Pediatric brain tumors are the leading cause of disease related death in children. Major factors contributing to treatment failures for children with brain tumors include: i) the lack of comprehensive molecular description of the disease and an associated dearth of integration of the tumors’ biological signatures at gene, protein and RNA levels; ii) paucity of comprehensive and molecularly-driven preclinical tests for informing precision-targeting disease pathways; and iii) lack of sensitive methods of assessing tumor response to treatment. Furthermore, while surgery remains the mainstay of pediatric brain tumor treatment, many tumors are non-resectable and/or progressive/disseminated tumors lead to significant tumor-related morbidity. In contrast to adults, tumors in central nervous system are often challenging to treat with traditional chemotherapy and radiation resulting in long-term neuro-toxicities in the context of the developing brain.
While pediatric cancers have benefited from large-scale genomics efforts lead by the NIH in the context of TARGET (Therapeutically Applicable Research To Generate Effective Treatments), brain tumors are not represented in these cohorts. The consortia-based efforts of the Children’s Brain Tumor Network and the Pacific Pediatric Neuro-Oncology Consortium and associated platforms were complemented with the launch of CAVATICA (cavatica.org), a scalable, cloud-based storage and compute environment providing comprehensive, secure, and integrated access to pediatric cancer genomic data that is further integrated with additional rare-disease-genomic data. These early efforts are now undergoing significant expansion through the Commons Fund’s Kids First Program and CHOP’s role in leading the development of the Kids First Data Resource Center (DRC) along with its partners at the Ontario Institute for Cancer Research, the University of Chicago, Children’s National Health System, the Oregon Health and Science University and Seven Bridges. The Kids First DRC will support accelerated scientific discovery across more than >20,000 WGS from dozens of childhood cancer and structural birth defects cohorts being sequenced over the next 2 years. It is in this context of emerging genomic data and a data commons architecture that we propose to define a discovery cohort for comprehensive proteomic analysis in pediatric brain tumors.
