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Comparative analysis of the transcriptomic response to cisplatin in drug-sensitive and drug-resistant testicular germ cell tumors.

GSE317098 Homo sapiens (human) RNA-seq (gene expression) 30 samples Submitted 2026/02/10 Platform GPL20301
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
Testicular cancerThis series is part of our curated briefing on it.
Samples
30 samples: 30 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.
Paper
Comparative Analysis of the Transcriptomic Response to Cisplatin in Drug-Sensitive and Drug-Resistant Testicular Germ Cell TumorsCancers · 2026
Summary (written by the submitters)
Testicular germ cell tumors (TGCTs) are uniquely curable with cisplatin-based therapies even when widely metastatic, however cisplatin resistance does occur resulting in very poor prognosis. The mechanisms to explain TGCT hypersensitivity to cisplatin and mechanisms of resistance are not well understood. The global transcriptional response to acute cisplatin treatment (24 hours after a 6-hour pulse of cisplatin) was assessed in three parental embryonal carcinoma TGCT cells lines compared to multiple isogenic, stable, cisplatin-resistant clonal lines from these pa-rental cells.
Read the full summary ↓
Cisplatin treatment of parental cells consistently showed a more robust overall transcriptional response to cisplatin compared to their cisplatin-resistant cellular counterparts for a common set of genes and pathways including the upregulation of genes associated with histone modifications and p53, EMT, and KRAS signaling and the downregulation of genes normally upregulated by MYC. Focusing on genes exclusively altered in parental cells revealed upregulated genes known to be induced by p53 and downregulated by MYC and the transferrin receptor, TFRC1. Several of these p53/MYC/TFRC1 targets were associated with a higher instance of disease free survival in a cohort of TGCT patients. Cisplatin resistance in TGCT cells is associated with a diminished alteration of cisplatin responsive genes especially genes known the be regulated by p53, MYC and TFRC1 that may be linked to cisplatin hypersensitivity and survival in TGCTs.
Published in
Comparative Analysis of the Transcriptomic Response to Cisplatin in Drug-Sensitive and Drug-Resistant Testicular Germ Cell Tumors
Khan MW, Shokry D, Boyd RI et al. · Cancers 2026 · PMID 41749828 · doi:10.3390/cancers18040575
This dataset
Open GSE317098 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 GSE317098_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 PRJNA1405775 and SRA study SRP664973. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41749828) ↗
Study design
30 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 30 sample titles: 30 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
More Testicular cancer datasets

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