Research progress on the effect of pyroptosis on the occurrence, development, invasion and metastasis of colorectal cancer.

Pyroptosis is a type of programmed cell death mediated by gasdermines (GSDMs). The N-terminal domain of GSDMs forms pores in the plasma membrane, causing cell membrane rupture and the release of cell contents, leading to an inflammatory response and mediating pyrodeath. Pyroptosis plays an important role in inflammatory diseases and malignant tumors. With the further study of pyroptosis, an increasing number of studies have shown that the pyroptosis pathway can regulate the tumor microenvironment and antitumor immunity of colorectal cancer and is closely related to the occurrence, development, treatment and prognosis of colorectal cancer. This review aimed to explore the molecular mechanism of pyroptosis and the role of pyroptosis in the occurrence, development, treatment and prognosis of colorectal cancer (CRC) and to provide ideas for the clinical diagnosis and treatment of CRC.

Exploring the anti-metastatic effects of Astragalus mongholicus Bunge-Curcuma aromatica Salisb. on colorectal cancer: A network-based metabolomics and pharmacology approach.

BACKGROUND: Colorectal cancer (CRC) is a common malignancy that can significantly diminish patients' quality of life. Astragalus mongholicus Bunge-Curcuma aromatica Salisb. (AC) is an ancient Chinese medicinal combination used for the treatment of CRC. However, the core ingredients and targets involved in regulating lipid and amino acid metabolism in CRC remain unknown. We aimed to explore the key components and pharmacological mechanisms of AC in the treatment of CRC through a comprehensive analysis of network metabolomics, network pharmacology, molecular docking, and biological methods. METHODS: Ultra-performance liquid chromatography/mass spectrometry (MS) was used for quality control. Gas chromatography/MS and liquid chromatography/MS were used to detect metabolites in the feces and serum of CRC mice. A network pharmacology approach and molecular docking were used to explore the potential genes involved in the CRC-target-component network. The effect of AC on tumor immunity was investigated using flow cytometry and polymerase chain reaction. RESULTS: AC, high-dose AC, and 5-fluorouracil treatment reduced liver metastasis and tumor mass. Compared with the CRC group, 2 amino acid metabolites and 14 lipid metabolites (LPC, PC, PE) were upregulated and 15 amino acid metabolites and 9 lipid metabolites (TG, PE, PG, 12-HETE) were downregulated. Subsequently, through network analysis, four components and six hub genes were identified for molecular docking. AC can bind to ALDH1B1, ALDH2, CAT, GOT2, NOS3, and ASS1 through beta-Elemene, canavanine, betaine, and chrysanthemaxanthin. AC promoted the responses of M1 macrophages and down-regulated the responses of M2 macrophages, Treg cells, and the gene expression of related factors. CONCLUSION: Our research showed that AC effectively inhibited the growth and metastasis of tumors and regulated metabolism and immunity in a CRC mouse model. Thus, AC may be an effective alternative treatment option for CRC.

Age-related twin-peak prevalence profiles of H. pylori infection, gastritis, GIN and gastric cancer: Analyses of 70,534 patients with gastroscopic biopsies.

OBJECTIVES: H. pylori (Hp) infection has been indicated in the pathogenesis of gastric diseases including gastric cancer (GC). This study aimed at exploring the relationships between Hp infection and gastric diseases including GC in a large dataset of routine patients undergoing gastroscopy. METHODS: From November 2007 to December 2017, 70,534 first-time visiting patients aged 18-94 years with gastroscopic biopsies were histologically diagnosed and analyzed. Patients' data were entered twice in an Excel spreadsheet database and analyzed using the SPSS (version 22.0) software package and statistical significance was defined as P<0.05 for all analyses. RESULTS: The first interesting observation was age-related twin-peak prevalence profiles (TPPs) for Hp infection, gastritis, and advanced diseases with different time spans (TS) between the first and second occurring peaks. Hp infection and gastritis had TPPs occurring at earlier ages than TPPs of gastric introepithelial neoplasia (GIN) and GC. More patients were clustered at the second occurring TPPs. The time spans (TS) from the first occurring peak of Hp infection to the first occurring peaks of other gastric diseases varied dramatically with 0-5 years for gastritis; 5-15 years for GINs, and 5-20 years for GC, respectively. The number of males with Hp infection and gastric diseases, excluding non-atrophic gastritis (NAG), was more than that of females (P<0.001). CONCLUSIONS: We have first observed age-related twin-peak prevalence profiles for Hp infection, gastritis, GIN, and GC, respectively, among a large population of patients undergoing gastroscopy. The second prevalence peak of GC is at ages of 70-74 years indicating that many GC patients would be missed during screening because the cut-off age for screening is 69 years old in China.

A Nomogram Based on Preoperative Clinical Bio-Indicators to Predict 5-year Survivals for Patients with Gastric Cancer After Radical Gastrectomy.

PURPOSE: This study aimed to improve the prediction of postoperative survival outcomes for patients with gastric cancer (GC) using a nomogram based on preoperative bio-indicators. PATIENTS AND METHODS: This retrospective study included 303 GC patients who had undergone radical gastrectomy from 2004 to 2013 at the First Affiliated Hospital, Shihezi University. The patients were followed up for 175 months after surgery and then divided into short-term (n=201) or long-term (n=102) survival groups. We used an expectation-maximization method to fill any missing data from the reviewed patient files. We then employed the Cox proportional hazard regression to identify biochemical markers that could predict 5-year overall survival (OS) as an endpoint among GC patients. Based on the results from the biochemical analysis, we developed a nomogram and assessed its performance and reliability. RESULTS: The variables significantly associated with OS in a multivariate analysis were age, body mass index (BMI), cell differentiation, high-density lipoprotein cholesterol (HDL-C), as well as serum potassium or serum magnesium. Combining all these predictors allowed us to establish a nomogram (C-index=0.701) whose accuracy of predicting survival was higher than the TNM staging system established by the 8th American Joint Committee on Cancer (C-index=0.666; p=0.016). Furthermore, decision curve of this nomogram was shown to have an ideal net clinical benefit rate. CONCLUSION: We have developed an algorithm using preoperative bio-indicators and clinical features to predict prognosis for GC patients. This tool may help clinicians to strategize appropriate treatment options for GC patients prior to surgery.