Exosomes, which are nanosized endocytic vesicles that are secreted by most cells, contain an abundant cargo of different RNA species that can modulate the behavior of recipient cells and may be used as circulating biomarkers for diseases. Here, we develop a web-accessible database (http://www.exoRBase.org), exoRBase, which is a repository of circular RNA (circRNA), long non-coding RNA (lncRNA) and messenger RNA (mRNA) derived from RNA-seq data analyses of human blood exosomes. Experimental validations from the published literature are also included. exoRBase features the integration and visualization of RNA expression profiles based on normalized RNA-seq data spanning both normal individuals and patients with different diseases. exoRBase aims to collect and characterize all long RNA species in human blood exosomes. The first release of exoRBase contains 58 330 circRNAs, 15 501 lncRNAs and 18 333 mRNAs. The annotation, expression level and possible original tissues are provided. exoRBase will aid researchers in identifying molecular signatures in blood exosomes and will trigger new exosomal biomarker discovery and functional implication for human diseases.

DNA modifications such as 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) are epigenetic marks known to affect global gene expression in mammals. Given their prevalence in the human genome, close correlation with gene expression and high chemical stability, these DNA epigenetic marks could serve as ideal biomarkers for cancer diagnosis. Taking advantage of a highly sensitive and selective chemical labeling technology, we report here the genome-wide profiling of 5hmC in circulating cell-free DNA (cfDNA) and in genomic DNA (gDNA) of paired tumor and adjacent tissues collected from a cohort of 260 patients recently diagnosed with colorectal, gastric, pancreatic, liver or thyroid cancer and normal tissues from 90 healthy individuals. 5hmC was mainly distributed in transcriptionally active regions coincident with open chromatin and permissive histone modifications. Robust cancer-associated 5hmC signatures were identified in cfDNA that were characteristic for specific cancer types. 5hmC-based biomarkers of circulating cfDNA were highly predictive of colorectal and gastric cancers and were superior to conventional biomarkers and comparable to 5hmC biomarkers from tissue biopsies. Thus, this new strategy could lead to the development of effective, minimally invasive methods for diagnosis and prognosis of cancer from the analyses of blood samples.

BACKGROUND:Predicting survival is uniquely difficult in patients with pancreatic cancer who receive chemotherapy. The authors developed a systemic inflammation response index (SIRI) based on peripheral neutrophil, monocyte, and lymphocyte counts and evaluated the ability of the SIRI to predict the survival of patients with pancreatic cancer who received chemotherapy. METHODS: The SIRI was developed in a training set of 177 patients who had advanced pancreatic cancer and received palliative chemotherapy. The ability of the SIRI to predict a patient's survival after chemotherapy was validated in 2 independent cohorts (n 5 397). RESULTS: Compared with patients who had an SIRI <1.8, patients in the training cohort who had an SIRI 1.8 had a shorter time to progression (TTP) (hazard ratio [HR], 2.348; 95% confidence interval, 1.559-3.535; P 5 .003) and shorter overall survival (OS) (HR, 2.789; 95% confidence interval, 1.897-4.121; P < .001). Comparable TTP and OS findings were observed in 2 independent validation cohorts. Multivariate analysis confirmed that the SIRI was an independent prognostic factor for both TTP and OS. In addition, compared with no change, an increase in the SIRI at week 8 was associated with poor TTP and OS, whereas a decrease in the SIRI was associated with improved outcomes. In addition, high SIRI scores were correlated with higher serum levels of interleukin 10, C-C motif chemokine ligand 17 (CCL17), CCL18, and CCL22 and with a shortened TTP. CONCLUSIONS: The SIRI can be used to predict the survival of patients with pancreatic adenocarcinomas who receive chemotherapy, potentially allowing clinicians to improve treatment outcomes by identifying candidates for aggressive therapy. Cancer 2016;122:2158-67.

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.