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scRNAseq of MC38 mouse tumors reveals diverse functions of LMO7 in regulating tumor microenvironment

GSE294033 Mus musculus (mouse) Single-cell RNA-seq 2 samples Submitted 2026/07/01 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 2 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
2 samples
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
LMO7 Suppresses Tumor-Associated Macrophage Phagocytosis of Tumor Cells Through Degradation of LRP1Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
Summary (written by the submitters)
We have employed a single cell sequening approach using 10x Genomics scRNAseq to study the function of LIM domain only 7 (LMO7) in tumor microenvironment. LMO7 has been widely reported in recent years as an E3 ubiquitin ligase with a wide range of regulatory effects on macrophages and fibroblasts. Based on this characteristic, we used scRNA-seq of tumor tissues from wild-type and LMO7 knockout mice to further explore its regulatory effects on the tumor microenvironment.
Read the full summary ↓
The results showed that LMO7 could significantly inhibit the pro-inflammatory polarization phenotype and phagocytic potential of macrophages, as well as inhibit the killing effect of CD8+ T cells.
Published in
LMO7 Suppresses Tumor-Associated Macrophage Phagocytosis of Tumor Cells Through Degradation of LRP1
Li M, Wang T, Zhong Y et al. · Advanced science (Weinheim, Baden-Wurttemberg, Germany) 2026 · PMID 41208232 · doi:10.1002/advs.202511162
This dataset
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.

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 GSE294033_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1247927 and SRA study SRP577191. Searching any of these in the dataset finder brings you back here.

Samples in this study

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