Background: Gastric cancer (GC) is associated with high mortality rates and an unfavorable prognosis at advanced stages. In addition, there are no effective methods for diagnosing gastric cancer at an early stage or for predicting the outcome for the purpose of selecting patient-specific treatment options. Therefore, it is important to investigate new methods for GC diagnosis.
Methodology/principal findings: To facilitate its use in a diagnostic setting, a group of 74 genes with diagnostic and prognostic information was translated into a customized microarray containing a reduced set of 1,042 probes suitable for high throughput processing. In this report, we demonstrate for the first time that the custom mini-array can be used as a reliable diagnostic tool in gastric cancer. With an AUC value of 0.565 (95% CI 0.305-0.825) indicating a perfect test, the sensitivity and specificity of diagnosis from the ROC curve were calculated to be 70% and 80%, respectively.
Conclusions/significance: The data clearly demonstrate the reproducibility and robustness of the small custom-made microarray. The array is an excellent tool for classifying and predicting the outcome of disease in gastric cancer patients.