Author:
Chopra Sunita,Moroni Maria,Sanjak Jaleal,MacMillan Laurel,Hritzo Bernadette,Martello Shannon,Bylicky Michelle,May Jared,Coleman C. Norman,Aryankalayil Molykutty J.
Abstract
AbstractGottingen minipigs mirror the physiological radiation response observed in humans and hence make an ideal candidate model for studying radiation biodosimetry for both limited-sized and mass casualty incidents. We examined the whole blood gene expression profiles starting one day after total-body irradiation with increasing doses of gamma-rays. The minipigs were monitored for up to 45 days or time to euthanasia necessitated by radiation effects. We successfully identified dose- and time-agnostic (over a 1–7 day period after radiation), survival-predictive gene expression signatures derived using machine-learning algorithms with high sensitivity and specificity. These survival-predictive signatures fare better than an optimally performing dose-differentiating signature or blood cellular profiles. These findings suggest that prediction of survival is a much more useful parameter for making triage, resource-utilization and treatment decisions in a resource-constrained environment compared to predictions of total dose received. It should hopefully be possible to build such classifiers for humans in the future.
Funder
Biomedical Advanced Research and Development Authority
National Cancer Institute
Publisher
Springer Science and Business Media LLC
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