GEO series

Mitochondrial potential as a biomarker of T cell fitness and function in cancer immunotherapy

GSE315510 Homo sapiens (human) Single-cell RNA-seq 30 samples Submitted 2026/03/25 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 30 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism: Homo sapiens (human)
Samples: 30 samples: 24 distinct titles, 6 of them repeatedGroups are read from the sample names, not from the paper. Check the list below.
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)

Checkpoint inhibitors have transformed cancer treatment, yet predicting responses remains challenging. Mitochondrial quality decreases in tumor infiltrating lymphocytes and correlates with impaired anti-tumor immunity in animal models. Mitochondrial membrane potential (MMP) increases with T cell activation but may also indicate cellular dysfunction.

Read the full summary ↓

Here we assessed the MMP of tumor-associated T cells as an indicator of cell phenotypes and immunotherapy responses in Non-Small Cell Lung Carinoma and clear cell Renal Cell Carcinoma patients. Primary tumors were collected followed by analysis of peripheral blood mononuclear cells (PBMC) prior to and after three weeks on treatment with immune checkpoint inhibition (ICI). PBMC T cells were analyzed for MMP using tetramethylrhodamine ethyl ester (TMRE) and sorted into high and low populations. TCRβ and single cell RNA sequencing of primary tumors identified and characterized peripheral blood T cell clones associated with the tumor microenvironment. As anticipated, ICI therapy increased the frequency of effector T cells in patients who experienced clinical benefit. TMREhigh peripheral blood T cells with tumor-matching TCRβ sequences had elevated oxidative phosphorylation gene signatures. Gene signatures of stress and exhaustion, such as Tigit and Cmc1, were also elevated in the TMREhigh CD8 T cell populations while gene expression patterns in TMRElow cells suggested mitochondrial fitness and cell longevity. Importantly, clinical benefit from ICI was negatively correlated with the TMREhigh CD8 T cell gene expression signature. These findings highlight the presence of a T cell population of with elevated MMP that correlates with T cell exhaustion-like states and failed response to immunotherapy.

This dataset

Open GSE315510 in finder → Find more human RNA-seq datasets →

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 GSE315510_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1398172 and SRA study SRP659727. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

24 distinct titles, 6 of them repeated

Lung, Partial disease, Pre-treatment, TMRE hi… ×2 Lung, Partial disease, Pre-treatment, TMRE lo… ×2 Lung, Partial disease, Post-treatment initiat… ×2 Lung, Partial disease, Post-treatment initiat… ×2 Lung, Stable disease, Pre-treatment, TMRE hig… ×2 Lung, Stable disease, Post-treatment initiati… ×2

How we read this: Read from 30 sample titles: 24 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

GSM9429755 Kidney, Progessive disease, Stable disease, Pre-treatment, TMRE low
GSM9429756 Kidney, Progessive disease, Stable disease, Pre-treatment, TMRE high
GSM9429757 Kidney, Progessive disease, Stable disease, Post-treatment initiation, TMRE low
GSM9429758 Kidney, Progessive disease, Stable disease, Post-treatment initiation, TMRE high
GSM9429759 Kidney, Mixed disease, Progressive disease, Pre-treatment, TMRE low
GSM9429760 Kidney, Mixed disease, Progressive disease, Pre-treatment, TMRE high
GSM9429761 Kidney, Mixed disease, Partial disease, Post-treatment initiation, TMRE low
GSM9429762 Kidney, Mixed disease, Partial disease, Post-treatment initiation, TMRE high
GSM9429763 Kidney, Partial disease Pre-treatment, Progressive disease Post-treatment initiation, TMRE low
GSM9429764 Kidney, Partial disease Pre-treatment, Progressive disease Post-treatment initiation, TMRE high
GSM9429765 Lung, Partial disease, Pre-treatment, TMRE high, Patient 1
GSM9429766 Lung, Partial disease, Pre-treatment, TMRE low, Patient 1
GSM9429767 Lung, Partial disease, Post-treatment initiation, TMRE high, Patient 1
GSM9429768 Lung, Partial disease, Post-treatment initiation, TMRE low, Patient 1
GSM9429769 Lung, Stable disease, Pre-treatment, TMRE high, Patient 1
GSM9429770 Lung Stable disease, Pre-treatment, TMRE low, Patient 1
GSM9429771 Lung, Stable disease, Post-treatment initiation, TMRE high, Patient 1
GSM9429772 Lung, Stable disease, Post-treatment initiation, TMRE low, Patient 1
GSM9429773 Lung, Progressive disease, Pre-treatment, TMRE high
GSM9429774 Lung, Progressive disease, Pre-treatment, TMRE low
GSM9429775 Lung, Progressive disease, Post-treatment initiation, TMRE high
GSM9429776 Lung, Progressive disease, Post-treatment initiation, TMRE low
GSM9429777 Lung, Partial disease, Pre-treatment, TMRE high, Patient 2
GSM9429778 Lung, Partial disease, Pre-treatment, TMRE low, Patient 2
GSM9429779 Lung, Partial disease, Post-treatment initiation, TMRE high, Patient 2
GSM9429780 Lung, Partial disease, Post-treatment initiation, TMRE low, Patient 2
GSM9429781 Lung, Stable disease, Pre-treatment, TMRE high, Patient 2
GSM9429782 Lung, Stable disease, Pre-treatment, TMRE low, Patient 2
GSM9429783 Lung, Stable disease, Post-treatment initiation, TMRE High, Patient 2
GSM9429784 Lung, Stable disease, Post-treatment initiation, TMRE low, Patient 2

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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.