Transcriptomics-driven non-invasive liquid biopsy for diagnosing peritoneal lavage cytology-positive gastric cancer.

Gastric cancer remains a leading cause of cancer-related mortality, with positive peritoneal lavage cytology (PLC) indicating early peritoneal metastasis and poor prognosis. However, conventional imaging and laparoscopy lack sufficient sensitivity for early detection. In this study, six mRNA biomarkers (NOX1, CHEK1, BUB1, NEK2, PRC1, SLCO1B3) were identified through transcriptomic analysis and integrated with clinical features to develop a Risk Stratification Assessment (RSA) model for predicting PLC-positive status. The six-mRNA panel was significantly upregulated in PLC-positive tissues and peripheral blood. The RSA model demonstrated strong diagnostic performance, with AUCs of 0.869 and 0.856 in training and validation cohorts, respectively, and 0.874 and 0.912 in peripheral blood analysis. Moreover, high-risk patients classified by the model had significantly lower 5-year overall survival rates than low-risk patients. This transcriptomics-based RSA model offers a non-invasive, accurate, and clinically meaningful tool for early identification of PLC-positive gastric cancer, potentially surpassing the sensitivity of current diagnostic methods. This study includes prospective analyses from two registered clinical trials: Chinese Clinical Trial Registry, ChiCTR1800014817 (registration date: January 8, 2018; http://www.chictr.org.cn) and ClinicalTrials.gov, NCT03718624 (registration date: October 26, 2018; https://clinicaltrials.gov/ct2/show/NCT03718624).