Poster #59 - Taha Mohseni Ahooyi(1)

Integrating Genetic and Clinical Data for Childhood Cancer and Birth Defects

Taha Mohseni Ahooyi(1); Benjamin Stear(1); Dave D. Hill(1); Ryan Corbett(2); J. Alan Simmons(3); Rebecca Kaufman(1); Shiping Zhang(1); Aditya Lahiri(1); Yuanchao Zhang(1); Asif Chinwalla(1); Christopher Nemarich(1); Adam Resnick(1); Sarah Tasian(1,4); Kristina Cole(1); Jonathan Silverstein(3); Elizabeth Goldmuntz(1,4); Jo Lynne Rokita(2); Sharon Diskin(1,4); Deanne M. Taylor(1,4) Affiliations: (1) the Children's Hospital of Philadelphia, (2) The George Washington University, (3) University of Pittsburg, (4) Perelman School of Medicine, University of Pennsylvania

A growing body of evidence indicates a functional link between genes involved in human developmental processes and childhood cancers (CCs). High-throughput omics data, such as whole genome and whole exome sequencing, increasingly emphasize the role of de novo genetic variations in contributing to both structural birth defects (SBDs) and childhood cancers within affected populations. However, identifying these correlations necessitates the collection and simultaneous analysis of large-scale datasets. To address this, we are developing a knowledge graph that integrates hundreds of manually curated ontological and empirical sources related to childhood cancers and specific congenital disorders. This effort builds upon our prior knowledge graph project (Data Distillery KG) as part of a U24 project. The current study presents preliminary findings from an analysis of two datasets prepared for integration: the Kids First congenital heart cohort and the Molecular Targets Project (MTP) childhood cancer cohorts. Our goal is to identify potential intersections in the genetic underpinnings of childhood cancers and congenital heart defects (CHD). Our results reveal that a significant number of genes with pathogenic and de novo mutations are common to both cohorts, a correlation that aligns with clinical evidence. Additionally, the genetic profiles of these de novo-harboring genes in the CHD cohort show substantial overlap with Acute Lymphoblastic Leukemia (ALL), consistent with frequently observed clinical patterns. This initial analysis serves as a proof-of-concept study, demonstrating the potential of the evolving knowledge graph for advancing discovery in the areas of childhood cancers and structural birth defects.