Dataset Information

Helicobacter pylori CagA induces tumor suppressor gene hypermethylation by upregulating DNMT1 via AKT-NF?B pathway in gastric cancer development.

ABSTRACT: Methylation of CpG islands in tumor suppressor gene prompter is one of the most characteristic abnormalities in Helicobacter pylori (HP)-associated gastric carcinoma (GC). Here, we investigated the pathogenic and molecular mechanisms underlying hypermethylation of tumor suppressor genes in HP induced GC development. We found that tumor suppressor genes hypermethylation, represented by MGMT, positively correlated with CagA in clinical specimens, gastric tissues from HP infected C57 mice and GC cell lines transfected by CagA or treated by HP infection. CagA enhanced PDK1 and AKT interaction and increased AKT phosphorylation. The P-AKT subsequent activated NF?B, which then bound to DNMT1 promoter and increased its expression. Finally, the upregulated DNMT1 promoted tumor suppressor genes hypermethylation with MGMT as a representative. In conclusion, CagA increased tumor suppressor genes hypermethylation via stimulating DNMT1 expression through the AKT-NF?B pathway.

SUBMITTER: Zhang BG

PROVIDER: S-EPMC4891084 | biostudies-other | 2016 Mar

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Helicobacter pylori CagA induces tumor suppressor gene hypermethylation by upregulating DNMT1 via AKT-NFκB pathway in gastric cancer development.

Zhang Bao-gui BG Hu Lei L Zang Ming-de MD Wang He-xiao HX Zhao Wei W Li Jian-fang JF Su Li-ping LP Shao Zhifeng Z Zhao Xiaodong X Zhu Zheng-gang ZG Yan Min M Liu Bingya B

Oncotarget 20160301 9

Methylation of CpG islands in tumor suppressor gene prompter is one of the most characteristic abnormalities in Helicobacter pylori (HP)-associated gastric carcinoma (GC). Here, we investigated the pathogenic and molecular mechanisms underlying hypermethylation of tumor suppressor genes in HP induced GC development. We found that tumor suppressor genes hypermethylation, represented by MGMT, positively correlated with CagA in clinical specimens, gastric tissues from HP infected C57 mice and GC ce ...[more]

PMID: 26848521

Similar Datasets

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

Helicobacter pylori CagA induces tumor suppressor gene hypermethylation by upregulating DNMT1 via AKT-NF?B pathway in gastric cancer development.

Publications

Helicobacter pylori CagA induces tumor suppressor gene hypermethylation by upregulating DNMT1 via AKT-NFκB pathway in gastric cancer development.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets