Glioblastoma (GBM) is the most lethal brain malignancy owing to its exceptional resistance to radiation, chemotherapy and surgical resection. While 50% of all GBM cases harbor oncogenic alterations in the gene encoding the Epidermal Growth Factor Receptor (EGFR), it is unclear how the vast majority of those alterations influence EGFR functionality, oncogenic activity and response to available cancer therapeutics. In contrast to EGFR variants found in other types of cancers that involve alterations primarily in the intracellularly- localized kinase domain (KD), the vast majority of EGFR alterations in GBM occur in the ectodomain (EC) extended into the extracellular space. Based on recent studies revealing therapeutic response differences between a small number of EGFR EC and KD variants, we hypothesize that the broader spectrum of oncogenic EGFR EC variants differs functionally from KD mutants with respect to oncogenic signaling and therapeutic vulnerabilities in GBM. The overarching goal of this study is to functionalize the spectrum of EGFR EC and KD aberrations occurring in GBM, as identifying bona fide ?driver? mutations and understanding their mechanism of action may inform new cancer diagnostics and therapies.
The specific aims of this study are (1) to construct a barcoded EGFR allelic series library, (2) to functionally validate EGFR mutant drivers of GBM, and (3) to determine signaling and therapeutic response differences mediated by oncogenic EGFR EC and KD variants. To address these aims, established high-throughput mutagenesis and molecular barcoding strategies will be leveraged to assemble a library consisting of 64 EGFR variants and controls selected from GBM sequencing data. To determine which mutations contribute to tumorigenesis, EGFR variants will be evaluated for oncogenic activity by employing pooled functional screens using two novel in vivo models that provide the appropriate genetic and biological context of GBM. Specifically, we will combine use of CRISPR-based gene editing of known GBM tumor suppressors with our barcoded EGFR expression libraries for pooled EGFR variant competition assays using 1) an in utero brain electroporation model and 2) a modified neural stem/progenitor cell (NSC) orthotopic transplant model. To investigate mechanistic differences between EGFR EC and KD variants, we will subject NSC cell populations derived from our in vivo studies to immunoblot analysis and drug sensitivity assays to identify differential signaling pathway activation and therapeutic responses by EGFR variants. Successful completion of these studies will not only illuminate the cancer functionality and mechanisms of action of EGFR variants in GBM, but may also uncover novel biomarkers/targets that will immediately inform new therapeutic modalities to treat this fatal disease.

Public Health Relevance

In this proposal we will construct the majority of cancer-related mutations found in the gene encoding Epidermal Growth Factor Receptor (EGFR), the most frequently altered gene in Glioblastoma (GBM), and characterize their oncogenic function and response to cancer therapeutics in the appropriate biological context of the brain. Successful completion of these studies will identify the subset of EGFR mutations that have a role in tumor development and determine their mechanism-of-action. Moreover, the proposed work may uncover novel biomarkers and targets that will immediately inform new therapeutic modalities to treat this fatal disease as well as other EGFR-driven cancers.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Postdoctoral Individual National Research Service Award (F32)
Project #
5F32CA221015-02
Application #
9598301
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Mcguirl, Michele
Project Start
2017-06-28
Project End
2018-09-08
Budget Start
2018-06-28
Budget End
2018-09-08
Support Year
2
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Baylor College of Medicine
Department
Genetics
Type
Schools of Medicine
DUNS #
051113330
City
Houston
State
TX
Country
United States
Zip Code
77030