BACKGROUND: The limited success of empirically designed treatment paradigms for patients diagnosed with glioblastoma multiforme (GBM) emphasizes the need for rationally designed treatment strategies based on the molecular profile of tumor samples and their correlation to clinical parameters. METHODS: In the current study, we utilize a novel real-time quantitative low density array (RTQ-LDA) to identify differentially expressed genes in de novo GBM tissues obtained from patients with distinctly different clinical outcomes. Total RNA was isolated from a cohort of 21 GBM specimens obtained from patients with either good (long-term survival (LTS) >36 months post surgery, n = 8) or poor (died of the disease (DOD) <24 months post surgery, n = 13) prognosis. Non-neoplastic brain tissue (n = 5) was obtained from patients who underwent surgery for refractory epilepsy. Demographic data was assessed for correlation with survival using Cox proportional hazards models. Sufficient RNA was available to use RTQ-LDA to quantify the expression of 93 independent genes in 5 LTS, 4 DOD, and 5 non-neoplastic brain samples. The eight differentially expressed genes identified by RTQ-LDA in LTS versus DOD (P <or= 0.050) were subsequently quantified in all 21 GBM samples by real-time quantitative PCR (RTQ). RESULTS: A correlation between younger patients and good prognosis was demonstrated (P <or= 0.05). The combination of RTQ-LDA and RTQ identified thymidylate synthetase (TS), ubiquitin specific protease 10 (USP10), and survivin as significantly over-expressed (P <or= 0.050) in DOD compared to LTS patients. Ribonucleotide reductase subunit M2 (RRM2) was identified as tumor-specific, but not associated with survival. CONCLUSIONS: Taken collectively, TS, USP10, survivin and RRM2 may be useful as prognostic indicators and/or in the development of rationally designed treatment protocols.
BACKGROUND: The limited success of empirically designed treatment paradigms for patients diagnosed with glioblastoma multiforme (GBM) emphasizes the need for rationally designed treatment strategies based on the molecular profile of tumor samples and their correlation to clinical parameters. METHODS: In the current study, we utilize a novel real-time quantitative low density array (RTQ-LDA) to identify differentially expressed genes in de novo GBM tissues obtained from patients with distinctly different clinical outcomes. Total RNA was isolated from a cohort of 21 GBM specimens obtained from patients with either good (long-term survival (LTS) >36 months post surgery, n = 8) or poor (died of the disease (DOD) <24 months post surgery, n = 13) prognosis. Non-neoplastic brain tissue (n = 5) was obtained from patients who underwent surgery for refractory epilepsy. Demographic data was assessed for correlation with survival using Cox proportional hazards models. Sufficient RNA was available to use RTQ-LDA to quantify the expression of 93 independent genes in 5 LTS, 4 DOD, and 5 non-neoplastic brain samples. The eight differentially expressed genes identified by RTQ-LDA in LTS versus DOD (P <or= 0.050) were subsequently quantified in all 21 GBM samples by real-time quantitative PCR (RTQ). RESULTS: A correlation between younger patients and good prognosis was demonstrated (P <or= 0.05). The combination of RTQ-LDA and RTQ identified thymidylate synthetase (TS), ubiquitin specific protease 10 (USP10), and survivin as significantly over-expressed (P <or= 0.050) in DOD compared to LTS patients. Ribonucleotide reductase subunit M2 (RRM2) was identified as tumor-specific, but not associated with survival. CONCLUSIONS: Taken collectively, TS, USP10, survivin and RRM2 may be useful as prognostic indicators and/or in the development of rationally designed treatment protocols.
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