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Single-Cell Transcriptomic Profiling of the Tumor Microenvironment in Treatment-Naive Hepatocellular Carcinoma Patients

GSE290925 Homo sapiens (human) Single-cell RNA-seq 12 samples Submitted 2025/03/03 Platform GPL18573
At a glance

Single-cell RNA-seq · human · 12 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
12 samples: 12 × Before treatment in hcc caseGroups 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.
Paper
CRISPR/Cas9-mediated SHP-1-knockout T cells combined with simvastatin enhances anti-tumor activity in humanized-PDX HCC modeliScience · 2025
Summary (written by the submitters)
This study provides high-resolution single-cell RNA sequencing (scRNA-seq) data of tumor tissues from 12 treatment-naive hepatocellular carcinoma (HCC) patients. The dataset captures the transcriptomic profiles of diverse cell populations, including tumor cells, immune cells (e.g., T cells, B cells, macrophages), and stromal cells, revealing cellular heterogeneity and key gene expression signatures within the HCC tumor microenvironment (TME). This resource is critical for investigating HCC pathogenesis, identifying therapeutic targets, and developing immunotherapeutic strategies.
Published in
CRISPR/Cas9-mediated SHP-1-knockout T cells combined with simvastatin enhances anti-tumor activity in humanized-PDX HCC model
Liu H, Ge W, Yu X et al. · iScience 2025 · PMID 40241752 · doi:10.1016/j.isci.2025.112266
This dataset
Open GSE290925 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 GSE290925_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 PRJNA1230890 and SRA study SRP567577. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40241752) ↗
Study design
12 × Before treatment in hcc case

Supports a between-group comparison across 12 samples.

How we read this: 1 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 Hepatocellular carcinoma 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.