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Opposing lineage specifiers induce a pro-tumor hybrid-identity state in lung adenocarcinoma [ChIP-seq]

GSE281961 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 60 samples Submitted 2025/06/13 Platform GPL24676Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 60 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
60 samples: 30 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
Opposing lineage specifiers induce a protumor hybrid identity state in lung adenocarcinomaGenes & development · 2025
Summary (written by the submitters)
Lineage plasticity is critical for tumor progression and therapy resistance, but the molecular mechanisms underlying cell identity shifts in cancer remain poorly understood. In lung adenocarcinoma (LUAD), the loss of pulmonary lineage fidelity and acquisition of alternate identity programs converge on hybrid-identity (hybrid-ID) states which are postulated to be key intermediates in LUAD evolution and are characterized by the co-activation of developmentally incompatible identity programs within individual cells.
Read the full summary ↓
Here, we uncover a previously unrecognized role for the gastrointestinal transcriptional regulator HNF4α in driving tumor growth and hybrid-ID states in LUAD. In LUAD cells expressing the lung lineage specifier NKX2-1, HNF4α induces a GI/liver-like state by directly binding and activating its canonical targets. HNF4α also disrupts NKX2-1 genomic localization and dampens pulmonary identity within hybrid-ID LUAD. We show that this hybrid-ID state is maintained by sustained by RAS/MEK signaling. Inhibition of the RAS/MEK signaling cascade augments NKX2-1 chromatin binding at pulmonary-specific genes and induces drug resistance-associated pulmonary signatures. Finally, we demonstrate that HNF4α depletion sensitizes LUAD cells to KRASG12D inhibition. Collectively, our data show that co-expression of opposing lineage specifiers is a novel mechanism of identity dysregulation in LUAD that influences both tumor progression and response to targeted therapy.
Published in
Opposing lineage specifiers induce a protumor hybrid identity state in lung adenocarcinoma
Fort G, Arnold H, Camolotto SA et al. · Genes & development 2025 · PMID 40506247 · doi:10.1101/gad.352742.125
This dataset
Open GSE281961 in finder → Find more ChIP / ATAC / CUT&Tag 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 GSE281961_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 PRJNA1186328 and SRA study SRP545352. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40506247) ↗
Study design
30 conditions, mostly in duplicate
3154_EtOH_Input ×2 3154_EtOH_HNF4a ×2 3154_EtOH_NKX2-1 ×2 3154_EtOH_FoxA1 ×2 3154_EtOH_FoxA2 ×2 3154_4OHT_Input ×2 3154_4OHT_NKX2-1 ×2 3154_4OHT_FoxA1 ×2 +22 more

Supports a between-group comparison across 60 samples.

How we read this: 30 replicated groups read from 60 sample titles; they account for 60 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

+ 20 more — browse all 60 samples with per-sample file links →

More Lung cancer datasets

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