GEO series

Effect of depletion of TSPAN6 on Biliary Epithelial Cells with and without LPS stimulation mirroring liver disease.

GSE317449 Homo sapiens (human) RNA-seq (gene expression) 20 samples Submitted 2026/01/31 Platform GPL34284

At a glance

RNA-seq (gene expression) · human · 20 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)
Samples: 20 samples: 5 × BEC TSPAN6 KD UT N= vs 5 × BEC TSPAN6 KD LPS N= vs 5 × BEC Control UT N= vs 5 × BEC Control LPS N=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)

A unique pathological hallmark of chronic liver disease (CLD) is the ductular reaction, characterised by the proliferation of reactive bile ducts associated with an inflammatory infiltrate. In this study we identify the Tetraspanin family member, TSPAN6, as a novel regulator of biliary-immune cell cross talk. We initially demonstrate that TSPAN6 is expressed by biliary ductules within the ductular reaction from samples of cirrhotic human liver tissue across multiple aetiologies and significantly elevated in cholestatic liver diseases.

Read the full summary ↓

We also confirm that it is upregulated in in vivo models of ductular reaction. Additionally, TSPAN6 protein expression demonstrated a positive correlation with the presence of infiltrating (MAC387+) macrophages. Using a human in vitro model of primary biliary epithelial cell (BEC)-monocyte cross talk, we demonstrate that TSPAN6 regulates BEC-driven monocyte activation and chemokine production. Specifically, LPS stimulation of BEC led to downstream inflammatory activation of human monocytes, with upregulation of pro-inflammatory chemokines. TSPAN6 knockdown in BEC partially reversed this in monocyte activation, with specific reduction in the chemokines CXCL1,2 and 5. Transcriptomic profiling, following TSPAN6 depletion, confirmed its involvement in membrane-associated trafficking and lipid modification pathways in biliary epithelial cells. We propose TSPAN6 as a potential organiser of epithelial signalling platforms, contributing to inflammation and regeneration, during liver injury and could therefore be a novel therapeutic target in CLD.

This dataset

Open GSE317449 in finder → Find more human 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 GSE317449_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 PRJNA1412982 and SRA study SRP665913. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

5 × BEC TSPAN6 KD UT N= vs 5 × BEC TSPAN6 KD LPS N= vs 5 × BEC Control UT N= vs 5 × BEC Control LPS N=

Supports a between-group comparison across 20 samples.

How we read this: 4 replicated groups read from 20 sample titles; they account for 20 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

GSM9472429 BEC TSPAN6 KD UT N=1 BEC TSPAN6 KD UT N=
GSM9472430 BEC TSPAN6 KD LPS N=1 BEC TSPAN6 KD LPS N=
GSM9472431 BEC Control UT N=1 BEC Control UT N=
GSM9472432 BEC Control LPS N=1 BEC Control LPS N=
GSM9472433 BEC TSPAN6 KD UT N=2 BEC TSPAN6 KD UT N=
GSM9472434 BEC TSPAN6 KD LPS N=2 BEC TSPAN6 KD LPS N=
GSM9472435 BEC Control UT N=2 BEC Control UT N=
GSM9472436 BEC Control LPS N=2 BEC Control LPS N=
GSM9472437 BEC TSPAN6 KD UT N=3 BEC TSPAN6 KD UT N=
GSM9472438 BEC TSPAN6 KD LPS N=3 BEC TSPAN6 KD LPS N=
GSM9472439 BEC Control UT N=3 BEC Control UT N=
GSM9472440 BEC Control LPS N=3 BEC Control LPS N=
GSM9472441 BEC TSPAN6 KD UT N=4 BEC TSPAN6 KD UT N=
GSM9472442 BEC Control UT N=4 BEC Control UT N=
GSM9472443 BEC TSPAN6 KD LPS N=4 BEC TSPAN6 KD LPS N=
GSM9472444 BEC Control LPS N=4 BEC Control LPS N=
GSM9472445 BEC TSPAN6 KD UT N=5 BEC TSPAN6 KD UT N=
GSM9472446 BEC Control UT N=5 BEC Control UT N=
GSM9472447 BEC TSPAN6 KD LPS N=5 BEC TSPAN6 KD LPS N=
GSM9472448 BEC Control LPS N=5 BEC Control LPS N=

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