Neuroblastoma detection using serum proteomic profiling: a novel mining technique for cancer?

Abstract

Background Serum proteins in neuroblastoma (NB), such as neuron-specific enolase and lactate dehydrogenase, are used as nonspecific markers of disease severity. In this study, we have generated serum protein profiles that correlate with NB by applying proteomic technologies to uncover, at the protein level, serum polypeptide expression patterns in patients with NB. Methods Surface-enhanced laser desorption/ionization–time-of-flight mass spectrometry was used to generate protein expression spectra in human NB (group I, n = 18) and healthy children (group II, n = 17) sera. Groups I and II mass spectral data were compared after baseline subtraction. Peaks with high signal-to-noise ratios were selected and grouped into bins with various intervals along mass-to-charge axis. Two-sample t test and 3-fold cross validation were used to identify differential biomarkers between groups I and II. Results Significant differentially expressed proteins were identified between groups I and II ( P ≤ .05). The discriminatory features (proteomic patterns) of cancer from normal sera were successfully identified using the classification algorithm. The average classification performance after 3-fold cross validation was 87.26%. Conclusion Surface-enhanced laser desorption/ionization–time-of-flight mass spectrometry is suitable for preliminary assessment of NB and could potentially provide a noninvasive diagnosis of NB. We propose that surface-enhanced laser desorption/ionization provides a novel method for NB diagnosis because direct observations of spectral differences between normal and NB sera are possible.