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XPO1inhibition induces NCOR1-Dependent oxidative stress to suppress hepatocellular carcinoma

GSE318009 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2026/06/14 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 24 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
24 samples: 8 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)
Hepatocellular carcinoma (HCC) remains a therapeutic challenge due to the limited efficacy of current systemic therapies. To identify potential novel therapeutic approaches, computational analysis of HCC datasets and drug screening were integrated, leading to the repurposing of hematological cancer drug selinexor (an XPO1 inhibitor) for HCC treatment.
Read the full summary ↓
Functional studies revealed that XPO1 inhibition triggers oxidative stress and cell cycle arrest in HCC cells through nuclear sequestration of NCOR1, disrupting redox homeostasis through FOXK1-dependent transcriptional activation of genes associated with Reactive Oxygen Species (ROS). A genome-wide CRISPR-Cas9 screen further identified the KEAP1-NRF2 axis as a key determinant of sensitivity to XPO1 inhibition. Furthermore, high-throughput compound screening demonstrated that disulfiram, a clinically-used aldehyde dehydrogenase inhibitor, synergizes with XPO1 inhibitor through exacerbation of ROS accumulation. Collectively, these findings demonstrate the therapeutic repurposing of selinexor for HCC while uncovering its novel mechanism of action, establishing a predictive biomarker, and proposing an immediately translatable combination therapy.
This dataset
Open GSE318009 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 GSE318009_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 PRJNA1416315 and SRA study SRP670334. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly in triplicate
Huh7 Ctrl ×3 Huh7 siNCOR1 ×3 Huh7 siNCOR1_KPT ×3 Huh7_KPT ×3 Hep3B_WT ×3 Hep3B_sgKEAP1 ×3 Huh7_WT ×3 Huh7_sgKEAP1 ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 replicated groups read from 24 sample titles; they account for 24 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.