Discovering clinical biomarkers of ionizing radiation exposure with serum proteomic analysis

Cynthia Ménard, Donald Johann, Mark Lowenthal, Thierry Muanza, Mary Sproull, Sally Ross, James Gulley, Emanuel Petricoin, C. Norman Coleman, Gordon Whiteley, Lance Liotta, Kevin Camphausen

Research output: Contribution to journalArticle

Abstract

In this study, we sought to explore the merit of proteomic profiling strategies in patients with cancer before and during radiotherapy in an effort to discover clinical biomarkers of radiation exposure. Patients with a diagnosis of cancer provided informed consent for enrollment on a study permitting the collection of serum immediately before and during a course of radiation therapy. High-resolution surface-enhanced laser desorption and ionization-time of flight (SELDI-TOF) mass spectrometry (MS) was used to generate high-throughput proteomic profiles of unfractionated serum samples using an immobilized metal ion-affinity chromatography nickel-affinity chip surface. Resultant proteomic profiles were analyzed for unique biomarker signatures using supervised classification techniques. MS-based protein identification was then done on pooled sera in an effort to begin to identify specific protein fragments that are altered with radiation exposure. Sixty-eight patients with a wide range of diagnoses and radiation treatment plans provided serum samples both before and during ionizing radiation exposure. Computer-based analyses of the SELDI protein spectra could distinguish unexposed from radiation-exposed patient samples with 91% to 100% sensitivity and 97% to 100% specificity using various classifier models. The method also showed an ability to distinguish high from low dose-volume levels of exposure with a sensitivity of 83% to 100% and specificity of 91% to 100%. Using direct identity techniques of albumin-bound peptides, known to underpin the SELDI-TOF fingerprints, 23 protein fragments/peptides were uniquely detected in the radiation exposure group, including an interleukin-6 precursor protein. The composition of proteins in serum seems to change with ionizing radiation exposure. Proteomic analysis for the discovery of clinical biomarkers of radiation exposure warrants further study.

Original languageEnglish (US)
Pages (from-to)1844-1850
Number of pages7
JournalCancer Research
Volume66
Issue number3
DOIs
StatePublished - Feb 1 2006
Externally publishedYes

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Ionizing Radiation
Proteomics
Biomarkers
Serum
Mass Spectrometry
Lasers
Radiotherapy
Radiation
Peptide Fragments
Proteins
Peptide Mapping
Protein Precursors
Nickel
Informed Consent
Affinity Chromatography
Radiation Exposure
Blood Proteins
Albumins
Interleukin-6
Neoplasms

ASJC Scopus subject areas

  • Cancer Research
  • Oncology

Cite this

Ménard, C., Johann, D., Lowenthal, M., Muanza, T., Sproull, M., Ross, S., ... Camphausen, K. (2006). Discovering clinical biomarkers of ionizing radiation exposure with serum proteomic analysis. Cancer Research, 66(3), 1844-1850. https://doi.org/10.1158/0008-5472.CAN-05-3466

Discovering clinical biomarkers of ionizing radiation exposure with serum proteomic analysis. / Ménard, Cynthia; Johann, Donald; Lowenthal, Mark; Muanza, Thierry; Sproull, Mary; Ross, Sally; Gulley, James; Petricoin, Emanuel; Coleman, C. Norman; Whiteley, Gordon; Liotta, Lance; Camphausen, Kevin.

In: Cancer Research, Vol. 66, No. 3, 01.02.2006, p. 1844-1850.

Research output: Contribution to journalArticle

Ménard, C, Johann, D, Lowenthal, M, Muanza, T, Sproull, M, Ross, S, Gulley, J, Petricoin, E, Coleman, CN, Whiteley, G, Liotta, L & Camphausen, K 2006, 'Discovering clinical biomarkers of ionizing radiation exposure with serum proteomic analysis', Cancer Research, vol. 66, no. 3, pp. 1844-1850. https://doi.org/10.1158/0008-5472.CAN-05-3466
Ménard, Cynthia ; Johann, Donald ; Lowenthal, Mark ; Muanza, Thierry ; Sproull, Mary ; Ross, Sally ; Gulley, James ; Petricoin, Emanuel ; Coleman, C. Norman ; Whiteley, Gordon ; Liotta, Lance ; Camphausen, Kevin. / Discovering clinical biomarkers of ionizing radiation exposure with serum proteomic analysis. In: Cancer Research. 2006 ; Vol. 66, No. 3. pp. 1844-1850.
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