Evidence map›Paper›PMID 39362942›Full record

ArticleScientific reports2024

Whole-blood RNA biomarkers for predicting survival in non-human primates following thoracic radiation.

Molykutty J Aryankalayil, Haaris Patel, Jared M May, Uma Shankavaram, Michelle A Bylicky, Shannon Martello, Sunita Chopra, Jim Axtelle, Naresh Menon, C Norman Coleman

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Molykutty J AryankalayilRadiation Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA. aryankalayilm@mail.nih.gov.
Haaris PatelRadiation Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA.
Jared M MayRadiation Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA.
Uma ShankavaramRadiation Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA.
Michelle A BylickyRadiation Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA.
Shannon MartelloRadiation Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA.
Sunita ChopraRadiation Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA.
Jim AxtelleChromoLogic LLC, Monrovia, CA, USA.
Naresh MenonChromoLogic LLC, Monrovia, CA, USA.
C Norman ColemanRadiation Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA.

Funding

Radiation-induced molecular targetsZIABC010670 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI COLEMAN, NORMAN · 2009 to 2024
$17.3M
Intramural NIH HHS ZIA BC010670
6 · The paper itself

Abstract

Radiation injury, either from radiotherapy or a mass-casualty event requires a health care system that can efficiently allocate resources to patients. We conducted a comprehensive transcriptome analysis of whole blood from a nonhuman primate model that received upper thoracic radiation (9.8-10.7 Gy). Blood samples were collected at multiple time points, extending up to 270 days post-irradiation with a minimum n = 6 for initial time points (Day 3-Day 40) and a total number of n = 28 primates. No males receiving the higher dose survived to Day 270. Using the Elastic Net model in R we found that pooling biomarkers from Day 3-21 increased our accuracy in discerning survival time, pleural effusion or dose compared to using biomarkers specific to a single day. For survival data, in predicting short term (less than 90 day), medium term (Day 91-269) or long-term survival (Day 270), prediction accuracy using only Day 3 data was 0.14 (95% Confidence Interval (CI) 0.1, 0.19) while pooled data for Male and Female was 0.76 (CI 0.69, 0.82). When pooled data was divided by biological sex, accuracy was 0.7 (CI 0.58, 0.8) for pooled data from Males and 0.84 (CI 0.76, 0.91) for Females. The development of RNA biomarkers as a tool to aid in clinical decision-making could significantly improve patient care in cases of radiation injury, whether from radiotherapy or mass-casualty events. Further validation and clinical translation of these findings could lead to improved patient care and management strategies in cases of radiation exposure.

Indexed as

BiomarkersAnimalsFemaleGene Expression ProfilingMacaca mulattaMaleRNAThoraxTranscriptomeBiomarkersRNALung radiationNon-human primateRadiationRadiation bio-dosimetry

Identifiers

PMID39362942
PMCPMC11449919

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.