GEO series

Lymph node macrophages drive immune tolerance and resistance to cancer therapy by expression of the immune-regulatory cytokine IL-33 [scRNA-seq]

GSE268778 Mus musculus (mouse) Single-cell RNA-seq 20 samples Submitted 2025/01/28 Platform GPL24247

At a glance

Single-cell RNA-seq · mouse · 20 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Mus musculus (mouse)
Samples: 20 samples: 8 conditions, mostly in duplicateGroups 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: Lymph node macrophages drive immune tolerance and resistance to cancer therapy by induction of the immune-regulatory cytokine IL-33Cancer cell · 2025

Summary (written by the submitters)

Apoptotic cells are immunosuppressive, creating a potential therapeutic barrier in cancer therapy. In this reportwe investigated responses to apoptotic tumor cell phagocytosis (i.e. efferocytosis) after therapy in the tumor draining lymph node (TDLN). Treatment with cisplatin or the BRAF inhibitor PLX4720 caused a significant increase in accumulation of apoptotic tumor material in the TDLN.

Read the full summary ↓

We identified the primary phagocyte population responsible for clearing dying tumors in the TDLN was medullary sinus macrophages (MSMs). Tumor cell efferocytosis by MSMs induced an immune suppressive transcriptional program distinct from other macrophage or dendritic cell populations in the TDLN. One of the most differentially induced mRNAs in MSMs wasIl33,coding fora potent immune-regulatory cytokine. Administration of neutralizing anti-IL-33 receptor antibodies or deletion ofIl33in MSMs altered tumor responses to therapy with a significant enhancement of anti-tumor activity compared to controls. Mechanistically, IL-33 activated Treg cells in the TDLN with subsequent suppression of CD8+T cell responses. Importantly, combining IL-33 receptor blockade, BRAF inhibitor, and PD-1 blockade significantly improved tumor regression with enhanced, CD8+T cell dependent immunity. Finally, apoptotic tumor cells induced IL-33 expression in human macrophages, IL-33 expression in sentinel lymph nodes positively corresponded with disease stage and negatively correlated with survival in melanoma and breast cancer. Thus, the data identifies an immune response to therapy that abrogates nascent anti-tumor immunity, providing a previously undescribed functional interaction with broad implications for cancer therapy.

Published in

Lymph node macrophages drive immune tolerance and resistance to cancer therapy by induction of the immune-regulatory cytokine IL-33

Lamorte S, Quevedo R, Jin R et al. · Cancer cell 2025 · PMID 40054466 · doi:10.1016/j.ccell.2025.02.017

This dataset

Open GSE268778 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 GSE268778_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 PRJNA1118731 and SRA study SRP511055. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40054466) ↗

Study design

8 conditions, mostly in duplicate

TDLN_KO_Tx ×2 TDLN_KO_Un_Tx ×2 TDLN_WT_Tx ×2 TDLN_WT_Un_Tx ×2 Tumor_KO_Tx ×2 Tumor_KO_Un_Tx ×2 Tumor_WT_Tx ×2 Tumor_WT_Un_Tx ×2 +4 more

Supports a case/control comparison: 6 samples read as cases, 4 as controls.

How we read this: 8 replicated groups read from 20 sample titles; they account for 16 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

GSM8298995 CD45_Tumor_KO_PLX4720
GSM8298996 CD45_Tumor_KO_Un
GSM8298997 CD45_Tumor_WT_PLX4720
GSM8298998 CD45_Tumor_WT_Un
GSM8298999 TDLN_KO_Tx1 TDLN_KO_Tx
GSM8299000 TDLN_KO_Un_Tx1 TDLN_KO_Un_Tx
GSM8299001 TDLN_WT_Tx1 TDLN_WT_Tx
GSM8299002 TDLN_WT_Un_Tx1 TDLN_WT_Un_Tx
GSM8299003 TDLN_KO_Tx7 TDLN_KO_Tx
GSM8299004 TDLN_KO_Un_Tx7 TDLN_KO_Un_Tx
GSM8299005 TDLN_WT_Tx7 TDLN_WT_Tx
GSM8299006 TDLN_WT_Un_Tx7 TDLN_WT_Un_Tx
GSM8299007 Tumor_KO_Tx7 Tumor_KO_Tx
GSM8299008 Tumor_KO_Un_Tx7 Tumor_KO_Un_Tx
GSM8299009 Tumor_WT_Tx7 Tumor_WT_Tx
GSM8299010 Tumor_WT_Un_Tx7 Tumor_WT_Un_Tx
GSM8299011 Tumor_KO_Tx1 Tumor_KO_Tx
GSM8299012 Tumor_KO_Un_Tx1 Tumor_KO_Un_Tx
GSM8299013 Tumor_WT_Tx1 Tumor_WT_Tx
GSM8299014 Tumor_WT_Un_Tx1 Tumor_WT_Un_Tx

Datasets on a similar topic

GSE268774 Lymph node macrophages drive immune tolerance and resistance to cancer therapy by expression of the immune-regulatory cytokine IL-33 [RNA-seq] 48 samples shares il-33, immune-regulatory, macrophages, resistance, tolerance, cytokine, therapy
GSE281467 Coactivation of innate immune suppressive cells induces acquired resistance against cancer immunotherapy targeting the innate immune system [TIICs RNA-seq] 30 samples shares resistance, therapy
GSE337190 CAR-NKT cells induce low cytokine release syndrome by targeting hyperinflammatory macrophages with mitigation from GM-SCF inhibition. 24 samples shares macrophages, cytokine
GSE290194 Repair-Associated Macrophages Increase after Early-phase Microglia Attenuation to Promote Ischemic Stroke Recovery [scRNA-Seq] 16 samples shares macrophages, scrna-seq
GSE284264 Spatial genomics reveals cholesterol metabolism as a key factor in immunotherapy resistance in colorectal cancer [bulk RNA-seq] 16 samples shares resistance, therapy
GSE261898 Acquired resistance to immunotherapy by physical barriers with cancer cell–expressing collagens in non–small cell lung cancer 14 samples shares resistance, therapy
GSE300299 Chikungunya virus persists in joint-associated macrophages and promotes chronic disease in mice [scRNA-seq] 12 samples shares macrophages, scrna-seq
GSE263545 Resident and recruited macrophages differentially contribute to cardiac healing after myocardial ischemia [scRNA-seq] 10 samples shares macrophages, scrna-seq

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.