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Screening for genes that promote copper toxicity in a cell model of Wilson disease [HepG2 cells ATP7B-KO]

GSE277865 Homo sapiens (human) RNA-seq (gene expression) 30 samples Submitted 2024/12/09 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 30 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
30 samples: 30 samples, each with a distinct title — no replicated groupsGroups 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
Prion protein promotes copper toxicity in Wilson diseaseNature communications · 2025
Summary (written by the submitters)
To find new genes that might be targeted for reduction of Copper (Cu) toxicity in Wilson disease we employed genome-wide shRNA screening in ATP7B-KO HepG2 cells, a bona fide WD cell model. Cells were screened using the Dharmacon™ Decode™ Pooled Lentiviral shRNA Screening Library targeting 18205 human genes (Dharmacon #RHS6083). The Lentiviral RNAi screening library is made of 10 pools of 9570 GIPZ short hairpin RNAs (shRNAs) packaged into high-titer lentiviral particles.
Read the full summary ↓
Genomic DNA was isolated from the cells and read counts for each shRNAs were obtained by deep sequencing to determine the abundance of each shRNA in the Cu-treated cells compared to controls. This analysis allowed the identification of genes whose downregulation promoted survival of ATP7B-KO cells upon Cu overload. To exclude that some shRNAs would have been responsible for ATP7B-KO survival by suppressing generic proapoptotic genes, we run the same screening with the proapoptotic drug vinblastine instead of CuCl2. Genes, whose suppression allowed cell to resist Cu but not vinblastine were considered as Cu-specific hits and through this approach we identified PrP as a suitable target for reduction of Cu toxicity in WD. Indeed, we found that Cu accumulation in ATP7B-KO cells stimulates expression of PrP, which brings to toxic Cu overload while PrP suppression significantly reduces Cu accumulation and toxicity in ATP7B-deficient cells. In sum our data highlight an important regulatory role of PrP in copper metabolism and as a therapeutic tool for Wilson disease.
Published in
Prion protein promotes copper toxicity in Wilson disease
Petruzzelli R, Catalano F, Crispino R et al. · Nature communications 2025 · PMID 39922819 · doi:10.1038/s41467-025-56740-x
This dataset
Open GSE277865 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 GSE277865_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 PRJNA1164671 and SRA study SRP534401. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39922819) ↗
Study design
30 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 30 sample titles: 30 distinct titles with little repetition. 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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