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Sci Rep. 2016 Jan 20;6:19413. doi: 10.1038/srep19413.

Plasma extracellular RNA profiles in healthy and cancer patients.

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Department of Pathology and MCW Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA.
Center for Biotherapy, the Second Affiliated Hospital of Harbin Medical University, Harbin, Postcode 150086, China.
Department of Internal Medicine, Medical College of Wisconsin, Milwaukee, WI 53226, USA.
Department of Surgery, Medical College of Wisconsin, Milwaukee, WI 53226, USA.
Department of Oncology, Mayo Clinic, Rochester, MN 55905, USA.
Departments of Transplantation and Cancer Biology, Mayo Clinic, Jacksonville, FL 32224, USA.


Extracellular vesicles are selectively enriched in RNA that has potential as disease biomarkers. To systemically characterize circulating extracellular RNA (exRNA) profiles, we performed RNA sequencing analysis on plasma extracellular vesicles derived from 50 healthy individuals and 142 cancer patients. Of ~12.6 million raw reads for each individual, the number of mappable reads aligned to RNA references was ~5.4 million including miRNAs (~40.4%), piwiRNAs (~40.0%), pseudo-genes (~3.7%), lncRNAs (~2.4%), tRNAs (~2.1%), and mRNAs (~2.1%). By expression stability testing, we identified a set of miRNAs showing relatively consistent expression, which may serve as reference control for exRNA quantification. By performing multivariate analysis of covariance, we identified significant associations of these exRNAs with age, sex and different types of cancers. In particular, down-regulation of miR-125a-5p and miR-1343-3p showed an association with all cancer types tested (false discovery rate <0.05). We developed multivariate statistical models to predict cancer status with an area under the curve from 0.68 to 0.92 depending cancer type and staging. This is the largest RNA-seq study to date for profiling exRNA species, which has not only provided a baseline reference profile for circulating exRNA, but also revealed a set of RNA candidates for reference controls and disease biomarkers.

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