GEO series

Dominant-negative TP53 mutations potentiated by the HSF1-regulated proteostasis network [1]

GSE280707 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/12/30 Platform GPL18573

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
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: Dominant-negative TP53 mutations potentiated by the HSF1-regulated proteostasis networkMolecular cell · 2026

Summary (written by the submitters)

Protein mutational landscapes are sculpted by the impacts of the resulting amino acid substitu-tions on the protein’s stability and folding or aggregation kinetics. These properties can, in turn, be modu-lated by the composition and activities of the cellular proteostasis network. Heat shock factor 1 (HSF1) is the master regulator of the cytosolic and nuclear proteostasis networks, dynamically tuning the expres-sion of cytosolic and nuclear chaperones and quality control factors to meet demand.

Read the full summary ↓

Chronic increases in HSF1 levels and activity are prominent hallmarks of cancer cells. One plausible explanation for this ob-servation is that the consequent upregulation of proteostasis factors could facilitate the acquisition of on-cogenic mutations. Here, we experimentally evaluate the impacts of chronic HSF1 activation on the muta-tional landscape accessible to the quintessential oncoprotein p53. Specifically, we apply quantitative deep mutational scanning to assess how HSF1 activation shapes the mutational pathways by which p53 can escape cytotoxic pressure conferred by the small molecule nutlin-3, which is a potent antagonist of the p53 negative regulator mouse double minute 2 homolog (MDM2). We find that activation of HSF1 broadly and significantly increases the fitness of dominant-negative substitutions within p53. This effect of HSF1 activation was particularly notable for non-conservative, otherwise biophysically unfavorable non-polar to polar or charged amino acid substitutions within buried regions of the p53 DNA-binding domain. These results indicate that chronic HSF1 activation profoundly shapes the oncogenic mutational land-scape, preferentially supporting the acquisition of cancer-associated substitutions that are biophysically destabilizing. Along with providing the first experimental and quantitative insights into how HSF1 influ-ences oncoprotein mutational spectra, these findings also implicate HSF1 inhibition as a strategy to re-duce the accessibility of mutations that drive chemotherapeutic resistance and metastasis.

Published in

Dominant-negative TP53 mutations potentiated by the HSF1-regulated proteostasis network

Halim S, Sebastian RM, Liivak KE et al. · Molecular cell 2026 · PMID 41539306 · doi:10.1016/j.molcel.2025.12.013

This dataset

Open GSE280707 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 GSE280707_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 PRJNA1180069 and SRA study SRP542185. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41539306) ↗

Samples in this study

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+ 12 more — browse all 12 samples with per-sample file links →

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GSE304320 Dominant-negative TP53 mutations potentiated by the HSF1-regulated proteostasis network 36 samples shares tp53, dominant-negative, hsf1-regulated, proteostasis, potentiated, mutations, network
GSE304317 Dominant-negative TP53 mutations potentiated by the HSF1-regulated proteostasis network [2] 24 samples shares tp53, dominant-negative, hsf1-regulated, proteostasis, potentiated, mutations, network
GSE252264 RIPK4 driven by TP53 mutations promotes resistance to PANoptosis and metastasis of CRC by phosphorylation of MTHFD1 18 samples shares tp53, mutations
GSE297670 Splice-altering TP53 missense mutations: Drivers of functional loss and therapeutic targets via RNA modulation 18 samples shares tp53, mutations
GSE305620 Establishment and Characterization of a New Immortalized Human Oral Keratinocyte (HOK) Cell Line Harboring Various TP53 Mutations 15 samples shares tp53, mutations
GSE252262 RIPK4 driven by TP53 mutations promotes resistance to PANoptosis and metastasis of CRC by phosphorylation of MTHFD1 [Anokis_seq] 12 samples shares tp53, mutations
GSE252263 RIPK4 driven by TP53 mutations promotes resistance to PANoptosis and metastasis of CRC by phosphorylation of MTHFD1 [RIPK4_sh_seq] 6 samples shares tp53, mutations
GSE34258 Genome sequencing of childhood medulloblastoma brain tumors links chromothripsis with TP53 mutations 49 samples shares tp53, mutations

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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.