GEO series

Reprogramming lineage features promotes epithelial behavior in carcinoma cells [ChIP-Seq]

GSE308983 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 23 samples Submitted 2026/08/06 Platform GPL16791

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 23 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: 23 samples: 23 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: Reprogramming lineage features promotes epithelial behavior in carcinoma cellsCancer letters · 2026

Summary (written by the submitters)

Cancer cells distort epigenetic control of gene expression, allowing for a remarkable degree of plasticity and loss of cell type identity. At the same time, expression of identity-discordant lineage determinants can significantly shift cell phenotype by creating lineage hybrid states. One example is the misexpression of IKZF3, encoding the lymphocyte restricted transcription factor Aiolos, by roughly half of non-small cell lung carcinomas (NSCLC) and the majority of small cell lung carcinomas [1].

Read the full summary ↓

During normal lymphocyte development, pre-B progenitors enter a proliferative phase dependent on survival cues from bone marrow stroma. To progress, Aiolos and its paralog Ikaros (IKZF1) repress multiple adhesion-related genes, releasing cells from this epithelial-type dependence on solid matrix in preparation for their release as mature lymphocytes into the circulation [2, 3]. In lung cancers, unlicensed expression of Aiolos initiates a similar shift from an epithelial to a lymphocyte-like state by repression of multiple adhesion-related genes, resulting in loss of anoikis and consequent metastatic spread [1]. To reverse these lymphoid traits, we created a chimeric epigenetic editor designed to specifically retrieve Aiolos-repressed epithelial adhesion properties. Here, we demonstrate proof of principle for epithelial lineage restoration by exploiting a lymphocyte developmental pathway.

Published in

Reprogramming lineage features promotes epithelial behavior in carcinoma cells

Wu RF, Fu G, Liao C et al. · Cancer letters 2026 · PMID 41192784 · doi:10.1016/j.canlet.2025.218117

This dataset

Open GSE308983 in finder → Find more human 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 GSE308983_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 PRJNA1333529 and SRA study SRP625646. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41192784) ↗

Study design

23 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 23 sample titles: 23 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

GSM9257761 control bio rep 1, H3K27ac ChIP
GSM9257762 control bio rep 1, H3K27me3 ChIP
GSM9257763 control bio rep 1, input
GSM9257764 TA bio rep 1, H3K27ac ChIP
GSM9257765 TA bio rep 1, HA ChIP
GSM9257766 TA bio rep 1, H3K27me3 ChIP
GSM9257767 TA bio rep 1, input
GSM9257768 control bio rep 2, H3K27ac ChIP
GSM9257769 control bio rep 2, Aiolos ChIP
GSM9257770 control bio rep 2, H3K27me3 ChIP
GSM9257771 control bio rep 2, input
GSM9257772 TA bio rep 2, H3K27ac ChIP
GSM9257773 TA bio rep 2, HA ChIP
GSM9257774 TA bio rep 2, H3K27me3 ChIP
GSM9257775 TA bio rep 2, input
GSM9257776 control bio rep 3, H3K27ac ChIP
GSM9257777 control bio rep 3, Aiolos ChIP
GSM9257778 control bio rep 3, H3K27me3 ChIP
GSM9257779 control bio rep 3, input
GSM9257780 TA bio rep 3, H3K27ac ChIP
GSM9257781 TA bio rep 3, HA ChIP
GSM9257782 TA bio rep 3, H3K27me3 ChIP
GSM9257783 TA bio rep 3, input

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