GEO series

Investigating therapy-induced senescence as a reversible escape mechanism of drug resistance in breast cancer cells using high-dose doxorubicin treatment [RNA-seq]

GSE287953 Homo sapiens (human) RNA-seq (gene expression) 45 samples Submitted 2025/05/07 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 45 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: Breast cancerThis series is part of our curated briefing on it.
Samples: 45 samples: 14 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: Therapy-induced senescence is a transient drug resistance mechanism in breast cancerMolecular cancer · 2025

Summary (written by the submitters)

The emergence of drug resistance remains a critical challenge in cancer treatment, significantly contributing to high mortality rates. Here, we investigate therapy-induced senescence (TIS) as a reversible escape mechanism of drug resistance in breast cancer cells. Using high-dose doxorubicin, we induced TIS in MCF7, T47D, MDA-MB-231 and Hs578T breast cancer cell lines.

Read the full summary ↓

Bulk RNA sequencing revealed a unique transcriptomic profile in TIS cells, distinct from both parental and repopulated cells in every cell line, exposing a small subpopulation of TIS cells with the potential to escape senescence. Gene set enrichment analysis indicated significant downregulation of proliferation-related genes, downregulation of DNA repair pathways, and the upregulation of immune response related genes.

Published in

Therapy-induced senescence is a transient drug resistance mechanism in breast cancer

Bajtai E, Kiss C, Bakos É et al. · Molecular cancer 2025 · PMID 40312750 · doi:10.1186/s12943-025-02310-0

This dataset

Open GSE287953 in finder → Find more human RNA-seq datasets → Breast cancer 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 GSE287953_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 PRJNA1215351 and SRA study SRP559762. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40312750) ↗

Study design

14 conditions, mostly in triplicate

MDA-MB-231, CTR, RNA-seq, ×4 MDA-MB-231, TIS, RNA-seq, ×4 MDA-MB-231, REPOP, RNA-seq, ×4 MCF7, CTR, RNA-seq, ×3 T47D, CTR, RNA-seq, ×3 Hs578T, CTR, RNA-seq, ×3 HFF, CTR, RNA-seq, ×3 MCF7, TIS, RNA-seq, ×3 +6 more

Supports a between-group comparison across 45 samples.

How we read this: 14 replicated groups read from 45 sample titles; they account for 45 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

GSM8756130 MCF7, CTR, RNA-seq, replicate 1 MCF7, CTR, RNA-seq,
GSM8756131 MCF7, CTR, RNA-seq, replicate 2 MCF7, CTR, RNA-seq,
GSM8756132 MCF7, CTR, RNA-seq, replicate 3 MCF7, CTR, RNA-seq,
GSM8756133 T47D, CTR, RNA-seq, replicate 1 T47D, CTR, RNA-seq,
GSM8756134 T47D, CTR, RNA-seq, replicate 2 T47D, CTR, RNA-seq,
GSM8756135 T47D, CTR, RNA-seq, replicate 3 T47D, CTR, RNA-seq,
GSM8756136 MDA-MB-231, CTR, RNA-seq, replicate 1 MDA-MB-231, CTR, RNA-se…
GSM8756137 MDA-MB-231, CTR, RNA-seq, replicate 2 MDA-MB-231, CTR, RNA-se…
GSM8756138 MDA-MB-231, CTR, RNA-seq, replicate 3 MDA-MB-231, CTR, RNA-se…
GSM8756139 MDA-MB-231, CTR, RNA-seq, replicate 4 MDA-MB-231, CTR, RNA-se…
GSM8756140 Hs578T, CTR, RNA-seq, replicate 1 Hs578T, CTR, RNA-seq,
GSM8756141 Hs578T, CTR, RNA-seq, replicate 2 Hs578T, CTR, RNA-seq,
GSM8756142 Hs578T, CTR, RNA-seq, replicate 3 Hs578T, CTR, RNA-seq,
GSM8756143 HFF, CTR, RNA-seq, replicate 1 HFF, CTR, RNA-seq,
GSM8756144 HFF, CTR, RNA-seq, replicate 2 HFF, CTR, RNA-seq,
GSM8756145 HFF, CTR, RNA-seq, replicate 3 HFF, CTR, RNA-seq,
GSM8756146 MCF7, TIS, RNA-seq, replicate 1 MCF7, TIS, RNA-seq,
GSM8756147 MCF7, TIS, RNA-seq, replicate 2 MCF7, TIS, RNA-seq,
GSM8756148 MCF7, TIS, RNA-seq, replicate 3 MCF7, TIS, RNA-seq,
GSM8756149 T47D, TIS, RNA-seq, replicate 1 T47D, TIS, RNA-seq,
GSM8756150 T47D, TIS, RNA-seq, replicate 2 T47D, TIS, RNA-seq,
GSM8756151 T47D, TIS, RNA-seq, replicate 3 T47D, TIS, RNA-seq,
GSM8756152 MDA-MB-231, TIS, RNA-seq, replicate 1 MDA-MB-231, TIS, RNA-se…
GSM8756153 MDA-MB-231, TIS, RNA-seq, replicate 2 MDA-MB-231, TIS, RNA-se…
GSM8756154 MDA-MB-231, TIS, RNA-seq, replicate 3 MDA-MB-231, TIS, RNA-se…
GSM8756155 MDA-MB-231, TIS, RNA-seq, replicate 4 MDA-MB-231, TIS, RNA-se…
GSM8756156 Hs578T, TIS, RNA-seq, replicate 1 Hs578T, TIS, RNA-seq,
GSM8756157 Hs578T, TIS, RNA-seq, replicate 2 Hs578T, TIS, RNA-seq,
GSM8756158 Hs578T, TIS, RNA-seq, replicate 3 Hs578T, TIS, RNA-seq,
GSM8756159 HFF, TIS, RNA-seq, replicate 1 HFF, TIS, RNA-seq,
GSM8756160 HFF, TIS, RNA-seq, replicate 2 HFF, TIS, RNA-seq,
GSM8756161 HFF, TIS, RNA-seq, replicate 3 HFF, TIS, RNA-seq,
GSM8756162 MCF7, REPOP, RNA-seq, replicate 1 MCF7, REPOP, RNA-seq,
GSM8756163 MCF7, REPOP, RNA-seq, replicate 2 MCF7, REPOP, RNA-seq,
GSM8756164 MCF7, REPOP, RNA-seq, replicate 3 MCF7, REPOP, RNA-seq,
GSM8756165 T47D, REPOP, RNA-seq, replicate 1 T47D, REPOP, RNA-seq,
GSM8756166 T47D, REPOP, RNA-seq, replicate 2 T47D, REPOP, RNA-seq,
GSM8756167 T47D, REPOP, RNA-seq, replicate 3 T47D, REPOP, RNA-seq,
GSM8756168 MDA-MB-231, REPOP, RNA-seq, replicate 1 MDA-MB-231, REPOP, RNA-…
GSM8756169 MDA-MB-231, REPOP, RNA-seq, replicate 2 MDA-MB-231, REPOP, RNA-…

+ 5 more — browse all 45 samples with per-sample file links →

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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.