These findings may be useful to stratify GC patients who are less likely to benefit from DNA demethylating-based therapies. TNFAIP3 intronic-specific CpG site demethylation contributes to gene upregulation in GC.
NRN1 promoter hypomethylation contributes to gene upregulation in advanced GC. Higher expression of NRN1 and TNFAIP3 is associated with advanced gastric cancer (GC). The identification of demethylated activated genes in GC may be useful in clinical practice, stratifying patients who are less likely to benefit from 5-AZAdC-based therapies. Reduced NRN1 promoter methylation was associated with III/IV TNM stage tumours (P = 0.03) and the presence of Helicobacter pylori infection (P = 0.02). We showed that increased NRN1 and TNFAIP3 expression seems to be regulated by DNA demethylation in GC samples: inverse correlations between the mRNA and DNA methylation levels in the promoter of NRN1 (P < 0.05) and the intron of TNFAIP3 (P < 0.05) were detected. Increased expression of NRN1 and TNFAIP3 was associated with advanced tumours (P < 0.05). We identified 83 candidate genes modulated by DNA methylation in GC cell lines. Among the genes identified in this analysis, we selected NRN1 and TNFAIP3 to be evaluated for gene expression by RT-qPCR and DNA methylation by bisulfite DNA next-generation sequencing in 43 and 52 pairs of GC and adjacent non-neoplastic tissue samples, respectively. Therefore, we compared the gene expression profile of 5-AZAdC-treated and untreated GC cell lines by a microarray assay.
Epigenetic manipulation of GC cell lines is a useful tool to better understand gene expression regulatory mechanisms for clinical applications. The use of 5-Aza-2′-deoxycytidine (5-AZAdC) was approved for the treatment of myelodysplastic syndromes, and this drug can treat solid tumours at low doses. Very few therapeutic options are currently available in this neoplasia. Gastric cancer (GC) is the third leading cause of cancer-related death worldwide. EPIC-TABSAT is freely accessible to all users at. Together with the computation of target-specific epialleles it is useful in validation, research, and routine diagnostic environments. The graphical user interface offers an unprecedented way to interpret TBS data alone or in combination with array-based methylation studies. The tool can handle multiple targets as well as multiple sequencing files in parallel and covers the complete data analysis workflow from calculation of quality metrics to methylation calling and interactive result presentation. Consequently, we have developed EPIC-TABSAT, a user-friendly web-based application for the analysis of targeted sequencing data that additionally allows the integration of array-based methylation results. Yet, an easy-to-use tool for the analysis of TBS data in combination with array-based methylation results has been missing. In addition to chip and sequencing based epigenome wide methylation profiling methods, targeted bisulfite sequencing (TBS) has been established as a cost-effective approach for routine diagnostics and target validation applications. DNA methylation is one of the major epigenetic modifications and has frequently demonstrated its suitability as diagnostic and prognostic biomarker.