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Plasma extracellular RNA profiles in healthy and cancer patients

GSE71008 Homo sapiens (human) Non-coding RNA profiling 192 samples Submitted 2016/01/29 Platform GPL9052
At a glance

Non-coding RNA profiling · human · 192 samples

What it is
Non-coding RNA profilingLevels of RNAs that do not code for proteins, such as miRNA or lncRNA.
Organism
Homo sapiens (human)
Topic
Prostate cancerThis series is part of our curated briefing on it.
Samples
192 samples
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Summary (written by the submitters)
Extracellular vesicles such as exosomes are selectively enriched in RNA that has potential for use as disease biomarkers. To systemically characterize circulating extracellular RNA profiles, we performed RNA sequencing analysis on plasma extracellular vesicles derived from 192 individuals including 100 colon cancer, 36 prostate cancer and 6 pancreatic cancer patients along with 50 healthy individuals.
Read the full summary ↓
Of ~12.6 million raw reads for each of these subjects, the number of mappable reads aligned to RNA references was ~5.4 million including microRNAs(miRNAs) (~40.4%), piwi-interacting RNAs(piwiRNAs) (~40.0%), pseudo-genes (~3.7%), long noncoding RNAs (lncRNAs) (~2.4%), tRNAs (~2.1%), and mRNAs (~2.1%). To select the best candidates for potential extracellular RNA reference controls, we performed abundant level stability testing and identified a set of miRNAs showing relatively consistent expression. To estimate biological variations, we performed association analysis of expression levels with age and sex in healthy individuals. This analysis showed significant sex association with seven small noncoding RNAs (false discovery rate, or FDR<0.05), while no small noncoding RNAs were statistically associated with age. To identify disease-associated RNA transcripts, we performed analysis of covariance by including disease status, age, sex, RNA isolation and gel size selection dates. We observed a gradual increase of significantly associated RNAs (in particular, miRNAs) with disease advancement as denoted by cancer staging. We found significant association of miR-125a-5p and miR-1246-3p with all cancer types tested (FDR<0.05). Based on the disease associations, we developed cancer type-specific multivariate statistical models to predict disease status with an area under the ROC curve from 0.67 in stage I colon cancer to 0.92 in advanced prostate cancer. To date, this is the largest RNA-seq study to systematically profile extracellular RNA species, which has not only provided a baseline reference profile for circulating extracellular RNA, but also a set of RNA candidates for reference controls and disease biomarkers.
This dataset
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE71008_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Also filed as BioProject PRJNA290097 and SRA study SRP061240. Searching any of these in the dataset finder brings you back here.

Samples in this study

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