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Epigenetic priming promotes acquisition of TKI resistance and oncogene amplification in human lung cancer

GSE254521 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 146 samples Submitted 2025/02/26 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 146 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Topic
Lung cancerThis series is part of our curated briefing on it.
Samples
146 samples: 68 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.
Paper
Epigenetic priming promotes acquisition of tyrosine kinase inhibitor resistance and oncogene amplification in human lung cancerbioRxiv : the preprint server for biology · 2025
SuperSeries — this record groups several sub-series.
Summary (written by the submitters)
This SuperSeries is composed of the SubSeries listed below.
Published in
Epigenetic priming promotes acquisition of tyrosine kinase inhibitor resistance and oncogene amplification in human lung cancer
Starble RM, Sun EG, Gbyli R et al. · bioRxiv : the preprint server for biology 2025 · PMID 39974875 · doi:10.1101/2025.01.26.634826
This dataset
Open GSE254521 in finder → Find more human RNA-seq datasets → Lung 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 GSE254521_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1070705 and SRA study SRP557817. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39974875) ↗
Study design
68 conditions, mostly in duplicate
PC9_M7A_KO_H2A ×4 PC9_M7A_KO_osi_H2A ×4 PC9_WT_H2A ×4 PC9_WT_osi_H2A ×4 PC9-OR_RNA_Seq ×3 PC9_RNA_Seq ×3 H1975-OR_RNA_Seq ×2 H1975_RNA_Seq ×2 +60 more

Supports a between-group comparison across 146 samples.

How we read this: 68 replicated groups read from 146 sample titles; they account for 146 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

+ 106 more — browse all 146 samples with per-sample file links →

More Lung cancer datasets

Search all human RNA-seq datasets in GEO →

Share this dataset

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.