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Blockage of Ca2+-permeable AMPA receptors suppresses proliferation of schwannoma cells

GSE335945 Homo sapiens (human) RNA-seq (gene expression) 9 samples Submitted 2026/06/19 Platform GPL34284
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)
Samples
9 samples: 9 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)
Schwannomas are common benign tumors, but management of large or multiple tumors, such as those in NF2-related schwannomatosis, remains challenging due to the risks associated with surgery and radiotherapy. Drug repositioning offers a promising strategy for these slow-growing tumors. While the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor is a known therapeutic target in glioma to prevent seizure and growth, its expression and role in schwannoma have not been fully elucidated.
Read the full summary ↓
We analyzed the intracellular genetic changes induced by PER treatment using RNA-seq. We treated human fibroblast cell lines (TIG-1) and human schwannoma cell lines (YST-1, HS-PSS) with PER at concentrations of 0 μM (control group), 10 μM, and 30 μM, respectively, and performed RNA-seq after culturing the cells for 7 days.
This dataset
Open GSE335945 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 GSE335945_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 PRJNA1479987 and SRA study SRP710908. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
9 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 9 sample titles: 9 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
Datasets on a similar topic

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