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Tune p53 transactivation and tumor suppression activity by modulating its liquid-liquid phase separation propensity

GSE276535 Homo sapiens (human) RNA-seq (gene expression) 15 samples Submitted 2026/07/08 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 15 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
15 samples: 5 conditions, mostly in triplicateGroups 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
Modulating p53 condensation rewires transcriptional programs to enhance tumor suppressionMolecular therapy : the journal of the American Society of Gene Therapy · 2026
Summary (written by the submitters)
p53, essential in cancer defence, is involved in transcriptional and DNA repair condensates. However, whether condensation can be driven by endogenous p53 and the functional significance of condensates in p53’s working and regulatory mechanisms were unknown. We show that endogenous p53 forms nanoscale condensates, co-localizing with different co-factors, enabling distinct functions within segregated compartments in cells.
Read the full summary ↓
Antagonists disperse these condensates, whereas activators enhance coalescence and alter p53 dynamics within these structures. Notably, we reveal a dual role for p53: it maintains tumor suppression and, paradoxically, boosts expression of neuron-related genes, which in certain contexts, can promote cancer cell growth. We developed liquid-liquid phase separation- enhanced p53 variants that amplify selected target gene transactivation and suppress oncogenic gene upregulation, curtailing proliferation of cancer cells resistant to wild-type p53. These findings reveal a critical role of liquid-liquid phase separation in p53 functional regulation, offering subtle control over its transcriptional landscape, particularly with respect to specific genes intersecting neuronal signalling and cancer pathways..
Published in
Modulating p53 condensation rewires transcriptional programs to enhance tumor suppression
Liu Y, Jia H, Guan X et al. · Molecular therapy : the journal of the American Society of Gene Therapy 2026 · PMID 41883163 · doi:10.1016/j.ymthe.2026.03.023
This dataset
Open GSE276535 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 GSE276535_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 PRJNA1157794 and SRA study SRP531053. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41883163) ↗
Study design
5 conditions, mostly in triplicate
WT ×3 Ctrl ×3 p53 ×3 LLPSEp53_1 ×3 LLPSEp53_2 ×3

Supports a between-group comparison across 15 samples.

How we read this: 5 replicated groups read from 15 sample titles; they account for 15 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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