Dataset Information

Statins Attenuate Helicobacter pylori CagA Translocation and Reduce Incidence of Gastric Cancer: In Vitro and Population-Based Case-Control Studies.

ABSTRACT: Gastric cancer is the second leading cause of cancer-related death worldwide. The correlation of Helicobacter pylori and the etiology of gastric cancer was substantially certain. Cholesterol-rich microdomains (also called lipid rafts), which provide platforms for signaling, are associated with H. pylori-induced pathogenesis leading to gastric cancer. Patients who have been prescribed statins, inhibitors of 3-hydroxy-3-methyl glutaryl coenzyme A (HMG-CoA) reductase, have exhibited a reduced risk of several types of cancer. However, no studies have addressed the effect of statins on H. pylori-associated gastric cancer from the antineoplastic perspective. In this study, we showed that treatment of gastric epithelial cells with simvastatin reduced the level of cellular cholesterol and led to attenuation of translocation and phosphorylation of H. pylori cytotoxin-associated gene A (CagA), which is recognized as a major determinant of gastric cancer development. Additionally, a nationwide case-control study based on data from the Taiwanese National Health Insurance Research Database (NHIRD) was conducted. A population-based case-control study revealed that patients who used simvastatin exhibited a significantly reduced risk of gastric cancer (adjusted odds ratio (OR) = 0.76, 95% confidence interval (CI) = 0.70-0.83). In patients exhibiting H. pylori infection who were prescribed simvastatin, the adjusted OR for gastric cancer was 0.25 (95% CI = 0.12-0.50). Our results combined an in vitro study with a nationwide population analysis reveal that statin use might be a feasible approach to prevent H. pylori-associated gastric cancer.

SUBMITTER: Lin CJ

PROVIDER: S-EPMC4701455 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Statins Attenuate Helicobacter pylori CagA Translocation and Reduce Incidence of Gastric Cancer: In Vitro and Population-Based Case-Control Studies.

Lin Chun-Jung CJ Liao Wei-Chih WC Lin Hwai-Jeng HJ Hsu Yuan-Man YM Lin Cheng-Li CL Chen Yu-An YA Feng Chun-Lung CL Chen Chih-Jung CJ Kao Min-Chuan MC Lai Chih-Ho CH Kao Chia-Hung CH

PloS one 20160105 1

Gastric cancer is the second leading cause of cancer-related death worldwide. The correlation of Helicobacter pylori and the etiology of gastric cancer was substantially certain. Cholesterol-rich microdomains (also called lipid rafts), which provide platforms for signaling, are associated with H. pylori-induced pathogenesis leading to gastric cancer. Patients who have been prescribed statins, inhibitors of 3-hydroxy-3-methyl glutaryl coenzyme A (HMG-CoA) reductase, have exhibited a reduced risk ...[more]

PMID: 26730715

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Project description:BackgroundAs a marker of Helicobacter pylori, Cytotoxin-associated gene A (cagA) has been revealed to be the major virulence factor causing gastroduodenal diseases. However, the molecular mechanisms that underlie the development of different gastroduodenal diseases caused by cagA-positive H. pylori infection remain unknown. Current studies are limited to the evaluation of the correlation between diseases and the number of Glu-Pro-Ile-Tyr-Ala (EPIYA) motifs in the CagA strain. To further understand the relationship between CagA sequence and its virulence to gastric cancer, we proposed a systematic entropy-based approach to identify the cancer-related residues in the intervening regions of CagA and employed a supervised machine learning method for cancer and non-cancer cases classification.MethodologyAn entropy-based calculation was used to detect key residues of CagA intervening sequences as the gastric cancer biomarker. For each residue, both combinatorial entropy and background entropy were calculated, and the entropy difference was used as the criterion for feature residue selection. The feature values were then fed into Support Vector Machines (SVM) with the Radial Basis Function (RBF) kernel, and two parameters were tuned to obtain the optimal F value by using grid search. Two other popular sequence classification methods, the BLAST and HMMER, were also applied to the same data for comparison.ConclusionOur method achieved 76% and 71% classification accuracy for Western and East Asian subtypes, respectively, which performed significantly better than BLAST and HMMER. This research indicates that small variations of amino acids in those important residues might lead to the virulence variance of CagA strains resulting in different gastroduodenal diseases. This study provides not only a useful tool to predict the correlation between the novel CagA strain and diseases, but also a general new framework for detecting biological sequence biomarkers in population studies.

Dataset Information

Statins Attenuate Helicobacter pylori CagA Translocation and Reduce Incidence of Gastric Cancer: In Vitro and Population-Based Case-Control Studies.

Publications

Statins Attenuate Helicobacter pylori CagA Translocation and Reduce Incidence of Gastric Cancer: In Vitro and Population-Based Case-Control Studies.

Similar Datasets

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