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Distinct Function for ASCL1 and NEUROD1 in Pulmonary Neuroendocrine Tumors (RNA-seq)

GSE69393 Homo sapiens (human) RNA-seq (gene expression) 6 samples Submitted 2016/07/21 Platform GPL13112Platform GPL9520
At a glance

RNA-seq (gene expression) · human · 6 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
6 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)
Small cell lung carcinoma (SCLC) and large cell neuroendocrine carcinoma (LCNEC) are high-grade pulmonary neuroendocrine tumors. The neural basic helix-loop-helix (bHLH) transcription factors ASCL1 and NEUROD1 have been shown to play crucial roles in promoting the malignant behavior and survival of human SCLC cell lines. In this study, we find ASCL1 and NEUROD1 identify distinct neuroendocrine tumors, bind distinct genomic loci, and regulate mostly distinct genes.
Read the full summary ↓
ASCL1 and NEUROD1 are often bound in super-enhancers that are associated with highly expressed genes in their respective SCLC cell lines suggesting different cell lineage of origin for these tumors. ASCL1 targets oncogenic genes such as MYCL1, RET, and NFIB, while NEUROD1 targets the oncogenic gene MYC. Although ASCL1 and NEUROD1 regulate different genes, many of these gene targets commonly contribute to neuroendocrine and cell migration function. ASCL1 in particular also regulates genes in the NOTCH pathway and genes important in cell-cycle dynamics. Finally, we demonstrate ASCL1 but not NEUROD1 is required for SCLC and LCNEC tumor formation in current in vivo genetic mouse models of pulmonary neuroendocrine tumors
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 GSE69393_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 PRJNA285362 and SRA study SRP058871. Searching any of these in the dataset finder brings you back here.

Samples in this study

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