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Effects of SLC2A1 knockdown in intrahepatic cholangiocarcinoma (ICC) cancer-associated fibroblasts (CAFs) on endothelial sprouting under normal and hypoxic conditions

GSE316921 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/01/30 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 12 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
CholangiocarcinomaThis series is part of our curated briefing on it.
Samples
12 samples: 3 × ICC CAF cells, shControl, Control condition, vs 3 × ICC CAF cells, shControl, Hypoxic condition, vs 3 × ICC CAF cells, shSLC2A1, Control condition, vs 3 × ICC CAF cells, shSLC2A1, Hypoxic condition,Groups 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.
Summary (written by the submitters)
Hypoxia is a critical determinant of endothelial sprouting. We here demonstrate that hypoxia-driven remodeling of the ICC tumor microenvironment promotes the emergence of a distinct CAF subset, termed tumor-like CAF (tCAF). We further identify SLC2A1 in tCAFs as a potential key regulator that facilitates endothelial sprouting, although the underlying molecular mechanisms remain to be elucidated.
Read the full summary ↓
Collectively, our data provide a molecular basis for the aggressive vascular invasive phenotype of ICC and delineate a hypoxia–tCAF–endothelial cell signaling axis, highlighting SLC2A1 as a potential therapeutic target for disrupting tumor angiogenesis in ICC.
This dataset
Open GSE316921 in finder → Find more human RNA-seq datasets → Cholangiocarcinoma landscape →
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.

Series matrix ↓
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 GSE316921_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA1405544 and SRA study SRP664686. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × ICC CAF cells, shControl, Control condition, vs 3 × ICC CAF cells, shControl, Hypoxic condition, vs 3 × ICC CAF cells, shSLC2A1, Control condition, vs 3 × ICC CAF cells, shSLC2A1, Hypoxic condition,

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 of them. 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.

Samples in this study
More Cholangiocarcinoma datasets

Search all human RNA-seq datasets in GEO →

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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.