Abstract 2352: Defining a pediatric cancer dependency map
Authors: Dharia Neekesh V. , Malone Clare , Iniguez Amanda Balboni , Guenther Lillian , Chen Liying , Alexe Gabriela , Durbin Adam D. , Zimmerman Mark W. , Hong Andrew , Bandopadhayay Pratiti , Filbin Mariella G. , Howard Thomas , Paolella Brenton , Fung Iris , Lee Josephine , Montgomery Phil , Krill-Burger John M. , Abraham Brian J. , Roth Jennifer , Root David E. , Young Richard A. , Look A. Thomas , Beroukhim Rameen , Boehm Jesse S. , Hahn William C. , Golub Todd R. , Tsherniak Aviad , Vazquez Francisca , Stegmaier Kimberly 
Published: August 2018

Abstract
Many children with metastatic or recurrent pediatric solid tumors continue to have poor survival, and there is an immense need to identify novel therapeutic approaches. Moreover, these cancers typically have simple genomes with limited known druggable molecular events. In order to discover new vulnerabilities in pediatric solid tumors, we have performed genome-scale CRISPR-Cas9 loss-of-function screening and deep “omic” characterization in over 60 pediatric cancer cell lines to date, including neuroblastoma, medulloblastoma, Ewing sarcoma, malignant rhabdoid tumor and rhabdomyosarcoma lines, to begin defining a pediatric cancer dependency map. Global analyses of the pediatric dependency landscape have identified emerging classes of pediatric cancers, including epigenetic-driven, aberrant transcription factor-driven and receptor tyrosine kinase-driven malignancies. For example, the preferential dependencies identified in a subset of neuroblastoma, which has aberrantly high expression of the transcription factor MYCN, are highly enriched for an interconnected network of genes annotated to have transcription factor activity. In addition to the global evaluation, we have developed methods and tools for prioritizing targets for further validation within a cancer type. These tools computationally integrate the pediatric dependency data across multiple datasets to identify categories of genetic dependencies that are especially strong hits or enriched hits in a specific pediatric malignancy. As an example, the intersection of MYCN-amplified neuroblastoma specific dependencies and H3-lysine 27 acetylation (H3K27ac) profiling across MYCN-amplified neuroblastoma allowed us to identify a transcriptional core regulatory circuit (CRC) that may drive the malignant state. Furthermore, targeting transcription with the BRD4 inhibitor JQ1 and CDK7 inhibitor THZ1 caused synergistic killing of neuroblastoma cells suggesting a novel therapeutic approach to treating this disease. Thus, defining a comprehensive pediatric cancer dependency map and developing the methods and tools to prioritize vulnerabilities in different cancer types will allow us to discover both novel biology and new therapeutic opportunities in childhood malignancies.
Citation Format: Neekesh V. Dharia, Clare Malone, Amanda Balboni Iniguez, Lillian Guenther, Liying Chen, Gabriela Alexe, Adam D. Durbin, Mark W. Zimmerman, Andrew Hong, Pratiti Bandopadhayay, Mariella G. Filbin, Thomas Howard, Brenton Paolella, Iris Fung, Josephine Lee, Phil Montgomery, John M. Krill-Burger, Brian J. Abraham, Jennifer Roth, David E. Root, Richard A. Young, A. Thomas Look, Rameen Beroukhim, Jesse S. Boehm, William C. Hahn, Todd R. Golub, Aviad Tsherniak, Francisca Vazquez, Kimberly Stegmaier. Defining a pediatric cancer dependency map [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2352.