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IQGAP3 bridges matrix stiffness with cancer stem cell maintenance and radioresistance by stabilizing SOX2 II

GSE291583 Homo sapiens (human) RNA-seq (gene expression) 16 samples Submitted 2025/03/14 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: 6 conditions, mostly in triplicateGroups 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)
Drivers of therapeutic resistance in cancer include evolution of tumor cell heterogeneity and the tumor microenvironment (TME). Here, we found that increased matrix stiffness promotes radioresistance in glioblastoma (GBM) and maintains the tumor cell hierarchy. Differential gene expression revealed that stiff matrices induced expression of IQGAP3 (IQ Motif Containing GTPase Activating Protein 3) specifically in GBM stem cells (GSCs).
Read the full summary ↓
IQGAP3 promoted GSC self-renewal and survival upon radiation treatment through binding and stabilization of the core stem cell transcription factor, SOX2. Targeting IQGAP3 reduced SOX2 protein levels in vitro and in vivo, increasing GSC radiosensitivity and inhibiting tumor growth. Structure-function drug screening of FDA-approved agents blocking IQGAP3 binding to SOX2 identified Trimetrexate as a brain penetrant pharmacologic disruptor of IQGAP3 function in radioresistance, sensitizing GSCs to radiotherapy. Our results identify molecular underpinnings for biomechanical promotion of cancer stem cell maintenance and therapeutic resistance, informing a therapeutic strategy to augment efficacy of radiotherapy.
This dataset
Open GSE291583 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 GSE291583_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 PRJNA1234192 and SRA study SRP569315. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly in triplicate
GSC MES20, soft ×3 GSC MES20, stiff ×3 GSC MES20, soft, radiation ×3 GSC MES20, stiff, radiation ×3 GSC MES20, shIQGAP3 ×2 GSC MES20, shCONT ×2

Supports a between-group comparison across 16 samples.

How we read this: 6 replicated groups read from 16 sample titles; they account for 16 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
More Glioblastoma datasets

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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.