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Updated: Dec 29, 2025

Author Spotlight: Radiotherapy and Clonogenic Assays for Advancing Cancer Research and Personalized Medicine
Published on: April 5, 2024
Impact of accumulated alterations in driver and passenger genes on response to radiation therapy
Yuji Seo1, Keisuke Tamari1, Yutaka Takahashi1
1Department of Radiation Oncology, Osaka University Graduate School of Medicine 2-2 Yamadaoka, Suita, Osaka, Japan.
Objective:
Although various single genetic factors have been shown to affect radiosensitivity, high-throughput DNA sequencing analyses have revealed complex genomic landscapes in many cancer types. The aim of this study is to elucidate the association between accumulated alterations in driver and passenger genes and radiation therapy response.
Methods:
We used 59 human solid cancer cell lines derived from 11 organ sites. Radiation-induced cell death was measured using a standard colony-forming assay delivered as a single dose ranging from 0 to 12 Gy. Comprehensive genomic data for the cell lines were acquired from the Catalogue Of Somatic Mutations In Cancer v. 80. Random forest classifiers were constructed to predict radioresistant phenotypes using genomic features. The Cancer Genome Atlas data sets were used to evaluate the clinical impact of the genomic feature following radiotherapy.
Results:
The 59 cancer cell lines harbored either nucleotide variations or copy number variations in a median of 157 genes per cell. Radiosensitivity of the cancer cells was correlated with neither the number of driver gene mutations nor the number of passenger gene mutations. However, the proportion of driver gene alterations to total gene alterations in gene sets selected from the Kyoto Encyclopedia Genes and Genomes predicted radioresistant cells with sensitivity of 85% and specificity of 73%. High probability of radioresistance predicted by the model was associated with worse overall survival following definitive radiotherapy in patients of The Cancer Genome Atlas data sets.
Conclusion:
Cellular radiosensitivity was associated with the proportion of driver to total gene alterations in the selected oncogenic pathways, which may be a biomarker candidate for response to radiation therapy.
Advances In Knowledge:
These findings suggest that accumulated alterations in not only driver genes but also passenger genes affect radiosensitivity.
Insights
The proportion of driver gene alterations to total gene alterations in oncogenic pathways predicts cancer cell radiosensitivity. This genomic feature may serve as a biomarker for radiation therapy response and patient survival outcomes.
Area of Science:
- Genomics
- Cancer Biology
- Radiation Oncology
Background:
- Single genetic factors influencing radiosensitivity are known, but complex genomic landscapes in cancer are increasingly recognized.
- High-throughput sequencing reveals numerous alterations in both driver and passenger genes across cancer types.
Purpose of the Study:
- To investigate the association between accumulated alterations in driver and passenger genes and response to radiation therapy.
- To identify potential genomic biomarkers for predicting radiosensitivity and patient outcomes.
Main Methods:
- Utilized 59 human solid cancer cell lines from 11 organ sites.
- Assessed radiation-induced cell death via colony-forming assays (0-12 Gy).
- Employed random forest classifiers on comprehensive genomic data (Catalogue Of Somatic Mutations In Cancer) to predict radioresistant phenotypes.
- Validated findings using The Cancer Genome Atlas (TCGA) datasets for clinical impact evaluation.
Main Results:
- Cancer cell lines exhibited a median of 157 gene alterations (nucleotide variations or copy number variations).
- Radiosensitivity did not correlate with the absolute number of driver or passenger gene mutations.
- The proportion of driver gene alterations within specific gene sets predicted radioresistant cells with 85% sensitivity and 73% specificity.
- A high predicted probability of radioresistance correlated with worse overall survival in TCGA patients receiving definitive radiotherapy.
Conclusions:
- Cellular radiosensitivity is linked to the proportion of driver to total gene alterations in selected oncogenic pathways.
- This genomic feature shows potential as a biomarker for predicting radiation therapy response.
- Accumulated alterations in both driver and passenger genes collectively influence radiosensitivity.
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