Whole blood gene expression within days after total-body irradiation predicts long term survival in Gottingen minipigs
© 2021. The Author(s)..
Gottingen 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.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:11 |
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| Enthalten in: |
Scientific reports - 11(2021), 1 vom: 05. Aug., Seite 15873 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Chopra, Sunita [VerfasserIn] |
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| Links: |
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| Themen: |
Biomarkers |
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| Anmerkungen: |
Date Completed 08.11.2021 Date Revised 27.02.2024 published: Electronic Citation Status MEDLINE |
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| doi: |
10.1038/s41598-021-95120-5 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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NLM328984213 |
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| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © 2021. The Author(s). | ||
| 520 | |a Gottingen 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 | ||
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| 700 | 1 | |a Moroni, Maria |e verfasserin |4 aut | |
| 700 | 1 | |a Sanjak, Jaleal |e verfasserin |4 aut | |
| 700 | 1 | |a MacMillan, Laurel |e verfasserin |4 aut | |
| 700 | 1 | |a Hritzo, Bernadette |e verfasserin |4 aut | |
| 700 | 1 | |a Martello, Shannon |e verfasserin |4 aut | |
| 700 | 1 | |a Bylicky, Michelle |e verfasserin |4 aut | |
| 700 | 1 | |a May, Jared |e verfasserin |4 aut | |
| 700 | 1 | |a Coleman, C Norman |e verfasserin |4 aut | |
| 700 | 1 | |a Aryankalayil, Molykutty J |e verfasserin |4 aut | |
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