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Involvement of p38 MAPK and MAPKAPK2 in promoting cell death and the inflammatory response to ischemic stress associated with necrotic glioblastoma

GSE281549 Homo sapiens (human) RNA-seq (gene expression) 16 samples Submitted 2025/01/22 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 16 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
GlioblastomaThis series is part of our curated briefing on it.
Samples
16 samples
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
Involvement of p38 MAPK and MAPKAPK2 in promoting cell death and the inflammatory response to ischemic stress associated with necrotic glioblastomaCell death & disease · 2025
Summary (written by the submitters)
The association of necrosis in tumors with poor prognosis implies a potential tumor-promoting role. However, the mechanisms underlying cell death in this context and how damaged tissue contributes to tumor progression remain unclear. Here, we identified p38 mitogen-activated protein kinases (p38) as a key player in promoting cell death and the inflammatory response to ischemic stress associated with necrotic tumors.
Read the full summary ↓
We found that glioblastoma (GBM) cells expressing patient-derived Kirsten rat sarcoma (KRAS) or phosphoinositide-3-kinase (PI3K) active mutants showed enhanced cell death under ischemia-mimetic conditions in vitro and were more likely to develop into necrotic tumors in vivo. Cell death in both settings depended on p38, which is also required for tumor progression driven by KRAS or PI3K. Under ischemia-mimetic conditions, GBM cells undergo reactive oxygen species (ROS)-dependent cell death. Gene expression in these cells recapitulated multiple features observed in peri-necrotic tumors from patient GBM. Further studies showed the involvement of a positive feedback loop between the p38-MAPK-activated protein kinase 2 (MK2) signaling axis and the unfolded protein response signaling components activating transcription factor 4 (ATF4) and inositol-requiring enzyme 1 (IRE1a) in driving ischemic tumor cell death. This signaling cascade was further potentiated by RAS or PI3K activation under ischemic conditions, contributing to the inflammatory gene expression response. Therefore, our study suggests that p38 could be targeted to relieve the inflammatory response in necrotic tumors and inhibit GBM progression.
Published in
Involvement of p38 MAPK and MAPKAPK2 in promoting cell death and the inflammatory response to ischemic stress associated with necrotic glioblastoma
Kim SY, Tang M, Chih SY et al. · Cell death & disease 2025 · PMID 39805854 · doi:10.1038/s41419-025-07335-3
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 GSE281549_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 PRJNA1184390 and SRA study SRP544377. Searching any of these in the dataset finder brings you back here.

Samples in this study

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