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Eliglustat-Induced Remodeling of Sulfo-Glycosphingolipid Metabolism and Gene Expression in hepatocellular carcinoma cells

GSE342040 Homo sapiens (human) RNA-seq (gene expression) 9 samples Submitted 2026/08/04 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 9 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
9 samples: 3 × HepG2, control, vs 3 × HepG2, Eliglustat20, vs 3 × HepG2, Eliglustat30,Groups 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)
Dysregulation of glycosphingolipid (GSL) metabolism contributes to cancer progression by altering membrane organization, signaling pathways, and cellular adaptation. Sulfated glycosphingolipids (Sulfo-GSLs), including sulfated lactosylceramide, are elevated in several malignancies and have been implicated in tumor cell adhesion and metastasis.
Read the full summary ↓
We previously identified elevated Sulfo-GSL levels in hepatocellular carcinoma (HCC) HepG2 cells, suggesting that targeting GSL biosynthesis may represent a potential therapeutic strategy. Here, we investigated the molecular consequences of UDP-glucose ceramide glucosyltransferase (UGCG) inhibition by eliglustat in HepG2 by integrating MALDI mass spectrometry-based lipid profiling with RNA sequencing. Eliglustat treatment induced dose-dependent remodeling of the cellular lipid profile, characterized by marked reduction of Sulfo-GSL species and a concomitant increase in selected phosphatidylinositol species. Lipidomic analysis revealed differential sensitivity of Sulfo-GSL molecular species, with preferential depletion of non-hydroxylated forms and relative preservation of hydroxylated species, indicating distinct metabolic responses within the same lipid class. Transcriptomic changes were limited at 20 µM eliglustat, whereas 30 µM induced extensive transcriptional reprogramming involving activation of immediate-early response genes, including EGR, FOS/JUN, and KLF family members, together with enrichment of inflammatory, stress-response, and senescence-associated pathways. Conversely, pathways related to cell-cycle progression, DNA replication, and chromatin organization were suppressed. Genes involved in GSL metabolism were also modulated, suggesting activation of compensatory mechanisms to restore lipid homeostasis. These findings demonstrate that UGCG inhibition induces coordinated lipidomic and transcriptional remodeling in HepG2, revealing both tumor-suppressive molecular features and adaptive responses to metabolic stress providing new insights into the cellular consequences of targeting GSL metabolism in HCC.
This dataset
Open GSE342040 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 GSE342040_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 PRJNA1505467 and SRA study SRP723129. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × HepG2, control, vs 3 × HepG2, Eliglustat20, vs 3 × HepG2, Eliglustat30,

Supports a between-group comparison across 9 samples.

How we read this: 3 replicated groups read from 9 sample titles; they account for 9 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

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