Evidence map›Paper›PMID 27485285›Full record

ArticleInternational journal of radiation oncology, biology, physics2016

Identifying Urinary and Serum Exosome Biomarkers for Radiation Exposure Using a Data Dependent Acquisition and SWATH-MS Combined Workflow.

Shilpa Kulkarni, Antonius Koller, Kartik M Mani, Ruofeng Wen, Alan Alfieri, Subhrajit Saha, Jian Wang, Purvi Patel, Nuno Bandeira, Chandan Guha and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of radiation oncology, biology, physics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–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

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Effect of radiotherapy on the DNA cargo and cellular uptake mechanisms of extracellular vesicles.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2023
    Review
  3. Article
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  7. In vitro models of exosome biology and toxicology: New frontiers in biomedical research.Toxicology in vitro : an international journal published in association with BIBRA · 2020
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
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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

11 authors.

Shilpa KulkarniDepartment of Radiation Oncology, Albert Einstein College of Medicine, Bronx, New York.
Antonius KollerProteomics Center, Stony Brook University School of Medicine, Stony Brook, New York; Proteomics Shared Resource, Herbert Irving Comprehensive Cancer Center, New York, New York.
Kartik M ManiDepartment of Radiation Oncology, Albert Einstein College of Medicine, Bronx, New York.
Ruofeng WenDepartment of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York.
Alan AlfieriDepartment of Radiation Oncology, Albert Einstein College of Medicine, Bronx, New York.
Subhrajit SahaDepartment of Radiation Oncology, Albert Einstein College of Medicine, Bronx, New York.
Jian WangCenter for Computational Mass Spectrometry, University of California, San Diego, California; Department of Computer Science and Engineering, University of California, San Diego, California.
Purvi PatelProteomics Shared Resource, Herbert Irving Comprehensive Cancer Center, New York, New York; Department of Pharmacological Sciences, Stony Brook University, Stony Brook, New York.
Nuno BandeiraCenter for Computational Mass Spectrometry, University of California, San Diego, California; Department of Computer Science and Engineering, University of California, San Diego, California; Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, California.
Chandan GuhaDepartment of Radiation Oncology, Albert Einstein College of Medicine, Bronx, New York. Electronic address: cguha@montefiore.org.
Emily I ChenProteomics Center, Stony Brook University School of Medicine, Stony Brook, New York; Proteomics Shared Resource, Herbert Irving Comprehensive Cancer Center, New York, New York; Department of Pharmacological Sciences, Stony Brook University, Stony Brook, New York; Department of Pharmacology, Columbia University Medical Center, New York, New York. Electronic address: ec2974@columbia.edu.

Funding

Stem Cell-Based Therapies for Radiation-Induced Gastrointestinal Sydrome (RIGS)U19AI091175 · NIAID · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI GUHA, CHANDAN · 2010 to 2014
$13.1M
TrainingP41GM103484 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PEVZNER, PAVEL A · 2012 to 2018
$8.7M
NIAID NIH HHS U19 AI091175NIGMS NIH HHS P41 GM103484
6 · The paper itself

Abstract

purposeEarly and accurate assessment of radiation injury by radiation-responsive biomarkers is critical for triage and early intervention. Biofluids such as urine and serum are convenient for such analysis. Recent research has also suggested that exosomes are a reliable source of biomarkers in disease progression. In the present study, we analyzed total urine proteome and exosomes isolated from urine or serum for potential biomarkers of acute and persistent radiation injury in mice exposed to lethal whole body irradiation (WBI). METHODS AND MATERIALS: For feasibility studies, the mice were irradiated at 10.4 Gy WBI, and urine and serum samples were collected 24 and 72 hours after irradiation. Exosomes were isolated and analyzed using liquid chromatography mass spectrometry/mass spectrometry-based workflow for radiation exposure signatures. A data dependent acquisition and SWATH-MS combined workflow approach was used to identify significantly exosome biomarkers indicative of acute or persistent radiation-induced responses. For the validation studies, mice were exposed to 3, 6, 8, or 10 Gy WBI, and samples were analyzed for comparison.

resultsA comparison between total urine proteomics and urine exosome proteomics demonstrated that exosome proteomic analysis was superior in identifying radiation signatures. Feasibility studies identified 23 biomarkers from urine and 24 biomarkers from serum exosomes after WBI. Urinary exosome signatures identified different physiological parameters than the ones obtained in serum exosomes. Exosome signatures from urine indicated injury to the liver, gastrointestinal, and genitourinary tracts. In contrast, serum showed vascular injuries and acute inflammation in response to radiation. Selected urinary exosomal biomarkers also showed changes at lower radiation doses in validation studies.

conclusionsExosome proteomics revealed radiation- and time-dependent protein signatures after WBI. A total of 47 differentially secreted proteins were identified in urinary and serum exosomes. Together, these data showed the feasibility of defining biomarkers that could elucidate tissue-associated and systemic response caused by high-dose ionizing radiation. This is the first report using an exosome proteomics approach to identify radiation signatures.

Indexed as

Acute Radiation SyndromeAnimalsBiological AssayBiomarkersExosomesFeasibility StudiesMiceProteomeRadiation DosageRadiation ExposureReproducibility of ResultsSensitivity and SpecificityWhole-Body CountingWorkflowBiomarkersProteome

Identifiers

PMID27485285
PMCPMC5042854

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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.