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Senescent cell extracellular vesicles are critical elements restricting cancer recurrence [bulk RNA-seq]

GSE262139 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2024/12/23 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 12 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Mus musculus (mouse)
Samples
12 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
Senescent Cell-Derived Extracellular Vesicles Inhibit Cancer Recurrence by Coordinating Immune SurveillanceCancer research · 2025
Summary (written by the submitters)
Senescent cell extracellular vesicles (senEVs)are novel and underappreciated components of the senescence secretome. To understand the role that senEVs play in inflammatory responses to senescence, we developed and validated a novel engraftment-based senescence model that allowed us to genetically block the release of senEVs in vivo. We found that senEVs orchestrate prompt removal of senescent cells and inhibit tumor recurrence.
Read the full summary ↓
Recruitment of MHC-II+ antigen presenting cells into the senescence microenvironment was significantly decreased in the absence of senEVs. Inhibition of senEV release changed the primary target of senescent cell signaling from antigen presenting cells to neutrophils. Antigen presenting cells recruited and activated CCR2+ TH17 cells, which in turn inhibited B cell activation. Through multimodal transcriptional and proteomic analysis, we identified 6 ligands that were specific to senEVs, suggesting a role in promoting cell adhesion. Overall, these results indicate that senEVs complement the activity of secreted inflammatory mediators in recruiting and activating distinct immune cell subsets for efficient removal of senescent cells.
Published in
Senescent Cell-Derived Extracellular Vesicles Inhibit Cancer Recurrence by Coordinating Immune Surveillance
Ziglari T, Calistri NL, Finan JM et al. · Cancer research 2025 · PMID 39804967 · doi:10.1158/0008-5472.CAN-24-0875
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 GSE262139_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1090460 and SRA study SRP497000. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 12 more — browse all 12 samples with per-sample file links →

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