The incidence of gastric cancer (GC) is extremely high in East Asia. GC is also one of the most common and lethal forms of cancer from a global perspective. However, to date, we have not been able to determine one or several genes as biomarkers in the diagnosis of GC and have also been unable to identify the genes which are important in the therapy of GC. In this study, we analyzed all genome-wide expression profiling arrays uploaded onto the Gene Expression Omnibus (GEO) database to filtrate the differentially expressed genes (DEGs) between normal stomach tissues and GC tissues. GSE13911, GSE19826 and GSE79973 were based on the GPL570 platform, and GSE29272 was based on the GPL96 platform. We screened out the DEGs from the two platforms and by selecting the intersection of these two platforms, we identified the common DEGs in the sequencing data from different laboratories. Finally, we obtained 3 upregulated and 34 downregulated DEGs in GC from 384 samples. As the number of downregulated DEGs was greater than that of the upregulated DEGs, functional analysis and pathway enrichment analysis were performed on the downregulated DEGs. Through our analysis, we identified the most significant genes associated with GC, such as secreted phosphoprotein 1 (SPP1), sulfatase 1 (SULF1), thrombospondin 2 (THBS2), ATPase H+/K+ transporting beta subunit (ATP4B), gastric intrinsic factor (GIF) and gastrokine 1 (GKN1). The prognostic power of these genes was corroborated in the Oncomine database and by Kaplan-Meier plotter (KM-plotter) analysis. Moreover, gastric acid secretion, collecting duct acid secretion, nitrogen metabolism and drug metabolism were significantly related to GC. Thus, these genes and pathways may be potential targets for improving the diagnosis and clinical effects in patients with GC.

Non-invasive prenatal testing (NIPT) for common fetal trisomies is effective. However, the usefulness of cell-free DNA testing to detect other chromosomal abnormalities is poorly understood. We analyzed the positive rate at different read depths in next-generation sequencing (NGS) and identified a strategy for fetal copy number variant (CNV) detection in NIPT. Pregnant women who underwent NIPT by NGS at read depths of 4–6 M and fetuses with suspected CNVs were analyzed by amniocentesis and chromosomal microarray analysis (CMA). These fetus samples were re-sequenced at a read depth of 25 M and the positive detection rate was determined. With the increase in read depth, the positive CNV detection rate increased. The positive CNV detection rates at 25 M with small fragments were higher by NGS than by karyotype analysis. Increasing read depth in NGS improves the positive CNV detection rate while lowering the false positive detection rate. NIPT by NGS may be an accurate method of fetal chromosome analysis and reduce the rate of birth defects.