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Chemotherapy triggers immune evasion by fostering LEPR+ Kupffer cell differentiation in liver metastases [RNA-seq]

GSE285990 Mus musculus (mouse) Single-cell RNA-seq 23 samples Submitted 2025/12/29 Platform GPL34281Platform GPL28330Platform GPL13112Platform GPL34328
At a glance

Single-cell RNA-seq · mouse · 23 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
Mus musculus (mouse)
Samples
23 samples: 20 distinct titles, 3 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
Chemotherapy triggers immune evasion by fostering LEPR(+) Kupffer cell differentiation in liver metastasesCancer cell · 2026
Summary (written by the submitters)
Conventional chemotherapy achieves clinical efficacy beyond its cytotoxic effects by reactivating immune surveillance. However, whether chemotherapy promotes immune evasion by remodeling the tumor microenvironment (TME) remains largely unexplored. Here, we integrate cross-species single-cell and spatial transcriptomics to explore how chemotherapy reprograms immune cell dynamics and plasticity.
Read the full summary ↓
Our findings reveal a central role for chemotherapy-educated, liver-resident Kupffer cells (KCs) in promoting immune tolerance and chemoresistance in liver metastases. These reprogrammed KCs, characterized by leptin receptor expression (LEPR+), originate from preexisting KCs and are differentiated via STING-ID1 signaling triggered by cGAMP released from chemotherapy-treated tumor cells. Unlike conventional KCs, LEPR+ KCs infiltrate tumors and engage in MerTK-dependent efferocytosis, which diminishes chemotherapy-induced immunogenic cell death (ICD) and suppresses antitumor immunity. Notably, targeting LEPR+ KCs enhances tumor immunogenicity and strengthens antitumor T-cell responses. Our study demonstrates that therapy-induced KC differentiation fosters immune evasion and suggests combining efferocytosis inhibitors with immunotherapy to overcome chemoresistance.
Published in
Chemotherapy triggers immune evasion by fostering LEPR(+) Kupffer cell differentiation in liver metastases
Wang X, Pan Q, Li Y et al. · Cancer cell 2026 · PMID 41687606 · doi:10.1016/j.ccell.2026.01.010
This dataset
Open GSE285990 in finder → Find more 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 GSE285990_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 PRJNA1207437 and SRA study SRP555750. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41687606) ↗
Study design
20 distinct titles, 3 of them repeated
KC-1 ×2 KC-2 ×2 LEPR+ KC ×2

How we read this: Read from 23 sample titles: 20 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
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