Clinical significance of the S204 phosphorylation of the Smad3 protein in combination with Ki67 for the metastasis and prognosis of gastric cancer

Clinical significance of the S204 phosphorylation of the Smad3 protein in combination with Ki67 for the metastasis and prognosis of gastric cancer | 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 Clinical significance of the S204 phosphorylation of the Smad3 protein in combination with Ki67 for the metastasis and prognosis of gastric cancer Yi-Hui Kang, Ren-Sheng Chen, Qing Hu, Hong-Tao Sun, Pei Guo, Shi-Lin Lv, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7284849/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 Dec, 2025 Read the published version in BMC Gastroenterology → Version 1 posted 10 You are reading this latest preprint version Abstract AIM The purpose of this study is to explore the prognostic evaluation value of Ki67 and pSmad3L (S204) for gastric cancer patients by jointly analyzing their expression levels in gastric cancer tissues. Methods This single-center observational study enrolled 98 patients with pathologically confirmed gastric cancer, collecting 82 paired samples of tumor and adjacent normal tissues. Immunohistochemistry was utilized to detect the expression levels of CD133, E-cad, Ki67, and pSmad3L (S204). Pearson correlation coefficients were calculated to assess inter-protein relationships, while chi-square tests evaluated associations with clinicopathological parameters. Kaplan-Meier analysis generated survival curves, and univariate and multivariate COX regression analyses were conducted to establish a prognostic prediction model. Results Compared with adjacent normal tissues, the expressions of CD133, E-cad, and Ki67 were upregulated in gastric cancer tissues. The high expression of CD133 was associated with the tumor type, and the high expression of Ki67 was related to tumor grading and distant metastasis. Multivariate analysis showed that the depth of invasion, lymph node metastasis, Ki67, and pSmad3L (S204) were independent prognostic risk factors for GC patients. The co-high expression of Ki67 and pSmad3L (S204) predicted a poor prognosis. Conclusion High expression of Ki67 and high expression of pSmad3L(S204) are independent risk factors for the prognosis of patients with gastric cancer, and the combined analysis of Ki67 and pSmad3L(S204) can help to improve the risk prediction. Gastric cancer CD133 E-cad Ki67 pSmad3L(S204) prognosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction Cancer remains a major public health problem worldwide, with nearly 20 million new cancer cases and nearly 9.7 million cancer deaths expected in 2022, according to the latest report from the International Agency for Research on Cancer (IARC). Among these, gastric cancer ranks fifth among common malignancies in terms of both incidence (4.9%) and mortality (6.8%)[ 1 ]. Although the mortality rate of gastric cancer has shown a decreasing trend in recent years, it is still higher than that in developed countries such as the United Kingdom and the United States, which is mainly related to its low rate of early diagnosis and the lack of uniformity in clinical cancer diagnosis and treatment strategies[ 2 ]. Gastric cancer is now mainly treated with systemic chemotherapy, radiotherapy, surgery, targeted and immunotherapy and other integrated treatments[ 3 ]. Early symptoms of gastric cancer are insidious and progress rapidly, and the best time for surgical treatment is usually missed when it is first diagnosed[ 4 ]. Although systemic chemotherapy can improve the quality and prolong the survival time of gastric cancer patients, the clinical benefit is still very limited[ 5 ]. Patients with advanced gastric cancer have a very poor prognosis due to the difficulty of screening for targeted drugs and multidrug resistance[ 6 ]. Therefore, the search for molecular markers that can diagnose gastric cancer at an early stage and predict the prognosis of gastric cancer patients is of great importance in realizing new therapeutic targets and improving prognosis. The gene encoding Ki67, which is located on human chromosome 10 (10q25-qter) and consists of 15 exons, is a widely used marker of cell proliferation[ 7 , 8 ]. Several clinical studies have confirmed that in pancreatic neuroendocrine tumors, dynamic elevation of the Ki67 proliferation index is significantly associated with increased tumor aggressiveness and poor patient prognosis, suggesting that the Ki67 index can be used as an important biological indicator to assess the progression and prognosis of pancreatic neuroendocrine tumors[ 9 ]. In uterine smooth muscle sarcoma (uLMS), quantitatively elevated Ki67 proliferation index was significantly and positively correlated with an increased risk of death in patients, in which a Ki67 index ≥ 10% was identified as an independent poor prognostic factor in uLMS, providing an important quantitative indicator for clinical prognostic assessment[ 10 ].Although the role of Ki67 has been extensively studied in a variety of tumors, its prognostic value in gastric cancer (GC) has not been fully elucidated. Samd3 is an important transcriptional regulator in the TGF-β signaling pathway and is a member of the SAMD protein family. In the classical TGF-β/SAMD3 pathway, phosphorylated SAMD2/3 and SAMD4 form a transcriptional complex that translocates to the nucleus and participates in the transcriptional regulation of several target genes[ 11 ]. It was shown that in lung epithelial cells, SAMD3 and ATOH8 interact to form a transcriptional complex capable of directly repressing the expression of key genes associated with cell cycle progression. This molecular mechanism not only accelerated the senescence process of lung epithelial cells, but also further promoted the transformation of senescent cells to a malignant phenotype[ 12 ]. In addition, single nucleotide polymorphisms (SNPs) in the SMAD3 gene were significantly associated with the prognosis of patients with lung adenocarcinoma (LUAD) treated with gefitinib, which may serve as an important molecular marker for predicting treatment response and survival[ 13 ]. In cervical cancer, phosphorylation of SAMD3 has been shown to significantly increase the transcriptional activity of the FOXP3 gene, which in turn induces the expansion of regulatory T lymphocytes. This process is closely associated with immune escape from cervical cancer and the immunosuppressive state of the tumor microenvironment, which ultimately leads to poor patient prognosis[ 14 ]. However, the relationship between Samd3 and Ki67 is not well understood. In summary, Smad3 protein, as a key regulator of the TGF-β signaling pathway, plays an important role in tumorigenesis and development by phosphorylation at its S204 site. Meanwhile, Ki67, as a marker of cell proliferation, has been widely used in the prognostic assessment of various malignant tumors. However, the co-expression of Smad3 S204 phosphorylation and Ki67 in gastric cancer and its effect on tumor metastasis and prognosis have not been fully investigated. Therefore, the aim of this study was to investigate the expression characteristics of Smad3 S204 phosphorylation and Ki67 in gastric cancer tissues, to analyze their correlation with clinicopathological parameters and prognosis, and to explore the potential value of co-expression of pSmad3 (S204) and Ki67 in gastric cancer metastasis and prognosis. 2. Methods and materials 2.1Patients and specimens Patients and specimens The microarrays were obtained from Shanghai Outdo Biotech Company, the diagnosis of the microarray samples was determined according to AJCC criteria[ 15 ], the histological grading of the tumors followed the WHO guidelines for classification of tumors of the gastrointestinal system[ 16 ], including 98 cases of cancerous and paraneoplastic tissues, and the use of the samples was approved by the Ethics Committee of Shanghai Outdo Biotech Company (Shanghai, China) (NO.: SHYJS-CP-1801009). IHC Immunohistochemical (IHC) staining experiments were performed as previously described[ 17 ]. Specifically, paraffin-embedded tissue sections (4 µm in thickness) were deparaffinized and fully hydrated, followed by antigenic repair by thermal induction in citrate buffer (pH 6.0) to ensure adequate exposure of antigenic epitopes. Subsequently, endogenous peroxidase activity was blocked using H₂O₂ to eliminate background interference. Next, the tissue sections were incubated overnight at 4°C with the following primary antibodies: anti- CD133(item number 18470-1-AP), anti-Ki67 (item number GM724007), anti- E-cad ((item number PA073), anti-PSMAD3L (S204) (item number 2816414), respectively. The next day, the sections were washed three times with phosphate buffer solution (PBS) to remove unbound primary antibodies. The sections were then incubated with anti-rabbit HRP-conjugated IgG secondary antibody (Zsbio, China) for 1 hour at 37°C to ensure specific binding. Meanwhile, sections treated with PBS alone were used as a negative control to exclude non-specific staining. At the end of the incubation, the sections were washed again with PBS and incubated with peroxidase substrate (Zsbio, China) for 20 minutes at 37°C to develop the color reaction. Finally, the nuclei were restained with hematoxylin to enhance the visualization of nuclear structures. After completion of staining, the sections were dehydrated and coverslipped for long-term storage and microscopic observation. Staining results were independently assessed by two pathologists who were unaware of the background of the study, based on the German semi-quantitative scoring method[ 18 ]. The scoring criteria took into account the overall intensity of the staining as well as the percentage of positively stained cells as an objective reflection of the expression level of the target proteins. The overall staining intensity was graded into four levels: no staining (0 points), light yellow staining (1 point), yellow staining (2 points), and dark yellow/brown staining (3 points). The percentage of positive staining was then defined as the proportion of positively stained glandular epithelial cells in the tissue on the slide and scored on the following scale: 75% (4 points). By combining the total staining intensity score with the positive staining percentage score, protein expression levels were further characterized as: negative (0–2 points), + (3–5 points), ++ (6–8 points), and +++ (9–12 points). Finally, all tissue samples were categorized into low expression groups (- or +) and high expression groups ( + + or ++++) based on the scoring results[ 17 ]. 2.2Statistical analysis Data were analyzed using SPSS 26.0 and R language (4.4.0). Measurement data were assessed for normality by the Kolmogorov-Smirnov test; normally distributed data were expressed as mean ± standard deviation (Mean ± SD), and comparisons between groups were made using the independent samples t-test; non-normally distributed data were expressed as median and interquartile range (Median [IQR]), and comparisons between groups were made using the Mann-Whitney U test. Categorical data were expressed as frequencies and percentages (n [%]), and the chi-square test was used for comparisons between groups. Survival analysis was performed by the Kaplan-Meier method, and Log-rank test was used for between-group comparisons. Clinical prediction models were constructed by screening variables with P < 0.01 by one-way Cox regression, and further by screening independent prognostic factors with P < 0.05 by multifactorial Cox regression, and forest plots were plotted using the “forestplot” package, and column line plots were plotted using the “rms” package. The “forestplot” package was used to draw forest plots, and the “rms” package was used to draw column plots. The “pROC” package was used to draw the ROC curve and calculate the AUC to assess the differentiation, the “rms” package was used to draw the calibration curve to assess the calibration degree, and the “rmda” package was used to draw the decision curve to analyze the clinical utility of the model. The “rms” package plotted calibration curves to assess calibration, and the “rmda” package plotted decision curves to analyze and assess clinical utility. p < 0.05 was considered a statistically significant difference. 3.Results 3.1 Clinical data: Among 98 patients with gastric cancer, 36 cases (36.7%) were female and 62 cases (63.3%) were male; 33 cases (33.7%) were < 60 years old and 65 cases (66.3%) were ≥ 60 years old; according to the WHO staging, among them, there were 8 cases (8.2%) of mucinous adenocarcinoma, 54 cases (55.1%) of adenocarcinoma, 19 cases (19.4%) of tubular adenocarcinoma, 12 cases (12.2%) of undifferentiated There were 12 cases (12.2%) of undifferentiated adenocarcinoma, 5 cases (5.1%) of indolent cell carcinoma; according to TNM staging, there were 14 cases (14.3%) of Stage II, 72 cases (73.5%) of Stage III, and 12 cases (12.2%) of Stage IV; the maximum diameter of the tumor was ≤ 5cm in 61 cases (62.2), and > 5cm in 37 cases (37.8%); the depth of invasion of T1 was in 6 cases (6.1%), and the depth of T2 was in 9 cases (9.2%), and the depth of invasion of T2 was in 6 cases (6.1%) and 9 cases (9.2%), respectively. There were 6 cases (6.1%) in T1, 9 cases (9.2%) in T2, 64 cases (65.3%) in T3, and 19 cases (19.4%) in T4; there were 21 cases (21.4%) of lymph node metastasis in N0, 16 cases (16.3%) in N1, 26 cases (26.5%) in N2, and 35 cases (35.7%) in N3; and 89 cases (90.8%) had distant metastasis, as shown in Table 1 . Table 1 Clinical baseline table of patients with gastric cancer [cases (%)] Variable levels Overall Gender, n(%) Females 36 (36.7%) Male 62 (63.3%) Age, n(%) ≤ 60 33 (33.7%) >60 65 (66.3%) Tumor type, n(%) Mucinous Adenocarcinoma 8 (8.2%) Adenocarcinoma 54 (55.1%) Tubular Adenocarcinoma 19 (19.4%) Undifferentiated Carcinoma 12 (12.2%) Signet ring cell carcinoma 5 (5.1%) Pathological grade, n(%) Ⅱ 14 (14.3%) Ⅲ 72 (73.5%) Ⅳ 12 (12.2%) Tumor size, n(%) ≤ 5cm 61 (62.2%) >5cm 37 (37.8%) T Stage, n(%) T1 6 (6.1%) T2 9 (9.2%) T3 64 (65.3%) T4 19 (19.4%) N Stage, n(%) N0 21 (21.4%) N1 16 (16.3%) N2 26 (26.5%) N3 35 (35.7%) Metastasis, n(%) M0 89 (90.8%) M1 9 (9.2%) AJCC Stage, n(%) Ⅰ 9 (9.2%) Ⅱ 31 (31.6%) Ⅲ 49 (50.0%) Ⅳ 9 (9.2%) 3.2 Comparison of the expression of CD133, E-cad, Ki67, pSmad3L (S204) proteins in gastric cancer tissues and normal tissues adjacent to the cancer : In order to investigate the roles of CD133, E-cad, Ki67, and pSmad3L (S204) in the metastasis and progression of gastric cancer, in this study, the expression of the above indexes was detected in 98 cases of gastric cancer tissues and 82 cases of matched normal tissues adjacent to the cancer through immunohistochemical staining method, and 82 matched paracancerous normal tissues, as shown Fig. 1 . The high expression rates of CD133 (56.1% (55/98)), E-cad (66.3% (65/98)) and Ki67 (64.3% (63/98)) in gastric cancer tissues were significantly higher than those in normal tissues adjacent to the cancer (13.4% (11/82), 26.9% (22/82), 7.3% (6/82)) and the differences were statistically significant (all P < 0.05). The high expression rate of pSmad3L (S204) was 31.7 (31/98), which was significantly lower than that of normal tissues next to cancer (79.3% (65/82)), and the difference was statistically significant (P < 0.001), as shown in Table 2 . Table 2 CD133, E-cad, Ki67, pSmad3L (S204) protein expression in gastric cancer and normal gastric tissues adjacent to the cancer [cases (%)] CD133 P value Ecad P value Ki67 P value pSmad3L(S204) P value Tumor Ad-tissue Tumor Ad-tissue Tumor Ad-tissue Tumor Ad-tissue - 2(2.0) 20(24.4) < 0.001 10(10.2) 1(1.2) < 0.001 1(1.0) 23(28.0) < 0.001 12(12.2) 4(4.9) < 0.001 + 41(41.8) 51(62.2) 23(23.5) 59(72.0) 34(34.7) 53(64.6) 55(56.1) 13(15.9) ++ 46(47.0) 11(13.4) 35(35.7) 19(23.2) 31(31.6) 5(6.1) 23(23.5) 30(36.6) +++ 9(9.2) 0(0) 30(30.6) 3(3.70) 32(32.7) 1(1.2) 8(8.2) 35(42.7) 3.3 Relationship between the expression of CD133, E-cad, Ki67, pSmad3L (S204) in gastric cancer tissues and the clinicopathological features of patients : In order to investigate the effects of the expression of Ki67 and pSmad3L (S204) and their downstream molecules on the metastasis and progression of gastric cancer, we analyzed the expression levels of CD133, E-cad, Ki67, pSmad3L (S204) and their downstream molecules in gastric cancer tissues of 98 cases of gastric cancer by means of chi-square test and Fisher exact probability. We analyzed the relationship between the expression levels of CD133, E-cad, Ki67, pSmad3L (S204) and the clinicopathological features of gastric cancer patients by chi-square test and Fisher's exact probability method. The results of the correlation of clinicopathological features showed that the high expression of CD133 was correlated with tumor type (P = 0.044); the high expression of Ki67 was correlated with tumor grade (P = 0.043) and distant metastasis (P = 0.007); and the differences of the expression of E-cad and pSmad3L (S204) in different clinicopathological features were not statistically significant, as shown in Table 3 . Table 3 Relationship between the protein expression levels of CD133, E-cad, Ki67, pSmad3L (S204) and clinicopathologic features of gastric cancer patients [cases (%)] Clinicopathological factors CD133 Ecad Ki67 pSmad3L(S204) precedent Low n(%) High n(%) P value Low n(%) High n(%) P value Low n(%) High n(%) P value Low n(%) High n(%) P value Gender Female 36 16(44.4%) 20(55.6%) 0.928 13(36.1%) 23(63.9%) 0.708 10(27.8%) 26(72.2%) 0.262 22(61.1%) 14(38.9%) 0.352 Male 62 27(43.5%) 35(56.5%) 20(32.3%) 42(67.7%) 25(40.3%) 37(59.7%) 45(72.6%) 17(27.4%) Age <60 33 13(39.4%) 20(60.6%) 0.727 12(36.4%) 21(63.6%) 0.945 14(42.4%) 19(57.6%) 0.138 22(66.7%) 11(33.3%) 0.775 ≥ 60 65 30(46.2%) 35(53.8%) 21(32.3%) 44(67.7%) 21(32.3%) 44(67.7%) 45(69.2%) 20(30.8%) Tumor type Mucinous Adenocarcinoma 8 6(75.0%) 2(25.0%) 0.044 3(37.5%) 5(62.5%) 0.55 4(50.0%) 4(50.0%) 0.229 8(100.0%) 0(0.0%) 0.082 Adenocarcinoma 54 18(33.3%) 36(66.7%) 16(29.6%) 38(70.4%) 17(31.5%) 37(68.5%) 36(66.7%) 18(33.3%) Tubular Adenocarcinoma 19 11(57.9%) 8(42.1%) 5(26.3%) 14(73.7%) 7(36.8%) 12(63.2%) 12(63.2%) 7(36.8%) Undifferentiated Carcinoma 12 7(58.3%) 5(41.7%) 5(41.7%) 7(58.3%) 4(33.3%) 8(66.7%) 8(66.7%) 4(33.3%) Signet ring cell carcinoma 5 1(20.0%) 4(80.0%) 4(80.0%) 1(20.0%) 3(60.0%) 2(40.0%) 3(60.0%) 2(40.0%) Pathological grade Ⅱ 14 8(57.1%) 6(42.9%) 0.11 5(35.7%) 9(64.3%) 0.654 4(28.6%) 10(71.4%) 0.043 9(64.3%) 5(35.7%) 0.624 Ⅲ 72 28(38.9%) 44(61.1%) 23(31.9%) 49(68.1%) 27(37.5%) 45(62.5%) 50(69.4%) 22(30.6%) Ⅳ 12 7(58.3%) 5(41.7%) 5(41.7%) 7(58.3%) 4(33.3%) 8(66.7%) 8(66.7%) 4(33.3%) Tumor size ≤ 5cm 61 26(42.6%) 35(57.4%) 0.596 21(34.4%) 40(65.6%) 0.978 21(34.4%) 40(65.6%) 0.198 46(75.4%) 15(24.6%) 0.117 >5cm 37 17(45.9%) 20(54.1%) 12(32.4%) 25(67.6%) 14(37.8%) 23(62.2%) 21(56.8%) 16(43.2%) T Stage T1 6 4(66.7%) 2(33.3%) 0.234 1(16.7%) 5(83.3%) 0.87 4(66.7%) 2(33.3%) 0.683 4(66.7%) 2(33.3%) 0.852 T2 9 7(77.8%) 2(22.2%) 3(33.3%) 6(66.7%) 4(44.4%) 5(55.6%) 6(66.7%) 3(33.3%) T3 64 28(43.8%) 36(56.3%) 21(32.8%) 43(67.2%) 20(31.3%) 44(68.8%) 45(70.3%) 19(29.7%) T4 19 4(21.1%) 15(78.9%) 8(42.1%) 11(57.9%) 7(36.8%) 12(63.2%) 12(63.2%) 7(36.8%) N Stage N0 21 11(52.4%) 10(47.6%) 0.836 9(42.9%) 12(57.1%) 0.298 9(42.9%) 12(57.1%) 0.807 17(81.0%) 4(19.0%) 0.475 N1 16 5(31.3%) 11(68.8%) 5(31.3%) 11(68.8%) 7(43.8%) 9(56.3%) 13(81.3%) 3(18.8%) N2 26 13(50.0%) 13(50.0%) 9(34.6%) 17(65.4%) 9(34.6%) 17(65.4%) 18(69.2%) 8(30.8%) N3 35 14(40.0%) 21(60.0%) 10(28.6%) 25(71.4%) 10(28.6%) 25(71.4%) 19(54.3%) 16(45.7%) Metastasis M0 89 41(46.1%) 48(53.9%) 0.578 32(36.0%) 57(64.0%) 0.297 33(37.1%) 56(62.9%) 0.007 62(69.7%) 27(30.3%) 0.630 M1 9 2(22.2%) 7(77.8%) 1(11.1%) 8(88.9%) 2(22.2%) 7(77.8%) 5(55.6%) 4(44.4%) 3.4 Effect of CD133, E-cad, Ki67, pSmad3L (S204) in gastric cancer tissues on patients' overall survival: To investigate the prognostic value of the expression of CD133, E-cad, Ki67, pSmad3L (S204) in patients with gastric cancer, in this study, we calculated the overall survival rate of patients with gastric cancer after operation by Kaplan-Meier analysis and plotted the Survival curves were calculated and plotted by Kaplan-Meier analysis. The results of Kaplan-Meier analysis showed that the 5-year survival rates of patients with high expression of CD133, E-cad, Ki67, and pSmad3L (S204) were 36.4%, 43.1%, 36.5%, and 19.4%, respectively; and those with low expression of CD133, E-cad, Ki67, and pSmad3L (S204) were 46.5%, 36.4%, 48.6%, and 50.7%, respectively. The median survival of those with high expression of pSmad3L (S204) was significantly shorter than that of those with low expression, and the difference was statistically significant (P = 0.022; 660 days vs. 1890 days); there was no statistically significant difference between the expression of CD133, E-cad, and Ki67, and the overall survival of the patients, as detailed in Fig. 2 . 3.5 Effect of combined analysis of Ki67 and pSmad3L (S204) in gastric cancer tissues on patients' overall survival : To further investigate the value of the combined expression of Ki67 and pSmad3L (S204) on the prognosis of patients with gastric cancer, in this study, we calculated the postoperative overall survival rate of patients with gastric cancer and plotted the survival curves by Kaplan-Meier analysis. Kaplan-Meier analysis showed that the 5-year survival rates of patients with Ki67(+) pSmad3L(S204)(+), Ki67(-) pSmad3L(S204)(-), Ki67(+) pSmad3L(S204)(-), Ki67(-) pSmad3L(S204)(+), and Ki67(-) pSmad3L(S204)(+) were 9.0%, 50.0%, 51.2%, and 44.4%.The median survival of patients with high expression of both Ki67 and pSmad3L(S204) was significantly shorter than that of the other groups, and the difference was statistically significant (P < 0.001; 555 days vs. 1845 days),as shown in Fig. 3 . 3.6 Prognostic value of Ki67, pSmad3L (S204) expression in patients with gastric cancer: In order to investigate the factors affecting postoperative survival of patients with gastric cancer, the present study was conducted by the COX proportional risk model to analyze the gender, age, tumor type, tumor grade, maximum tumor diameter, depth of infiltration, lymph node metastasis, distant metastasis, AJCC stage, CD133, E-cad, Ki67, and pSmad3L (S204) expression levels were analyzed. The results of the univariate COX proportional risk regression model showed that tumor type, tumor grade, depth of infiltration, lymph node metastasis, distant metastasis, AJCC stage, Ki67, and pSmad3L (S204) were all predictive factors for the prognosis of patients with gastric cancer (HR = 1.32; HR = 1.75; HR = 1.67; HR = 1.52; HR = 2.83; HR = 1.87; HR = 1.39; HR = 1.51; all P < 0.05). There were no statistically significant differences in gender, age, CD133, and E-cad differences. Variables with statistically significant differences in the univariate analysis were included in the multifactorial COX proportional risk regression model analysis, and the results showed that the depth of infiltration, lymph node metastasis, Ki67, and pSmad3L (S204) were independent risk factors predicting the prognosis of patients with gastric cancer (HR = 1.65; HR = 1.44; HR = 1.63; HR = 1.55; all P < 0.05). See Table 4 for details. Table 4 Analysis of unifactorial and multifactorial COX proportional risk regression models affecting the prognosis of patients with gastric cancer Characteristics univariate analysis multivariate analysis HR 95%CI P value HR 95%CI P value Gender 0.77 0.47–1.26 p = .301 Age 1.3 0.77–2.19 p = .333 Tumor type 1.32 1.04–1.66 p = .021 1.22 0.90–1.64 p = .206 Pathological grade 1.75 1.09–2.80 p = .021 1.39 0.79–2.44 p = .257 Tumor size 1.52 0.93–2.50 p = .097 T Stage 1.67 1.15–2.42 p = .007 1.65 1.05–2.59 p = .030 N Stage 1.52 1.21–1.91 p < .001 1.44 1.07–1.94 p = .017 Metastasis 2.83 1.34–5.98 p = .007 2.32 0.76–7.04 p = .138 AJCC Stage 1.87 1.32–2.64 p < .001 0.88 0.46–1.66 p = .682 CD133 1.21 0.84–1.73 p = .300 Ecad 0.91 0.71–1.17 p = .465 Ki67 1.39 1.04–1.87 p = .026 1.63 1.20–2.21 p = .002 pSmad3L(S204) 1.51 1.11–2.06 p = .008 1.55 1.10–2.18 p = .013 3.7 Establishment of clinical prediction model: The independent risk factors were screened in this study, and forest plots and nomograms were drawn according to the risk prediction model, as shown in Fig. 4 , 5 . Evaluation of differentiation: The results of the ROC curve analysis showed that the area under the curve (AUC) of the prediction model for the survival rate of gastric cancer patients in the 1st, 3rd, and 5th years after surgery was 0.74 (95% CI: 0.618), 0.76 (95% CI: 0.666–0.857), 0.79 (95% CI: 0.699–0.877), and 0.79 (95% CI: 0.699–0.877) respectively. ~0.870), 0.76 (95% CI: 0.666–0.857), and 0.79 (95% CI: 0.699–0.877), respectively. This indicates that the prediction model has better predictive efficacy and higher discriminative ability for the prognosis of gastric cancer patients, as shown in Fig. 6 A.Calibration evaluation: the results of the calibration curve analysis showed that the predicted probability of the prediction model and the actual probability of the prediction model showed a higher degree of agreement in the first year of the postoperative period of the gastric cancer patients, but the degree of agreement gradually declined in the third year and the fifth year. This indicates that the prediction model has good calibration ability in the first year after surgery for gastric cancer patients. For details, see Fig. 6 B, 6 C and 6 D for details. Evaluation of effectiveness: The DCA curve analysis results show that the DCA curves of this prediction model in the 1st, 3rd, and 5th years after the operation of gastric cancer patients are located in the upper right of the intersection point of ALL curve and None curve. See Fig. 6 E for details. 3.8 Effect of Ki67 and pSmad3L (S204) Expression on Overall Survival in Gastric Cancer Patients with Lymph Node Metastasis : To further investigate the relationship between Ki67 and pSmad3L (S204) protein expression and survival in gastric cancer patients with lymph node metastasis, the present study was conducted to calculate the overall survival rate of gastric cancer patients with lymph node metastasis after surgery by Kaplan-Meier analysis and to plot the survival curves. The results showed that the 5-year survival rates of patients with high expression of Ki67 and pSmad3L(S204) were 23.8% and 8.3%, respectively, and the 5-year survival rates of patients with low expression were 36.8% and 40.5%, respectively. High pSmad3L(S204) expressors had a significantly shorter median survival than low expressors, and the difference was statistically significant (P = 0.015; 600 days vs. 840 days); there was no statistically significant difference between Ki67 expression and overall survival of patients, as shown in Fig. 7 . 4.Discussion Ki67, a marker of cell proliferation, is an indicator of the malignancy and aggressiveness of tumor cells[ 19 ]. Our results showed that the high expression of Ki67 in gastric cancer tissues was significantly higher than that in normal tissues adjacent to the cancer (P = 0.001), and the high expression of Ki67 was closely correlated with M stage (P = 0.007) and tumor grade (P = 0.043). This result preliminarily indicated that the high expression of Ki67 might be highly correlated with the occurrence of gastric cancer. Yerushalmi[ 20 ] and others have shown that Ki67 can be used as a predictive and prognostic marker for breast cancer, and an expression level higher than 10–14% indicates that the patient has a high prognostic risk. Wei[ 21 ] further found that high expression of Ki67 was significantly correlated with poor prognosis and disease progression in lung cancer patients by meta-analysis, suggesting that it can be used as a potential biomarker for lung cancer. La Rosa[ 22 ] and others confirmed that the ability of Ki67 to predict the prognosis of tumors is tissue-specific, and that its clinical value varies depending on the type of tumor and the site of origin. To further explore the prognostic value of Ki67, we performed univariate and multivariate Cox regression analysis. The results showed that high expression of Ki67 was an independent risk factor for the prognosis of gastric cancer patients (HR = 1.63, 95%CI: 1.20–2.21, P = 0.002). This finding suggests that Ki67 may be involved in the metastatic process of gastric cancer by promoting the proliferation and invasion of tumor cells. Meanwhile, the high expression of Ki67 was closely associated with poorer prognosis of patients, suggesting that it may be a new target for gastric cancer treatment. The TGF-β signaling pathway exhibits a dual role in cancer progression. In the early stage of cancer, TGF-β exerts its tumor suppressor effects by inducing cell cycle arrest and promoting apoptosis. However, with tumor progression, TGF-β promotes cancer value-addition and infiltration by promoting epithelial-mesenchymal transition (EMT), regulating the tumor microenvironment, invasion, evasion of immune surveillance and metastatic spread[ 23 ]. The Smad protein family serves as a key mediator of the TGF-β signaling pathway, helping TGF-β to enter the nucleus to mediate transcriptional activation of multiple target genes during signal transduction to achieve tumor suppression or tumorigenesis [ 24 ],thus serving as a potential immunotherapeutic target for a variety of malignancies[ 25 ]. In this study, we found that high pSmad3L(S204) expression was significantly associated with shorter overall survival in gastric cancer patients (P = 0.022; 660 days vs 1890 days). Notably, in the subgroup with lymph node metastasis, the survival of patients with high pSmad3L(S204) expression was further shortened (P = 0.015; 600 days vs 840 days), a finding that is highly consistent with previous studies[ 26 , 27 ]. By univariate and multivariate COX regression analyses, we confirmed that high expression of pSmad3L(S204) was an independent risk factor for the prognosis of gastric cancer patients (HR = 1.55, 95%CI: 1.10–2.18, P = 0.013), suggesting that it has a high predictive value for the prognosis of gastric cancer patients. Yoshida [ 28 ] et al. found that Smad phosphorylation isoform signaling may serve as a potential biomarker for predicting the effect of drug intervention in hepatic fibrocellular carcinoma. In addition, Hori [ 29 ] et al. confirmed the significant prognostic value of pSmad3L in pancreatic intraductal papillary mucinous neoplasia (IPMN) by immunohistochemistry, which provides more reliable evidence for predicting malignant transformation and prognosis of IPMN. Based on the above research findings, we believe that pSmad3L(S204) not only serves as a reliable predictor of gastric cancer prognosis, but also may be a potential tumor therapeutic target. This finding provides a new idea for the precision treatment of gastric cancer and lays a theoretical foundation for the development of targeted therapeutic strategies based on pSmad3L(S204). To further evaluate the synergistic effect of Ki67 and pSmad3L(S204) in the prognosis of gastric cancer, we performed co-expression analysis. The results showed that gastric cancer patients with high expression of both Ki67 and pSmad3L(S204) had significantly shorter overall survival (P < 0.001; 555 days vs. 1845 days). This finding not only confirmed the independent prognostic value of Ki67 and pSmad3L(S204) in gastric cancer progression, but also revealed the possible synergistic effect of the two in promoting malignant tumor progression, which will provide a more comprehensive molecular basis for individualized treatment of gastric cancer. 5.Conclusion High expression of Ki67 and high expression of pSmad3L(S204) are independent risk factors for the prognosis of patients with gastric cancer, and the combined analysis of Ki67 and pSmad3L(S204) can help to improve the risk prediction. Abbreviations GC: Gastric Cancer IARC: International Agency for Research on Cancer uLMS: Uterine Smooth Muscle Sarcoma SNPs: Single Nucleotide Polymorphisms LUAD: Lung Adenocarcinoma AJCC: American Joint Committee on Cancer WHO: World Health Organization IHC: Immunohistochemical PBS: Phosphate Buffer Solution HRP: Horseradish Peroxidase SD: Standard Deviation IQR: Interquartile Range ROC: Receiver Operating Characteristic AUC: Area Under the Curve TNM: Tumor Node Metastasis DCA: Decision Curve Analysis EMT: Epithelial-Mesenchymal Transition IPMN: Intraductal Papillary Mucinous Neoplasia Declarations Acknowledgments This work was supported by the Key Laboratory Project of Digestive Diseases in Jiangxi Province (2024SSY06101), and Jiangxi Clinical Research Center for Gastroenterology (20223BCG74011). Funding supported by the National Nature Science Foundation of China (Grants 82360517, 82060450, 81460374, 31460304), Nature Science Foundation of Jiangxi province of China (20232BAB206086, 20192BAB205072, 20203BBGL73206, 2017BCB23086, 2017BAB205062, 2018BAB205050). Contributions: Huang DQ and Kang YH conceived and designed the study, analyzed and interpreted the data, and wrote the manuscript; Hu Q, Guo P, Lv SL, Sun HT , Luo LY and Chen RS collected clinical samples and completed the related experiments; All authors approved the final manuscript. Ethics declarations Ethics approval and consent to participate The study was conducted in accordance with the Declaration of Helsinki. This study involving patient participants was reviewed and approved by the Ethics Committee of Shanghai Outdo Biotech Company (Shanghai, China) (NO.: SHYJS-CP-1801009). The patients provided their written informed consent to participate in this study. Written informed consent was obtained from all participants. Consent for publication Informed consent was obtained from all subjects involved in the study. Competing interests The authors have no conflicts of interest to declare. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. References Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2024;74:229-63. Feng RM, Zong YN, Cao SM, Xu RH. Current cancer situation in China: good or bad news from the 2018 Global Cancer Statistics? Cancer Commun (Lond). 2019;39:22. Joshi SS, Badgwell BD. Current treatment and recent progress in gastric cancer. CA Cancer J Clin. 2021;71:264-79. Li P, Huang C-M, Zheng C-H, Russo A, Kasbekar P, Brennan MF, et al. Comparison of gastric cancer survival after R0 resection in the US and China. Journal of surgical oncology. 2018;118:975-82. Glimelius B, Ekström K, Hoffman K, Graf W, Sjödén PO, Haglund U, et al. Randomized comparison between chemotherapy plus best supportive care with best supportive care in advanced gastric cancer. Ann Oncol. 1997;8:163-8. Jin X, Liu Z, Yang D, Yin K, Chang X. Recent Progress and Future Perspectives of Immunotherapy in Advanced Gastric Cancer. Front Immunol. 2022;13:948647. Duchrow M, Schlüter C, Key G, Kubbutat MH, Wohlenberg C, Flad HD, et al. Cell proliferation-associated nuclear antigen defined by antibody Ki-67: a new kind of cell cycle-maintaining proteins. Arch Immunol Ther Exp (Warsz). 1995;43:117-21. Scholzen T, Gerdes J. The Ki-67 protein: from the known and the unknown. J Cell Physiol. 2000;182:311-22. Bourdeleau P, Pokossy-Epée J, Hentic O, Tihy M, Awan ZA, Couvelard A, et al. 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Ni H, Zhang H, Li L, Huang H, Guo H, Zhang L, et al. T cell-intrinsic STING signaling promotes regulatory T cell induction and immunosuppression by upregulating FOXP3 transcription in cervical cancer. J Immunother Cancer. 2022;10. Edge SB, Compton CC. The American Joint Committee on Cancer: the 7th edition of the AJCC cancer staging manual and the future of TNM. Ann Surg Oncol. 2010;17:1471-4. Fenoglio-Preiser C, Carneiro F, Correa P, Guilford P, Lambert R, Megraud F, et al. Gastric carcinoma. 2000;1:35-52. Zou J, Li C, Jiang S, Luo L, Yan X, Huang D, et al. AMPK inhibits Smad3-mediated autoinduction of TGF-β1 in gastric cancer cells. J Cell Mol Med. 2021;25:2806-15. Cheng X, Li D, Qi T, Sun J, Zhou T, Zheng WV. Objective to identify and verify the regulatory mechanism of DTNBP1 as a prognostic marker for hepatocellular carcinoma. Sci Rep. 2022;12:211. 李科, 曹永清, 肖劲军, 陈辉. TTF-1、NapsinA和Ki-67在非小细胞肺癌中的表达及意义 %J 河北医药. 2018;40:735-8. Yerushalmi R, Woods R, Ravdin PM, Hayes MM, Gelmon KA. 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Hepatobiliary & Pancreatic Diseases International. 2020;19:581-9. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 12 Dec, 2025 Read the published version in BMC Gastroenterology → Version 1 posted Editorial decision: Revision requested 31 Oct, 2025 Reviews received at journal 30 Oct, 2025 Reviewers agreed at journal 29 Oct, 2025 Reviews received at journal 02 Oct, 2025 Reviewers agreed at journal 21 Sep, 2025 Reviewers invited by journal 21 Sep, 2025 Editor invited by journal 02 Sep, 2025 Editor assigned by journal 19 Aug, 2025 Submission checks completed at journal 16 Aug, 2025 First submitted to journal 16 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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16:23:19","extension":"png","order_by":26,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":67881,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7284849/v1/5e4fa58dc369f395fea0c0d1.png"},{"id":92735614,"identity":"661675fe-c4d2-4a27-a68f-5b51b339ff08","added_by":"auto","created_at":"2025-10-03 16:31:19","extension":"png","order_by":27,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":24309,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7284849/v1/2198efedc6913e24119a81dc.png"},{"id":92734118,"identity":"dc75eb36-cc3c-4746-b6ac-82bc29581176","added_by":"auto","created_at":"2025-10-03 16:23:20","extension":"xml","order_by":28,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":145695,"visible":true,"origin":"","legend":"","description":"","filename":"2376eb5c1886422186fb73e494b523f51structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7284849/v1/3dfd91ca8006981ac1c7744f.xml"},{"id":92734109,"identity":"56cb4ef0-00f9-4b23-9228-0ab80e1503ff","added_by":"auto","created_at":"2025-10-03 16:23:20","extension":"html","order_by":29,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":152680,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7284849/v1/10eb79362aee99e2c3405fc5.html"},{"id":92734112,"identity":"84d494c7-0028-4b77-9b77-f4d4c1f67d03","added_by":"auto","created_at":"2025-10-03 16:23:20","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":30342241,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExpression of CD133, E-cad, Ki67 and pSmad3L (S204) in gastric cancer. This figure demonstrates the typical immunohistochemical staining results of CD133, E-cad, Ki67 and pSmad3L (S204) in gastric cancer tissues and normal gastric mucosa tissues adjacent to the cancer (×20, 100 μm)；\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7284849/v1/829eb791c358c1cf0edfb261.png"},{"id":92734098,"identity":"bd236c1e-8c3a-4983-96c2-7ab9d4444dc0","added_by":"auto","created_at":"2025-10-03 16:23:19","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3693591,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan Meier survival curve analysis: the relationship between the protein expression levels of CD133, E-cad, Ki67, and pSmad3L (S204) and the prognosis of patients with gastric cancer. a: the relationship between the protein expression level of CD133 and OS in patients with gastric cancer; b: the relationship between the protein expression level of E-cad and OS in patients with gastric cancer; c: the relationship between the protein expression level of Ki67 and OS in patients with gastric cancer; d: the relationship between the protein expression level of pSmad3L (S204) and OS in patients with gastric cancer;\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7284849/v1/ce86982db915afc9a3ad4c5b.png"},{"id":92734106,"identity":"f65adfff-fb82-46dc-a858-797b95bba259","added_by":"auto","created_at":"2025-10-03 16:23:19","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":827748,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan-Meier survival curve analysis: Prognostic relationship between Ki67 combined pSmad3L (S204) protein expression levels and gastric cancer patients; a: patients with high/low Ki67 expression and/or high/low pSmad3L (S204) expression were analyzed; b: patients with high expression of both Ki67 and pSmad3L (S204) were analyzed in comparison with the remaining patients;\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7284849/v1/fb2cd70e9c73d52aff2a4ab8.png"},{"id":92734103,"identity":"abcebcb0-24df-42d9-b3d6-40e29a4ab75d","added_by":"auto","created_at":"2025-10-03 16:23:19","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":251969,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eForest plot for multifactor COX risk proportionality modeling；\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7284849/v1/5f988f79a4d9154560a21731.png"},{"id":92734095,"identity":"bea8ccb2-3eac-4c7e-9689-e23e05ff278a","added_by":"auto","created_at":"2025-10-03 16:23:18","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":265064,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrognostic column line diagram for gastric cancer patients；\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7284849/v1/c93e0191dbdb0d8ed87aabdf.png"},{"id":92734107,"identity":"db324acc-d1fe-4a18-b3b6-c5afa723a635","added_by":"auto","created_at":"2025-10-03 16:23:20","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":2665075,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEvaluation of the multivariable Cox proportional hazards model：A：ROC curves for the column-line diagram model；B：Calibration curves for gastric cancer patients at year 1；C：Calibration curves for gastric cancer patients at year 3；D：Calibration curves for gastric cancer patients at year 5；E：shows the decision curve of the line diagram；\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7284849/v1/85732b5fb17df2496690b7a6.png"},{"id":92735617,"identity":"d2acd762-eb88-4d66-a463-ef133ed50898","added_by":"auto","created_at":"2025-10-03 16:31:20","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1150803,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan Meier survival curve analysis: relationship between Ki67, pSmad3L (S204) protein expression levels in gastric cancer patients with lymph node metastasis and the prognosis of gastric cancer patients. a: Relationship between Ki67 expression levels and OS in gastric cancer patients with lymph node metastasis; b: Relationship between pSmad3L (S204) expression levels and OS in gastric cancer patients with lymph node metastasis;\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7284849/v1/45ba8f7ec0d898e6e57221d8.png"},{"id":98244851,"identity":"cfc3ae67-63df-40c6-9039-d95d45277337","added_by":"auto","created_at":"2025-12-15 16:15:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":37087758,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7284849/v1/b0b11aba-2e8b-49de-aa80-bcbc08432afe.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Clinical significance of the S204 phosphorylation of the Smad3 protein in combination with Ki67 for the metastasis and prognosis of gastric cancer","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCancer remains a major public health problem worldwide, with nearly 20\u0026nbsp;million new cancer cases and nearly 9.7\u0026nbsp;million cancer deaths expected in 2022, according to the latest report from the International Agency for Research on Cancer (IARC). Among these, gastric cancer ranks fifth among common malignancies in terms of both incidence (4.9%) and mortality (6.8%)[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Although the mortality rate of gastric cancer has shown a decreasing trend in recent years, it is still higher than that in developed countries such as the United Kingdom and the United States, which is mainly related to its low rate of early diagnosis and the lack of uniformity in clinical cancer diagnosis and treatment strategies[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Gastric cancer is now mainly treated with systemic chemotherapy, radiotherapy, surgery, targeted and immunotherapy and other integrated treatments[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Early symptoms of gastric cancer are insidious and progress rapidly, and the best time for surgical treatment is usually missed when it is first diagnosed[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Although systemic chemotherapy can improve the quality and prolong the survival time of gastric cancer patients, the clinical benefit is still very limited[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Patients with advanced gastric cancer have a very poor prognosis due to the difficulty of screening for targeted drugs and multidrug resistance[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Therefore, the search for molecular markers that can diagnose gastric cancer at an early stage and predict the prognosis of gastric cancer patients is of great importance in realizing new therapeutic targets and improving prognosis.\u003c/p\u003e\u003cp\u003eThe gene encoding Ki67, which is located on human chromosome 10 (10q25-qter) and consists of 15 exons, is a widely used marker of cell proliferation[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Several clinical studies have confirmed that in pancreatic neuroendocrine tumors, dynamic elevation of the Ki67 proliferation index is significantly associated with increased tumor aggressiveness and poor patient prognosis, suggesting that the Ki67 index can be used as an important biological indicator to assess the progression and prognosis of pancreatic neuroendocrine tumors[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In uterine smooth muscle sarcoma (uLMS), quantitatively elevated Ki67 proliferation index was significantly and positively correlated with an increased risk of death in patients, in which a Ki67 index\u0026thinsp;\u0026ge;\u0026thinsp;10% was identified as an independent poor prognostic factor in uLMS, providing an important quantitative indicator for clinical prognostic assessment[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].Although the role of Ki67 has been extensively studied in a variety of tumors, its prognostic value in gastric cancer (GC) has not been fully elucidated.\u003c/p\u003e\u003cp\u003eSamd3 is an important transcriptional regulator in the TGF-β signaling pathway and is a member of the SAMD protein family. In the classical TGF-β/SAMD3 pathway, phosphorylated SAMD2/3 and SAMD4 form a transcriptional complex that translocates to the nucleus and participates in the transcriptional regulation of several target genes[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. It was shown that in lung epithelial cells, SAMD3 and ATOH8 interact to form a transcriptional complex capable of directly repressing the expression of key genes associated with cell cycle progression. This molecular mechanism not only accelerated the senescence process of lung epithelial cells, but also further promoted the transformation of senescent cells to a malignant phenotype[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In addition, single nucleotide polymorphisms (SNPs) in the SMAD3 gene were significantly associated with the prognosis of patients with lung adenocarcinoma (LUAD) treated with gefitinib, which may serve as an important molecular marker for predicting treatment response and survival[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In cervical cancer, phosphorylation of SAMD3 has been shown to significantly increase the transcriptional activity of the FOXP3 gene, which in turn induces the expansion of regulatory T lymphocytes. This process is closely associated with immune escape from cervical cancer and the immunosuppressive state of the tumor microenvironment, which ultimately leads to poor patient prognosis[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. However, the relationship between Samd3 and Ki67 is not well understood.\u003c/p\u003e\u003cp\u003eIn summary, Smad3 protein, as a key regulator of the TGF-β signaling pathway, plays an important role in tumorigenesis and development by phosphorylation at its S204 site. Meanwhile, Ki67, as a marker of cell proliferation, has been widely used in the prognostic assessment of various malignant tumors. However, the co-expression of Smad3 S204 phosphorylation and Ki67 in gastric cancer and its effect on tumor metastasis and prognosis have not been fully investigated. Therefore, the aim of this study was to investigate the expression characteristics of Smad3 S204 phosphorylation and Ki67 in gastric cancer tissues, to analyze their correlation with clinicopathological parameters and prognosis, and to explore the potential value of co-expression of pSmad3 (S204) and Ki67 in gastric cancer metastasis and prognosis.\u003c/p\u003e"},{"header":"2. Methods and materials","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1Patients and specimens\u003c/h2\u003e\u003cp\u003e\u003cb\u003ePatients and specimens\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe microarrays were obtained from Shanghai Outdo Biotech Company, the diagnosis of the microarray samples was determined according to AJCC criteria[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], the histological grading of the tumors followed the WHO guidelines for classification of tumors of the gastrointestinal system[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], including 98 cases of cancerous and paraneoplastic tissues, and the use of the samples was approved by the Ethics Committee of Shanghai Outdo Biotech Company (Shanghai, China) (NO.: SHYJS-CP-1801009).\u003c/p\u003e\u003cp\u003e\u003cb\u003eIHC\u003c/b\u003e\u003c/p\u003e\u003cp\u003eImmunohistochemical (IHC) staining experiments were performed as previously described[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Specifically, paraffin-embedded tissue sections (4 \u0026micro;m in thickness) were deparaffinized and fully hydrated, followed by antigenic repair by thermal induction in citrate buffer (pH 6.0) to ensure adequate exposure of antigenic epitopes.\u003c/p\u003e\u003cp\u003eSubsequently, endogenous peroxidase activity was blocked using H₂O₂ to eliminate background interference. Next, the tissue sections were incubated overnight at 4\u0026deg;C with the following primary antibodies: anti- CD133(item number 18470-1-AP), anti-Ki67 (item number GM724007), anti- E-cad ((item number PA073), anti-PSMAD3L (S204) (item number 2816414), respectively. The next day, the sections were washed three times with phosphate buffer solution (PBS) to remove unbound primary antibodies. The sections were then incubated with anti-rabbit HRP-conjugated IgG secondary antibody (Zsbio, China) for 1 hour at 37\u0026deg;C to ensure specific binding. Meanwhile, sections treated with PBS alone were used as a negative control to exclude non-specific staining. At the end of the incubation, the sections were washed again with PBS and incubated with peroxidase substrate (Zsbio, China) for 20 minutes at 37\u0026deg;C to develop the color reaction. Finally, the nuclei were restained with hematoxylin to enhance the visualization of nuclear structures. After completion of staining, the sections were dehydrated and coverslipped for long-term storage and microscopic observation. Staining results were independently assessed by two pathologists who were unaware of the background of the study, based on the German semi-quantitative scoring method[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The scoring criteria took into account the overall intensity of the staining as well as the percentage of positively stained cells as an objective reflection of the expression level of the target proteins. The overall staining intensity was graded into four levels: no staining (0 points), light yellow staining (1 point), yellow staining (2 points), and dark yellow/brown staining (3 points). The percentage of positive staining was then defined as the proportion of positively stained glandular epithelial cells in the tissue on the slide and scored on the following scale: \u0026lt;5% (0 points); 5%-25% (1 point); 25%-50% (2 points); 50%-75% (3 points); \u0026gt;75% (4 points). By combining the total staining intensity score with the positive staining percentage score, protein expression levels were further characterized as: negative (0\u0026ndash;2 points), + (3\u0026ndash;5 points), ++ (6\u0026ndash;8 points), and +++ (9\u0026ndash;12 points). Finally, all tissue samples were categorized into low expression groups (- or +) and high expression groups (\u0026thinsp;+\u0026thinsp;+\u0026thinsp;or ++++) based on the scoring results[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2Statistical analysis\u003c/h2\u003e\u003cp\u003eData were analyzed using SPSS 26.0 and R language (4.4.0). Measurement data were assessed for normality by the Kolmogorov-Smirnov test; normally distributed data were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD), and comparisons between groups were made using the independent samples t-test; non-normally distributed data were expressed as median and interquartile range (Median [IQR]), and comparisons between groups were made using the Mann-Whitney U test. Categorical data were expressed as frequencies and percentages (n [%]), and the chi-square test was used for comparisons between groups. Survival analysis was performed by the Kaplan-Meier method, and Log-rank test was used for between-group comparisons. Clinical prediction models were constructed by screening variables with P\u0026thinsp;\u0026lt;\u0026thinsp;0.01 by one-way Cox regression, and further by screening independent prognostic factors with P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 by multifactorial Cox regression, and forest plots were plotted using the \u0026ldquo;forestplot\u0026rdquo; package, and column line plots were plotted using the \u0026ldquo;rms\u0026rdquo; package. The \u0026ldquo;forestplot\u0026rdquo; package was used to draw forest plots, and the \u0026ldquo;rms\u0026rdquo; package was used to draw column plots. The \u0026ldquo;pROC\u0026rdquo; package was used to draw the ROC curve and calculate the AUC to assess the differentiation, the \u0026ldquo;rms\u0026rdquo; package was used to draw the calibration curve to assess the calibration degree, and the \u0026ldquo;rmda\u0026rdquo; package was used to draw the decision curve to analyze the clinical utility of the model. The \u0026ldquo;rms\u0026rdquo; package plotted calibration curves to assess calibration, and the \u0026ldquo;rmda\u0026rdquo; package plotted decision curves to analyze and assess clinical utility. p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered a statistically significant difference.\u003c/p\u003e\u003c/div\u003e"},{"header":"3.Results","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 Clinical data:\u003c/h2\u003e\n \u003cp\u003eAmong 98 patients with gastric cancer, 36 cases (36.7%) were female and 62 cases (63.3%) were male; 33 cases (33.7%) were \u0026lt;\u0026thinsp;60 years old and 65 cases (66.3%) were \u0026ge;\u0026thinsp;60 years old; according to the WHO staging, among them, there were 8 cases (8.2%) of mucinous adenocarcinoma, 54 cases (55.1%) of adenocarcinoma, 19 cases (19.4%) of tubular adenocarcinoma, 12 cases (12.2%) of undifferentiated There were 12 cases (12.2%) of undifferentiated adenocarcinoma, 5 cases (5.1%) of indolent cell carcinoma; according to TNM staging, there were 14 cases (14.3%) of Stage II, 72 cases (73.5%) of Stage III, and 12 cases (12.2%) of Stage IV; the maximum diameter of the tumor was \u0026le;\u0026thinsp;5cm in 61 cases (62.2), and \u0026gt;\u0026thinsp;5cm in 37 cases (37.8%); the depth of invasion of T1 was in 6 cases (6.1%), and the depth of T2 was in 9 cases (9.2%), and the depth of invasion of T2 was in 6 cases (6.1%) and 9 cases (9.2%), respectively. There were 6 cases (6.1%) in T1, 9 cases (9.2%) in T2, 64 cases (65.3%) in T3, and 19 cases (19.4%) in T4; there were 21 cases (21.4%) of lymph node metastasis in N0, 16 cases (16.3%) in N1, 26 cases (26.5%) in N2, and 35 cases (35.7%) in N3; and 89 cases (90.8%) had distant metastasis, as shown in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003e\u003c/p\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\u003eClinical baseline table of patients with gastric cancer [cases (%)]\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003elevels\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOverall\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\u003eGender, n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36 (36.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e62 (63.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge, n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33 (33.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e65 (66.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor type, n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMucinous Adenocarcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8 (8.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdenocarcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54 (55.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTubular Adenocarcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19 (19.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUndifferentiated Carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12 (12.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSignet ring cell carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5 (5.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePathological grade, n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eⅡ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14 (14.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eⅢ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e72 (73.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eⅣ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12 (12.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor size, n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;5cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e61 (62.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;5cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37 (37.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT Stage, n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6 (6.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9 (9.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e64 (65.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19 (19.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN Stage, n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21 (21.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16 (16.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26 (26.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35 (35.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMetastasis, n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e89 (90.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9 (9.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAJCC Stage, n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eⅠ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9 (9.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eⅡ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e31 (31.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eⅢ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eⅣ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9 (9.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003ch2\u003e\u003cstrong\u003e3.2 Comparison of the expression of CD133, E-cad, Ki67, pSmad3L (S204) proteins in gastric cancer tissues and normal tissues adjacent to the cancer\u003c/strong\u003e:\u003c/h2\u003e\n \u003cp\u003eIn order to investigate the roles of CD133, E-cad, Ki67, and pSmad3L (S204) in the metastasis and progression of gastric cancer, in this study, the expression of the above indexes was detected in 98 cases of gastric cancer tissues and 82 cases of matched normal tissues adjacent to the cancer through immunohistochemical staining method, and 82 matched paracancerous normal tissues, as shown Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The high expression rates of CD133 (56.1% (55/98)), E-cad (66.3% (65/98)) and Ki67 (64.3% (63/98)) in gastric cancer tissues were significantly higher than those in normal tissues adjacent to the cancer (13.4% (11/82), 26.9% (22/82), 7.3% (6/82)) and the differences were statistically significant (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The high expression rate of pSmad3L (S204) was 31.7 (31/98), which was significantly lower than that of normal tissues next to cancer (79.3% (65/82)), and the difference was statistically significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), as shown in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCD133, E-cad, Ki67, pSmad3L (S204) protein expression in gastric cancer and normal gastric tissues adjacent to the cancer [cases (%)]\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eCD133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eEcad\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eKi67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003epSmad3L(S204)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAd-tissue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAd-tissue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAd-tissue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAd-tissue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20(24.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10(10.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23(28.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(12.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4(4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41(41.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51(62.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23(23.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59(72.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34(34.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53(64.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55(56.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13(15.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e++\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46(47.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11(13.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35(35.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19(23.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31(31.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5(6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23(23.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30(36.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+++\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9(9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30(30.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(3.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32(32.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8(8.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35(42.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003ch2\u003e\u003cstrong\u003e3.3 Relationship between the expression of CD133, E-cad, Ki67, pSmad3L (S204) in gastric cancer tissues and the clinicopathological features of patients\u003c/strong\u003e:\u003c/h2\u003e\n \u003cp\u003eIn order to investigate the effects of the expression of Ki67 and pSmad3L (S204) and their downstream molecules on the metastasis and progression of gastric cancer, we analyzed the expression levels of CD133, E-cad, Ki67, pSmad3L (S204) and their downstream molecules in gastric cancer tissues of 98 cases of gastric cancer by means of chi-square test and Fisher exact probability. We analyzed the relationship between the expression levels of CD133, E-cad, Ki67, pSmad3L (S204) and the clinicopathological features of gastric cancer patients by chi-square test and Fisher\u0026apos;s exact probability method. The results of the correlation of clinicopathological features showed that the high expression of CD133 was correlated with tumor type (P\u0026thinsp;=\u0026thinsp;0.044); the high expression of Ki67 was correlated with tumor grade (P\u0026thinsp;=\u0026thinsp;0.043) and distant metastasis (P\u0026thinsp;=\u0026thinsp;0.007); and the differences of the expression of E-cad and pSmad3L (S204) in different clinicopathological features were not statistically significant, as shown in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRelationship between the protein expression levels of CD133, E-cad, Ki67, pSmad3L (S204) and clinicopathologic features of gastric cancer patients [cases (%)]\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eClinicopathological factors\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eCD133\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eEcad\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eKi67\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003epSmad3L(S204)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eprecedent\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLow n(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHigh n(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLow n(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHigh n(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLow n(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHigh n(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLow n(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHigh n(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP 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\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\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\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\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\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\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16(44.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20(55.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.928\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"31\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13(36.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23(63.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.708\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"31\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(27.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26(72.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.262\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"31\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22(61.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14(38.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.352\u003c/p\u003e\n \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=\"char\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27(43.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35(56.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20(32.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e42(67.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25(40.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37(59.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45(72.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17(27.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\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\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\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\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13(39.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20(60.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.727\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12(36.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21(63.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.945\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14(42.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19(57.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22(66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11(33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.775\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30(46.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35(53.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21(32.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e44(67.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21(32.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e44(67.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45(69.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20(30.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor type\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\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\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\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMucinous Adenocarcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6(75.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2(25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"5\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3(37.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5(62.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"5\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"5\"\u003e\n \u003cp\u003e0.229\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8(100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0(0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"5\"\u003e\n \u003cp\u003e0.082\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdenocarcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18(33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36(66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16(29.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e38(70.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17(31.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37(68.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36(66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18(33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTubular Adenocarcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11(57.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8(42.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5(26.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14(73.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7(36.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12(63.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12(63.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7(36.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUndifferentiated Carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7(58.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5(41.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5(41.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7(58.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8(66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8(66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSignet ring cell carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1(20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(80.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(80.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1(20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3(60.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2(40.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3(60.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2(40.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePathological grade\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\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\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\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=\"char\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8(57.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6(42.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"3\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5(35.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9(64.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"3\"\u003e\n \u003cp\u003e0.654\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(71.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"3\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9(64.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5(35.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"3\"\u003e\n \u003cp\u003e0.624\u003c/p\u003e\n \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=\"char\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28(38.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e44(61.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23(31.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49(68.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27(37.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45(62.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50(69.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22(30.6%)\u003c/p\u003e\n \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=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7(58.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5(41.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5(41.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7(58.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8(66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8(66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor size\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\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\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\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;5cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26(42.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35(57.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.596\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21(34.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40(65.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.978\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21(34.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40(65.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e46(75.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15(24.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;5cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17(45.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20(54.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12(32.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25(67.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14(37.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23(62.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21(56.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16(43.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT 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\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\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\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\u003eT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2(33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"4\"\u003e\n \u003cp\u003e0.234\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1(16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5(83.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"4\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2(33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"4\"\u003e\n \u003cp\u003e0.683\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2(33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"4\"\u003e\n \u003cp\u003e0.852\u003c/p\u003e\n \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=\"char\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7(77.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2(22.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3(33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6(66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(44.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5(55.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6(66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3(33.3%)\u003c/p\u003e\n \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=\"char\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28(43.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36(56.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21(32.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e43(67.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20(31.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e44(68.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45(70.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19(29.7%)\u003c/p\u003e\n \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=\"char\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(21.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15(78.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8(42.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11(57.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7(36.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12(63.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12(63.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7(36.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN 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\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\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\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\u003eN0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11(52.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(47.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"4\"\u003e\n \u003cp\u003e0.836\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9(42.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12(57.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"4\"\u003e\n \u003cp\u003e0.298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9(42.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12(57.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"4\"\u003e\n \u003cp\u003e0.807\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17(81.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(19.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"4\"\u003e\n \u003cp\u003e0.475\u003c/p\u003e\n \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=\"char\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5(31.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11(68.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5(31.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11(68.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7(43.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9(56.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13(81.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3(18.8%)\u003c/p\u003e\n \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=\"char\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13(50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13(50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9(34.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17(65.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9(34.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17(65.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18(69.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8(30.8%)\u003c/p\u003e\n \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=\"char\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14(40.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21(60.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25(71.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25(71.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19(54.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16(45.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMetastasis\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\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\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\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e41(46.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48(53.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.578\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32(36.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e57(64.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33(37.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e56(62.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e62(69.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27(30.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.630\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2(22.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7(77.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1(11.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8(88.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2(22.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7(77.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5(55.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(44.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4 Effect of CD133, E-cad, Ki67, pSmad3L (S204) in gastric cancer tissues on patients\u0026apos; overall survival:\u003c/h2\u003e\n \u003cp\u003eTo investigate the prognostic value of the expression of CD133, E-cad, Ki67, pSmad3L (S204) in patients with gastric cancer, in this study, we calculated the overall survival rate of patients with gastric cancer after operation by Kaplan-Meier analysis and plotted the Survival curves were calculated and plotted by Kaplan-Meier analysis. The results of Kaplan-Meier analysis showed that the 5-year survival rates of patients with high expression of CD133, E-cad, Ki67, and pSmad3L (S204) were 36.4%, 43.1%, 36.5%, and 19.4%, respectively; and those with low expression of CD133, E-cad, Ki67, and pSmad3L (S204) were 46.5%, 36.4%, 48.6%, and 50.7%, respectively. The median survival of those with high expression of pSmad3L (S204) was significantly shorter than that of those with low expression, and the difference was statistically significant (P\u0026thinsp;=\u0026thinsp;0.022; 660 days vs. 1890 days); there was no statistically significant difference between the expression of CD133, E-cad, and Ki67, and the overall survival of the patients, as detailed in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n \u003ch2\u003e\u003cstrong\u003e3.5 Effect of combined analysis of Ki67 and pSmad3L (S204) in gastric cancer tissues on patients\u0026apos; overall survival\u003c/strong\u003e:\u003c/h2\u003e\n \u003cp\u003eTo further investigate the value of the combined expression of Ki67 and pSmad3L (S204) on the prognosis of patients with gastric cancer, in this study, we calculated the postoperative overall survival rate of patients with gastric cancer and plotted the survival curves by Kaplan-Meier analysis. Kaplan-Meier analysis showed that the 5-year survival rates of patients with Ki67(+) pSmad3L(S204)(+), Ki67(-) pSmad3L(S204)(-), Ki67(+) pSmad3L(S204)(-), Ki67(-) pSmad3L(S204)(+), and Ki67(-) pSmad3L(S204)(+) were 9.0%, 50.0%, 51.2%, and 44.4%.The median survival of patients with high expression of both Ki67 and pSmad3L(S204) was significantly shorter than that of the other groups, and the difference was statistically significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; 555 days vs. 1845 days),as shown in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e3.6 Prognostic value of Ki67, pSmad3L (S204) expression in patients with gastric cancer:\u003c/h2\u003e\n \u003cp\u003eIn order to investigate the factors affecting postoperative survival of patients with gastric cancer, the present study was conducted by the COX proportional risk model to analyze the gender, age, tumor type, tumor grade, maximum tumor diameter, depth of infiltration, lymph node metastasis, distant metastasis, AJCC stage, CD133, E-cad, Ki67, and pSmad3L (S204) expression levels were analyzed. The results of the univariate COX proportional risk regression model showed that tumor type, tumor grade, depth of infiltration, lymph node metastasis, distant metastasis, AJCC stage, Ki67, and pSmad3L (S204) were all predictive factors for the prognosis of patients with gastric cancer (HR\u0026thinsp;=\u0026thinsp;1.32; HR\u0026thinsp;=\u0026thinsp;1.75; HR\u0026thinsp;=\u0026thinsp;1.67; HR\u0026thinsp;=\u0026thinsp;1.52; HR\u0026thinsp;=\u0026thinsp;2.83; HR\u0026thinsp;=\u0026thinsp;1.87; HR\u0026thinsp;=\u0026thinsp;1.39; HR\u0026thinsp;=\u0026thinsp;1.51; all P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). There were no statistically significant differences in gender, age, CD133, and E-cad differences. Variables with statistically significant differences in the univariate analysis were included in the multifactorial COX proportional risk regression model analysis, and the results showed that the depth of infiltration, lymph node metastasis, Ki67, and pSmad3L (S204) were independent risk factors predicting the prognosis of patients with gastric cancer (HR\u0026thinsp;=\u0026thinsp;1.65; HR\u0026thinsp;=\u0026thinsp;1.44; HR\u0026thinsp;=\u0026thinsp;1.63; HR\u0026thinsp;=\u0026thinsp;1.55; all P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). See Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e for details.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAnalysis of unifactorial and multifactorial COX proportional risk regression models affecting the prognosis of patients with gastric cancer\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eunivariate analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003emultivariate analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \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\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.47\u0026ndash;1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u0026thinsp;=\u0026thinsp;.301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"13\"\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 \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.77\u0026ndash;2.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u0026thinsp;=\u0026thinsp;.333\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\u003eTumor type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.04\u0026ndash;1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u0026thinsp;=\u0026thinsp;.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.90\u0026ndash;1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u0026thinsp;=\u0026thinsp;.206\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePathological grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09\u0026ndash;2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u0026thinsp;=\u0026thinsp;.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.79\u0026ndash;2.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u0026thinsp;=\u0026thinsp;.257\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.93\u0026ndash;2.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u0026thinsp;=\u0026thinsp;.097\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\u003eT Stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.15\u0026ndash;2.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u0026thinsp;=\u0026thinsp;.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.05\u0026ndash;2.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u0026thinsp;=\u0026thinsp;.030\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN Stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.21\u0026ndash;1.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.07\u0026ndash;1.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u0026thinsp;=\u0026thinsp;.017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMetastasis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.34\u0026ndash;5.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u0026thinsp;=\u0026thinsp;.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.76\u0026ndash;7.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u0026thinsp;=\u0026thinsp;.138\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAJCC Stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.32\u0026ndash;2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.46\u0026ndash;1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u0026thinsp;=\u0026thinsp;.682\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.84\u0026ndash;1.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u0026thinsp;=\u0026thinsp;.300\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\u003eEcad\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.71\u0026ndash;1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u0026thinsp;=\u0026thinsp;.465\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\u003eKi67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.04\u0026ndash;1.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u0026thinsp;=\u0026thinsp;.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.20\u0026ndash;2.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u0026thinsp;=\u0026thinsp;.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epSmad3L(S204)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.11\u0026ndash;2.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u0026thinsp;=\u0026thinsp;.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.10\u0026ndash;2.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u0026thinsp;=\u0026thinsp;.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e3.7 Establishment of clinical prediction model:\u003c/h2\u003e\n \u003cp\u003eThe independent risk factors were screened in this study, and forest plots and nomograms were drawn according to the risk prediction model, as shown in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e. Evaluation of differentiation: The results of the ROC curve analysis showed that the area under the curve (AUC) of the prediction model for the survival rate of gastric cancer patients in the 1st, 3rd, and 5th years after surgery was 0.74 (95% CI: 0.618), 0.76 (95% CI: 0.666\u0026ndash;0.857), 0.79 (95% CI: 0.699\u0026ndash;0.877), and 0.79 (95% CI: 0.699\u0026ndash;0.877) respectively. ~0.870), 0.76 (95% CI: 0.666\u0026ndash;0.857), and 0.79 (95% CI: 0.699\u0026ndash;0.877), respectively. This indicates that the prediction model has better predictive efficacy and higher discriminative ability for the prognosis of gastric cancer patients, as shown in Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eA.Calibration evaluation: the results of the calibration curve analysis showed that the predicted probability of the prediction model and the actual probability of the prediction model showed a higher degree of agreement in the first year of the postoperative period of the gastric cancer patients, but the degree of agreement gradually declined in the third year and the fifth year. This indicates that the prediction model has good calibration ability in the first year after surgery for gastric cancer patients. For details, see Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eB,\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eC and \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eD for details. Evaluation of effectiveness: The DCA curve analysis results show that the DCA curves of this prediction model in the 1st, 3rd, and 5th years after the operation of gastric cancer patients are located in the upper right of the intersection point of ALL curve and None curve. See Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eE for details.\u003c/p\u003e\n \u003ch2\u003e\u003cstrong\u003e3.8 Effect of Ki67 and pSmad3L (S204) Expression on Overall Survival in Gastric Cancer Patients with Lymph Node Metastasis\u003c/strong\u003e:\u003c/h2\u003e\n \u003cp\u003eTo further investigate the relationship between Ki67 and pSmad3L (S204) protein expression and survival in gastric cancer patients with lymph node metastasis, the present study was conducted to calculate the overall survival rate of gastric cancer patients with lymph node metastasis after surgery by Kaplan-Meier analysis and to plot the survival curves. The results showed that the 5-year survival rates of patients with high expression of Ki67 and pSmad3L(S204) were 23.8% and 8.3%, respectively, and the 5-year survival rates of patients with low expression were 36.8% and 40.5%, respectively. High pSmad3L(S204) expressors had a significantly shorter median survival than low expressors, and the difference was statistically significant (P\u0026thinsp;=\u0026thinsp;0.015; 600 days vs. 840 days); there was no statistically significant difference between Ki67 expression and overall survival of patients, as shown in Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4.Discussion","content":"\u003cp\u003eKi67, a marker of cell proliferation, is an indicator of the malignancy and aggressiveness of tumor cells[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Our results showed that the high expression of Ki67 in gastric cancer tissues was significantly higher than that in normal tissues adjacent to the cancer (P\u0026thinsp;=\u0026thinsp;0.001), and the high expression of Ki67 was closely correlated with M stage (P\u0026thinsp;=\u0026thinsp;0.007) and tumor grade (P\u0026thinsp;=\u0026thinsp;0.043). This result preliminarily indicated that the high expression of Ki67 might be highly correlated with the occurrence of gastric cancer. Yerushalmi[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] and others have shown that Ki67 can be used as a predictive and prognostic marker for breast cancer, and an expression level higher than 10\u0026ndash;14% indicates that the patient has a high prognostic risk. Wei[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] further found that high expression of Ki67 was significantly correlated with poor prognosis and disease progression in lung cancer patients by meta-analysis, suggesting that it can be used as a potential biomarker for lung cancer. La Rosa[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] and others confirmed that the ability of Ki67 to predict the prognosis of tumors is tissue-specific, and that its clinical value varies depending on the type of tumor and the site of origin. To further explore the prognostic value of Ki67, we performed univariate and multivariate Cox regression analysis. The results showed that high expression of Ki67 was an independent risk factor for the prognosis of gastric cancer patients (HR\u0026thinsp;=\u0026thinsp;1.63, 95%CI: 1.20\u0026ndash;2.21, P\u0026thinsp;=\u0026thinsp;0.002). This finding suggests that Ki67 may be involved in the metastatic process of gastric cancer by promoting the proliferation and invasion of tumor cells. Meanwhile, the high expression of Ki67 was closely associated with poorer prognosis of patients, suggesting that it may be a new target for gastric cancer treatment.\u003c/p\u003e\u003cp\u003eThe TGF-β signaling pathway exhibits a dual role in cancer progression. In the early stage of cancer, TGF-β exerts its tumor suppressor effects by inducing cell cycle arrest and promoting apoptosis. However, with tumor progression, TGF-β promotes cancer value-addition and infiltration by promoting epithelial-mesenchymal transition (EMT), regulating the tumor microenvironment, invasion, evasion of immune surveillance and metastatic spread[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The Smad protein family serves as a key mediator of the TGF-β signaling pathway, helping TGF-β to enter the nucleus to mediate transcriptional activation of multiple target genes during signal transduction to achieve tumor suppression or tumorigenesis [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e],thus serving as a potential immunotherapeutic target for a variety of malignancies[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn this study, we found that high pSmad3L(S204) expression was significantly associated with shorter overall survival in gastric cancer patients (P\u0026thinsp;=\u0026thinsp;0.022; 660 days vs 1890 days). Notably, in the subgroup with lymph node metastasis, the survival of patients with high pSmad3L(S204) expression was further shortened (P\u0026thinsp;=\u0026thinsp;0.015; 600 days vs 840 days), a finding that is highly consistent with previous studies[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. By univariate and multivariate COX regression analyses, we confirmed that high expression of pSmad3L(S204) was an independent risk factor for the prognosis of gastric cancer patients (HR\u0026thinsp;=\u0026thinsp;1.55, 95%CI: 1.10\u0026ndash;2.18, P\u0026thinsp;=\u0026thinsp;0.013), suggesting that it has a high predictive value for the prognosis of gastric cancer patients. Yoshida [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] et al. found that Smad phosphorylation isoform signaling may serve as a potential biomarker for predicting the effect of drug intervention in hepatic fibrocellular carcinoma. In addition, Hori [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] et al. confirmed the significant prognostic value of pSmad3L in pancreatic intraductal papillary mucinous neoplasia (IPMN) by immunohistochemistry, which provides more reliable evidence for predicting malignant transformation and prognosis of IPMN. Based on the above research findings, we believe that pSmad3L(S204) not only serves as a reliable predictor of gastric cancer prognosis, but also may be a potential tumor therapeutic target. This finding provides a new idea for the precision treatment of gastric cancer and lays a theoretical foundation for the development of targeted therapeutic strategies based on pSmad3L(S204).\u003c/p\u003e\u003cp\u003eTo further evaluate the synergistic effect of Ki67 and pSmad3L(S204) in the prognosis of gastric cancer, we performed co-expression analysis. The results showed that gastric cancer patients with high expression of both Ki67 and pSmad3L(S204) had significantly shorter overall survival (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; 555 days vs. 1845 days). This finding not only confirmed the independent prognostic value of Ki67 and pSmad3L(S204) in gastric cancer progression, but also revealed the possible synergistic effect of the two in promoting malignant tumor progression, which will provide a more comprehensive molecular basis for individualized treatment of gastric cancer.\u003c/p\u003e"},{"header":"5.Conclusion","content":"\u003cp\u003eHigh expression of Ki67 and high expression of pSmad3L(S204) are independent risk factors for the prognosis of patients with gastric cancer, and the combined analysis of Ki67 and pSmad3L(S204) can help to improve the risk prediction.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eGC: Gastric Cancer\u003c/p\u003e\n\u003cp\u003eIARC: International Agency for Research on Cancer\u003c/p\u003e\n\u003cp\u003euLMS: Uterine Smooth Muscle Sarcoma\u003c/p\u003e\n\u003cp\u003eSNPs: Single Nucleotide Polymorphisms\u003c/p\u003e\n\u003cp\u003eLUAD: Lung Adenocarcinoma\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAJCC: American Joint Committee on Cancer\u003c/p\u003e\n\u003cp\u003eWHO: World Health Organization\u003c/p\u003e\n\u003cp\u003eIHC: Immunohistochemical\u003c/p\u003e\n\u003cp\u003ePBS: Phosphate Buffer Solution\u003c/p\u003e\n\u003cp\u003eHRP: Horseradish Peroxidase\u003c/p\u003e\n\u003cp\u003eSD: Standard Deviation\u003c/p\u003e\n\u003cp\u003eIQR: Interquartile Range\u003c/p\u003e\n\u003cp\u003eROC: Receiver Operating Characteristic\u003c/p\u003e\n\u003cp\u003eAUC: Area Under the Curve\u003c/p\u003e\n\u003cp\u003eTNM: Tumor Node Metastasis\u003c/p\u003e\n\u003cp\u003eDCA: Decision Curve Analysis\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEMT: Epithelial-Mesenchymal Transition\u003c/p\u003e\n\u003cp\u003eIPMN: Intraductal Papillary Mucinous Neoplasia\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgments\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Key Laboratory Project of Digestive Diseases in Jiangxi Province (2024SSY06101), and Jiangxi Clinical Research Center for Gastroenterology (20223BCG74011).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003esupported by the National Nature Science Foundation of China (Grants 82360517, 82060450, 81460374, 31460304), Nature Science Foundation of Jiangxi province of China (20232BAB206086, 20192BAB205072, 20203BBGL73206, 2017BCB23086, 2017BAB205062, 2018BAB205050).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eContributions:\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eHuang DQ and Kang YH conceived and designed the study, analyzed and interpreted the data, and wrote the manuscript; Hu Q, Guo P, Lv SL, Sun HT , Luo LY and Chen RS collected clinical samples and completed the related experiments; All authors approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics declarations\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki. This study involving patient participants was reviewed and approved by the Ethics Committee of Shanghai Outdo Biotech Company (Shanghai, China) (NO.: SHYJS-CP-1801009). The patients provided their written informed consent to participate in this study. Written informed consent was obtained from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all subjects involved in the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicts of interest to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, et al. 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The prognostic significance of Smad3, Smad4, Smad3 phosphoisoform expression in esophageal squamous cell carcinoma %J Medical oncology %J. 2014;31.\u003c/li\u003e\n\u003cli\u003eYoshida K, Matsuzaki K, Murata M, Yamaguchi T, Suwa K, Okazaki K. Clinico-Pathological Importance of TGF-\u0026beta;/Phospho-Smad Signaling during Human Hepatic Fibrocarcinogenesis. Cancers (Basel). 2018;10.\u003c/li\u003e\n\u003cli\u003eHori Y, Ikeura T, Yamaguchi T, Yoshida K, Matsuzaki K, Ishida M, et al. Role of phosphorylated Smad3 signal components in intraductal papillary mucinous neoplasm of pancreas. Hepatobiliary \u0026amp; Pancreatic Diseases International. 2020;19:581-9.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-gastroenterology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmge","sideBox":"Learn more about [BMC Gastroenterology](http://bmcgastroenterol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmge/default.aspx","title":"BMC Gastroenterology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Gastric cancer, CD133, E-cad, Ki67, pSmad3L(S204), prognosis","lastPublishedDoi":"10.21203/rs.3.rs-7284849/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7284849/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eAIM\u003c/h2\u003e\u003cp\u003eThe purpose of this study is to explore the prognostic evaluation value of Ki67 and pSmad3L (S204) for gastric cancer patients by jointly analyzing their expression levels in gastric cancer tissues.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis single-center observational study enrolled 98 patients with pathologically confirmed gastric cancer, collecting 82 paired samples of tumor and adjacent normal tissues. Immunohistochemistry was utilized to detect the expression levels of CD133, E-cad, Ki67, and pSmad3L (S204). Pearson correlation coefficients were calculated to assess inter-protein relationships, while chi-square tests evaluated associations with clinicopathological parameters. Kaplan-Meier analysis generated survival curves, and univariate and multivariate COX regression analyses were conducted to establish a prognostic prediction model.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eCompared with adjacent normal tissues, the expressions of CD133, E-cad, and Ki67 were upregulated in gastric cancer tissues. The high expression of CD133 was associated with the tumor type, and the high expression of Ki67 was related to tumor grading and distant metastasis. Multivariate analysis showed that the depth of invasion, lymph node metastasis, Ki67, and pSmad3L (S204) were independent prognostic risk factors for GC patients. The co-high expression of Ki67 and pSmad3L (S204) predicted a poor prognosis.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eHigh expression of Ki67 and high expression of pSmad3L(S204) are independent risk factors for the prognosis of patients with gastric cancer, and the combined analysis of Ki67 and pSmad3L(S204) can help to improve the risk prediction.\u003c/p\u003e","manuscriptTitle":"Clinical significance of the S204 phosphorylation of the Smad3 protein in combination with Ki67 for the metastasis and prognosis of gastric cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-03 16:23:11","doi":"10.21203/rs.3.rs-7284849/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-31T09:32:39+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-30T05:18:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"153548633963865484294489052258343120804","date":"2025-10-30T01:31:29+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-02T08:26:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"18695255208747477405044734695720036521","date":"2025-09-22T03:37:29+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-22T03:03:56+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-02T10:08:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-19T07:05:19+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-16T15:35:14+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Gastroenterology","date":"2025-08-16T15:31:31+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-gastroenterology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmge","sideBox":"Learn more about [BMC Gastroenterology](http://bmcgastroenterol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmge/default.aspx","title":"BMC Gastroenterology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"47d31f04-f8e1-4e6f-a330-a2aa5ee5c615","owner":[],"postedDate":"October 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-15T16:09:23+00:00","versionOfRecord":{"articleIdentity":"rs-7284849","link":"https://doi.org/10.1186/s12876-025-04485-8","journal":{"identity":"bmc-gastroenterology","isVorOnly":false,"title":"BMC Gastroenterology"},"publishedOn":"2025-12-12 15:59:29","publishedOnDateReadable":"December 12th, 2025"},"versionCreatedAt":"2025-10-03 16:23:11","video":"","vorDoi":"10.1186/s12876-025-04485-8","vorDoiUrl":"https://doi.org/10.1186/s12876-025-04485-8","workflowStages":[]},"version":"v1","identity":"rs-7284849","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7284849","identity":"rs-7284849","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}