Background: Extracellular vesicles (EVs) contain a rich cargo of different RNA species with specialized functions and clinical applications. However, the landscape and characteristics of extracellular vesicle long RNA (exLR) in human blood remain largely unknown.
Methods: We presented an optimized strategy for exLR sequencing (exLR-seq) of human plasma. The sample cohort included 159 healthy individuals, 150 patients with cancer (5 cancer types), and 43 patients with other diseases. Bioinformatics approaches were used to analyze the distribution and features of exLRs. Support vector machine algorithm was performed to construct the diagnosis classifier, and diagnostic efficiency was evaluated by ROC analysis.
Results: More than 10000 exLRs, including mRNA, circRNA, and lncRNA, were reliably detected in each exLR-seq sample from 1-2 mL of plasma. We observed that blood EVs contain a substantial fraction of intact mRNAs and a large number of assembling spliced junctions; circRNA was also enriched in blood EVs. Interestingly, blood exLRs reflected their tissue origins and the relative fractions of different immune cell types. Additionally, the exLR profile could distinguish patients with cancer from healthy individuals. We further showed that 8 exLRs can serve as biomarkers for hepatocellular carcinoma (HCC) diagnosis with high diagnostic efficiency in training [area under the curve (AUC) = 0.9527; 95% CI, 0.9170-0.9883], validation cohort (AUC = 0.9825; 95% CI, 0.9606-1), and testing cohort (AUC = 0.9627; 95% CI, 0.9263-0.9991).
Conclusions: In summary, this study revealed abundant exLRs in human plasma and identified diverse specific markers potentially useful for cancer diagnosis.
© 2019 American Association for Clinical Chemistry.