Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) extends MALDI-TOF's capability by incorporating an element of chromatog-raphy-based selection to isolate different sets ofproteins based on their biophysical properties (24,25). By combining protein capture on chromatographic surfaces with MS and artificial intelligence, SELDI is capability of generating protein profiles reproducibly from crude biological fluids with relative high throughput. The ease and speed of screening samples have made SELDI a popular method for biomarker discovery (26). Ion signatures generated by cluster analysis has achieved high specificity and sensitivity for ovarian, prostate, and breast cancer diagnosis (27-32). Despite these impressive results, a different view argues against the commonly held idea that biomolecules or fragments of biomolecules constituting the diagnostic pattern are derived from the tumor itself, thus casting doubt on the value of using the signature pattern for diagnosis (33). Validation will need to rely on extensive clinical trials. SELDI has limitations in the ability to detect large ions and, thus, implementing the strategy with higher performance mass analyzers and tandem mass spectrometers to further characterize those unknown molecules are warranted. Better interpretation of the diagnostic patterns for a better understanding of cancer disease mechanism would be useful.
The contribution of laser capture microdissection (LCM) to SELDI's success in biomarker discovery cannot be overstated (34,35). Cancer proteomics has long been hampered by limited sample material and tissue heterogeneity. The capability of LCM to enrich cells of interest from tissue sections overcame the problem of tissue heterogeneity, thus becoming an indispensable component of the SELDI-TOF technique in cancer biomarker discovery.
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