Dataset Information

Three-dimensional combined biomarkers assay could improve diagnostic accuracy for gastric cancer.

ABSTRACT: So far, stomach-specific biomarkers, gastric cancer(GC)-related environmental factors, and cancer-associated biomarkers are three major classes of serological biomarkers with GC warning potential, joint detection of which is expected to increase the diagnosis efficiency. We investigated whether the combination of serum pepsinogens(PGs), IgG anti-Helicobacter pylori (HpAb), and osteopontin (OPN) can be used as a panel for GC diagnose. Serum was collected from 365 GC patients and 729 healthy individuals,furtherly 332 cases and 332 age- and sex-matched controls were selected for the matched analysis. Serum levels were measured by ELISA. Logistic regression and receiver operator characteristic curve (ROC) were used to assess the associations of biomarkers with GC and the discriminative performance of biomarkers for GC. The area under ROC from three-dimensional combination of PGI/II-HpAb-OPN (0.826) was significantly higher than two-dimensional combination of PGI/II-HpAb (0.786, P?

SUBMITTER: Sun L

PROVIDER: S-EPMC5599671 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Three-dimensional combined biomarkers assay could improve diagnostic accuracy for gastric cancer.

Sun Liping L Tu Huakang H Chen Tiejun T Yuan Quan Q Liu Jingwei J Dong Nannan N Yuan Yuan Y

Scientific reports 20170914 1

So far, stomach-specific biomarkers, gastric cancer(GC)-related environmental factors, and cancer-associated biomarkers are three major classes of serological biomarkers with GC warning potential, joint detection of which is expected to increase the diagnosis efficiency. We investigated whether the combination of serum pepsinogens(PGs), IgG anti-Helicobacter pylori (HpAb), and osteopontin (OPN) can be used as a panel for GC diagnose. Serum was collected from 365 GC patients and 729 healthy indiv ...[more]

PMID: 28912586

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Project description:BackgroundGastric cancer (GC) is one of the most common cancers all over the world, causing high mortality. Gastric cancer screening is one of the effective strategies used to reduce mortality. We expect that good biomarkers can be discovered to diagnose and treat gastric cancer as early as possible.MethodsWe download four gene expression profiling datasets of gastric cancer (GSE118916, GSE54129, GSE103236, GSE112369), which were obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between gastric cancer and adjacent normal tissues were detected to explore biomarkers that may play an important role in gastric cancer. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of overlap genes were conducted by the Metascape online database; the protein-protein interaction (PPI) network was constructed by the STRING online database, and we screened the hub genes of the PPI network using the Cytoscape software. The survival curve analysis was conducted by km-plotter and the stage plots of hub genes were created by the GEPIA online database. PCR, WB, and immunohistochemistry were used to verify the expression of hub genes. A neural network model was established to quantify the predictors of gastric cancer.ResultsThe relative expression level of cadherin-3 (CDH3), lymphoid enhancer-binding factor 1 (LEF1), and matrix metallopeptidase 7 (MMP7) were significantly higher in gastric samples, compared with the normal groups (p<0.05). Receiver operator characteristic (ROC) curves were constructed to determine the effect of the three genes' expression on gastric cancer, and the AUC was used to determine the degree of confidence: CDH3 (AUC = 0.800, P<0.05, 95% CI =0.857-0.895), LEF1 (AUC=0.620, P<0.05, 95%CI=0.632-0.714), and MMP7 (AUC=0.914, P<0.05, 95%CI=0.714-0.947). The high-risk warning indicator of gastric cancer contained 8<CDH3<15 and 10<expression of LEF1<16.ConclusionsCDH3, LEF1, and MMP7 can be used as candidate biomarkers to construct a neural network model from hub genes, which may be helpful for the early diagnosis of gastric cancer.

Dataset Information

Three-dimensional combined biomarkers assay could improve diagnostic accuracy for gastric cancer.

Publications

Three-dimensional combined biomarkers assay could improve diagnostic accuracy for gastric cancer.

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