GEO series

TIGIT and PD-L1 co-blockade promotes clonal expansion of multipotent, non-exhausted antitumor T cells by facilitating co-stimulation

GSE220901 Mus musculus (mouse) RNA-seq (gene expression) 168 samples Submitted 2024/12/31 Platform GPL17021Platform GPL21103

At a glance

RNA-seq (gene expression) · mouse · 168 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: 168 samples: 156 distinct titles, 12 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.
Paper: TIGIT and PD-L1 co-blockade promotes clonal expansion of multipotent, non-exhausted antitumor T cells by facilitating co-stimulationNature cancer · 2024

Summary (written by the submitters)

Blockade of the immune checkpoints PD-1 and TIGIT has demonstrated activity in mouse tumor models and human patients with cancer. Although these coinhibitory receptors can restrict signaling in CD8+ T cells by regulating their associated co-stimulatory receptors CD28 and CD226, the functional consequences of combining PD-1 and TIGIT blockade remain poorly characterized.

Read the full summary ↓

In mouse tumor models, we show that combination blockade elicited CD226-driven clonal expansion of tumor antigen-specific CD8+ T cells. The expanded clones emerged from a population of stem-like cells in draining lymph nodes, entering the blood as a previously unidentified single-phenotype, multiclonal population. Upon reaching the tumor, these transiting cells expanded further and differentiated into effector or exhausted T cells, with combination blockade restricting entry into the exhaustion pathway by favoring co-stimulation. Thus, PD-1 and TIGIT inhibition helps shape the repertoire of tumor-reactive CD8+ T cells in draining lymph nodes and determines their immunological fate in the tumor to enhance therapeutic benefit. Analysis of clinical trial samples suggests a similar mechanism may also occur in patients with cancer.

Published in

TIGIT and PD-L1 co-blockade promotes clonal expansion of multipotent, non-exhausted antitumor T cells by facilitating co-stimulation

Nutsch K, Banta KL, Wu TD et al. · Nature cancer 2024 · PMID 39681653 · doi:10.1038/s43018-024-00870-6

This dataset

Open GSE220901 in finder → Find more mouse 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 GSE220901_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 PRJNA911822 and SRA study SRP412889. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39681653) ↗

Study design

156 distinct titles, 12 of them repeated

Pooled mice S1-3, blood day 0, scRNA-seq, seq… ×2 Pooled mice S1-3, blood day 0, ADT-seq and CI… ×2 Pooled mice S1-3, blood day 0, scTCR-seq, seq… ×2 Pooled mice S4-7, blood day 0, scRNA-seq, seq… ×2 Pooled mice S4-7, blood day 0, ADT-seq and CI… ×2 Pooled mice S4-7, blood day 0, scTCR-seq, seq… ×2 Pooled mice S1-3, blood day 7, scRNA-seq, seq… ×2 Pooled mice S1-3, blood day 7, ADT-seq and CI… ×2 +4 more

Supports a case/control comparison: 57 samples read as cases, 15 as controls.

How we read this: Read from 168 sample titles: 156 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

GSM6827309 Control, replicate 1, tumor, scRNA-seq
GSM6827310 Control, replicate 1, tumor, ADT-seq and CITE-seq
GSM6827311 Control, replicate 1, tumor, scTCR-seq
GSM6827312 Control, replicate 2, tumor, scRNA-seq
GSM6827313 Control, replicate 2, tumor, ADT-seq and CITE-seq
GSM6827314 Control, replicate 2, tumor, scTCR-seq
GSM6827316 Control, replicate 4, tumor, scRNA-seq
GSM6827317 Control, replicate 4, tumor, ADT-seq and CITE-seq
GSM6827318 Control, replicate 4, tumor, scTCR-seq
GSM6827319 Control, replicate 5, tumor, scRNA-seq
GSM6827320 Control, replicate 5, tumor, ADT-seq and CITE-seq
GSM6827321 Control, replicate 5, tumor, scTCR-seq
GSM6827322 Control, replicate 3, tumor, scRNA-seq
GSM6827323 Control, replicate 3, tumor, ADT-seq and CITE-seq
GSM6827325 Control, replicate 3, tumor, scTCR-seq
GSM6827326 Anti-PDL1, replicate 1, tumor, scRNA-seq
GSM6827327 Anti-PDL1, replicate 1, tumor, ADT-seq and CITE-seq
GSM6827328 Anti-PDL1, replicate 1, tumor, scTCR-seq
GSM6827329 Anti-PDL1, replicate 2, tumor, scRNA-seq
GSM6827330 Anti-PDL1, replicate 2, tumor, ADT-seq and CITE-seq
GSM6827331 Anti-PDL1, replicate 2, tumor, scTCR-seq
GSM6827333 Anti-PDL1, replicate 3, tumor, scRNA-seq
GSM6827334 Anti-PDL1, replicate 3, tumor, ADT-seq and CITE-seq
GSM6827335 Anti-PDL1, replicate 3, tumor, scTCR-seq
GSM6827336 Anti-PDL1, replicate 4, tumor, scRNA-seq
GSM6827337 Anti-PDL1, replicate 4, tumor, ADT-seq and CITE-seq
GSM6827338 Anti-PDL1, replicate 4, tumor, scTCR-seq
GSM6827339 Anti-PDL1, replicate 5, tumor, scRNA-seq
GSM6827340 Anti-PDL1, replicate 5, tumor, ADT-seq and CITE-seq
GSM6827342 Anti-PDL1, replicate 5, tumor, scTCR-seq
GSM6827343 Anti-TIGIT, replicate 2, tumor, scRNA-seq
GSM6827344 Anti-TIGIT, replicate 2, tumor, ADT-seq and CITE-seq
GSM6827345 Anti-TIGIT, replicate 2, tumor, scTCR-seq
GSM6827346 Anti-TIGIT, replicate 3, tumor, scRNA-seq
GSM6827347 Anti-TIGIT, replicate 3, tumor, ADT-seq and CITE-seq
GSM6827348 Anti-TIGIT, replicate 3, tumor, scTCR-seq
GSM6827349 Anti-TIGIT, replicate 1, tumor, scRNA-seq
GSM6827350 Anti-TIGIT, replicate 1, tumor, ADT-seq and CITE-seq
GSM6827351 Anti-TIGIT, replicate 1, tumor, scTCR-seq
GSM6827353 Anti-TIGIT, replicate 4, tumor, scRNA-seq

+ 128 more — browse all 168 samples with per-sample file links →

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GSE271663 Tumor-Suppressing Multi-Enterobacteria enhance the anti-PD-1/PD-L1 efficacy in microsatellite stable colorectal cancer 36 samples shares pd-l1
GSE291836 Radiation and anti-PD-L1 synergize by stimulating a stem-like T cell population in the tumor-draining lymph node 19 samples shares pd-l1
GSE291126 Tractable mouse TNBC models capture the heterogeneous tumor immune microenvironment and adaptation to PD-L1 blockade 6 samples shares pd-l1
GSE253444 Combining TIGIT blockade with MDSC inhibition hinders breast cancer bone metastasis by activating anti-tumor immunity 55 samples shares tigit
GSE263274 Insights into the mechanisms of serplulimab: a distinctive anti-PD-1 monoclonal antibody, in combination with a TIGIT or LAG3 inhibitor in preclinical tumor immunotherapy studies 45 samples shares tigit
GSE292146 Tractable mouse TNBC models capture the heterogeneous tumor immune microenvironment and adaptation to PD-L1 blockade 38 samples shares pd-l1

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