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Lenvatinib enhances the response of biliary tract cancer to anti-HER2 therapy

GSE315906 Homo sapiens (human) RNA-seq (gene expression) 30 samples Submitted 2026/06/01 Platform GPL34284
At a glance

RNA-seq (gene expression) · human · 30 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
CholangiocarcinomaThis series is part of our curated briefing on it.
Samples
30 samples: 10 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.
Paper
Lenvatinib enhances the response of biliary tract cancer to anti-HER2 therapySignal transduction and targeted therapy · 2026
Summary (written by the submitters)
HER2 is a frequently overexpressed gene in biliary tract cancer (BTC). Although several targeted agents, including trastuzumab, have been approved for the treatment of BTC, their clinical efficacy remains limited. To explore this issue, we treated two BTC cell lines—SNU1196 and GBC-SD—with different anti-HER2 agents. We then performed gene expression profiling analysis using data from RNA-seq of 2 different cells treated with different drugs.
Published in
Lenvatinib enhances the response of biliary tract cancer to anti-HER2 therapy
Sun H, Li S, Zhu Z et al. · Signal transduction and targeted therapy 2026 · PMID 42502083 · doi:10.1038/s41392-026-02775-5
This dataset
Open GSE315906 in finder → Find more human RNA-seq datasets → Cholangiocarcinoma 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 GSE315906_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 PRJNA1399903 and SRA study SRP660628. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42502083) ↗
Study design
10 conditions, mostly in triplicate
SNU1196 cells, vehicle ×3 SNU1196 cells, pyrotinib ×3 SNU1196 cells, afatinib ×3 SNU1196 cells, CP724714 ×3 SNU1196 cells, trastuzumab ×3 GBC-SD cells, vehicle ×3 GBC-SD cells, pyrotinib ×3 GBC-SD cells, afatinib ×3 +2 more

Supports a between-group comparison across 30 samples.

How we read this: 10 replicated groups read from 30 sample titles; they account for 30 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 Cholangiocarcinoma 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.