Epigenetic activation of VEGFA by SMARCD1 mediates tumor progression and bevacizumab resistance in clear cell renal cell carcinoma

Epigenetic activation of VEGFA by SMARCD1 mediates tumor progression and bevacizumab resistance in clear cell renal cell carcinoma | 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 Epigenetic activation of VEGFA by SMARCD1 mediates tumor progression and bevacizumab resistance in clear cell renal cell carcinoma Hanqing Liu, Yan Shen, Yuchen Hou, Congyun Xu, Xiaoyu Bai, Yixun Liu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8031896/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 23 Mar, 2026 Read the published version in BMC Cancer → Version 1 posted 12 You are reading this latest preprint version Abstract Background Clear cell renal cell carcinoma (ccRCC) is an aggressive malignancy characterized by strong invasiveness and treatment resistance. Although SMARCD1 has been studied in several cancers, its function in ccRCC and its regulatory relationship with the key angiogenic factor VEGFA remain unexplored. Methods Clinical relevance of SMARCD1 was assessed through in vitro experiments and data analysis. Integrated in vivo and in vitro functional studies evaluated SMARCD1’s biological impact in ccRCC. SMARCD1-VEGFA epigenetic regulation was investigated via ChIP-qPCR, ATAC-qPCR, luciferase reporter assays, and HUVEC angiogenesis models. Bevacizumab-resistant cell lines and combination therapy models were established to validate SMARCD1’s role in drug resistance. Results SMARCD1 expression was significantly upregulated in ccRCC tissues and was strongly correlated with both disease progression and adverse clinical outcomes. Functionally, we have demonstrated that SMARCD1 promotes tumor proliferation, migration, and angiogenesis. Mechanistically, we have discovered that SMARCD1 binds directly to the VEGFA promoter, enhancing chromatin accessibility and modifying histone marks to activate transcriptional expression. The pro-tumor effects of SMARCD1 were found to be critically dependent on VEGFA. Furthermore, SMARCD1 knockdown sensitized bevacizumab-resistant ccRCC models to anti-angiogenic therapy. Conclusion This study establishes that SMARCD1 promotes ccRCC progression and bevacizumab resistance by epigenetically remodeling the VEGFA promoter region. These findings provide a mechanistic foundation for novel precision therapies targeting the SMARCD1-VEGFA axis. SMARCD1 VEGFA ccRCC Epigenetics Angiogenesis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Renal cell carcinoma (RCC) encompasses several subtypes. Among these, ccRCC is the predominant malignant tumor of the kidney, representing 70–80% of RCC. The disease is known for its aggressive and metastatic behavior and is frequently discovered incidentally through abdominal imaging [ 1 , 2 ]. The standard first-line treatment is surgery, nonetheless, some patients experience recurrence or distant metastasis after surgery, and ccRCC is notably resistant to radiotherapy, chemotherapy, and immunotherapy [ 2 – 4 ]. The 2022 WHO classification of kidney tumors newly included “molecularly defined renal carcinomas” as a distinct category, emphasizing the growing role of molecular mechanisms in precision medicine [ 5 ] Thus, it is critical to improve early detection and treatment for advanced or metastatic ccRCC by identifying new biomarkers and therapeutic targets, and clarifying their molecular mechanisms. SMARCD1 (BAF60A), a core subunit of the SWI/SNF chromatin remodeling complex, recognizes histone modifications such as H3K4me3 and recruits remodeling enzymes [ 6 , 7 ]. Emerging evidence suggests that SMARCD1 overexpression differentially affects patient survival across cancer types. In liver cancer, SMARCD1 serves as a key prognostic gene, promoting tumor growth through activation of the mTOR signaling pathway[ 8 ]. In bladder cancer, knockdown of SMARCD1 significantly inhibits cancer cell proliferation, migration, and invasion, while also increasing sensitivity to gemcitabine [ 9 ]. In acute myeloid leukemia (AML), leukemic cell lines rely on SMARCD1-maintained high promoter accessibility [ 10 ].However, the function and mechanisms of SMARCD1 remain unexplored in ccRCC. This study may provide valuable insights for identifying novel therapeutic targets and sensitive biomarkers in ccRCC. As reported, VEGFA is highly expressed in ccRCC compared to other epithelial cancers, making VEGFA targeting a fundamental component of ccRCC management [ 11 , 12 ]. As a key member of the VEGF family, VEGFA acts as a master regulator of tumor angiogenesis [ 13 ]. Anti-angiogenic therapies targeting the VEGF signaling pathway are particularly relevant for treating ccRCC, given that it is a highly vascular tumor [ 14 ]. VEGFA is modulated by histone modifications: enrichment of H3K27ac promotes its expression at enhancers, whereas H3K9me3 has a repressive effect [ 15 ]. The anti-angiogenic drug bevacizumab works by sequestering VEGFA, thus blocking its receptor interaction and inhibiting tumor blood vessel growth [ 16 ]. However, acquired resistance commonly develops in ccRCC patients. Emerging evidence indicates that epigenetic reprogramming plays a key role in this process [ 17 , 18 ]. In resistant tumor cells, the VEGFA locus adopts a more open chromatin architecture, characterized by increased H3K27ac modification at enhancers, thereby maintaining a transcription-ready state. This epigenetic memory enables sustained VEGFA expression under therapeutic pressure, providing a molecular basis for drug resistance [ 19 ]. In this study, we identified SMARCD1 overexpression in ccRCC, which correlated with poor patient prognosis. Functional assays demonstrated that SMARCD1 promotes ccRCC progression and metastasis. Moreover, we found that SMARCD1 modulates chromatin accessibility at the VEGFA promoter region. We further investigated whether SMARCD1 is associated with drug resistance in ccRCC. In summary, our findings indicate that SMARCD1 promotes proliferation, metastasis, and confers bevacizumab resistance in ccRCC by epigenetically remodeling and opening the VEGFA promoter region. Methods and materials Human Clear Cell Renal Cell Carcinoma (ccRCC) Tissues This study utilized clinical specimens and related patient information under the approval of the Ethics Committee of Anhui Provincial Hospital. From June 2021 to August 2025, we collected 220 ccRCC specimens and matched adjacent non-neoplastic tissues from the Department of Urology at Anhui Provincial Hospital. Fresh ccRCC and normal tissues were preserved in liquid nitrogen. A tissue microarray (TMA) comprising these 220 samples (107 males, 113 females; 133 stage I–II, 74 stage III, 13 stage IV) was constructed by Ruichuang Biotechnology Co., Ltd. (Shanghai, China). We have obtained written informed consent from all participants. Methodologies for Cell Culture and Transfection The RCC cell lines (Caki-2, 786-O, KMRC-2, ACHN, SLR-23, SLR-20) were acquired from the ATCC (Manassas, VA). Cells were cultured in RPMI 1640 (786-O, SLR-20, ACHN, KMRC-2) or DMEM (SLR-23, Caki-2, 293T), with 10% fetal bovine serum (FBS). Cells were used within 18 passages after thawing in this study. Cell culture was performed in a humidified incubator at 37°C with 5% CO2, with passaging conducted every 2–4 days. SiRNAs targeting SMARCD1, PBRM1, SMARCA2, and SMARCA4 were diluted to 20 µM using DEPC water. Approximately 2×10⁵ cells were plated per well in 6-well plates. After 24 hours, Lipofectamine 3000–siRNA complexes were prepared in DMEM with 10% FBS and applied to the cells. Cells were harvested 48 hours post-transfection for downstream assays. siSMARCD1: AUGAGGAAACGGCUAGAUATT; siPBRM1: GAAGAGGUUUUCACUCUCUGCUAAA; siSMARCA2: CCGCATAGCTCATAGGATA; siSMARCA4: GCAUUUCAAGGAAUAUCACTT As to lentivirus plasmids, virus production used 293 T cells. Briefly, 70–80% confluency of cells was co-transfected with the shRNA lentivector and helper plasmids psPAX2/pMD2.G in 6-well plates. Fresh complete medium supplemented with 10% FBS was used to replace the old medium after overnight incubation. Viral supernatants were collected at 48- and 72- hours post-transfection, with fresh medium added again after the first collection. The combined supernatants were concentrated by low-speed centrifugation and then filtered through 0.45 µm filters. ccRCC cells were plated in 6-well plates to reach approximately 50–70% confluency. Each well was then transduced with 100 µL of viral supernatant supplemented with 4–8 µg/mL polybrene. The medium was replaced after 12–18 hours. After an additional 48-hour incubation period, selection of transduced cells was performed with 2 µg/mL puromycin. Knockdown efficiency was verified by Western blot. The oligonucleotide sequences used are listed below (5′→3′): shRNA1: 5′-AAGTCCTTGGTGATTGAACTGGA-3′ shRNA2: 5′-AATGTACGGTGTACTGTCCTACT-3′ Stable Gene Knockout Using CRISPR/Cas9 The pX459 plasmid was used to deliver SMARCD1-targeting sgRNAs into 786-O or KMRC-2 cells. Twenty-four hours later, transfected cells underwent a 7-day puromycin selection treatment at a concentration of 1 µg/mL. Monoclonal lines were established in 96-well plates. Knockout efficiency was verified by Western blot and qPCR. The sgRNA sequences used were: SMARCD1-sgRNA-1: TGATGTGGTGGGTAACCCAGAGG SMARCD1-sgRNA-2: AGTTTTCAGAGATCCCTCAGCGG Quantitative Real-Time PCR (qRT-PCR) Total RNA was extracted using the Sparkjade SPARKeasy Cell RNA Kit (AC0205B). Gene expression was quantified by qRT-PCR employing the TIANGEN FastReal SYBR Green Kit (FP217-01). The endogenous control gene β-actin was used for normalization, and relative expression levels were determined by the 2⁻ΔΔCt method. Primer sequences: SMARCD1: F: 5′-AAACGGAAGCTGCGAATTTTC-3′, R: 5′-AGCCGTCCTTCTACCCGAA-3′ VEGFA: F: 5′-GAGCCTTGCCTTGCTGCTCTA-3′, R: 5′-CACCAGGGTCTCGATTGGATG-3′ Cell Proliferation Assays For the MTT assay, we seeded approximately 3,000 cells per well in 96-well plates after transfection with siRNA or plasmids. Then, 20 µL of MTT reagent (BS186, Biosharp, China) was added to each well, and the plates were incubated at 37°C for 4 hours. Following incubation, the resulting formazan crystals were dissolved in 150 µL of DMSO with gentle shaking for 10 minutes. Absorbance was subsequently measured at 570 nm using a microplate reader. In the CCK-8 assay, tumor cells were plated in 96-well plates at a density of 3000 cells per well, with 100 µL of DMEM medium containing 10% FBS. The medium of all groups was refreshed every two days, and 10 µL of CCK-8 solution was introduced per the manufacturer's protocol (Dojindo, Kumamoto, Japan). After a 2-hour incubation at 37°C in the absence of light, cell viability was assessed by measuring the absorbance at 450 nm. For the colony formation assay, transfected cells were seeded in 6-well plates at a density of approximately 800 cells per well and cultured under the indicated treatment conditions for 12 days. Subsequently, the colonies were fixed with 4% paraformaldehyde (PFA) for 30 minutes and stained with 0.1% crystal violet for an additional 30 minutes. Transwell assays For migration and invasion assays, 40,000 cells were seeded in the upper chamber using serum-free DMEM, while the lower chamber was filled with DMEM supplemented with 20% FBS. For the invasion assay, the membrane was pre-coated with Matrigel. After 24 hours, non-migratory/non-invasive cells were gently removed from the upper chamber. Cells that had migrated or invaded to the lower surface were fixed, stained, and quantified by counting under a microscope. Five randomly selected fields were imaged and analyzed for each replicate. Western Blotting For western blotting, transfected cells were collected approximately 2×105, lysed with 250 µL RIPA buffer (BI-WB013, SBJbio). Protein concentration was quantified using a bicinchoninic acid (BCA) assay. Subsequently, they were separated using SDS-PAGE(GF1810, GeneFist, China) and transferred to PVDF membranes༈EMD Millipore, Billerica, MA, USA). Membranes were blocked with 5% non-fat milk for 1 hour and incubation with primary antibodies at 4°C overnight. After washing with TBST, the membranes were incubated with secondary antibodies for 1 hour at room temperature. Protein bands were visualized using an enhanced chemiluminescence (ECL) detection system and analyzed. Mouse xenograft models and experiments All animal experiments were approved by the Animal Experimentation Ethics Committee of The First Affiliated Hospital of the University of Science and Technology of China (Approval No. 2025-N(A)-0148). Female BALB/c nude mice (4–6 weeks old) were obtained from Shanghai SLAC Laboratory Animal Co., Ltd. and randomly assigned to experimental groups. Each mouse received a subcutaneous injection of 5×10⁶ 786-O cells suspended in 100 µL of a 1:1 mixture of PBS and Matrigel. Tumor size was monitored every 7 days starting from day 7 after injection. Tumor volumes were calculated according to the formula: V (mm³) = 0.52 × length (mm) × width² (mm²). On day 42, all mice were humanely euthanized, and final tumor volumes and weights were recorded. For orthotopic models, 786-O cells were injected into the kidneys of 6-week-old female nude mice as previously described. To enable in vivo tracking of lung metastasis, cells were transduced with a CMV-Luc-PGK-puro lentivirus (Genomeditech) prior to injection. For bevacizumab efficacy evaluation, 4×10⁵ 786-O-BR or KMRC-2-BR cells were injected directly into the mouse kidney. Beginning on day 7 post-injection, tumor-bearing mice were randomly assigned to receive either bevacizumab or placebo every other day. Tumor volume was measured every 7 days following initiation of treatment. All animals were euthanized at 6 weeks post-injection. Immunohistochemistry (IHC) was carried out as described previously [ 20 ]. Gene Set Enrichment Analysis (GSEA) GSEA was conducted using the TCGA dataset and CCLE data. Samples were categorized into high and low SMARCD1 expression groups according to the median expression value. Enrichment analysis was performed using GSEA v4.3.3. Chromatin immunoprecipitation (ChIP)-qPCR assay We first cross-linked 1×10⁷ 786-O cells with 1% formaldehyde at room temperature for 15 minutes and then quenched the reaction by incubating with 0.25 M glycine for an additional 5 minutes in preparation for the ChIP-qPCR assay. Nuclear lysates were sonicated to shear DNA to fragments of approximately 400–800 base pairs. Chromatin fragments were precipitated with specific antibodies and protein A/G agarose beads at 4°C for 16 hours. After washing and reverse cross-linking, gene expression in the ChIP products was measured by RT-qPCR. Sequences used are listed below. VEGFA-promoter (5′→3′): GGCGGGTAGGTTTGAATC (sense), CGTATGCACTGTGGAGTC (antisense). Luciferase Reporter Assay Using FuGENE 6 transfection reagent (Roche, Indianapolis, IN, USA), we plated cells at 50% confluence in 24-well plates and transfected them with 200 ng of a firefly luciferase reporter construct along with 1 ng of the pRL-SV40 Renilla luciferase construct for normalization. After 48 hours, we prepared cell extracts and measured luciferase activities following the protocol of the Dual-Luciferase Reporter Assay System (Promega, Sunnyvale, CA, USA). Tube Formation Assay We evaluated the tube formation capability of HUVECs. Briefly, we thawed growth Matrigel (BD Biosciences, Franklin Lakes, NJ) on ice and gently mixed it with an equal volume of DMEM. Then, 200 µL of this mixture were aliquoted into each well of a 24-well plate and allowed to polymerize at 37°C for 30 minutes. Following gel formation, we seeded HUVECs from each experimental group at a density of 1×10⁵ cells per well in 500 µL of serum-free medium. The plates were incubated for 12 hours under standard culture conditions (37°C, 5% CO₂). We captured images of the resulting tubular networks using an inverted microscope and analyzed five randomly selected fields per well with ImageJ software equipped with the Angiogenesis Analyzer plugin. Quantification included both total tube length and number of complete tubular structures. All experiments were performed in three independent replicates. Statistical Analysis Our studies were conducted with 5–10 mice per group or triplicated in independent cell-based assays. Results are displayed as mean ± SD or SEM in the figures. Cox proportional hazards regression was carried out using SPSS 22.0. Statistical significance was determined using Student’s t test, one-way ANOVA, two-way ANOVA, Pearson correlation, and log-rank test in GraphPad Prism 9.5 and R v4.3.2., the 0.05 level of confidence was accepted for statistical significance. Result 1. High SMARCD1 Expression is Associated with Poor Prognosis in ccRCC To investigate the clinical significance of SMARCD1 in ccRCC, we examined SMARCD1 protein expression in 8 pairs of freshly collected ccRCC specimens and matched adjacent normal kidney tissues. SMARCD1 levels were elevated in all 8 tumor samples compared to their normal counterparts, as detected by western blot.(Fig. 1 A). We further validated this finding using a tissue microarray (TMA) containing 220 ccRCC cases, which included both tumor and paired non-tumor kidney tissues. Immunohistochemical (IHC staining consistently demonstrated stronger SMARCD1 expression in tumor tissues relative to normal sections (Fig. 1 B). Moreover, SMARCD1 expression was markedly elevated in high-grade relative to low-grade ccRCC specimens (Fig. 1 C). Notably, the intensity of SMARCD1 immunostaining showed a positive correlative trend with clinicopathological stage, tumor grade, and metastatic progression (Figs. 1 D–F). We analyzed the relationship between SMARCD1 expression and overall survival in the TCGA-KIRC cohort. Using the TCGA database, we successfully stratified ccRCC patients into two groups based on SMARCD1 levels. Significant differences in overall survival were observed among these groups (N = 530, log-rank test P < 0.001, Fig. 1 G). As expected, Kaplan-Meier survival curve analysis indicated that ccRCC patients from our cohort (Anhui Provincial Hospital) with high SMARCD1 expression had a more unfavorable prognosis than those with low SMARCD1 (N = 200, log-rank test P < 0.001, Fig. 1 H). To comprehensively and systematically evaluate the functional contributions of SMARCD1 homologous members (such as SMARCA2, SMARCA4, and PBRM1) to ccRCC pathogenesis, we conducted a targeted siRNA-based screen in ccRCC cell lines. As reported, SMARCA2 and SMARCA4 are canonical oncogenes, while PBRM1 is a tumor suppressor gene [ 21 ]. Compared to these classical oncogenes and tumor suppressors, MTT assays identified SMARCD1 as an equally potent oncogenic driver, in which SMARCD1 knockdown resulted in a substantial decrease in cell growth (Fig. 1 I). To study the biological function of SMARCD1 in appropriate cell lines, we grouped them into SMARCD1-low (SLR-23, Caki-2, ACHN) and SMARCD1-high (KMRC-2, 786-O, SLR-20) based on RT-qPCR analysis (Fig. 1 J). In summary, SMARCD1 is frequently upregulated in ccRCC and may represent an independent chromatin-regulatory factor linked to unfavorable clinical outcomes in patients. 2. SMARCD1 is Essential for ccRCC Cell Proliferation and Migration To identify suitable cell lines for experiments, using two different shRNA constructs to knock down SMARCD1, we observed that SMARCD1 knockdown suppressed the proliferation of canonical ccRCC cells such as 786-O, KMRC-2, and SLR-20 cells (Fig. 2 A). To determine whether SMARCD1 regulates ccRCC cell proliferation in vitro, we used CRISPR-Cas9 technology to delete SMARCD1 in 786-O and KMRC-2 cells, as verified by Western blotting (Fig. 2 B). As expected, CCK-8 assays detected that SMARCD1 deficiency could notably suppress the proliferation rates of SMARCD1-high (786-O, KMRC-2) ccRCC cells (Fig. 2 C). In contrast, we overexpressed SMARCD1 in SLR-23 and Caki-2 cells by lentivirus-infection technology, also confirmed by Western blotting (Fig. 2 D). CCK-8 assays showed SMARCD1 overexpression significantly increased proliferation in SLR-23 and Caki-2 cells. (Fig. 2 E). To study whether SMARCD1 regulates the growth of ccRCC in vivo, we established a subcutaneous xenograft model by implanting either parental control cells or SMARCD1-KD 786-O cells. The results showed that knockout of SMARCD1 markedly inhibited the formation of ccRCC tumors in mice (Fig. 2 F). Furthermore, IHC analysis detected that, compared with the control group, SMARCD1 knockdown significantly reduced Ki-67 and CK18 expression in tumor tissues (Fig. 2 G). Notably, CD31 is a vascular endothelial growth factor marker commonly used to assess microvascular density. The results showed that the microvascular density in SMARCD1-KD tumors was reduced relative to the control group (Fig. 2 G). To determine whether SMARCD1 regulates the migratory capacity of ccRCC cells in vivo and in vitro, we observed that knocking down SMARCD1 in KMRC-2 and 786-O cells severely inhibited colony formation and migratory capacity, while re-expressing SMARCD1 completely restored these functions (Fig. 2 H and I). We then further analyzed the role of SMARCD1 in ccRCC cells in vivo by tail-vein injection model. Luciferase-labeled 786-O cells with or without SMARCD1 knockdown were introduced into nude mice. The SMARCD1-KD group developed dramatically fewer metastases than the control group within four weeks, a finding confirmed by both bioluminescence imaging (BLI) and direct quantification of lesions (Fig. 2 J). Last, using another cell line, KMRC-2, we established a metastasis model and found that SMARCD1 overexpression effectively enhanced lung metastatic capacity compared to controls, as indicated by BLI signals (Fig. 2 K). Together, our findings demonstrate that SMARCD1 promotes ccRCC migration in vivo and in vitro. Collectively, these data indicate that SMARCD1 promotes ccRCC proliferation and migration in vitro and in vivo. At the same time, we found that SMARCD1 is closely related to tumor microvascular formation. 3.SMARCD1 Promotes Angiogenesis by Epigenetically Remodeling the VEGFA Promoter and Activating VEGFA Expression To investigate the pathway through which SMARCD1 promotes ccRCC progression, gene enrichment analysis demonstrated a high correlation between angiogenesis pathways and SMARCD1 (Fig. 3 A), supported by previous IHC analysis (Fig. 2 G). To study SMARCD1's role in angiogenesis, we first performed ChIP-qPCR in 786-O and KMRC-2 cells to examine if SMARCD1 localizes to chromatin near promoters. Compared to controls, SMARCD1 is associated with chromatin regions near the promoters of key angiogenesis factors VEGFA, EPO, and ANGPTL4 (Figs. 3 B-D). Concurrently, SMARCD1 knockdown significantly reduced VEGFA protein levels compared to control cells (Fig. 3 E). RT-qPCR analysis further showed that SMARCD1 knockdown significantly inhibited VEGFA mRNA levels, while SMARCD1 overexpression markedly elevated VEGFA levels (Fig. 3 F-G). To assess transcriptional activation, we measured VEGFA promoter activity using a luciferase reporter plasmid. SMARCD1-knockout 786-O and KMRC-2 cells exhibited significantly diminished promoter activity versus controls (Fig. 3 H). The qPCR analysis detected that SMARCD1 deletion reduced chromatin accessibility at the VEGFA promoter. Conversely, SMARCD1 overexpression increased it (Fig. 3 I). Levels of the activating histone marks H3K4me3, H3K27ac, and H3K9ac—classical indicators of open chromatin—increased at the VEGFA promoter upon SMARCD1 overexpression, as determined by ChIP-qPCR. Conversely, SMARCD1 overexpression reduced the levels of the repressive mark H3K9me3. Knockout experiments reciprocally reversed these histone modification patterns (Figs. 3 J-M). It is well-established that VEGFA regulates vascular permeability and promotes the proliferation and migration of vascular endothelial cells. Therefore, we conducted tube formation assays to validate SMARCD1's role in ccRCC angiogenesis. Conditioned medium from SMARCD1-overexpressing 786-O cells significantly enhanced tube formation compared to vector control medium. Conversely, conditioned medium from SMARCD1 knockdown 786-O cells attenuated tube formation compared to vector control medium (Fig. 3 N). In conclusion, SMARCD1 can open the VEGFA promoter region through epigenetic remodeling and manipulate VEGFA signaling and angiogenesis in ccRCC. 4.SMARCD1 Promotes ccRCC Malignant Progression in a VEGFA-Dependent Manner To investigate the oncogenic role of the SMARCD1-VEGFA interaction in ccRCC, we sequentially transfected control and SMARCD1 plasmids into control and VEGFA-knockout 786-O cell lines. CCK-8 assays demonstrated that VEGFA knockout significantly impeded cell growth (Fig. 4 A). Subsequently, using the same four cell line groups (control vs. VEGFA-KO, each transfected with control or SMARCD1 plasmid), we found, as expected, that SMARCD1 overexpression enhanced cell colony formation and migratory capacity, while VEGFA knockout significantly suppressed these phenotypes (Figs. 4 B and C). Then, using conditioned medium from these four cell line groups, angiogenesis assays showed that conditioned medium from SMARCD1-overexpressing 786-O cells significantly increased tube formation and HUVEC viability compared to controls. Conversely, conditioned medium from VEGFA-knockout 786-O cells reduced tube formation and HUVEC viability. Subsequently, overexpressing VEGFA in conditioned medium from SMARCD1 knockdown 786-O cells restored tumor cell-induced tube formation and HUVEC growth capacity (Figs. 4 D-I). Finally, based on tumor volume curves, mass comparison analysis, and IHC intensity analysis, VEGFA knockout markedly suppressed SMARCD1 induced ccRCC growth and angiogenesis in vivo (Figs. 4 J-L). In summary, our results establish SMARCD1 as a key promoter of ccRCC malignant progression in a VEGFA-dependent manner. 5. SMARCD1 Confers Bevacizumab Resistance in ccRCC Reportedly, aberrant VEGFA signaling contributes to bevacizumab resistance in colon cancer [ 22 ]. Given the confirmed importance of SMARCD1 in regulating VEGFA-dependent angiogenesis, we sought to investigate whether SMARCD1 counteracts the effects of the anti-angiogenic agent bevacizumab. Using CCK-8 assays, we compared bevacizumab-treated control groups to SMARCD1-overexpressing 786-O and KMRC-2 cell lines. Proliferation of SMARCD1-overexpressing cells was significantly faster than that of controls (Fig. 5 A). In contrast, proliferation of SMARCD1 knockdown cells was significantly slower than that of controls (Fig. 5 B). Colony formation assays showed similar results: bevacizumab did not inhibit colony formation and migration in SMARCD1-overexpressing 786-O cells (Figs. 5 C–D). Therefore, our results indicate that SMARCD1 was associated with bevacizumab resistance. We generated bevacizumab-resistant 786-O cells (designated 786-O-BR). CCK-8 results demonstrated that bevacizumab markedly inhibited proliferation in SMARCD1 knockdown 786-O-BR cells compared with control cells (Fig. 5 E). We then validated this result in vivo using subcutaneous xenograft models of 786-O-BR. Although bevacizumab monotherapy showed minimal efficacy on tumor suppression, the bevacizumab combination with SMARCD1 knockdown markedly enhanced tumor suppression (Figs. 5 F–G). We also validated this result in bevacizumab-resistant KMRC-2 cells we generated (Figs. 5 H–J). In conclusion, SMARCD1 is an epigenetic vulnerability in ccRCC that functionally confers bevacizumab resistance. Discussion In recent years, epigenetic regulation has gained significant traction in ccRCC pathogenesis. The molecular heterogeneity and treatment resistance of ccRCC are closely related to the epigenome. Epigenetic changes—heritable modifications that regulate gene expression without altering the DNA sequence—are potent drivers of tumorigenesis. These changes include DNA methylation, histone modifications, chromatin remodeling, and non-coding RNA regulation. While VHL tumor suppressor gene inactivation occurs in over 90% of ccRCC cases, VHL loss alone is insufficient to induce tumors in mouse models, pointing to critical contributions from other epigenetic events [ 23 ]. Advances in sequencing and single-cell analysis have enabled our team and others to identify key epigenetic regulators in ccRCC, such as BRD9 and KDM4B [ 20 , 24 ], providing a crucial foundation for novel diagnostics and targeted therapies. Large-scale omics studies strongly support the centrality of epigenetic dysregulation in ccRCC. For instance, Terekhanova et al.'s (2023) Nature study, presenting a single-cell epigenomic atlas spanning 11 cancer types (integrating snATAC-seq and snRNA-seq data from 201 samples, including ccRCC), revealed highly specific chromatin accessibility patterns in ccRCC. This work identified aberrant activity of ccRCC-specific transcriptional regulators such as HNF1A and KLF9, which are strongly associated with tumor progression and metastasis[ 19 ]. Epigenetic mechanisms can influence gene expression by modulating chromatin accessibility including DNA methylation, histone acetylation, and histone methylation [ 25 ]. Chromatin accessibility refers to the dynamic property allowing regulatory factors access to DNA; regions where nucleosomes are displaced, exposing the DNA, are termed "open chromatin" [ 26 ]. These accessible regions are enriched for cis-regulatory elements (promoters, enhancers, silencers, insulators) that, by binding transcription factors (TFs), dictate cell-type-specific gene programs [ 27 ]. This dynamic remodeling is primarily governed by two mechanisms: ATP-dependent remodeling complexes and histone modifications [ 28 ]. Histone modifications function combinatorially and fall into two main types: those associated with permissive chromatin, such as H3K4me3, H3K4me1, and H3K27ac, and those associated with repressed chromatin, including H3K27me3 and H3K9me3. [ 29 ]. ATP-dependent remodelers utilize nucleosome alterations to regulate chromatin accessibility (such as sliding, eviction, histone variant exchange) [ 30 ]. Crucially, the SWI/SNF complex—among eukaryotes' most vital remodelers—maintains open chromatin for enhancer/promoter functionality. SWI/SNF subunit genes harbor mutations in > 20% of cancers [ 31 , 32 ]. Our investigation uncovers a pivotal role for SMARCD1 in ccRCC. We found SMARCD1 upregulated in ccRCC tissues, and its depletion significantly inhibited tumor cell proliferation and migration. Functionally, SMARCD1 drives ccRCC proliferation, migration, and angiogenesis in vitro and in vivo, critically dependent on VEGFA. Mechanistically, SMARCD1 orchestrates epigenetic remodeling to open the VEGFA promoter region: qPCR confirmed reduced chromatin accessibility at VEGFA upon SMARCD1 knockdown. Furthermore, we found a new epigenetic mechanism of ccRCC that SMARCD1 overexpression increased enriching activating histone marks (H3K4me3, H3K27ac, H3K9ac) while decreasing the repressive mark H3K9me3 at the VEGFA promoter. Significantly, we discovered that SMARCD1 confers bevacizumab resistance in ccRCC. This parallels observations in other cancers: Shuyang Wang et al. showed FOXF1 elevates VEGFA, promoting colon cancer angiogenesis and bevacizumab resistance [ 22 ], while ETV5 directly binds the VEGFA promoter to drive resistance [ 33 ]. A major translational hurdle is the current lack of specific SMARCD1 inhibitors. Study Limitations: Mechanistic Depth: Our exploration of SMARCD1's mechanisms in ccRCC requires further depth and breadth. To achieve more precise localization of the binding sites, high-throughput sequencing techniques such as ChIP-seq and ATAC-seq can be employed. We consider that SMARCD1 may drive resistance via multi-pathway mechanisms in bevacizumab-resistant models, thus comprehensive transcriptomic and proteomic studies are needed for further clarification. Therapeutic Translation: While SMARCD1 represents a promising therapeutic target, developing specific inhibitors poses significant challenges. We propose close collaboration with pharmacologists to screen for potential SMARCD1 inhibitors. In conclusion, we find a novel SMARCD1–VEGFA epigenetic regulatory axis (Fig. 6 ). This study establishes that SMARCD1 promotes ccRCC proliferation, metastasis, and bevacizumab resistance by epigenetically remodeling the VEGFA promoter to enhance its accessibility and drive angiogenesis. Our findings nominate SMARCD1 as a promising therapeutic target for precision therapy in ccRCC. Declarations Author contributions HQ. L, J. X and YX. L conceived and designed the study, HQ. L Y. S, YC. H, CY. X, and XY. B collected clinical the performed the experiments and analyzed the results, HQ. L contributed to the writing of the manuscript. HQ. L, J. X and YX. L completed the revision work. All authors reviewed the manuscript. All authors agree to submit this version of the manuscript. Acknowledgements We sincerely appreciate assistance from Medical Research Center of Anhui Provincial Hospital in providing convenient experimental conditions. Funding None Ethics approval and consent to participate This study was performed in line with the principles of the Declaration of Helsinki. The use of human specimens for this basic science study was approved by the Ethics Committee of The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China. Informed consent for the use of specimens was obtained from all donors or their legal guardians. The Ethics committee of experimental animals of The First Afliated Hospital of University of Science and Technology of China granted ethical approval for this study (approval number: 2025-N(A)-0148). Data availability The data from the TCGA and Cancer Cell Line Encyclopedia (CCLE) are publicly available and were used in this study. 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Malone HA, Roberts CWM: Chromatin remodellers as therapeutic targets . Nat Rev Drug Discov 2024, 23 (9):661-681. Feng H, Liu K, Shen X, Liang J, Wang C, Qiu W, Cheng X, Zhao R: Targeting tumor cell-derived CCL2 as a strategy to overcome Bevacizumab resistance in ETV5(+) colorectal cancer . Cell Death Dis 2020, 11 (10):916. Additional Declarations No competing interests reported. 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02:00:50","extension":"html","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":120057,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8031896/v1/be6c7e47ca04f841b235cebf.html"},{"id":96333386,"identity":"8649ad23-25d1-4e96-887d-0d0432b6e67b","added_by":"auto","created_at":"2025-11-20 02:00:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":292949,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHigh SMARCD1 expression was associated with a poorer prognosis in patients with ccRCC.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Western blot analysis of SMARCD1 protein levels in 8 pairs of tumor and matched adjacent normal tissues from our cohort. (B) Representative IHC images of TMA sections stained with anti-SMARCD1 antibody (scale bars: 50 µm and 20 µm); quantified h-scores are shown at right.(C) IHC staining demonstrates association between high SMARCD1 expression in tumors and advanced disease stage.(D-F) SMARCD1 h-score and clinical features in ccRCC samples were correlated using Kruskal–Wallis test.(G-H) Kaplan–Meier analysis of TCGA and Anhui Provincial Hospital RCC databases comparing survival in ccRCC patients with high vs. low SMARCD1 expression.(I) siRNA knockdown of three SMARCD1 homologous family members and their effects on RCC (786-O or KMRC-2) cell growth.(J) ccRCC cell lines stratified into SMARCD1-low and -high groups by RT-qPCR.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8031896/v1/2fd64ba7597cd3dffa3ff7a8.png"},{"id":96365790,"identity":"9f2c1dfc-aec5-4e7d-befa-3c5e9aed8273","added_by":"auto","created_at":"2025-11-20 10:10:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":540542,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSMARCD1 drives malignant progression of ccRCC cells both in vivo and in vitro.\u003cbr\u003e\n \u003c/strong\u003e(A) CCK-8 assay evaluates cell growth after SMARCD1 knockdown in SMARCD1-high cell lines.(B) Western blot confirms SMARCD1 protein knockdown in 786-O and KMRC-2 cells.(C) CCK-8 assay shows growth of RCC cells transduced with shCtrl or shSMARCD1 lentivirus; SMARCD1 re-expression restores growth.(D) SMARCD1 protein and mRNA levels in overexpressing SLR-23 and Caki-2 cells, detected by Western blot and RT-qPCR.(E) Growth rates of EV-, SMARCD1#1-, or SMARCD1#2-transfected ccRCC (SLR-23, Caki-2) cells by CCK-8.(F) Subcutaneous tumor growth in control vs. SMARCD1 knockdown 786-O cells (two-way ANOVA, Tukey’s test); representative images (scale: 1 cm).(G) Representative IHC of Ki-67, CK-18, and CD-31 in tumors from control and SMARCD1 knockdown 786-O cells.(H-I) Colony formation and Transwell assays in control, knockdown, and rescued 786-O (H) or KMRC-2 (I) cells; quantitation at right. (J-K) Bioluminescence imaging (BLI) of metastases in control-injected mice, SMARCD1-KD, or SMARCD1-overexpressing 786-O cells; signal quantitation at right.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8031896/v1/82240f5fc6fb54141a830c3d.png"},{"id":96365810,"identity":"a6d54771-61e5-45ff-9238-c4b6f3249106","added_by":"auto","created_at":"2025-11-20 10:10:49","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":367711,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSMARCD1 promotes ccRCC angiogenesis by epigenetically remodeling and opening VEGFA promoter region.\u003c/strong\u003e\u003cbr\u003e\n(A) GSEA revealed enrichedangiogenesis signaling in SMARCD1-high versus SMARCD1-low groups.(B–D) ChIP–qPCR demonstrates SMARCD1 enrichment at VEGFA, EPO, and ANGPTL4 chromatin regions in 786-O and KMRC-2 cells.(E-F) VEGFA expression upon SMARCD1 knockdown in 786-O and KMRC-2 cells, assessed by Western blot (E) and RT–qPCR (F).(G) RT–qPCR measures VEGFA expression in control and SMARCD1-overexpressing SLR-23 and Caki-2 cells.(H) Luciferase reporter assay evaluates VEGFA promoter activity in 786-O and KMRC-2 cells.(I) qPCR analysis of chromatin accessibility at selected promoters in SMARCD1-knockdown and overexpressing 786-O cells.(J–M) ChIP–qPCR profiling of H3K4me3, H3K27ac, H3K9ac, and H3K9me3 occupancy at the VEGFA promoter following SMARCD1 modulation in 786-O cells.(N-O) HUVEC tube formation assay evaluating the functional effect of SMARCD1 expression changes.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8031896/v1/7b2a79fcabd90932795e54e7.png"},{"id":96333393,"identity":"353bdf2c-ee92-4a8a-a02c-319d358332f9","added_by":"auto","created_at":"2025-11-20 02:00:49","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":395319,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSMARCD1 depends on VEGFA to promotes the malignant progression of ccRCC.\u003c/strong\u003e\u003cbr\u003e\n(A) CCK-8 assay evaluating the effect of VEGFA knockdown on the growth of SMARCD1-overexpressing RCC cells.(B-C) Colony formation (B) and Transwell (C) assays indicating that SMARCD1 enhances proliferation and migration of 786-O cells in a VEGFA-dependent manner; quantitative data are shown on the right. (D) Quantification and comparison of HUVEC tube formation under six conditioned media treatments. (E) SMARCD1 overexpression failed to rescue subcutaneous tumor growth suppressed by VEGFA knockdown in nude mice. Tumor growth curves were generated based on weekly volume measurements. (F) Tumor weights from the indicated experimental groups. (G)Representative immunohistochemical images of tumor tissues showing Ki-67 and CD31 expression.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8031896/v1/d0902008bf27a3854df2ba0c.png"},{"id":96333394,"identity":"a892b3e9-cd05-4c5a-9c67-c3274cbf6aff","added_by":"auto","created_at":"2025-11-20 02:00:50","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":409212,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSMARCD1 modulates bevacizumab resistance in ccRCC.\u003c/strong\u003e\u003cbr\u003e\n(A) CCK-8 assays were used to assess the proliferation rates of 786-O or KMRC-2 cells overexpressing SMARCD1, with or without bevacizumab treatment.(B) CCK-8 assays were performed to evaluate the proliferation of 786-O or KMRC-2 cells with SMARCD1 knockdown, under control or bevacizumab-treated conditions.(C–D) Colony formation (left) and Transwell assays (right) were conducted in bevacizumab-resistant 786-O cells overexpressing (C) or knockdown for (D) SMARCD1 followed by bevacizumab treatment. Quantitative data are shown on the right.(E) Growth curves of bevacizumab-resistant 786-O cells from control and SMARCD1 knockdown groups treated with bevacizumab.(F) Tumor growth curves in mouse xenograft models from the indicated groups.(G) Representative IHC images showing expression levels of Ki-67 and CD31 in tumor sections from each group.(H) Quantitative analysis of cell growth curves in bevacizumab-resistant KMRC-2 cells with or without SMARCD1 knockdown and treated with bevacizumab.(I) Tumor growth in mouse models inoculated with KMRC-2-BR cells from the respective treatment groups.(J) Representative IHC staining of Ki-67 and CD31 in tumor tissues from each group.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8031896/v1/26835e25a024d4242fca459e.png"},{"id":96333402,"identity":"85583946-429f-42d8-aeeb-fba0135426c9","added_by":"auto","created_at":"2025-11-20 02:00:50","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":158104,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSchematic of the SMARCD1-VEGFA Axis in ccRCC Pathogenesis and Bevacizumab Resistance\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8031896/v1/0d28733e8f4dc9e41133db45.png"},{"id":105756189,"identity":"456c50dc-c61a-4016-9baf-b13a38ddbb00","added_by":"auto","created_at":"2026-03-30 16:37:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3948826,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8031896/v1/960777ed-ea2e-43be-9392-b4696d6defb8.pdf"},{"id":96367371,"identity":"7fdf15bf-5309-4eff-81d7-a2074a4ae374","added_by":"auto","created_at":"2025-11-20 10:12:38","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1368006,"visible":true,"origin":"","legend":"","description":"","filename":"wb.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8031896/v1/bf7e31ec85a508730f87afca.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Epigenetic activation of VEGFA by SMARCD1 mediates tumor progression and bevacizumab resistance in clear cell renal cell carcinoma","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRenal cell carcinoma (RCC) encompasses several subtypes. Among these, ccRCC is the predominant malignant tumor of the kidney, representing 70\u0026ndash;80% of RCC. The disease is known for its aggressive and metastatic behavior and is frequently discovered incidentally through abdominal imaging [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The standard first-line treatment is surgery, nonetheless, some patients experience recurrence or distant metastasis after surgery, and ccRCC is notably resistant to radiotherapy, chemotherapy, and immunotherapy [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The 2022 WHO classification of kidney tumors newly included \u0026ldquo;molecularly defined renal carcinomas\u0026rdquo; as a distinct category, emphasizing the growing role of molecular mechanisms in precision medicine [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] Thus, it is critical to improve early detection and treatment for advanced or metastatic ccRCC by identifying new biomarkers and therapeutic targets, and clarifying their molecular mechanisms.\u003c/p\u003e\u003cp\u003eSMARCD1 (BAF60A), a core subunit of the SWI/SNF chromatin remodeling complex, recognizes histone modifications such as H3K4me3 and recruits remodeling enzymes [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Emerging evidence suggests that SMARCD1 overexpression differentially affects patient survival across cancer types. In liver cancer, SMARCD1 serves as a key prognostic gene, promoting tumor growth through activation of the mTOR signaling pathway[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In bladder cancer, knockdown of SMARCD1 significantly inhibits cancer cell proliferation, migration, and invasion, while also increasing sensitivity to gemcitabine [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In acute myeloid leukemia (AML), leukemic cell lines rely on SMARCD1-maintained high promoter accessibility [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].However, the function and mechanisms of SMARCD1 remain unexplored in ccRCC. This study may provide valuable insights for identifying novel therapeutic targets and sensitive biomarkers in ccRCC.\u003c/p\u003e\u003cp\u003eAs reported, VEGFA is highly expressed in ccRCC compared to other epithelial cancers, making VEGFA targeting a fundamental component of ccRCC management [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. As a key member of the VEGF family, VEGFA acts as a master regulator of tumor angiogenesis [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Anti-angiogenic therapies targeting the VEGF signaling pathway are particularly relevant for treating ccRCC, given that it is a highly vascular tumor [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. VEGFA is modulated by histone modifications: enrichment of H3K27ac promotes its expression at enhancers, whereas H3K9me3 has a repressive effect [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The anti-angiogenic drug bevacizumab works by sequestering VEGFA, thus blocking its receptor interaction and inhibiting tumor blood vessel growth [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, acquired resistance commonly develops in ccRCC patients. Emerging evidence indicates that epigenetic reprogramming plays a key role in this process [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In resistant tumor cells, the VEGFA locus adopts a more open chromatin architecture, characterized by increased H3K27ac modification at enhancers, thereby maintaining a transcription-ready state. This epigenetic memory enables sustained VEGFA expression under therapeutic pressure, providing a molecular basis for drug resistance [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn this study, we identified SMARCD1 overexpression in ccRCC, which correlated with poor patient prognosis. Functional assays demonstrated that SMARCD1 promotes ccRCC progression and metastasis. Moreover, we found that SMARCD1 modulates chromatin accessibility at the VEGFA promoter region. We further investigated whether SMARCD1 is associated with drug resistance in ccRCC. In summary, our findings indicate that SMARCD1 promotes proliferation, metastasis, and confers bevacizumab resistance in ccRCC by epigenetically remodeling and opening the VEGFA promoter region.\u003c/p\u003e"},{"header":"Methods and materials","content":"\u003cp\u003eHuman Clear Cell Renal Cell Carcinoma (ccRCC) Tissues\u003c/p\u003e\n\u003cp\u003eThis study utilized clinical specimens and related patient information under the approval of the Ethics Committee of Anhui Provincial Hospital. From June 2021 to August 2025, we collected 220 ccRCC specimens and matched adjacent non-neoplastic tissues from the Department of Urology at Anhui Provincial Hospital. Fresh ccRCC and normal tissues were preserved in liquid nitrogen. A tissue microarray (TMA) comprising these 220 samples (107 males, 113 females; 133 stage I\u0026ndash;II, 74 stage III, 13 stage IV) was constructed by Ruichuang Biotechnology Co., Ltd. (Shanghai, China). We have obtained written informed consent from all participants.\u003c/p\u003e\n\u003cp\u003eMethodologies for Cell Culture and Transfection\u003c/p\u003e\n\u003cp\u003eThe RCC cell lines (Caki-2, 786-O, KMRC-2, ACHN, SLR-23, SLR-20) were acquired from the ATCC (Manassas, VA). Cells were cultured in RPMI 1640 (786-O, SLR-20, ACHN, KMRC-2) or DMEM (SLR-23, Caki-2, 293T), with 10% fetal bovine serum (FBS). Cells were used within 18 passages after thawing in this study. Cell culture was performed in a humidified incubator at 37\u0026deg;C with 5% CO2, with passaging conducted every 2\u0026ndash;4 days.\u003c/p\u003e\n\u003cp\u003eSiRNAs targeting SMARCD1, PBRM1, SMARCA2, and SMARCA4 were diluted to 20 \u0026micro;M using DEPC water. Approximately 2\u0026times;10⁵ cells were plated per well in 6-well plates. After 24 hours, Lipofectamine 3000\u0026ndash;siRNA complexes were prepared in DMEM with 10% FBS and applied to the cells. Cells were harvested 48 hours post-transfection for downstream assays.\u003c/p\u003e\n\u003cp\u003esiSMARCD1: AUGAGGAAACGGCUAGAUATT;\u003c/p\u003e\n\u003cp\u003esiPBRM1: GAAGAGGUUUUCACUCUCUGCUAAA;\u003c/p\u003e\n\u003cp\u003esiSMARCA2: CCGCATAGCTCATAGGATA;\u003c/p\u003e\n\u003cp\u003esiSMARCA4: GCAUUUCAAGGAAUAUCACTT\u003c/p\u003e\n\u003cp\u003eAs to lentivirus plasmids, virus production used 293 T cells. Briefly, 70\u0026ndash;80% confluency of cells was co-transfected with the shRNA lentivector and helper plasmids psPAX2/pMD2.G in 6-well plates. Fresh complete medium supplemented with 10% FBS was used to replace the old medium after overnight incubation. Viral supernatants were collected at 48- and 72- hours post-transfection, with fresh medium added again after the first collection. The combined supernatants were concentrated by low-speed centrifugation and then filtered through 0.45 \u0026micro;m filters. ccRCC cells were plated in 6-well plates to reach approximately 50\u0026ndash;70% confluency. Each well was then transduced with 100 \u0026micro;L of viral supernatant supplemented with 4\u0026ndash;8 \u0026micro;g/mL polybrene. The medium was replaced after 12\u0026ndash;18 hours. After an additional 48-hour incubation period, selection of transduced cells was performed with 2 \u0026micro;g/mL puromycin. Knockdown efficiency was verified by Western blot. The oligonucleotide sequences used are listed below (5\u0026prime;\u0026rarr;3\u0026prime;):\u003c/p\u003e\n\u003cp\u003eshRNA1: 5\u0026prime;-AAGTCCTTGGTGATTGAACTGGA-3\u0026prime;\u003c/p\u003e\n\u003cp\u003eshRNA2: 5\u0026prime;-AATGTACGGTGTACTGTCCTACT-3\u0026prime;\u003c/p\u003e\n\u003cp\u003eStable Gene Knockout Using CRISPR/Cas9\u003c/p\u003e\n\u003cp\u003eThe pX459 plasmid was used to deliver SMARCD1-targeting sgRNAs into 786-O or KMRC-2 cells. Twenty-four hours later, transfected cells underwent a 7-day puromycin selection treatment at a concentration of 1 \u0026micro;g/mL. Monoclonal lines were established in 96-well plates. Knockout efficiency was verified by Western blot and qPCR. The sgRNA sequences used were:\u003c/p\u003e\n\u003cp\u003eSMARCD1-sgRNA-1: TGATGTGGTGGGTAACCCAGAGG\u003c/p\u003e\n\u003cp\u003eSMARCD1-sgRNA-2: AGTTTTCAGAGATCCCTCAGCGG\u003c/p\u003e\n\u003cp\u003eQuantitative Real-Time PCR (qRT-PCR)\u003c/p\u003e\n\u003cp\u003eTotal RNA was extracted using the Sparkjade SPARKeasy Cell RNA Kit (AC0205B). Gene expression was quantified by qRT-PCR employing the TIANGEN FastReal SYBR Green Kit (FP217-01). The endogenous control gene \u0026beta;-actin was used for normalization, and relative expression levels were determined by the 2⁻\u0026Delta;\u0026Delta;Ct method.\u003c/p\u003e\n\u003cp\u003ePrimer sequences:\u003c/p\u003e\n\u003cp\u003eSMARCD1: F: 5\u0026prime;-AAACGGAAGCTGCGAATTTTC-3\u0026prime;,\u003c/p\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003cp\u003eR: 5\u0026prime;-AGCCGTCCTTCTACCCGAA-3\u0026prime;\u003c/p\u003e\n \u003cp\u003eVEGFA: F: 5\u0026prime;-GAGCCTTGCCTTGCTGCTCTA-3\u0026prime;,\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003eR: 5\u0026prime;-CACCAGGGTCTCGATTGGATG-3\u0026prime;\u003c/p\u003e\n\u003cp\u003eCell Proliferation Assays\u003c/p\u003e\n\u003cp\u003eFor the MTT assay, we seeded approximately 3,000 cells per well in 96-well plates after transfection with siRNA or plasmids. Then, 20 \u0026micro;L of MTT reagent (BS186, Biosharp, China) was added to each well, and the plates were incubated at 37\u0026deg;C for 4 hours. Following incubation, the resulting formazan crystals were dissolved in 150 \u0026micro;L of DMSO with gentle shaking for 10 minutes. Absorbance was subsequently measured at 570 nm using a microplate reader. In the CCK-8 assay, tumor cells were plated in 96-well plates at a density of 3000 cells per well, with 100 \u0026micro;L of DMEM medium containing 10% FBS. The medium of all groups was refreshed every two days, and 10 \u0026micro;L of CCK-8 solution was introduced per the manufacturer\u0026apos;s protocol (Dojindo, Kumamoto, Japan). After a 2-hour incubation at 37\u0026deg;C in the absence of light, cell viability was assessed by measuring the absorbance at 450 nm. For the colony formation assay, transfected cells were seeded in 6-well plates at a density of approximately 800 cells per well and cultured under the indicated treatment conditions for 12 days. Subsequently, the colonies were fixed with 4% paraformaldehyde (PFA) for 30 minutes and stained with 0.1% crystal violet for an additional 30 minutes.\u003c/p\u003e\n\u003cp\u003eTranswell assays\u003c/p\u003e\n\u003cp\u003eFor migration and invasion assays, 40,000 cells were seeded in the upper chamber using serum-free DMEM, while the lower chamber was filled with DMEM supplemented with 20% FBS. For the invasion assay, the membrane was pre-coated with Matrigel. After 24 hours, non-migratory/non-invasive cells were gently removed from the upper chamber. Cells that had migrated or invaded to the lower surface were fixed, stained, and quantified by counting under a microscope. Five randomly selected fields were imaged and analyzed for each replicate.\u003c/p\u003e\n\u003cp\u003eWestern Blotting\u003c/p\u003e\n\u003cp\u003eFor western blotting, transfected cells were collected approximately 2\u0026times;105, lysed with 250 \u0026micro;L RIPA buffer (BI-WB013, SBJbio). Protein concentration was quantified using a bicinchoninic acid (BCA) assay. Subsequently, they were separated using SDS-PAGE(GF1810, GeneFist, China) and transferred to PVDF membranes༈EMD Millipore, Billerica, MA, USA). Membranes were blocked with 5% non-fat milk for 1 hour and incubation with primary antibodies at 4\u0026deg;C overnight. After washing with TBST, the membranes were incubated with secondary antibodies for 1 hour at room temperature. Protein bands were visualized using an enhanced chemiluminescence (ECL) detection system and analyzed.\u003c/p\u003e\n\u003cp\u003eMouse xenograft models and experiments\u003c/p\u003e\n\u003cp\u003eAll animal experiments were approved by the Animal Experimentation Ethics Committee of The First Affiliated Hospital of the University of Science and Technology of China (Approval No. 2025-N(A)-0148).\u003c/p\u003e\n\u003cp\u003eFemale BALB/c nude mice (4\u0026ndash;6 weeks old) were obtained from Shanghai SLAC Laboratory Animal Co., Ltd. and randomly assigned to experimental groups. Each mouse received a subcutaneous injection of 5\u0026times;10⁶ 786-O cells suspended in 100 \u0026micro;L of a 1:1 mixture of PBS and Matrigel. Tumor size was monitored every 7 days starting from day 7 after injection. Tumor volumes were calculated according to the formula: V (mm\u0026sup3;)\u0026thinsp;=\u0026thinsp;0.52 \u0026times; length (mm) \u0026times; width\u0026sup2; (mm\u0026sup2;). On day 42, all mice were humanely euthanized, and final tumor volumes and weights were recorded.\u003c/p\u003e\n\u003cp\u003eFor orthotopic models, 786-O cells were injected into the kidneys of 6-week-old female nude mice as previously described. To enable in vivo tracking of lung metastasis, cells were transduced with a CMV-Luc-PGK-puro lentivirus (Genomeditech) prior to injection. For bevacizumab efficacy evaluation, 4\u0026times;10⁵ 786-O-BR or KMRC-2-BR cells were injected directly into the mouse kidney. Beginning on day 7 post-injection, tumor-bearing mice were randomly assigned to receive either bevacizumab or placebo every other day. Tumor volume was measured every 7 days following initiation of treatment. All animals were euthanized at 6 weeks post-injection. Immunohistochemistry (IHC) was carried out as described previously [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eGene Set Enrichment Analysis (GSEA)\u003c/p\u003e\n\u003cp\u003eGSEA was conducted using the TCGA dataset and CCLE data. Samples were categorized into high and low SMARCD1 expression groups according to the median expression value. Enrichment analysis was performed using GSEA v4.3.3.\u003c/p\u003e\n\u003cp\u003eChromatin immunoprecipitation (ChIP)-qPCR assay\u003c/p\u003e\n\u003cp\u003eWe first cross-linked 1\u0026times;10⁷ 786-O cells with 1% formaldehyde at room temperature for 15 minutes and then quenched the reaction by incubating with 0.25 M glycine for an additional 5 minutes in preparation for the ChIP-qPCR assay. Nuclear lysates were sonicated to shear DNA to fragments of approximately 400\u0026ndash;800 base pairs. Chromatin fragments were precipitated with specific antibodies and protein A/G agarose beads at 4\u0026deg;C for 16 hours. After washing and reverse cross-linking, gene expression in the ChIP products was measured by RT-qPCR. Sequences used are listed below.\u003c/p\u003e\n\u003cp\u003eVEGFA-promoter (5\u0026prime;\u0026rarr;3\u0026prime;):\u003c/p\u003e\n\u003cp\u003eGGCGGGTAGGTTTGAATC (sense),\u003c/p\u003e\n\u003cp\u003eCGTATGCACTGTGGAGTC (antisense).\u003c/p\u003e\n\u003cp\u003eLuciferase Reporter Assay\u003c/p\u003e\n\u003cp\u003eUsing FuGENE 6 transfection reagent (Roche, Indianapolis, IN, USA), we plated cells at 50% confluence in 24-well plates and transfected them with 200 ng of a firefly luciferase reporter construct along with 1 ng of the pRL-SV40 Renilla luciferase construct for normalization. After 48 hours, we prepared cell extracts and measured luciferase activities following the protocol of the Dual-Luciferase Reporter Assay System (Promega, Sunnyvale, CA, USA).\u003c/p\u003e\n\u003cp\u003eTube Formation Assay\u003c/p\u003e\n\u003cp\u003eWe evaluated the tube formation capability of HUVECs. Briefly, we thawed growth Matrigel (BD Biosciences, Franklin Lakes, NJ) on ice and gently mixed it with an equal volume of DMEM. Then, 200 \u0026micro;L of this mixture were aliquoted into each well of a 24-well plate and allowed to polymerize at 37\u0026deg;C for 30 minutes. Following gel formation, we seeded HUVECs from each experimental group at a density of 1\u0026times;10⁵ cells per well in 500 \u0026micro;L of serum-free medium. The plates were incubated for 12 hours under standard culture conditions (37\u0026deg;C, 5% CO₂). We captured images of the resulting tubular networks using an inverted microscope and analyzed five randomly selected fields per well with ImageJ software equipped with the Angiogenesis Analyzer plugin. Quantification included both total tube length and number of complete tubular structures. All experiments were performed in three independent replicates.\u003c/p\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003eStatistical Analysis\u003c/h2\u003e\n \u003cp\u003eOur studies were conducted with 5\u0026ndash;10 mice per group or triplicated in independent cell-based assays. Results are displayed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or SEM in the figures. Cox proportional hazards regression was carried out using SPSS 22.0. Statistical significance was determined using Student\u0026rsquo;s t test, one-way ANOVA, two-way ANOVA, Pearson correlation, and log-rank test in GraphPad Prism 9.5 and R v4.3.2., the 0.05 level of confidence was accepted for statistical significance.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Result","content":"\u003cp\u003e\u003cb\u003e1. High SMARCD1 Expression is Associated with Poor Prognosis in ccRCC\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo investigate the clinical significance of SMARCD1 in ccRCC, we examined SMARCD1 protein expression in 8 pairs of freshly collected ccRCC specimens and matched adjacent normal kidney tissues. SMARCD1 levels were elevated in all 8 tumor samples compared to their normal counterparts, as detected by western blot.(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). We further validated this finding using a tissue microarray (TMA) containing 220 ccRCC cases, which included both tumor and paired non-tumor kidney tissues. Immunohistochemical (IHC staining consistently demonstrated stronger SMARCD1 expression in tumor tissues relative to normal sections (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Moreover, SMARCD1 expression was markedly elevated in high-grade relative to low-grade ccRCC specimens (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Notably, the intensity of SMARCD1 immunostaining showed a positive correlative trend with clinicopathological stage, tumor grade, and metastatic progression (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD–F).\u003c/p\u003e\u003cp\u003eWe analyzed the relationship between SMARCD1 expression and overall survival in the TCGA-KIRC cohort. Using the TCGA database, we successfully stratified ccRCC patients into two groups based on SMARCD1 levels. Significant differences in overall survival were observed among these groups (N = 530, log-rank test P \u0026lt; 0.001, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG). As expected, Kaplan-Meier survival curve analysis indicated that ccRCC patients from our cohort (Anhui Provincial Hospital) with high SMARCD1 expression had a more unfavorable prognosis than those with low SMARCD1 (N = 200, log-rank test P \u0026lt; 0.001, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eH). To comprehensively and systematically evaluate the functional contributions of SMARCD1 homologous members (such as SMARCA2, SMARCA4, and PBRM1) to ccRCC pathogenesis, we conducted a targeted siRNA-based screen in ccRCC cell lines. As reported, SMARCA2 and SMARCA4 are canonical oncogenes, while PBRM1 is a tumor suppressor gene [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Compared to these classical oncogenes and tumor suppressors, MTT assays identified SMARCD1 as an equally potent oncogenic driver, in which SMARCD1 knockdown resulted in a substantial decrease in cell growth (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eI). To study the biological function of SMARCD1 in appropriate cell lines, we grouped them into SMARCD1-low (SLR-23, Caki-2, ACHN) and SMARCD1-high (KMRC-2, 786-O, SLR-20) based on RT-qPCR analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eJ).\u003c/p\u003e\u003cp\u003eIn summary, SMARCD1 is frequently upregulated in ccRCC and may represent an independent chromatin-regulatory factor linked to unfavorable clinical outcomes in patients.\u003c/p\u003e\u003cp\u003e\u003cb\u003e2. SMARCD1 is Essential for ccRCC Cell Proliferation and Migration\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo identify suitable cell lines for experiments, using two different shRNA constructs to knock down SMARCD1, we observed that SMARCD1 knockdown suppressed the proliferation of canonical ccRCC cells such as 786-O, KMRC-2, and SLR-20 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). To determine whether SMARCD1 regulates ccRCC cell proliferation in vitro, we used CRISPR-Cas9 technology to delete SMARCD1 in 786-O and KMRC-2 cells, as verified by Western blotting (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). As expected, CCK-8 assays detected that SMARCD1 deficiency could notably suppress the proliferation rates of SMARCD1-high (786-O, KMRC-2) ccRCC cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). In contrast, we overexpressed SMARCD1 in SLR-23 and Caki-2 cells by lentivirus-infection technology, also confirmed by Western blotting (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). CCK-8 assays showed SMARCD1 overexpression significantly increased proliferation in SLR-23 and Caki-2 cells. (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). To study whether SMARCD1 regulates the growth of ccRCC in vivo, we established a subcutaneous xenograft model by implanting either parental control cells or SMARCD1-KD 786-O cells. The results showed that knockout of SMARCD1 markedly inhibited the formation of ccRCC tumors in mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF). Furthermore, IHC analysis detected that, compared with the control group, SMARCD1 knockdown significantly reduced Ki-67 and CK18 expression in tumor tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG). Notably, CD31 is a vascular endothelial growth factor marker commonly used to assess microvascular density. The results showed that the microvascular density in SMARCD1-KD tumors was reduced relative to the control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG).\u003c/p\u003e\u003cp\u003eTo determine whether SMARCD1 regulates the migratory capacity of ccRCC cells in vivo and in vitro, we observed that knocking down SMARCD1 in KMRC-2 and 786-O cells severely inhibited colony formation and migratory capacity, while re-expressing SMARCD1 completely restored these functions (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eH and I).\u003c/p\u003e\u003cp\u003eWe then further analyzed the role of SMARCD1 in ccRCC cells in vivo by tail-vein injection model. Luciferase-labeled 786-O cells with or without SMARCD1 knockdown were introduced into nude mice. The SMARCD1-KD group developed dramatically fewer metastases than the control group within four weeks, a finding confirmed by both bioluminescence imaging (BLI) and direct quantification of lesions (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eJ). Last, using another cell line, KMRC-2, we established a metastasis model and found that SMARCD1 overexpression effectively enhanced lung metastatic capacity compared to controls, as indicated by BLI signals (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eK). Together, our findings demonstrate that SMARCD1 promotes ccRCC migration in vivo and in vitro.\u003c/p\u003e\u003cp\u003eCollectively, these data indicate that SMARCD1 promotes ccRCC proliferation and migration in vitro and in vivo. At the same time, we found that SMARCD1 is closely related to tumor microvascular formation.\u003c/p\u003e\u003cp\u003e\u003cb\u003e3.SMARCD1 Promotes Angiogenesis by Epigenetically Remodeling the VEGFA Promoter and Activating VEGFA Expression\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo investigate the pathway through which SMARCD1 promotes ccRCC progression, gene enrichment analysis demonstrated a high correlation between angiogenesis pathways and SMARCD1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA), supported by previous IHC analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG). To study SMARCD1's role in angiogenesis, we first performed ChIP-qPCR in 786-O and KMRC-2 cells to examine if SMARCD1 localizes to chromatin near promoters. Compared to controls, SMARCD1 is associated with chromatin regions near the promoters of key angiogenesis factors VEGFA, EPO, and ANGPTL4 (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB-D). Concurrently, SMARCD1 knockdown significantly reduced VEGFA protein levels compared to control cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE). RT-qPCR analysis further showed that SMARCD1 knockdown significantly inhibited VEGFA mRNA levels, while SMARCD1 overexpression markedly elevated VEGFA levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF-G). To assess transcriptional activation, we measured VEGFA promoter activity using a luciferase reporter plasmid. SMARCD1-knockout 786-O and KMRC-2 cells exhibited significantly diminished promoter activity versus controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eH). The qPCR analysis detected that SMARCD1 deletion reduced chromatin accessibility at the VEGFA promoter. Conversely, SMARCD1 overexpression increased it (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eI). Levels of the activating histone marks H3K4me3, H3K27ac, and H3K9ac—classical indicators of open chromatin—increased at the VEGFA promoter upon SMARCD1 overexpression, as determined by ChIP-qPCR. Conversely, SMARCD1 overexpression reduced the levels of the repressive mark H3K9me3. Knockout experiments reciprocally reversed these histone modification patterns (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eJ-M).\u003c/p\u003e\u003cp\u003eIt is well-established that VEGFA regulates vascular permeability and promotes the proliferation and migration of vascular endothelial cells. Therefore, we conducted tube formation assays to validate SMARCD1's role in ccRCC angiogenesis. Conditioned medium from SMARCD1-overexpressing 786-O cells significantly enhanced tube formation compared to vector control medium. Conversely, conditioned medium from SMARCD1 knockdown 786-O cells attenuated tube formation compared to vector control medium (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eN). In conclusion, SMARCD1 can open the VEGFA promoter region through epigenetic remodeling and manipulate VEGFA signaling and angiogenesis in ccRCC.\u003c/p\u003e\u003cp\u003e\u003cb\u003e4.SMARCD1 Promotes ccRCC Malignant Progression in a VEGFA-Dependent Manner\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo investigate the oncogenic role of the SMARCD1-VEGFA interaction in ccRCC, we sequentially transfected control and SMARCD1 plasmids into control and VEGFA-knockout 786-O cell lines. CCK-8 assays demonstrated that VEGFA knockout significantly impeded cell growth (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA).\u003c/p\u003e\u003cp\u003eSubsequently, using the same four cell line groups (control vs. VEGFA-KO, each transfected with control or SMARCD1 plasmid), we found, as expected, that SMARCD1 overexpression enhanced cell colony formation and migratory capacity, while VEGFA knockout significantly suppressed these phenotypes (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB and C).\u003c/p\u003e\u003cp\u003eThen, using conditioned medium from these four cell line groups, angiogenesis assays showed that conditioned medium from SMARCD1-overexpressing 786-O cells significantly increased tube formation and HUVEC viability compared to controls. Conversely, conditioned medium from VEGFA-knockout 786-O cells reduced tube formation and HUVEC viability. Subsequently, overexpressing VEGFA in conditioned medium from SMARCD1 knockdown 786-O cells restored tumor cell-induced tube formation and HUVEC growth capacity (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD-I).\u003c/p\u003e\u003cp\u003eFinally, based on tumor volume curves, mass comparison analysis, and IHC intensity analysis, VEGFA knockout markedly suppressed SMARCD1 induced ccRCC growth and angiogenesis in vivo (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eJ-L).\u003c/p\u003e\u003cp\u003eIn summary, our results establish SMARCD1 as a key promoter of ccRCC malignant progression in a VEGFA-dependent manner.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e5. SMARCD1 Confers Bevacizumab Resistance in ccRCC\u003c/b\u003e\u003c/p\u003e\u003cp\u003eReportedly, aberrant VEGFA signaling contributes to bevacizumab resistance in colon cancer [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Given the confirmed importance of SMARCD1 in regulating VEGFA-dependent angiogenesis, we sought to investigate whether SMARCD1 counteracts the effects of the anti-angiogenic agent bevacizumab.\u003c/p\u003e\u003cp\u003eUsing CCK-8 assays, we compared bevacizumab-treated control groups to SMARCD1-overexpressing 786-O and KMRC-2 cell lines. Proliferation of SMARCD1-overexpressing cells was significantly faster than that of controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). In contrast, proliferation of SMARCD1 knockdown cells was significantly slower than that of controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Colony formation assays showed similar results: bevacizumab did not inhibit colony formation and migration in SMARCD1-overexpressing 786-O cells (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC–D).\u003c/p\u003e\u003cp\u003eTherefore, our results indicate that SMARCD1 was associated with bevacizumab resistance. We generated bevacizumab-resistant 786-O cells (designated 786-O-BR). CCK-8 results demonstrated that bevacizumab markedly inhibited proliferation in SMARCD1 knockdown 786-O-BR cells compared with control cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE). We then validated this result in vivo using subcutaneous xenograft models of 786-O-BR. Although bevacizumab monotherapy showed minimal efficacy on tumor suppression, the bevacizumab combination with SMARCD1 knockdown markedly enhanced tumor suppression (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF–G). We also validated this result in bevacizumab-resistant KMRC-2 cells we generated (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH–J). In conclusion, SMARCD1 is an epigenetic vulnerability in ccRCC that functionally confers bevacizumab resistance.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn recent years, epigenetic regulation has gained significant traction in ccRCC pathogenesis. The molecular heterogeneity and treatment resistance of ccRCC are closely related to the epigenome. Epigenetic changes\u0026mdash;heritable modifications that regulate gene expression without altering the DNA sequence\u0026mdash;are potent drivers of tumorigenesis. These changes include DNA methylation, histone modifications, chromatin remodeling, and non-coding RNA regulation. While VHL tumor suppressor gene inactivation occurs in over 90% of ccRCC cases, VHL loss alone is insufficient to induce tumors in mouse models, pointing to critical contributions from other epigenetic events [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Advances in sequencing and single-cell analysis have enabled our team and others to identify key epigenetic regulators in ccRCC, such as BRD9 and KDM4B [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], providing a crucial foundation for novel diagnostics and targeted therapies.\u003c/p\u003e\u003cp\u003eLarge-scale omics studies strongly support the centrality of epigenetic dysregulation in ccRCC. For instance, Terekhanova et al.'s (2023) Nature study, presenting a single-cell epigenomic atlas spanning 11 cancer types (integrating snATAC-seq and snRNA-seq data from 201 samples, including ccRCC), revealed highly specific chromatin accessibility patterns in ccRCC. This work identified aberrant activity of ccRCC-specific transcriptional regulators such as HNF1A and KLF9, which are strongly associated with tumor progression and metastasis[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Epigenetic mechanisms can influence gene expression by modulating chromatin accessibility including DNA methylation, histone acetylation, and histone methylation [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Chromatin accessibility refers to the dynamic property allowing regulatory factors access to DNA; regions where nucleosomes are displaced, exposing the DNA, are termed \"open chromatin\" [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. These accessible regions are enriched for cis-regulatory elements (promoters, enhancers, silencers, insulators) that, by binding transcription factors (TFs), dictate cell-type-specific gene programs [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. This dynamic remodeling is primarily governed by two mechanisms: ATP-dependent remodeling complexes and histone modifications [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Histone modifications function combinatorially and fall into two main types: those associated with permissive chromatin, such as H3K4me3, H3K4me1, and H3K27ac, and those associated with repressed chromatin, including H3K27me3 and H3K9me3. [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. ATP-dependent remodelers utilize nucleosome alterations to regulate chromatin accessibility (such as sliding, eviction, histone variant exchange) [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Crucially, the SWI/SNF complex\u0026mdash;among eukaryotes' most vital remodelers\u0026mdash;maintains open chromatin for enhancer/promoter functionality. SWI/SNF subunit genes harbor mutations in \u0026gt;\u0026thinsp;20% of cancers [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOur investigation uncovers a pivotal role for SMARCD1 in ccRCC. We found SMARCD1 upregulated in ccRCC tissues, and its depletion significantly inhibited tumor cell proliferation and migration. Functionally, SMARCD1 drives ccRCC proliferation, migration, and angiogenesis in vitro and in vivo, critically dependent on VEGFA. Mechanistically, SMARCD1 orchestrates epigenetic remodeling to open the VEGFA promoter region: qPCR confirmed reduced chromatin accessibility at VEGFA upon SMARCD1 knockdown. Furthermore, we found a new epigenetic mechanism of ccRCC that SMARCD1 overexpression increased enriching activating histone marks (H3K4me3, H3K27ac, H3K9ac) while decreasing the repressive mark H3K9me3 at the VEGFA promoter. Significantly, we discovered that SMARCD1 confers bevacizumab resistance in ccRCC. This parallels observations in other cancers: Shuyang Wang et al. showed FOXF1 elevates VEGFA, promoting colon cancer angiogenesis and bevacizumab resistance [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], while ETV5 directly binds the VEGFA promoter to drive resistance [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. A major translational hurdle is the current lack of specific SMARCD1 inhibitors.\u003c/p\u003e\u003cp\u003eStudy Limitations:\u003c/p\u003e\u003cp\u003eMechanistic Depth: Our exploration of SMARCD1's mechanisms in ccRCC requires further depth and breadth. To achieve more precise localization of the binding sites, high-throughput sequencing techniques such as ChIP-seq and ATAC-seq can be employed. We consider that SMARCD1 may drive resistance via multi-pathway mechanisms in bevacizumab-resistant models, thus comprehensive transcriptomic and proteomic studies are needed for further clarification.\u003c/p\u003e\u003cp\u003eTherapeutic Translation: While SMARCD1 represents a promising therapeutic target, developing specific inhibitors poses significant challenges. We propose close collaboration with pharmacologists to screen for potential SMARCD1 inhibitors.\u003c/p\u003e\u003cp\u003eIn conclusion, we find a novel SMARCD1\u0026ndash;VEGFA epigenetic regulatory axis (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). This study establishes that SMARCD1 promotes ccRCC proliferation, metastasis, and bevacizumab resistance by epigenetically remodeling the VEGFA promoter to enhance its accessibility and drive angiogenesis. Our findings nominate SMARCD1 as a promising therapeutic target for precision therapy in ccRCC.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHQ. L, J. X and YX. L conceived and designed the study, HQ. L Y. S, YC. H, CY. X, and XY. B collected clinical the performed the experiments and analyzed the results, HQ. L contributed to the writing of the manuscript. HQ. L, J. X and YX. L completed the revision work. All authors reviewed the manuscript. All authors agree to submit this version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe sincerely appreciate assistance from Medical Research Center of Anhui Provincial Hospital in providing convenient experimental conditions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was performed in line with the principles of the Declaration of Helsinki. The use of human specimens for this basic science study was approved by the Ethics Committee of The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China. Informed consent for the use of specimens was obtained from all donors or their legal guardians.\u003c/p\u003e\n\u003cp\u003eThe Ethics committee of experimental animals of The First Afliated Hospital of University of Science and Technology of China granted ethical approval for this study (approval number: 2025-N(A)-0148).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data from the TCGA and Cancer Cell Line Encyclopedia (CCLE) are publicly available and were used in this study. The data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Competing Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there are no competing interests of a financial or commercial nature that could have influenced the research presented in this paper.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBukavina L, Bensalah K, Bray F, Carlo M, Challacombe B, Karam JA, Kassouf W, Mitchell T, Montironi R, O\u0026apos;Brien T\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eEpidemiology of Renal Cell Carcinoma: 2022 Update\u003c/strong\u003e. \u003cem\u003eEur Urol \u003c/em\u003e2022, \u003cstrong\u003e82\u003c/strong\u003e(5):529-542.\u003c/li\u003e\n\u003cli\u003eSchiavoni V, Campagna R, Pozzi V, Cecati M, Milanese G, Sartini D, Salvolini E, Galosi AB, Emanuelli M: \u003cstrong\u003eRecent Advances in the Management of Clear Cell Renal Cell Carcinoma: Novel Biomarkers and Targeted Therapies\u003c/strong\u003e. \u003cem\u003eCancers (Basel) \u003c/em\u003e2023, \u003cstrong\u003e15\u003c/strong\u003e(12).\u003c/li\u003e\n\u003cli\u003eChoueiri TK, Motzer RJ: \u003cstrong\u003eSystemic Therapy for Metastatic Renal-Cell Carcinoma\u003c/strong\u003e. \u003cem\u003eN Engl J Med \u003c/em\u003e2017, \u003cstrong\u003e376\u003c/strong\u003e(4):354-366.\u003c/li\u003e\n\u003cli\u003eChatwal MS, Chahoud J, Spiess PE: \u003cstrong\u003eRevisiting mechanisms of resistance to immunotherapies in metastatic clear-cell renal-cell carcinoma\u003c/strong\u003e. \u003cem\u003eCancer Drug Resist \u003c/em\u003e2023, \u003cstrong\u003e6\u003c/strong\u003e(2):314-326.\u003c/li\u003e\n\u003cli\u003eAmin MB, Netto GJ, Berney DM, Board WCoTE: \u003cstrong\u003eUrinary and Male Genital Tumours\u003c/strong\u003e, vol. 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family remodelers\u003c/strong\u003e. \u003cem\u003eMol Cell \u003c/em\u003e2024, \u003cstrong\u003e84\u003c/strong\u003e(2):194-201.\u003c/li\u003e\n\u003cli\u003eMalone HA, Roberts CWM: \u003cstrong\u003eChromatin remodellers as therapeutic targets\u003c/strong\u003e. \u003cem\u003eNat Rev Drug Discov \u003c/em\u003e2024, \u003cstrong\u003e23\u003c/strong\u003e(9):661-681.\u003c/li\u003e\n\u003cli\u003eFeng H, Liu K, Shen X, Liang J, Wang C, Qiu W, Cheng X, Zhao R: \u003cstrong\u003eTargeting tumor cell-derived CCL2 as a strategy to overcome Bevacizumab resistance in ETV5(+) colorectal cancer\u003c/strong\u003e. \u003cem\u003eCell Death Dis \u003c/em\u003e2020, \u003cstrong\u003e11\u003c/strong\u003e(10):916.\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":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"SMARCD1, VEGFA, ccRCC, Epigenetics, Angiogenesis","lastPublishedDoi":"10.21203/rs.3.rs-8031896/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8031896/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003cbr\u003e\nClear cell renal cell carcinoma (ccRCC) is an aggressive malignancy characterized by strong invasiveness and treatment resistance. Although SMARCD1 has been studied in several cancers, its function in ccRCC and its regulatory relationship with the key angiogenic factor VEGFA remain unexplored.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003cbr\u003e\nClinical relevance of SMARCD1 was assessed through in vitro experiments and data analysis. Integrated in vivo and in vitro functional studies evaluated SMARCD1’s biological impact in ccRCC. SMARCD1-VEGFA epigenetic regulation was investigated via ChIP-qPCR, ATAC-qPCR, luciferase reporter assays, and HUVEC angiogenesis models. Bevacizumab-resistant cell lines and combination therapy models were established to validate SMARCD1’s role in drug resistance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003cbr\u003e\nSMARCD1 expression was significantly upregulated in ccRCC tissues and was strongly correlated with both disease progression and adverse clinical outcomes. Functionally, we have demonstrated that SMARCD1 promotes tumor proliferation, migration, and angiogenesis. Mechanistically, we have discovered that SMARCD1 binds directly to the VEGFA promoter, enhancing chromatin accessibility and modifying histone marks to activate transcriptional expression. The pro-tumor effects of SMARCD1 were found to be critically dependent on VEGFA. Furthermore, SMARCD1 knockdown sensitized bevacizumab-resistant ccRCC models to anti-angiogenic therapy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003cbr\u003e\nThis study establishes that SMARCD1 promotes ccRCC progression and bevacizumab resistance by epigenetically remodeling the VEGFA promoter region. These findings provide a mechanistic foundation for novel precision therapies targeting the SMARCD1-VEGFA axis.\u003c/p\u003e","manuscriptTitle":"Epigenetic activation of VEGFA by SMARCD1 mediates tumor progression and bevacizumab resistance in clear cell renal cell carcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-20 02:00:45","doi":"10.21203/rs.3.rs-8031896/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-16T03:15:48+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-13T10:45:26+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-11T13:41:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"176329813461985203702669221069938191332","date":"2026-01-03T10:26:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"58096006276584955277896642428158432292","date":"2026-01-02T12:54:55+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-28T13:42:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"219132477939953415036778829583499782727","date":"2025-11-26T02:20:03+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-10T16:44:37+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-10T16:21:06+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-07T08:05:44+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-06T07:09:08+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2025-11-06T07:05:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b3bf629f-4945-4d10-975e-f825302776ff","owner":[],"postedDate":"November 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-30T16:36:54+00:00","versionOfRecord":{"articleIdentity":"rs-8031896","link":"https://doi.org/10.1186/s12885-026-15791-z","journal":{"identity":"bmc-cancer","isVorOnly":false,"title":"BMC Cancer"},"publishedOn":"2026-03-23 16:11:57","publishedOnDateReadable":"March 23rd, 2026"},"versionCreatedAt":"2025-11-20 02:00:45","video":"","vorDoi":"10.1186/s12885-026-15791-z","vorDoiUrl":"https://doi.org/10.1186/s12885-026-15791-z","workflowStages":[]},"version":"v1","identity":"rs-8031896","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8031896","identity":"rs-8031896","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}