GEO series

Tumor exosome integrins determine organotropic metastasis

GSE68919 Homo sapiens (human) RNA-seq (gene expression) 8 samples Submitted 2015/06/17 Platform GPL16791

At a glance

RNA-seq (gene expression) · human · 8 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: 8 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)

Stephen Paget first proposed, in 1889, that organ distribution of metastases is a non-random event, yet metastatic organotropism remains one of the greatest mysteries in cancer biology. Here, we demonstrate that exosomes released by lung-, liver- and brain-tropic tumor cells fuse preferentially with resident cells at their predicted destination, such as fibroblasts and epithelial cells in the lung, Kupffer cells in the liver, and endothelial cells in the brain.

Read the full summary ↓

We found that exosome homing to organ-specific cell types prepares the pre-metastatic niche and that treatment with exosomes derived from lung tropic models can redirect metastasis to the lung. Proteomic profiling of exosomes revealed distinct integrin expression patterns associated with each organ-specific metastasis. Whereas exosomal integrins α6β4 and α6β1 were associated with lung metastasis, exosomal integrins αvβ5 and αvβ3 were linked with liver and brain metastases, respectively. Targeting α6β4 and αvβ5 integrins decreased exosome uptake and metastasis in the lung and liver, respectively. Importantly, we demonstrate that exosome uptake activates a cell-specific subset of S100 family genes, known to support cell migration and niche formation. Finally, our clinical data indicate that integrin-expression profiles in circulating plasma exosomes from cancer patients could be used to predict organ-specific metastasis.

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 GSE68919_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 PRJNA284109 and SRA study SRP058375. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 25985394) ↗

Samples in this study

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+ 8 more — browse all 8 samples with per-sample file links →

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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.