Canadian Journal of Gastroenterology and Hepatology

Background. H2.0-like homeobox (HLX) is highly expressed in several hematopoietic malignancies. However, the role of HLX in the carcinogenesis and progression of colorectal cancer (CRC) patients has rarely been reported. Methods. In this study, the data were collected from The Cancer Genome Atlas and Gene Expression Omnibus databases. The diagnostic value of HLX was analyzed by the R package “pROC.” The overall survival was estimated using the “survival” and “survminer” packages. A nomogram was established to predict 1-, 3-, and 5-year overall survival of CRC patients. The CIBERSORT software was employed to calculate the relative proportions of 22 immune cells. Results. HLX expression was downregulated in CRC patients. Remarkably, HLX expression was increased with stage (stage I–stage III) of CRC, and the CRC patients with high HLX expression exhibited a poor prognosis. The promoter methylation level of HLX was prominently increased in CRC samples compared to paracancerous samples. We also found that the six miRNAs target HLX genes, leading to its downregulation, and HLX expression had a negative correlation with its downstream target gene BRI3BP in both CRC and normal samples. Finally, we found that the 12 immune infiltrating cells were observably different between high and low HLX expression groups. The HLX had a significant positive correlation with 8 immune checkpoints (PD-1 (PDCD1), CTLA4, PDL-1 (CD274), PDL-2 (PDCD1LG2), CD80, CD86, LAG3, and TIGIT) expressions. Conclusion. HLX probably played a carcinostasis role in the early stages of CRC but exhibited a cancer-promoting effect in the advanced stages. Meanwhile, HLX could serve as a reliable prognostic indicator for CRC.

Gambogic acid (GA) is a natural xanthonoid secreted by Garcinia hanburyi tree. It possesses anti-cancer activity in various types of cancers. In gastric cancer, it inhibits cell proliferation through increasing apoptosis. However, whether necroptosis is involved in the GA-induced proliferation inhibited in gastric cancer is unknown. In the present study, we found that RIPK1 specific inhibitor necrostatin-1 (Nec-1) attenuated GA-induced proliferation inhibition. GA treatment increased the phosphorylation of necroptosis-related proteins, RIPK1, RIPK3, and MLKL, and their interactions to form the necrosome complex. The effector protein Drp-1 was dephosphorylated by GA treatment. Inhibition of necroptosis by different inhibitors and PGAM5 knockdown attenuated GA-induced cell death in gastric cancer cell lines, thereby attenuating GA-caused cell proliferation inhibition. All the data supported the conclusion that GA could inhibit gastric cancer cell proliferation by inducing necroptosis.

Aim. The present study aimed at investigating associations of the platelet-to-monocyte ratio (PMR), a novel hematological indicator of inflammatory responses with 30-day outcomes in patients with HBV-associated decompensated cirrhosis (HBV-DeCi). Methods. We recruited 329 patients with HBV-DeCi for this retrospective study and extracted baseline clinical data and laboratory characteristics from medical records. Univariate and multivariate analyses were performed to determine major factors influencing 30-day mortality. Receiver operating characteristic curve analysis was performed to compare the predictive values of prognostic markers. Results. During the 30-day follow-up period, 21 (6.4%) patients died. The PMR was significantly different between nonsurvivors and survivors. Lower PMR was found to be associated with an increased risk of 30-day mortality, and PMR (odds ratio: 1.011; 95% CI: 1.003–1.019; ) was found to be an independent predictor of 30-day mortality in patients with HBV-DeCi with a significant predictive value (AUC = 0.826, 95% CI: 0.781–0.865). The combination of PMR and MELD score could improve prognostic accuracy in these patients (AUC = 0.911, 95% CI: 0.876–0.940). Conclusions. Our results demonstrate that low PMR may be an independent predictor of 30-day mortality in patients with HBV-DeCi, and combined with the MELD score, it may be useful to complement other conventional measures to enable effective management of these patients.

Objectives. The rapidly evolving organ failure and high short-run mortality of acute-on-chronic liver failure (ACLF) are inseparable from the role of systemic inflammatory response. S100A8 and S100A9 are associated with the excessive cytokine storm and play a decisive part within the process of inflammation. We aimed to clarify the role of them in predicting prognosis of hepatitis B virus-related ACLF (HBV-ACLF). Methods. S100A8 and S100A9 levels were analyzed in plasma of 187 transplant-free HBV-ACLF patients, 28 healthy controls and 40 chronic hepatitis B (CHB) patients. S100A8 and S100A9 mRNAs were checked in liver samples from 32 HBV-ACLF patients with liver transplantation, 19 patients undergoing surgery for hepatic hemangioma and 10 CHB patients with needle biopsy. Results. The plasma levels of the S100A8 and S100A9 were higher in HBV-ACLF patients than in CHB patients (S100A8 :  and S100A9 : ) and healthy controls (S100A8 :  and S100A9 : ), and similar results were obtained for mRNA expression. Moreover, both proteins were related to ACLF grade, different types of organ failure, and infection, and they correlated with other prognostic scoring systems. S100A8 and S100A9 can dependently predict 28/90-day mortality (28-day: S100A8: hazard ratio (HR): 1.027; 95% confidence interval (CI): 1.007–1.048; , S100A9 : HR: 1.009; 95% CI: 1.001–1.017; , 90-day: S100A8 : HR: 1.023; 95% CI: 1.011–1.035; , S100A9 : HR: 1.008; 95% CI: 1.004–1.012; and ). Among all of the scoring systems, the combined scoring model (S100A8 and S100A9 jointly with the Chronic Liver Failure-Consortium Organ Failure score (CLIF-C OFs)) displayed the highest area under the receiver operating curve (0.923 (95% CI, 0.887–0.961)) in the prediction of 90-day mortality. Conclusions. S100A8 and S100A9 are promising biomarkers for the analysis of risk stratification and prognosis in ACLF patients. In addition, combining them with the CLIF-C OFs may better predict the prognosis of ACLF.

Cardiovascular diseases are currently one of the most important causes of morbidity and mortality in liver transplant patients over the long term. Therefore, evaluating prognostic factors for cardiovascular events (CVEs) in this population is essential for taking preventive measures. The aim of this study was to identify the impact of diabetes and other metabolic disorders on CVEs in liver transplant patients. Three hundred fifty-six liver transplant recipients who survived at least 6 months after surgery were enrolled. Patients were followed for a median time of 118 months (12–250 months). All cardiovascular events were carefully recorded and detailed in the patients’ charts. Demographic data, diabetes, hypertension, dyslipidemia, weight changes, and a diagnosis of metabolic syndrome both before and after transplantation were noted to assess their possible relationship with CVE. The presence of a diagnosis of metabolic-associated fatty liver disease (MAFLD) was also evaluated. Immunosuppressive therapy was included in the analysis. Diabetes mellitus (DM), especially when present before transplantation, was strongly associated with CVEs (hazard risk HR 3.10; 95% confidence interval CI: 1.60–6.03). Metabolic syndrome was found to be associated with CVEs in univariate analysis (HR 3.24; 95% CI: 1.36–7.8), while pretransplantation and de novo MAFLD were not. Immunosuppressive therapy had no influence on predisposing transplanted patients to CVEs during follow-up. Further prospective studies may be useful in investigating the risk factors for CVEs after liver transplantation and improving the long-term survival of transplant patients.

Background. Vibration-controlled transient elastography (VCTA) and controlled attenuation parameter (CAP) are used more frequently to diagnose liver fibrosis and steatosis among nonalcoholic fatty liver disease patients. However, limited robust data are available on the clinical variables strongly related to these disorders and who needs to be referred for screening. Methods. We used the National Health and Nutritional Examination Survey 2017-2018 database to identify the clinical predictors strongly related to liver steatosis and advanced fibrosis. Baseline comparisons among these groups were made based on widely accepted cutoffs. Linear and logistic regressions were performed to identify the associations between the clinical variables and liver steatosis and fibrosis. We used adaptive lasso regression, gradient-boosted model, and decision trees to determine clinical variables strongly related to these outcomes. A Naïve Byes classifier and decision trees were used to calculate the predicted probabilities of liver steatosis and fibrosis. Results. 32% of our population had evidence of liver steatosis using 294 dB/m as a cutoff. An increase in age, serum triglyceride, and body mass index were associated with a statistically significant increase in liver steatosis; in contrast, females had statistically significantly lower values for liver steatosis by 15 points in the multivariable linear regression model. Serum LDL, smoking, and systolic and diastolic blood pressure are poorly associated with liver steatosis in the adaptive lasso regression. On the other hand, sex, tobacco use, metabolic energy expenditure, and serum triglyceride are the least associated with liver fibrosis based on decision tree analysis and a gradient-boosted model. In decision trees, people with a body mass index above 30 and HbA1c above 5.7 have a 72% likelihood of liver steatosis compared to 14% for people with a body mass index below 30. On the other hand, people with a body mass index above 41 have a 38% likelihood of liver fibrosis. Conclusion. Body mass index, hemoglobin A1c, serum triglyceride level, sex, and age could provide a good prediction for liver steatosis, while body mass index, blood pressure, platelet counts, hemoglobin A1c, serum LDL, or HDL are highly associated with liver fibrosis and should be used as an initial screening tool prior referral for VCTE/CAP.