Overexpression of DIO1 is related to poor prognosis through regulating EMT and TAM infiltration in gastric carcinoma

Overexpression of DIO1 is related to poor prognosis through regulating EMT and TAM infiltration in gastric carcinoma | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Overexpression of DIO1 is related to poor prognosis through regulating EMT and TAM infiltration in gastric carcinoma Xinyou Liu, Kuan Yu, Zhenbin Shen, Qi Sun, Masami Yamamoto, Tetsuya Tsukamoto, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7563912/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 Gastric cancer (GC) remains a prevalent and lethal malignancy, with high rates of invasion and metastasis. Deiodinase 1 (DIO1) demonstrates the potential for tumor proliferation and invasion across various cancers, including GC. Herein, we aimed to investigate the role of DIO1 in tumor progression and its clinical significance in GC. In this study, we included 135 tumor microarray specimens from GC patients at Zhongshan Hospital, 329 GC patients from the Cancer Genome Atlas , and 300 GC patients from the Asian Cancer Research Group . Analysis of these three independent cohorts revealed that elevated DIO1 levels function as an independent adverse prognostic factor in GC. In vitro and in vivo studies manifested that DIO1 promotes GC cell proliferation, migration, and epithelial-mesenchymal transition (EMT) through the WNT/β-catenin/Twist axis. Furthermore, DIO1 enhances CCL2 production, facilitating tumor-associated macrophage (TAM) chemotaxis. Functional assays confirmed that DIO1 knockdown suppresses GC progression while its overexpression exacerbates it. In conclusion, our findings indicated that DIO1 is a pivotal oncogene in GC, serving as a potential inferior prognostic marker and a promising therapeutic target for improving GC treatment outcomes. DIO1 Gastric carcinoma EMT TAM poor prognosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Practitioner Points Elevated DIO1 levels predict poor prognosis in gastric cancer and guide risk stratification. DIO1 drives gastric cancer proliferation and EMT via the WNT/β-catenin/Twist axis, promoting tumor aggressiveness and metastasis. Targeting DIO1 may offer a novel therapeutic strategy by suppressing tumor-associated macrophage recruitment and tumor proliferation. Background Gastric cancer (GC) is a prevalent and lethal malignancy, ranking fifth in incidence and fourth in mortality worldwide 1 . Surgical resection remains the primary treatment for GC 2 . However, many patients are diagnosed at advanced stages, missing the opportunity for surgical options and resulting in unsatisfactory prognosis 3 . For these patients, comprehensive treatment strategies, including chemotherapy, radiation therapy, targeted therapy, and immunotherapy, offer hope. Hence, identifying new predictors and finding new therapeutic approaches are crucial challenges. GC is predominantly adenocarcinoma but is a complex, heterogeneous disease with various phenotypes. The Laurén classification 4 , dividing GC into intestinal, diffuse, and intermediate subtypes, provides limited personalized guidance 5, 6 . Molecular classification, however, offers a new approach to personalized GC treatment. The Cancer Genome Atlas (TCGA) and the Asian Cancer Research Group (ACRG) proposed two distinct 4-group classifications. Notably, the epithelial-mesenchymal transition (EMT) subtype, identified by ACRG, has the highest metastasis rate and poorest prognosis 7 . EMT is a cellular program where epithelial cells lose polarity and adhesion, which is essential for embryogenesis, wound healing, and tumor progression 8 . It is also linked to recurrence and metastasis 9, 10 . Iodothyronine deiodinases (DIO), a family of selenoproteins, regulate the availability of the thyroid hormone l-thyroxine (T4) 11 . Recent research suggests that the DIO family may promote EMT 12 . Deiodinase 1 (DIO1), encoded by a 4-exon gene on human chromosome 1p32.3, is mainly expressed in the liver, kidney, thyroid, and pituitary 13 . Previous studies have shown that decreased DIO1 levels may facilitate hepatocellular carcinoma (HCC) progression 14 . Additionally, increased DIO1 expression is associated with poor prognosis in GC 15 . However, the mechanisms by which DIO1 influences GC invasiveness are poorly understood. Herein, we confirmed the predictive value of DIO1 expression by three independent cohorts. We comprehensively analyzed DIO1’s modulating role in GC progression through in vitro and in vivo experiments and explored the chemotactic function of DIO1 on tumor-associated macrophages (TAM). Notably, we revealed that DIO1 may promote GC progression via the WNT/β-catenin/Twist axis. Moreover, DIO1 shaped the tumor microenvironment (TME) with high TAM infiltration. In conclusion, these results suggested that DIO1 is a potential therapeutic target for GC treatment. Methods Patients ' Cohort Three independent GC cohorts were enrolled in this study. The Zhongshan Cohort consisted of 135 GC patients from Zhongshan Hospital, Fudan University (Shanghai, China). Transcriptomic and clinical data were obtained from the Asian Cancer Research Group (ACRG) database ( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE62254 ) and The Cancer Genome Atlas (TCGA) database ( https://portal.gdc.cancer.gov/ ). The TCGA Cohort included 329 tumor samples and 210 normal samples (excluding samples that lacked necessary clinical information). The ACRG Cohort included 300 GC patients. The clinicopathological characteristics of enrolled patients are listed in Table 1 . The clinical tumor stages were determined referring to the 8th Edition of the American Joint Committee on Cancer (AJCC) Cancer Staging System. Table 1 Relationship between DIO1 expression and clinical characteristics Factors TCGA Cohort ACRG Cohort Zhongshan Cohort DIO1 expression DIO1 expression DIO1 expression High Low P -value High Low P -value High Low P -value All patients 137 192 47 253 69 66 Age(years) a 0.363 0.148 0.953 Median (IQR) 66(39–90) 68(35–90) 66(36–81) 64(24–86) 62(35–80) 57(22–79) Gender 0.289 0.343 0.465 Female 45 74 13 88 48 42 Male 92 118 34 165 21 24 Grade 0.435 NA G1 4 4 6 3 G2 42 75 21 25 G3 88 108 42 38 G4 3 5 0 0 Lauren classification NA 0.081 0.005 Diffuse 18 132 23 38 Intestinal 29 121 46 28 T classification 0.901 0.014 0.323 T1 6 10 36 150 16 16 T2 26 40 6 85 6 12 T3 64 91 5 16 22 21 T4 41 51 25 17 N classification 0.173 0.148 0.416 N0 40 60 3 35 28 24 N1 32 54 27 104 14 10 N2 26 43 9 71 10 17 N3 39 35 8 43 17 15 TNM stage 0.614 0.003 0.488 Ⅰ 19 27 2 28 16 21 Ⅱ 41 65 22 75 21 16 Ⅲ 65 78 6 90 32 29 IV 12 22 17 60 0 0 Adjuvant chemotherapy b 0.962 0.912 NA No 61 86 13 68 Yes 76 106 34 185 Tissue Specimens We utilized 30 Stomach Adenocarcinoma (STAD) samples and paired normal tissues from Zhongshan Hospital (Xiamen) and 135 STAD samples from the Zhongshan Cohort to assess DIO1 expression levels. The methods included immunohistochemistry (IHC), reverse-transcription-polymerase chain reaction (RT-PCR) and Western Blot. Informed consent was not applicable as the study utilized anonymized data collected retrospectively, in accordance with ethical guidelines and institutional review board approval from Zhongshan Hospital and Zhongshan Hospital (Xiamen). Cell lines and cell culture Human gastric cancer cell lines (MKN74, AGS, SNU1, KATO III, MKN45, HGC-27) and the normal gastric mucosal epithelial cell line (GES1) were sourced from the Cell Bank of the Chinese Academy of Sciences (Shanghai, China). The cell lines GES1, MKN74, AGS, SNU1, KATO III, MKN45, and HGC-27 were cultured in RPMI-1640 medium (Gibco, USA) with 10% fetal bovine serum (FBS) (HyClone, Logan, UT, USA) and 1% penicillin-streptomycin (Gibco, USA). In contrast, AGS cells were cultured in DMEM medium (Gibco, USA) with 10% FBS. All the cells were maintained in a humidified incubator at 37°C with 5% CO2. YTN16, a transplantable gastric cancer cell line in C57BL/6 mice, was utilized in this study. Professor Sachiyo Nomura kindly provided the mouse-derived YTN16 GC cell line from the University of Tokyo. The cells were cultured per established protocols 16 . IHC Staining and Evaluation IHC staining was performed on formalin-fixed, paraffin-embedded tissue microarrays (TMAs) and paraffin sections. The sections were incubated with an anti-DIO1 primary antibody (diluted 1:400, Proteintech) followed by a secondary antibody. DAB solution was used for staining visualization, and counterstaining was performed with hematoxylin. IHC staining followed the manufacturer’s instructions, including negative and positive controls. Microscopic images were captured at x200 magnification, and three representative fields per sample were analyzed. Two pathologists, blinded to clinical information, independently evaluated and scored the IHC staining using a system that combined staining intensity and the percentage of positively stained cells to produce a total score ranging from 0 to 12. The antibodies used have been listed in Table S2. Assessment of Immune Infiltration We used the Tumor Immune Estimation Resource (TIMER) algorithm, a deconvolution algorithm, to predict the relative proportions of 6 infiltrating immune cell types in 329 STAD samples. The algorithm estimated the abundance of six tumor-infiltrating immune cells (TIICs) subsets (B cells, CD4 T cells, CD8T cells, macrophages, neutrophils, and dendritic cells) (available at https://cistrome.shinyapps.io/timer/ ) 1 . Patients were categorized into high and low DIO1 expression groups based on the median value of DIO1 expression, with P < 0.05 as the threshold. Cignal™ Finder 10-Pathway Reporter Array Luciferase reporter assays on the activity of ten diverse cancer-associated pathways of parental and anlotinib-resistant GC cells were performed using the Cignal™ Finder 10-Pathway Reporter Array (Qiagen, Dusseldorf, Germany) in accordance with the manufacturer’s protocols. The Luciferase activities were measured with a Dual-Luciferase Reporter Assay System (Promega, Wisconsin, USA) as described previously. Real-time polymerase chain reaction(RT-qPCR) Specific primers for DIO1 and other target genes were designed (Table S1 ). Total RNA was extracted from gastric cancer and normal gastric tissues, and cDNA was synthesized using the HiScript®III 1st Strand cDNA Synthesis Kit (Beijing, China). Gene expression was quantified using the Taq Pro Universal SYBR qPCR Master Mix (Beijing, China), with GAPDH as the internal reference gene. The 2-ΔΔCt method expressed the fold change in gene expression relative to the control group. Western Blot Analysis Gastric cancer tissues stored at -196°C were used for Western Blot analysis. The anti-DIO1 polyclonal antibody (1:500 dilution, Proteintech, USA) was applied to detect the DIO1 protein. Similarly, GAPDH and other specific proteins were detected using corresponding polyclonal antibodies (all at a 1:500 dilution rate, Proteintech, USA). The results were analyzed using Image-Pro Plus software Colony Formation Assay To assess cell proliferation, 5 × 10³ cells were seeded in 6-well plates and cultured for 5–7 days. Fixed and stained with 0.5% crystal violet in 25% methanol for 1 hour, colonies were counted. Experiments were conducted in triplicate, with statistical significance assessed using Student’s t-test. Cellular Assays The MTT Cell Proliferation and Cytotoxicity Assay Kit was used to detect cell viability. Cells were seeded in 96-well plates and incubated for 72 hours, followed by MTT treatment and absorbance measurement at 450 nm. For the wound healing assay, cells were scratched, and images were captured at 0 and 24 hours. Wound healing was quantified by calculating the average wound area from three measurements. The transwell migration assay was performed using the Costar transwell system (CLS3364; Corning), with stained cells observed under a microscope (×4 magnification). For the wound healing assay, cancer cells were seeded in a 24-well plate and grown to confluence overnight. The next day, the monolayer was wounded with repeated scratches using a 200 µl pipette tip, and the media was changed to remove cell debris. Each wound was imaged at 0 hours and again after 24 hours. Wound healing was assessed by averaging three measurements of the wound areas. A transwell migration assay was performed using the Costar transwell system (CLS3364; Corning). Briefly, cancer cells (2 × 10 3 cells) were suspended in 200 µl serum-free medium and seeded in the upper insert chamber, with 500 µl medium added to the lower chamber. After 4 hours, media in both chambers were removed. Cells that migrated to the lower chamber through the 8-µm pore membrane were stained with crystal violet and visualized using a microscope (×4 magnification). Mice and Treatment For tumor-bearing experiments, 5×10 6 stably infected cancer cells were resuspended in sterile PBS (200 µL) and subcutaneously injected into one flank of 4-week-old female BALB/c-nude mice or C57BL/6 mice (n = 6, per group). Mice were obtained from the Animal Center of the Chinese Academy of Science, and the Ethics Committee of Zhongshan Hospital approved all animal experiments. All protocols followed guidelines for the welfare of laboratory animals. Following cancer cell injection, tumor sizes on the flanks were measured biweekly using vernier calipers, and tumor volume was calculated using the formula: V=(L×W2)/2. After 24 days, surgeries were performed under sodium pentobarbital anesthesia with minimized suffering, and tumor xenografts were harvested for ELISA analysis. ELISA Cells (2 × 10 6 /100 mm dish) were cultured for 24 hours. Then, the media were replaced with 10 ml of serum-free DMEM. Supernatants were collected 24 hours later, and any floating cells were removed by 0.45 µm filtration. The concentration of CCL2 protein in the supernatant was determined using a mouse-specific CCL2 ELISA kit (Abcam, Cat # ab206310). All experiments followed the manufacturer's instructions. Statistical Analysis Data processing and statistical analyses were conducted using R software v3.6.1 (R Foundation for Statistical Computing, Vienna, Austria), GraphPad Prism v10.2.1 (Macintosh Version, GraphPad Software, California, USA), Strawberry Perl v.5.30.1.1, and SPSS v.25 (SPSS Inc.). Analysis of variance (ANOVA) or Student’s t-test was employed to assess significant differences in DIO1 mRNA levels among various subgroups. The chi-square test was used to analyze the correlation between DIO1 expression levels and clinicopathological parameters of STAD. Survival analyses were conducted using the Kaplan–Meier method, and comparisons were made using the log-rank test. Univariate and multivariate survival analyses were performed using a Cox regression model. A P-value < 0.05 was considered statistically significant unless otherwise noted. For more information on the Material and Methods utilized in this research, please refer to Doc. S1 and Table S1 -S2. Results 3.1 DIO1 expression is upregulated in gastric cancer and is associated with poor prognosis The mRNA expression levels of DIO1 in cancer and para-cancerous tissues were analyzed using the TCGA database ( Fig. 1 A ) . The results showed elevated DIO1 expression in BRAC, PRAD, and STAD cancer tissues compared to para-cancerous tissues. Specifically, in gastric cancer (GC), analysis of TCGA transcriptomic data (329 GC tissues and 210 para-cancerous tissues; Fig. 1 B) revealed significantly higher DIO1 expression in GC tissues ( P < 0.05). Afterward, Kaplan-Meier curves and log-rank tests were conducted to compare the overall survival (OS) and progress-free interval (PFI) between DIO1 high- and low- expression subgroups. In both the TCGA and ACRG cohorts, higher DIO1 expression was associated with significantly worse OS ( P = 0.018 and P = 0.017; Fig. 1 C-D, left panel ) and PFI ( P = 0.002 and P = 0.05; Fig. 1 C-D, right panel ). Multivariate Cox regression analysis incorporated clinicopathological parameters (age, gender, Lauren classification, tumor grade, TNM stage), ACT, and DIO1 expression. DIO1 expression independently predicted poor prognosis for OS (TCGA cohort: HR = 1.51, 95% CI = 1.07–2.14, P = 0.020; ACRG cohort: HR = 1.81, 95% CI = 1.20–2.73, P = 0.005; Fig. 1 E) and PFI (TCGA cohort: HR = 1.66, 95% CI = 1.16–2.39, P = 0.006; ACRG cohort: HR = 1.50, 95% CI = 0.98–2.30, P = 0.065; Fig. 1 E). To further confirm our findings, IHC staining was performed on TMAs from the Zhongshan cohort ( Fig. 1 F ) , revealing variable DIO1 expression among GC patients. Survival analysis in the Zhongshan cohort aligned with results from the TCGA and ACRG cohorts ( Fig. 1 G ) . Collectively, these findings suggest that DIO1 expression may serve as an independent adverse prognostic marker for survival in GC. 3.2 Levels of mRNA and protein expression of DIOs in gastric cancer qRT-PCR analysis and Western blotting were conducted to confirm the expression of DIO1 in GC patients ( Fig. 1 H, I ) . The results revealed that the protein levels of DIO1 were significantly elevated in GC tissues compared to adjacent non-cancerous tissues. To further identify the role of DIO1 in various GC cell lines, qRT-PCR analysis and Western Blotting were performed ( Fig. 1 J ) . The findings indicated that the HGC-27 GC cell line exhibited the highest levels of DIO1 expression, whereas the GES-1 cell line, MKN74 and AGS GC cell line showed low DIO1 expression. 3.3 DIO1 promoted gastric cancer cell proliferation and metastasis To explore the role of DIO1 in gastric mucosa tumorigenesis, we established a HGC-27 cell line with DIO1 knockdown using three independent shRNAs (sh1, sh2, sh3) and an AGS cell line with DIO1 overexpression. Knockdown and overexpression efficiencies were validated by qRT-PCR and WB ( Fig. 2 A, B ) . DIO1 knockdown inhibited HGC-27 cell proliferation, while DIO1 overexpression accelerated AGS cell growth, as shown by the MTT assay ( P < 0.01, Fig. 2 C, D). Similarly, colony-forming assays revealed fewer colonies in the DIO1 knockdown group ( P < 0.01; Fig. 2 E) and more colonies in the DIO1 overexpression group ( P < 0.01; Fig. 2 F). DIO1 knockdown significantly reduced the flattening and spreading of HGC-27 cells, while its overexpression enhanced these properties in AGS cells, as shown by the wound healing assay ( P < 0.01; Fig. 2 G, H). Similarly, the transwell assay demonstrated reduced invasiveness in DIO1 knockdown cells and increased invasion in DIO1-overexpressing cells ( P < 0.01; Fig. 2 I, J). Epithelial-mesenchymal transition (EMT), a process observed in various cancers, including GC, drives changes in cell migration and invasion 17 . Our findings suggest that DIO1 regulates EMT by modulating key markers such as E-cadherin, N-cadherin, Vimentin, Snail, and Twist. Specifically, DIO1 knockdown significantly upregulated E-cadherin in HGC-27 cells ( Fig. 2 K ) , while its overexpression in AGS cells increased N-cadherin, Vimentin, and Twist levels and reduced E-cadherin expression ( Fig. 2 L ) . 3.4 DIO1 promotes gastric cancer cell EMT process and proliferation through regulation of 3,3'-5-triiodothyronine expression The conversion of T4 to the active hormone 3,3'-5-triiodothyronine (T3) is mediated by the 5'-deiodinases DIO1 and DIO2 18 . Studies indicate that the DIO1 inhibitor PTU significantly lowers T3 levels, particularly in hyperthyroid patients compared to euthyroid individuals 19 . T3 has been increasingly recognized for its role in tumorigenesis 20 . Given the observed link between DIO1 and EMT, we hypothesized that DIO1 might promote EMT by upregulating T3. To test this, we measured T3 concentrations in the supernatant of GC cells. ( Fig. 3 A ) . DIO1 knockdown significantly reduced T3 levels in HGC-27 cells, while DIO1 overexpression increased T3 levels in AGS cells ( Fig. 3 A ) . To determine whether DIO1 influences EMT through T3 regulation, we analyzed its EMT-related markers. Similar to DIO1-deficient HGC-27 cells, T3-deprived HGC-27 cells showed reduced N-cadherin, Vimentin, and Twist levels, with increased E-cadherin expression ( Fig. 3 B, left panel) . Conversely, AGS cells treated with additional T3 and overexpressing DIO1 exhibited elevated N-cadherin, Vimentin, and Twist levels and decreased E-cadherin expression ( Fig. 3 B, right panel) . To evaluate the DIO1 function in vivo, we implanted HGC-27-DIO-KD, HGC-27-Mock, AGS-DIO-OE, and AGS-Mock cells subcutaneously into nude mice (5 × 10^ 6 cells per mouse, six mice per group). After five weeks, tumors in the HGC-27-DIO-KD group were significantly smaller than those in the HGC-27-Mock group ( as shown in the upper patr of Figuer 3C) . In contrast, tumors in the AGS-DIO-OE group were notably larger than those in the AGS-Mock group (as shown in the lower part of Fig. 3 C ) . Quantitative analysis confirmed these findings, with significant tumor volume reduction in the HGC-27-DIO1-KD group ( P < 0.001) and a marked increase in the AGS-DIO1-OE group ( P < 0.001) ( Fig. 3 D ) . Thyroid hormone T3 levels in subcutaneous tumor tissues were also assessed ( Fig. 3 E ) . Tumors from HGC-27-DIO1-KD mice showed significantly reduced T3 levels, while tumors from AGS-DIO1-OE mice exhibited increased T3 levels. These findings highlight DIO1’s role in promoting EMT by elevating T3 levels in the local tumor environment, thereby facilitating GC progression. 3.5 DIO1 promotes gastric cancer cell EMT process and proliferation via WNT/β-catenin/Twist signaling pathway To investigate how DIO1 promotes EMT and GC cell proliferation, we analyzed EMT-related signaling pathways using the Cignal Finder Reporter Array and Western Blot. DIO1 knockdown significantly reduced WNT signaling activity in HGC-27 cells, while DIO1 overexpression enhanced it in AGS cells ( Fig. 4 A, B; left panel) . The WNT/β-catenin pathway, a key regulator in cancer progression 21 , was further assessed by examining the phosphorylation of β-catenin, AKT, ERK, and SMAD3. Notably, β-catenin expression decreased in HGC-27 cells with DIO1 knockdown but increased in AGS cells with DIO1 overexpression ( Fig. 4 A, B; right panel) . Previous studies revealed that TR-α1 (thyroid hormone receptor T3) overexpression stabilizes β-catenin and promotes carcinoma development 22–24 . We hypothesize that T3 activates β-catenin via TR-α1. Supporting this, TR-α1 knockdown reduced β-catenin activity in AGS cells with DIO1 overexpression ( Fig. 4 C ) . Given Twist’s role in EMT and cell migration 25 , we examined the influence of β-catenin on Twist using a β-catenin agonist in DIO1-knockdown HGC-27 cells and a β-catenin inhibitor in DIO1-overexpressing AGS cells ( Fig. 4 D ) . The β-catenin agonist (SKL2001) increased N-cadherin, Vimentin, and Twist expression while reducing E-cadherin levels ( Fig. 4 D, left panel) , thereby promoting cell growth in HGC-27 cells, effects counteracted by Twist knockdown ( Fig. 4 E ) . Conversely, the β-catenin inhibitor (WIKI-4) reduced N-cadherin, Vimentin, and Twist expression while increasing E-cadherin levels ( Fig. 4 D, right panel) , suppressing AGS cell proliferation. These effects were reversed by Twist overexpression ( Fig. 4 F ) . Transwell migration assays showed that DIO1 knockdown reduced HGC-27 cell migration, an effect reversed by the β-catenin agonist SKL2001 or Twist overexpression ( Fig. 4 G ) . Conversely, DIO1 overexpression enhanced AGS cell migration, which was suppressed by the β-catenin inhibitor WIKI-4 or Twist knockdown ( Fig. 4 H ) . In summary, DIO1 promotes GC cell proliferation and migration via the WNT/β-catenin/Twist axis, highlighting its potential as a therapeutic target in GC. 3.6 DIO1 upregulates β-Catenin activity to enhance CCL2 production and TAM chemotaxis in Gastric Cancer Tumor-infiltrating immune cells are key components of the TME and play critical roles in tumor progression 26, 27 . We assessed the relationship between DIO1 expression and immune infiltration in GC, finding that DIO1 mRNA levels positively correlated with CD4 + T cells, CD8 + T cells, neutrophils, macrophages, and myeloid dendritic cells ( Fig. 5 A ) . To investigate DIO1's role in immune cell infiltration in vivo, YTN16-DIO-KD and YTN16-Mock cells were implanted into NGS and C57BL/6 mice (5 × 10^6 cells per mouse, six mice per group). At five weeks, tumor volumes were significantly smaller in both NGS-YTN16-DIO1-KD and C57BL/6-YTN16-DIO1-KD groups compared to their respective controls (Fig. 5 C, P < 0.001). Notably, tumors in immunocompetent C57BL/6 mice with DIO1 knockdown were smaller than those in NGS mice (Fig. 5 C, P = 0.007), indicating that immune activation in immunocompetent mice may suppress tumor growth. Tumor-associated macrophages (TAMs) infiltrate the TME and exert immunosuppressive effects 27, 28 . IHC confirmed that TAMs were significantly enriched in C57BL/6-YTN16 tumors with mock controls compared to those with DIO1 knockdown ( Fig. 5 B ) . Transwell assays showed that DIO1 knockdown reduced macrophage migration in HGC-27 cells (Fig. 5 D, P < 0.001), while DIO1 overexpression increased migration in AGS cells (Fig. 5 D, P < 0.001). Chemokines regulate immune cell localization and function in the TME 29, 30 . To explore how DIO1 promotes TAM infiltration, we measured chemokine levels in GC cell supernatants. CCL2 levels were significantly reduced in DIO1-deficient HGC-27 cells and elevated in DIO1-overexpressing AGS cells (Fig. 5 E, P < 0.05). As CCL2 is crucial for TAM recruitment 31, 32 , Transwell assays confirmed its role in DIO1-mediated TAM infiltration. Overexpression of CCL2 increased macrophage migration in HGC-27-DIO-KD cells ( Fig. 5 F, above panel) , while CCL2 knockdown reduced macrophage migration in AGS-DIO-OE cells ( Fig. 5 F, below panel) . These results suggest that DIO1 promotes TAM recruitment by upregulating CCL2. Recent studies showed that the WNT/β-catenin pathway influences immune cell recruitment in the TME 33 . To determine its role in the DIO1/CCL2/TAM axis, we tested the effect of β-catenin modulation. The β-catenin agonist (SKL2001) increased macrophage migration and CCL2 levels in HGC-27-DIO-KD cells ( Fig. 5 H, above panel; Fig. 5 G, left panel) , while β-catenin inhibition reduced macrophage migration and CCL2 levels in AGS-DIO1-OE cells ( Fig. 5 H, below panel; Fig. 5 G, Right panel) . Interestingly, Twist knockdown did not affect macrophage migration, indicating that Twist is not involved in this pathway ( Fig. 5 G-H ) . In summary, these findings indicate that DIO1 enhances CCL2 production by upregulating β-catenin activity, thereby facilitating the chemotactic movement of TAMs in GC cells. Discussion Our study uncovered that DIO1, overexpressed in GC, acts as a novel oncogenic gene promoting tumor proliferation and invasion. Intriguingly, DIO1 not only induces EMT in GC cells but also correlates with immune responses. Mechanistically, DIO1 functions as a critical oncogene in GC by upregulating β-catenin, which subsequently increases Twist expression, CCL2 secretion, and TAM infiltration, thereby promoting the EMT pathway. DIO1, a deiodinase essential for triiodothyronine (T3) synthesis, regulates thyroid hormone homeostasis and cellular processes such as differentiation, proliferation, and apoptosis. While previous studies reported that DIO1 silencing enhances renal cancer cell proliferation and migration 34 , our findings reveal that DIO1 is highly expressed in GC tissues, promoting tumor proliferation, migration, and invasion. Overexpression of DIO1 significantly increases T3 levels, underscoring molecular differences between gastric adenocarcinoma and clear-cell renal cell carcinoma. EMT, characterized by a loss of epithelial features 8 (e.g., E-cadherin downregulation) and gain of mesenchymal traits (e.g., vimentin and N-cadherin upregulation) 35, 36 , drives tumor progression, metastasis, and therapy resistance 37, 38 . Our gain- and loss-of-function studies demonstrated that DIO1 overexpression induces EMT via Twist, while DIO1 knockdown reverses these changes. This is the first study to establish the pivotal role of DIO1 in EMT and GC progression. We investigated the molecular mechanisms of DIO1 in EMT and GC progression. Reporter assays revealed that DIO1 modulation significantly impacts the WNT/β-catenin pathway. Rescue experiments further confirmed the critical role of this pathway in DIO1-induced EMT. TAMs play critical roles in the tumor microenvironment (TME), influencing immune suppression and resistance to immunotherapy 39 . Activation of the WNT/β-catenin pathway promotes TAM recruitment and shifts their phenotype from tumor-inhibiting M1-like to tumor-promoting M2-like 40 . Aberrant WNT/β-catenin activation in cancer cells further drives EMT and modulates immune responses in the TME 41 . We validated the associations between DIO1 and the immune microenvironment via the TCGA cohort. Furthermore, under the guidance of Professor Sachiyo Nomura, we were gifted with an innovative gastric adenocarcinoma cell line derived from mice 16 . This development has made it possible to conduct in vivo experiments using immunocompetent GC mouse models. Our vivo experiment showed a significant decrease in TAMs in mice with DIO1 knockdown. Chemotactic experiments revealed that TAM chemotaxis decreased with DIO1 depletion and reversed with DIO1 overexpression. We demonstrated that β-catenin directly interacts with CCL2, promoting TAM recruitment in a CCL2-dependent manner. Before our research, few studies reported the relationship between DIO1 and β-catenin in EMT and TAMs. Therefore, our research indicates a novel potential target for immunotherapy in gastric cancer. There are several limitations to this study. First, the upstream signaling responsible for DIO1 overexpression in GC requires further exploration. Second, the relationship between GC and thyroid disease needs validation in larger cohorts. Third, additional experiments are necessary in order to investigate how DIO1 influences the TME systematically. Conclusions In summary, this study identifies DIO1 as an oncogene that promotes GC progression through enhanced EMT and TAM infiltration. These findings suggest DIO1 as a potential prognostic marker and therapeutic target for GC. Abbreviations 1. DIO1 Deiodinase 1 2. GC Gastric Cancer 3. EMT Epithelial-Mesenchymal Transition 4. TAM Tumor-Associated Macrophages 5. TCGA The Cancer Genome Atlas 6. ACRG Asian Cancer Research Group 7. TME Tumor Microenvironment 8. IHC Immunohistochemistry 9. RT PCR-Reverse-Transcription Polymerase Chain Reaction 10. qRT PCR-Quantitative Reverse Transcription Polymerase Chain Reaction 11. TMA Tissue Microarray 12. FBS Fetal Bovine Serum 13. PBS Phosphate Buffered Saline 14. MTT Methylthiazolyldiphenyl-tetrazolium bromide (Cell Proliferation Assay) 15. ELISA Enzyme-Linked Immunosorbent Assay 16. ANOVA Analysis of Variance 17. OS Overall Survival 18. PFI Progression-Free Interval 19. HR Hazard Ratio 20. CI Confidence Interval 21. STAD Stomach Adenocarcinoma 22. T3 Triiodothyronine (3,3'-5-triiodothyronine) 23. T4 Thyroxine (Tetraiodothyronine) 24. PTU Propylthiouracil 25. TR α1-Thyroid Hormone Receptor Alpha-1 26. MDSCs Myeloid-Derived Suppressor Cells 27. Treg Regulatory T Cells 28. SKL2001 β-catenin Agonist 29. WIKI 4-β-catenin Inhibitor Declarations Conflict of Interest: There are no conflicts of interest for the authors. Ethics declarations Ethics approval and consent to participate: Approval of the research protocol by an Institutional Reviewer Board: Approval granted by the Ethics Committee of Zhongshan Hospital, Fudan University (No.B2024-261) Consent for publication: Not Applicable Funding Information This study was funded by grants from the National Natural Science Foundation of China (82372792), the Natural Science Foundation of Xiamen (3502Z20227276), Xiamen Science and Technology Plan Project (3502Z20209060), Medical and Health Guided Project of Xiamen (3502220214201076). Author Contribution XL conducted the research and performed statistical analysis.KY and ZS conducted the research, interpreted the results, and drafted the manuscript.QS conducted pathological analysis.Masami Yamamoto, Tetsuya Tsukamoto and Sachiyo Nomura donor cell lines.XW, BC, and YC proposed concepts, designed the study, interpreted results, reviewed the manuscript, secured funding, and supervised the study. Acknowledgements: The authors thank Prof. Yihong Sun and Prof. Kuntang Shen (Gastric Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China) for their invaluable suggestions and assistance with specimen collection. We also thank Prof. Hailong Wu (Shanghai University of Medicine & Health Sciences, Shanghai, China) for his assistance in obtaining the YTN16 cell line. The authors thank Prof. Yingyong Hou, Dr. Xiaolei Zhang, and Dr. Xinxin Guo (Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China) for their excellent pathological technology support. Data Availability The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. References Sung H, Ferlay J, Siegel RL, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin . 2021; 71: 209–249. Coburn N, Cosby R, Klein L, et al. 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Cancer Biol Med . 2021; 19: 305–318. Additional Declarations No competing interests reported. Supplementary Files SUPPORTINGINFORMATION.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. 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3,3'-5-triiodothyronine.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7563912/v1/89f5cfe37e7cc1a51f84738f.png"},{"id":91815767,"identity":"cb73f6af-3dad-4891-b69f-46bc4d1857c3","added_by":"auto","created_at":"2025-09-22 06:31:32","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":870596,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDIO1 induced gastric cancer EMT by activating the β-catenin/TWIST signaling pathway.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7563912/v1/d88caf60fb6dc6effa593c01.png"},{"id":91815771,"identity":"8035d773-3efa-4d91-a83c-d9aef6088cd0","added_by":"auto","created_at":"2025-09-22 06:31:32","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1113743,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDIO1 induced the infiltration of tumor-associated macrophages through the secretion of CCL2.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7563912/v1/cc1f4f5ea715220c0977663d.png"},{"id":91817638,"identity":"73cc69b7-3577-44cd-9403-1da3b64ed4f0","added_by":"auto","created_at":"2025-09-22 06:59:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5841911,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7563912/v1/9be84b82-d2fa-42b8-ba80-e850af6b2723.pdf"},{"id":91816392,"identity":"a3ae0097-6433-4471-a4fa-4d577f65b7ec","added_by":"auto","created_at":"2025-09-22 06:39:32","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":14917,"visible":true,"origin":"","legend":"","description":"","filename":"SUPPORTINGINFORMATION.docx","url":"https://assets-eu.researchsquare.com/files/rs-7563912/v1/11e5e3497c59ea08bf239489.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Overexpression of DIO1 is related to poor prognosis through regulating EMT and TAM infiltration in gastric carcinoma","fulltext":[{"header":"Practitioner Points","content":"\u003col\u003e\n \u003cli\u003eElevated DIO1 levels predict poor prognosis in gastric cancer and guide risk stratification.\u003c/li\u003e\n \u003cli\u003eDIO1 drives gastric cancer proliferation and EMT via the WNT/β-catenin/Twist axis, promoting tumor aggressiveness and metastasis.\u003c/li\u003e\n \u003cli\u003eTargeting DIO1 may offer a novel therapeutic strategy by suppressing tumor-associated macrophage recruitment and tumor proliferation.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Background","content":"\u003cp\u003eGastric cancer (GC) is a prevalent and lethal malignancy, ranking fifth in incidence and fourth in mortality worldwide\u003csup\u003e1\u003c/sup\u003e. Surgical resection remains the primary treatment for GC\u003csup\u003e2\u003c/sup\u003e. However, many patients are diagnosed at advanced stages, missing the opportunity for surgical options and resulting in unsatisfactory prognosis\u003csup\u003e3\u003c/sup\u003e. For these patients, comprehensive treatment strategies, including chemotherapy, radiation therapy, targeted therapy, and immunotherapy, offer hope. Hence, identifying new predictors and finding new therapeutic approaches are crucial challenges.\u003c/p\u003e\u003cp\u003eGC is predominantly adenocarcinoma but is a complex, heterogeneous disease with various phenotypes. The Laur\u0026eacute;n classification\u003csup\u003e4\u003c/sup\u003e, dividing GC into intestinal, diffuse, and intermediate subtypes, provides limited personalized guidance\u003csup\u003e5, 6\u003c/sup\u003e. Molecular classification, however, offers a new approach to personalized GC treatment. The Cancer Genome Atlas (TCGA) and the Asian Cancer Research Group (ACRG) proposed two distinct 4-group classifications. Notably, the epithelial-mesenchymal transition (EMT) subtype, identified by ACRG, has the highest metastasis rate and poorest prognosis\u003csup\u003e7\u003c/sup\u003e. EMT is a cellular program where epithelial cells lose polarity and adhesion, which is essential for embryogenesis, wound healing, and tumor progression\u003csup\u003e8\u003c/sup\u003e. It is also linked to recurrence and metastasis\u003csup\u003e9, 10\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIodothyronine deiodinases (DIO), a family of selenoproteins, regulate the availability of the thyroid hormone l-thyroxine (T4) \u003csup\u003e11\u003c/sup\u003e. Recent research suggests that the DIO family may promote EMT\u003csup\u003e12\u003c/sup\u003e. Deiodinase 1 (DIO1), encoded by a 4-exon gene on human chromosome 1p32.3, is mainly expressed in the liver, kidney, thyroid, and pituitary\u003csup\u003e13\u003c/sup\u003e. Previous studies have shown that decreased DIO1 levels may facilitate hepatocellular carcinoma (HCC) progression\u003csup\u003e14\u003c/sup\u003e. Additionally, increased DIO1 expression is associated with poor prognosis in GC\u003csup\u003e15\u003c/sup\u003e. However, the mechanisms by which DIO1 influences GC invasiveness are poorly understood.\u003c/p\u003e\u003cp\u003eHerein, we confirmed the predictive value of DIO1 expression by three independent cohorts. We comprehensively analyzed DIO1\u0026rsquo;s modulating role in GC progression through in vitro and in vivo experiments and explored the chemotactic function of DIO1 on tumor-associated macrophages (TAM). Notably, we revealed that DIO1 may promote GC progression via the WNT/β-catenin/Twist axis. Moreover, DIO1 shaped the tumor microenvironment (TME) with high TAM infiltration. In conclusion, these results suggested that DIO1 is a potential therapeutic target for GC treatment.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003ePatients\u003c/strong\u003e\u0026apos; \u003cstrong\u003eCohort\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThree independent GC cohorts were enrolled in this study. The Zhongshan Cohort consisted of 135 GC patients from Zhongshan Hospital, Fudan University (Shanghai, China). Transcriptomic and clinical data were obtained from the Asian Cancer Research Group (ACRG) database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE62254\u003c/span\u003e\u003c/span\u003e) and The Cancer Genome Atlas (TCGA) database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://portal.gdc.cancer.gov/\u003c/span\u003e\u003c/span\u003e). The TCGA Cohort included 329 tumor samples and 210 normal samples (excluding samples that lacked necessary clinical information). The ACRG Cohort included 300 GC patients. The clinicopathological characteristics of enrolled patients are listed in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The clinical tumor stages were determined referring to the 8th Edition of the American Joint Committee on Cancer (AJCC) Cancer Staging System.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRelationship between DIO1 expression and clinical characteristics\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eFactors\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eTCGA Cohort\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eACRG Cohort\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eZhongshan Cohort\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eDIO1 expression\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eDIO1 expression\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eDIO1 expression\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAll patients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e192\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e253\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge(years)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.363\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.953\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66(39\u0026ndash;90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68(35\u0026ndash;90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66(36\u0026ndash;81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64(24\u0026ndash;86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62(35\u0026ndash;80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57(22\u0026ndash;79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.289\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.343\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.465\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGrade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.435\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\" rowspan=\"5\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eG1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eG2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eG3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eG4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLauren classification\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\" rowspan=\"3\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiffuse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIntestinal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT classification\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.901\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.014\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.323\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN classification\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.416\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTNM stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.614\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.488\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eⅠ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eⅡ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eⅢ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdjuvant chemotherapy\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.962\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.912\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\" rowspan=\"3\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eTissue Specimens\u003c/h2\u003e\n \u003cp\u003eWe utilized 30 Stomach Adenocarcinoma (STAD) samples and paired normal tissues from Zhongshan Hospital (Xiamen) and 135 STAD samples from the Zhongshan Cohort to assess DIO1 expression levels. The methods included immunohistochemistry (IHC), reverse-transcription-polymerase chain reaction (RT-PCR) and Western Blot. Informed consent was not applicable as the study utilized anonymized data collected retrospectively, in accordance with ethical guidelines and institutional review board approval from Zhongshan Hospital and Zhongshan Hospital (Xiamen).\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eCell lines and cell culture\u003c/h3\u003e\n\u003cp\u003eHuman gastric cancer cell lines (MKN74, AGS, SNU1, KATO III, MKN45, HGC-27) and the normal gastric mucosal epithelial cell line (GES1) were sourced from the Cell Bank of the Chinese Academy of Sciences (Shanghai, China). The cell lines GES1, MKN74, AGS, SNU1, KATO III, MKN45, and HGC-27 were cultured in RPMI-1640 medium (Gibco, USA) with 10% fetal bovine serum (FBS) (HyClone, Logan, UT, USA) and 1% penicillin-streptomycin (Gibco, USA). In contrast, AGS cells were cultured in DMEM medium (Gibco, USA) with 10% FBS. All the cells were maintained in a humidified incubator at 37\u0026deg;C with 5% CO2. YTN16, a transplantable gastric cancer cell line in C57BL/6 mice, was utilized in this study. Professor Sachiyo Nomura kindly provided the mouse-derived YTN16 GC cell line from the University of Tokyo. The cells were cultured per established protocols\u003csup\u003e16\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eIHC Staining and Evaluation\u003c/h3\u003e\n\u003cp\u003eIHC staining was performed on formalin-fixed, paraffin-embedded tissue microarrays (TMAs) and paraffin sections. The sections were incubated with an anti-DIO1 primary antibody (diluted 1:400, Proteintech) followed by a secondary antibody. DAB solution was used for staining visualization, and counterstaining was performed with hematoxylin. IHC staining followed the manufacturer\u0026rsquo;s instructions, including negative and positive controls. Microscopic images were captured at x200 magnification, and three representative fields per sample were analyzed. Two pathologists, blinded to clinical information, independently evaluated and scored the IHC staining using a system that combined staining intensity and the percentage of positively stained cells to produce a total score ranging from 0 to 12. The antibodies used have been listed in Table S2.\u003c/p\u003e\n\u003ch3\u003eAssessment of Immune Infiltration\u003c/h3\u003e\n\u003cp\u003eWe used the Tumor Immune Estimation Resource (TIMER) algorithm, a deconvolution algorithm, to predict the relative proportions of 6 infiltrating immune cell types in 329 STAD samples. The algorithm estimated the abundance of six tumor-infiltrating immune cells (TIICs) subsets (B cells, CD4 T cells, CD8T cells, macrophages, neutrophils, and dendritic cells) (available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cistrome.shinyapps.io/timer/\u003c/span\u003e\u003c/span\u003e)\u003csup\u003e1\u003c/sup\u003e. Patients were categorized into high and low DIO1 expression groups based on the median value of DIO1 expression, with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 as the threshold.\u003c/p\u003e\n\u003ch3\u003eCignal\u0026trade; Finder 10-Pathway Reporter Array\u003c/h3\u003e\n\u003cp\u003eLuciferase reporter assays on the activity of ten diverse cancer-associated pathways of parental and anlotinib-resistant GC cells were performed using the Cignal\u0026trade; Finder 10-Pathway Reporter Array (Qiagen, Dusseldorf, Germany) in accordance with the manufacturer\u0026rsquo;s protocols. The Luciferase activities were measured with a Dual-Luciferase Reporter Assay System (Promega, Wisconsin, USA) as described previously.\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eReal-time polymerase chain reaction(RT-qPCR)\u003c/h2\u003e\n \u003cp\u003eSpecific primers for DIO1 and other target genes were designed (Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e). Total RNA was extracted from gastric cancer and normal gastric tissues, and cDNA was synthesized using the HiScript\u0026reg;III 1st Strand cDNA Synthesis Kit (Beijing, China). Gene expression was quantified using the Taq Pro Universal SYBR qPCR Master Mix (Beijing, China), with GAPDH as the internal reference gene. The 2-\u0026Delta;\u0026Delta;Ct method expressed the fold change in gene expression relative to the control group.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eWestern Blot Analysis\u003c/h3\u003e\n\u003cp\u003eGastric cancer tissues stored at -196\u0026deg;C were used for Western Blot analysis. The anti-DIO1 polyclonal antibody (1:500 dilution, Proteintech, USA) was applied to detect the DIO1 protein. Similarly, GAPDH and other specific proteins were detected using corresponding polyclonal antibodies (all at a 1:500 dilution rate, Proteintech, USA). The results were analyzed using Image-Pro Plus software\u003c/p\u003e\n\u003ch3\u003eColony Formation Assay\u003c/h3\u003e\n\u003cp\u003eTo assess cell proliferation, 5 \u0026times; 10\u0026sup3; cells were seeded in 6-well plates and cultured for 5\u0026ndash;7 days. Fixed and stained with 0.5% crystal violet in 25% methanol for 1 hour, colonies were counted. Experiments were conducted in triplicate, with statistical significance assessed using Student\u0026rsquo;s t-test.\u003c/p\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eCellular Assays\u003c/h2\u003e\n \u003cp\u003eThe MTT Cell Proliferation and Cytotoxicity Assay Kit was used to detect cell viability. Cells were seeded in 96-well plates and incubated for 72 hours, followed by MTT treatment and absorbance measurement at 450 nm. For the wound healing assay, cells were scratched, and images were captured at 0 and 24 hours. Wound healing was quantified by calculating the average wound area from three measurements. The transwell migration assay was performed using the Costar transwell system (CLS3364; Corning), with stained cells observed under a microscope (\u0026times;4 magnification).\u003c/p\u003e\n \u003cp\u003eFor the wound healing assay, cancer cells were seeded in a 24-well plate and grown to confluence overnight. The next day, the monolayer was wounded with repeated scratches using a 200 \u0026micro;l pipette tip, and the media was changed to remove cell debris. Each wound was imaged at 0 hours and again after 24 hours. Wound healing was assessed by averaging three measurements of the wound areas.\u003c/p\u003e\n \u003cp\u003eA transwell migration assay was performed using the Costar transwell system (CLS3364; Corning). Briefly, cancer cells (2 \u0026times; 10\u003csup\u003e3\u003c/sup\u003e cells) were suspended in 200 \u0026micro;l serum-free medium and seeded in the upper insert chamber, with 500 \u0026micro;l medium added to the lower chamber. After 4 hours, media in both chambers were removed. Cells that migrated to the lower chamber through the 8-\u0026micro;m pore membrane were stained with crystal violet and visualized using a microscope (\u0026times;4 magnification).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eMice and Treatment\u003c/h2\u003e\n \u003cp\u003eFor tumor-bearing experiments, 5\u0026times;10\u003csup\u003e6\u003c/sup\u003e stably infected cancer cells were resuspended in sterile PBS (200 \u0026micro;L) and subcutaneously injected into one flank of 4-week-old female BALB/c-nude mice or C57BL/6 mice (n\u0026thinsp;=\u0026thinsp;6, per group). Mice were obtained from the Animal Center of the Chinese Academy of Science, and the Ethics Committee of Zhongshan Hospital approved all animal experiments. All protocols followed guidelines for the welfare of laboratory animals. Following cancer cell injection, tumor sizes on the flanks were measured biweekly using vernier calipers, and tumor volume was calculated using the formula: V=(L\u0026times;W2)/2. After 24 days, surgeries were performed under sodium pentobarbital anesthesia with minimized suffering, and tumor xenografts were harvested for ELISA analysis.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eELISA\u003c/h2\u003e\n \u003cp\u003eCells (2 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e/100 mm dish) were cultured for 24 hours. Then, the media were replaced with 10 ml of serum-free DMEM. Supernatants were collected 24 hours later, and any floating cells were removed by 0.45 \u0026micro;m filtration. The concentration of CCL2 protein in the supernatant was determined using a mouse-specific CCL2 ELISA kit (Abcam, Cat # ab206310). All experiments followed the manufacturer\u0026apos;s instructions.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003eStatistical Analysis\u003c/h2\u003e\n \u003cp\u003eData processing and statistical analyses were conducted using R software v3.6.1 (R Foundation for Statistical Computing, Vienna, Austria), GraphPad Prism v10.2.1 (Macintosh Version, GraphPad Software, California, USA), Strawberry Perl v.5.30.1.1, and SPSS v.25 (SPSS Inc.). Analysis of variance (ANOVA) or Student\u0026rsquo;s t-test was employed to assess significant differences in DIO1 mRNA levels among various subgroups. The chi-square test was used to analyze the correlation between DIO1 expression levels and clinicopathological parameters of STAD. Survival analyses were conducted using the Kaplan\u0026ndash;Meier method, and comparisons were made using the log-rank test. Univariate and multivariate survival analyses were performed using a Cox regression model. A P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant unless otherwise noted.\u003c/p\u003e\n \u003cp\u003eFor more information on the Material and Methods utilized in this research, please refer to Doc. S1 and Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e-S2.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e3.1 \u003cb\u003eDIO1 expression is upregulated in gastric cancer and is associated with poor prognosis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe mRNA expression levels of DIO1 in cancer and para-cancerous tissues were analyzed using the TCGA database \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. The results showed elevated DIO1 expression in BRAC, PRAD, and STAD cancer tissues compared to para-cancerous tissues. Specifically, in gastric cancer (GC), analysis of TCGA transcriptomic data (329 GC tissues and 210 para-cancerous tissues; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB) revealed significantly higher DIO1 expression in GC tissues (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAfterward, Kaplan-Meier curves and log-rank tests were conducted to compare the overall survival (OS) and progress-free interval (PFI) between DIO1 high- and low- expression subgroups. In both the TCGA and ACRG cohorts, higher DIO1 expression was associated with significantly worse OS (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.018 and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.017; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC-D, \u003cb\u003eleft panel\u003c/b\u003e) and PFI (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002 and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC-D, \u003cb\u003eright panel\u003c/b\u003e).\u003c/p\u003e\u003cp\u003eMultivariate Cox regression analysis incorporated clinicopathological parameters (age, gender, Lauren classification, tumor grade, TNM stage), ACT, and DIO1 expression. DIO1 expression independently predicted poor prognosis for OS (TCGA cohort: HR\u0026thinsp;=\u0026thinsp;1.51, 95% CI\u0026thinsp;=\u0026thinsp;1.07\u0026ndash;2.14, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.020; ACRG cohort: HR\u0026thinsp;=\u0026thinsp;1.81, 95% CI\u0026thinsp;=\u0026thinsp;1.20\u0026ndash;2.73, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE) and PFI (TCGA cohort: HR\u0026thinsp;=\u0026thinsp;1.66, 95% CI\u0026thinsp;=\u0026thinsp;1.16\u0026ndash;2.39, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006; ACRG cohort: HR\u0026thinsp;=\u0026thinsp;1.50, 95% CI\u0026thinsp;=\u0026thinsp;0.98\u0026ndash;2.30, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.065; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE).\u003c/p\u003e\u003cp\u003eTo further confirm our findings, IHC staining was performed on TMAs from the Zhongshan cohort \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF\u003cb\u003e)\u003c/b\u003e, revealing variable DIO1 expression among GC patients. Survival analysis in the Zhongshan cohort aligned with results from the TCGA and ACRG cohorts \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG\u003cb\u003e)\u003c/b\u003e. Collectively, these findings suggest that DIO1 expression may serve as an independent adverse prognostic marker for survival in GC.\u003c/p\u003e\u003cp\u003e3.2 \u003cb\u003eLevels of mRNA and protein expression of DIOs in gastric cancer\u003c/b\u003e\u003c/p\u003e\u003cp\u003eqRT-PCR analysis and Western blotting were conducted to confirm the expression of DIO1 in GC patients \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eH, I\u003cb\u003e)\u003c/b\u003e. The results revealed that the protein levels of DIO1 were significantly elevated in GC tissues compared to adjacent non-cancerous tissues. To further identify the role of DIO1 in various GC cell lines, qRT-PCR analysis and Western Blotting were performed \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eJ\u003cb\u003e)\u003c/b\u003e. The findings indicated that the HGC-27 GC cell line exhibited the highest levels of DIO1 expression, whereas the GES-1 cell line, MKN74 and AGS GC cell line showed low DIO1 expression.\u003c/p\u003e\u003cp\u003e3.3 \u003cb\u003eDIO1 promoted gastric cancer cell proliferation and metastasis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo explore the role of DIO1 in gastric mucosa tumorigenesis, we established a HGC-27 cell line with DIO1 knockdown using three independent shRNAs (sh1, sh2, sh3) and an AGS cell line with DIO1 overexpression. Knockdown and overexpression efficiencies were validated by qRT-PCR and WB \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, B\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eDIO1 knockdown inhibited HGC-27 cell proliferation, while DIO1 overexpression accelerated AGS cell growth, as shown by the MTT assay (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC, D). Similarly, colony-forming assays revealed fewer colonies in the DIO1 knockdown group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE) and more colonies in the DIO1 overexpression group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF). DIO1 knockdown significantly reduced the flattening and spreading of HGC-27 cells, while its overexpression enhanced these properties in AGS cells, as shown by the wound healing assay (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG, H). Similarly, the transwell assay demonstrated reduced invasiveness in DIO1 knockdown cells and increased invasion in DIO1-overexpressing cells (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eI, J).\u003c/p\u003e\u003cp\u003eEpithelial-mesenchymal transition (EMT), a process observed in various cancers, including GC, drives changes in cell migration and invasion \u003csup\u003e17\u003c/sup\u003e. Our findings suggest that DIO1 regulates EMT by modulating key markers such as E-cadherin, N-cadherin, Vimentin, Snail, and Twist. Specifically, DIO1 knockdown significantly upregulated E-cadherin in HGC-27 cells \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eK\u003cb\u003e)\u003c/b\u003e, while its overexpression in AGS cells increased N-cadherin, Vimentin, and Twist levels and reduced E-cadherin expression \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eL\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e3.4 \u003cb\u003eDIO1 promotes gastric cancer cell EMT process and proliferation through regulation of 3,3'-5-triiodothyronine expression\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe conversion of T4 to the active hormone 3,3'-5-triiodothyronine (T3) is mediated by the 5'-deiodinases DIO1 and DIO2\u003csup\u003e18\u003c/sup\u003e. Studies indicate that the DIO1 inhibitor PTU significantly lowers T3 levels, particularly in hyperthyroid patients compared to euthyroid individuals\u003csup\u003e19\u003c/sup\u003e. T3 has been increasingly recognized for its role in tumorigenesis \u003csup\u003e20\u003c/sup\u003e. Given the observed link between DIO1 and EMT, we hypothesized that DIO1 might promote EMT by upregulating T3. To test this, we measured T3 concentrations in the supernatant of GC cells. \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. DIO1 knockdown significantly reduced T3 levels in HGC-27 cells, while DIO1 overexpression increased T3 levels in AGS cells \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo determine whether DIO1 influences EMT through T3 regulation, we analyzed its EMT-related markers. Similar to DIO1-deficient HGC-27 cells, T3-deprived HGC-27 cells showed reduced N-cadherin, Vimentin, and Twist levels, with increased E-cadherin expression \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, \u003cb\u003eleft panel)\u003c/b\u003e. Conversely, AGS cells treated with additional T3 and overexpressing DIO1 exhibited elevated N-cadherin, Vimentin, and Twist levels and decreased E-cadherin expression \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, \u003cb\u003eright panel)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eTo evaluate the DIO1 function in vivo, we implanted HGC-27-DIO-KD, HGC-27-Mock, AGS-DIO-OE, and AGS-Mock cells subcutaneously into nude mice (5 \u0026times; 10^\u003csup\u003e6\u003c/sup\u003e cells per mouse, six mice per group). After five weeks, tumors in the HGC-27-DIO-KD group were significantly smaller than those in the HGC-27-Mock group \u003cb\u003e( as shown in the upper patr of Figuer 3C)\u003c/b\u003e. In contrast, tumors in the AGS-DIO-OE group were notably larger than those in the AGS-Mock group \u003cb\u003e(as shown in the lower part of\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e. Quantitative analysis confirmed these findings, with significant tumor volume reduction in the HGC-27-DIO1-KD group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and a marked increase in the AGS-DIO1-OE group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD\u003cb\u003e)\u003c/b\u003e. Thyroid hormone T3 levels in subcutaneous tumor tissues were also assessed \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE\u003cb\u003e)\u003c/b\u003e. Tumors from HGC-27-DIO1-KD mice showed significantly reduced T3 levels, while tumors from AGS-DIO1-OE mice exhibited increased T3 levels. These findings highlight DIO1\u0026rsquo;s role in promoting EMT by elevating T3 levels in the local tumor environment, thereby facilitating GC progression.\u003c/p\u003e\u003cp\u003e3.5 \u003cb\u003eDIO1 promotes gastric cancer cell EMT process and proliferation via WNT/β-catenin/Twist signaling pathway\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo investigate how DIO1 promotes EMT and GC cell proliferation, we analyzed EMT-related signaling pathways using the Cignal Finder Reporter Array and Western Blot. DIO1 knockdown significantly reduced WNT signaling activity in HGC-27 cells, while DIO1 overexpression enhanced it in AGS cells \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, B; \u003cb\u003eleft panel)\u003c/b\u003e. The WNT/β-catenin pathway, a key regulator in cancer progression\u003csup\u003e21\u003c/sup\u003e, was further assessed by examining the phosphorylation of β-catenin, AKT, ERK, and SMAD3. Notably, β-catenin expression decreased in HGC-27 cells with DIO1 knockdown but increased in AGS cells with DIO1 overexpression \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, B; \u003cb\u003eright panel)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003ePrevious studies revealed that TR-α1 (thyroid hormone receptor T3) overexpression stabilizes β-catenin and promotes carcinoma development\u003csup\u003e22\u0026ndash;24\u003c/sup\u003e. We hypothesize that T3 activates β-catenin via TR-α1. Supporting this, TR-α1 knockdown reduced β-catenin activity in AGS cells with DIO1 overexpression \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eGiven Twist\u0026rsquo;s role in EMT and cell migration\u003csup\u003e25\u003c/sup\u003e, we examined the influence of β-catenin on Twist using a β-catenin agonist in DIO1-knockdown HGC-27 cells and a β-catenin inhibitor in DIO1-overexpressing AGS cells \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eThe β-catenin agonist (SKL2001) increased N-cadherin, Vimentin, and Twist expression while reducing E-cadherin levels \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD, \u003cb\u003eleft panel)\u003c/b\u003e, thereby promoting cell growth in HGC-27 cells, effects counteracted by Twist knockdown \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE\u003cb\u003e)\u003c/b\u003e. Conversely, the β-catenin inhibitor (WIKI-4) reduced N-cadherin, Vimentin, and Twist expression while increasing E-cadherin levels \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD, \u003cb\u003eright panel)\u003c/b\u003e, suppressing AGS cell proliferation. These effects were reversed by Twist overexpression \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eTranswell migration assays showed that DIO1 knockdown reduced HGC-27 cell migration, an effect reversed by the β-catenin agonist SKL2001 or Twist overexpression \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eG\u003cb\u003e)\u003c/b\u003e. Conversely, DIO1 overexpression enhanced AGS cell migration, which was suppressed by the β-catenin inhibitor WIKI-4 or Twist knockdown \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eH\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eIn summary, DIO1 promotes GC cell proliferation and migration via the WNT/β-catenin/Twist axis, highlighting its potential as a therapeutic target in GC.\u003c/p\u003e\u003cp\u003e3.6 \u003cb\u003eDIO1 upregulates β-Catenin activity to enhance CCL2 production and TAM chemotaxis in Gastric Cancer\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTumor-infiltrating immune cells are key components of the TME and play critical roles in tumor progression\u003csup\u003e26, 27\u003c/sup\u003e. We assessed the relationship between DIO1 expression and immune infiltration in GC, finding that DIO1 mRNA levels positively correlated with CD4\u0026thinsp;+\u0026thinsp;T cells, CD8\u0026thinsp;+\u0026thinsp;T cells, neutrophils, macrophages, and myeloid dendritic cells \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo investigate DIO1's role in immune cell infiltration in vivo, YTN16-DIO-KD and YTN16-Mock cells were implanted into NGS and C57BL/6 mice (5 \u0026times; 10^6 cells per mouse, six mice per group). At five weeks, tumor volumes were significantly smaller in both NGS-YTN16-DIO1-KD and C57BL/6-YTN16-DIO1-KD groups compared to their respective controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Notably, tumors in immunocompetent C57BL/6 mice with DIO1 knockdown were smaller than those in NGS mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC, P\u0026thinsp;=\u0026thinsp;0.007), indicating that immune activation in immunocompetent mice may suppress tumor growth.\u003c/p\u003e\u003cp\u003eTumor-associated macrophages (TAMs) infiltrate the TME and exert immunosuppressive effects\u003csup\u003e27, 28\u003c/sup\u003e. IHC confirmed that TAMs were significantly enriched in C57BL/6-YTN16 tumors with mock controls compared to those with DIO1 knockdown \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. Transwell assays showed that DIO1 knockdown reduced macrophage migration in HGC-27 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while DIO1 overexpression increased migration in AGS cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003eChemokines regulate immune cell localization and function in the TME\u003csup\u003e29, 30\u003c/sup\u003e. To explore how DIO1 promotes TAM infiltration, we measured chemokine levels in GC cell supernatants. CCL2 levels were significantly reduced in DIO1-deficient HGC-27 cells and elevated in DIO1-overexpressing AGS cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). As CCL2 is crucial for TAM recruitment\u003csup\u003e31, 32\u003c/sup\u003e, Transwell assays confirmed its role in DIO1-mediated TAM infiltration. Overexpression of CCL2 increased macrophage migration in HGC-27-DIO-KD cells \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF, \u003cb\u003eabove panel)\u003c/b\u003e, while CCL2 knockdown reduced macrophage migration in AGS-DIO-OE cells \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF, \u003cb\u003ebelow panel)\u003c/b\u003e. These results suggest that DIO1 promotes TAM recruitment by upregulating CCL2.\u003c/p\u003e\u003cp\u003eRecent studies showed that the WNT/β-catenin pathway influences immune cell recruitment in the TME\u003csup\u003e33\u003c/sup\u003e. To determine its role in the DIO1/CCL2/TAM axis, we tested the effect of β-catenin modulation. The β-catenin agonist (SKL2001) increased macrophage migration and CCL2 levels in HGC-27-DIO-KD cells \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH, \u003cb\u003eabove panel;\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG, \u003cb\u003eleft panel)\u003c/b\u003e, while β-catenin inhibition reduced macrophage migration and CCL2 levels in AGS-DIO1-OE cells \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH, \u003cb\u003ebelow panel;\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG, \u003cb\u003eRight panel)\u003c/b\u003e. Interestingly, Twist knockdown did not affect macrophage migration, indicating that Twist is not involved in this pathway \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG-H\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eIn summary, these findings indicate that DIO1 enhances CCL2 production by upregulating β-catenin activity, thereby facilitating the chemotactic movement of TAMs in GC cells.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study uncovered that DIO1, overexpressed in GC, acts as a novel oncogenic gene promoting tumor proliferation and invasion. Intriguingly, DIO1 not only induces EMT in GC cells but also correlates with immune responses. Mechanistically, DIO1 functions as a critical oncogene in GC by upregulating β-catenin, which subsequently increases Twist expression, CCL2 secretion, and TAM infiltration, thereby promoting the EMT pathway.\u003c/p\u003e\u003cp\u003eDIO1, a deiodinase essential for triiodothyronine (T3) synthesis, regulates thyroid hormone homeostasis and cellular processes such as differentiation, proliferation, and apoptosis.\u003c/p\u003e\u003cp\u003eWhile previous studies reported that DIO1 silencing enhances renal cancer cell proliferation and migration\u003csup\u003e34\u003c/sup\u003e, our findings reveal that DIO1 is highly expressed in GC tissues, promoting tumor proliferation, migration, and invasion. Overexpression of DIO1 significantly increases T3 levels, underscoring molecular differences between gastric adenocarcinoma and clear-cell renal cell carcinoma.\u003c/p\u003e\u003cp\u003eEMT, characterized by a loss of epithelial features\u003csup\u003e8\u003c/sup\u003e (e.g., E-cadherin downregulation) and gain of mesenchymal traits (e.g., vimentin and N-cadherin upregulation)\u003csup\u003e35, 36\u003c/sup\u003e, drives tumor progression, metastasis, and therapy resistance\u003csup\u003e37, 38\u003c/sup\u003e. Our gain- and loss-of-function studies demonstrated that DIO1 overexpression induces EMT via Twist, while DIO1 knockdown reverses these changes. This is the first study to establish the pivotal role of DIO1 in EMT and GC progression.\u003c/p\u003e\u003cp\u003eWe investigated the molecular mechanisms of DIO1 in EMT and GC progression. Reporter assays revealed that DIO1 modulation significantly impacts the WNT/β-catenin pathway. Rescue experiments further confirmed the critical role of this pathway in DIO1-induced EMT.\u003c/p\u003e\u003cp\u003eTAMs play critical roles in the tumor microenvironment (TME), influencing immune suppression and resistance to immunotherapy\u003csup\u003e39\u003c/sup\u003e. Activation of the WNT/β-catenin pathway promotes TAM recruitment and shifts their phenotype from tumor-inhibiting M1-like to tumor-promoting M2-like\u003csup\u003e40\u003c/sup\u003e. Aberrant WNT/β-catenin activation in cancer cells further drives EMT and modulates immune responses in the TME\u003csup\u003e41\u003c/sup\u003e. We validated the associations between DIO1 and the immune microenvironment via the TCGA cohort. Furthermore, under the guidance of Professor Sachiyo Nomura, we were gifted with an innovative gastric adenocarcinoma cell line derived from mice\u003csup\u003e16\u003c/sup\u003e. This development has made it possible to conduct in vivo experiments using immunocompetent GC mouse models. Our vivo experiment showed a significant decrease in TAMs in mice with DIO1 knockdown. Chemotactic experiments revealed that TAM chemotaxis decreased with DIO1 depletion and reversed with DIO1 overexpression. We demonstrated that β-catenin directly interacts with CCL2, promoting TAM recruitment in a CCL2-dependent manner. Before our research, few studies reported the relationship between DIO1 and β-catenin in EMT and TAMs. Therefore, our research indicates a novel potential target for immunotherapy in gastric cancer.\u003c/p\u003e\u003cp\u003eThere are several limitations to this study. First, the upstream signaling responsible for DIO1 overexpression in GC requires further exploration. Second, the relationship between GC and thyroid disease needs validation in larger cohorts. Third, additional experiments are necessary in order to investigate how DIO1 influences the TME systematically.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, this study identifies DIO1 as an oncogene that promotes GC progression through enhanced EMT and TAM infiltration. These findings suggest DIO1 as a potential prognostic marker and therapeutic target for GC.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e1. DIO1\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDeiodinase 1\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e2. GC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eGastric Cancer\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e3. EMT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEpithelial-Mesenchymal Transition\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e4. TAM\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTumor-Associated Macrophages\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e5. TCGA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eThe Cancer Genome Atlas\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e6. ACRG\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAsian Cancer Research Group\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e7. TME\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTumor Microenvironment\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e8. IHC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eImmunohistochemistry\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e9. RT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePCR-Reverse-Transcription Polymerase Chain Reaction\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e10. qRT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePCR-Quantitative Reverse Transcription Polymerase Chain Reaction\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e11. TMA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTissue Microarray\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e12. FBS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eFetal Bovine Serum\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e13. PBS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePhosphate Buffered Saline\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e14. MTT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMethylthiazolyldiphenyl-tetrazolium bromide (Cell Proliferation Assay)\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e15. ELISA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEnzyme-Linked Immunosorbent Assay\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e16. ANOVA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAnalysis of Variance\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e17. OS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eOverall Survival\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e18. PFI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eProgression-Free Interval\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e19. HR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHazard Ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e20. CI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eConfidence Interval\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e21. STAD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eStomach Adenocarcinoma\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e22. T3\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTriiodothyronine (3,3'-5-triiodothyronine)\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e23. T4\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eThyroxine (Tetraiodothyronine)\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e24. PTU\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePropylthiouracil\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e25. TR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eα1-Thyroid Hormone Receptor Alpha-1\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e26. MDSCs\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMyeloid-Derived Suppressor Cells\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e27. Treg\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eRegulatory T Cells\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e28. SKL2001\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eβ-catenin Agonist\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e29. WIKI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003e4-β-catenin Inhibitor\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eConflict of Interest:\u003c/h2\u003e\u003cp\u003eThere are no conflicts of interest for the authors.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eEthics declarations\u003c/h2\u003e\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u003cp\u003e Approval of the research protocol by an Institutional Reviewer Board: Approval granted by the Ethics Committee of Zhongshan Hospital, Fudan University (No.B2024-261)\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eConsent for publication:\u003c/h2\u003e\u003cp\u003eNot Applicable\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding Information\u003c/h2\u003e\u003cp\u003e This study was funded by grants from the National Natural Science Foundation of China (82372792), the Natural Science Foundation of Xiamen (3502Z20227276), Xiamen Science and Technology Plan Project (3502Z20209060), Medical and Health Guided Project of Xiamen (3502220214201076).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eXL conducted the research and performed statistical analysis.KY and ZS conducted the research, interpreted the results, and drafted the manuscript.QS conducted pathological analysis.Masami Yamamoto, Tetsuya Tsukamoto and Sachiyo Nomura donor cell lines.XW, BC, and YC proposed concepts, designed the study, interpreted results, reviewed the manuscript, secured funding, and supervised the study.\u003c/p\u003e\u003ch2\u003eAcknowledgements:\u003c/h2\u003e\u003cp\u003eThe authors thank Prof. Yihong Sun and Prof. Kuntang Shen (Gastric Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China) for their invaluable suggestions and assistance with specimen collection.\u003c/p\u003e\u003cp\u003eWe also thank Prof. Hailong Wu (Shanghai University of Medicine \u0026amp; Health Sciences, Shanghai, China) for his assistance in obtaining the YTN16 cell line.\u003c/p\u003e\u003cp\u003eThe authors thank Prof. Yingyong Hou, Dr. Xiaolei Zhang, and Dr. Xinxin Guo (Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China) for their excellent pathological technology support.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSung H, Ferlay J, Siegel RL, et al. 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Therapeutic implications of cancer epithelial-mesenchymal transition (EMT). \u003cem\u003eArch Pharm Res\u003c/em\u003e. 2019; 42: 14–24.\u003c/li\u003e\n\u003cli\u003eAshrafizadeh M, Dai J, Torabian P, et al. Circular RNAs in EMT-driven metastasis regulation: modulation of cancer cell plasticity, tumorigenesis and therapy resistance. \u003cem\u003eCell Mol Life Sci\u003c/em\u003e. 2024; 81: 214.\u003c/li\u003e\n\u003cli\u003eWang Y, Johnson KCC, Gatti-Mays ME, Li Z. Emerging strategies in targeting tumor-resident myeloid cells for cancer immunotherapy. \u003cem\u003eJ Hematol Oncol\u003c/em\u003e. 2022; 15: 118.\u003c/li\u003e\n\u003cli\u003eSarode P, Zheng X, Giotopoulou GA, et al. Reprogramming of tumor-associated macrophages by targeting β-catenin/FOSL2/ARID5A signaling: A potential treatment of lung cancer. \u003cem\u003eSci Adv\u003c/em\u003e. 2020; 6: eaaz6105.\u003c/li\u003e\n\u003cli\u003eWang K, Qiu X, Zhao Y, Wang H, Chen L. The Wnt/β-catenin signaling pathway in the tumor microenvironment of hepatocellular carcinoma. \u003cem\u003eCancer Biol Med\u003c/em\u003e. 2021; 19: 305–318.\u003c/li\u003e\n\u003c/ol\u003e"}],"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":"DIO1, Gastric carcinoma, EMT, TAM, poor prognosis","lastPublishedDoi":"10.21203/rs.3.rs-7563912/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7563912/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGastric cancer (GC) remains a prevalent and lethal malignancy, with high rates of invasion and metastasis. Deiodinase 1 (DIO1) demonstrates the potential for tumor proliferation and invasion across various cancers, including GC. Herein, we aimed to investigate the role of DIO1 in tumor progression and its clinical significance in GC. In this study, we included 135 tumor microarray specimens from GC patients at Zhongshan Hospital, 329 GC patients from the \u003cem\u003eCancer Genome Atlas\u003c/em\u003e, and 300 GC patients from the \u003cem\u003eAsian Cancer Research Group\u003c/em\u003e. Analysis of these three independent cohorts revealed that elevated DIO1 levels function as an independent adverse prognostic factor in GC. In vitro and in vivo studies manifested that DIO1 promotes GC cell proliferation, migration, and epithelial-mesenchymal transition (EMT) through the WNT/β-catenin/Twist axis. Furthermore, DIO1 enhances CCL2 production, facilitating tumor-associated macrophage (TAM) chemotaxis. Functional assays confirmed that DIO1 knockdown suppresses GC progression while its overexpression exacerbates it. In conclusion, our findings indicated that DIO1 is a pivotal oncogene in GC, serving as a potential inferior prognostic marker and a promising therapeutic target for improving GC treatment outcomes.\u003c/p\u003e","manuscriptTitle":"Overexpression of DIO1 is related to poor prognosis through regulating EMT and TAM infiltration in gastric carcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-22 06:31:27","doi":"10.21203/rs.3.rs-7563912/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":"f0b42e80-9b2b-4861-be4b-9c2b02e1f30d","owner":[],"postedDate":"September 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-22T06:31:29+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-22 06:31:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7563912","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7563912","identity":"rs-7563912","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}