GEO series

Ionic immune suppression within the tumour microenvironment limits T cell effector function

GSE84996 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2016/08/13 Platform GPL17021

At a glance

RNA-seq (gene expression) · mouse · 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: Mus musculus (mouse)
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)

Tumours progress despite being infiltrated by effector T cells. Tumour necrosis is associated with poor survival in a variety of cancers. Here, we report that that necrosis causes release of an intracellular ion, potassium, into the extracellular fluid of human and mouse tumours. Surprisingly, elevated extracellular potassium ([K+]e) was sufficient to profoundly suppress mouse and human T cell anti-tumour function.

Read the full summary ↓

Elevations in [K+]e acted to acutely impair T cell receptor (TCR) dependent Akt-mTOR phosphorylation and effector function. Potassium mediated suppression of Akt-mTOR signalling and T cell effector function required intact activity of PP2A, a serine/threonine phosphatase. The suppressive effect mediated by elevated [K+]e required a T cell-intrinsic increase in intracellular potassium ([K+]i) and was independent of changes in plasma membrane potential (Vm). Finally, ionic reprogramming of tumour-specific T cells via over-expression of the voltage-gated potassium channel Kv1.3 lowered [K+]i and improved effector functions in vitro and in vivo, with this gain of function being dependent on intact channel function. Consequently, Kv1.3 T cell expression enhanced tumour clearance and the survival of melanoma-bearing mice. These results uncover a previously undescribed ionic checkpoint against T cell function within tumours and identify new strategies for cancer immunotherapy.

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 GSE84996_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 PRJNA335843 and SRA study SRP080338. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 27626381) ↗

Samples in this study

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+ 12 more — browse all 12 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.