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A tumor-associated macrophage-targeted immunocytokine leveraging T and NK cell synergy for potent cancer immunotherapy [CITE-seq]

GSE303868 Homo sapiens (human) Single-cell RNA-seq 36 samples Submitted 2025/11/19 Platform GPL34281
At a glance

Single-cell RNA-seq · human · 36 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
36 samples: 6 conditions, mostly with about 8 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
Macrophage-targeted immunocytokine leverages myeloid, T, and NK cell synergy for cancer immunotherapyCell · 2025
Summary (written by the submitters)
Tumor-associated macrophages (TAMs) expressing the myeloid checkpoint TREM2 are key immunosuppressive cells in the tumor microenvironment (TME), driving tumor progression and contributing to poor prognosis in cancer patients. Due to their pivotal role, TAMs have emerged as a promising target for immunotherapies. However, current TAM-targeting monotherapies show limited efficacy, highlighting the need for strategies engaging multiple immune modalities.
Read the full summary ↓
Here, we developed a new class of cancer immunotherapies: myeloid-targeted immunocytokines and NK-T cell enhancers (MiTEs). MiTEs are trans-acting immunocytokines with tumor-specific activation, allowing dual targeting of TAMs and lymphocytes by TREM2 antagonism and cytotoxic effector cell activation through IL-2. To avoid off-target toxicities, MiTEs contain an IL-2 masking moiety, which is cleaved by a TAM-specific protease. MiTEs demonstrate high efficacy in preclinical tumor models through extensive immune reprogramming spanning TAM, T and NK cell compartments. MiTEs show transformative potential for treating solid-cancers by inducing potent multi-arm anti-tumor immunity and minimizing toxicities.
Published in
Macrophage-targeted immunocytokine leverages myeloid, T, and NK cell synergy for cancer immunotherapy
von Locquenghien M, Zwicky P, Xie K et al. · Cell 2025 · PMID 41265436 · doi:10.1016/j.cell.2025.10.030
This dataset
Open GSE303868 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 GSE303868_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 PRJNA1298584 and SRA study SRP604570. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41265436) ↗
Study design
6 conditions, mostly with about 8 replicates each
GEX-2025-05-22-1 ×8 Feature-2025-05-22-1 ×8 GEX-2025-05-23-2 ×8 Feature-2025-05-23-2 ×8 GEX-2025-05-16-1 ×2 Feature-2025-05-16-1 ×2

Supports a between-group comparison across 36 samples.

How we read this: 6 replicated groups read from 36 sample titles; they account for 36 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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