BI-12RTOG 0525 RECURSIVE PARTITIONING ANALYSIS BASED ON CLINICAL AND PROTEIN BIOMARKER PARAMETERS
Other Scholarly Work
Bell, Erica Hlavin, Pugh, Stephanie, Gilbert, Mark et al. (2014). BI-12RTOG 0525 RECURSIVE PARTITIONING ANALYSIS BASED ON CLINICAL AND PROTEIN BIOMARKER PARAMETERS
. NEURO-ONCOLOGY, 16(Suppl 5), v25-v25.
Bell, Erica Hlavin, Pugh, Stephanie, Gilbert, Mark et al. (2014). BI-12RTOG 0525 RECURSIVE PARTITIONING ANALYSIS BASED ON CLINICAL AND PROTEIN BIOMARKER PARAMETERS
. NEURO-ONCOLOGY, 16(Suppl 5), v25-v25.
BACKGROUND: The objective was to revise the clinically-based RTOG RPA (cRPA) model for glioblastoma (GBM) through incorporation of protein biomarkers. METHODS: RTOG 0525 patients with adequate specimens were analyzed for up to 22 protein biomarkers representing key pathways putatively associated with treatment resistance and/or adverse clinical outcome. Protein expression levels were quantified using a molecular microscopy-based approach (AQUA) and cytoplasmic versus nuclear expression was determined. Each protein biomarker was analyzed for prognostic significance by uni- and multivariate (UVA, MVA) Cox regression analysis. Proteins significantly associated with survival along with age, KPS, neurologic function, and surgery status were incorporated into the clinical RPA model (cpRPA). RESULTS: 428 samples were analyzed. On stepwise MVA (n = 164), nuclear MGMT (p = 0.001, HR = 1.84), and cMET (p = 0.001, HR = 1.83) were independently prognostic. The new cpRPA model was developed using 168 patients with all significant protein biomarker data and was comprised of three classes incorporating nuclear MGMT, age, and performance status. The new cpRPA model showed greater separation of prognostic classes of GBM relative to the currently used cRPA model (Median overall-survival for Classes III, IV, and V are 30.0, 16.1, and 11.4 months for cRPA and 21.1, 11.3, and 4.8 months for the cpRPA based on three new cpRPA classes (I-III) (p < 0.001). CONCLUSIONS: Incorporating protein biomarkers with variables in the existing cRPA produces greater separation of the survival curves, suggesting a role for further validation studies. This project was supported by grants U10CA21661, U10CA180868, U10CA180822, U10 CA37422, U24CA180803, RO1CA108633 (To AC), 1RC2CA148190 (To AC) U10CA180850-01 (To AC), 1R01CA169368 (To AC) from the National Cancer Institute (NCI), Brain Tumor Funders Collaborative Grant (To AC), Ohio State University Comprehensive Cancer Center Award (To AC) and Merck & Co.
