Integrating Epidemiologic and Genomic Data to Elucidate the Genetic Overlap Between Congenital Anomalies and Pediatric Cancer

摘要 在美国，癌症仍然是20岁以下人群因疾病死亡的主要原因，而且 大约80%的幸存者在45岁之前至少有一种慢性健康状况。之一 儿童和青少年患癌症的最大风险因素是先天性畸形-这是 对于染色体异常（例如，唐氏综合征）和非染色体出生缺陷（例如，非 综合征性先天性心脏缺陷），正如我们最近在超过1000万例肝移植患者的登记关联研究中所证实的那样 出生通过将四个州基于人口的出生缺陷和癌症登记数据联系起来， 儿童异常和癌症之间的遗传重叠（GOBACK）研究，我们发现了多种新的 不属于已知癌症易感综合征的先天性异常-癌症关联，包括 后鼻孔闭锁-急性白血病（HR = 9.2，95%CI：3.8 - 22.1）和CHD-神经母细胞瘤（HR = 3.4，95%CI：2.6 - 4.5）。 此外，与我们的流行病学研究结果一致，我们的基因组评估导致了 以多种先天性异常为特征白血病易感性疾病的鉴定 （包括后鼻孔闭锁）和USP9X中的致病性种系变异。在本申请中，我们建议 扩展我们的综合流行病学和基因组学方法，以解决我们的中心假设， 多效性遗传变异产生特定的先天性异常-儿科癌症（CA-PC）模式 每种共存表型的风险增加。我们的总体目标是阐明 通过利用和整合现有数据集， 包括1）Gabriella米勒儿童第一儿科研究计划，44例先天性畸形， 儿科癌症队列，代表20，000名患者和48，000个基因组; 2）All of Us研究 使用超过90，000人的WGS数据进行编程;以及3）GOBACK登记连锁出生队列， 包括基于人口的超过2 500万例活产数据。在目标1中，我们将分析扩大的人口- 基于> 2500万儿童的队列，以确定新的CA-PC模式并确认先前报告的模式。 在目标2中，我们将分析2，000名患有这两种疾病的儿童的种系全基因组测序（WGS）数据 先天性异常和儿科癌症，以及超过20，000名患有先天性异常或 儿科癌症，以确定新的多效性基因，携带罕见的致病性变异，负责特定的 CA-PC模式。在目标3中，我们将描述导致儿童癌症的体细胞改变的情况， 通过分析2000例肿瘤正常WGS和RNA-Seq数据， 孩子这项工作将产生对癌症易感性的新见解，并随后导致改善 照顾有先天性异常的儿童，在美国每年有120，000名新生儿。在 此外，对高危人群中癌症发展的了解可以提供临床实用性（例如，遗传 咨询或治疗目标）的儿童和成人癌症的一般人群。

ABSTRACT In the United States, cancer remains the leading cause of death by disease in those <20 years of age, and approximately 80% of survivors have at least one chronic health condition by 45 years of age. 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 recently validated in our registry linkage study of over 10 million live births. By linking data from population-based birth defects and cancer registries in four states included in the Genetic Overlap Between Anomalies and Cancer in Kids (GOBACK) Study, we identified multiple novel congenital anomaly-cancer associations that are not part of known cancer predisposition syndromes, including choanal atresia-acute leukemia (HR=9.2, 95% CI: 3.8-22.1) and CHD-neuroblastoma (HR=3.4, 95%: 2.6-4.5). Furthermore, consistent with our epidemiologic findings, our genomic assessments have led to the identification of a novel leukemia predisposition disorder characterized by multiple congenital anomalies (including choanal atresia) and pathogenic germline variants in USP9X. In this application, we propose to expand our integrated epidemiologic and genomic approach to address our central hypothesis that pleiotropic genetic variation generates specific congenital anomaly-pediatric cancer (CA-PC) patterns with increased risk conferred to each co-occurring phenotype. Our overall objective is to elucidate the overlap between congenital anomalies and pediatric cancer by leveraging and integrating existing datasets, including 1) the Gabriella Miller Kids First Pediatric Research Program with 44 congenital anomaly and pediatric cancer cohorts, representing 20,000 patients and 48,000 genomes; 2) the All of Us Research Program with WGS data on >90,000 individuals; and 3) the GOBACK Registry Linkage Birth Cohort, which includes population-based data on >25 million live births. In Aim 1, we will analyze an expanded population- based cohort of >25 million children to identify new CA-PC patterns and confirm previously reported patterns. In Aim 2, we will analyze germline whole-genome sequencing (WGS) data from 2,000 children with both congenital anomalies and pediatric cancer and over 20,000 children with either congenital anomalies or pediatric cancer to identify novel pleiotropic genes harboring rare, pathogenic variants responsible for specific CA-PC patterns. In Aim 3, we will describe the landscape of somatic alterations in pediatric cancers that result from pathogenic CA-PC variants through the analysis of tumor-normal WGS and RNA-Seq data in 2,000 children. This work will generate novel insights into cancer predisposition and subsequently lead to improved care for children with congenital anomalies, who comprise 120,000 births every year in the United States. In addition, insights into cancer development among at-risk populations could provide clinical utility (e.g., genetic counseling or therapeutic targets) for children and adults with cancer in the general population.