Telomere length dynamics and chromosomal instability for predicting individual radiosensitivity and risk via machine learning

Jared J. Luxton, Miles J. McKenna, Aidan M. Lewis, Lynn E. Taylor, Sameer G. Jhavar, Gregory P. Swanson, Susan M. Bailey

Research output: Contribution to journalArticlepeer-review

Abstract

The ability to predict a cancer patient’s response to radiotherapy and risk of developing adverse late health effects would greatly improve personalized treatment regimens and individual outcomes. Telomeres represent a compelling biomarker of individual radiosensitivity and risk, as exposure can result in dysfunctional telomere pathologies that coincidentally overlap with many radiation-induced late effects, ranging from degenerative conditions like fibrosis and cardiovascular disease to proliferative pathologies like cancer. Here, telomere length was longitudinally assessed in a cohort of fifteen prostate cancer patients undergoing Intensity Modulated Radiation Therapy (IMRT) utilizing Telomere Fluorescence in situ Hybridization (Telo-FISH). To evaluate genome instability and enhance predictions for individual patient risk of secondary malignancy, chromosome aberrations were assessed utilizing directional Genomic Hybridization (dGH) for high-resolution inversion detection. We present the first implementation of individual telomere length data in a machine learning model, XGBoost, trained on pre-radiotherapy (baseline) and in vitro exposed (4 Gy γ-rays) telomere length measurements, to predict post radiotherapy telomeric outcomes, which together with chromosomal instability provide insight into individual radiosensitivity and risk for radiation-induced late effects.

Original languageEnglish (US)
Article number188
JournalJournal of Personalized Medicine
Volume11
Issue number3
DOIs
StatePublished - Mar 2021

Keywords

  • Chromosomal instability
  • IMRT
  • Individual radiosensitivity
  • Inversions
  • Late effects
  • Machine learn-ing
  • Personalized medicine
  • Prostate cancer
  • Telomeres

ASJC Scopus subject areas

  • Medicine (miscellaneous)

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