GEO series

ETC-501 is a Brain Penetrant MNK Kinase Inhibitor that Potentiates TMZ-Induced Senescence and Sensitizes Glioblastoma Cells to Senolytic Therapy

GSE280372 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/12/29 Platform GPL24676

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: GlioblastomaThis series is part of our curated briefing on it.
Samples: 12 samples: 3 × LN229 cells, DMSO, vs 3 × LN229 cells, ETC-501, vs 3 × T98G cells, DMSO, vs 3 × T98G cells, ETC-501,Groups 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)

Glioblastoma (GBM) is the deadliest primary brain tumor in adults, with a median survival of only 15 months and fewer than 10% of patients surviving beyond 5 years. Despite aggressive multimodal therapies, including surgical resection, radiation, and temozolomide (TMZ) chemotherapy, recurrence is almost inevitable. The MNK-eIF4E axis plays a significant role in cancer cell survival, and MNK1 and MNK2 are upregulated in gliomas.

Read the full summary ↓

In this study, we discovered that elevated MNK1/2 expression correlates with poor prognosis and aggressive GBM phenotypes. Development of ETC-501, a selective brain-penetrant MNK kinase inhibitor, enabled modulation of key oncogenic pathways, including MYC signaling, DNA replication, cell cycle regulation, and inflammation. ETC-501 effectively inhibited GBM proliferation, impaired DNA damage repair, delayed cell cycle progression, and suppressed ribosome biogenesis. Notably, in combination with TMZ, ETC-501 not only enhanced senescence but also attenuated the senescence-associated secretory phenotype in GBM cells. The augmented senescence increased the vulnerability of GBM cells to the senolytic agent navitoclax, facilitating targeted elimination of residual senescent cells. These findings underscore the therapeutic potential of MNK inhibition in GBM, offering a promising strategy to advance GBM treatment paradigms and improve patient outcomes.

This dataset

Open GSE280372 in finder → Find more human RNA-seq datasets → Glioblastoma 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 GSE280372_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 PRJNA1178117 and SRA study SRP540996. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

3 × LN229 cells, DMSO, vs 3 × LN229 cells, ETC-501, vs 3 × T98G cells, DMSO, vs 3 × T98G cells, ETC-501,

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

GSM8595745 LN229 cells, DMSO, rep1 LN229 cells, DMSO,
GSM8595746 LN229 cells, DMSO, rep2 LN229 cells, DMSO,
GSM8595747 LN229 cells, DMSO, rep3 LN229 cells, DMSO,
GSM8595748 LN229 cells, ETC-501, rep1 LN229 cells, ETC-501,
GSM8595749 LN229 cells, ETC-501, rep2 LN229 cells, ETC-501,
GSM8595750 LN229 cells, ETC-501, rep3 LN229 cells, ETC-501,
GSM8595751 T98G cells, DMSO, rep1 T98G cells, DMSO,
GSM8595752 T98G cells, DMSO, rep2 T98G cells, DMSO,
GSM8595753 T98G cells, DMSO, rep3 T98G cells, DMSO,
GSM8595754 T98G cells, ETC-501, rep1 T98G cells, ETC-501,
GSM8595755 T98G cells, ETC-501, rep2 T98G cells, ETC-501,
GSM8595756 T98G cells, ETC-501, rep3 T98G cells, ETC-501,

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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.