Mining exosomal genes for pancreatic cancer targets

Abstract

Background: Exosomes, cell-derived vesicles encompassing lipids, DNA, proteins coding genes and noncoding RNAs (ncRNAs) are present in diverse body fluids. They offer novel biomarker and drug therapy potential for diverse diseases, including cancer. Materials and Methods: Using gene ontology, exosomal genes database and GeneCards metadata analysis tools, a database of cancer-associated protein coding genes and ncRNAs (n=2,777) was established. Variant analysis, expression profiling and pathway mapping were used to identify putative pancreatic cancer exosomal gene candidates. Results: Five hundred and seventy-five proteincoding genes, 26 RNA genes and one pseudogene directly associated with pancreatic cancer were identified in the study. Nine open reading frames (ORFs) encompassing enzymes, apoptosis and transcriptional regulators, and secreted factors and five cDNAs (enzymes) emerged from the analysis. Among the ncRNA class, 26 microRNAs (miRs), one pseudogene, one long noncoding RNA (LNC) and one antisense gene were identified. Furthermore, 22 exosomeassociated protein-coding targets (a cytokine, enzymes, membrane glycoproteins, receptors, and a transporter) emerged as putative leads for pancreatic cancer therapy. Seven of these protein-coding targets are FDA-approved and the drugs-based on these could provide repurposing opportunities for pancreatic cancer. Conclusion: The database of exosomal genes established in this study provides a framework for developing novel biomarkers and drug therapy targets for pancreatic cancer.