GEO series

Exome and whole genome sequencing of esophageal adenocarcinoma identifies recurrent driver events and mutational complexity

GSE42363 Homo sapiens (human) Expression microarray 14 samples Submitted 2013/02/11 Platform GPL570

At a glance

Expression microarray · human · 14 samples

What it is: Expression microarrayGene activity read on a chip (the older technology that RNA-seq replaced).
Organism: Homo sapiens (human)
Topic: Esophageal cancerThis series is part of our curated briefing on it.
Samples: 14 samples
Data you can get: A processed expression table (series matrix) and the array files, from NCBI.

Summary (written by the submitters)

The incidence of esophageal adenocarcinoma (EAC) has risen 600% over the last 30 years. With an extremely poor five-year survival rate of only 15%, identification of new therapeutic targets for EAC is of great importance. Here, we analyze the mutation spectra from the whole exome sequencing of 149 EAC tumors/normal pairs, 15 of which have also been subjected to whole genome sequencing.

Read the full summary ↓

We identify a novel mutational signature in EACs defined by a high prevalence of A to C transversions at Ap*A dinucleotides. Statistical analysis of the exome data identified 26 genes that are mutated at a significant frequency. Of these 26 genes, only four (TP53, CDKN2A, SMAD4, and PIK3CA) have been previously implicated in EAC. The novel significantly mutated genes include several chromatin modifying factors and candidate contributors to EAC: SPG20, TLR4, ELMO1, and DOCK2. Notably, functional analyses of EAC-derived mutations in ELMO1 increase cellular invasion. Therefore, we suggest a new hypothesis about the potential activation of the RAC1 pathway to be a contributor to EAC tumorigenesis.

This dataset

Open GSE42363 in finder → Find more human microarray datasets → Esophageal cancer landscape →

Download · which file do I need?

Direct links to NCBI, 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.

All supplementary files ↗

3 · The original raw files

Whole study · RAW.tar

Everything the authors deposited as one archive (GSE42363_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

Whole study · RAW.tar ↓

What the files usually look like: For arrays the series matrix is normally the normalised expression table you want; the raw array files (CEL and similar) are in the RAW.tar.

Also filed as BioProject PRJNA181161. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 23525077) ↗

Samples in this study

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

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GSE180791 Proteogenomic characterization reveals that lipid droplet formation promotes esophageal squamous cell cancer progression 102 samples same disease briefing · shares esophageal
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GSE203067 Single-Cell Transcriptomic Analysis of Primary and Metastatic Tumor Ecosystems in Esophageal Squamous Cell Carcinoma 21 samples same disease briefing · shares esophageal
GSE182090 RNA-sequencing assay to Identify Genes Promoting Lung Metastasis of Esophageal Squamous Cell Carcinoma (ESCC) Cells 12 samples same disease briefing · shares esophageal
GSE225645 Hypoxia-induced gene expression profiling of esophageal cancer cell lines 12 samples same disease briefing · shares esophageal

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