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Proteasome inhibition sensitizes anaplastic Wilms tumor to actinomycin D

GSE270330 Homo sapiens (human) RNA-seq (gene expression) 36 samples Submitted 2024/06/20 Platform GPL18573
At a glance

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)
Topic
Wilms tumourThis series is part of our curated briefing on it.
Samples
36 samples: 6 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
Actinomycin D and bortezomib disrupt protein homeostasis in Wilms tumorbioRxiv : the preprint server for biology · 2024
Summary (written by the submitters)
Wilms tumor is the most common kidney cancer in children, and anaplastic Wilms tumor is the most chemoresistant histological subtype. Here we explore how anaplastic Wilms tumor cells evade the common chemotherapeutic drug actinomycin D, which inhibits ribosomal biogenesis. We found that, when ribosomal capacity is limited by actinomycin D treatment, anaplastic Wilms tumor cells preferentially translate proteasome components and upregulate proteasome activity.
Read the full summary ↓
Accordingly, increased proteasome levels are associated with anaplastic histology and with worse prognosis in Wilms tumor. Lastly, we show that the proteasome inhibitor bortezomib sensitizes cells to actinomycin D treatment both in vitro and in vivo.
Published in
Actinomycin D and bortezomib disrupt protein homeostasis in Wilms tumor
Tiburcio PDB, Chen K, Xu L et al. · bioRxiv : the preprint server for biology 2024 · PMID 38948702 · doi:10.1101/2024.06.11.598518
This dataset
Open GSE270330 in finder → Find more human RNA-seq datasets → Wilms tumour landscape →
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 GSE270330_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 PRJNA1126209 and SRA study SRP515023. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38948702) ↗
Study design
6 conditions, mostly in triplicate
WiT49, actD, 6hr, ×3 WiT49, DMSO, 6hr, ×3 WiT49, actD, 72hr, ×3 WiT49, DMSO, 72hr, ×3 WiT49, actD, 2wk, ×3 WiT49, DMSO, 2wk, ×3 WiT49, actD, 6hr, rep1, riboseq ×1 WiT49, actD, 6hr, rep2, riboseq ×1 +16 more

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 36 sample titles; they account for 18 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
More Wilms tumour datasets

Search all human RNA-seq datasets in GEO →

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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.