Identification of a plasma proteomic signature to distinguish pediatric osteosarcoma from benign osteochondroma

Yiting Li, Tu Anh Dang, Jianhe Shen, Laszlo Perlaky, John Hicks, Jeffrey Murray, William Meyer, Murali Chintagumpala, Ching C. Lau, Tsz Kwong Man

Research output: Contribution to journalArticle

49 Scopus citations

Abstract

Osteosarcoma (OS) is the most common malignant bone tumor in children. To identify a plasma proteomic signature that can detect OS, we used SELDI MS to perform proteomic profiling on plasma specimens from 29 OS and 20 age-matched osteochondroma (OC) patients. Nineteen statistically significant ion peaks that were differentially expressed in OS when compared with OC patients were identified (p < 0.001 and false discovery rate < 10%). Using the proteomic profiles, we constructed a multivariate 3-nearest neighbors classifier to distinguish OS from OC patients with a sensitivity of 97% and a specificity of 80% based on external leave-one-out cross-validation. Permutation test showed that the classification result was statistically significant (p < 0.00005). One of the proteins (m/z 11 704) in the proteomic signature was identified as serum amyloid protein A (SAA) by PMF. The higher plasma level of SAA in OS patients was further validated by Western blotting when compared to that of osteochrondroma patients and normal subjects as reference. The classifier based on this plasma proteomic signature may be useful to differentiate malignant bone cancer from benign bone tumors and for early detection of OS in high-risk individuals.

Original languageEnglish (US)
Pages (from-to)3426-3435
Number of pages10
JournalProteomics
Volume6
Issue number11
DOIs
StatePublished - Jun 2006

Keywords

  • Molecular classification
  • Osteosarcoma
  • SELDI
  • Serum amyloid protein A

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics

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