Rev-erbα deletion promotes gastric cancer progression through attenuating DLAT and DLST induced cuproptosis

Rev-erbα deletion promotes gastric cancer progression through attenuating DLAT and DLST induced cuproptosis | 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 Rev-erbα deletion promotes gastric cancer progression through attenuating DLAT and DLST induced cuproptosis Xiaoshan Wang, Yuwei Wu, Nana Wang, Mengding Chen, Feixu Chen, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4774872/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Cuproptosis is a unique copper-dependent cell death pathway. Nuclear receptor subfamily 1 group D member 1 (NR1D1/Rev-erbα) is a ligand-activated transcriptional regulator that is involved in regulating the development of circadian rhythm, lipid metabolism and immunity-associated diseases including cancer. However, the role of Rev-erbα in cuproptosis of gastric cancer (GC) cells remains poorly understood. Methods Functional assays both in vivo and in vitro were employed to explore the role of Rev-erbα on cell progression and cuproptosis, and its regulatory mechanism. Moreover, clinicopathological retrospective analysis explored the relationship of Rev-erbα with DLAT and DLST. Results Rev-erbα deletion promoted GC progression through cuproptosis. The Rev-erbα activator, GSK4112, inhibited GC progression through cuproptosis, and obtained a synergistical inhibitory effect with elesclomol. Mechanistically, Rev-erbα deletion promoted dihydrolipoamide S-acetyltransferase (DLAT) and dihydrolipoamide S-succinyltransferase (DLST) expression through inhibiting DLAT oligomerization. Notably, this regulation was dependent on the DNA-binding domain (DBD) of Rev-erbα. Moreover, the combination of GSK4112 with elesclomol inhibited DLAT and DLST expression, and Rev-erbα SUMOylation. Furthermore, DLAT and DLST expression levels were associated with histological grade and tumor-node-metastasis stage in patients with GC. Thus, DLAT or DLST expression exhibit potential as independent biomarkers for predicting the prognosis of patients with GC. In addition, Rev-erbα expression was negatively correlated with DLAT and DLST expression, and high Rev-erbα and low DLAT expression, or high Rev-erbα and low DLST let to optimal levels of disease-free survival in patients with GC. Conclusion Rev-erbα exhibits potential in the treatment of GC. Rev-erbα DLAT DLST progression cuproptosis gastric cancer Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Although the effectiveness of chemotherapy and targeted therapy has been demonstrated in the treatment of gastric cancer (GC), it remains one of the most common malignant tumors worldwide(1). Traditionally, cell apoptosis was the main mechanism underlying anti-cancer in the treatment of tumors. However, the intrinsic resistance of tumor cells has limited the role of these anti-cancer drugs in promoting tumor cell apoptosis(2). Therefore, non-apoptotic forms of cell death have provided a novel direction for research focused on the treatment of GC. Cuproptosis is a novel type of cell death that was initially proposed in 2022(3). Copper ion as an essential cofactor for living organisms, including mitochondrial respiration, antioxidant reactions, and biological macromolecule synthesis; However, excessive concentrations of copper cause mitochondrial cell death. This is due to the disruption of homeostasis maintenance following a series of lipoacylation and oligopolization of proteins, and the loss of the Fe-S cluster protein (3). Dihydrolipoamide S-acetyltransferase (DLAT) is one of the components of the pyruvate dehydrogenase (PDH) complex, which catalyzes the decarboxylation of pyruvate to acetyl-CoA in the tricarboxylic acid (TCA) cycle(4,5). Thus, DLAT plays an important role in lipid metabolism(5). Dihydrolipoamide S-succinyltransferase (DLST) is a key component of the α-ketoglutarate dehydrogenase complex, which catalyzes - α-ketoglutarate to produce succinyl-CoA(6). As copper ion transporters, DLAT and DLST maintain intracellular copper ion concentrations and escape abnormal cell death(3). Results of previous study revealed that DLAT and DLST expression levels are significantly increased in a variety of malignant tumors(7). However, the specific regulatory mechanisms remain to be fully elucidated. Nuclear receptor subfamily 1 group D member 1 (NR1D1/Rev-erbα) is an orphan nuclear hormone receptor that inhibits target gene transcription through binding to the region of retinoic acid-related orphan receptors response elements (RORE) sites or recruitment of the suppressor, N-CoR(8). Moreover, a series of post-translational modifications of Rev-erbα impacts stability of the protein, leading dysregulation(9). Thus, abnormal transcription and post-translational modification of Rev-erbα are involved in the occurrence and development of various malignant tumors(10). Previous studies demonstrated that Rev-erbα plays an important role in tumors, chronic disease and inflammation through ferroptosis (11–13). However, whether Rev-erbα is involved in regulating cuproptosis remains unknown. This study aimed to explore the role of Rev-erbα on cuproptosis both in vitro and in vivo. Thus, results of present study may provide a novel theoretical basis for the regulatory mechanism of cuproptosis in the treatment of GC. Materials and methods Patients and specimens Patients with GC were treated with D 2 radical gastrectomy according to the Chinese Society of Clinical Oncology and National Comprehensive Cancer Network guidelines( 14 , 15 ). Clinicopathological parameters and paraffin-embedded tissues were collected from the Department of Pathology in The First Affiliated Hospital of Anhui Medical University from August 2020 to September 2021. The tumor-node-metastasis (TNM) stage was assessed using enhanced computed tomography of abdomen and pelvis,according to 7th Edition of the International Union against Cancer TNM classification. Disease-free survival (DFS) was measured until local recurrence, distance metastasis or at 42 months. All patients provided written informed consent, and the present study was approved by the human Ethics Committee of Anhui Medical University (ethics approval no.20180344). Cell culture and treatment Human GC (AGS, PCH2024042803, MKN-74, PC-H2024052320) and Mouse Forestomach Carcinoma (MFC; PC-H2024031919) cell lines were purchased from Procell Life Science & Technology Co., Ltd. Cells were treated with the Rev-erbα activator, GSK4112 (5 µM; GlpBio), tetrathiomolybdate (TTM; 20µM; Sigma-Aldrich, Merck KGaA) or elesclomol (50 nM; MedChemExpress) for 24h at room temperature. These reagents were dissolved in dimethyl sulfoxide (DMSO). Construction of Rev-erbα knockout (KO) cell lines RNA-guided CRISPR/Cas9-mediated genome editing was performed in our previous study( 16 ). Briefly, Rev-erbα-targeting sgRNAs (cat. no. SC-401211; Santa Cruz Biotechnology, Inc.) were cloned using a lentiCRISPRv1 plasmid (Addgene, Inc.) to generate lentiCRISPRv1-Rev-erbα-sgRNA virus, according to the manufacturer’s protocol. The CRISPR-EGFP-sgRNA plasmid (Addgene, Inc.) was used to generate CRISPR-EGFP-sgRNA virus as a control. Cells were transduced into 1.5ml virus-containing supernatant with 6µg/ml polybrene at a multiplicity of infection (MOI) of 0.3 for AGS cells and 0.5 for MKN74 cells. Cells were incubated for 12 h at 37℃ and resuspended with 2 µg/ml puromycin for 2 weeks. Protein expression levels of Rev-erbα were detected using western blot analysis. Rev-erbα wild-type (WT) plasmids and plasmids lacking the DNA binding domain (DBD) were transfected into Rev-erbα KO cells( 17 ). Transfection of small interfering (si)RNA To reduce endogenous DLAT and DLST expression, cells were transfected with human siRNA-DLAT (Guangzhou RiboBio Co., Ltd.) and siRNA-DLST (Guangzhou RiboBio Co., Ltd.) at room temperature for 30 min, using Lipofectamine® RNAiMAX (Thermo Fisher Scientific, Inc.) according to the manufacturer’s protocol. Cells were cultured for 12 h, and the cell medium was changed for subsequent experiments. Cell Counting Kit-8 (CCK-8) assay Cells were seeded into 96-well microplates and subsequently incubated with 10 µl enhanced CCK-8 (Beyotime, Institute of Biotechnology) for 1h according to the manufacturer’s protocol. Optical density (OD) values were measured at 450nm using a microplate reader (Multiskan FC; Thermo Fisher Scientific, Inc.). Colony formation assay Cells (800 cells/well) were seeded into 6-well plates and cultured for 10 days at 37℃. Cells were washed using phosphate buffer solution (PBS) three times, and subsequently fixed with 4% paraformaldehyde for 10min at room temperature. Cell colonies were stained using 0.1% crystal violet, and colonies were counted three times in each well. Transwell assay Cells were seeded into 24-well microplates (Corning, Inc.). For invasion assays, Transwell membranes were pre-coated with Matrigel for 2 h at 37℃. Cells were suspended in 200 µl with serum-free medium and seeded into upper chamber. Subsequently, cells were transferred to corresponding wells containing 600µl medium and20% FBS, and cultured for 24h at 37℃. The lower surface of the chamber was fixed with 4% paraformaldehyde and stained with 0.1% crystal violet for 10 min at room temperature. Cell numbers were determined using ImageJ software (version, 1.54j; National Institutes of Health). Model of mice construction Mice (age, 6–8 weeks; C57; Beijing Vital River Laboratory Animal Technology Co., Ltd.) were randomly divided into three groups. Pre-treated MFC cells (2 x 10 5 cells/100 µl) were injected into the subcutaneous flanks of mice to construct subcutaneous tumors. Palpable tumors were measured every 2–3 days for 2 weeks, and mice were subsequently sacrificed using cervical dislocation. Tumors weight and volume were measured (1/2 x long diameter x short diameter), and the maximum was 784 mm 3 . All animal experiments complied with the International Protective Guidelines For Laboratory animals. The present study was approved by the Ethics Committee of Anhui Medical University (LLSC20180365). Western blot analysis proteins were extracted from cells using RIPA lysis buffer and, protein quantification was carried out using BCA assay kit (Beyotime, Institute of Biotechnology). Proteins were separated using SDS-PAGE (8% gel for lower 60KD and 10% gel for other KD proteins) and transferred onto polyvinylidene fluoride (PVDF) membrane. Membranes were incubated with the following primary antibodies: Anti-Rev-erbα (anti-rabbit; 1:1000; Affinity Biosciences), anti-DLAT (anti-rabbit; 1:1000; Abcam), anti-DLST (anti-rabbit; 1:1000; Abcam) and anti-β-actin (anti-rabbit; 1:1000Abcam) overnight at 4 0 C. Subsequently, membranes were incubated with secondary antibodies (anti-rabbit; 1:10000; Affinity Biosciences) for 2 h at room temperature. Protein bands were visualized using enhanced chemiluminescence (Fine-do X6; Tanon Science and Technology Co., Ltd.). Reverse-transcription quantitative (RT-q) PCR Total RNA was isolated from cells using TRIzol® reagent (Invitrogen; Thermo Fisher Scientific, Inc.) and cDNA was generated using a cDNA kit (TaKaRa Bio, Inc), according to the manufacturer’s instructions. qPCR was performed using GoTaq® Green Master Mix (Promega Corporation) on a 7900 Thermal Cycler (Thermo Fisher Scientific, Inc.) at an initial denaturation at 95˚C for 30 sec, followed by 40 cycles of denaturation for 5 sec at 95˚C, annealing for 30 sec at 60˚C and extension for 15 sec at 72˚C. Primers used for qPCR are displayed in Table S1 . mRNA expression levels were semi–quantified using the 2 −ΔΔCq method ( 18 ). β-actin was used as an internal control. Immunohistochemistry Sections were deparaffinized and immersed into boiling citrate buffer (pH,6.0). Subsequently, sections were incubated with the following primary antibodies: Anti-Rev-erbα (1:100; Affinity Biosciences), anti-DLAT (1:100; Affinity Biosciences), anti-DLST (1:100; Affinity Biosciences), anti-Ki-67 antibody (1:50 dilution; Affinity Biosciences) and anti-Proliferating Cell Nuclear Antigen antibody (PCNA; 1:50; Affinity Biosciences) for 2 h. Sections were stained with 3,3'-diaminobenzidine (1:100; OriGene Technologies, Inc.) and 20% hematoxylin at room temperature. Relative expression levels were assessed using mean OD (MOD) ( 19 ). High and low expression were calculated using the proportion grade multiplied by the staining intensity score. Scoring was as follows: 3 (> 76%), 2 (26–75%, brown and yellow-brown),1 (26–50%, light staining) and 0 (< 25%, no staining). A score of 0–2 was indicative of low expression and 3–6 was indicative of high expression. Immunoprecipitation (IP) assay Cell lysates were incubated with anti-Rev-erbα (1µg; Santa Cruz Biotechnology, Inc.) and Protein A/G PLUS-Agarose beads (10 µl; Santa Cruz Biotechnology, Inc.) overnight at 4°C. The mixture was centrifuged at 32,869.2 x g at 4˚C for 30 min and the Rev-erbα immunoprecipitation was collected. Cells were subsequently incubated with anti-SUMO-1 (1:1000; Cell Signaling Technology, Inc.) or SUMO-2 (1:1000; Cell Signaling Technology, Inc. Inductively coupled plasma-mass spectrometry (ICP-MS) assay Cells were lysed using RIPA buffer and supernatant was collected following centrifugation at 32,869.2 x g at 4˚C for 30 min. The filtered supernatant was diluted in 5% nitric acid. Subsequently, copper nominal concentration (Sigma-Aldrich; Merck KGaA) was used to formulate the standard curve, according to multiple dilution gradients. ICP-MS (7700X; Agilent Technologies, Inc.) was performed to detect the cellular copper concentration. Zero Interaction Potency (ZIP) model analysis cells viability was assessed using a CCK-8 assay as previously described. Synergistic effects were analyzed using ZIP model, according to (version, 3.0; https://synergyfinder.org/ ) ( 20 ). Scores that exceeded 10 were indicative of synergistic effects. Statistical analysis Data are expressed as the mean ± standard deviation. Statistical analysis was performed using SPSS (version, 19.0; IBM Corp.) and GraphPad Prism (version, 10.0.0; GraphPad Software, Inc.). Comparisons between multiple groups were carried out using Student’s t-tests (paired) or one-way ANOVA analysis. The Student-Newman-Keuls test was the post-hoc test used following analysis of variance. A correlation analysis was performed using Chi-squared. Survival analysis was performed using the Kaplan-Meier method and log-rank test. Univariate and multivariate survival analyses were performed by Cox proportional hazards model. P < 0.05 was considered to indicate a statistically significant difference. Results Rev-erbα deletion promotes GC progression and inhibits cuproptosis in GC cells To explore the role of Rev-erbα in GC progression and cuproptosis. CRISPR/Cas9 technology was used for Rev-erbα gene knockout ( Fig. 1A ). Results of the present study revealed that OD, colony number, migration, invasion and epithelial-mesenchymal transition (EMT) were increased in the Rev-erbα KO group, compared with the control (CON) group ( Fig. 1B-E ). In addition, results of the ICP-MS assay demonstrated that copper concentration was lower in the Rev-erbα KO group, compared with the CON group ( Fig. 1F ). These results indicated that Rev-erbα deletion may promote GC progression through attenuating cuproptosis. GSK4112 inhibits GC progression through promoting cuproptosis Results of previous studies demonstrated that GSK4112 acts as a Rev-erbα activator that inhibits inflammation ( 21 , 22 ). In addition, TTM, a copper chelator, alleviated cellular copper concentration( 3 ). Results of the present study revealed that GSK4112 significantly inhibited OD, cell colony number, migration, invasion and EMT; However, these effects were reversed following treatment with TTM in GC cells ( Fig. 2A-D ). In addition, MFC cells treated with GSK4112 or GSK4112 + TTM were used in mice. Results of the present study revealed a reduced tumor volume, tumor weight and proliferation capacity in the GSK4112 group, compared with Vehicle group. However, GSK4112-mediated effects were reversed following the addition of TTM ( Fig. S1 Aand B ). Moreover, results of the ICP-MS assay demonstrated that the concentration of copper in GC cells treated with GSK4112 was higher than GC cells treated with Vehicle or GSK4112 + TTM ( Fig. 2E ). These results demonstrated that GSK4112 is a suppressor of GC, and verified that Rev-erbα may inhibit GC progression through promoting cuproptosis. Rev-erbα deletion promotes GC progression through attenuating DLAT-and DLST-induced cuproptosis To determine the specific regulatory mechanisms underlying cuproptosis. DLAT and DLST expression was inhibited in GC cells. Results of functional assays revealed that siRNA-DLAT and siRNA-DLST reduced the effects of Rev-erbα KO on the progression of GC cells ( Fig. 3A-D ). In addition, results of the ICP-MS assay revealed that Rev-erbα KO + siRNA-DLAT or Rev-erbα KO + siRNA-DLST group rescued the attenuative effects of Rev-erbα KO + Vehicle group on cellular copper concentrations in GC cells ( Fig. 3E ). Next, Results of the western blot analysis revealed that Rev-erbα KO significantly enhanced DLAT and DLST expression in GC cells compared with the CON group ( Fig. 4A ). Moreover, Rev-erbα KO also inhibited the oligomerization of DLAT in GC cells (Fig. 4B) . The DBD of Rev-erbα binds to the genome( 23 ). Thus, Rev-erbαWT plasmids and plasmids lacking the DBD were used for transduction in Rev-erbα KO cells. Results of the western blot analysis revealed that Rev-erbα DBD mutant cells exhibited significantly increased levels of DLAT and DLST expression, highlighting that the Rev-erbα-mediated DLAT and DLST is dependent on DBD ( Fig. 4C ). Elesclomol in combination with GSK4112 synergistically inhibits GC cell progression and promotes cuproptosis Elesclomol is a potent copper ionophore that promotes cuproptosis through inhibiting ferredoxin 1 (FDX1)-mediated Fe-S cluster biosynthesis( 3 , 24 ). Results of a previous study revealed that FDX1 is an upstream regulator of DLAT and DLST( 3 ). Thus, the effects of elesclomol in combination with GSK4112 were determined in the present study. Results of the ICP-MS assay demonstrated that the combination of elesclomol with GSK4112 significantly promoted cuproptosis, compared with elesclomol treatment alone or Vehicle in GC cells ( Fig. 5A ). Moreover, the combination of elesclomol with GSK4112 exerted a synergistic effect on GC progression ( Fig. 5B ). Results of the western blot analysis revealed that a combination of elesclomol with GSK4112 resulted in the optimal inhibition of DLAT expression; However, DLST expression remained unaltered in GC cells ( Fig. 5C ). Moreover, results of the IP assay revealed that elesclomol inhibited SUMO-1 and SUMO-2 expression in GC cells; However, Rev-erbα expression remained altered. Collectively, these results indicated that Rev-erbα SUMOylation may be inhibited following treatment with elesclomol ( Fig. 5D ). Rev-erbα is associated with DLAT and DLST expression in patients with GC Using data obtained from The Cancer Genome Atlas Program (TCGA), TIMER 2.0 revealed high levels of DLAT and DLST expression in stomach adenocarcinoma-tumor ( Fig. 6A ). In addition, clinicopathological parameters and sections were obtained to perform a retrospective analysis. As shown in Table I, DLAT and DLST expression levels were significantly associated with histological grade and TNM stage. By contrast, age, gender, tumor size, primary tumor site, chronic disease, nerve and vascular invasion, and lymph node metastasis were not associated with DLAT or DLST expression levels. Moreover, results of the univariate and multivariate Cox regression models demonstrated that DFS is associated with histological grade, TNM stage, DLAT expression levels and DLST expression levels. Collectively, these results indicated that DLAT and DLST are independent biomarkers for predicting the prognosis of patients with GC ( Table II). In addition, results of the present study revealed that Rev-erbα expression levels were negatively correlated with DLAT or DLST expression levels in patients with GC ( Fig. 6B ). Furthermore, Notably, a more optimal DFS was observed in patients exhibiting high levels of Rev-erbα expression with low DLAT or DLST expression compared with alternate expression patterns in patients with GC ( Fig. 6C ). Discussion REV-ERBα and REV-ERBβ exhibit a high degree of homology with similar functions, and both are core members of the mammalian molecular biological clock system( 25 ). However, REV-ERBα impacts circadian rhythm to a greater degree, compared with REV-ERBβ( 25 ). Rev-erbα use compound of activation function, DBD and the ligand binding domain to inhibit transcription, and is commonly expressed in a variety of organs, tissues and cells( 25 ). REV-ERBα plays a key role in cell proliferation, metabolism, inflammation and DNA damage response. Perturbations of these processes are hallmarks of cancer, and results of a previous study demonstrated that chronic circadian rhythm disruption predisposed individuals to cancer development( 10 ). Results of a previous study revealed that NR1D1 suppressed tumor progression and lung metastasis through promoting DNA damage induced accumulation of cytosolic DNA fragments, and activation of the cyclic GMP-AMP synthase (cGAS)- stimulator of interferon gene (STING) signaling pathway( 26 ). Moreover, Rev-erbα inhibited autophagy through the downstream target of Atg5 in small cell lung cancer (SCLC). SR9009, an activator of Rev-erbα, impacted both chemosensitive and chemoresistant SCLC cells( 27 ). In addition, Rev-erbα expression predicted poor clinical outcomes in patients with N-MYC-driven human neuroblastomas, and suppressed the clonogenicity of neuroblastoma cells through diminishing ectopic brain and muscle arnt-like (BMAL1) expression( 28 ). However, the specific role of Rev-erbα in copper metabolism or cell death is yet to be elucidated in tumor progression, metastasis and chemoresistance. Results of the present study revealed that Rev-erbα deletion promoted GC cell progression through attenuating cuproptosis. By contrast, GSK4112, an activator of Rev-erbα, inhibited GC progression through promoting cuproptosis both in vitro and in vivo. Moreover, TTM rescued GSK4112-induced cuproptosis and promoted the progression of GC. Copper ion is an essential trace element in a variety of processes and a cofactor of essential enzymes( 29 ). Copper content is highly regulated by a series of transporters, molecular chaperons and enzymes that maintain copper concentrations at low levels( 29 ). In previous studies, abnormal copper metabolism was associated with cancer, cardiovascular disease, neurodegenerative diseases and genetic variation including hepatolenticular degeneration and Menkes disease( 3 , 7 , 29 – 31 ). Moreover, copper-mediated accumulation of inflammation also promoted abnormal cell death, which is associated with malignant tumors( 32 , 33 ). Cuproptosis as a novel form of cell death, is dependent on the accumulation of cellular copper ions. Cuproptosis is associated with mitochondrial respiration and oligomerization of lipoacylated proteins( 3 ). Results of a previous study used CRISPR-Cas9 to demonstrate that DLAT and DLST are closely associated with cuproptosis ( 3 ). Results of the present study revealed that siRNA-DLAT and siRNA-DLST reversed the effects of Rev-erbα KO on the progression of GC cells. Mechanistically, Rev-erbα deletion significantly enhanced DLAT and DLST expression and inhibited the oligomerization of DLAT in GC cells. Thus, Rev-erbα-medicated regulation of cuproptosis may be induced by DLAT and DLST in GC. In addition, results of the present study revealed that the DBD was the core region of Rev-erbα that regulates DLAT and DLST-induced cuproptosis in GC cells. Elesclomol is a copper ionophore that induces cuproptosis through the accumulation of cellular copper ions. Moreover, elesclomol binds copper to inhibit proteasomes and produce reactive oxygen species, leading to oxidative stress and cell apoptosis( 34 ). Therefore, elesclomol exhibits potential as an anti-tumor agent, and may exhibit more effective therapeutic responses through combining with glycolysis inhibitors or anti-tumor reagents( 24 ). Results of the present study revealed that elesclomol promoted cuproptosis in GC cells. Moreover, the combination of elesclomol with GSK4112 promoted cuproptosis to the highest degree, and exerted a synergistic effect on the inhibition of GC cells progression. Mechanistically, the combination of elesclomol and GSK4112 intensified the regulatory inhibition of DLAT expression. By contrast, elesclomol inhibited Rev-erbα SUMOylation, which may impact Rev-erbα stability. According to results obtained from TCGA, DLAT and DLST were expressed at high levels in GC. Results of the present study revealed that in 138 patients with GC, the majority exhibited high DLAT and DLST expression levels. In addition, DLAT and DLST expression levels were significantly associated with histological grade and TNM stage. Thus, DLAT or DLST may act as independent biomarkers for predicting the prognosis of patients with GC. These results were comparable with those observed in previous studies( 35 – 37 ). Results of the present study also demonstrated that Rev-erbα expression levels was negatively correlated with DLAT or DLST expression levels in patients with GC. Patients with high Rev-erbα expression levels in addition to low DLAT expression levels, and patients with low DLST expression levels exhibited optimal DFS, compared with patients with alternate expression patterns. Clinical data supported these in vitro and in vivo findings, suggesting that Rev-erbα may inhibit GC progression through promoting DLAT and DLST expression. Thus, compounds that activate Rev-erbα may exhibit potential in the treatment of GC. In conclusion, results of the present study revealed that Rev-erbα deletion promoted GC cell progression through attenuating cuproptosis. Mechanistically, Rev-erbα deletion may enhance DLAT and DLST expression, and inhibit the oligomerization of DLAT. Moreover, GSK4112 inhibited GC cell progression through promoting cuproptosis, and obtained a synergistic effect when combined with elesclomol. These findings highlighted a novel theoretical basis for the role of Rev-erbα in the treatment of GC. Declarations Ethics approval This study was carried out following the World Medical Association’s Declaration of Helsinki and was approved by the Research Ethics Committee in The First Affiliated of Anhui Medical University. Patient consent for publication This paper has not been accepted for publication. Written informed consent was obtained from all patients for publication. Competing interest The authors declares that there no conflicts of interest. Funding This study was funded by natural science foundation of Anhui province (grant no. 2008085MH1294). Authors contributions Xiaoshan, Wang designed the study. Yuwei, Wu and Nana, Wang drafted the manuscript, collected the clinicopathological data and performed analysis. Xiaoshan, Wang performed functional experiments in vivo and vitro. Nana, Wang performed immunohistochemistry staining. Mengding, Chen and Feixu, Chen performed ZIP analysis. Acknowledgement Not applicable. Data Availability Statement The data that support the findings of our study was available on request from the corresponding author. References Smyth EC, Nilsson M, Grabsch HI, van Grieken NC and Lordick F: Gastric cancer. In: The Lancet, 2020. Wong RSY: Apoptosis in cancer: From pathogenesis to treatment. Journal of Experimental and Clinical Cancer Research 30, 2011. 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Kirshner JR, He S, Balasubramanyam V, et al. : Elesclomol induces cancer cell apoptosis through oxidative stress. Mol Cancer Ther 7, 2008. Yang W, Wang Y, Huang Y, et al. : 4-Octyl itaconate inhibits aerobic glycolysis by targeting GAPDH to promote cuproptosis in colorectal cancer. Biomedicine and Pharmacotherapy 159, 2023. Anderson NM, Qin X, Finan JM, et al. : Metabolic enzyme DLST promotes tumor aggression and reveals a vulnerability to OXPHOS inhibition in high-risk neuroblastoma. Cancer Res 81, 2021. Chen Q, Wang Y, Yang L, et al. : PM2.5 promotes NSCLC carcinogenesis through translationally and transcriptionally activating DLAT-mediated glycolysis reprograming. Journal of Experimental and Clinical Cancer Research 41, 2022. Tables Table 1. The relationship of the expression levels of DLAT and DLST with clinicopathological parameters in GC patients Clinicopathological parameters Total Case,n DLAT expression levels, n DLST expression levels, n N=138 High (n=81) Low (n=57) χ 2 P-value High (n=77) Low (n=61) χ 2 P-value Age,years <60 32 23 9 2.319 0.128 21 11 1.154 0.283 ≥60 106 58 48 56 50 Gender Male 97 55 42 0.295 0.587 50 47 1.847 0.174 Female 41 26 15 27 14 Tumor size,cm <4 58 33 25 0.036 0.849 32 26 0.000 1.000 ≥4 90 48 32 45 35 Primary tumor site Antrum and body 84 48 36 0.586 0.746 45 39 0.467 0.792 Cardia and fundus 41 26 15 24 17 Diffuse 13 7 6 8 5 Histological grade High and moderate differentiation 73 33 40 10.482 0.001 30 43 12.345 <0.001 Low differentiation 65 48 17 47 18 TNM stage I-II 36 11 25 14.377 <0.001 9 27 17.079 <0.001 III-IV 102 70 32 68 34 Chronic disease No 88 57 31 3.040 0.081 52 36 0.732 0.392 Yes 50 24 26 25 25 Nerve and vascular invasion No 110 63 47 0.210 0.647 58 52 1.503 0.220 Yes 28 18 10 19 9 Lymph node metastasis No 68 35 33 2.329 0.127 32 36 3.481 0.062 Yes 70 46 24 45 25 Table 2. Univariate and multivariate analyses of c linicopathological parameters in GC patients for DFS Clinicopathological parameters Univariate analysis Multivariate analysis HR 95%CI P-value HR 95%CI P-value Age,years <60 vs. ≥60 1.038 0.658-1.636 0.873 Gender Male vs. Female 1.143 0.768-1.701 0.509 Tumor size,cm <4 vs. ≥4 1.013 0.704-1.458 0.943 Primary tumor site Antrum and body vs. Cardia and fundus vs. Diffuse 0.379 Histological grade High and moderate differentiation vs. Low differentiation 1.827 1.169-2.853 0.008 1.906 1.265-2.873 0.002 TNM stage I-II vs. III-IV 0.482 0.285-0.816 0.007 1.906 1.265-2.873 0.002 Chronic disease No vs. Yes 0.991 0.670-1.468 0.966 Nerve and vascular invasion No vs. Yes 0.820 0.511-1.316 0.412 Lymph node metastasis No vs. Yes 0.930 0.599-1.444 0.745 DLAT expression levels Low vs. High 0.612 0.409-0.915 0.017 0.594 0.400-0.883 0.010 DLST expression levels Low vs. High 0.590 0.394-0.883 0.010 0.602 0.411-0.882 0.009 Additional Declarations No competing interests reported. Supplementary Files SupplementFigureLegends.docx FigureS1.jpg TableS1.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4774872","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":333466845,"identity":"e5d597b3-7260-489a-8c5f-973b294f1ff4","order_by":0,"name":"Xiaoshan Wang","email":"","orcid":"","institution":"First Affiliated Hospital of Anhui Medical University, Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xiaoshan","middleName":"","lastName":"Wang","suffix":""},{"id":333466847,"identity":"e9b483f9-5f16-45d9-af21-9186ef5933b8","order_by":1,"name":"Yuwei Wu","email":"","orcid":"","institution":"First Affiliated Hospital of Anhui Medical University, Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yuwei","middleName":"","lastName":"Wu","suffix":""},{"id":333466850,"identity":"3a0a8dfc-6627-4ee9-893a-ce0b4d6715b3","order_by":2,"name":"Nana Wang","email":"","orcid":"","institution":"North District of the First Affiliated Hospital of Anhui Medical University, Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Nana","middleName":"","lastName":"Wang","suffix":""},{"id":333466851,"identity":"9d79dc9d-5c39-4fc9-967f-775e3be184cc","order_by":3,"name":"Mengding Chen","email":"","orcid":"","institution":"First Affiliated Hospital of Anhui Medical University, Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Mengding","middleName":"","lastName":"Chen","suffix":""},{"id":333466852,"identity":"2605d52d-5c8f-4d3f-a970-d205c5ea56d1","order_by":4,"name":"Feixu Chen","email":"","orcid":"","institution":"First Affiliated Hospital of Anhui Medical University, Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Feixu","middleName":"","lastName":"Chen","suffix":""},{"id":333466853,"identity":"c2190b83-6723-4c50-836e-e7c06202e48e","order_by":5,"name":"Zhengguang Wang","email":"data:image/png;base64,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","orcid":"","institution":"First Affiliated Hospital of Anhui Medical University, Anhui Medical University","correspondingAuthor":true,"prefix":"","firstName":"Zhengguang","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-07-21 01:23:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4774872/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4774872/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":62798243,"identity":"c294506b-bfca-40e4-9a8e-b018c2c9e5c1","added_by":"auto","created_at":"2024-08-19 15:33:04","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1766614,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRev-erbαdeletion promotes progression and inhibits cuproptosis in GC cells. (A) \u003c/strong\u003eRev-erbα protein expression levels were detected in KO and CON GC cells. \u003cstrong\u003e(B) \u003c/strong\u003eThe absorbance value of Rev-erbα KO and CON GC cells through CCK-8 assay. N=3. \u003cstrong\u003e(C)\u003c/strong\u003e The colonies of Rev-erbα KO and CON GC cells were performed with colony formation assay. N=3. \u003cstrong\u003e(D) \u003c/strong\u003eThe\u003cstrong\u003e \u003c/strong\u003emigration and invasion ability of Rev-erbα KO and CON GC cells were performed with transwell assay. N=3. \u003cstrong\u003e(E) \u003c/strong\u003eThe relative mRNA levels of E-cadherin, N-cadherin and Vimentin in Rev-erbα KO and CONGC cells. N=3. \u003cstrong\u003e(F) \u003c/strong\u003eThe measurement of cellular copper was performed with ICP-MS in Rev-erbα KO and CON GC cells. N=3. All data are represented as the mean ± standard deviation. β-actin as a loading control. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt;0.001 and ****P\u0026lt;0.000.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4774872/v1/b377fb012d078634a04e660a.jpg"},{"id":62798254,"identity":"13149e9f-013e-4a79-9b82-31f45f63626d","added_by":"auto","created_at":"2024-08-19 15:33:07","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2073635,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGSK4112 inhibits GC progression through promoting cuproptosis in vitro. (A) \u003c/strong\u003eThe absorbance value of GC cells treated with GSK4112 and TTM through CCK-8 assay. N=3. \u003cstrong\u003e(B) \u003c/strong\u003eThe colonies of GC cells treated with GSK4112 and TTM were performed with colony formation assay. N=3. \u003cstrong\u003e(C) \u003c/strong\u003eThe\u003cstrong\u003e \u003c/strong\u003emigration and invasion ability of GC cells treated with GSK4112 and TTM were performed with transwell assay. N=3. \u003cstrong\u003e(D) \u003c/strong\u003eThe relative mRNA levels of E-cadherin, N-cadherin and Vimentin in GC cells treated with GSK4112 and TTM. N=3. \u003cstrong\u003e(E) \u003c/strong\u003eThe measurement of cellular copper was performed with ICP-MS in GC cells treated with GSK4112 and TTM. N=3. All data are represented as the mean ± standard deviation. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt;0.001 and ****P\u0026lt;0.000. Vs. Vehicle group. \u003csup\u003e+\u003c/sup\u003eP\u0026lt; 0.05, \u003csup\u003e++\u003c/sup\u003eP \u0026lt; 0.01, and \u003csup\u003e+++\u003c/sup\u003eP \u0026lt;0.001. Vs. GSK4112+TTM group.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4774872/v1/1ab69c59e794b0fc2bee55a4.jpg"},{"id":62798242,"identity":"9937718b-f71c-472e-bf70-e9ca5b05e2fb","added_by":"auto","created_at":"2024-08-19 15:33:03","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2704900,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRev-erbα deletion promotes progression through attenuating DLAT and DLST induced cuproptosis in GC cells. (A) \u003c/strong\u003eThe absorbance value of Rev-erbα KO GC cells transfected with siRNA-DLAT or siRNA-DLST through CCK-8 assay. N=3. \u003cstrong\u003e(B) \u003c/strong\u003eThe colonies of Rev-erbα KO GC cells transfected with siRNA-DLAT or siRNA-DLST were performed with colony formation assay. N=3. \u003cstrong\u003e(C) \u003c/strong\u003eThe\u003cstrong\u003e \u003c/strong\u003emigration and invasion ability of Rev-erbα KO GC cells transfected with siRNA-DLAT or siRNA-DLST were performed with transwell assay. N=3. \u003cstrong\u003e(D) \u003c/strong\u003eThe relative mRNA levels of E-cadherin, N-cadherin and Vimentin in Rev-erbα KO GC cells transfected with siRNA-DLAT or siRNA-DLST. N=3. \u003cstrong\u003e(E) \u003c/strong\u003eThe measurement of cellular copper was performed with ICP-MS in Rev-erbα KO GC cells transfected with siRNA-DLAT or siRNA-DLST. N=3. All data are represented as the mean ± standard deviation. β-actin as a loading control. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt;0.001 and ****P\u0026lt;0.000. Vs. CON+siRNA-NC group. \u003csup\u003e+\u003c/sup\u003eP\u0026lt; 0.05, \u003csup\u003e++\u003c/sup\u003eP \u0026lt; 0.01, and \u003csup\u003e+++\u003c/sup\u003eP \u0026lt;0.001. Vs. Rev-erbα+ siRNA-DLAT group. \u003csup\u003e#\u003c/sup\u003eP\u0026lt; 0.05, \u003csup\u003e##\u003c/sup\u003eP \u0026lt; 0.01, and \u003csup\u003e###\u003c/sup\u003eP \u0026lt;0.001. Vs. Rev-erbα+ siRNA-DLST group.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4774872/v1/92d6e2a067a51cc3b32d53d7.jpg"},{"id":62798250,"identity":"3f8bb702-ea2d-4ce5-a796-e3ded8e9b85b","added_by":"auto","created_at":"2024-08-19 15:33:06","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":350874,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRev-erbαdeletion enhances DLAT and DLST expression, and inhibits oligomerization of DLAT in GC cells. (A)\u003c/strong\u003e The DLAT and DLST protein expression levels were exhibited by western blot bands in Rev-erbα KO and CON GC cells. \u003cstrong\u003e(B)\u003c/strong\u003e The oligomerization of DLAT protein was exhibited by western blot bands in Rev-erbα KO and CON GC cells. \u003cstrong\u003e(C) \u003c/strong\u003eThe DLAT and DLST protein expression levels were exhibited by western blot bands in Rev-erbα WT and DBD mutant cells. Rev-erbα KO GC cells transfected with Rev-erbα WT plasmids and plasmids lacking DBD (DBD mutant) using the floxp-cre system. β-actin as a loading control.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4774872/v1/e3d0b0ce652a38fd93bdf172.jpg"},{"id":62798257,"identity":"d3a6ee5c-154e-42be-a84f-95f406755045","added_by":"auto","created_at":"2024-08-19 15:33:08","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":828053,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe combination of GSK4112 with elesclomol synergistically inhibits progression and promotes cuproptosis in GC cells. (A) \u003c/strong\u003eThe measurement of cellular copper was performed with ICP-MS in GC cells treated with GSK4112 and elesclomol. N=3. \u003cstrong\u003e(B) \u003c/strong\u003eThe combination effect of\u003cstrong\u003e \u003c/strong\u003eGSK4112 and elesclomol was analyzed by ZIP model in GC cells. \u003cstrong\u003e(C) \u003c/strong\u003eThe DLAT and DLST protein expression levels were exhibited by western blot bands in GC cells treated with GSK4112 and elesclomol. \u003cstrong\u003e(D) \u003c/strong\u003eRepresentative immunoblot of Rev-erbα SUMOylation by IP assay in GC cells treated with elesclomol. All data are represented as the mean ± standard deviation. β-actin as a loading control. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt;0.001 and ****P\u0026lt;0.000.\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4774872/v1/d996357ee5b3a01f85a40eff.jpg"},{"id":62798249,"identity":"b70779d9-d055-4d68-811d-1813cfcce9fb","added_by":"auto","created_at":"2024-08-19 15:33:06","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":2262139,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe relationship of Rev-erbα with DLAT and DLST in GC patients. (A) \u003c/strong\u003eDLAT and DLSTmRNA expression levels in stomach adenocarcinoma-tumor (STAD-tumor)tissues and stomach adenocarcinoma-normal (STAD-normal) tissues from TCGA database were analyzed throughTIMER 2.0. \u003cstrong\u003e(B) \u003c/strong\u003eUp:\u003cstrong\u003e \u003c/strong\u003eRev-erbα, DLAT and DLST expression levels were detected through immunohistochemistry stain in normal gastric and GC patients with high, moderate and low differentiation tissues. Original 200 and 400 magnification. Scale bar =100 μm. Down: The correlation analysis of Rev-erbα expression levels with DLAT and DLST expression levels in GC patients, respectively. \u003cstrong\u003e(C) \u003c/strong\u003eThe DFS times of GC patient with Rev-erbα, DLAT and DLST expression patterns. All data are represented as the mean ± standard deviation. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt;0.001 and ****P\u0026lt;0.000.\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4774872/v1/3768f3ef12d0014e93af0d45.jpg"},{"id":86622235,"identity":"eaa766b6-11ea-4e5b-917d-d8362f12371d","added_by":"auto","created_at":"2025-07-14 03:47:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":11812103,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4774872/v1/bfe8fdf8-5287-4a2a-b196-17362830070f.pdf"},{"id":62798244,"identity":"67f57647-6b71-4f8c-8dd9-884a6e2e4f33","added_by":"auto","created_at":"2024-08-19 15:33:04","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":11494,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementFigureLegends.docx","url":"https://assets-eu.researchsquare.com/files/rs-4774872/v1/9a3f1a886bf0ed4846f2e870.docx"},{"id":62798246,"identity":"9b3deac9-c408-4eaf-829b-5ff2607f905c","added_by":"auto","created_at":"2024-08-19 15:33:05","extension":"jpg","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1910144,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4774872/v1/f2ed3de6fe5e49847fea541b.jpg"},{"id":62799404,"identity":"47d995c5-4fcc-42a9-ba68-3f40748ceaa7","added_by":"auto","created_at":"2024-08-19 15:41:04","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":13052,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4774872/v1/52755e00bc6659f574a8d0c2.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Rev-erbα deletion promotes gastric cancer progression through attenuating DLAT and DLST induced cuproptosis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAlthough the effectiveness of chemotherapy and targeted therapy has been demonstrated in the treatment of gastric cancer (GC), it remains one of the most common malignant tumors worldwide(1). Traditionally, cell apoptosis was the main mechanism underlying anti-cancer in the treatment of tumors. However, the intrinsic resistance of tumor cells has limited the role of these anti-cancer drugs in promoting tumor cell apoptosis(2). Therefore, non-apoptotic forms of cell death have provided a novel direction for research focused on the treatment of GC.\u003c/p\u003e\n\u003cp\u003eCuproptosis\u0026nbsp;is a novel type of cell death that was initially proposed in 2022(3). Copper ion as an essential cofactor for living organisms, including mitochondrial respiration, antioxidant reactions, and biological macromolecule synthesis; However, excessive concentrations of copper cause mitochondrial cell death. This is due to the disruption of homeostasis maintenance following a series of lipoacylation and oligopolization of proteins, and the loss of the Fe-S cluster protein\u003csup\u003e\u0026nbsp;\u003c/sup\u003e(3). Dihydrolipoamide S-acetyltransferase (DLAT) is one of the components of the pyruvate dehydrogenase (PDH) complex, which catalyzes the decarboxylation of pyruvate to acetyl-CoA in the tricarboxylic acid (TCA) cycle(4,5). Thus, DLAT\u0026nbsp;plays an important role in lipid metabolism(5).\u0026nbsp;Dihydrolipoamide S-succinyltransferase (DLST)\u0026nbsp;is a key component of the \u0026alpha;-ketoglutarate dehydrogenase complex, which\u0026nbsp;catalyzes - \u0026alpha;-ketoglutarate\u0026nbsp;to produce succinyl-CoA(6). As copper ion transporters, DLAT and DLST maintain intracellular copper ion concentrations and escape abnormal cell death(3). Results of previous study revealed that DLAT and DLST expression levels are significantly increased in a variety of malignant tumors(7). However, the specific regulatory mechanisms remain to be fully elucidated.\u003c/p\u003e\n\u003cp\u003eNuclear receptor subfamily 1 group D member 1 (NR1D1/Rev-erb\u0026alpha;)\u0026nbsp;is an orphan nuclear hormone receptor that inhibits target gene transcription through binding to the region of retinoic acid-related orphan receptors response elements (RORE) sites or recruitment of the suppressor, N-CoR(8). Moreover, a series of post-translational modifications\u0026nbsp;of Rev-erb\u0026alpha;\u0026nbsp;impacts stability of the protein, leading dysregulation(9). Thus, abnormal transcription and post-translational modification of\u0026nbsp;Rev-erb\u0026alpha;\u0026nbsp;are involved in the occurrence and development of various malignant tumors(10). Previous studies\u0026nbsp;demonstrated that Rev-erb\u0026alpha; plays an important role in tumors, chronic disease and inflammation through ferroptosis\u003csup\u003e\u0026nbsp;\u003c/sup\u003e(11\u0026ndash;13). However, whether Rev-erb\u0026alpha; is involved in regulating cuproptosis remains unknown. This study aimed to explore the role of Rev-erb\u0026alpha; on cuproptosis both in vitro and in vivo. Thus, results of present study may provide a novel theoretical basis for the regulatory mechanism of cuproptosis in the treatment of GC.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003ePatients and specimens\u003c/h2\u003e \u003cp\u003ePatients with GC were treated with D\u003csub\u003e2\u003c/sub\u003e radical gastrectomy according to the Chinese Society of Clinical Oncology and National Comprehensive Cancer Network guidelines(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Clinicopathological parameters and paraffin-embedded tissues were collected from the Department of Pathology in The First Affiliated Hospital of Anhui Medical University from August 2020 to September 2021. The tumor-node-metastasis (TNM) stage was assessed using enhanced computed tomography of abdomen and pelvis,according to 7th Edition of the International Union against Cancer TNM classification. Disease-free survival (DFS) was measured until local recurrence, distance metastasis or at 42 months. All patients provided written informed consent, and the present study was approved by the human Ethics Committee of Anhui Medical University (ethics approval no.20180344).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCell culture and treatment\u003c/h2\u003e \u003cp\u003eHuman GC (AGS, PCH2024042803, MKN-74, PC-H2024052320) and Mouse Forestomach Carcinoma (MFC; PC-H2024031919) cell lines were purchased from Procell Life Science \u0026amp; Technology Co., Ltd. Cells were treated with the Rev-erbα activator, GSK4112 (5 \u0026micro;M; GlpBio), tetrathiomolybdate (TTM; 20\u0026micro;M; Sigma-Aldrich, Merck KGaA) or elesclomol (50 nM; MedChemExpress) for 24h at room temperature. These reagents were dissolved in dimethyl sulfoxide (DMSO).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eConstruction of Rev-erbα knockout (KO) cell lines\u003c/h2\u003e \u003cp\u003eRNA-guided CRISPR/Cas9-mediated genome editing was performed in our previous study(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Briefly, Rev-erbα-targeting sgRNAs (cat. no. SC-401211; Santa Cruz Biotechnology, Inc.) were cloned using a lentiCRISPRv1 plasmid (Addgene, Inc.) to generate lentiCRISPRv1-Rev-erbα-sgRNA virus, according to the manufacturer\u0026rsquo;s protocol. The CRISPR-EGFP-sgRNA plasmid (Addgene, Inc.) was used to generate CRISPR-EGFP-sgRNA virus as a control. Cells were transduced into 1.5ml virus-containing supernatant with 6\u0026micro;g/ml polybrene at a multiplicity of infection (MOI) of 0.3 for AGS cells and 0.5 for MKN74 cells. Cells were incubated for 12 h at 37℃ and resuspended with 2 \u0026micro;g/ml puromycin for 2 weeks. Protein expression levels of Rev-erbα were detected using western blot analysis. Rev-erbα wild-type (WT) plasmids and plasmids lacking the DNA binding domain (DBD) were transfected into Rev-erbα KO cells(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eTransfection of small interfering (si)RNA\u003c/h2\u003e \u003cp\u003eTo reduce endogenous DLAT and DLST expression, cells were transfected with human siRNA-DLAT (Guangzhou RiboBio Co., Ltd.) and siRNA-DLST (Guangzhou RiboBio Co., Ltd.) at room temperature for 30 min, using Lipofectamine\u0026reg; RNAiMAX (Thermo Fisher Scientific, Inc.) according to the manufacturer\u0026rsquo;s protocol. Cells were cultured for 12 h, and the cell medium was changed for subsequent experiments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eCell Counting Kit-8 (CCK-8) assay\u003c/h2\u003e \u003cp\u003eCells were seeded into 96-well microplates and subsequently incubated with 10 \u0026micro;l enhanced CCK-8 (Beyotime, Institute of Biotechnology) for 1h according to the manufacturer\u0026rsquo;s protocol. Optical density (OD) values were measured at 450nm using a microplate reader (Multiskan FC; Thermo Fisher Scientific, Inc.).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eColony formation assay\u003c/h2\u003e \u003cp\u003eCells (800 cells/well) were seeded into 6-well plates and cultured for 10 days at 37℃. Cells were washed using phosphate buffer solution (PBS) three times, and subsequently fixed with 4% paraformaldehyde for 10min at room temperature. Cell colonies were stained using 0.1% crystal violet, and colonies were counted three times in each well.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eTranswell assay\u003c/h2\u003e \u003cp\u003eCells were seeded into 24-well microplates (Corning, Inc.). For invasion assays, Transwell membranes were pre-coated with Matrigel for 2 h at 37℃. Cells were suspended in 200 \u0026micro;l with serum-free medium and seeded into upper chamber. Subsequently, cells were transferred to corresponding wells containing 600\u0026micro;l medium and20% FBS, and cultured for 24h at 37℃. The lower surface of the chamber was fixed with 4% paraformaldehyde and stained with 0.1% crystal violet for 10 min at room temperature. Cell numbers were determined using ImageJ software (version, 1.54j; National Institutes of Health).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eModel of mice construction\u003c/h2\u003e \u003cp\u003eMice (age, 6\u0026ndash;8 weeks; C57; Beijing Vital River Laboratory Animal Technology Co., Ltd.) were randomly divided into three groups. Pre-treated MFC cells (2 x 10\u003csup\u003e5\u003c/sup\u003e cells/100 \u0026micro;l) were injected into the subcutaneous flanks of mice to construct subcutaneous tumors. Palpable tumors were measured every 2\u0026ndash;3 days for 2 weeks, and mice were subsequently sacrificed using cervical dislocation. Tumors weight and volume were measured (1/2 x long diameter x short diameter), and the maximum was 784 mm\u003csup\u003e3\u003c/sup\u003e. All animal experiments complied with the International Protective Guidelines For Laboratory animals. The present study was approved by the Ethics Committee of Anhui Medical University (LLSC20180365).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eWestern blot analysis\u003c/h2\u003e \u003cp\u003eproteins were extracted from cells using RIPA lysis buffer and, protein quantification was carried out using BCA assay kit (Beyotime, Institute of Biotechnology). Proteins were separated using SDS-PAGE (8% gel for lower 60KD and 10% gel for other KD proteins) and transferred onto polyvinylidene fluoride (PVDF) membrane. Membranes were incubated with the following primary antibodies: Anti-Rev-erbα (anti-rabbit; 1:1000; Affinity Biosciences), anti-DLAT (anti-rabbit; 1:1000; Abcam), anti-DLST (anti-rabbit; 1:1000; Abcam) and anti-β-actin (anti-rabbit; 1:1000Abcam) overnight at 4\u003csup\u003e0\u003c/sup\u003eC. Subsequently, membranes were incubated with secondary antibodies (anti-rabbit; 1:10000; Affinity Biosciences) for 2 h at room temperature. Protein bands were visualized using enhanced chemiluminescence (Fine-do X6; Tanon Science and Technology Co., Ltd.).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eReverse-transcription quantitative (RT-q) PCR\u003c/h2\u003e \u003cp\u003eTotal RNA was isolated from cells using TRIzol\u0026reg; reagent (Invitrogen; Thermo Fisher Scientific, Inc.) and cDNA was generated using a cDNA kit (TaKaRa Bio, Inc), according to the manufacturer\u0026rsquo;s instructions. qPCR was performed using GoTaq\u0026reg; Green Master Mix (Promega Corporation) on a 7900 Thermal Cycler (Thermo Fisher Scientific, Inc.) at an initial denaturation at 95˚C for 30 sec, followed by 40 cycles of denaturation for 5 sec at 95˚C, annealing for 30 sec at 60˚C and extension for 15 sec at 72˚C. Primers used for qPCR are displayed in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. mRNA expression levels were semi\u0026ndash;quantified using the 2\u003csup\u003e\u0026minus;ΔΔCq\u003c/sup\u003e method (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). β-actin was used as an internal control.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eImmunohistochemistry\u003c/h2\u003e \u003cp\u003eSections were deparaffinized and immersed into boiling citrate buffer (pH,6.0). Subsequently, sections were incubated with the following primary antibodies: Anti-Rev-erbα (1:100; Affinity Biosciences), anti-DLAT (1:100; Affinity Biosciences), anti-DLST (1:100; Affinity Biosciences), anti-Ki-67 antibody (1:50 dilution; Affinity Biosciences) and anti-Proliferating Cell Nuclear Antigen antibody (PCNA; 1:50; Affinity Biosciences) for 2 h. Sections were stained with 3,3'-diaminobenzidine (1:100; OriGene Technologies, Inc.) and 20% hematoxylin at room temperature. Relative expression levels were assessed using mean OD (MOD) (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). High and low expression were calculated using the proportion grade multiplied by the staining intensity score. Scoring was as follows: 3 (\u0026gt;\u0026thinsp;76%), 2 (26\u0026ndash;75%, brown and yellow-brown),1 (26\u0026ndash;50%, light staining) and 0 (\u0026lt;\u0026thinsp;25%, no staining). A score of 0\u0026ndash;2 was indicative of low expression and 3\u0026ndash;6 was indicative of high expression.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eImmunoprecipitation (IP) assay\u003c/h2\u003e \u003cp\u003eCell lysates were incubated with anti-Rev-erbα (1\u0026micro;g; Santa Cruz Biotechnology, Inc.) and Protein A/G PLUS-Agarose beads (10 \u0026micro;l; Santa Cruz Biotechnology, Inc.) overnight at 4\u0026deg;C. The mixture was centrifuged at 32,869.2 x g at 4˚C for 30 min and the Rev-erbα immunoprecipitation was collected. Cells were subsequently incubated with anti-SUMO-1 (1:1000; Cell Signaling Technology, Inc.) or SUMO-2 (1:1000; Cell Signaling Technology, Inc.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eInductively coupled plasma-mass spectrometry (ICP-MS) assay\u003c/h2\u003e \u003cp\u003eCells were lysed using RIPA buffer and supernatant was collected following centrifugation at 32,869.2 x g at 4˚C for 30 min. The filtered supernatant was diluted in 5% nitric acid. Subsequently, copper nominal concentration (Sigma-Aldrich; Merck KGaA) was used to formulate the standard curve, according to multiple dilution gradients. ICP-MS (7700X; Agilent Technologies, Inc.) was performed to detect the cellular copper concentration.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eZero Interaction Potency (ZIP) model analysis\u003c/h2\u003e \u003cp\u003ecells viability was assessed using a CCK-8 assay as previously described. Synergistic effects were analyzed using ZIP model, according to (version, 3.0; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://synergyfinder.org/\u003c/span\u003e\u003cspan address=\"https://synergyfinder.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Scores that exceeded 10 were indicative of synergistic effects.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eData are expressed as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. Statistical analysis was performed using SPSS (version, 19.0; IBM Corp.) and GraphPad Prism (version, 10.0.0; GraphPad Software, Inc.). Comparisons between multiple groups were carried out using Student\u0026rsquo;s t-tests (paired) or one-way ANOVA analysis. The Student-Newman-Keuls test was the post-hoc test used following analysis of variance. A correlation analysis was performed using Chi-squared. Survival analysis was performed using the Kaplan-Meier method and log-rank test. Univariate and multivariate survival analyses were performed by Cox proportional hazards model. P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered to indicate a statistically significant difference.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eRev-erbα deletion promotes GC progression and inhibits cuproptosis in GC cells\u003c/h2\u003e \u003cp\u003eTo explore the role of Rev-erbα in GC progression and cuproptosis. CRISPR/Cas9 technology was used for Rev-erbα gene knockout (\u003cb\u003eFig.\u0026nbsp;1A\u003c/b\u003e). Results of the present study revealed that OD, colony number, migration, invasion and epithelial-mesenchymal transition (EMT) were increased in the Rev-erbα KO group, compared with the control (CON) group (\u003cb\u003eFig.\u0026nbsp;1B-E\u003c/b\u003e). In addition, results of the ICP-MS assay demonstrated that copper concentration was lower in the Rev-erbα KO group, compared with the CON group (\u003cb\u003eFig.\u0026nbsp;1F\u003c/b\u003e). These results indicated that Rev-erbα deletion may promote GC progression through attenuating cuproptosis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eGSK4112 inhibits GC progression through promoting cuproptosis\u003c/h2\u003e \u003cp\u003eResults of previous studies demonstrated that GSK4112 acts as a Rev-erbα activator that inhibits inflammation (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). In addition, TTM, a copper chelator, alleviated cellular copper concentration(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Results of the present study revealed that GSK4112 significantly inhibited OD, cell colony number, migration, invasion and EMT; However, these effects were reversed following treatment with TTM in GC cells (\u003cb\u003eFig.\u0026nbsp;2A-D\u003c/b\u003e). In addition, MFC cells treated with GSK4112 or GSK4112\u0026thinsp;+\u0026thinsp;TTM were used in mice. Results of the present study revealed a reduced tumor volume, tumor weight and proliferation capacity in the GSK4112 group, compared with Vehicle group. However, GSK4112-mediated effects were reversed following the addition of TTM (\u003cb\u003eFig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eAand B\u003c/b\u003e). Moreover, results of the ICP-MS assay demonstrated that the concentration of copper in GC cells treated with GSK4112 was higher than GC cells treated with Vehicle or GSK4112\u0026thinsp;+\u0026thinsp;TTM (\u003cb\u003eFig.\u0026nbsp;2E\u003c/b\u003e). These results demonstrated that GSK4112 is a suppressor of GC, and verified that Rev-erbα may inhibit GC progression through promoting cuproptosis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eRev-erbα deletion promotes GC progression through attenuating DLAT-and DLST-induced cuproptosis\u003c/h2\u003e \u003cp\u003eTo determine the specific regulatory mechanisms underlying cuproptosis. DLAT and DLST expression was inhibited in GC cells. Results of functional assays revealed that siRNA-DLAT and siRNA-DLST reduced the effects of Rev-erbα KO on the progression of GC cells (\u003cb\u003eFig.\u0026nbsp;3A-D\u003c/b\u003e). In addition, results of the ICP-MS assay revealed that Rev-erbα KO\u0026thinsp;+\u0026thinsp;siRNA-DLAT or Rev-erbα KO\u0026thinsp;+\u0026thinsp;siRNA-DLST group rescued the attenuative effects of Rev-erbα KO\u0026thinsp;+\u0026thinsp;Vehicle group on cellular copper concentrations in GC cells (\u003cb\u003eFig.\u0026nbsp;3E\u003c/b\u003e). Next, Results of the western blot analysis revealed that Rev-erbα KO significantly enhanced DLAT and DLST expression in GC cells compared with the CON group (\u003cb\u003eFig.\u0026nbsp;4A\u003c/b\u003e). Moreover, Rev-erbα KO also inhibited the oligomerization of DLAT in GC cells \u003cb\u003e(Fig.\u0026nbsp;4B)\u003c/b\u003e. The DBD of Rev-erbα binds to the genome(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Thus, Rev-erbαWT plasmids and plasmids lacking the DBD were used for transduction in Rev-erbα KO cells. Results of the western blot analysis revealed that Rev-erbα DBD mutant cells exhibited significantly increased levels of DLAT and DLST expression, highlighting that the Rev-erbα-mediated DLAT and DLST is dependent on DBD (\u003cb\u003eFig.\u0026nbsp;4C\u003c/b\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eElesclomol in combination with GSK4112 synergistically inhibits GC cell progression and promotes cuproptosis\u003c/h2\u003e \u003cp\u003eElesclomol is a potent copper ionophore that promotes cuproptosis through inhibiting ferredoxin 1 (FDX1)-mediated Fe-S cluster biosynthesis(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Results of a previous study revealed that FDX1 is an upstream regulator of DLAT and DLST(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Thus, the effects of elesclomol in combination with GSK4112 were determined in the present study. Results of the ICP-MS assay demonstrated that the combination of elesclomol with GSK4112 significantly promoted cuproptosis, compared with elesclomol treatment alone or Vehicle in GC cells (\u003cb\u003eFig.\u0026nbsp;5A\u003c/b\u003e). Moreover, the combination of elesclomol with GSK4112 exerted a synergistic effect on GC progression (\u003cb\u003eFig.\u0026nbsp;5B\u003c/b\u003e). Results of the western blot analysis revealed that a combination of elesclomol with GSK4112 resulted in the optimal inhibition of DLAT expression; However, DLST expression remained unaltered in GC cells (\u003cb\u003eFig.\u0026nbsp;5C\u003c/b\u003e). Moreover, results of the IP assay revealed that elesclomol inhibited SUMO-1 and SUMO-2 expression in GC cells; However, Rev-erbα expression remained altered. Collectively, these results indicated that Rev-erbα SUMOylation may be inhibited following treatment with elesclomol (\u003cb\u003eFig.\u0026nbsp;5D\u003c/b\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eRev-erbα is associated with DLAT and DLST expression in patients with GC\u003c/h2\u003e \u003cp\u003eUsing data obtained from The Cancer Genome Atlas Program (TCGA), TIMER 2.0 revealed high levels of DLAT and DLST expression in stomach adenocarcinoma-tumor (\u003cb\u003eFig.\u0026nbsp;6A\u003c/b\u003e). In addition, clinicopathological parameters and sections were obtained to perform a retrospective analysis. As shown in \u003cb\u003eTable\u003c/b\u003e I, DLAT and DLST expression levels were significantly associated with histological grade and TNM stage. By contrast, age, gender, tumor size, primary tumor site, chronic disease, nerve and vascular invasion, and lymph node metastasis were not associated with DLAT or DLST expression levels. Moreover, results of the univariate and multivariate Cox regression models demonstrated that DFS is associated with histological grade, TNM stage, DLAT expression levels and DLST expression levels. Collectively, these results indicated that DLAT and DLST are independent biomarkers for predicting the prognosis of patients with GC (\u003cb\u003eTable\u003c/b\u003e II). In addition, results of the present study revealed that Rev-erbα expression levels were negatively correlated with DLAT or DLST expression levels in patients with GC (\u003cb\u003eFig.\u0026nbsp;6B\u003c/b\u003e). Furthermore, Notably, a more optimal DFS was observed in patients exhibiting high levels of Rev-erbα expression with low DLAT or DLST expression compared with alternate expression patterns in patients with GC (\u003cb\u003eFig.\u0026nbsp;6C\u003c/b\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eREV-ERBα and REV-ERBβ exhibit a high degree of homology with similar functions, and both are core members of the mammalian molecular biological clock system(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). However, REV-ERBα impacts circadian rhythm to a greater degree, compared with REV-ERBβ(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Rev-erbα use compound of activation function, DBD and the ligand binding domain to inhibit transcription, and is commonly expressed in a variety of organs, tissues and cells(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). REV-ERBα plays a key role in cell proliferation, metabolism, inflammation and DNA damage response. Perturbations of these processes are hallmarks of cancer, and results of a previous study demonstrated that chronic circadian rhythm disruption predisposed individuals to cancer development(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Results of a previous study revealed that NR1D1 suppressed tumor progression and lung metastasis through promoting DNA damage induced accumulation of cytosolic DNA fragments, and activation of the cyclic GMP-AMP synthase (cGAS)- stimulator of interferon gene (STING) signaling pathway(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Moreover, Rev-erbα inhibited autophagy through the downstream target of Atg5 in small cell lung cancer (SCLC). SR9009, an activator of Rev-erbα, impacted both chemosensitive and chemoresistant SCLC cells(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). In addition, Rev-erbα expression predicted poor clinical outcomes in patients with N-MYC-driven human neuroblastomas, and suppressed the clonogenicity of neuroblastoma cells through diminishing ectopic brain and muscle arnt-like (BMAL1) expression(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). However, the specific role of Rev-erbα in copper metabolism or cell death is yet to be elucidated in tumor progression, metastasis and chemoresistance. Results of the present study revealed that Rev-erbα deletion promoted GC cell progression through attenuating cuproptosis. By contrast, GSK4112, an activator of Rev-erbα, inhibited GC progression through promoting cuproptosis both in vitro and in vivo. Moreover, TTM rescued GSK4112-induced cuproptosis and promoted the progression of GC.\u003c/p\u003e \u003cp\u003eCopper ion is an essential trace element in a variety of processes and a cofactor of essential enzymes(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Copper content is highly regulated by a series of transporters, molecular chaperons and enzymes that maintain copper concentrations at low levels(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). In previous studies, abnormal copper metabolism was associated with cancer, cardiovascular disease, neurodegenerative diseases and genetic variation including hepatolenticular degeneration and Menkes disease(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Moreover, copper-mediated accumulation of inflammation also promoted abnormal cell death, which is associated with malignant tumors(\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Cuproptosis as a novel form of cell death, is dependent on the accumulation of cellular copper ions. Cuproptosis is associated with mitochondrial respiration and oligomerization of lipoacylated proteins(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Results of a previous study used CRISPR-Cas9 to demonstrate that DLAT and DLST are closely associated with cuproptosis (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Results of the present study revealed that siRNA-DLAT and siRNA-DLST reversed the effects of Rev-erbα KO on the progression of GC cells. Mechanistically, Rev-erbα deletion significantly enhanced DLAT and DLST expression and inhibited the oligomerization of DLAT in GC cells. Thus, Rev-erbα-medicated regulation of cuproptosis may be induced by DLAT and DLST in GC. In addition, results of the present study revealed that the DBD was the core region of Rev-erbα that regulates DLAT and DLST-induced cuproptosis in GC cells.\u003c/p\u003e \u003cp\u003eElesclomol is a copper ionophore that induces cuproptosis through the accumulation of cellular copper ions. Moreover, elesclomol binds copper to inhibit proteasomes and produce reactive oxygen species, leading to oxidative stress and cell apoptosis(\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Therefore, elesclomol exhibits potential as an anti-tumor agent, and may exhibit more effective therapeutic responses through combining with glycolysis inhibitors or anti-tumor reagents(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Results of the present study revealed that elesclomol promoted cuproptosis in GC cells. Moreover, the combination of elesclomol with GSK4112 promoted cuproptosis to the highest degree, and exerted a synergistic effect on the inhibition of GC cells progression. Mechanistically, the combination of elesclomol and GSK4112 intensified the regulatory inhibition of DLAT expression. By contrast, elesclomol inhibited Rev-erbα SUMOylation, which may impact Rev-erbα stability.\u003c/p\u003e \u003cp\u003eAccording to results obtained from TCGA, DLAT and DLST were expressed at high levels in GC. Results of the present study revealed that in 138 patients with GC, the majority exhibited high DLAT and DLST expression levels. In addition, DLAT and DLST expression levels were significantly associated with histological grade and TNM stage. Thus, DLAT or DLST may act as independent biomarkers for predicting the prognosis of patients with GC. These results were comparable with those observed in previous studies(\u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). Results of the present study also demonstrated that Rev-erbα expression levels was negatively correlated with DLAT or DLST expression levels in patients with GC. Patients with high Rev-erbα expression levels in addition to low DLAT expression levels, and patients with low DLST expression levels exhibited optimal DFS, compared with patients with alternate expression patterns. Clinical data supported these in vitro and in vivo findings, suggesting that Rev-erbα may inhibit GC progression through promoting DLAT and DLST expression. Thus, compounds that activate Rev-erbα may exhibit potential in the treatment of GC.\u003c/p\u003e \u003cp\u003eIn conclusion, results of the present study revealed that Rev-erbα deletion promoted GC cell progression through attenuating cuproptosis. Mechanistically, Rev-erbα deletion may enhance DLAT and DLST expression, and inhibit the oligomerization of DLAT. Moreover, GSK4112 inhibited GC cell progression through promoting cuproptosis, and obtained a synergistic effect when combined with elesclomol. These findings highlighted a novel theoretical basis for the role of Rev-erbα in the treatment of GC.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval\u0026nbsp;\u003c/strong\u003eThis study was carried out following the World Medical Association\u0026rsquo;s Declaration of Helsinki and was approved by the Research Ethics Committee in The First Affiliated of Anhui Medical University.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient consent for publication\u0026nbsp;\u003c/strong\u003eThis paper has not been accepted for publication. Written informed consent was obtained from all patients for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest\u003c/strong\u003e The authors declares that there no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003eThis study was funded by natural science foundation of Anhui province (grant no. 2008085MH1294).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors contributions\u0026nbsp;\u003c/strong\u003eXiaoshan, Wang designed the study. Yuwei, Wu and Nana, Wang drafted the manuscript, collected the clinicopathological data and performed analysis. Xiaoshan, Wang performed functional experiments in vivo and vitro. Nana, Wang performed immunohistochemistry staining. Mengding, Chen and Feixu, Chen performed ZIP analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u0026nbsp;\u003c/strong\u003eThe data that support the findings of our study was available on request from the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSmyth EC, Nilsson M, Grabsch HI, van Grieken NC and Lordick F: Gastric cancer. In: The Lancet, 2020.\u003c/li\u003e\n\u003cli\u003eWong RSY: Apoptosis in cancer: From pathogenesis to treatment. Journal of Experimental and Clinical Cancer Research 30, 2011.\u003c/li\u003e\n\u003cli\u003eTsvetkov P, Coy S, Petrova B, \u003cem\u003eet al.\u003c/em\u003e: Copper induces cell death by targeting lipoylated TCA cycle proteins. 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The relationship of the expression levels of DLAT\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;and\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eDLST with\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eclinicopathological parameters in GC patients\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"747\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinicopathological\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eparameters\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eCase,n\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.01070950468541%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDLAT expression levels, n\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.7429718875502%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDLST expression levels, n\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eN=138\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh (n=81)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow (n=57)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh (n=77)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow (n=61)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge,years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e2.319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e0.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e1.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e0.283\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e0.295\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e0.587\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e1.847\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e0.174\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTumor size,cm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e0.849\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimary tumor site\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003eAntrum and body\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e0.586\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e0.746\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e0.467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e0.792\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003eCardia and fundus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003eDiffuse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistological grade\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003eHigh and moderate differentiation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e10.482\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e12.345\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003eLow differentiation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTNM stage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003eI-II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e14.377\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e17.079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003eIII-IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eChronic disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e3.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e0.732\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e0.392\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNerve and vascular invasion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e0.210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e0.647\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e1.503\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e0.220\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLymph node metastasis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e2.329\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e0.127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e3.481\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.214190093708165%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.032128514056225%\" valign=\"top\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.236947791164658%\" valign=\"top\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96921017402945%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370816599732262%\" valign=\"top\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.835341365461847%\" valign=\"top\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.165997322623829%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.504685408299865%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Univariate and multivariate analyses of c\u003c/strong\u003e\u003cstrong\u003elinicopathological\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;parameters in GC patients for DFS\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" \u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.160493827160494%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinicopathological\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eparameters\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.15520282186949%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.68430335097002%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariate analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.160493827160494%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95%CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95%CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.640211640211641%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.160493827160494%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge,years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.640211640211641%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.160493827160494%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;60 vs.\u0026nbsp;\u0026ge;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e1.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e0.658-1.636\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e0.873\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.640211640211641%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.160493827160494%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.640211640211641%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.160493827160494%\" valign=\"top\"\u003e\n \u003cp\u003eMale vs. Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e1.143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e0.768-1.701\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e0.509\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.640211640211641%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.160493827160494%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTumor size,cm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.640211640211641%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.160493827160494%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;4 vs.\u0026nbsp;\u0026ge;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e1.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e0.704-1.458\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e0.943\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.640211640211641%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.160493827160494%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimary tumor site\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.640211640211641%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.160493827160494%\" valign=\"top\"\u003e\n \u003cp\u003eAntrum and body vs. Cardia and fundus vs. Diffuse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e0.379\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.640211640211641%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.160493827160494%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistological grade\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.640211640211641%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.160493827160494%\" valign=\"top\"\u003e\n \u003cp\u003eHigh and moderate differentiation\u0026nbsp;vs.\u0026nbsp;Low differentiation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e1.827\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e1.169-2.853\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e1.906\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e1.265-2.873\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.640211640211641%\" valign=\"top\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.160493827160494%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTNM stage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.640211640211641%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.160493827160494%\" valign=\"top\"\u003e\n \u003cp\u003eI-II vs. III-IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e0.482\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e0.285-0.816\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e1.906\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e1.265-2.873\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.640211640211641%\" valign=\"top\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.160493827160494%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eChronic disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.640211640211641%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.160493827160494%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u0026nbsp;vs.\u0026nbsp;Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e0.991\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e0.670-1.468\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e0.966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.640211640211641%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.160493827160494%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNerve and vascular invasion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.640211640211641%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.160493827160494%\" valign=\"top\"\u003e\n \u003cp\u003eNo vs. Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e0.820\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e0.511-1.316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e0.412\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.640211640211641%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.160493827160494%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLymph node metastasis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.640211640211641%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.160493827160494%\" valign=\"top\"\u003e\n \u003cp\u003eNo vs. Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e0.930\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e0.599-1.444\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e0.745\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.640211640211641%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.160493827160494%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDLAT expression levels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.640211640211641%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.160493827160494%\" valign=\"top\"\u003e\n \u003cp\u003eLow vs. High\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e0.612\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e0.409-0.915\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e0.594\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e0.400-0.883\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.640211640211641%\" valign=\"top\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.160493827160494%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDLST expression levels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.640211640211641%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.160493827160494%\" valign=\"top\"\u003e\n \u003cp\u003eLow vs. High\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e0.590\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e0.394-0.883\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.818342151675486%\" valign=\"top\"\u003e\n \u003cp\u003e0.602\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.225749559082892%\" valign=\"top\"\u003e\n \u003cp\u003e0.411-0.882\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.640211640211641%\" valign=\"top\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Rev-erbα, DLAT, DLST, progression, cuproptosis, gastric cancer","lastPublishedDoi":"10.21203/rs.3.rs-4774872/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4774872/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eCuproptosis is a unique copper-dependent cell death pathway. Nuclear receptor subfamily 1 group D member 1 (NR1D1/Rev-erbα) is a ligand-activated transcriptional regulator that is involved in regulating the development of circadian rhythm, lipid metabolism and immunity-associated diseases including cancer. However, the role of Rev-erbα in cuproptosis of gastric cancer (GC) cells remains poorly understood.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eFunctional assays both in vivo and in vitro were employed to explore the role of Rev-erbα on cell progression and cuproptosis, and its regulatory mechanism. Moreover, clinicopathological retrospective analysis explored the relationship of Rev-erbα with DLAT and DLST.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eRev-erbα deletion promoted GC progression through cuproptosis. The Rev-erbα activator, GSK4112, inhibited GC progression through cuproptosis, and obtained a synergistical inhibitory effect with elesclomol. Mechanistically, Rev-erbα deletion promoted dihydrolipoamide S-acetyltransferase (DLAT) and dihydrolipoamide S-succinyltransferase (DLST) expression through inhibiting DLAT oligomerization. Notably, this regulation was dependent on the DNA-binding domain (DBD) of Rev-erbα. Moreover, the combination of GSK4112 with elesclomol inhibited DLAT and DLST expression, and Rev-erbα SUMOylation. Furthermore, DLAT and DLST expression levels were associated with histological grade and tumor-node-metastasis stage in patients with GC. Thus, DLAT or DLST expression exhibit potential as independent biomarkers for predicting the prognosis of patients with GC. In addition, Rev-erbα expression was negatively correlated with DLAT and DLST expression, and high Rev-erbα and low DLAT expression, or high Rev-erbα and low DLST let to optimal levels of disease-free survival in patients with GC.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eRev-erbα exhibits potential in the treatment of GC.\u003c/p\u003e","manuscriptTitle":"Rev-erbα deletion promotes gastric cancer progression through attenuating DLAT and DLST induced cuproptosis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-19 15:32:56","doi":"10.21203/rs.3.rs-4774872/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3b0ecead-5304-4171-8b93-c66a2e28610d","owner":[],"postedDate":"August 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-14T03:39:27+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-19 15:32:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4774872","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4774872","identity":"rs-4774872","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}