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Enhancer invasion shapes MYCN dependent transcriptional amplification in neuroblastoma

GSE80154 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 144 samples Submitted 2018/01/29 Platform GPL18573Platform GPL11154Platform GPL19057Platform GPL16043
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 144 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
NeuroblastomaThis series is part of our curated briefing on it.
Samples
144 samples
Data you can get
A processed expression table (series matrix) and the array files, from NCBI.
Summary (written by the submitters)
Amplification of the locus encoding the oncogenic transcription factor MYCN is a defining feature of high-risk neuroblastoma. Here we present the first dynamic chromatin and transcriptional landscape of MYCN perturbation in neuroblastoma. At oncogenic levels, MYCN associates with E-box binding motifs in an affinity-dependent manner, binding to strong canonical E-boxes at promoters and invading abundant weaker non-canonical E-boxes clustered at enhancers.
Read the full summary ↓
Loss of MYCN leads to a global reduction in transcription, which is most pronounced at MYCN target genes with the greatest enhancer occupancy. These highly occupied MYCN target genes show tissue-specific expression and are linked to poor patient survival. The activity of genes with MYCN-occupied enhancers is dependent on the tissue-specific transcription factor TWIST1, which co-occupies enhancers with MYCN and is required for MYCN-dependent proliferation. These data implicate tissue-specific enhancers in defining often highly tumor-specific ‘MYC target gene signatures’ and identify disruption of the MYCN enhancer regulatory axis as a promising therapeutic strategy in neuroblastoma.
This dataset
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.

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 GSE80154_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA318035 and SRA study SRP073110. Searching any of these in the dataset finder brings you back here.

Samples in this study

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