← BioTransfer GEO Dataset Finder
GEO series

Transcriptome Analysis of Human Cancer Cells with Depleted or Overexpressed STELLA Proteins [RNA-seq]

GSE255105 Homo sapiens (human) RNA-seq (gene expression) 51 samples Submitted 2024/10/25 Platform GPL11154
At a glance

RNA-seq (gene expression) · human · 51 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
51 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
Defining ortholog-specific UHRF1 inhibition by STELLA for cancer therapyNature communications · 2025
Summary (written by the submitters)
UHRF1 maintains DNA methylation by recruiting DNA methyltransferases (DNMT’s) to chromatin. These dynamics are well defined for mouse STELLA (mSTELLA) but poorly characterized for human STELLA (hSTELLA). Herein, we demonstrate that hSTELLA is defective, while mSTELLA is fully proficient in associating with UHRF1 and inhibiting the abnormal DNA methylation and oncogenic functions of UHRF1 in human cancer cells.
Read the full summary ↓
We illustrate, in structural studies a region of low sequence homology between the above STELLA orthologs, allows mSTELLA but not hSTELLA to bind tightly to the essential histone binding domains of UHRF1, thus mediating their above functional differences. The ortholog-specific binding modes of STELLA proteins with UHRF1 prompt us to explore a rationale for designing UHRF1 inhibitors for cancer therapy. For this, we use a lipid nanoparticle (LNP)-mediated mRNA delivery approach demonstrating the short mSTELLA, but not hSTELLA regions are required to reverse cancer-specific DNA methylation abnormalities and impair CRC tumor growth.
Published in
Defining ortholog-specific UHRF1 inhibition by STELLA for cancer therapy
Bai W, Xu J, Gu W et al. · Nature communications 2025 · PMID 39774694 · doi:10.1038/s41467-024-55481-7
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 GSE255105_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 PRJNA1073525 and SRA study SRP488281. 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.

+ 51 more — browse all 51 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.