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DNA-damaging Chemotherapy altered the Cardiac Pathogenesis by reshaping the Composition and Functionality of Cardiac Resident Macrophages (bulk RNA-Seq).

GSE275096 Mus musculus (mouse) Single-cell RNA-seq 35 samples Submitted 2025/12/31 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 35 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
35 samples: 35 samples, each with a distinct title — no replicated groupsGroups 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.
Summary (written by the submitters)
Cardiovascular comorbidities including heart failure and ischemic heart injury represent the most common causes of death among cancer survivors. Despite extensive investigation, we continue to have a poor understanding of how previous chemotherapy reagents exposure impact the heart. Here, we investigated the effect of chemotherapy reagent on the composition and function of the cardiac resident macrophages and found carboplatin selectively deplete the CCR2¬¬¬¬– cardiac macrophages by activating P53 signaling pathway and inducing necroptosis and apoptosis.
Read the full summary ↓
Using Bulk-RNA-seq and lineage-tracing mice, we found CCR2– cardiac macrophages returned after Carboplatin-exposure primarily from monocytes recruitment and demonstrated a different transcriptomic profile. These reshaped CRMs attenuated heart remodeling upon hypertensive heart injury and ischemic-reperfusion injury while selective ablation of the reshaped CRMs abolished this mitigation phenotype. Using bulk-seq, single-cell RNA seq and lineage-tracing mice, we showed that the reshaped CRMs in carboplatin-exposed mice mitigated ventricle remodeling via elevated IFN-I signaling. Together, this study characterized how DNA-damaging chemotherapy reagent change the cardiac immune landscape and demonstrated a novel protective mechanism in adverse cardiac injury response that depends on the carboplatin-reshaped CRMs. These findings highlight the importance of type-I interferon signaling in the long-term effect of chemotherapy and provide promising pathway to retard cardiac pathogenesis.
This dataset
Open GSE275096 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 GSE275096_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 PRJNA1149095 and SRA study SRP530607. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
35 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 35 sample titles: 35 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
Datasets on a similar topic

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.