Introduction: The early diagnosis and detection could greatly improve the clinical outcome of gastric cancer (GC) patients. However, the non-invasive biomarkers for GC detection remain to be identified.

Method: We used online databases (GEPIA, UALCAN, Kaplan-Meier plotter, TIMER, and MEXPRESS) to explore the association between H19 or metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) expression in tissues and the occurrence, development, prognosis, the levels of immune cell infiltration, and methylation of GC; the correlation between mRNA expression and DNA methylation levels of genes were also examined. Methylation levels of H19 or MALAT1 in peripheral blood were compared between 150 GC patients and 100 healthy controls (HCs). Predictive nomograms were constructed among female and male groups for GC diagnosis. The calibration curves, Hosmer-Lemeshow test, and decision curve analysis were also used to examine the nomograms' predictive ability and clinical values.

Results: Using multiple online databases, we found that the mRNA expressions of H19 and MALAT1 in tissues were related to the occurrence of GC, and such expressions were associated with immune cell infiltration of GC and negatively correlated with DNA methylation levels of H19 and MALAT1. H19 gene, H19C island, and MALAT1B island, as well as 20 CpG sites were hypermethylated in peripheral blood of GC patients compared with HCs; similar results were also found in female and male groups ( < .05 for all). The combination of H19c3, H19c4, MALAT1b12, and age, as well as the combination of H19b7, H19c1, H19c5, and age in the nomograms could distinguish GC patients from HCs in the female group and male group, respectively.

Conclusion: We found statistically significant hypermethylation of H19 and MALAT1 promoters in GC patients, and meaningful sensitivity and specificity of MALAT1 and H19 methylation in discriminating GC and HCs were observed in both female and male groups, which indicates that the peripheral blood-based DNA methylation of H19 and MALAT1 could act as potential non-invasive biomarkers for the diagnosis of GC.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8504648PMC
http://dx.doi.org/10.1177/10732748211043667DOI Listing

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