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Comprehensive Molecular Profiling of Combined Hepatocellular Carcinoma and Cholangiocarcinoma reveals Distinct Notch Signaling Subgroups with Prognostic Significance

GSE290614 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2025/03/04 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 18 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
18 samples: 6 conditions, mostly in triplicateGroups 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)
Combined hepatocellular carcinoma and cholangiocarcinoma (cHCC-CCC) exhibits distinct Notch signaling activation patterns, with elevated Notch1 and downstream target expression compared to HCC and CCC. Stratification into three subgroups based on Notch1 and Hes5 expression revealed that Notch-responsive tumors (high Notch1 and Hes5) demonstrated aggressive biological behavior, poor prognosis, and molecular profiles resembling CCC.
Read the full summary ↓
These findings underscore the heterogeneity of cHCC-CCC and suggest that Notch1 and Hes5 serve as potential biomarkers for risk stratification and therapeutic targeting, particularly for Notch pathway and immune checkpoint inhibitors.
This dataset
Open GSE290614 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 GSE290614_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 PRJNA1229012 and SRA study SRP566599. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40637792) ↗
Study design
6 conditions, mostly in triplicate
Normal liver tissue (Control) ×3 cHCC-CCC Notch Inactivated ×3 cHCC-CCC Notch Responsive ×3 cHCC-CCC Notch Non-responsive ×3 Cholangiocarcinoma ×3 Hepatocellularcarcinoma ×3

Supports a case/control comparison: 6 samples read as cases, 3 as controls.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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.