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The lineage master transcription factor, p63 recruits a cancer-specific cofactor, FOXK1 to mediate oncogenic 3D chromatin dynamics in squamous cell carcinoma [RNA-seq]

GSE274688 Homo sapiens (human) RNA-seq (gene expression) 22 samples Submitted 2026/07/13 Platform GPL34284Platform GPL11154Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 22 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
22 samples: 11 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.
Summary (written by the submitters)
Transcriptional dysregulation by a lineage master transcription factor (TF) is a critical mechanism in cancer, involving alteration of three-dimensional (3D) chromatin architecture. However, the underlying mechanisms of altered master TF-dependent chromatin interactions in cancer cells remain unclear. Here, we employ multi-omic approaches to examine chromatin interactions dependent on p63, a master TF in epidermis, in squamous cell carcinomas (SCCs) compared to normal keratinocytes (KCs), integrating chromatin looping and accessibility, transcriptome, p63 binding and proteomics.
Read the full summary ↓
p63 facilitates higher connectivity between the promoters of prognostic genes in SCCs, and distal enhancers. Many SCC-specific p63-dependent genes are connected to SCC-specific p63-dependent epigenetic signature via a cis-regulatory element (CRE) without the signature, referred to as ‘Secondary’ regulation mode. Notably, we identify FOXK1 as a cancer-specific cofactor, cooperating with p63 to shape the oncogenic chromatin landscape, inhibiting cell proliferation. Our findings suggest the p63-FOXK1 axis as a potential target for cancer therapy in SCCs.
This dataset
Open GSE274688 in finder → Find more human RNA-seq datasets →
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 GSE274688_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 PRJNA1147657 and SRA study SRP526067. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
11 conditions, mostly in duplicate
RNA-seq_CAL27,control siRNA, ×2 RNA-seq_CAL27,p63 siRNA, ×2 RNA-seq_SCC13,control siRNA, ×2 RNA-seq_SCC13,p63 siRNA, ×2 RNA-seq_Undifferentiated KC,control siRNA, ×2 RNA-seq_Undifferentiated KC,p63 siRNA, ×2 RNA-seq_Differentiated KC,control siRNA, ×2 RNA-seq_Differentiated KC,p63 siRNA, ×2 +3 more

Supports a case/control comparison: 2 samples read as cases, 12 as controls.

How we read this: 11 replicated groups read from 22 sample titles; they account for 22 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
Datasets on a similar topic

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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.