SELDI-TOF MS proteomics in breast cancer

Bashar A. Zeidan, Ramsey I. Cutress, Claire Hastie, Alex H. Mirnezami, Graham Packham, Paul A. Townsend

    Research output: Contribution to journalArticlepeer-review


    Background: Proteomic profiling is a rapidly developing technology that may enable early disease screening and diagnosis. Surface-enhanced laser desorption ionization-time of flight mass spectrometry (SELDI-TOF MS) has demonstrated promising results in screening and early detection of many diseases. In particular, it has emerged as a high-throughput tool for detection and differentiation of several cancer types. This review aims to appraise published data on the impact of SELDI-TOF MS in breast cancer. Methods: A systematic literature search between 1965 and 2009 was conducted using the PubMed, EMBASE, and Cochrane Library databases. Studies covering different aspects of breast cancer proteomic profiling using SELDI-TOF MS technology were critically reviewed by researchers and specialists in the field. Results: Fourteen key studies involving breast cancer biomarker discovery using SELDI-TOF MS proteomic profiling were identified. The studies differed in their inclusion and exclusion criteria, biologic samples, preparation protocols, arrays used, and analytical settings. Taken together, the numerous studies suggest that SELDI-TOF MS methodology may be used as a fast and robust approach to study the breast cancer proteome and enable the analysis of the correlations between proteomic expression patterns and breast cancer. Conclusion: SELDI-TOF MS is a promising high-throughput technology with potential applications in breast cancer screening, detection, and prognostication. Further studies are needed to resolve current limitations and facilitate clinical utility. © 2009 Humana Press.
    Original languageEnglish
    Pages (from-to)133-147
    Number of pages14
    JournalClinical Proteomics
    Issue number3-4
    Publication statusPublished - Dec 2009


    • Biomarkers
    • Breast cancer
    • Proteomics
    • SELDI


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