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Finding Sorafenib-Responding Signature in Hepatocellular Carcinoma (HCC)

GSE285625 Homo sapiens (human) RNA-seq (gene expression) 33 samples Submitted 2025/12/31 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 33 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
Hepatocellular carcinomaThis series is part of our curated briefing on it.
Samples
33 samples
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
Identifying sorafenib benefit among patients with hepatocellular carcinoma: A transcriptomic and genomic approachJHEP reports : innovation in hepatology · 2026
Summary (written by the submitters)
Sorafenib has been a cornerstone in hepatocellular carcinoma (HCC) therapy; however, its efficacy is limited, and identifying patients that will respond to sorafenib is challenging. Gene expression data from 33 HCC tumors treated with sorafenib were analyzed to construct a prediction model aimed at identifying patients with greater benefit from sorafenib treatment.
Read the full summary ↓
The analysis of transcriptome data revealed a 50-gene signature, KUSS50 (Korea University Sorafenib Signature with 50 genes), that exhibited high predictive power in identifying patients responded to sorafenib treatment in a training cohort. Extensive validation across 2 independent cohorts (IMbrave150 and BIOSTORM) given sorafenib demonstrated KUSS50's high specificity in predicting sorafenib response. Genomic analyses identified distinct molecular characteristics linked with KUSS50 subtypes, including an increased mutation rate and activation of ferroptosis, suggesting increased baseline ferroptotic activity in HCCs, which may sensitize them to sorafenib. The benefit subtype also overlapped with those in previously defined genomic HCC subtypes associated with stemness and aggressiveness. Conversely, the non-benefit subtype correlated with -catenin mutations and increased tumor purity, underscoring the biological significance of the signature. In conclusion, KUSS50 is a clinically actionable biomarker for optimizing HCC patient selection for treatment with sorafenib, providing an opportunity to improve outcomes. Further exploration of KUSS50's underlying biology, particularly the involvement of ferroptosis in sorafenib sensitivity, could provide additional therapeutic insights.
Published in
Identifying sorafenib benefit among patients with hepatocellular carcinoma: A transcriptomic and genomic approach
Yim SY, Kim H, Kim TH et al. · JHEP reports : innovation in hepatology 2026 · PMID 41810428 · doi:10.1016/j.jhepr.2026.101742
This dataset
Open GSE285625 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 GSE285625_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 PRJNA1204978 and SRA study SRP554727. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41810428) ↗
Study design
A cohort of 33 individual samples

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

How we read this: Sample titles run T02 … T41 and carry no group information.

Samples in this study
More Hepatocellular carcinoma datasets

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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.