GEO series

KPNA3 drives temozolomide resistance in glioblastoma by upregulating MGMT and activating STAT3 to sustain glioma stem cells

GSE327029 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/07/17 Platform GPL29480

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: 6 × SF126 vs 6 × U118MGGroups 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: Karyopherin Subunit Alpha 3 Drives Temozolomide Resistance in Glioblastoma by Upregulating MGMT and Activating STAT3 to Sustain Glioma Stem CellsCell biology international · 2026

Summary (written by the submitters)

Glioblastoma (GBM) invariably develops resistance to temozolomide (TMZ), the frontline chemotherapeutic agent, leading to treatment failure. The molecular mechanisms underlying this resistance remain incompletely understood. Here, we identify karyopherin subunit alpha 3 (KPNA3) as a novel and critical driver of TMZ resistance. Through integrated bioinformatics analysis of temozolomide-resistant glioma cells (SF126R) and patient databases, we found KPNA3 expression is elevated in TMZ-resistant contexts and correlates with poor prognosis in TMZ-treated patients.

Read the full summary ↓

Functional studies demonstrated that KPNA3 knockdown in resistant cells impaired malignant behaviors, re-sensitized cells to TMZ-induced apoptosis, and suppressed glioma stem cell (GSC) properties, including sphere formation and expression of stemness factors (OCT4, ALDH1A1). Mechanistically, KPNA3 promotes resistance via a dual pathway: it upregulates the expression of the DNA repair enzyme MGMT and activates the STAT3 signaling pathway. KPNA3 knockdown reduced both MGMT levels and STAT3 phosphorylation (Tyr705). Furthermore, pharmacological inhibition of STAT3 mirrored the effect of KPNA3 knockdown by potently inhibiting GSC generation. Clinically, KPNA3 and p-STAT3 protein levels were positively correlated in high-grade glioma tissues. Collectively, our findings unveil KPNA3 as a central regulator that concurrently enhances DNA repair and sustains the GSC population to foster TMZ resistance, nominating it as a promising therapeutic target for overcoming chemoresistance in GBM.

Published in

Karyopherin Subunit Alpha 3 Drives Temozolomide Resistance in Glioblastoma by Upregulating MGMT and Activating STAT3 to Sustain Glioma Stem Cells

Gao Y, Yuan H, Zhou H et al. · Cell biology international 2026 · PMID 42295990 · doi:10.1002/cbin.70175

This dataset

Open GSE327029 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 GSE327029_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 PRJNA1449345 and SRA study SRP689467. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42295990) ↗

Study design

6 × SF126 vs 6 × U118MG

Supports a between-group comparison across 12 samples.

How we read this: 2 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

GSM9646863 SF126-1 SF126
GSM9646864 SF126-2 SF126
GSM9646865 SF126-3 SF126
GSM9646866 SF126R-1 SF126
GSM9646867 SF126R-2 SF126
GSM9646868 SF126R-3 SF126
GSM9646869 U118MG-1 U118MG
GSM9646870 U118MG-2 U118MG
GSM9646871 U118MG-3 U118MG
GSM9646872 U118MGR-1 U118MG
GSM9646873 U118MGR-2 U118MG
GSM9646874 U118MGR-3 U118MG

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