The loss-of-function variants are thought to be associated with inflammation in the stomach. We here aimed to evaluate the extent and role of methylation at the SSTR2 promoter in inflammation and gastric tumor formation. A whole-genome bisulfite sequencing analysis revealed that the SSTR2 promoter was significantly hypermethylated in gastric tumors, dysplasia, and intestinal metaplasia compared to non-tumor tissues from patients with gastric cancer. Using public data, we confirmed SSTR2 promoter methylation in primary gastric tumors and intestinal metaplasia, and even aged gastric mucosae infected with Helicobacter pylori, suggesting that aberrant methylation is initiated in normal gastric mucosa. The loss-of-function of SSTR2 in SNU638 cell-induced cell proliferation in vitro, while stable transfection of SSTR2 in AGS and MKN74 cells inhibited cell proliferation and tumorigenesis in vitro and in vivo. As revealed by a comparison of target genes differentially expressed in these cells with hallmark molecular signatures, inflammation-related pathways were distinctly induced in SSTR2-KO SNU638 cell. By contrast, inflammation-related pathways were inhibited in AGS and MKN74 cells ectopically expressing SSTR2. Collectively, we propose that SSTR2 silencing upon promoter methylation is initiated in aged gastric mucosae infected with H. pylori and promotes the establishment of an inflammatory microenvironment via the intrinsic pathway. These findings provide novel insights into the initiation of gastric carcinogenesis.
Objectives: Gastric cancer (GC) is the fourth most common cancer worldwide, with the highest incidence and mortality regardless of sex. Despite technological advances in diagnosing and treating gastric cancer, GC still has high incidence and mortality rates. Therefore, continuous research is needed to overcome GC. In various studies, cell lines are used to find and verify the cause of specific diseases. Large-scale genomic studies such as ENCODE and Roadmap epigenomic projects provide multiomics data from various organisms and samples. However, few multi-omics data for gastric tissues and cell lines have been generated. Therefore, we performed RNA-seq, Exome-seq, and ChIP-seq with several gastric cell lines to generate a multi-omics data set in gastric cancer. Data description: Multiomic data, such as RNA-seq, Exome-seq, and ChIP-seq, were produced in gastric cancer and normal cell lines. RNA-seq data were generated from nine GC and one normal gastric cell line, mapped to a human reference genome (hg38) using the STAR alignment tool, and quantified with HTseq. Exome sequence data were produced in nine GC and two normal gastric lines. Sequenced reads were mapped and processed using BWA-MEM and GATK, variants were called by stralka2, and annotation was performed using ANNOVAR. Finally, for the ChIP-seq, nine GC cell lines and four GC cell lines were used in two experimental sets; chip-seq was performed to confirm changes in H3K4me3 and H3K27me3. Data was mapped to human reference hg38 with BWA-MEM, and peak calling and annotation were performed using the Homer tool. Since these data provide multi-omics data for GC cell lines, it will be useful for researchers who use the GC cell lines to study.