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A set of proteins reflecting the prognosis of patients have clinical significancesince they could be utilized as predictive biomarkers and/or potential therapeutictargets. With the aim of finding novel diagnostic and prognostic markers for glioblastoma(GBM), a tissue microarray (TMA) library consisting of 62 GBMs and 28 GBM-associatednormal spots was constructed. Immunohistochemistry against 78 GBM-associated proteinswas performed. Expression levels of each protein for each patient were analyzedusing an image analysis program and converted to H-score [summation of the intensitygrade of staining (0-3) multiplied by the percentage of positive cells correspondingto each grade]. Based on H-score and hierarchical clustering methods, we dividedthe GBMs into two groups (n=19 and 37) that had significantly different survivallengths (p&lt;0.05). In the two groups, expression of nine proteins (survivin,cyclin E, DCC, TGF-β, CDC25B, histone H1, p-EGFR, p-VEGFR2/3, p16) was significantlychanged (q&lt;0.05). Prognosis-predicting potential of these proteins were validatedwith another independent library of 82 GBM TMAs and a public GBM DNA microarraydataset. In addition, we determined 32 aberrant or mislocalized subcellular proteinexpression patterns in GBMs compared with relatively normal brain tissues, whichcould be useful for diagnostic biomarkers of GBM. We therefore suggest that theseproteins can be used as predictive biomarkers and/or potential therapeutic targetsfor GBM.

Identification of prognostic biomarkers for glioblastomas using protein expression profiling