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Next Generation Thiazolyl Ketone Inhibitors of Cytosolic Phospholipase A2 α: from Synthesis to Chemotherapeutic Mechanism of Action

GSE251999 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2024/11/19 Platform GPL30173
At a glance

RNA-seq (gene expression) · human · 24 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
24 samples: 24 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
Next generation thiazolyl ketone inhibitors of cytosolic phospholipase A(2) α for targeted cancer therapyNature communications · 2025
Summary (written by the submitters)
Eicosanoids participate in the pathologies of inflammation and carcinogenesis and limiting their production by inhibiting group IVA cytosolic phospholipase A2 (cPLA2α) is a potential approach to cancer treatment. Here we report the synthesis of a new generation of thiazolyl ketone inhibitors of cPLA2α starting from compound GK470 (AVX235), and the discovery of a more potent and selective lead, GK420 (AVX420), with significant chemotherapeutic properties.
Read the full summary ↓
A cancer cell line screen revealed the selective growth inhibitory effects of AVX420 in acute leukemias, uncovering a novel function of cPLA2α to promote cancer cell survival during oxidative stress by epigenetic control of tumour suppressor gene transcription. Moreover, we showed that in sensitive cells, AVX420 increased intracellular reactive oxygen species (ROS) and instigated a transcriptional response resulting in cell death. Our study suggests AVX420 has the potential to treat acute leukemias, and other cancers with specific adaptations to a high ROS burden.
Published in
Next generation thiazolyl ketone inhibitors of cytosolic phospholipase A(2) α for targeted cancer therapy
Ashcroft FJ, Bourboula A, Mahammad N et al. · Nature communications 2025 · PMID 39747052 · doi:10.1038/s41467-024-55536-9
This dataset
Open GSE251999 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 GSE251999_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 PRJNA1057046 and SRA study SRP480085. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39747052) ↗
Study design
24 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 24 sample titles: 24 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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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.