FFPE RNA-Seq of early gastric cancer lesions
This study aimed to identify and validate a gene expression signature for the early detection of gastric cancer (GC) and the risk stratification of metachronous gastric lesions (MGLs) in an intermediate-risk European population. RNA sequencing was performed on formalin-fixed paraffin-embedded (FFPE) gastric mucosa samples (n=54), comprising non-tumor and early tumor tissues, including low-grade dysplasia, high-grade dysplasia, and early adenocarcinoma. A machine learning framework (tidymodels) was applied to select candidate genes, which were subsequently validated by RT-qPCR. A logistic regression model incorporating six genes showed high discriminatory power for early gastric lesions. The model was further tested for its potential to predict MGL development and for non-invasive application in saliva. This RNA-Seq dataset underpins the discovery and development of a clinically actionable diagnostic signature for early gastric neoplasia.