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RNA G-quadruplexes cause eIF4A-dependent oncogene translation in cancer

GSE56887 Homo sapiens (human) RNA-seq (gene expression) 10 samples Submitted 2014/07/27 Platform GPL11154
At a glance

RNA-seq (gene expression) · human · 10 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
10 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)
The translational control of oncoprotein expression is implicated in many cancers. Here we report an eIF4A/DDX2 RNA helicase-dependent mechanism of translational control that contributes to oncogenesis and underlies the anticancer effects of Silvestrol and related compounds. For example, eIF4A promotes T-ALL development in vivo and is required for leukaemia maintenance.
Read the full summary ↓
Accordingly, inhibition of eIF4A with Silvestrol has powerful therapeutic effects in vitro and in vivo. We use transcriptome-scale ribosome footprinting to identify the hallmarks of eIF4A-dependent transcripts. These include 5'UTR sequences such as the 12-mer guanine quartet (CGG)4 motif that can form RNA G-quadruplex structures. Notably, among the most eIF4A-dependent and Silvestrol-sensitive transcripts are a number of oncogenes, super-enhancer associated transcription factors, and epigenetic regulators. Hence, the 5'UTRs of selected cancer genes harbour a targetable requirement for the eIF4A RNA helicase.
This dataset
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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.

Series matrix ↓
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 GSE56887_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA244865 and SRA study SRP041255. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 25079319) ↗
Samples in this study

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