Work

Novel miRNA set for screening gastric cancer with high sensitivity: an ROC analysis of 6,997 samples

Year: 2025

Type: article

Abstract: Aims Cancer screening is essential for reducing GC-associated deaths. Nonetheless, implementing population-based screening strategies poses challenges. In this study, a comprehensive receiver operating characteristic (ROC) analysis was conducted on 2565 microRNAs (miRNAs) from 6997 samples to identify a classifier for GC screening.Method First, batch effects were corrected across the five Gene Expression Omnibus Series (GSE) datasets. Second, a predictive model was established using the incidence method. Finally, this model was validated using randomly selected datasets, all datasets after batch effect removal, and each of the datasets separately.Results Six miRNAs, namely miR-1290, miR-5100, miR-1343-3p, miR-8073, miR-4706, and miR-4787-3p were identified, with an area under the ROC curve (AUC) of 0.990 ± 0.002, 0.993 ± 0.002, 0.996 ± 0.004, 0.978 ± 0.010, 0.957 ± 0.015, and 0.969 ± 0.015, respectively. The miRNA set obtained by combining the six miRNAs yielded an AUC of 0.997 ± 0.001, which was higher than that of the six individual miRNAs (p < 0.001). Validation across the total dataset and five GSE datasets (GSE106817, GSE112264, GSE113486, GSE113740, and GSE164174) yielded AUCs of 0.997, 0.999, 1.000, 1.000, 0.996, and 0.994, respectively.Conclusion The novel miRNA set comprising miR-1290, miR-5100, miR-1343-3p, miR-8073, miR-4706, and miR-4787-3p holds promise as a diagnostic classifier for GC screening.

Source: Biomarkers in Medicine

DOI: 10.1080/17520363.2025.2600246