The pluripotency factor NANOG contributes to mesenchymal plasticity and is predictive for outcome in esophageal adenocarcinoma
RNA-seq (gene expression) · human · 106 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)
- Topic
- Esophageal cancerThis series is part of our curated briefing on it.
- Samples
- 106 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.
- Paper
- The pluripotency factor NANOG contributes to mesenchymal plasticity and is predictive for outcome in esophageal adenocarcinomaCommunications medicine · 2024
Read the full summary ↓
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE254942_RAW.tar (it can run to tens of gigabytes).
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 PRJNA1072677. Searching any of these in the dataset finder brings you back here.
The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.
+ 106 more — browse all 106 samples with per-sample file links →
- GSE232467 Single-cell Transcriptomic Analysis Reveals Landscape of Epithelial-Mesenchymal Transition Molecular Heterogeneity in Esophageal Squamous Cell Carcinoma 6 samples same disease briefing · shares mesenchymal, esophageal
- GSE1420 Barrett's esophagus, Barrett's-associated adenocarcinomas and normal esophageal epithelium 24 samples same disease briefing · shares adenocarcinoma, esophageal
- GSE160269 Dissecting esophageal squamous-cell carcinoma ecosystem by single-cell transcriptomic analysis 128 samples same disease briefing · shares esophageal
- GSE180791 Proteogenomic characterization reveals that lipid droplet formation promotes esophageal squamous cell cancer progression 102 samples same disease briefing · shares esophageal
- GSE185617 Long non-coding RNA LINC00680 functions as a ceRNA to promote esophageal squamous cell carcinoma progression through the miR-423-5p/PAK6 axis 24 samples same disease briefing · shares esophageal
- 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
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.