The Mayo Glioblastoma (GBM) Xenograft National Resource will provide users with robust animal models, with corresponding phenotypic and molecular characterizations, that recapitulate key molecular and histologic phenotypes of human GBM tumors from a panel of 79 patient-derived xenografts (PDX). These tumor models were created at the Mayo Clinic by implanting surgical tissue directly into immunocompromised mice and then serially passaging these tumors in mice. The PDX models are highly representative of human GBM tumors and preserve the complex molecular features of the human tumors they were derived from. These highly translational and relevant models have been used widely in neuro-oncology research; the Mayo GBM PDXs are used in over 100 peer-reviewed manuscripts and are key reagents in 37 NIH-funded grants (including 16 NINDS-funded grants). As a complement to the rich multi-omic data sets available on human tumor samples (e.g., The Cancer Genome Atlas), the goal of this R24 is to provide a similar level of molecular characterization across our GBM PDX models and make the data freely-available for Users. Availability of comprehensive multi-omic data for this large PDX panel is critically important to allow Users to readily identify the most relevant tumor model(s) for use in their specific research projects. Towards this goal, the RNAseq, total- and phospho-proteomics studies proposed in this study (Aim 1) will be combined with our whole-exome sequencing and whole methylome studies to provide a broad molecular characterization across the PDX panel. These datasets will be integrated using systems biology approaches to identify critically deregulated signaling networks, which will help Users with limited bioinformatics experience interpret the multi-omic PDX characterizations (Aim 2). We will host all of the PDX molecular and phenotypic characterizations using the open-source cBioPortal software (used to host The Cancer Genome Atlas data at MSKCC) to provide a user-friendly interface to a powerful database with robust integrative multi-omic search capabilities (Aim 3). In parallel, the Mayo GBM Xenograft National Resource will develop an archive of early-passage tumor analytes (DNA, RNA, and protein extracts) and frozen or cryopreserved tumor samples for distribution to Users (Aim 4). In this way, the Aims planned for this proposed National Resource will significantly enhance the availability of highly characterized GBM PDX models for use in basic and translational research across the neuro-oncology community.
The use of clinically relevant brain tumor models is essential for generating meaningful basic and translational scientific discoveries that ultimately could guide development of novel therapeutic strategies for clinical practice. The Mayo GBM Xenograft National Resource will provide detailed molecular and phenotypic characterization of a panel of 79 patient-derived GBM xenograft models and distribute these models across the neuro-oncology research community.
| Chen, Jee-Wei E; Pedron, Sara; Shyu, Peter et al. (2018) Influence of Hyaluronic Acid Transitions in Tumor Microenvironment on Glioblastoma Malignancy and Invasive Behavior. Front Mater 5: |
| Stathias, Vasileios; Jermakowicz, Anna M; Maloof, Marie E et al. (2018) Drug and disease signature integration identifies synergistic combinations in glioblastoma. Nat Commun 9:5315 |
