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TP63-mediated enhancer reprogramming drives the squamous subtype of pancreatic ductal adenocarcinoma (RNA-seq)

GSE115462 Homo sapiens (human) RNA-seq (gene expression) 42 samples Submitted 2018/11/13 Platform GPL18573Platform GPL11154Platform GPL19057
At a glance

RNA-seq (gene expression) · human · 42 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
42 samples
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)
The aberrant expression of squamous lineage markers in pancreatic ductal adenocarcinoma (PDA) has been correlated with poor clinical outcomes. However, the functional role of this putative trans-differentiation event in PDA pathogenesis remains unclear. Here, we show that expression of the transcription factor TP63 (ΔN isoform) is sufficient to install and sustain the enhancer landscape and transcriptional signature of the squamous lineage in human PDA cells.
Read the full summary ↓
In addition, we demonstrate that TP63-driven enhancer reprogramming promotes aggressive tumor phenotypes, including enhanced cell motility and invasion and an accelerated growth of primary PDA tumors and metastases in vivo. Conversely, we provide evidence that squamous PDA remains addicted to TP63 to sustain the growth of primary tumors and metastases. Taken together, our study validates the functional significance of squamous trans-differentiation in PDA, and reveals TP63-based reprogramming of PDA cells as an experimental tool for investigating vulnerabilities linked to this cell fate transition.
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 GSE115462_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: 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 PRJNA475110 and SRA study SRP149985. Searching any of these in the dataset finder brings you back here.

Samples in this study

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