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Updated: Nov 11, 2025

Genome-Wide Analysis of DNA Methylation in Gastrointestinal Cancer
Published on: September 18, 2020
Distinct genomic profile in h. pylori-associated gastric cancer
Xiaochen Zhang1, Fang Liu2, Hua Bao3
1Department of Medical Oncology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
Abstract:
Gastric cancer is one of the most common and deadly cancer types. Currently, four subtypes have been identified with unique molecular alterations: Epstein-Barr virus (EBV)-positive, microsatellite instability (MSI), chromosomal instability (CIN), and genomic stable (GS) tumors. Notably, many gastric tumors are associated with the bacterium Helicobacter pylori but the genomic landscape of this subgroup of tumors remains largely unknown. Targeted sequencing covering 425 genes was performed retrospectively on 1703 gastric tumor tissues and matched normal blood samples. Nonsynonymous mutations, copy-number variation (CNV), and MSI status were called from human DNA reads; nonhuman DNA reads were mapped to NCBI microbial reference genome using Kraken and significant species were identified. Overall, 37 (2.76%) from a total of 1703 samples were EBV-positive, 200 (11.74%) samples were H. pylori-positive, and 10 samples were positive for both. Among the rest, 59 (3.46%) samples were MSI, 380 (22.31%) were CIN, and 1017 (59.72%) were GS. Most of the 200 H. pylori-positive samples tend to be genome stable (85.5%, p < 0.001) and microsatellite stable (95%, p = 0.04). Compared to 1017 GS tumors, mutations in AKT3, EPAS1, MLH1, and BKT and amplifications of NFE2L2, TERC, MCL1, and TOP1 were significantly enriched in H. pylori-positive tumors. And compared to EBV-positive tumors, mutations in PIK3CA, ARID1A, and PTEN were significantly depleted in H. pylori-positive subtype while TP53 mutations were enriched. This study characterized the unique genomic landscape of H. pylori-positive gastric tumors using targeted panel sequencing. The successful identification of DNA reads from infectious agents in tumor samples indicates that deep sequencing is a promising way to uncover characteristics of microbial environment in tumors.
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