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Transcriptomic analysis of human gastric cancer cell lines following T-DXd treatment

GSE245851 Homo sapiens (human) RNA-seq (gene expression) 15 samples Submitted 2024/10/20 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 15 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
Gastric cancerThis series is part of our curated briefing on it.
Samples
15 samples: 5 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
Immunomodulatory effects of trastuzumab deruxtecan through the cGAS-STING pathway in gastric cancer cellsCell communication and signaling : CCS · 2024
Summary (written by the submitters)
Despite the clinical success of trastuzumab deruxtecan (T-DXd) in treating HER2-positive gastric cancers (GCs), its precise immunomodulatory mechanisms remain elusive. This study investigates T-DXd's immune-related actions in GC cells through RNA sequencing.
Published in
Immunomodulatory effects of trastuzumab deruxtecan through the cGAS-STING pathway in gastric cancer cells
Oh KS, Nam AR, Bang JH et al. · Cell communication and signaling : CCS 2024 · PMID 39449023 · doi:10.1186/s12964-024-01893-3
This dataset
Open GSE245851 in finder → Find more human RNA-seq datasets → Gastric cancer 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 GSE245851_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 PRJNA1028336 and SRA study SRP466477. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39449023) ↗
Study design
5 conditions, mostly in triplicate
NCI-N87 cells, vehicle control / biol ×3 NCI-N87 cells, trastuzumab / biol ×3 NCI-N87 cells, T-DXd / biol ×3 SNU-484 cells, vehicle control / biol ×3 SNU-484 cells, T-DXd / biol ×3

Supports a between-group comparison across 15 samples.

How we read this: 5 replicated groups read from 15 sample titles; they account for 15 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 Gastric cancer datasets

Search all human RNA-seq datasets in GEO →

Share this dataset

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.