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MYC couples SWI/SNF and metabolic reprogramming to sustain minimal residual disease in mTORC1-activated cancer cells [RNA-seq]

GSE270777 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2025/06/10 Platform GPL24676Platform GPL24247
At a glance

RNA-seq (gene expression) · human · 18 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
18 samples: 8 conditions, mostly in duplicateGroups 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)
Therapeutics blocking PI3K-mTORC1 are commonly used for tumor treatment, and at times achieve major responses, yet minimal residual disease (MRD) persists, leading to tumor relapse. We examined the MRD models established both in vitro (Rapamycin persistent, RP) and in vivo after mTORC1 inhibition. All RP/MRD cell lines showed complete growth and signaling insensitivity to rapamycin but variable sensitivity to bi-steric mTORC1 inhibitors.
Read the full summary ↓
MTORS2035 mutations were identified in 4 of 7 RP cell lines. Multi-omic analysis identified a pronounced shift to oxidative phosphorylation and away from glycolysis in all RP/MRD models, with increased mitochondrial number and function. MYC and SWI/SNF expression were greatly enhanced. Both the SWI/SNF inhibitor AU-15330 and the Complex I inhibitor of oxidative phosphorylation IACS-010759 showed pronounced synergy with bi-steric mTORC1 inhibitors to cause cuproptotic cell death in RP/MRD cells, suggesting these combinations as a potential patient treatment strategy for rapalog resistance.
This dataset
Open GSE270777 in finder → Find more 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 GSE270777_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 PRJNA1128159 and SRA study SRP516122. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly in duplicate
m705RP ×3 HCV29RP ×3 CDX ×2 CDXRP ×2 H101C ×2 H101RP ×2 PDX ×2 PDXRP ×2

Supports a between-group comparison across 18 samples.

How we read this: 8 replicated groups read from 18 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
Datasets on a similar topic

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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.