Abstract IA-18: Big pediatric cancer genomic data: Discovery, precision medicine, and data sharing

Abstract

Abstract High throughput next generation sequencing (NGS) has enabled tremendous advances in our understanding of the genomic landscape of pediatric cancer, leading to discoveries of new mechanisms of tumor initiation and progression, novel targets, and diagnostic and prognostic markers. By focusing on the development of innovative computational analysis tools, we have investigated the genomic variants in pediatric cancer in the following areas: 1) genomic landscapes of >20 subtypes of pediatric cancer; 2) a pan-cancer study of genomes and transcriptomes of pediatric cancer which unveiled that >50% of the driver genes are absent in adult cancer; 3) clonal evolution of relapsed pediatric leukemia driven by therapy-induced variants bearing novel mutational signature; and 4) pathogenic germline mutations in cancer predisposition genes. These insights led to implementation of clinical cancer genomic profiling by three-platform of whole genome, whole exome and transcriptome sequencing for all eligible pediatric cancer patients at St Jude. Use of these data sets improved molecular diagnosis of pediatric cancer. Since 2015, we have analyzed >1,200 pediatric oncology patients providing critical data that may affect patient care. The omics data generated from our research and clinical programs can be accessed on St. Jude Cloud (https://www.stjude.cloud), a cloud-based data sharing ecosystem for accessing, analyzing and visualizing genomic data generated from >10,000 pediatric cancer patients, long-term survivors of pediatric cancer and >800 pediatric sickle cell patients. Access to three interconnected Apps on St. Jude Cloud, i.e. Genomics Platform, Pediatric Cancer (PeCan) Knowledgebase and Visualization Community, provides a unique experience for simultaneously performing advanced data analysis and enhancing the knowledgebase for pediatric cancer. Citation Format: Jinghui Zhang. Big pediatric cancer genomic data: Discovery, precision medicine, and data sharing [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr IA-18.