GEO series

Coactivation of innate immune suppressive cells induces acquired resistance against cancer immunotherapy targeting the innate immune system [TME RNA-seq]

GSE281466 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2025/01/15 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 18 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: 18 samples: 6 conditions, mostly in triplicateGroups 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: Coactivation of innate immune suppressive cells induces acquired resistance against combined TLR agonism and PD-1 blockadeScience translational medicine · 2025

Summary (written by the submitters)

Immune checkpoint blockade therapy has been successfully applied in clinical settings as a standard therapy for many cancer types, but its clinical efficacy is restricted to patients with immunologically hot tumors. Various strategies to modify the tumor microenvironment (TME), such as Toll-like receptor (TLR) agonists, have been explored but have not been successful.

Read the full summary ↓

Here, we identified a mechanism of acquired resistance to combination treatment consisting of an agonist for multiple TLRs, OK-432 (Picibanil), and PD-1 blockade. Adding the TLR agonist failed to convert the TME from immunogenically cold to hot. The combination treatment did not augment antitumor immunity, particularly CD8+ T cell responses, in multiple animal models. The failure was attributed to the coactivation of innate suppressive cells, such as CD11b+ Gr1+ Ly6C- Ly6G+ myeloid-derived suppressor cells (MDSCs) expressing CXCR2, through high CXCL1 production by macrophages in the TME upon OK-432 treatment. Thus, a triple combination treatment with OK-432, PD-1 blockade, and a CXCR2 neutralizing antibody overcame the resistance induced by MDSCs, resulting in a far stronger antitumor effect than that of any dual combination or single treatment. The accumulation of MDSCs was similarly observed in the pleural effusion of lung cancer patients after OK-432 administration. We propose that successful combination cancer immunotherapy stimulating innate immunity against immunologically cold tumors requires modulation of unwanted activation of innate immune suppressive cells, including MDSCs.

Published in

Coactivation of innate immune suppressive cells induces acquired resistance against combined TLR agonism and PD-1 blockade

Nishinakamura H, Shinya S, Irie T et al. · Science translational medicine 2025 · PMID 39937883 · doi:10.1126/scitranslmed.adk3160

This dataset

Open GSE281466 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 GSE281466_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 PRJNA1183898 and SRA study SRP544121. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39937883) ↗

Study design

6 conditions, mostly in triplicate

CT26_Ctrl ×3 CT26_OK432 ×3 CT26NYESO1_Ctrl ×3 CT26NYESO1_OK432 ×3 LL2_Ctrl ×3 LL2_OK432 ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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

GSM8621187 CT26_Ctrl_1 CT26_Ctrl
GSM8621188 CT26_Ctrl_2 CT26_Ctrl
GSM8621189 CT26_Ctrl_3 CT26_Ctrl
GSM8621190 CT26_OK432_1 CT26_OK432
GSM8621191 CT26_OK432_2 CT26_OK432
GSM8621192 CT26_OK432_3 CT26_OK432
GSM8621193 CT26NYESO1_Ctrl_1 CT26NYESO1_Ctrl
GSM8621194 CT26NYESO1_Ctrl_2 CT26NYESO1_Ctrl
GSM8621195 CT26NYESO1_Ctrl_3 CT26NYESO1_Ctrl
GSM8621196 CT26NYESO1_OK432_1 CT26NYESO1_OK432
GSM8621197 CT26NYESO1_OK432_2 CT26NYESO1_OK432
GSM8621198 CT26NYESO1_OK432_3 CT26NYESO1_OK432
GSM8621199 LL2_Ctrl_1 LL2_Ctrl
GSM8621200 LL2_Ctrl_2 LL2_Ctrl
GSM8621201 LL2_Ctrl_3 LL2_Ctrl
GSM8621202 LL2_OK432_1 LL2_OK432
GSM8621203 LL2_OK432_2 LL2_OK432
GSM8621204 LL2_OK432_3 LL2_OK432

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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.