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Protein Kinase R regulates pancreatic ductal adenocarcinoma progression by modulating the cell cycle via GADD45A

GSE285947 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2025/07/16 Platform GPL15520
At a glance

RNA-seq (gene expression) · human · 18 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
Pancreatic cancerThis series is part of our curated briefing on it.
Samples
18 samples: 18 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
Protein kinase R regulates pancreatic ductal adenocarcinoma progression by modulating the cell cycle via GADD45AScientific reports · 2025
Summary (written by the submitters)
Protein kinase R (PKR) functions both as a promoter and inhibitor in various cancers, yet its role in pancreatic ductal adenocarcinoma (PDAC) remains unclear. This study aimed to investigate the role of PKR in PDAC. PKR expression in PDAC cell lines was assessed using real-time reverse transcriptase polymerase chain reaction and western blot analysis.
Read the full summary ↓
The MTS assay was employed to evaluate the effect of PKR on cell proliferation. To elucidate the underlying mechanisms of PKR's action on PDAC, RNA-sequencing (RNA-seq) analysis was performed, and flow cytometry was used to examine the effects of PKR knockdown on cell cycle progression and apoptosis in PDAC cells. The results indicated that PDAC cell lines exhibited significantly reduced proliferation when transfected with PKR-targeting siRNAs or treated with PKR inhibitors. RNA-seq analysis revealed a substantial upregulation of GADD45A expression upon inhibition of PKR expression. Following PKR silencing, cell cycle analysis showed a marked accumulation of cells in the G1 phase, which is consistent with GADD45A's known role as a cell cycle regulator. Furthermore, the inhibition of proliferation caused by PKR knockdown was reversed by the downregulation of GADD45A, suggesting an interactive effect between PKR and GADD45A in regulating PDAC cell growth. In conclusion, PKR promotes PDAC cell proliferation by modulating the cell cycle through the regulation of GADD45A expression. These findings suggest that PKR may serve as a potential novel therapeutic target for PDAC.
Published in
Protein kinase R regulates pancreatic ductal adenocarcinoma progression by modulating the cell cycle via GADD45A
Numata Y, Koizumi M, Watanabe T et al. · Scientific reports 2025 · PMID 40640279 · doi:10.1038/s41598-025-06213-4
This dataset
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.

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 GSE285947_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1207023 and SRA study SRP555521. Searching any of these in the dataset finder brings you back here.

Study design
18 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 18 sample titles: 18 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
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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.