← BioTransfer GEO Dataset Finder
GEO series

Mutant p53 gain-of-function impact is repressed in the presence of other major oncogenic drivers

GSE239817 Homo sapiens (human) RNA-seq (gene expression) 72 samples Submitted 2024/08/31 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 72 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
72 samples
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
A common druggable signature of oncogenic c-Myc, mutant KRAS and mutant p53 reveals functional redundancy and competition among oncogenes in cancerCell death & disease · 2024
Summary (written by the submitters)
Mutant TP53, mutant KRAS and hyperactive CMYC are driver oncogenes with no standard clinical protocols for their direct targeting. To identify interplay of mutant TP53, KRAS and hyperactive CMYC, and exploit them in a therapeutic manner, we performed global proteomics and transcriptomics in a panel of 8 cell lines of colorectal and lung cancers 48h post knock-out of the oncogenes with CRISPR/Cas9.
Read the full summary ↓
In each cancer type the cell lines containing either all, or one, of each of the activated oncogenes were analyzed. Higher numbers of significant protein and transcript level changes were observed upon CMYC and KRAS disruption compared to mutant TP53 disruption. In contrast to mutant KRAS and CMYC downstream programs the number of mutant p53-dependent proteins and transcripts was reduced several-fold in the presence of mutant KRAS and hyperactive CMYC, compared to cell lines with mutant p53 only. We observed a functional repression of the mutant p53 ability to drive phenotype of cancer cells and transcriptional activity in the presence of mutated KRAS and/or overexpressed CMYC, which in such configuration overtake many of the mutant p53 functions. An overlap of pathways regulated by the transcripts and proteins revealed a molecular program shared by the oncogenes as well as pathways lost or retained in the mutant p53 program, when co-present with the other oncogenes. This allowed to exploit the program common to the oncogenes by experimental, pre-clinical drug targeting. Oncogene cooperation is known to be important in driving cell transformation, however our observations suggest that mutant KRAS and/or overexpressed CMYC compete with mutant p53 for activation of important oncogenic pathways. While the exact mechanism of this competition is under investigation, we hypothesize that mutant p53 is a context-dependent oncogene – whose gain-of-function range of impact heavily depends on the molecular background of neoplastic cells.
Published in
A common druggable signature of oncogenic c-Myc, mutant KRAS and mutant p53 reveals functional redundancy and competition among oncogenes in cancer
Grześ M, Jaiswar A, Grochowski M et al. · Cell death & disease 2024 · PMID 39217152 · doi:10.1038/s41419-024-06965-3
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 GSE239817_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 PRJNA1001013 and SRA study SRP452596. Searching any of these in the dataset finder brings you back here.

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 72 more — browse all 72 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.