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.

Abstract

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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