Abstract C223: Network-based approach aids in the discovery of context-specific druggable targets for treatment of glioblastoma.
Harshil Dhruv, Seungchan Kim, Jeffrey Kiefer, Dorothea Emig-Agius, Darren Finlay, Sung-Won Jung, Kristiina Vuori, Michael E. Berens · Molecular Cancer Therapeutics · 2013
Abstract Systematic discovery of actionable cancer targets could fill an unmet need for improved approaches to manage Glioblastoma Multiforme (GBM). Critical barriers to the discovery of druggable targets in cancer include: 1) molecular heterogeneity of the disease across patients, 2) implementation of a systematic approach to utilize existing knowledge and molecular data for target discovery, and 3) the lack of a relevant, rapid and systematic pipeline to enable empirical testing of hypotheses. We describe a network-based method to stratify GBM clinical samples into molecularly homogeneous subsets based on gene expression, gene copy number, and miRNAs, which we term “molecular contexts," or mCs. Within these mCs, a knowledge-based topological analysis of pathway elements was used to uncover discrete mC-specific targets. An empiric chemical screen probed the target space across different mCs, mC-4 and mC-14, which were molecularly orthogonal to each other. Specimens in mC-4 were enriched with samples previously classified as Mesenchymal-type GBM, while mC-14 was enriched with Proneural-subtype GBM. The chemical screen was carried out using short-term in vitro cultures derived from patient-derived GBM xenografts, which mapped to mC4 and mC14 based on gene expression. We employed a network-based topological approach to discern targets and pathways as candidate druggable vulnerabilities. The chemical validation screen was carried out with an assembled chemical biology fingerprint (CBF) library comprised of 650 small molecules targeting multiple cancer-associated pathways and processes. Matching specific chemical hits to their respective targets allowed for validation of specific gene hits from the topological analysis. Of particular interest were two molecular context specific lethal compounds in the screen, tamoxifen citrate and arsenic trioxide, specific to the mC4 and mC14, respectively. PKC, among the targets of Tamoxifen citrate, was a predicted node of vulnerability for mC-4 GBM, while PML gene, a target of Arsenic Trioxide, was a predicted target for mC-14. In summary, our results suggest that context analysis coupled with knowledge-based enrichment and topological analysis identifies specific GBM contexts with novel unique drugable targets. Supported by NIH U01 CA168397. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):C223. Citation Format: Harshil D. Dhruv, Seungchan Kim, Jeff Kiefer, Dorothea Emig-Agius, Darren Finlay, Sungwon Jung, Kristiina Vuori, Michael Berens. Network-based approach aids in the discovery of context-specific druggable targets for treatment of glioblastoma. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr C223.