Background: Exosomes, endosome-derived membrane microvesicles, contain specific RNA transcripts that are thought to be involved in cell-cell communication. These RNA transcripts have great potential as disease biomarkers. To characterize exosomal RNA profiles systemically, we performed RNA sequencing analysis using three human plasma samples and evaluated the efficacies of small RNA library preparation protocols from three manufacturers. In all we evaluated 14 libraries (7 replicates). Results: From the 14 size-selected sequencing libraries, we obtained a total of 101.8 million raw single-end reads, an average of about 7.27 million reads per library. Sequence analysis showed that there was a diverse collection of the exosomal RNA species among which microRNAs (miRNAs) were the most abundant, making up over 42.32% of all raw reads and 76.20% of all mappable reads. At the current read depth, 593 miRNAs were detectable. The five most common miRNAs (miR-99a-5p, miR-128, miR-124-3p, miR-22-3p, and miR-99b-5p) collectively accounted for 48.99% of all mappable miRNA sequences. MiRNA target gene enrichment analysis suggested that the highly abundant miRNAs may play an important role in biological functions such as protein phosphorylation, RNA splicing, chromosomal abnormality, and angiogenesis. From the unknown RNA sequences, we predicted 185 potential miRNA candidates. Furthermore, we detected significant fractions of other RNA species including ribosomal RNA (9.16% of all mappable counts), long non-coding RNA (3.36%), piwi-interacting RNA (1.31%), transfer RNA (1.24%), small nuclear RNA (0.18%), and small nucleolar RNA (0.01%); fragments of coding sequence (1.36%), 5^′ untranslated region (0.21%), and 3^′ untranslated region (0.54%) were also present. In addition to the RNA composition of the libraries, we found that the three tested commercial kits generated a sufficient number of DNA fragments for sequencing but each had significant bias toward capturing specific RNAs. Conclusions: This study demonstrated that a wide variety of RNA species are embedded in the circulating vesicles. To our knowledge, this is the first report that applied deep sequencing to discover and characterize profiles of plasma-derived exosomal RNAs. Further characterization of these extracellular RNAs in diverse human populations will provide reference profiles and open new doors for the development of blood-based biomarkers for human diseases.

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.

Colon cancer arises from the accumulation of multiple genetic and epigenetic alterations to normal colonic tissue. microRNAs (miRNAs) are small, non-coding regulatory RNAs that post-transcriptionally regulate gene expression. Differential miRNA expression in cancer versus normal tissue is a common event and may be pivotal for tumor onset and progression.

Prostate cancer, a complex disease, can be relatively harmless or extremely aggressive. To identify candidate genes involved in causal pathways of aggressive prostate cancer, we implemented a systems biology approach by combining differential expression analysis and coexpression network analysis to evaluate transcriptional profiles using lymphoblastoid cell lines from 62 prostate cancer patients with aggressive phenotype (Gleason grade ≥ 8) and 63 prostate cancer patients with nonaggressive phenotype (Gleason grade ≤ 5). From 13,935 mRNA genes and 273 microRNAs (miRNA) tested, we identified significant differences in 1,100 mRNAs and 7 miRNAs with a false discovery rate (FDR) of <0.01. We also identified a coexpression module demonstrating significant association with the aggressive phenotype of prostate cancer (P = 3.67 × 10⁻¹¹). The module of interest was characterized by overrepresentation of cell cycle–related genes (FDR = 3.50 × 10⁻⁵⁰). From this module, we further defined 20 hub genes that were highly connected to other genes. Interestingly, 5 of the 7 differentially expressed miRNAs have been implicated in cell cycle regulation and 2 (miR-145 and miR-331-3p) are predicted to target 3 of the 20 hub genes. Ectopic expression of these two miRNAs reduced expression of target hub genes and subsequently resulted in cell growth inhibition and apoptosis. These results suggest that cell cycle is likely to be a molecular pathway causing aggressive phenotype of prostate cancer. Further characterization of cell cycle–related genes (particularly, the hub genes) and miRNAs that regulate these hub genes could facilitate identification of candidate genes responsible for the aggressive phenotype and lead to a better understanding of prostate cancer etiology and progression. [Cancer Res 2009;69(24):9490–7]

Treatment options for metastatic castrate-resistant prostate cancer (mCRPC) are limited and typically are centered on docetaxel-based chemotherapy. We previously reported that elevated miR-375 levels were significantly associated with poor overall survival of mCRPC patients. In this study, we evaluated if miR-375 induced chemo-resistance to docetaxel through regulating target genes associated with drug resistance. We first compared miR-375 expression level between prostate cancer tissues and normal prostate tissues using data from The Cancer Genome Atlas (TCGA). To examine the role of miR-375 in docetaxel resistance, we transfected miR-375 using a pre-miRNA lentiviral vector and examined the effects of exogenously overexpressed miR-375 on cell growth in two prostate cancer cell lines, DU145 and PC-3. To determine the effect of overexpressed miR-375 on tumor growth and chemo-resistance in vivo, we injected prostate cancer cells overexpressing miR-375 into nude mice subcutaneously and evaluated tumor growth rate during docetaxel treatment. Lastly, we utilized qRT-PCR and Western blot assay to examine two miR-375 target genes, SEC23A and YAP1, for their expression changes after miR-375 transfection. By examining 495 tumor tissues and 52 normal tissues from TCGA data, we found that compared to normal prostate, miR-375 was significantly overexpressed in prostate cancer tissues (8.45-fold increase, p value = 1.98E-23). Docetaxel treatment induced higher expression of miR-375 with 5.83- and 3.02-fold increases in DU145 and PC-3 cells, respectively. Interestingly, miR-375 appeared to play a dual role in prostate cancer proliferation. While miR-375 overexpression caused cell growth inhibition and cell apoptosis, elevated miR-375 also significantly reduced cell sensitivity to docetaxel treatment in vitro, as evidenced by decreased apoptotic cells. In vivo xenograft mouse study showed that tumors with increased miR-375 expression were more tolerant to docetaxel treatment, demonstrated by greater tumor weight and less apoptotic cells in miR-375 transfected group when compared to empty vector control group. In addition, we examined expression levels of the two miR-375 target genes (SEC23A and YAP1) and observed significant reduction in the expression at both protein and mRNA levels in miR-375 transfected prostate cancer cell lines. TCGA dataset analysis further confirmed the negative correlations between miR-375 and the two target genes (r = −0.62 and −0.56 for SEC23A and YAP1, respectively; p < 0.0001). miR-375 is involved in development of chemo-resistance to docetaxel through regulating SEC23A and YAP1 expression. Our results suggest that miR-375 or its target genes, SEC23A or YAP1, might serve as potential predictive biomarkers to docetaxel-based chemotherapy and/or therapeutic targets to overcome chemo-resistance in mCRPC stage.