Dominant-negative TP53 mutations potentiated by the HSF1-regulated proteostasis network
RNA-seq (gene expression) · human · 36 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
- 36 samples: 6 conditions, mostly with about 6 replicates eachGroups 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
- Dominant-negative TP53 mutations potentiated by the HSF1-regulated proteostasis networkMolecular cell · 2026
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE304320_RAW.tar (it can run to tens of gigabytes).
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 PRJNA1300364 and SRA study SRP542185. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 36 samples.
How we read this: 6 replicated groups read from 36 sample titles; they account for 36 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.
- GSM8604613 par-cHSF1_37_DMSO_1 par-cHSF1_37_DMSO
- GSM8604615 par-cHSF1_37_DMSO_2 par-cHSF1_37_DMSO
- GSM8604616 par-cHSF1_37_DMSO_3 par-cHSF1_37_DMSO
- GSM8604618 par-cHSF1_37_DMSO_4 par-cHSF1_37_DMSO
- GSM8604619 par-cHSF1_37_DMSO_5 par-cHSF1_37_DMSO
- GSM8604621 par-cHSF1_37_DMSO_6 par-cHSF1_37_DMSO
- GSM8604622 par-cHSF1_37_dox_1 par-cHSF1_37_dox
- GSM8604624 par-cHSF1_37_dox_2 par-cHSF1_37_dox
- GSM8604625 par-cHSF1_37_dox_3 par-cHSF1_37_dox
- GSM8604626 par-cHSF1_37_dox_4 par-cHSF1_37_dox
- GSM8604628 par-cHSF1_37_dox_5 par-cHSF1_37_dox
- GSM8604629 par-cHSF1_37_dox_6 par-cHSF1_37_dox
- GSM9147333 A549 parental DMSO 1 A549 parental DMSO
- GSM9147334 A549 parental DMSO 2 A549 parental DMSO
- GSM9147335 A549 parental DMSO 3 A549 parental DMSO
- GSM9147336 A549 parental DMSO 4 A549 parental DMSO
- GSM9147337 A549 parental DMSO 5 A549 parental DMSO
- GSM9147338 A549 parental DMSO 6 A549 parental DMSO
- GSM9147339 A549 parental DOX 1 A549 parental DOX
- GSM9147340 A549 parental DOX 2 A549 parental DOX
- GSM9147341 A549 parental DOX 3 A549 parental DOX
- GSM9147342 A549 parental DOX 4 A549 parental DOX
- GSM9147343 A549 parental DOX 5 A549 parental DOX
- GSM9147344 A549 parental DOX 6 A549 parental DOX
- GSM9147345 A549 cHSF1 DOX 1 A549 cHSF1 DOX
- GSM9147346 A549 cHSF1 DOX 2 A549 cHSF1 DOX
- GSM9147347 A549 cHSF1 DOX 3 A549 cHSF1 DOX
- GSM9147348 A549 cHSF1 DOX 4 A549 cHSF1 DOX
- GSM9147349 A549 cHSF1 DOX 5 A549 cHSF1 DOX
- GSM9147350 A549 cHSF1 DOX 6 A549 cHSF1 DOX
- GSM9147351 A549 dncHSF1 DOX 1 A549 dncHSF1 DOX
- GSM9147352 A549 dncHSF1 DOX 2 A549 dncHSF1 DOX
- GSM9147353 A549 dncHSF1 DOX 3 A549 dncHSF1 DOX
- GSM9147354 A549 dncHSF1 DOX 4 A549 dncHSF1 DOX
- GSM9147355 A549 dncHSF1 DOX 5 A549 dncHSF1 DOX
- GSM9147356 A549 dncHSF1 DOX 6 A549 dncHSF1 DOX
- 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
- GSE280707 Dominant-negative TP53 mutations potentiated by the HSF1-regulated proteostasis network [1] 12 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
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.