Serum Circulating mRNA Panel for the Early Detection of Gastric Cancer: A Potential Biomarker Test

Abstract

Circulating free messenger RNAs (cfmRNAs) in serum have emerged as potential noninvasive biomarkers for cancer diagnosis, including gastric cancer (GC). This study utilized RNA‐sequencing data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to identify a training set of 100 differentially expressed genes (DEGs) specific to GC patients. Employing a support vector machine (SVM) classification, we narrowed down the candidate gene set to 23, which was further refined to 4 genes–DMBX1, EVX1, MAL, and PIWIL1–after validation through reverse transcription quantitative polymerase chain reaction (RT‐qPCR). The diagnostic performance of mRNA panels, particularly the combinations of DMBX1 with EVX1 and EVX1 with PIWIL1, was exceptional, achieving area under the curve (AUC) values of 0.800, sensitivities of 90.0 %, and specificities of 80.0 %. The accuracy of these biomarkers was corroborated through various machine learning algorithms, underscoring their robust diagnostic potential. The findings of this study are poised to significantly influence clinical practice by providing robust tools for early GC detection. As these biomarkers undergo further investigation and validation, they hold promise to become integral to the diagnostic for GC.