Abstract 5094: Protein biomarker discovery in glioblastoma using Seldi-Tof-MS (2011)

Abstract Glioblastoma (GBM) is an aggressive brain tumor with a poor prognosis. Generally, patients with GBM show a modest response to all therapeutic modalities. The unsatisfactory response to treatment resides in our lack of ability to identify patients who are most likely to benefit from chemotherapy, in particular targeted therapy. Biomarkers, with high sensitivity and specificity to identify favorable response to treatment are urgently needed to improve survival times. SELDI-TOF MS was used to examine the differential expression of proteins in GBM patients dichotomized according to response to the standard treatment schedule of temozolomide combined with radiotherapy (chemoradiotherapy). Patients with newly diagnosed GBM were recruited from Royal North Shore Hospital (Sydney, Australia). For uniformity, only patients who received chemoradiotherapy were included in this study. Patient response to chemoradiotherapy was defined according to Progression Free Survival (PFS) ≥ 8 months and/or Overall Survival (OS) &gt; 24 months. A known marker of response, MGMT promoter methylation was also measured in all patients. Proteins extracted from 42 fresh-frozen GBM tumour samples were directly analyzed on four different chip surfaces; H50 (hydrophobic), IMAC (metal affinity), Q10 (anion exchange) and CM10 (cation exchange). Total number of 27 patients, PFS &lt; 8 months (n=15) and PFS ≥ 8 months (n=12), separated from the patient cohort. In 54 spectra from 27 samples (performed in duplicate) 61, 47, 84 and 70 common peaks were identified for H50, IMAC, Q10 and CM10 chips, respectively. In combination of data from all chip surfaces, 35 significantly differentially expressed proteins were detected between the two PFS groups. These proteins were evaluated individually and in combination using binary logistic regression (BLR) analysis. Combined analysis of three upregulated proteins in PFS ≥ 8 months group showed a stronger area under the curve (AUC=1.000) when compared with their individual AUCs. Joint BLR analysis of nine significantly upregulated proteins in PFS &lt; 8 months group demonstrated a powerful predictability by AUC=1.000. 39 out of 42 patients could be classified into Long Term Survived (LTS) (n=7) and Short Term Survived (STS) (n=32) patient subgroups. 70 peaks with H50 and 73 with CM10 were identified common to both patient groups. 13 protein peaks were found differentially expressed between groups. Two upregulated proteins identified in the LTS patient group were detected by BLR analysis as the most potent biomarkers to discriminate between the two OS groups with an improved AUC=0.87 in combination. In conclusion, proteomics is an effective method for identifying potential candidate biomarkers associated with response to treatment. Further experiments will be performed for identification and validation of explored peptides. These findings will provide new insights into understanding response of GBM patients to the standard therapy. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 5094. doi:10.1158/1538-7445.AM2011-5094