The development of drugs to inhibit glioblastoma (GBM) growth requires reliable pre-clinical models. To date, proteomic level validation of widely used patient-derived glioblastoma xenografts (PDGX) has not been performed. In the present study, we characterized 20 PDGX models according to subtype classification based on The Cancer Genome Atlas criteria, TP53, PTEN, IDH 1/2, and TERT promoter genetic analysis, EGFR amplification status, and examined their proteomic profiles against those of their parent tumors. The 20 PDGXs belonged to three of four The Cancer Genome Atlas subtypes: eight classical, eight mesenchymal, and four proneural; none neural. Amplification of EGFR gene was observed in 9 of 20 xenografts, and of these, 3 harbored the EGFRvIII mutation. We then performed proteomic profiling of PDGX, analyzing expression/activity of several proteins including EGFR. Levels of EGFR phosphorylated at Y1068 vary considerably between PDGX samples, and this pattern was also seen in primary GBM. Partitioning of 20 PDGX into high (n = 5) and low (n = 15) groups identified a panel of proteins associated with high EGFR activity. Thus, PDGX with high EGFR activity represent an excellent pre-clinical model to develop therapies for a subset of GBM patients whose tumors are characterized by high EGFR activity. Further, the proteins found to be associated with high EGFR activity can be monitored to assess the effectiveness of targeting EGFR. The development of drugs to inhibit glioblastoma (GBM) growth requires reliable pre-clinical models. We validated proteomic profiles using patient-derived glioblastoma xenografts (PDGX), characterizing 20 PDGX models according to subtype classification based on The Cancer Genome Atlas (TCGA) criteria, TP53, PTEN, IDH 1/2, and TERT promoter genetic analysis, EGFR amplification status, and examined their proteomic profiles against those of their parent tumors. Proteins found to be associated with high EGFR activity represent potential biomarkers for GBM monitoring.
Keywords: EGFR; RPPA; glioblastoma; signaling; xenografts.
© 2015 International Society for Neurochemistry.