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Combination anti-PD-1 and anti-CTLA-4 therapy generates waves of clonal responses that include progenitor-exhausted CD8 T cells [dataset 2]

GSE272734 Homo sapiens (human) Single-cell RNA-seq 40 samples Submitted 2024/07/30 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 40 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
40 samples: 8 conditions, mostly with about 5 replicates eachGroups 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.
Paper
Combination anti-PD-1 and anti-CTLA-4 therapy generates waves of clonal responses that include progenitor-exhausted CD8(+) T cellsCancer cell · 2024
Summary (written by the submitters)
Combination checkpoint blockade with anti-PD-1 and anti-CTLA-4 antibodies has shown promising efficacy in melanoma. However, the underlying mechanism in humans remains unclear. We performed RNA+TCR single-cell analysis across time in 36 stage IV melanoma patients treated with anti-PD-1, anti-CTLA-4, or combination therapy. We developed the algorithm Cyclone to track temporal clonal dynamics and underlying cell states.
Read the full summary ↓
Checkpoint blockade induced waves of clonal T cell responses that peaked at distinct timepoints. Combination therapy resulted in greater magnitude of clonal responses at 6 and 9 weeks compared to single-agent therapies, including melanoma-specific CD8 T cells and exhausted CD8 T cell (TEX) clones. Focused analyses of TEX identified that anti-CTLA-4 induced robust expansion and proliferation of progenitor TEX, which synergized with anti-PD-1 to reinvigorate TEX during combination therapy. These next generation immune profiling approaches can guide the selection of drugs, schedule, and dosing for novel combination strategies.
Published in
Combination anti-PD-1 and anti-CTLA-4 therapy generates waves of clonal responses that include progenitor-exhausted CD8(+) T cells
Wang K, Coutifaris P, Brocks D et al. · Cancer cell 2024 · PMID 39214097 · doi:10.1016/j.ccell.2024.08.007
This dataset
Open GSE272734 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 GSE272734_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 PRJNA1138630 and SRA study SRP521306. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39214097) ↗
Study design
8 conditions, mostly with about 5 replicates each
GEX-13-689-wk ×5 GEX-16-2006-wk ×5 GEX-17-3017-wk ×5 GEX-18-3282-wk ×5 TCR-13-689-wk ×5 TCR-16-2006-wk ×5 TCR-17-3017-wk ×5 TCR-18-3282-wk ×5

Supports a between-group comparison across 40 samples.

How we read this: 8 replicated groups read from 40 sample titles; they account for 40 of them. 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
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