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PI3K-AKT activation determines oncogenic RAS-induced hypertranscription and replication stress [ChrRNAseq]

GSE322524 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/03/09 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)
Samples
12 samples: 3 × BJ-hTert cells, HRASG12V expression, 0h induction, vs 3 × BJ-hTert cells, HRASG12V expression, 48h induction, vs 3 × BJ-hTert cells, KRASG12V expression, 0h induction, vs 3 × BJ-hTert cells, KRASG12V expression, 48h induction,Groups 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)
Oncogenic RAS activation, hypertranscription and transcription-replication conflicts (TRCs) are frequent features of cancer cells that are under investigation for therapeutic targeting. RAS oncogenes promote RNA polymerase activity and hypertranscription for cell growth and proliferation, which can the lead to TRCs. Here, we investigated hypertranscription and replication stress induced by the HRAS and KRAS oncogenes, and their downstream signalling through the MAPK and PI3K pathways.
Read the full summary ↓
We show that HRAS causes more TRCs than KRAS because HRAS specifically hyperactivates the PI3K-AKT signalling pathway. MAPK signalling is insufficient to cause hypertranscription and TRCs, which require PI3K activity. PI3K hyperactivation was associated with increased E2F and MYC transcription programmes, increased S phase entry, increased nascent transcription of genes encoding ribosome biogenesis factors and expression of small nucleolar RNAs (snoRNAs). Inhibiting S phase entry alone did not rescue hypertranscription and replication stress, which required both MAPK and PI3K signalling. We report that a main downstream effector of PI3K-induced hypertranscription is AKT-mediated phosphorylation of GSK3b, which stabilises MYC. Cancer datasets further support that PI3K mutations may be associated with hypertranscription and replication stress signatures. Our findings suggest a mechanistic explanation for replication stress variability across RAS models and identify potential new predictors of TRCs in cancer.
This dataset
Open GSE322524 in finder → Find more human 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 GSE322524_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 PRJNA1430363 and SRA study SRP680181. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × BJ-hTert cells, HRASG12V expression, 0h induction, vs 3 × BJ-hTert cells, HRASG12V expression, 48h induction, vs 3 × BJ-hTert cells, KRASG12V expression, 0h induction, vs 3 × BJ-hTert cells, KRASG12V expression, 48h induction,

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
Datasets on a similar topic

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