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Loss of Hepatocyte PI3Ka Protects Mice from Hepatocellular Carcinoma in association with altered lipid metabolism gene expression

GSE302836 Mus musculus (mouse) RNA-seq (gene expression) 42 samples Submitted 2026/04/30 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 42 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
42 samples: 42 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.
Paper
Loss of hepatocyte PI3Kα reduces hepatocellular carcinoma and hepatocyte proliferation in association with altered lipid metabolismJHEP reports : innovation in hepatology · 2026
Summary (written by the submitters)
Hepatocellular Carcinoma (HCC) is a disease with an increasing incidence and a high mortality rate; therefore, targeted therapies for HCC are urgently needed. PI3K-AKT-mTORC1 signaling is frequently induced in solid tumors and is associated with tumor progression and with the most aggressive type of HCC. However, complete inhibition of all PI3K isoforms is unlikely to achieve a favorable therapeutic index for HCC treatment due to on-target side effects.
Read the full summary ↓
Here, we investigate the role of hepatocyte PI3Ka in HCC using conditional knockout mice. We found that PI3Ka in the hepatocyte is dispensable for AKT phosphorylation in HCC and in normal liver, and hepatocytes during compensatory proliferation following administration of the hepatocarcinogen. We have also found that AKT phosphorylation induced by hepatocyte growth factor (HGF) and epidermal growth factor (EGF) is mediated by redundant PI3Ka and PI3Kb activities. Nonetheless, mice lacking hepatocyte PI3Ka showed reduced HCC proliferation and reduced hepatocyte proliferation induced by DEN. This phenotype was associated with a gene expression signature indicating altered lipid metabolism and reduced formation of lipid droplets. Together, these results indicate that PI3Ka is a promising target for the treatment of HCC.
Published in
Loss of hepatocyte PI3Kα reduces hepatocellular carcinoma and hepatocyte proliferation in association with altered lipid metabolism
Becattini B, Sardi C, Edelbroek B et al. · JHEP reports : innovation in hepatology 2026 · PMID 41997233 · doi:10.1016/j.jhepr.2026.101847
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 GSE302836_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 PRJNA1292245 and SRA study SRP601323. Searching any of these in the dataset finder brings you back here.

Study design
42 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 42 sample titles: 42 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

+ 2 more — browse all 42 samples with per-sample file links →

Datasets on a similar topic

Search all mouse 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.