GEO series

Single-cell RNA sequencing of human hepatocellular carcinoma and adjacent non-tumour liver tissues reveals etiology-associated and etiology-independent tumour microenvironmental features

GSE326201 Homo sapiens (human) Single-cell RNA-seq 18 samples Submitted 2026/05/27 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 18 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: Hepatocellular carcinomaThis series is part of our curated briefing on it.
Samples: 18 samples: 18 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.

Summary (written by the submitters)

Hepatocellular carcinoma (HCC) arises in the context of diverse aetiological backgrounds, yet the extent to which the tumour microenvironment is shaped by aetiology-associated versus aetiology-independent programmes remains incompletely understood. This dataset was generated to support interrogation of the cellular architecture of human HCC and the surrounding liver microenvironment at single-cell resolution.

Read the full summary ↓

By profiling tumour and adjacent non-tumour liver tissues, the study provides a resource for examining malignant, immune, stromal, and hepatic parenchymal cell populations, and for investigating shared and aetiology-linked features of the HCC tumour microenvironment.

This dataset

Open GSE326201 in finder → Find more human RNA-seq datasets → Hepatocellular carcinoma 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 GSE326201_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: 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 PRJNA1444132 and SRA study SRP687235. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

18 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 18 sample titles: 18 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.

Samples in this study

GSM9625168 HCC patient 001, HCV, non-tumour tissue
GSM9625169 HCC patient 001, HCV, tumour tissue
GSM9625170 HCC patient 002, NBNC, non-tumour tissue
GSM9625171 HCC patient 002, NBNC, tumour tissue
GSM9625172 HCC patient 004, HBV, non-tumour tissue
GSM9625173 HCC patient 004, HBV, tumour tissue
GSM9625174 HCC patient 005, NBNC, non-tumour tissue
GSM9625175 HCC patient 005, NBNC, tumour tissue
GSM9625176 HCC patient 006, NBNC, tumour tissue
GSM9625177 HCC patient 008, NBNC, non-tumour tissue
GSM9625178 HCC patient 008, NBNC, tumour tissue
GSM9625179 HCC patient 009, HBV, non-tumour tissue
GSM9625180 HCC patient 009, HBV, tumour tissue
GSM9625181 HCC patient 010, NBNC, tumour tissue
GSM9625182 HCC patient 011, HCV, non-tumour tissue
GSM9625183 HCC patient 011, HCV, tumour tissue
GSM9625184 HCC patient 012, HBV, non-tumour tissue
GSM9625185 HCC patient 012, HBV, tumour tissue

More Hepatocellular carcinoma datasets

GSE105130 Comprehensive analysis of Transcriptome Profiles in Hepatocellular Carcinoma patients 52 samples same disease briefing · shares hepatocellular
GSE140228 Landscape and Dynamics of Single Immune Cells in Hepatocellular Carcinoma 41 samples same disease briefing · shares hepatocellular
GSE14520 Gene expression data of human hepatocellular carcinoma (HCC) 488 samples same disease briefing · shares hepatocellular
GSE10143 Gene Expression in Fixed Tissues and Outcome in Hepatocellular Carcinoma 387 samples same disease briefing · shares hepatocellular
GSE107170 Molecular Signature of Hepatitis D Virus-Associated Hepatocellular Carcinoma 307 samples same disease briefing · shares hepatocellular
GSE109211 Molecular predictors of prevention of recurrence in hepatocellular carcinoma with sorafenib as adjuvant treatment in the phase 3 STORM trial 140 samples same disease briefing · shares hepatocellular
GSE10186 Integrative Transcriptome Analysis Reveals Common Molecular Subtypes of Human Hepatocellular Carcinoma 118 samples same disease briefing · shares hepatocellular
GSE114564 Identification of novel serum biomarkers in early-stage HCC patients. 118 samples same disease briefing

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.