Exosomal microRNA signature from plasma-derived extracellular vesicles in gastric cancer

Abstract

AbstractBackgroundGastric cancer is a heterogeneous pathology that represents the fifth most frequent malignancy in the world, with more than 750,000 deaths by 2020. With significant repercussions in public health, this pathology lacks biomarkers for early diagnosis, with endoscopy biopsy being the golden test for its detection. In the exploration of new strategies to control gastric cancer in recent years, liquid biopsy appears as a potential source of biomarkers using non-invasive procedures.MethodsHere we present the characterization of miRNAs contained in plasma-derived exosomes from patients with gastric cancer. Extracellular vesicles (EVs) were isolated using size-exclusion chromatography (SEC) and their characterization was performed by electron microscopy, protein expression, and nanoparticle analysis techniques. Total RNA from isolated exosomes was obtained for small RNA-seq analysis.ResultsTranscriptomic miRNA data were used to identify differentially expressed miRNAs between patients with benign and malignant gastric diseases, which resulted in a molecular signature of nine miRNAs, that were used in a regression model to classify individuals as either having benign or malignant disease. Further, we compared benign-malignant patients at different stages of gastric cancer, and we detected 15 differentially expressed miRNAs. Among these 15 miRNAs, miR-92a-3p, miR451a, and miR126-3p were identified as winners due to their clinical and regulatory relevance.ResultsOur results offer relevant information of a Colombian case study allowing us to propose three transcriptomic gastric cancer biomarkers in liquid biopsy.Graphical AbstractSummaryEVs are structures surrounded by a lipid bilayer that facilitate intercellular communication by transporting biomolecules commonly referred to as part of liquid biopsy. In this study, we examine the miRNAs contents of plasma isolated EVs from patients with both benign gastric diseases and gastric cancer to identify potential biomarkers for gastric cancer.