Genetic variant of cyclooxygenase-2 in gastric cancer: More inflammation and susceptibility.

Gastric cancer accounts for the majority cancer-related deaths worldwide. Although various methods have considerably improved the screening, diagnosis, and treatment of gastric cancer, its incidence is still high in Asia, and the 5-year survival rate of advanced gastric cancer patients is only 10%-20%. Therefore, more effective drugs and better screening strategies are needed for reducing the incidence and mortality of gastric cancer. Cyclooxygenase-2 (COX-2) is considered to be the key inducible enzyme in prostaglandins (PGs) synthesis, which is involved in multiple pathways in the inflammatory response. For example, inflammatory cytokines stimulate innate immune responses via Toll-like receptors and nuclear factor-kappa B to induce COX-2/PGE2 pathway. In these processes, the production of an inflammatory microenvironment promotes the occurrence of gastric cancer. Epidemiological studies have also indicated that non-steroidal anti-inflammatory drugs can reduce the risk of malignant tumors of the digestive system by blocking the effect of COX-2. However, clinical use of COX-2 inhibitors to prevent or treat gastric cancer may be limited because of potential side effects, especially in the cardiovascular system. Given these side effects and low treatment efficacy, new therapeutic approaches and early screening strategies are urgently needed. Some studies have shown that genetic variation in COX-2 also play an important role in carcinogenesis. However, the genetic variation analysis in these studies is incomplete and isolated, pointing out only a few single nucleotide polymorphisms (SNPs) and the risk of gastric cancer, and no comprehensive study covering the whole gene region has been carried out. In addition, copy number variation (CNV) is not mentioned. In this review, we summarize the SNPs in the whole COX-2 gene sequence, including exons, introns, and both the 5' and 3' untranslated regions. Results suggest that COX-2 does not increase its expression through the CNV and the SNPs in COX-2 may serve as the potential marker to establish risk stratification in the general population. This review synthesizes emerging insights of COX-2 as a biomarker in multiple studies, summarizes the association between whole COX-2 sequence variation and susceptibility to gastric cancer, and discusses the future prospect of therapeutic intervention, which will be helpful for early screening and further research to find new approaches to gastric cancer treatment.

Two-level analysis of risk factors for ischemic cardiovascular disease-A community-based study from Henan, China.

BACKGROUND: Ischemic cardiovascular disease (ICVD) has high incidence and high mortality worldwide. The studies of its risk factors were mostly concentrated on an individual level, and there are scarce studies on the two levels of risk factors which include individual and regional levels. METHODS: The data were obtained from a community-based study in 4 cities and 6 counties of Henan, China. Risk factors were initially screened by one-way analysis of variance or chi-square test. Then, they were re-analyzed using a two-level logistic regression model to construct a personal disease risk prediction model. RESULTS: A two-level ICVD risk prediction model comprised 11 variables: age, body mass index (BMI), family history of hypertension, marital status, salt intake, smoking, moderate recreational physical activities, alcohol intake, and education at the individual level. Among the unalterable risk factors, for each additional unit of age and family history of hypertension, the risk of ICVD increased by 1.08 and 1.07 units [ß95% confidence interval (95%CI): 0.99-1.16, 0.97-1.17, both p < 0.0001], respectively. Among the modifiable risk factors, the ICVD risk increases by 0.67, 0.27, and 0.28 units for each additional unit of BMI, marital status, and education (ß95%CI: 0.60-0.74, p < 0.0001; ß95%CI: 0.14-0.40, p = 0.0012, 0.18-0.37, p = 0.0001). CONCLUSIONS: The two-level ICVD risk model can predict that the risk of one person for ICVD will be lower if one is younger, thinner, and well-educated without a family history of hypertension. Overall, the two-level ICVD risk prediction model gets a better fitting effect than the single-level model.