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Bidirection activation of stem-like programs in metastatic cancer and alveolar type II cells within the niche [ATAC-seq]

GSE240038 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 12 samples Submitted 2024/05/02 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 12 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
12 samples: 3 × AT2 cells (4T1 Distal) vs 3 × AT2 cells (4T1 Niche) vs 3 × AT2 cells (CT26 Distal) vs 3 × AT2 cells (CT26 Niche)Groups 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)
A key step for metastatic outgrowth involves the generation of a deeply altered microenvironment (niche) that supports the malignant behavior of cancer cells. However, it is unclear whether a fundamental program driving the generation of this de novo cellular environment can be identified. Here, by focusing on breast cancer metastasis to the lung, we describe a cancer-dependent chromatin remodeling and activation of developmental programs in alveolar type II (AT2) cells.
Read the full summary ↓
We have identified a relationship linking high metastatic competency in the lung with the induction of a multilineage state in AT2 cells in the niche. In turn, this cancer-induced reprogramming of AT2 cells promoted stem-like features in the cancer cells. In conclusion, we propose the concept of “reflected stemness” during metastatic niche initiation, whereby metastatic cells reprogram the local tissue into a stem-like state that enhance intrinsic cancer-initiating potential, creating a positive feedback loop where tumorigenic programs may be amplified.
This dataset
Open GSE240038 in finder → Find more mouse ChIP / ATAC / CUT&Tag 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 GSE240038_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 PRJNA1001961 and SRA study SRP453248. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × AT2 cells (4T1 Distal) vs 3 × AT2 cells (4T1 Niche) vs 3 × AT2 cells (CT26 Distal) vs 3 × AT2 cells (CT26 Niche)

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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.