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Alphavirus M1 disrupts super-enhancer-driven oncogenic transcription in osteosarcoma [RNA-seq]

GSE293856 Homo sapiens (human) RNA-seq (gene expression) 32 samples Submitted 2026/05/31 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 32 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
OsteosarcomaThis series is part of our curated briefing on it.
Samples
32 samples: 12 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.
Summary (written by the submitters)
Oncolytic virotherapy has shown promise for various cancers, but its application in osteosarcoma (OS) remains underexplored. This study provides the first evidence of the potent oncolytic activity of M1, a natural Getah-like alphavirus, against OS. We demonstrate that OS cells exhibit heightened sensitivity to M1 infection, with its anti-tumor effects not solely dependent on the canonical ER stress-induced apoptosis.
Read the full summary ↓
Proteomic and ChIP-seq analyses show the DNA-directed RNA polymerase II subunit RPB1 contributes to oncogenic super-enhancer activity and serves as a direct target of M1-mediated regulation. The oncolytic potency correlated positively with the transcriptional dependency on RPB1 within super-enhancer regions. Mechanistically, the viral non-structural protein NSP2 disrupts super-enhancer activity by recruiting the CUL2-RBX1-ELOC complex, which triggers K63-linked ubiquitination and degradation of RPB1. These findings uncover a previously unrecognized oncolytic mechanism of M1 and its therapeutic potential in OS, with RPB1 as a predictive biomarker for virotherapy response.
This dataset
Open GSE293856 in finder → Find more human RNA-seq datasets → Osteosarcoma 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 GSE293856_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 PRJNA1246599 and SRA study SRP576529. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 conditions, mostly in triplicate
U2-OS cells, pre-M1 virus infection, biol ×3 U2-OS cells, 6 hours post-M1 virus infection,… ×3 U2-OS cells, 12 hours post-M1 virus infection… ×3 U2-OS cells, 24 hours post-M1 virus infection… ×3 SJSA-1 cells, pre-M1 virus infection, biol ×3 SJSA-1 cells, 6 hours post-M1 virus infection… ×3 SJSA-1 cells, 12 hours post-M1 virus infectio… ×3 SJSA-1 cells, 24 hours post-M1 virus infectio… ×3 +4 more

Supports a case/control comparison: 4 samples read as cases, 4 as controls.

How we read this: 12 replicated groups read from 32 sample titles; they account for 32 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 Osteosarcoma datasets

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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.