GEO series

LIX1L aggravates NASH-HCC progression by reprogramming of hepatic Metabolism and microenvironment via CD36

GSE264479 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2024/04/25 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 12 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: Mus musculus (mouse)
Samples: 12 samples: 12 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)

Limb expression 1-like protein (LIX1L) plays important role in various liver disorders, but its role and underlying mechanism in nonalcoholic hepatitis (NASH) and HCC progression remains obscure. Here, we report that LIX1L functions as a key integrative regulator linking lipid metabolism and inflammation, adipose tissue dysfunction and hepatic microenvironment reprogramming which promotes NASH progression.

Read the full summary ↓

LIX1L significantly upregulated in NAFLD/NASH patients, mouse models and palmitic acid-stimulated hepatocytes. Lix1l deletion inhibits lipid deposition, inflammatory response and fibrosis in liver as well as adipocyte differentiation by downregulation of fatty acid translocase CD36 expression, alleviating NASH and associated HCC progression. In contrast, adeno-associated virus (AAV)-mediated LIX1L overexpression exacerbates NASH progression in mice. Mechanistically, metabolic stress promotes PARP1 mediated poly-ADP-ribosylation (PARylation) of LIX1L, subsequently increasing the stability and RNA binding ability of LIX1L protein. LIX1L binds to AU-rich element (ARE) in the 3’ untranslated region (UTR) of CD36 mRNA, thus attenuating CD36 mRNA decay. In NASH and associated HCC mouse models, LIX1L deficiency-mediated downregulation of CD36 suppresses adipogenesis, hepatic lipid uptake, and reprograms the tumor-prone liver microenvironment with increased cytotoxic T lymphocytes (CTLs), reduced immunosuppressive cell proportions. These data indicate a systematic function of LIX1L in the pathogenesis of NASH and underscore the PARP1/LIX1L/CD36 axis as a potential target for treatment of NASH and associated HCC.

This dataset

Open GSE264479 in finder → Find more mouse RNA-seq datasets →

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 GSE264479_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 PRJNA1102661 and SRA study SRP502988. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

12 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 12 sample titles: 12 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

GSM8218793 Liver, WT-4, LFD,12wks
GSM8218794 Liver, WT-7, LFD,12wks
GSM8218795 Liver, WT-8, LFD,12wks
GSM8218796 Liver, WT-1, HFD,12wks
GSM8218797 Liver, WT-2, HFD,12wks
GSM8218798 Liver, WT-6, HFD,12wks
GSM8218799 Liver, KO-2, LFD, 12wks
GSM8218800 Liver, KO-4, LFD, 12wks
GSM8218801 Liver, KO-5, LFD, 12wks
GSM8218802 Liver, KO-1, HFD, 12wks
GSM8218803 Liver, KO-5, HFD, 12wks
GSM8218804 Liver, KO-6, HFD, 12wks

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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.