Back

Targeting Radiation-Induced Glioma-Initiating Cells in Patient-Derived Glioblastoma

Cardenas, A.; Sutlief, S.; Pajonk, F.

2025-10-09 cancer biology
10.1101/2025.10.08.681196 bioRxiv
Show abstract

BackgroundGlioblastoma (GB) is a highly aggressive and treatment-resistant brain cancer with poor prognosis. Surgical resection followed by radiotherapy (RT) with the chemotherapeutic, temozolomide (TMZ), is the standard GB treatment; yet recurrence often occurs. GB is organized hierarchically with a small population of radiation-resistant glioma-initiating cells (GICs) that self-renew and drive tumor growth. Importantly, RT can induce a subset of cells from non-tumor-initiating into glioma-initiating cells (iGICs). Both GICs and iGICs contribute to tumor recurrence and therapy resistance. Thus, without effective elimination of non-tumorigenic GB and prevention or targeting of GICs, a cure is unlikely. The objective of this study is to identify small molecules that block RT-induced phenotypic conversion to occur. MethodWe conducted a high-throughput screen of NCIs Cancer Therapy Evaluation Program (CTEP) compounds with evidence for crossing the blood-brain-barrier. To identify "stemness" or reprogramming of cells, we transduced GB cell lines representing each TCGA subtype to express a fluorescent reporter for proteasomal activity that distinguishes non-tumor-initiating cells from GICs. We tested CTEP agents at 10 different concentrations in combination with radiation. ResultsOur results identified selumetinib as a candidate compound that effectively prevents radiation-induced phenotype conversion. Furthermore, in combination with radiation, selumetinib decreased stem cell maintenance in GICs with differential effects on viability in non-tumorigenic cells. ConclusionTaken together, these findings suggest that repurposing FDA-approved compounds alongside current therapies may effectively target the cellular and molecular heterogeneity of GB--and because these agents are already clinically approved, this approach can be rapidly implemented in the clinic.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

1
Neuro-Oncology
36 papers in training set
Top 0.1%
49.5%
2
Molecular Cancer Therapeutics
40 papers in training set
Top 0.2%
4.7%
50% of probability mass above
3
Scientific Reports
3612 papers in training set
Top 28%
3.9%
4
International Journal of Radiation Oncology*Biology*Physics
25 papers in training set
Top 0.2%
3.1%
5
Clinical Cancer Research
64 papers in training set
Top 0.9%
2.4%
6
Nature Communications
5641 papers in training set
Top 41%
2.3%
7
Cancer Research Communications
51 papers in training set
Top 0.6%
2.3%
8
Neuro-Oncology Advances
25 papers in training set
Top 0.2%
2.1%
9
Cell Reports Medicine
153 papers in training set
Top 2%
1.9%
10
Cancers
213 papers in training set
Top 3%
1.9%
11
Radiotherapy and Oncology
19 papers in training set
Top 0.2%
1.7%
12
Communications Biology
993 papers in training set
Top 15%
1.7%
13
npj Precision Oncology
53 papers in training set
Top 0.9%
1.6%
14
Frontiers in Oncology
103 papers in training set
Top 2%
1.6%
15
Cancer Research
130 papers in training set
Top 3%
1.1%
16
Oncotarget
18 papers in training set
Top 0.3%
1.1%
17
International Journal of Cancer
49 papers in training set
Top 1.0%
1.1%
18
iScience
1154 papers in training set
Top 30%
1.0%
19
PLOS ONE
5266 papers in training set
Top 58%
1.0%
20
Proceedings of the National Academy of Sciences
2444 papers in training set
Top 39%
1.0%
21
Neoplasia
23 papers in training set
Top 0.9%
0.8%
22
JCI Insight
277 papers in training set
Top 8%
0.8%
23
eLife
5828 papers in training set
Top 66%
0.8%
24
Theranostics
37 papers in training set
Top 1%
0.8%
25
Journal of Clinical Investigation
179 papers in training set
Top 7%
0.6%
26
JNCI: Journal of the National Cancer Institute
19 papers in training set
Top 0.4%
0.6%
27
Molecular Oncology
55 papers in training set
Top 2%
0.6%