GEO series

Analysis of cellular and exosomal RNAs in AC16 cells regulated by hypertrophic cardiomyocyte

GSE266430 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/03/24 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 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: Homo sapiens (human)
Topic: Breast cancerThis series is part of our curated briefing on it.
Samples: 12 samples: 3 × AC16 cells, cell-L-Con vs 3 × AC16 cells, cell-L-Ang vs 3 × AC16 exosomes,exo-L-Con vs 3 × AC16 exosomes,exo-L-AngGroups 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 diseases (CVDs) and cancer are among the most serious life-threatening diseases with very high morbidity and mortality rates. An increasing number of clinical studies have shown that cardiovascular disease is strongly associated with an increased risk of cancer and can contribute to cancer development, but the mechanisms associated with this need to be further explored in depth.

Read the full summary ↓

Exosomes play an important role in promoting the development of cancer, and breast cancer is the most prevalent cancer among women. In the present study, we showed by in vivo experiments that exosomes from hypertrophic cardiomyocytes significantly promote breast cancer progression. In order to explore the mechanism by which hypertrophic cardiomyocytes promote the progression of breast cancer, we conducted whole transcriptome sequencing of exosomes and cells from normal cardiomyocytes and hypertrophic cardiomyocytes. Interestingly, the majority of miRNAs were downregulated in the exosomes of hypertrophic cardiomyocytes. In the downregulated miRNAs within the exosomes of hypertrophic cardiomyocytes, a consistent sequence GGCXGAGG was identified. We found that hnRNPQ regulates exosomal sorting of miR-10400-3p and several other miRNAs. Based on this, we validated the expression levels of plasma exosomal miRNAs in patients with myocardial hypertrophy using clinical data and patient samples, providing predictive markers for cancer progression in myocardial hypertrophy patients. Our findings suggest that hypertrophic cardiomyocytes regulate the expression of the RNA-binding protein hnRNPQ, which affects the levels of exosomal miRNAs and plays a key role in promoting the development of breast cancer.

This dataset

Open GSE266430 in finder → Find more human RNA-seq datasets → Breast cancer landscape →

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 GSE266430_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: 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 PRJNA1107172 and SRA study SRP505449. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

3 × AC16 cells, cell-L-Con vs 3 × AC16 cells, cell-L-Ang vs 3 × AC16 exosomes,exo-L-Con vs 3 × AC16 exosomes,exo-L-Ang

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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

GSM8246819 AC16 cells, cell-L-Con1 AC16 cells, cell-L-Con
GSM8246820 AC16 cells, cell-L-Con2 AC16 cells, cell-L-Con
GSM8246821 AC16 cells, cell-L-Con3 AC16 cells, cell-L-Con
GSM8246822 AC16 cells, cell-L-Ang1 AC16 cells, cell-L-Ang
GSM8246823 AC16 cells, cell-L-Ang2 AC16 cells, cell-L-Ang
GSM8246824 AC16 cells, cell-L-Ang3 AC16 cells, cell-L-Ang
GSM8246825 AC16 exosomes,exo-L-Con1 AC16 exosomes,exo-L-Con
GSM8246826 AC16 exosomes,exo-L-Con2 AC16 exosomes,exo-L-Con
GSM8246827 AC16 exosomes,exo-L-Con3 AC16 exosomes,exo-L-Con
GSM8246828 AC16 exosomes,exo-L-Ang1 AC16 exosomes,exo-L-Ang
GSM8246829 AC16 exosomes,exo-L-Ang2 AC16 exosomes,exo-L-Ang
GSM8246830 AC16 exosomes,exo-L-Ang3 AC16 exosomes,exo-L-Ang

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Search all human RNA-seq datasets in GEO →

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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.