GEO series

Comprehensive single cell transcriptomics analysis of murine osteosarcoma uncovers Skp2 function in metastasis, genomic instability and immune activation and reveals additional target pathways

GSE262743 Mus musculus (mouse) Single-cell RNA-seq 10 samples Submitted 2024/06/28 Platform GPL21103

At a glance

Single-cell RNA-seq · mouse · 10 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: 10 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: Comprehensive single cell transcriptomics analysis of murine osteosarcoma uncovers Skp2 function in metastasis, genomic instability and immune activation and reveals additional target pathwaysbioRxiv : the preprint server for biology · 2024

Summary (written by the submitters)

Osteosarcoma (OS) is the most common primary pediatric bone malignancy. One promising new therapeutic target is SKP2, encoding a substrate recognition factor of the SCF E3 ubiquitin ligase responsible for ubiquitination and proteasome degradation of substrate p27, thus driving cellular proliferation. We have shown previously that knockout of Skp2 in an immunocompetent transgenic mouse model of OS improved survival, drove apoptosis, and induced tumor inflammation.

Read the full summary ↓

Here, we applied single-cell RNA-sequencing (scRNA-seq) to study primary OS tumors derived from Osx-Cre driven conditional knockout of Rb1 and Trp53. We showed that murine OS models recapitulate the tumor heterogeneity and microenvironment complexity observed in patient tumors. We further compared this model with OS models with functional disruption of Skp2: one with Skp2 knockout and the other with the Skp2-p27 interaction disrupted (resulting in p27 overexpression). We found reduction of T cell exhaustion and upregulation of interferon activation, along with evidence of replicative and endoplasmic reticulum-related stress in the Skp2 disruption models, and showed that interferon induction was correlated with improved survival in OS patients. Additionally, our scRNA-seq analysis uncovered decreased activities of metastasis-related gene signatures in the Skp2-modulated OS, which we validated by observation of a strong reduction in lung metastasis in the Skp2 knockout mice. Finally, we report several potential mechanisms of escape from targeting Skp2 in OS, including upregulation of Myc targets, DNA copy number amplification and overexpression of alternative E3 ligase genes, and potential alternative lineage activation. These mechanistic insights into OS tumor biology and Skp2 function suggest novel targets for new, synergistic therapies, while the data and our comprehensive analysis may serve as a public resource for further big data-driven OS research.

Published in

Comprehensive single cell transcriptomics analysis of murine osteosarcoma uncovers Skp2 function in metastasis, genomic instability and immune activation and reveals additional target pathways

Ferrena A, Zhang R, Wang J et al. · bioRxiv : the preprint server for biology 2024 · PMID 38895216 · doi:10.1101/2024.06.04.597347

This dataset

Open GSE262743 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 GSE262743_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 PRJNA1093096 and SRA study SRP498543. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38895216) ↗

Samples in this study

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+ 10 more — browse all 10 samples with per-sample file links →

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