Pediatric Cancer Web Portal: From Data to Discovery, Enhancing Pediatric Cancer Research

Khushbu Patel, Division of Oncology and Center for Childhood Cancer Research and Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, PA, USA Komal Rathi, Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, PA, USA Alvin Farrel, Department of Bioinformatics and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, PA, USA Pichai Raman, Department of Bioinformatics and Health Informatics and Center for Data-Driven Discovery in Biomedicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA John M. Maris, Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia and Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA

Poster # 44

Introduction: Next-generation sequencing technologies have enabled significant progress in understanding and treating various cancers. Large-scale genomic datasets from patient tumors and tumor models, such as patient-derived xenografts (PDXs) and cell lines, are now accessible through freely available online web tools and data portals. However, there remains a lack of centralized data portals for pediatric cancers. To address this, we developed a user-friendly Pediatric Cancer Web Portal that houses genomic data from pediatric cancer patients and childhood tumor models, including cell lines and PDXs. Methods and Results: The Pediatric Cancer Web Portal hosts a diverse collection of datasets, including 26 cell lines, 39 patient datasets, 2 mouse-human hybrid time series datasets, 3 PDX datasets covering various cancer histologies, and expression data from normal tissues sourced from GTEx dataset. The patient datasets comprise the multi-tumor TARGET dataset and expression data from common childhood malignant tumors, such as Hepatoblastoma, Retinoblastoma, Medulloblastoma, Hodgkin's lymphoma, and Wilm's tumor, among others. The portal offers users access to publicly available patient and cell line datasets, facilitating the comparison of expression profiles across genomic models and various childhood cancer cohorts from sources like GTEx, TCGA, and TARGET. Users can also determine statistical differences between cohorts, visualize expression using different plot types, and apply log transformation. Additionally, the portal facilitates the correlation of gene expression and comparison of survival probabilities across different patient subtypes or risk strata. Users have the option to download tabular data, processed data used for visualizations, and the visualizations themselves. This evolving tool serves as a valuable resource for pediatric oncologists, empowering them to explore data, develop hypotheses, and gain a profound understanding of expression profiles and underlying mechanisms driving specific pediatric cancers. Conclusion: By providing a user-friendly point and click interface to explore publicly available genomic data in primary tumors and tumor models, Pediatric Cancer Web Portal serves as a valuable tool to discover and evaluate potential targets which may play a role in aggressive childhood cancers.