← BioTransfer GEO Dataset Finder
GEO series

The translational landscape of mTOR signaling steers cancer initiation and metastasis

GSE35469 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2012/02/28 Platform GPL9115
At a glance

RNA-seq (gene expression) · human · 12 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)
Topic
Prostate cancerThis series is part of our curated briefing on it.
Samples
12 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 mammalian target of rapamycin (mTOR) kinase is a master regulator of protein synthesis that couples nutrient sensing to cell growth and cancer. However, the downstream translationally regulated nodes of gene expression that may direct cancer development are poorly characterized. Employing ribosome profiling we uncover specialized translation of the prostate cancer genome by oncogenic mTOR signaling, revealing a remarkably specific repertoire of genes involved in cell proliferation, metabolism, and invasion.
Read the full summary ↓
We extend these findings by functionally characterizing a class of translationally controlled pro-invasion mRNAs that we show direct prostate cancer invasion and metastasis downstream of oncogenic mTOR signaling. We further develop a clinically relevant ATP site inhibitor of mTOR, INK128, which reprograms this gene expression signature with therapeutic benefit for prostate cancer metastasis, for which there is presently no cure. Together, these findings significantly extend our understanding of how the “cancerous” translation machinery steers specific cancer cell behaviors and may be therapeutically targeted.
This dataset
Open GSE35469 in finder → Find more human RNA-seq datasets → Prostate cancer landscape →
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 GSE35469_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 PRJNA152347 and SRA study SRP010679. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 22367541) ↗
Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 12 more — browse all 12 samples with per-sample file links →

More Prostate cancer datasets

Search all human RNA-seq datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.