Objective:To investigate the expression of the B cell ectopic gene 2 (BTG2) in the pancreatic cancer tissue and analyze its relationship with the clinicopathological features and prognosis.Methods:46 pairs of pancreatic cancer tissues and corresponding adjacent tissues kept in paraffin in the pathology department, and 9 fresh pancreatic cancer tissues and corresponding adjacent tissues resected by surgery in Department of Pancreatic Surgery of Sinopharm Dongfeng General Hospital from June 2015 to December 2020 were collected. BTG2 gene expression in 46 pairs of pancreatic cancer tissues and corresponding adjacent tissues were detected by immunohistochemical staining, and high and low BTG2 expression groups were divided. BTG2 gene expression in 9 fresh pancreatic cancer tissues and corresponding adjacent tissues were detected by RT-PCR. The correlation between BTG2 protein expression level and clinicopathological features was analyzed. Furthermore, the survival curve and death risk curve were drawn using the Kaplan-Meier method, and the Cox regression hazards model was applied for the univariate and multivariate analysis of the factors affecting the prognosis of pancreatic cancer.Results:29 of 46 (63.04%) pancreatic cancer tissues had high BTG2 expression, and 38(82.61%) of corresponding adjacent tissues had high BTG2 expression; and BTG2 high expression rate of adjacent tissues was significantly higher than that of cancer tissues. Three out of 9 pancreatic cancer tissues were highly differentiated, and six cases had medium-and low differentiation. The BTG2 expression of highly differentiated pancreatic carcinoma was significantly higher than that of moderately and poorly differentiated carcinoma tissues [(0.66±0.07 vs 0.24±0.18); the expression level of adjacent tissues was significantly higher than that of cancer tissues (1.00±0.00 vs 0.38±0.30), and all differences were statistically significant (all P values <0.001). Low BTG2 expression in pancreatic cancer was associated with low tumor differentiation and vascular invasion (all P values <0.05), but was not correlated with tumor location, volume, lymph node metastasis, CA19-9 level and postoperative liver metastasis. The median survival of high BTG2 expression group was significantly longer than that of low BTG2 expression group (525 d vs 266 d, P<0.001). Among patients with survival time ≥300 d, the survival time was significantly higher in the high BTG2 expression group than in the BTG2 low expression group (616±135d vs 426±113 d), and the difference was statistically significant ( P<0.001). Among patients with survival time <300 d, there was no significant difference between BTG2 high and low expression group. The results of the univariate analysis showed that tumor differentiation degree, vascular invasion, BTG2 expression, CA19-9 levels, and postoperative liver metastasis were all associated with the prognosis of pancreatic cancer. The results of the multivariate analysis showed that BTG2 expression level ( HR=2.572, 95% CI1.140-5.802, P=0.023), vascular invasion ( HR=0.023, 95% CI0.072-0.572, P=0.003) and postoperative liver metastasis ( HR=0.240, 95% CI0.102-0.564, P<0.001) were independent risk factors affecting the prognosis of patients with pancreatic cancer. Conclusions:BTG2 expression in pancreatic cancer tissues was significantly lower than that in adjacent tissues, and its low expression was associated with strong aggressiveness, low differentiation degree and poor prognosis of pancreatic cancer. The effect of BTG2 on the prognosis in pancreatic cancer patients was mainly in the long term.

Background Heavy metal exposure may be associated with the risk of metabolic syndrome (MetS) and serum uric acid. The role of serum uric acid in the relationship between heavy metal exposure and MetS is currently unclear. Objective To evaluate the relationships of heavy metal exposure with MetS and serum uric acid, and to quantify the role of serum uric acid in the relationship. Methods In 2021, convenience sampling was used to select 571 local adults in Liuzhou, Guangxi. Demographic characteristics, lifestyle habits, and physiological and biochemical indicators were collected through questionnaire surveys and physical examinations. Fasting blood and mid-stream morning urine were also collected. The concentrations of 16 heavy metals in urine were measured using inductively coupled plasma mass spectrometry. Least absolute shrinkage and selection operator (LASSO) regression was employed to identify heavy metals associated with MetS. Logistic regression and linear regression models were employed to evaluate the association between the selected heavy metals and MetS as well as serum uric acid. Bayesian kernel machine regression (BKMR) model was utilized to assess the impact of combined exposures to multiple metals on the risk of MetS and identify the main effect metals. Generalized structural equation model was used to evaluate potential mediating effect of serum uric acid on the relationship between heavy metal exposure and MetS. Results The LASSO regression identified a total of 9 heavy metals that were associated with MetS. The logistic regression revealed a positive correlation between zinc and copper in urine and MetS (P _trend<0.05), while vanadium showed a negative correlation with MetS (P _trend<0.05). Compared to the low concentration groups, the high concentration groups of zinc (OR=2.37, 95%CI: 1.33, 4.20) and copper (OR=2.29, 95%CI: 1.26, 4.18) had an increased risk of MetS, while the high concentration group of vanadium showed a decreased risk of MetS (OR=0.47, 95%CI: 0.27, 0.84). The main effect metals identified by the BKMR model were consistent with the results of logistic regression. The linear regression analysis demonstrated an association between urinary zinc and vanadium concentrations and serum uric acid levels (P _trend<0.05). Compared to the low concentration group, the high concentration group of zinc showed an increase in serum uric acid level (β=0.07, 95%CI: 0.03, 0.11), while the high concentration group of vanadium showed a decrease in serum uric acid level (β=-0.06, 95%CI: -0.09, -0.02). The mediation analysis revealed that serum uric acid played a mediating role in the relationship between urinary zinc and vanadium concentrations and MetS, with mediation proportions of 8.33% and 16.67%, respectively. Conclusion Exposure to heavy metals zinc, copper, and vanadium are closely associated with MetS. Zinc and vanadium exposures are correlated with serum uric acid levels, and serum uric acid plays a partial mediating role in the relationship between zinc and vanadium exposures and MetS.