Plasma RNA sequencing of extracellular RNAs reveals potential biomarkers for non-small cell lung cancer.

BACKGROUND: Lung cancer is one of the most common malignancies, and it has extremely high incidence and mortality rates. Although there have been many studies focused on lung cancer biomarkers, few have reported the extracellular RNA profiles of lung cancer. In this study, we used RNA-seq technology to analyze extracellular RNAs in low volume peripheral blood plasma; we compared the differentially expressed genes from the plasma of non-small cell lung cancer (NSCLC) patients with that of healthy controls. METHODS: We used RNA-seq technology and bioinformatics to analyze the extracellular RNA (exRNA) sequences of 12 human plasma samples (500 µl per sample), 6 from NSCLC patients and 6 from healthy controls. Subsequently, we used gene ontology (GO) enrichment, KEGG analysis and coexpression experiments to compare the differentially expressed genes (DEGs) and identify tumor biomarkers that were highly correlated with NSCLC. These DEGs were further verified by quantitative PCR. RESULTS: Approximately 20 million clean reads were produced for each plasma sample; 50-80% of the reads aligned to the human references, and hundreds of thousands of reads were counted in each plasma sample. In addition, a total of 640 genes (368 upregulated and 272 downregulated) were differentially expressed between NSCLC plasma and normal plasma. Further, we identified 7 key DEGs that are highly correlated with lung tumorigenesis: COX1, COX2, COX3, ND1, ND2, ND4L, and ATP6. CONCLUSION: exRNA-seq from a small amount (400-500 µl) of plasma opens new possibilities for exploring lung cancer biomarkers in the plasma.