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Foxa1-Mediated Chromatin Remodeling and Enhancer Reprogramming Promotes Gemcitabine Resistance in Pancreatic Cancer

GSE278100 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 54 samples Submitted 2024/11/30 Platform GPL21273
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 54 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
Mus musculus (mouse)
Samples
54 samples: 18 conditions, mostly in triplicateGroups 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)
Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy characterized by a poor prognosis, and resistance to gemcitabine, a frontline chemotherapeutic agent, poses a significant challenge to effective treatment. Unraveling the molecular underpinnings of gemcitabine resistance is essential for devising novel therapeutic strategies.
Read the full summary ↓
Here we derived gemcitabine-resistant and parental pancreatic cancer cell lines from KPC mouse models of PDAC. Employing a multi-omics approach, we integrated RNA-seq, ATAC-seq, and ChIP-seq analyses to characterize the genome-wide alterations in gene transcription, chromatin accessibility, histone modifications, and transcription factor (TF) binding in resistant cells. High-throughput chromatin conformation capture (Hi-C) was used to explore 3D chromatin remodeling. Our analyses identified differentially expressed genes (DEGs) critical for gemcitabine metabolism and resistance, notably Rrm1 and Cdadc1. We observed the upregulation of NF-kB, p53, and MAPK pathways, and the downregulation of mTORC1, MYC targets, and reactive oxygen species pathways. Differentially accessible regions (DARs) showed a significant positive correlation with the expression patterns of DEGs and histone mark H3K27 acetylation. Motif enrichment analyses revealed that TFs from the AP-1, Fox, and Hox families were significantly enriched at DARs, underscoring Foxa1 as a pivotal regulator of resistance-associated genes. We discovered that 3D chromatin reorganization, particularly the enhancement of enhancer-promoter interactions involving super-enhancer (SE) reprogramming mediated by Foxa1 and Ctcf/Smc3, drives the expression of critical resistance genes. Targeting Foxa1 or disrupting SE-associated transcription using JQ1, a bromodomain inhibitor, effectively inhibited resistant cell proliferation and enhanced gemcitabine sensitivity. In summary, this study elucidates the role of TF-mediated chromatin remodeling in gemcitabine resistance and suggests that targeting super-enhancers could be a promising therapeutic strategy to overcome resistance in PDAC, potentially revolutionizing drug therapy for this disease.
This dataset
Open GSE278100 in finder → Find more mouse 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 GSE278100_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 PRJNA1165706 and SRA study SRP534984. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
18 conditions, mostly in triplicate
RNA-seq, Parental cells, ×3 RNA-seq, Gemcitabine-resistant cells, ×3 ATAC-seq, Parental cells, ×3 ATAC-seq, Gemcitabine-resistant cells, ×3 ChIP-seq, Foxa1, Parental cells, ×3 ChIP-seq, Foxa1, Gemcitabine-resistant cells, ×3 ChIP-seq, H3K27ac, Parental cells, ×3 ChIP-seq, H3K27ac, Gemcitabine-resistant cell… ×3 +10 more

Supports a between-group comparison across 54 samples.

How we read this: 18 replicated groups read from 54 sample titles; they account for 54 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

+ 14 more — browse all 54 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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