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Polyploid cisplatin-resistant cancer cells have altered nuclear organization and epigenomic status

GSE297299 Homo sapiens (human) RNA-seq (gene expression) 16 samples Submitted 2025/05/19 Platform GPL34281Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 16 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
16 samples: 16 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
Polyploid cisplatin-resistant cancer cells have altered nuclear organization and epigenomic statusNeoplasia (New York, N.Y.) · 2026
Summary (written by the submitters)
Chemotherapy resistance remains a critical barrier in cancer treatment, partly driven by polyploid cells that survive therapy and contribute to tumor recurrence. Here, we investigated epigenomic and transcriptional changes associated with cisplatin-surviving polyploid cells compared to parental cancer cells in prostate cancer (PC3) and triple-negative breast cancer (MDA-MB-231) cell lines.
Read the full summary ↓
We observed persistent dysregulation of chromatin compaction and altered nuclear structure in polyploid cells following cisplatin treatment. Genome-wide chromatin accessibility profiling via ATAC-seq revealed significant remodeling, notably decreased promoter accessibility at proliferation-associated loci and increased accessibility of distal regulatory elements linked to inflammation and stress response. RNA-seq analyses demonstrated a coordinated transcriptional shift away from proliferative signatures toward inflammatory and survival pathways, including activation of NFκB, interferon response, and integrated stress response pathways. Importantly, we identified subsets of genes showing concordant changes in promoter accessibility and transcriptional activity, directly linking chromatin remodeling to transcriptional reprogramming. These integrated findings highlight the role of chromatin dynamics and epigenetic plasticity in chemotherapy resistance, demonstrating that widespread chromatin accessibility changes facilitate the transition to a stress-adapted, polyploid cell state. This study provides new insights into the molecular mechanisms supporting cancer cell persistence after chemotherapy.
Published in
Polyploid cisplatin-resistant cancer cells have altered nuclear organization and epigenomic status
Gonye AL, Orzolek L, Cherry C et al. · Neoplasia (New York, N.Y.) 2026 · PMID 41570447 · doi:10.1016/j.neo.2025.101268
This dataset
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.

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 GSE297299_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1263486 and SRA study SRP585605. Searching any of these in the dataset finder brings you back here.

Study design
16 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 16 sample titles: 16 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
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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.