GENO-21: BRCA1 PROTEIN EXPRESSION PREDICTS SURVIVAL IN GLIOBLASTOMA PATIENTS FROM A NRG ONCOLOGY/RTOG COHORT

BACKGROUND: Glioblastoma multiforme is the most common malignant brain tumor, associated with mean survival <1 year in the pre-temozolomide era. Histologic parameters have had limited value in predicting survival among patients with glioblastoma. Despite advances in recent molecular and genetic profiling studies identifying several prognostic and predictive biomarkers, none has translated into routine clinical use. Our aim was to investigate the expression and prognostic significance of a panel of diverse cellular molecular markers of tumor formation and growth in an annotated glioblastoma tissue microarray. METHODS: A tissue array composed of archived glioblastoma tumors from 66 patients treated with surgery, radiation, and non-temozolomide chemotherapy, was provided by the RTOG. RAD51, BRCA-1, PTEN, and miRNA-210 expression levels were assessed using quantitative in-situ hybridization and automated quantitative protein analysis (AQUA). The objectives of this analysis were to determine the association of each biomarker with overall survival (OS), using the Cox proportional hazard model. Event-time distributions were estimated using the Kaplan-Meier method and compared by the log-rank test. RESULTS: Among the four biomarkers assessed, only BRCA1 expression had a statistically significant correlation with survival. From univariate analysis, patients with low BRCA1 protein expression showed a favorable outcome for OS (p = 0.04; hazard ratio = 0.56) in comparison with high expressors, with median survival times of 18.9 vs. 4.8 months. CONCLUSIONS: BRCA1 protein expression was an important prognostic determinant in our cohort of glioblastoma patients treated with surgery followed by chemo-radio-therapy. This result may imply that low BRCA1 in the tumor, and the consequent low level of DNA repair, causes vulnerability of the cancer cells to treatment. Prospective validation of these results is necessary. This project was supported by grants U10CA21661, U10CA180868, U10CA180822 and U10CA37422 (CCOP) from the National Cancer Institute (NCI) and Genentech.