GEO series

In vivo manipulation of the protein homeostasis network in rhabdomyosarcoma

GSE270783 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/06/24 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 12 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: Soft tissue sarcomaThis series is part of our curated briefing on it.
Samples: 12 samples: 12 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: In vivo manipulation of the protein homeostasis network in rhabdomyosarcomaOncotarget · 2025

Summary (written by the submitters)

Dysregulation of the proteostasis network is associated with various diseases including cancer. Previous studies have shown that inhibiting components of this network, such as HSP70 chaperones, can selectively induce cell death in rhabdomyosarcoma (RMS), a common pediatric soft tissue sarcoma. Here we show that inhibiting VCP, an ATPase involved in protein degradation, activates the unfolded protein response and induces apoptosis in RMS, with a preclinical p97 inhibitor showing promising anti-tumor activity in mouse models.

Read the full summary ↓

The findings confirm the efficacy of targeting the proteostasis network in RMS and suggest that targeting compensatory network components might yield synergistic outcomes.

Published in

In vivo manipulation of the protein homeostasis network in rhabdomyosarcoma

Kwong K, Pan Y, Morales J et al. · Oncotarget 2025 · PMID 40879698 · doi:10.18632/oncotarget.28764

This dataset

Open GSE270783 in finder → Find more human RNA-seq datasets → Soft tissue sarcoma 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 GSE270783_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 PRJNA1128163 and SRA study SRP516090. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40879698) ↗

Study design

12 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 12 sample titles: 12 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

GSM8351834 X213,Sensitive_Vehicle
GSM8351835 X214,Sensitive_Vehicle
GSM8351836 X215,Sensitive_Vehicle
GSM8351837 X216,Sensitive_CB_5083
GSM8351838 X217,Sensitive_CB_5083
GSM8351839 X218,Sensitive_CB_5083
GSM8351840 X230,Resistant_Vehicle
GSM8351841 X231,Resistant_Vehicle
GSM8351842 X232,Resistant_CB_5083
GSM8351843 X233,Resistant_CB_5083
GSM8351844 X234,Resistant_CB_5083
GSM8351845 X253,Resistant_Vehicle

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GSE279954 mRNA/sRNA Co-Sequencing Reveals Multiple New Targeted Therapy Candidates in Rhabdomyosarcoma 26 samples same disease briefing · shares rhabdomyosarcoma
GSE292872 FANCM is Required for the PAX3::FOXO1-Driven Oncogenic Program in Rhabdomyosarcoma [RNA-Seq] 21 samples same disease briefing · shares rhabdomyosarcoma
GSE202614 TLE3 function in rhabdomyosarcoma tumor xenografts. 20 samples same disease briefing · shares rhabdomyosarcoma
GSE240287 RNA-sequencing of matched samples from rhabdomyosarcoma samples, obtained before therapy and mid-treatment resection 18 samples same disease briefing · shares rhabdomyosarcoma
GSE286950 PAX3-FOXO1 drives targetable cell state-dependent metabolic vulnerabilities in rhabdomyosarcoma 16 samples same disease briefing · shares rhabdomyosarcoma

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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.