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Grant Details

Grant Number: 1R03CA272955-01 Interpret this number
Primary Investigator: Lupo, Philip
Organization: Baylor College Of Medicine
Project Title: Deep Phenotyping Children with Congenital Anomalies and Cancer Enrolled in Project:everychild
Fiscal Year: 2022


ABSTRACT One of the strongest risk factors for cancer in children and adolescents is being born with a congenital anomaly— this is true both for chromosomal abnormalities (e.g., Down syndrome) and non-chromosomal birth defects (e.g., non-syndromic congenital heart defects), as validated in our registry linkage study of over 10 million live births. A vital next step in this work is to assemble sufficiently large cohorts of families and children with congenital anomalies and cancer that include: 1) comprehensive phenotypic and clinical information, which can be used to ascertain syndromic characteristics, endophenotypes, and treatment outcomes; and 2) well-annotated biological samples, which can be used for wide-ranging molecular assessments. Without these cohorts and these data, it is difficult to translate findings from registry linkage studies into novel insights concerning disrupted development and cancer predisposition. Furthermore, providing a platform for the integration of these data will increase the power for detecting the pathways underlying congenital anomalies and cancer. Two important resources for addressing these gaps are: 1) Project:EveryChild (PEC); and 2) the Gabriella Miller Kids First Pediatric Data Resource Center (KF-DRC). PEC is the Children’s Oncology Group (COG) registry, eligibility screening, biology, and outcome study (APEC14B1) that has been open since 2015 and currently includes >25,000 children. The DRC is the platform for the Kids First program in terms of aggregation of curated genomic and phenotypic data from structural birth defects and childhood cancer cohorts, as well as a central portal where these data and analysis tools are accessible to the research community. The objective of this application is to deeply characterize the phenotypes of children with congenital anomalies and cancer enrolled in COG PEC and integrate these data in the KF-DRC. Our hypothesis is that the processes and informatic framework we develop will strengthen future Kids First datasets and their impact by providing an implementation template for obtaining curated phenotypic data from PEC to combine with genomic data being generated in COG as part of Kids First and the Childhood Cancer Data Initiative (CCDI). We are uniquely poised to lead this effort with deep experience in both PEC and the DRC. To meet our objective, we propose the following aims: 1) Collect extensive phenotypic and clinical data from children with congenital anomalies and cancer enrolled in Project:EveryChild; and 2) Integrate phenotypic and clinical data from Project:EveryChild into the Gabriella Miller Kids First Pediatric Data Resource Center. This study will generate a robust resource for Kids First by providing deep phenotypic data on children with congenital anomalies and cancer, as well as serving as a scalable template for obtaining and curating phenotypic data for cohorts of children in COG undergoing comprehensive molecular profiling as part of Kids First and the CCDI. Finally, this work may ultimately inform novel strategies for cancer screening, counseling, and treatment for at-risk children.



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