Evidence map›Paper›PMID 27345199›Full record

ReviewLife sciences in space research2016

Evaluating biomarkers to model cancer risk post cosmic ray exposure.

Deepa M Sridharan, Aroumougame Asaithamby, Steve R Blattnig, Sylvain V Costes, Paul W Doetsch, William S Dynan, Philip Hahnfeldt, Lynn Hlatky, Yared Kidane, Amy Kronenberg and 10 more

Open access · hybridAbstract readReview
In one paragraph

Review in Life sciences in space research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
3.1field-weighted citation impact, top 9% of its field
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

21 citing papers in PubMed, 47 citations in OpenAlex.

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  19. Longitudinal metabolic alterations in plasma of rats exposed to low doses of high linear energy transfer radiation.Journal of environmental science and health. Part C, Toxicology and carcinogenesis · 2021
    Article
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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

20 authors at 8 institutions in 1 country.

Deepa M SridharanLawrence Berkeley National Laboratory, Berkeley, CA, United States.
Aroumougame AsaithambyUT Southwestern Medical Center, Dallas, TX, United States.
Steve R BlattnigLangley Research Center, Langley Research Center (LaRC), VA, United States.
Sylvain V CostesLawrence Berkeley National Laboratory, Berkeley, CA, United States.
Paul W DoetschEmory University, Atlanta, GA, United States.
William S DynanEmory University, Atlanta, GA, United States.
Philip HahnfeldtCCSB-Tufts School of Medicine, Boston, MA, United States.
Lynn HlatkyCCSB-Tufts School of Medicine, Boston, MA, United States.
Yared KidaneWyle Science, Technology & Engineering Group, Houston, TX, United States.
Amy KronenbergLawrence Berkeley National Laboratory, Berkeley, CA, United States.
Mamta D NaiduCCSB-Tufts School of Medicine, Boston, MA, United States.
Leif E PetersonHouston Methodist Research Institute, Houston, TX, United States.
Ianik PlanteWyle Science, Technology & Engineering Group, Houston, TX, United States.
Artem L PonomarevWyle Science, Technology & Engineering Group, Houston, TX, United States.
Janapriya SahaUT Southwestern Medical Center, Dallas, TX, United States.
Antoine M SnijdersLawrence Berkeley National Laboratory, Berkeley, CA, United States.
Kalayarasan SrinivasanUT Southwestern Medical Center, Dallas, TX, United States.
Jonathan TangExogen Biotechnology, Inc., Berkeley, CA, United States.
Erica WernerEmory University, Atlanta, GA, United States.
Janice M PluthLawrence Berkeley National Laboratory, Berkeley, CA, United States. Electronic address: jmpluth@lbl.gov.
Lawrence Berkeley National Laboratory · USEmory University · USTufts University · USWyle (United States) · USSouthwestern Medical CenterHouston Methodist · USLangley Research Center · USThe University of Texas Southwestern Medical Center · US

Funding

Laser Capture Microscopy and 2D-DIGE: Cancer ProteomicsR33CA095941 · NCI · MEDICAL COLLEGE OF GEORGIA (MCG) · PI DYNAN, WILLIAM S · 2005 to 2007
$1.0M
NASA NNX15AD63GNCI NIH HHS R33 CA095941
6 · The paper itself

Abstract

Robust predictive models are essential to manage the risk of radiation-induced carcinogenesis. Chronic exposure to cosmic rays in the context of the complex deep space environment may place astronauts at high cancer risk. To estimate this risk, it is critical to understand how radiation-induced cellular stress impacts cell fate decisions and how this in turn alters the risk of carcinogenesis. Exposure to the heavy ion component of cosmic rays triggers a multitude of cellular changes, depending on the rate of exposure, the type of damage incurred and individual susceptibility. Heterogeneity in dose, dose rate, radiation quality, energy and particle flux contribute to the complexity of risk assessment. To unravel the impact of each of these factors, it is critical to identify sensitive biomarkers that can serve as inputs for robust modeling of individual risk of cancer or other long-term health consequences of exposure. Limitations in sensitivity of biomarkers to dose and dose rate, and the complexity of longitudinal monitoring, are some of the factors that increase uncertainties in the output from risk prediction models. Here, we critically evaluate candidate early and late biomarkers of radiation exposure and discuss their usefulness in predicting cell fate decisions. Some of the biomarkers we have reviewed include complex clustered DNA damage, persistent DNA repair foci, reactive oxygen species, chromosome aberrations and inflammation. Other biomarkers discussed, often assayed for at longer points post exposure, include mutations, chromosome aberrations, reactive oxygen species and telomere length changes. We discuss the relationship of biomarkers to different potential cell fates, including proliferation, apoptosis, senescence, and loss of stemness, which can propagate genomic instability and alter tissue composition and the underlying mRNA signatures that contribute to cell fate decisions. Our goal is to highlight factors that are important in choosing biomarkers and to evaluate the potential for biomarkers to inform models of post exposure cancer risk. Because cellular stress response pathways to space radiation and environmental carcinogens share common nodes, biomarker-driven risk models may be broadly applicable for estimating risks for other carcinogens.

Indexed as

BiomarkersCosmic RadiationDose-Response Relationship, RadiationEvaluation Studies as TopicHumansNeoplasms, Radiation-InducedRisk AssessmentBiomarkersBiomarkersCancer riskHZEModelingSpace radiation

Identifiers

PMID27345199
PMCPMC5613937
OpenAlexW2396533964

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.