SUMMARY Accelerating cures for children with cancer remains an immediate challenge as a result of extensive oncogenic heterogeneity between and within histologies, distinct molecular mechanisms evolving between diagnosis and relapsed disease, and limited therapeutic options. To systematically prioritize and rationally test novel agents in preclinical murine models, researchers within the Pediatric Preclinical Testing Consortium are continuously developing patient-derived xenografts (PDXs)—many of which are refractory to current standard-of-care treatments—from high-risk childhood cancers. Here, we genomically characterize 261 PDX models from 37 unique pediatric cancers; demonstrate faithful recapitulation of histologies and subtypes; and refine our understanding of relapsed disease. In addition, we use expression signatures to classify tumors for TP53 and NF1 pathway inactivation. We anticipate that these data will serve as a resource for pediatric oncology drug development and will guide rational clinical trial design for children with cancer.

Neuroblastoma is a cancer of the developing sympathetic nervous system. It is diagnosed in 600-700 children per year in the United States and accounts for 12% of pediatric cancer deaths. Despite recent advances in our understanding of this malignancy's complex genetic architecture, the contribution of rare germline variants remains undefined. Here, we conducted a genome-wide analysis of large (>500 kb), rare (<1%) germline copy number variants (CNVs) in two independent, multi-ethnic cohorts totaling 5,585 children with neuroblastoma and 23,505 cancer-free control children. We identified a 550-kb deletion on chromosome 16p11.2 significantly enriched in neuroblastoma cases (0.39% of cases and 0.03% of controls; p ¼ 3.34 3 10 À9 ). Notably, this CNV corresponds to a known microdeletion syndrome that affects approximately one in 3,000 children and confers risk for diverse developmental phenotypes including autism spectrum disorder and other neurodevelopmental disorders. The CNV had a substantial impact on neuroblastoma risk, with an odds ratio of 13.9 (95% confidence interval ¼ 5.8-33.4). The association remained significant when we restricted our analysis to individuals of European ancestry in order to mitigate potential confounding by population stratification (0.42% of cases and 0.03% of controls; p ¼ 4.10 3 10 À8 ). We used whole-genome sequencing (WGS) to validate the deletion in paired germline and tumor DNA from 12 cases. Finally, WGS of four parent-child trios revealed that the deletion primarily arose de novo without maternal or paternal bias. This finding expands the clinical phenotypes associated with 16p11.2 microdeletion syndrome to include cancer, and it suggests that disruption of the 16p11.2 region may dysregulate neurodevelopmental pathways that influence both neurological phenotypes and neuroblastoma.

Motivation Despite widespread prevalence of somatic structural variations (SV) across most tumor types, understanding of their molecular implications often remains poor. SVs are extremely heterogeneous in size and complexity, hindering the interpretation of their pathogenic role. Tools integrating large SV datasets across platforms are required to fully characterize the cancer’s somatic landscape. Results svpluscnv R package is a swiss army knife for the integration and interpretation of orthogonal datasets including copy number variant (CNV) segmentation profiles and sequencing-based structural variant calls (SVC). The package implements analysis and visualization tools to evaluate chromosomal instability and ploidy, identify genes harboring recurrent SVs and detects complex rearrangements such as chromothripsis and chromoplexia. Further, it allows systematic identification of hot-spot shattered genomic regions, showing reproducibility across alternative detection methods and datasets. Availability https://github.com/ccbiolab/svpluscnv Supplementary information Supplementary data are available at Bioinformatics online.