title: Identifying Urinary and Serum Exosome Biomarkers for Radiation Exposure Using a Data Dependent Acquisition and SWATH-MS Combined Workflow.
abstract: Early 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).
  
  
  
  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.
  
  
  
  A 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.
  
  
  
  Exosome 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.
authors.affiliation: Department of Radiation Oncology, Albert Einstein College of Medicine, Bronx, New York.
authors.forename: Shilpa
authors.initials: S
authors.lastname: Kulkarni
authors.affiliation: Proteomics Center, Stony Brook University School of Medicine, Stony Brook, New York; Proteomics Shared Resource, Herbert Irving Comprehensive Cancer Center, New York, New York.
authors.forename: Antonius
authors.initials: A
authors.lastname: Koller
authors.affiliation: Department of Radiation Oncology, Albert Einstein College of Medicine, Bronx, New York.
authors.forename: Kartik M
authors.initials: KM
authors.lastname: Mani
authors.affiliation: Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York.
authors.forename: Ruofeng
authors.initials: R
authors.lastname: Wen
authors.affiliation: Department of Radiation Oncology, Albert Einstein College of Medicine, Bronx, New York.
authors.forename: Alan
authors.initials: A
authors.lastname: Alfieri
authors.affiliation: Department of Radiation Oncology, Albert Einstein College of Medicine, Bronx, New York.
authors.forename: Subhrajit
authors.initials: S
authors.lastname: Saha
authors.affiliation: Center for Computational Mass Spectrometry, University of California, San Diego, California; Department of Computer Science and Engineering, University of California, San Diego, California.
authors.forename: Jian
authors.initials: J
authors.lastname: Wang
authors.affiliation: Proteomics Shared Resource, Herbert Irving Comprehensive Cancer Center, New York, New York; Department of Pharmacological Sciences, Stony Brook University, Stony Brook, New York.
authors.forename: Purvi
authors.initials: P
authors.lastname: Patel
authors.affiliation: Center 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.
authors.forename: Nuno
authors.initials: N
authors.lastname: Bandeira
authors.affiliation: Department of Radiation Oncology, Albert Einstein College of Medicine, Bronx, New York. Electronic address: cguha@montefiore.org.
authors.forename: Chandan
authors.initials: C
authors.lastname: Guha
authors.affiliation: Proteomics 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.
authors.forename: Emily I
authors.initials: EI
authors.lastname: Chen
mesh_terms: D054508:Acute Radiation Syndrome / Q000097:blood* / Q000175:diagnosis / Q000652:urine*; D000818:Animals; D001681:Biological Assay / Q000379:methods*; D015415:Biomarkers / Q000097:blood / Q000652:urine; D055354:Exosomes / Q000737:chemistry*; D005240:Feasibility Studies; D051379:Mice; D020543:Proteome / Q000032:analysis*; D011829:Radiation Dosage; D000069079:Radiation Exposure / Q000032:analysis*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014915:Whole-Body Counting / Q000379:methods; D057188:Workflow
chemical_list: D015415:Biomarkers; D020543:Proteome