Confers Ferroptosis Resistance to Promote Breast Cancer Malignancy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article DCBLD1/CCNB1 Axis Confers Ferroptosis Resistance to Promote Breast Cancer Malignancy Zhiyong Liu, Ran Chen, Hong Hu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8870092/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 DCBLD1 has emerged as an oncogene implicated in the progression of various cancers. Despite its recognized role in tumorigenesis, its precise mechanisms in breast cancer development remain largely undefined. Our comprehensive findings establish DCBLD1 as a crucial oncogenic driver and an independent prognostic indicator in breast cancer. Mechanistically, we demonstrate that DCBLD1 promotes malignant breast tumor progression by inhibiting ferroptosis through its direct regulation of CCNB1, ultimately leading to ACSL4 destabilization and degradation. This study unveils a novel DCBLD1-CCNB1-ACSL4 axis in ferroptosis regulation, providing critical insights into breast cancer pathogenesis and identifying potential therapeutic vulnerabilities Biological sciences/Cancer Biological sciences/Cell biology Biological sciences/Computational biology and bioinformatics Health sciences/Oncology DCBLD1 CCNB1 Ferroptosis Breast Cancer ACSL4 Tumor Progression Cell Cycle Therapeutic Target Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 INTRODUCTION Breast cancer remains a formidable global health challenge, representing the most frequently diagnosed cancer worldwide with over 2.3 million new cases annually and accounting for 11.7% of all cancer cases [1]. Molecularly, breast cancer is diverse, categorized into distinct subtypes including hormone receptor-positive/HER2-negative (Luminal A), hormone receptor-positive/HER2-positive (Luminal B), HER2-positive/hormone receptor-negative, and Triple-negative breast cancer (TNBC) [2]. These subtypes exhibit varying pathogenic mechanisms, metastatic patterns, prognoses, and therapeutic responses. Despite comprehensive treatment strategies involving surgery, chemotherapy, radiotherapy, endocrine therapy, HER2-targeted therapy, and immunotherapy, the incidence and mortality rates continue to rise, underscoring the urgent need for novel mechanistic insights and therapeutic targets [3]. DCBLD1 (Discoidin, CUB and LCCL domain-containing protein 1) is a highly conserved transmembrane protein, structurally similar to neuropilin, that has recently emerged as a significant oncogene [4–5]. Its overexpression is associated with poor prognosis in various cancers, including head and neck squamous cell carcinoma, non-small cell lung cancer, breast cancer, and pancreatic cancer [6–8]. While DCBLD1’s role in tumorigenesis is recognized, its specific mechanisms in breast cancer progression remain largely uncharacterized. CCNB1 (Cyclin B1) is a pivotal regulatory protein in cell cycle control, particularly critical during the G2/M phase transition where it forms the Maturation Promoting Factor (MPF) with CDK1 to drive mitosis [9–10]. Abnormal overexpression of CCNB1 is frequently observed in numerous malignancies, including breast cancer, where high expression correlates with increased proliferative activity and poor patient prognosis [11–13]. Recently, ferroptosis, a distinct form of iron-dependent programmed cell death characterized by the accumulation of lipid peroxides, has gained significant attention [14–15]. Unlike other cell death pathways, ferroptosis exhibits unique morphological features such as mitochondrial shrinkage and reduced mitochondrial cristae, while largely maintaining cell membrane integrity [16]. Key mechanisms driving ferroptosis involve dysregulated iron metabolism, glutathione (GSH) depletion, and loss of glutathione peroxidase 4 (GPX4) activity, collectively leading to heightened intracellular oxidative stress and lipid peroxidation [17–18]. Given the therapeutic potential of inducing ferroptosis in cancer, understanding its regulation, particularly in the context of oncogene activity, is crucial for developing new breast cancer treatments. MATERIALS AND METHODS Bioinformatic Analysis To investigate DCBLD1 expression profiles, we analyzed breast cancer and normal tissue samples from the Gene Expression Omnibus (GEO) database, specifically GSE54002. This expression profiling microarray dataset was subjected to Quantile normalization of its expression matrix using the R package affy, and differential expression analysis was subsequently performed using the R package limma. For prognostic analysis, breast cancer samples from the METABRIC database were accessed via cBioPortal ( https://www.cbioportal.org/ ). Corresponding clinical and expression data were downloaded. This dataset, also derived from expression profiling microarrays, utilized the downloaded normalized expression matrix directly for analysis without further processing or transformation. Tissue Microarray (TMA) Analysis To complement the bioinformatic findings, human breast tissue microarrays (TMAs) (Model No. HBreD161SU01-M-110) were obtained from Shanghai Zhuocheng Biotechnology Co., Ltd. These TMAs comprised 143 breast cancer tissue samples and 18 adjacent paracancerous tissue samples. Clinicopathological information corresponding to these samples was statistically analyzed in conjunction with relevant biological assays to experimentally validate the results obtained from bioinformatic analyses. This research was conducted with the approval of the ethics committee. Lentiviral Vector Construction and Packaging o modulate DCBLD1 and CCNB1 expression, shRNA sequences targeting human DCBLD1 (shDCBLD1-1: 5′-TAAGAAAGAAGATGAGACAAT-3′; shDCBLD1-2: 5′-GCAGGAATAATTGCTGATGAA-3′) and CCNB1 (shCCNB1: 5′-GGTAACAAAGTCAGTGAACAA-3′) were designed and synthesized (Yibeirui Bio tech Co., Ltd., Shanghai), annealed, and cloned into the lentiviral knockdown vector BR-V121 (VectorBuilder, USA) under a U6 promoter. Wild-type cDNAs of DCBLD1 and CCNB1 were amplified by PCR from human cDNA, digested, and subcloned into the overexpression vector BR-V121 (CMV promoter). For virus production, lentiviral vectors (knockdown or overexpression) were co-transfected with packaging plasmids psPAX2 (Addgene, USA) and pMD2.G (Addgene, USA)into HEK293T (ATCC, USA) cells using Lipofectamine 3000 (Thermo Fisher Scientific, USA). At 48 and 72 h post-transfection, supernatants were harvested, centrifuged at 2,500 × g for 10 min at 4°C to remove debris, filtered through 0.45 µm PVDF membranes, and concentrated by ultracentrifugation at 25,000 × g for 2.5 h at 4°C. The viral pellet was resuspended overnight at 4°C in PBS with 0.1% BSA, aliquoted, and stored at -80°C. Viral titer was determined by p24 ELISA or FACS (GFP-positive cells), and infection efficiency/target gene modulation were validated by qRT-PCR and Western blot. Quantitative PCR (qPCR) Total RNA was extracted using TRIzol reagent (Invitrogen, Thermo Fisher Scientific, USA) and reverse transcribed with HiScript® QRT SuperMix (Vazyme, China). qPCR was performed on a CFX96 system (Bio-Rad, USA) using ChamQ Universal SYBR qPCR Master Mix (Vazyme, China). Reactions (20 µL) contained 10 µL 2× SYBR Mix, 0.4 µL primers (10 µM), 1 µL cDNA, and 8.2 µL water. Cycling conditions: 95°C for 30 s, 40 cycles of 95°C for 10 s/60°C for 30 s, followed by melting curve analysis. Relative expression was calculated by 2-ΔΔCt method using GAPDH as reference. The primer sequences used here were as follows: DCBLD1: Forward, 5′-AAGGGATCAGTCGATATGAAGGG-3′; Reverse, 5′-ACAGAAATCGCTTGTCTGACAG-3′ CCNB1: Forward, 5′-TCGCATCAAACTCTCTGGCTA-3′; Reverse, 5′-TGAGCGACTAAACTCACCACT-3′ GAPDH (reference gene): Forward, 5′-ACAACTTTGGTATCGTGGAAGG-3′; Reverse, 5′-GCCATCACGCCACAGTTTC-3′ Co-immunoprecipitation (CO-IP) and Western blot analysis Cells were washed twice with pre - cold PBS and lysed in Flag lysis buffer for normal western blot or in BC100 buffer with protease inhibitor cocktail on ice for 30 min for co - IP, then centrifuged to remove debris. Protein concentration was measured by BCA assay, and supernatants were boiled with loading buffer. For normal western blot, samples were analyzed by SDS–PAGE and probed with specific antibodies (DCBLD1: Proteintech, 24504-1-AP, 1:500; CDK1: Proteintech, 10762-1-AP, 1:2000; CCNB1: Proteintech, 28603-1-AP, 1:3000; β-Actin: Proteintech, 66009-1-Ig, 1:20000; ACSL4: Proteintech, 22401-1-AP, 1:4000/1:2000; SLC7A11: Proteintech, 26864-1-AP, 1:1000; GAPDH: Proteintech, 60004-1-Ig, 1:30000). For Co-IP, supernatant was incubated with antibody-conjugated protein A/G beads overnight at 4°C, immunoprecipitates were washed and boiled, then analyzed by western blot with indicated antibodies. Cell viability detection 1x10 4 cells/well were seeded in 96-well plates. After 16–24 h, Cell viability was measured with Cell Counting Kit-8 (CCK-8) according to the manufacturer’s protocol. Briefly, 10 µl CCK8 reagent per well was diluted into 96 plates and incubated for 1 h. The absorbance of the samples at 450 nm was determined using microplate reader (Tecan infinite M2009PR). Relative cell viability was calculated by normalizing absorbance at 450 nm. Colony formation assay Cells (500/well) were seeded in 6-well plates (Cornin, USA) and cultured in complete medium (DMEM + 10% FBS + 1% penicillin-streptomycin) at 37°C, 5% CO₂. After 10–14 days, colonies were fixed with 4% paraformaldehyde (Sigma-Aldrich, USA) for 15 min, stained with 0.1% crystal violet (Beyotime, China) for 30 min, and washed with PBS (Gibco, USA). Colonies (> 50 cells) were counted under a microscope (Olympus, Japan). Experiments were performed in triplicate Flow Cytometry for Apoptosis Detection Cells subjected to various treatments were washed twice with ice-cold PBS. Subsequently, cells were resuspended in binding buffer and stained with Annexin V-FITC and PI dye, according to the manufacturer's instructions for the Annexin V-FITC Apoptosis Detection Kit (eBioscience 88-8007-74). After mixing, the samples were incubated in the dark at room temperature for 15 minutes. Immediately following incubation, samples were acquired using a Millipore Guava easyCyte HT™ flow cytometer, with at least 10,000 events collected per sample. Transwell Assays Cell migration was evaluated using 24-well Transwell chambers (8 µm pores, Corning #3422, USA). Cells (5×10⁴) in 200 µL serum-free medium were seeded into the upper chamber, with 600 µL complete medium (10% FBS) in the lower chamber as chemoattractant. After 24 h incubation at 37°C, non-migrated cells were removed with a cotton swab. Migrated cells on the lower surface were fixed with 4% paraformaldehyde (Sigma-Aldrich, USA) for 20 min and stained with 0.1% crystal violet (Beyotime, China) for 30 min. Migrated cells were counted in five random fields under 200× magnification (Olympus, Japan). Experiments were performed in triplicate. Wound Healing (Scratch) Assay Cells were grown to confluence in 96-well plates, and a linear scratch was made in the monolayer using a sterile pipette tip. After washing away detached cells with PBS, cultures were incubated in serum-free or low-serum medium. Images of the same wound areas were captured immediately (0 hours) and at later time points using an inverted microscope. The percentage of wound closure was then quantified by comparing the wound area at later time points to the initial area by Cellomics ArrayScan VTI Live Cell Module (Thermo) In Vivo Xenograft Tumor Model Female BALB/c nude mice (4–6 weeks old) were purchased from Changzhou Cavens Laboratory Animal Co., Ltd. (China). MDA-MB-231 cells stably transfected with shCtrl or shDCBLD1 lentiviral vectors were harvested and resuspended in PBS. A total of 5×10⁶ cells in 100 µL PBS were subcutaneously injected into the right flank of each mouse (n = 6 per group). Tumor growth was monitored for 21 days, with tumor volume measured every 3 days using a digital caliper and calculated as V = 0.5 × length × width². At the experimental endpoint, mice were euthanized by cervical dislocation, and tumors were harvested and weighed. All animal procedures were approved by the Institutional Animal Care and Use Committee of Wuhan Saishine Biomedical Technology Co., Ltd RESULTS DCBLD1 is highly expressed in breast cancer and correlates with unfavorable prognosis Public databases and patient cohorts were analyzed to elucidate the clinical relevance of DCBLD1 in breast cancer. Analysis of breast cancer samples from the GEO database (GSE54002) revealed significantly higher DCBLD1 expression in tumor tissues compared to normal controls (Fig. 1 a). Survival analysis using the METABRIC database showed that elevated DCBLD1 expression correlated with significantly shorter overall survival (OS) in breast cancer patients (Fig. 1 b). Furthermore, high DCBLD1 expression was positively correlated with advanced tumor grade and M value (Supplementary Fig. 1a-b). To complement the bioinformatic findings, we utilized human breast tissue microarrays (TMAs) (Model No. HBreD161SU01-M-110) acquired from Shanghai Zhuocheng Biotechnology Co., Ltd. These TMAs comprised 143 breast cancer tissue specimens and 18 adjacent paracancerous tissue samples. We then integrated the corresponding clinicopathological information and performed statistical and relevant biological assays on the samples to experimentally validate the results from the initial bioinformatic analyses (Table 1 ). This validation confirmed significantly higher DCBLD1 expression in tumor tissues compared to para-carcinoma tissues (Fig. 1 c). Consistently, patients exhibiting high DCBLD1 protein expression showed significantly reduced overall survival (OS) (Fig. 1 d). Collectively, these results strongly establish DCBLD1 as a potential prognostic biomarker and a driver of breast cancer progression. Table 1 Relationship between DCBLD1 expression and tumor characteristics in patients with breast cancer Characteristic No. of patients DCBLD1 expression p value Low High All patients 133 52 81 Age (years) 0.945 ≤ 47 67 26 41 >47 66 26 40 Grade P<0.001 II 75 48 27 III 58 4 54 tumor size (cm) 0.574 <3.5 68 25 43 ≥ 3.5 65 27 38 T stage 0.174 T1 20 6 14 T2 82 31 51 T3 31 15 16 Nodal Staging(N) 0.723 N0 42 16 26 N1 40 17 23 N2 46 19 27 N3 5 0 5 Metastasis Staging 0.009 M0 115 50 65 M1 18 2 16 DCBLD1 knockdown inhibits malignant phenotypes of breast cancer cells To investigate DCBLD1's functional role, we first screened breast cancer cell lines. qPCR revealed that DCBLD1 was highly expressed in several breast cancer cell lines, particularly MDA-MB-231 and BT-549 cells, compared to normal MCF-10A epithelial cells (Fig. S1 a). We then generated stable DCBLD1-knockdown MDA-MB-231 and BT-549 cell lines using shRNAs (sh-1 and sh-2), confirming robust knockdown in both cell lines (Fig. S1 b-d). Concurrently, flow cytometry analysis showed a significant increase in apoptosis following DCBLD1 knockdown (Fig. 2 c). Furthermore, DCBLD1 deficiency remarkably suppressed cell migration, demonstrated by impaired wound closure in scratch assays and reduced cell transmigration in Transwell assays (Fig. 2 d-e). These collective findings underscore DCBLD1's pro-oncogenic role in promoting breast cancer cell proliferation, survival, and migration. DCBLD1 regulates CCNB1 expression and interacts with the CCNB1-CDK1 complex Gene Set Enrichment Analysis (GSEA) suggested a potential link between DCBLD1 and cell cycle regulation (Fig. S2 ), which helps elucidate the underlying mechanisms. Protein-protein interaction analysis (STRING) and AlphaFold3 prediction indicated a putative interaction between DCBLD1 and the cell cycle regulator CCNB1 (Fig. S3 ). Consistent with this, Western blot and qPCR analyses demonstrated that DCBLD1 knockdown significantly reduced CCNB1 expression in both BT-549 and MDA-MB-231 cells (Fig. 3 a-b). Co-immunoprecipitation (Co-IP) assays further confirmed endogenous interactions between DCBLD1 and CCNB1, as well as between DCBLD1 and CDK1, in both cell lines (Fig. 3 c). Further Co-IP experiments confirmed that in DCBLD1-HA overexpressing cells, the CDK1-MYC signal in the immunoprecipitated complex was significantly enhanced, suggesting that DCBLD1 overexpression promotes the binding between CCNB1 and CDK1, thereby strengthening their interaction (Fig. 3 d). GSEA of METABRIC breast cancer data, stratified by CCNB1 expression, indicated CCNB1's negative correlation with mitochondrial oxidative stress and positive regulation of mitochondrial oxidative phosphorylation and respiratory chain complex assembly (Supplementary Fig. 4a-d). Intriguingly, CCNB1 expression also correlated with various ferroptosis-related markers (Supplementary Fig. 4e-i). Given that CCNB1-CDK1 complex can phosphorylate and promote the degradation of ferroptosis-related protein ACSL4, and that SQLE can stabilize CCNB1 to reduce ROS [19–21], we hypothesized that DCBLD1 enhances CCNB1-CDK1 interaction, stabilizes CCNB1, and accelerates ACSL4 degradation, thereby inhibiting ferroptosis and promoting breast cancer progression. DCBLD1 and CCNB1 regulate ferroptosis pathway activity To investigate the link between DCBLD1, CCNB1, and ferroptosis, Spearman correlation analysis of the GSE5764 breast cancer dataset revealed a negative correlation between ACSL4 and both CCNB1 and DCBLD1 expression (Fig. 4 a). Functionally, Western blot analysis demonstrated that CCNB1 knockdown significantly decreased the expression of ferroptosis inhibitors GPX4 and SLC7A11, while upregulating the pro-ferroptotic protein ACSL4 in both BT-549 and MDA-MB-231 cells (Fig. 4 b-c). Correspondingly, DCBLD1 knockdown led to decreased GSH concentration, increased intracellular iron, and elevated reactive oxygen species (ROS) levels (Fig. 4 d). Similarly, CCNB1 knockdwon consistently resulted in reduced GPX4 and SLC7A11, increased ACSL4, diminished GSH, enhanced iron accumulation, and elevated ROS levels in both cell lines (Fig. 4 e), confirming their shared role in regulating ferroptosis. DCBLD1-CCNB1 signaling axis-mediated ferroptosis suppression drives breast cancer We utilized a rescue experiment approach—overexpressing DCBLD1 and subsequently knocking down CCNB1 in breast cancer cells—to validate that DCBLD1 promotes breast cancer progression via the CCNB1-ferroptosis axis. DCBLD1 overexpression induced profound pro-ferroptotic metabolic alterations: a significant depletion of reduced glutathione (GSH) levels, an increase in intracellular labile iron (Fe2+) content, and elevated reactive oxygen species (ROS) accumulation. Crucially, these detrimental metabolic shifts were substantially attenuated, and the relevant indicators returned to baseline levels, when CCNB1 was simultaneously knocked down in the DCBLD1-overexpressing cells (Fig. 5 a). To further substantiate the role of the ferroptosis pathway, we performed a series of functional assays CCK-8 (Fig. 5 b, d), colony formation (Fig. 5 c), and Transwell assays (Fig. 5 e). DCBLD1 overexpression significantly enhanced tumor proliferation and migration. Conversely, CCNB1 knockdown notably reduced these malignant phenotypes. Consistent with the molecular findings, the enhanced proliferation and migration induced by DCBLD1 overexpression were reversed when CCNB1 was knocked down. Furthermore, treating DCBLD1-overexpressing breast cancer cells with the ferroptosis inducer Erastin [22] yielded functional changes in proliferation and migration that mimicked the effects observed in the DCBLD1 overexpression plus CCNB1 knockdown cells. This consistency provides strong evidence that DCBLD1 promotes malignant progression by suppressing ferroptosis via the CCNB1 axis. In vivo validation of the DCBLD1-CCNB1 axis promoting malignant cancer progression To confirm our in vitro findings, we established subcutaneous xenograft models in nude mice using DCBLD1-knockdown breast cancer cells. Compared to control groups, DCBLD1 knockout significantly reduced tumor weight and volume (Fig. 6 a-c). Immunohistochemical (IHC) staining of excised tumor tissues revealed that DCBLD1 knockdown inhibited the expression of the proliferation marker Ki-67 (Fig. 6 e), and reduced CCNB1 and CDK1 levels (Fig. 6 f-g). Crucially, DCBLD1 knockdown also significantly altered ferroptosis markers in vivo , leading to reduced GPX4 and SLC7A11, alongside elevated ACSL4 expression (Fig. 6 h-j). These in vivo results strongly corroborate the role of the DCBLD1-CCNB1 axis in promoting breast cancer progression by suppressing ferroptosis. DISCUSSION Cancer progression is governed by fundamental hallmarks, including resistance to cell death [23]. Our study identifies DCBLD1 as a novel oncogene in breast cancer, elucidating its mechanism in promoting tumorigenesis by inhibiting ferroptosis, a critical form of regulated cell death. Through integrated bioinformatic analysis, in vitro functional assays, and in vivo xenograft models, we consistently demonstrate that DCBLD1 is highly expressed in breast cancer, and its knockdown profoundly suppresses cell proliferation while concurrently inducing ferroptosis. Crucially, we unveil a novel DCBLD1/CCNB1/ferroptosis signaling axis, providing foundational insights into DCBLD1's biological function and highlighting its potential as a therapeutic target in breast cancer. Consistent with previous reports of DCBLD1's pro-tumorigenic role in other cancers [24, 25], we show its significant upregulation in breast cancer tissues and cell lines, correlating with unfavorable patient prognosis. Our key contribution is the novel finding that DCBLD1 promotes breast cancer progression by modulating ferroptosis, thereby expanding its functional repertoire within breast cancer biology. Mechanistically, DCBLD1 knockdown significantly reduced CCNB1 expression. As a pivotal G2/M cell cycle regulator, CCNB1 forms a complex with CDK1 to drive proliferation [26]. Importantly, CDK1 is known to phosphorylate and inhibit ACSL4, a key ferroptosis-executing enzyme [27]. Our findings validate that DCBLD1, by upregulating CCNB1, promotes its interaction with CDK1, ultimately leading to ACSL4 destabilization and ferroptosis suppression. This pathway precisely clarifies how DCBLD1 modulates ferroptosis. Ferroptosis, characterized by iron-dependent lipid peroxidation [28, 29], is increasingly recognized in cancer therapy. We observed that DCBLD1 knockdown promoted lipid ROS accumulation, downregulated GPX4 and SLC7A11, and upregulated ACSL4, all hallmarks of ferroptosis. These in vitro findings were robustly corroborated in vivo , where DCBLD1 knockdown significantly inhibited xenograft tumor growth and altered ferroptosis markers within tumor tissues. Furthermore, DCBLD1 knockdown also suppressed Ki-67 expression, suggesting a multi-faceted contribution to tumor development beyond ferroptosis modulation [30–32]. From a clinical perspective, the DCBLD1/CCNB1 axis represents a promising novel therapeutic target. Inducing ferroptosis is an emerging anti-cancer strategy [33, 34]. Combining DCBLD1 inhibition with ferroptosis activators could significantly improve breast cancer treatment, particularly for challenging subtypes like triple-negative breast cancer (TNBC) which lack targeted therapies. Despite these advancements, our study has limitations, primarily relying on cell lines and mouse models, necessitating validation in larger clinical cohorts. Future research should explore upstream regulatory mechanisms of DCBLD1, its potential role in modulating the immune microenvironment, or its involvement in other cell death pathways. In conclusion, we systematically elucidate that DCBLD1 promotes breast cancer progression by inhibiting ferroptosis via CCNB1. DCBLD1 emerges as both a crucial biomarker and a promising therapeutic target for ferroptosis-based breast cancer interventions. Declarations Acknowledgments We express our gratitude to the Breast Diagnosis and Treatment Center of the First Affiliated Hospital of Gannan Medical University for their support. Funding None. Conflicts of Interest The authors declare no conflicts of interest. Ethics declaration This study was conducted in accordance with the principles of the Declaration of Helsinki. Human breast tissue microarrays used in this study were obtained from Shanghai Zhuocheng Biotechnology Co., Ltd., and no human participants were recruited specifically for this research. All animal experiments were approved by the Institutional Animal Care and Use Committee of Wuhan Saishine Biomedical Technology Co., Ltd. (Protocol No. [SY202400212]), and were carried out in accordance with the relevant guidelines and regulations for the care and use of laboratory animals. Data Availability All data generated or analyzed during this study are included in this published article and its Supplementary Information files. 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Malumbres M, Barbacid M. Cell cycle, CDKs and cancer: a changing paradigm. Nat Rev Cancer. 2009 Mar;9(3):153 − 66. Singh M, Arora HL, Naik R, Joshi S, Sonawane K, Sharma NK, Sinha BK. Ferroptosis in Cancer: Mechanism and Therapeutic Potential. Int J Mol Sci. 2025 Apr 18;26(8):3852. Hassannia B, Vandenabeele P, Vanden Berghe T. Targeting Ferroptosis to Iron Out Cancer. Cancer Cell. 2019 Jun 10;35(6):830–849. Gown AM. The Biomarker Ki-67: Promise, Potential, and Problems in Breast Cancer. Appl Immunohistochem Mol Morphol. 2023 Aug 1;31(7):478–484. Lashen AG, Toss MS, Ghannam SF, Makhlouf S, Green A, Mongan NP, Rakha E. Expression, assessment and significance of Ki67 expression in breast cancer: an update. J Clin Pathol. 2023 Jun;76(6):357–364. Zhang A, Wang X, Fan C, Mao X. The Role of Ki67 in Evaluating Neoadjuvant Endocrine Therapy of Hormone Receptor-Positive Breast Cancer. Front Endocrinol (Lausanne). 2021 Nov 3; 12:687244. Hanker AB, Sudhan DR, Arteaga CL. Overcoming Endocrine Resistance in Breast Cancer. Cancer Cell. 2020 Apr 13;37(4):496–513. Zheng Q, Zhang M, Zhou F, Zhang L, Meng X. The Breast Cancer Stem Cells Traits and Drug Resistance. Front Pharmacol. 2021 Jan 28; 11:599965. Additional Declarations No competing interests reported. Supplementary Files SupplementaryInformationfile.pptx file.pptx OriginalimagesforWB.pdf Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 15 Apr, 2026 Reviews received at journal 03 Apr, 2026 Reviews received at journal 03 Apr, 2026 Reviewers agreed at journal 30 Mar, 2026 Reviewers agreed at journal 30 Mar, 2026 Reviewers invited by journal 15 Mar, 2026 Editor assigned by journal 12 Mar, 2026 Editor invited by journal 24 Feb, 2026 Submission checks completed at journal 23 Feb, 2026 First submitted to journal 23 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8870092","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":606505005,"identity":"91978a24-c72a-4c6d-8bcc-a5b587421542","order_by":0,"name":"Zhiyong Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIie3QLQvCQBjA8ecYbGW6ekm/womgDsY+i2NwFoPRpCfCkmDdkl/BaHz00KRYDQbTrBOLweBbVM7ZDPcrx8Hz514ANO0PsddCS2VniJgxz8+TEAHQqFbiVTCPOzzMm3QDge2qtLPFY6dWtzbHw2lGyUAgkx5DAyy5nKoSd9SqDJI1NSxDNGWb7Ytgc75TXgw5GRYiahKBeE9SA6hdUyfb9JnYgIGQDSaJ+JrsXqdQwBAk5EncOCVJElF2/2SYjxgPzW9vqTscslPU60+c8Tm7XD3fseRKmbwzfxvXNE3TPrkBFSlQOdHeMXoAAAAASUVORK5CYII=","orcid":"","institution":"The First Affiliated Hospital of Gannan Medical University","correspondingAuthor":true,"prefix":"","firstName":"Zhiyong","middleName":"","lastName":"Liu","suffix":""},{"id":606505006,"identity":"34a9b321-7df7-46ec-80b9-22547c4d55ad","order_by":1,"name":"Ran Chen","email":"","orcid":"","institution":"The First Affiliated Hospital of Gannan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ran","middleName":"","lastName":"Chen","suffix":""},{"id":606505008,"identity":"ba0ab009-4865-4e4b-81ba-119cad8e5335","order_by":2,"name":"Hong Hu","email":"","orcid":"","institution":"The First Affiliated Hospital of Gannan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Hong","middleName":"","lastName":"Hu","suffix":""}],"badges":[],"createdAt":"2026-02-13 09:39:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8870092/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8870092/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105033893,"identity":"fcc11d8d-59ba-4701-b6c0-6660c6d84572","added_by":"auto","created_at":"2026-03-20 07:22:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":374331,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDCBLD1 is highly expressed in breast cancer and correlates with unfavorable prognosis.\u003c/strong\u003e \u003cstrong\u003ea\u003c/strong\u003e DCBLD1 expression in breast cancer tissues and normal tissues in GSE54002 (P-value = 0.0113; adjusted P-value [Padj] = 0.0225, Benjamini-Hochberg corrected). The log2 Fold Change (log2FC) of DCBLD1 expression between cancerous and normal tissues was 0.536, indicating a notable upregulation in tumors. \u003cstrong\u003eb\u003c/strong\u003e Survival analysis of breast cancer samples from the METABRIC database in high DCBLD1 high expression vs low expressions. high DCBLD1 expression in breast cancer was significantly associated with poorer overall survival (Log-rank P = 1.93e-06; HR = 1.33, 95% CI: 1.18-1.49).\u003cstrong\u003e c\u003c/strong\u003e DCBLD1 expression in breast cancer tissues and para-carcinoma tissues on human tissue microarrays. \u003cstrong\u003ed\u003c/strong\u003e Survival analysis of breast cancer samples from the human tissue microarrays in high DCBLD1 high expression vs low expressions (Log-rank P = 0.0005; HR = 2.43, 95% CI: 1.46-4.02).\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8870092/v1/649d3b0f19e40ad0b0ae7174.png"},{"id":104841289,"identity":"1cf02245-c750-4c57-b481-f3a0a506af76","added_by":"auto","created_at":"2026-03-17 19:37:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":708486,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDCBLD1 knockdown inhibits malignant phenotypes of breast cancer cells. a \u003c/strong\u003eCell proliferation was evaluated using the Cell Counting Kit-8 (CCK-8) assay measured by the absorbance of OD450. \u003cstrong\u003eb \u003c/strong\u003eCell proliferative capacity was assessed using a colony formation assay. \u003cstrong\u003ec \u003c/strong\u003eCell apoptosis assessment via flow cytometry. \u003cstrong\u003ed \u003c/strong\u003eAssessing cell migration and invasion using a wound healing assay.\u003cstrong\u003e e \u003c/strong\u003eAssessing the migratory and invasive capabilities of tumor cells using a Transwell assay.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8870092/v1/0f98732bc497baeee4c7e6f8.png"},{"id":104841287,"identity":"0f37216e-aed1-4d25-b361-28cc6f70a208","added_by":"auto","created_at":"2026-03-17 19:37:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":319149,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDCBLD1 regulates CCNB1 expression and interacts with the CCNB1-CDK1 complex. a\u003c/strong\u003e mRNA level analysis of CCNB1 in DCBLD1-knockdown cells by qPCR. \u003cstrong\u003eb\u003c/strong\u003e Western blot analysis of CCNB1 expression in DCBLD1-knockdown cells. \u003cstrong\u003ec\u003c/strong\u003e Co-IP experiment to analyze the relationship between DCBLD1 and CCNB1 or CDK1 in HEK293T cells. \u003cstrong\u003ed \u003c/strong\u003eCo-IP experiment to analyze the relationship between DCBLD1 and the CCNB1-CDK1 complex in HEK293T cells.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8870092/v1/f121a25ea96afd745f381fc6.png"},{"id":104841290,"identity":"1ea05e65-8d8b-4876-9ac7-cb8fa01397fe","added_by":"auto","created_at":"2026-03-17 19:37:35","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":405710,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDCBLD1 and CCNB1 regulate ferroptosis pathway activity. a\u003c/strong\u003e Spearman correlation analysis between DCBLD1/ CCNB1 and ACSL4 in GSE54002.\u003cstrong\u003eb\u003c/strong\u003e Western blot analysis of ferroptosis-related proteins (GPX4/SLC7A11/ACSL4) expression in DCBLD1-knockdown cells. \u003cstrong\u003ec\u003c/strong\u003e Western blot analysis of ferroptosis-related proteins (GPX4/SLC7A11/ACSL4) expression in CCNB1-knockdown cells. \u003cstrong\u003ed \u003c/strong\u003eAnalysis of key ferroptotic metabolic indicators (GSH/intracellular iron/reactive oxygen species) level\u003cstrong\u003e \u003c/strong\u003ein DCBLD1-knockdown cells. \u003cstrong\u003ee \u003c/strong\u003eAnalysis of key ferroptotic metabolic indicators (GSH/intracellular iron/reactive oxygen species) level in CCNB1-knockdown cells.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8870092/v1/7d71706b92f0f110158688a2.jpeg"},{"id":104841293,"identity":"00f23e4e-f081-4314-93bb-a1d31a3aee3f","added_by":"auto","created_at":"2026-03-17 19:37:35","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":480466,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDCBLD1-CCNB1 signaling axis-mediated ferroptosis suppression drives breast cancer. a \u003c/strong\u003eGSH concentration, intracellular labile iron (Fe2+) content, and ROS accumulation in DCBLD1 overexpression, CCNB1 knockdown, and DCBLD1 overexpression + CCNB1 knockdown breast cancer cells. \u003cstrong\u003eb\u003c/strong\u003eCell proliferation quantified by the CCK-8 assay in DCBLD1 OE, CCNB1 KD, DCBLD1 OE + CCNB1 KD, and DCBLD1 OE cells treated with Erastin (ferroptosis inducer).\u003cstrong\u003ec\u003c/strong\u003e Cell proliferation measured by the colony formation assay in DCBLD1 OE, CCNB1 KD, DCBLD1 OE + CCNB1 KD, and DCBLD1 OE cells treated with Erastin. \u003cstrong\u003ed\u003c/strong\u003eCell proliferation quantified by the CCK-8 assay in DCBLD1 OE, CCNB1 KD, and DCBLD1 OE cells treated with Erastin (ferroptosis inducer). \u003cstrong\u003ee \u003c/strong\u003eCell migration measured by the Transwell assay in DCBLD1 OE, CCNB1 KD, DCBLD1 OE + CCNB1 KD, and DCBLD1 OE cells treated with Erastin.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8870092/v1/460a048c0228e5f51799ea90.png"},{"id":105033879,"identity":"61dc07ba-2256-401a-bbcf-5e65f6a9585b","added_by":"auto","created_at":"2026-03-20 07:22:02","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":771198,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eIn vivo \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003evalidation of the DCBLD1-CCNB1 axis promoting malignant cancer progression. \u003c/strong\u003eTumor growth and Western blot analysis: \u003cstrong\u003ea\u003c/strong\u003e Tumor volume monitored over the designated experimental period. \u003cstrong\u003eb\u003c/strong\u003e Macroscopic size and weight of tumors harvested at the study endpoint. \u003cstrong\u003ec\u003c/strong\u003e Western blot analysis of DCBLD1, CCNB1, and CDK1 expression in harvested tumor tissues. Immunohistochemistry (IHC) Analysis: The expression levels of the indicated proteins were assessed using Immunohistochemistry (IHC) analysis on paraffin-embedded tumor tissue samples. \u003cstrong\u003ed\u003c/strong\u003e DCBLD1 expression.\u003cstrong\u003e e\u003c/strong\u003eKi67 expression (proliferation marker). \u003cstrong\u003ef\u003c/strong\u003e CDK1 expression. \u003cstrong\u003eg\u003c/strong\u003eCCNB1 expression. \u003cstrong\u003eh\u003c/strong\u003e GPX4 expression.\u003cstrong\u003e i \u003c/strong\u003eSLC7A11 expression. \u003cstrong\u003ej\u003c/strong\u003eACSL4 expression.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8870092/v1/8ecd66a797d1772174441764.png"},{"id":105563039,"identity":"72c69789-9548-4706-beb6-1478653401a3","added_by":"auto","created_at":"2026-03-27 12:45:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4128892,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8870092/v1/e634b9ac-25d7-419b-a2b1-ddac1e765d75.pdf"},{"id":104841295,"identity":"5619402a-9ede-4ae0-94ae-e6f5ecbbf613","added_by":"auto","created_at":"2026-03-17 19:37:36","extension":"pptx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":2729806,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformationfile.pptx","url":"https://assets-eu.researchsquare.com/files/rs-8870092/v1/788c2c26d4b8f58e8cd49178.pptx"},{"id":104841294,"identity":"59e00146-1974-456a-8e35-6cc4b0e344db","added_by":"auto","created_at":"2026-03-17 19:37:36","extension":"pptx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":19699085,"visible":true,"origin":"","legend":"","description":"","filename":"file.pptx","url":"https://assets-eu.researchsquare.com/files/rs-8870092/v1/b96833b3d4fc6639890ca6f1.pptx"},{"id":105033884,"identity":"86c58e8e-8429-4db3-a3a5-7ba7a84476ca","added_by":"auto","created_at":"2026-03-20 07:22:03","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":340759,"visible":true,"origin":"","legend":"","description":"","filename":"OriginalimagesforWB.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8870092/v1/5676613a59edbc51507b2c32.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"DCBLD1/CCNB1 Axis Confers Ferroptosis Resistance to Promote Breast Cancer Malignancy","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eBreast cancer remains a formidable global health challenge, representing the most frequently diagnosed cancer worldwide with over 2.3\u0026nbsp;million new cases annually and accounting for 11.7% of all cancer cases [1]. Molecularly, breast cancer is diverse, categorized into distinct subtypes including hormone receptor-positive/HER2-negative (Luminal A), hormone receptor-positive/HER2-positive (Luminal B), HER2-positive/hormone receptor-negative, and Triple-negative breast cancer (TNBC) [2]. These subtypes exhibit varying pathogenic mechanisms, metastatic patterns, prognoses, and therapeutic responses. Despite comprehensive treatment strategies involving surgery, chemotherapy, radiotherapy, endocrine therapy, HER2-targeted therapy, and immunotherapy, the incidence and mortality rates continue to rise, underscoring the urgent need for novel mechanistic insights and therapeutic targets [3].\u003c/p\u003e \u003cp\u003eDCBLD1 (Discoidin, CUB and LCCL domain-containing protein 1) is a highly conserved transmembrane protein, structurally similar to neuropilin, that has recently emerged as a significant oncogene [4\u0026ndash;5]. Its overexpression is associated with poor prognosis in various cancers, including head and neck squamous cell carcinoma, non-small cell lung cancer, breast cancer, and pancreatic cancer [6\u0026ndash;8]. While DCBLD1\u0026rsquo;s role in tumorigenesis is recognized, its specific mechanisms in breast cancer progression remain largely uncharacterized.\u003c/p\u003e \u003cp\u003eCCNB1 (Cyclin B1) is a pivotal regulatory protein in cell cycle control, particularly critical during the G2/M phase transition where it forms the Maturation Promoting Factor (MPF) with CDK1 to drive mitosis [9\u0026ndash;10]. Abnormal overexpression of CCNB1 is frequently observed in numerous malignancies, including breast cancer, where high expression correlates with increased proliferative activity and poor patient prognosis [11\u0026ndash;13].\u003c/p\u003e \u003cp\u003eRecently, ferroptosis, a distinct form of iron-dependent programmed cell death characterized by the accumulation of lipid peroxides, has gained significant attention [14\u0026ndash;15]. Unlike other cell death pathways, ferroptosis exhibits unique morphological features such as mitochondrial shrinkage and reduced mitochondrial cristae, while largely maintaining cell membrane integrity [16]. Key mechanisms driving ferroptosis involve dysregulated iron metabolism, glutathione (GSH) depletion, and loss of glutathione peroxidase 4 (GPX4) activity, collectively leading to heightened intracellular oxidative stress and lipid peroxidation [17\u0026ndash;18]. Given the therapeutic potential of inducing ferroptosis in cancer, understanding its regulation, particularly in the context of oncogene activity, is crucial for developing new breast cancer treatments.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eBioinformatic Analysis\u003c/h2\u003e \u003cp\u003eTo investigate DCBLD1 expression profiles, we analyzed breast cancer and normal tissue samples from the Gene Expression Omnibus (GEO) database, specifically GSE54002. This expression profiling microarray dataset was subjected to Quantile normalization of its expression matrix using the R package affy, and differential expression analysis was subsequently performed using the R package limma. For prognostic analysis, breast cancer samples from the METABRIC database were accessed via cBioPortal (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cbioportal.org/\u003c/span\u003e\u003cspan address=\"https://www.cbioportal.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Corresponding clinical and expression data were downloaded. This dataset, also derived from expression profiling microarrays, utilized the downloaded normalized expression matrix directly for analysis without further processing or transformation.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTissue Microarray (TMA) Analysis\u003c/h3\u003e\n\u003cp\u003eTo complement the bioinformatic findings, human breast tissue microarrays (TMAs) (Model No. HBreD161SU01-M-110) were obtained from Shanghai Zhuocheng Biotechnology Co., Ltd. These TMAs comprised 143 breast cancer tissue samples and 18 adjacent paracancerous tissue samples. Clinicopathological information corresponding to these samples was statistically analyzed in conjunction with relevant biological assays to experimentally validate the results obtained from bioinformatic analyses. This research was conducted with the approval of the ethics committee.\u003c/p\u003e\n\u003ch3\u003eLentiviral Vector Construction and Packaging\u003c/h3\u003e\n\u003cp\u003eo modulate DCBLD1 and CCNB1 expression, shRNA sequences targeting human DCBLD1 (shDCBLD1-1: 5\u0026prime;-TAAGAAAGAAGATGAGACAAT-3\u0026prime;; shDCBLD1-2: 5\u0026prime;-GCAGGAATAATTGCTGATGAA-3\u0026prime;) and CCNB1 (shCCNB1: 5\u0026prime;-GGTAACAAAGTCAGTGAACAA-3\u0026prime;) were designed and synthesized (Yibeirui Bio tech Co., Ltd., Shanghai), annealed, and cloned into the lentiviral knockdown vector BR-V121 (VectorBuilder, USA) under a U6 promoter. Wild-type cDNAs of DCBLD1 and CCNB1 were amplified by PCR from human cDNA, digested, and subcloned into the overexpression vector BR-V121 (CMV promoter). For virus production, lentiviral vectors (knockdown or overexpression) were co-transfected with packaging plasmids psPAX2 (Addgene, USA) and pMD2.G (Addgene, USA)into HEK293T (ATCC, USA) cells using Lipofectamine 3000 (Thermo Fisher Scientific, USA). At 48 and 72 h post-transfection, supernatants were harvested, centrifuged at 2,500 \u0026times; g for 10 min at 4\u0026deg;C to remove debris, filtered through 0.45 \u0026micro;m PVDF membranes, and concentrated by ultracentrifugation at 25,000 \u0026times; g for 2.5 h at 4\u0026deg;C. The viral pellet was resuspended overnight at 4\u0026deg;C in PBS with 0.1% BSA, aliquoted, and stored at -80\u0026deg;C. Viral titer was determined by p24 ELISA or FACS (GFP-positive cells), and infection efficiency/target gene modulation were validated by qRT-PCR and Western blot.\u003c/p\u003e\n\u003ch3\u003eQuantitative PCR (qPCR)\u003c/h3\u003e\n\u003cp\u003eTotal RNA was extracted using TRIzol reagent (Invitrogen, Thermo Fisher Scientific, USA) and reverse transcribed with HiScript\u0026reg; QRT SuperMix (Vazyme, China). qPCR was performed on a CFX96 system (Bio-Rad, USA) using ChamQ Universal SYBR qPCR Master Mix (Vazyme, China). Reactions (20 \u0026micro;L) contained 10 \u0026micro;L 2\u0026times; SYBR Mix, 0.4 \u0026micro;L primers (10 \u0026micro;M), 1 \u0026micro;L cDNA, and 8.2 \u0026micro;L water. Cycling conditions: 95\u0026deg;C for 30 s, 40 cycles of 95\u0026deg;C for 10 s/60\u0026deg;C for 30 s, followed by melting curve analysis. Relative expression was calculated by 2-ΔΔCt method using GAPDH as reference.\u003c/p\u003e \u003cp\u003eThe primer sequences used here were as follows:\u003c/p\u003e \u003cp\u003eDCBLD1: Forward, 5\u0026prime;-AAGGGATCAGTCGATATGAAGGG-3\u0026prime;; Reverse, 5\u0026prime;-ACAGAAATCGCTTGTCTGACAG-3\u0026prime;\u003c/p\u003e \u003cp\u003eCCNB1: Forward, 5\u0026prime;-TCGCATCAAACTCTCTGGCTA-3\u0026prime;; Reverse, 5\u0026prime;-TGAGCGACTAAACTCACCACT-3\u0026prime;\u003c/p\u003e \u003cp\u003eGAPDH (reference gene): Forward, 5\u0026prime;-ACAACTTTGGTATCGTGGAAGG-3\u0026prime;; Reverse, 5\u0026prime;-GCCATCACGCCACAGTTTC-3\u0026prime;\u003c/p\u003e\n\u003ch3\u003eCo-immunoprecipitation (CO-IP) and Western blot analysis\u003c/h3\u003e\n\u003cp\u003eCells were washed twice with pre - cold PBS and lysed in Flag lysis buffer for normal western blot or in BC100 buffer with protease inhibitor cocktail on ice for 30 min for co - IP, then centrifuged to remove debris. Protein concentration was measured by BCA assay, and supernatants were boiled with loading buffer. For normal western blot, samples were analyzed by SDS\u0026ndash;PAGE and probed with specific antibodies (DCBLD1: Proteintech, 24504-1-AP, 1:500; CDK1: Proteintech, 10762-1-AP, 1:2000; CCNB1: Proteintech, 28603-1-AP, 1:3000; β-Actin: Proteintech, 66009-1-Ig, 1:20000; ACSL4: Proteintech, 22401-1-AP, 1:4000/1:2000; SLC7A11: Proteintech, 26864-1-AP, 1:1000; GAPDH: Proteintech, 60004-1-Ig, 1:30000). For Co-IP, supernatant was incubated with antibody-conjugated protein A/G beads overnight at 4\u0026deg;C, immunoprecipitates were washed and boiled, then analyzed by western blot with indicated antibodies.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eCell viability detection\u003c/h2\u003e \u003cp\u003e1x10\u003csup\u003e4\u003c/sup\u003e cells/well were seeded in 96-well plates. After 16\u0026ndash;24 h, Cell viability was measured with Cell Counting Kit-8 (CCK-8) according to the manufacturer\u0026rsquo;s protocol. Briefly, 10 \u0026micro;l CCK8 reagent per well was diluted into 96 plates and incubated for 1 h. The absorbance of the samples at 450 nm was determined using microplate reader (Tecan infinite M2009PR). Relative cell viability was calculated by normalizing absorbance at 450 nm.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eColony formation assay\u003c/h3\u003e\n\u003cp\u003eCells (500/well) were seeded in 6-well plates (Cornin, USA) and cultured in complete medium (DMEM\u0026thinsp;+\u0026thinsp;10% FBS\u0026thinsp;+\u0026thinsp;1% penicillin-streptomycin) at 37\u0026deg;C, 5% CO₂. After 10\u0026ndash;14 days, colonies were fixed with 4% paraformaldehyde (Sigma-Aldrich, USA) for 15 min, stained with 0.1% crystal violet (Beyotime, China) for 30 min, and washed with PBS (Gibco, USA). Colonies (\u0026gt;\u0026thinsp;50 cells) were counted under a microscope (Olympus, Japan). Experiments were performed in triplicate\u003c/p\u003e\n\u003ch3\u003eFlow Cytometry for Apoptosis Detection\u003c/h3\u003e\n\u003cp\u003eCells subjected to various treatments were washed twice with ice-cold PBS. Subsequently, cells were resuspended in binding buffer and stained with Annexin V-FITC and PI dye, according to the manufacturer's instructions for the Annexin V-FITC Apoptosis Detection Kit (eBioscience 88-8007-74). After mixing, the samples were incubated in the dark at room temperature for 15 minutes. Immediately following incubation, samples were acquired using a Millipore Guava easyCyte HT\u0026trade; flow cytometer, with at least 10,000 events collected per sample.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eTranswell Assays\u003c/h2\u003e \u003cp\u003eCell migration was evaluated using 24-well Transwell chambers (8 \u0026micro;m pores, Corning #3422, USA). Cells (5\u0026times;10⁴) in 200 \u0026micro;L serum-free medium were seeded into the upper chamber, with 600 \u0026micro;L complete medium (10% FBS) in the lower chamber as chemoattractant. After 24 h incubation at 37\u0026deg;C, non-migrated cells were removed with a cotton swab. Migrated cells on the lower surface were fixed with 4% paraformaldehyde (Sigma-Aldrich, USA) for 20 min and stained with 0.1% crystal violet (Beyotime, China) for 30 min. Migrated cells were counted in five random fields under 200\u0026times; magnification (Olympus, Japan). Experiments were performed in triplicate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eWound Healing (Scratch) Assay\u003c/h2\u003e \u003cp\u003eCells were grown to confluence in 96-well plates, and a linear scratch was made in the monolayer using a sterile pipette tip. After washing away detached cells with PBS, cultures were incubated in serum-free or low-serum medium. Images of the same wound areas were captured immediately (0 hours) and at later time points using an inverted microscope. The percentage of wound closure was then quantified by comparing the wound area at later time points to the initial area by Cellomics ArrayScan VTI Live Cell Module (Thermo)\u003c/p\u003e \u003cp\u003e \u003cb\u003eIn Vivo\u003c/b\u003e \u003cb\u003eXenograft Tumor Model\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFemale BALB/c nude mice (4\u0026ndash;6 weeks old) were purchased from Changzhou Cavens Laboratory Animal Co., Ltd. (China). MDA-MB-231 cells stably transfected with shCtrl or shDCBLD1 lentiviral vectors were harvested and resuspended in PBS. A total of 5\u0026times;10⁶ cells in 100 \u0026micro;L PBS were subcutaneously injected into the right flank of each mouse (n\u0026thinsp;=\u0026thinsp;6 per group). Tumor growth was monitored for 21 days, with tumor volume measured every 3 days using a digital caliper and calculated as V\u0026thinsp;=\u0026thinsp;0.5 \u0026times; length \u0026times; width\u0026sup2;. At the experimental endpoint, mice were euthanized by cervical dislocation, and tumors were harvested and weighed. All animal procedures were approved by the Institutional Animal Care and Use Committee of Wuhan Saishine Biomedical Technology Co., Ltd\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eDCBLD1 is highly expressed in breast cancer and correlates with unfavorable prognosis\u003c/h2\u003e \u003cp\u003ePublic databases and patient cohorts were analyzed to elucidate the clinical relevance of DCBLD1 in breast cancer. Analysis of breast cancer samples from the GEO database (GSE54002) revealed significantly higher DCBLD1 expression in tumor tissues compared to normal controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). Survival analysis using the METABRIC database showed that elevated DCBLD1 expression correlated with significantly shorter overall survival (OS) in breast cancer patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). Furthermore, high DCBLD1 expression was positively correlated with advanced tumor grade and M value (Supplementary Fig.\u0026nbsp;1a-b). To complement the bioinformatic findings, we utilized human breast tissue microarrays (TMAs) (Model No. HBreD161SU01-M-110) acquired from Shanghai Zhuocheng Biotechnology Co., Ltd. These TMAs comprised 143 breast cancer tissue specimens and 18 adjacent paracancerous tissue samples. We then integrated the corresponding clinicopathological information and performed statistical and relevant biological assays on the samples to experimentally validate the results from the initial bioinformatic analyses (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This validation confirmed significantly higher DCBLD1 expression in tumor tissues compared to para-carcinoma tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). Consistently, patients exhibiting high DCBLD1 protein expression showed significantly reduced overall survival (OS) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed). Collectively, these results strongly establish DCBLD1 as a potential prognostic biomarker and a driver of breast cancer progression.\u003c/p\u003e \u003cp\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\u003eRelationship between DCBLD1 expression and tumor characteristics in patients with breast cancer\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNo. of patients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eDCBLD1 expression\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll patients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.945\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etumor size (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.574\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT stage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.174\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNodal Staging(N)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.723\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetastasis Staging\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\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=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eDCBLD1 knockdown inhibits malignant phenotypes of breast cancer cells\u003c/h2\u003e \u003cp\u003eTo investigate DCBLD1's functional role, we first screened breast cancer cell lines. qPCR revealed that DCBLD1 was highly expressed in several breast cancer cell lines, particularly MDA-MB-231 and BT-549 cells, compared to normal MCF-10A epithelial cells (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003ea). We then generated stable DCBLD1-knockdown MDA-MB-231 and BT-549 cell lines using shRNAs (sh-1 and sh-2), confirming robust knockdown in both cell lines (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eb-d). Concurrently, flow cytometry analysis showed a significant increase in apoptosis following DCBLD1 knockdown (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). Furthermore, DCBLD1 deficiency remarkably suppressed cell migration, demonstrated by impaired wound closure in scratch assays and reduced cell transmigration in Transwell assays (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed-e). These collective findings underscore DCBLD1's pro-oncogenic role in promoting breast cancer cell proliferation, survival, and migration.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eDCBLD1 regulates CCNB1 expression and interacts with the CCNB1-CDK1 complex\u003c/h2\u003e \u003cp\u003eGene Set Enrichment Analysis (GSEA) suggested a potential link between DCBLD1 and cell cycle regulation (Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e), which helps elucidate the underlying mechanisms. Protein-protein interaction analysis (STRING) and AlphaFold3 prediction indicated a putative interaction between DCBLD1 and the cell cycle regulator CCNB1 (Fig. \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). Consistent with this, Western blot and qPCR analyses demonstrated that DCBLD1 knockdown significantly reduced CCNB1 expression in both BT-549 and MDA-MB-231 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea-b). Co-immunoprecipitation (Co-IP) assays further confirmed endogenous interactions between DCBLD1 and CCNB1, as well as between DCBLD1 and CDK1, in both cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). Further Co-IP experiments confirmed that in DCBLD1-HA overexpressing cells, the CDK1-MYC signal in the immunoprecipitated complex was significantly enhanced, suggesting that DCBLD1 overexpression promotes the binding between CCNB1 and CDK1, thereby strengthening their interaction (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed).\u003c/p\u003e \u003cp\u003eGSEA of METABRIC breast cancer data, stratified by CCNB1 expression, indicated CCNB1's negative correlation with mitochondrial oxidative stress and positive regulation of mitochondrial oxidative phosphorylation and respiratory chain complex assembly (Supplementary Fig.\u0026nbsp;4a-d). Intriguingly, CCNB1 expression also correlated with various ferroptosis-related markers (Supplementary Fig.\u0026nbsp;4e-i). Given that CCNB1-CDK1 complex can phosphorylate and promote the degradation of ferroptosis-related protein ACSL4, and that SQLE can stabilize CCNB1 to reduce ROS [19\u0026ndash;21], we hypothesized that DCBLD1 enhances CCNB1-CDK1 interaction, stabilizes CCNB1, and accelerates ACSL4 degradation, thereby inhibiting ferroptosis and promoting breast cancer progression.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eDCBLD1 and CCNB1 regulate ferroptosis pathway activity\u003c/h2\u003e \u003cp\u003eTo investigate the link between DCBLD1, CCNB1, and ferroptosis, Spearman correlation analysis of the GSE5764 breast cancer dataset revealed a negative correlation between ACSL4 and both CCNB1 and DCBLD1 expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003eFunctionally, Western blot analysis demonstrated that CCNB1 knockdown significantly decreased the expression of ferroptosis inhibitors GPX4 and SLC7A11, while upregulating the pro-ferroptotic protein ACSL4 in both BT-549 and MDA-MB-231 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb-c). Correspondingly, DCBLD1 knockdown led to decreased GSH concentration, increased intracellular iron, and elevated reactive oxygen species (ROS) levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed). Similarly, CCNB1 knockdwon consistently resulted in reduced GPX4 and SLC7A11, increased ACSL4, diminished GSH, enhanced iron accumulation, and elevated ROS levels in both cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee), confirming their shared role in regulating ferroptosis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eDCBLD1-CCNB1 signaling axis-mediated ferroptosis suppression drives breast cancer\u003c/h2\u003e \u003cp\u003eWe utilized a rescue experiment approach\u0026mdash;overexpressing DCBLD1 and subsequently knocking down CCNB1 in breast cancer cells\u0026mdash;to validate that DCBLD1 promotes breast cancer progression via the CCNB1-ferroptosis axis. DCBLD1 overexpression induced profound pro-ferroptotic metabolic alterations: a significant depletion of reduced glutathione (GSH) levels, an increase in intracellular labile iron (Fe2+) content, and elevated reactive oxygen species (ROS) accumulation. Crucially, these detrimental metabolic shifts were substantially attenuated, and the relevant indicators returned to baseline levels, when CCNB1 was simultaneously knocked down in the DCBLD1-overexpressing cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003eTo further substantiate the role of the ferroptosis pathway, we performed a series of functional assays CCK-8 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb, d), colony formation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec), and Transwell assays (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ee). DCBLD1 overexpression significantly enhanced tumor proliferation and migration. Conversely, CCNB1 knockdown notably reduced these malignant phenotypes. Consistent with the molecular findings, the enhanced proliferation and migration induced by DCBLD1 overexpression were reversed when CCNB1 was knocked down. Furthermore, treating DCBLD1-overexpressing breast cancer cells with the ferroptosis inducer Erastin [22] yielded functional changes in proliferation and migration that mimicked the effects observed in the DCBLD1 overexpression plus CCNB1 knockdown cells. This consistency provides strong evidence that DCBLD1 promotes malignant progression by suppressing ferroptosis via the CCNB1 axis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eIn vivo\u003c/b\u003e \u003cb\u003evalidation of the DCBLD1-CCNB1 axis promoting malignant cancer progression\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo confirm our in vitro findings, we established subcutaneous xenograft models in nude mice using DCBLD1-knockdown breast cancer cells. Compared to control groups, DCBLD1 knockout significantly reduced tumor weight and volume (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea-c). Immunohistochemical (IHC) staining of excised tumor tissues revealed that DCBLD1 knockdown inhibited the expression of the proliferation marker Ki-67 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ee), and reduced CCNB1 and CDK1 levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ef-g). Crucially, DCBLD1 knockdown also significantly altered ferroptosis markers \u003cem\u003ein vivo\u003c/em\u003e, leading to reduced GPX4 and SLC7A11, alongside elevated ACSL4 expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eh-j). These \u003cem\u003ein vivo\u003c/em\u003e results strongly corroborate the role of the DCBLD1-CCNB1 axis in promoting breast cancer progression by suppressing ferroptosis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eCancer progression is governed by fundamental hallmarks, including resistance to cell death [23]. Our study identifies DCBLD1 as a novel oncogene in breast cancer, elucidating its mechanism in promoting tumorigenesis by inhibiting ferroptosis, a critical form of regulated cell death. Through integrated bioinformatic analysis, in vitro functional assays, and \u003cem\u003ein vivo\u003c/em\u003e xenograft models, we consistently demonstrate that DCBLD1 is highly expressed in breast cancer, and its knockdown profoundly suppresses cell proliferation while concurrently inducing ferroptosis. Crucially, we unveil a novel DCBLD1/CCNB1/ferroptosis signaling axis, providing foundational insights into DCBLD1's biological function and highlighting its potential as a therapeutic target in breast cancer.\u003c/p\u003e \u003cp\u003eConsistent with previous reports of DCBLD1's pro-tumorigenic role in other cancers [24, 25], we show its significant upregulation in breast cancer tissues and cell lines, correlating with unfavorable patient prognosis. Our key contribution is the novel finding that DCBLD1 promotes breast cancer progression by modulating ferroptosis, thereby expanding its functional repertoire within breast cancer biology.\u003c/p\u003e \u003cp\u003eMechanistically, DCBLD1 knockdown significantly reduced CCNB1 expression. As a pivotal G2/M cell cycle regulator, CCNB1 forms a complex with CDK1 to drive proliferation [26]. Importantly, CDK1 is known to phosphorylate and inhibit ACSL4, a key ferroptosis-executing enzyme [27]. Our findings validate that DCBLD1, by upregulating CCNB1, promotes its interaction with CDK1, ultimately leading to ACSL4 destabilization and ferroptosis suppression. This pathway precisely clarifies how DCBLD1 modulates ferroptosis.\u003c/p\u003e \u003cp\u003eFerroptosis, characterized by iron-dependent lipid peroxidation [28, 29], is increasingly recognized in cancer therapy. We observed that DCBLD1 knockdown promoted lipid ROS accumulation, downregulated GPX4 and SLC7A11, and upregulated ACSL4, all hallmarks of ferroptosis. These in vitro findings were robustly corroborated \u003cem\u003ein vivo\u003c/em\u003e, where DCBLD1 knockdown significantly inhibited xenograft tumor growth and altered ferroptosis markers within tumor tissues. Furthermore, DCBLD1 knockdown also suppressed Ki-67 expression, suggesting a multi-faceted contribution to tumor development beyond ferroptosis modulation [30\u0026ndash;32].\u003c/p\u003e \u003cp\u003eFrom a clinical perspective, the DCBLD1/CCNB1 axis represents a promising novel therapeutic target. Inducing ferroptosis is an emerging anti-cancer strategy [33, 34]. Combining DCBLD1 inhibition with ferroptosis activators could significantly improve breast cancer treatment, particularly for challenging subtypes like triple-negative breast cancer (TNBC) which lack targeted therapies.\u003c/p\u003e \u003cp\u003eDespite these advancements, our study has limitations, primarily relying on cell lines and mouse models, necessitating validation in larger clinical cohorts. Future research should explore upstream regulatory mechanisms of DCBLD1, its potential role in modulating the immune microenvironment, or its involvement in other cell death pathways. In conclusion, we systematically elucidate that DCBLD1 promotes breast cancer progression by inhibiting ferroptosis via CCNB1. DCBLD1 emerges as both a crucial biomarker and a promising therapeutic target for ferroptosis-based breast cancer interventions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eWe express our gratitude to the Breast Diagnosis and Treatment Center of the First Affiliated Hospital of Gannan Medical University for their support.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the principles of the Declaration of Helsinki. Human breast tissue microarrays used in this study were obtained from Shanghai Zhuocheng Biotechnology Co., Ltd., and no human participants were recruited specifically for this research.\u003c/p\u003e\n\u003cp\u003eAll animal experiments were approved by the Institutional Animal Care and Use Committee of Wuhan Saishine Biomedical Technology Co., Ltd. (Protocol No. [SY202400212]), and were carried out in accordance with the relevant guidelines and regulations for the care and use of laboratory animals.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in this published article and its Supplementary Information files. Raw data are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eConceptualization and design:\u003c/strong\u003e Zhi-yong Liu, Ran Chen.\u003cbr\u003e\u003cstrong\u003eData collection and analysis:\u003c/strong\u003e Zhi-yong Liu, Ran Chen.\u003cbr\u003e\u003cstrong\u003eManuscript drafting and revision:\u003c/strong\u003e Zhi-yong Liu, Ran Chen.\u003cbr\u003e\u0026nbsp;All authors have read and approved the final manuscript and agree to be accountable for all aspects of the work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. 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Front Pharmacol. 2021 Jan 28; 11:599965.\u003c/li\u003e\n\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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"DCBLD1, CCNB1, Ferroptosis, Breast Cancer, ACSL4, Tumor Progression, Cell Cycle, Therapeutic Target","lastPublishedDoi":"10.21203/rs.3.rs-8870092/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8870092/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDCBLD1 has emerged as an oncogene implicated in the progression of various cancers. Despite its recognized role in tumorigenesis, its precise mechanisms in breast cancer development remain largely undefined. Our comprehensive findings establish DCBLD1 as a crucial oncogenic driver and an independent prognostic indicator in breast cancer. Mechanistically, we demonstrate that DCBLD1 promotes malignant breast tumor progression by inhibiting ferroptosis through its direct regulation of CCNB1, ultimately leading to ACSL4 destabilization and degradation. This study unveils a novel DCBLD1-CCNB1-ACSL4 axis in ferroptosis regulation, providing critical insights into breast cancer pathogenesis and identifying potential therapeutic vulnerabilities\u003c/p\u003e","manuscriptTitle":"DCBLD1/CCNB1 Axis Confers Ferroptosis Resistance to Promote Breast Cancer Malignancy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-17 19:37:30","doi":"10.21203/rs.3.rs-8870092/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-15T09:33:59+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-03T20:04:12+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-03T13:41:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"135654323576951271799428277167153202187","date":"2026-03-30T15:41:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"114368211525655114166123947305340919999","date":"2026-03-30T04:40:59+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-16T01:02:11+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-13T02:33:46+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-24T19:23:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-23T07:52:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-02-23T07:48:29+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bfb749f3-bf64-4ff9-b59d-c4690bffa030","owner":[],"postedDate":"March 17th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":64537404,"name":"Biological sciences/Cancer"},{"id":64537405,"name":"Biological sciences/Cell biology"},{"id":64537406,"name":"Biological sciences/Computational biology and bioinformatics"},{"id":64537407,"name":"Health sciences/Oncology"}],"tags":[],"updatedAt":"2026-05-11T01:23:30+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-17 19:37:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8870092","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8870092","identity":"rs-8870092","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}