GEO series

Molecular Characterisation of the A52 Murine Hepatocellular Carcinoma Cell Line

GSE302860 Mus musculus (mouse) RNA-seq (gene expression) 10 samples Submitted 2025/12/31 Platform GPL34290

At a glance

RNA-seq (gene expression) · mouse · 10 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: 10 samples: 5 × A52 Tissue RNA vs 2 × A52 Cell RNA vs 2 × AML-12 Cell RNAGroups 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.
Paper: Molecular characterization of the A52 murine hepatocellular carcinoma cell lineAnimal models and experimental medicine · 2026

Summary (written by the submitters)

Background: To combat hepatocellular carcinoma (HCC) disease heterogeneity and growing mortality, there is an urgent need for targeted and personalised therapeutics. While syngeneic mouse models are commonly used for preclinical validation of these therapeutics, the lack of genetically characterised murine cell lines adds uncertainty to the study of drug-gene interactions in these models.

Read the full summary ↓

We previously generated a novel murine cell line, A52, from a diethylnitrosamine (DEN)-induced adiponectin-knockout mouse model. Here, we present a comprehensive genomic and transcriptomic characterisation of the A52 cell line. Methods: A52 cells were grown in various culture medium compositions to investigate robustness to simple media. Whole-genome sequencing (WGS) and RNAseq were performed on A52 cells from both cell culture and syngeneic tumour tissue, as well as a reference cell line representing non-tumour cells, AML-12. Results: A52 was found to show robust growth in all medium compositions. Substantial chromosomal instability was observed in A52, including trisomy 15 and notable amplifications of oncogenic loci such as Myc and Cd274 (PDL-1), alongside frequent small variants and structural rearrangements. Notably, the cell line harbours the common HCC driver Braf V584E mutation, and a novel Plk1 p.R364W variant predicted as a driver mutation. Transcriptomic profiling defined a distinct "A52 gene signature" enriched in EGFR-ERBB signalling and cell migration pathways. Integrative analyses demonstrated that the A52 gene signature aligns closely with a subset of human HCC lacking CTNNB1 mutations. Conclusion: This study provides a critical genetic resource, facilitating more precise preclinical modelling and therapeutic validation in HCC.

Published in

Molecular characterization of the A52 murine hepatocellular carcinoma cell line

Gillman R, Sun EJ, Wankell M et al. · Animal models and experimental medicine 2026 · PMID 41760594 · doi:10.1002/ame2.70152

This dataset

Open GSE302860 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 GSE302860_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 PRJNA1292710 and SRA study SRP601461. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41760594) ↗

Study design

5 × A52 Tissue RNA vs 2 × A52 Cell RNA vs 2 × AML-12 Cell RNA

Supports a between-group comparison across 9 samples.

How we read this: 3 replicated groups read from 10 sample titles; they account for 9 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

GSM9112499 A52 Tissue RNA rep1 A52 Tissue RNA
GSM9112500 A52 Tissue RNA rep2 A52 Tissue RNA
GSM9112501 A52 Tissue RNA rep3 A52 Tissue RNA
GSM9112502 A52 Tissue RNA rep4 A52 Tissue RNA
GSM9112503 A52 Tissue RNA rep5 A52 Tissue RNA
GSM9112504 A52 Cell RNA rep1 A52 Cell RNA
GSM9112505 A52 Cell RNA rep2 A52 Cell RNA
GSM9112506 A52 Cell DNA rep1
GSM9112507 AML-12 Cell RNA rep1 AML-12 Cell RNA
GSM9112508 AML-12 Cell RNA rep2 AML-12 Cell RNA

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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.