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BRD9 inhibition as potential treatment option for testicular germ cell tumors

GSE282367 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/11/19 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 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
Homo sapiens (human)
Topic
Testicular cancerThis series is part of our curated briefing on it.
Samples
12 samples: 3 × 2102 EP, I-BRD9, biol vs 3 × 2102 EP, DMSO, biol vs 3 × TCam-2, I-BRD9, biol vs 3 × TCam-2, DMSO, biolGroups 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)
Testicular germ cell tumors (TGCT) are the predominant tumor in younger males. Usually, curation rates are quite high, but 15-20 % of patients with metastatic non-seminomas are resistant to standard cisplatin-based therapy. Interfering with the epigenetic landscape has already been shown to be effective in prostate cancer. BRD9 is an epigenetic reader which is part of the SWI-SNF chromatin-remodeling complex involved in regulation of gene expression.
Read the full summary ↓
Alternative treatment options for therapy-resistant TGCT patients need to be investigated. BRD9 seems to be a promising target for analyzing the effect of BRD9 inhibition in TGCT cell lines. BRD9 expression was analyzed by meta-analysis of microarray data as well as by Western Blot and immunohistochemistry of tissue microarrays in TGCT cell lines and TGCT tissues. Viability was assessed by performing XTT-assay to determine the effect of BRD9 inhibition in TGCT cell lines. FACS analysis was used to display changes in cell cycle distribution as well as apoptosis. The impact on transcriptome level of BRD9 inhibition was analyzed by 3’mRNA-sequencing. BRD9 was heterogeneously expressed in TGCT cell lines and tissues. Nevertheless, inhibition of BRD9 led to strong decrease in viability. I-BRD9 induced apoptosis as well as cell cycle arrest in G1-phase. On transcriptome level, prominent downregulation of pluripotency markers (NANOG, PRMD14 and KLF4) and upregulation of genes involved in epithelium development were detected. I-BRD9 treatment of GCT cell lines reduced viability, induced apoptosis and cell cycle arrest while control cells remain mainly unaffected. Transcriptomic data indicate exit of pluripotency and differentiation towards the epithelial fate. In fact, loss of pluripotency and differentiation seems to be a common aspect of GCT reacting to drug application. The data implicate I-BRD9 as a possible treatment alternative for TGCTs.
This dataset
Open GSE282367 in finder → Find more human RNA-seq datasets → Testicular 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 GSE282367_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 PRJNA1188376 and SRA study SRP546352. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × 2102 EP, I-BRD9, biol vs 3 × 2102 EP, DMSO, biol vs 3 × TCam-2, I-BRD9, biol vs 3 × TCam-2, DMSO, biol

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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 Testicular cancer datasets

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