Cancer-associated fibroblasts promote esophageal carcinogenesis and lung metastasis by CDH11-mediated extracellular matrix environment remodeling [scRNA-Seq]
Single-cell RNA-seq · human · 23 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Homo sapiens (human)
- Topic
- Esophageal cancerThis series is part of our curated briefing on it.
- Samples
- 23 samples: 23 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
- 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.
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 GSE309392_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA1335380 and SRA study SRP628865. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 23 sample titles: 23 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM9266755 scRNA-Seq of Homo sapiens:ESCC_normal1 [P1]
- GSM9266756 scRNA-Seq of Homo sapiens:ESCC_normal2 [P2]
- GSM9266757 scRNA-Seq of Homo sapiens:ESCC_normal3 [P3_4]
- GSM9266758 scRNA-Seq of Homo sapiens:ESCC_normal3 [P3_3]
- GSM9266759 scRNA-Seq of Homo sapiens:ESCC_normal3 [P3_2]
- GSM9266760 scRNA-Seq of Homo sapiens:ESCC_normal3 [P3_1]
- GSM9266761 scRNA-Seq of Homo sapiens:ESCC_normal4 [P4_4]
- GSM9266762 scRNA-Seq of Homo sapiens:ESCC_normal4 [P4_3]
- GSM9266763 scRNA-Seq of Homo sapiens:ESCC_normal4 [P4_2]
- GSM9266764 scRNA-Seq of Homo sapiens:ESCC_normal4 [P4_1]
- GSM9266765 scRNA-Seq of Homo sapiens:ESCC_normal5 [P5_4]
- GSM9266766 scRNA-Seq of Homo sapiens:ESCC_normal5 [P5_3]
- GSM9266767 scRNA-Seq of Homo sapiens:ESCC_normal5 [P5_2]
- GSM9266768 scRNA-Seq of Homo sapiens:ESCC_normal5 [P5_1]
- GSM9266769 scRNA-Seq of Homo sapiens:ESCC1 [P6]
- GSM9266770 scRNA-Seq of Homo sapiens:ESCC2 [P7]
- GSM9266771 scRNA-Seq of Homo sapiens:ESCC3 [P8]
- GSM9266772 scRNA-Seq of Homo sapiens:ESCC_met1 [P9]
- GSM9266773 scRNA-Seq of Homo sapiens:ESCC_met2 [P10]
- GSM9266774 scRNA-Seq of Homo sapiens:ESCC_met3 [P11_4]
- GSM9266775 scRNA-Seq of Homo sapiens:ESCC_met3 [P11_3]
- GSM9266776 scRNA-Seq of Homo sapiens:ESCC_met3 [P11_2]
- GSM9266777 scRNA-Seq of Homo sapiens:ESCC_met3 [P11_1]
- GSE182090 RNA-sequencing assay to Identify Genes Promoting Lung Metastasis of Esophageal Squamous Cell Carcinoma (ESCC) Cells 12 samples same disease briefing · shares esophageal, metastasis
- 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
- GSE225645 Hypoxia-induced gene expression profiling of esophageal cancer cell lines 12 samples same disease briefing · shares esophageal
- GSE201404 Ivermectin inhibits the growth of esophageal squamous cell carcinoma by activating ATF4-mediated endoplasmic reticulum stress-autophagy pathway 10 samples same disease briefing · shares esophageal
- GSE169337 Identification of differentially expressed genes in cisplatin-resistant and parental esophageal squamous cell carcinoma cells 8 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.