Genomic Approaches to Defining Inherited Basis of Childhood Cancer

定义儿童癌症遗传基础的基因组方法

• 批准号: 8292210
• 负责人: Sharon E. Plon
• 金额: $ 43.37万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-01 至 2015-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8292210
• 关键词: Adult; Affect; Age; Alleles; Bioinformatics; Cancer Detection; Cancer Etiology; Cancer Family; Cancer Patient; Cancer-Predisposing Gene; Candidate Disease Gene; Cell Line; Child; Childhood; Clinical; Code; Constitutional; Copy Number Polymorphism; DNA; DNA Resequencing; DNA Sequence Rearrangement; Data; Deletion Mutation; Developmental Delay Disorders; Enrollment; Evaluation; Evolution; Exons; Family; Family history of; Family member; Gene Deletion; General Population; Generations; Genes; Genetic Predisposition to Disease; Genetic Programming; Genome; Genomics; Goals; Health Sciences; Human Genome; Inherited; Knowledge; Libraries; Malignant Childhood Neoplasm; Malignant Neoplasms; Medical; Medicine; Methodology; Missense Mutation; Modeling; Molecular; Mutation; National Cancer Institute; Oncogenes; Patients; Pattern; Pediatric Hospitals; Phenotype; Philadelphia; Population Heterogeneity; Predisposition; Prevention approach; Probability; RNA Splicing; Rice; Risk; Sampling; Second Primary Neoplasms; Sequence Analysis; Site; Somatic Mutation; Specimen; Statistical Methods; Strategic Planning; Syndrome; Technology; Texas; Tumor Suppressor Genes; Tumor Tissue; Universities; University of Texas M D Anderson Cancer Center; Variant; base; cancer genetics; cancer risk; clinical application; clinically relevant; cohort; exome; genome sequencing; genome wide association study; immortalized cell; improved; insight; next generation; novel; proband; sarcoma; statistics; therapeutic target; tumor

Identification of mutations in specific genes responsible for cancer susceptibility impacts decisions about treatment of the patient as well as allowing increased surveillance and prevention approaches for at-risk family members. In addition, knowledge of inherited predisposition to pediatric malignancies has provided important insights into the mechanisms of cancer and potential therapeutic targets in both children and adults with cancer in the general population. Current utilization of high-throughput sequencing methodologies for coding changes has been focused on somatic mutations in tumor tissue, and conversely; genome-wide association studies of cancer susceptibility have focused on common variations that individually have small impacts on cancer risk. We propose a project at the intersection of these two different approaches. We plan to use massively parallel sequence analyses of constitutional DNA from childhood cancer patients with medical and family history suggestive of a cancer susceptibility syndrome. In Aim 1 we will focus on cohorts of families with consistent and specific phenotypes, for example, probands with childhood sarcomas and second malignancies by age 40 where thorough analysis of well-characterized cancer-associated genes has been negative. The molecular analyses of germline DNA will include two comprehensive approaches (1) capture of all coding exons followed by sequencing at dense coverage to identify mutations pathogenic mutations (deletion, nonsense, frameshift or splice site) that impact coding sequence (whole exome) and (2) whole genome sequencing of paired-ends libraries at lower coverage to identify copy number changes and novel rearrangements. In Aim 2, we will carry out informative statistical and bioinformatics analysis of rare or novel missense alleles, using original methodology involving optimization of alignment depths for evolution-based studies of functionality. In Aim 3, analyses of copy number change and rearrangement by whole genome sequencing will include an additional cohort of subjects with childhood cancer and congenital anomalies or developmental delay to uncover novel contiguous gene or rearrangement syndromes. Results from these initial cohorts will then be validated by targeted sequencing of implicated genes in additional childhood cancer probands and families. To complete this translational, cross-disciplinary project we include collaborators from pediatric cancer genetics programs at Texas Children's Hospital, University of Texas MD Anderson Cancer Center and Health Science Center at San Antonio and the Children's Hospital of Philadelphia, the Human Genome Sequencing Center and the Department of Statistics at Rice University. The clinical centers enroll families from ethnically diverse populations with linkage to medical data, and establishment of immortalized cell lines to facilitate the generation of functionally and clinically relevant data. Our plan to thoroughly interrogate the constitutional genome will advance the goals of the National Cancer Institute's Strategic Plan on gaining a fuller understanding of the spectrum of genetic susceptibility to cancer in highly affected childhood cancer families. 1

鉴定负责癌症易感性的特定基因中突变会影响有关的决策 对患者的治疗以及允许增加的监视和预防方法 成员。此外，对儿科恶性肿瘤的遗传易感性的了解提供了重要的 洞悉儿童和成人癌症的癌症机制和潜在的治疗靶标 在一般人群中。当前利用高通量测序方法用于编码更改 相反，已经专注于肿瘤组织中的体细胞突变。全基因组关联研究 癌症的敏感性集中在对癌症风险影响很小的较小影响的常见变异上。 我们在这两种不同方法的交集中提出了一个项目。我们计划使用大规模平行 儿童癌症患者的宪法DNA的序列分析 提示癌症易感性综合征。在目标1中，我们将专注于一致的家庭 和特定的表型，例如，童年肉瘤和第二次恶性肿瘤的概率40岁 在彻底分析良好的癌症相关基因的情况下是阴性的。分子 种系DNA的分析将包括两种综合方法（1）捕获所有编码外显子遵循 通过在密集覆盖范围内进行测序以鉴定突变致病突变（删除，废话，移架或 剪接站点）影响编码顺序（整个外显子组）和（2）配对末端的整个基因组测序 较低覆盖范围的库，以识别副本数字更改和新的重排。在AIM 2中，我们将携带 使用原始 涉及优化对齐深度的方法，用于基于进化的功能研究。在AIM 3中， 通过整个基因组测序对拷贝数变化和重排的分析将包括一个额外 患有儿童癌症和先天性异常或发育迟缓的受试者队列以发现新颖 连续基因或重排综合征。然后，这些初始人群的结果将通过 在其他儿童癌症概率和家庭中对涉及基因的靶向测序。 为了完成这个翻译的跨学科项目，我们包括小儿癌的合作者 德克萨斯儿童医院，德克萨斯大学医学博士安德森癌症中心与健康的遗传学计划 圣安东尼奥的科学中心和费城儿童医院，人类基因组测序 赖斯大学中心和统计系。临床中心从种族 与医学数据联系的不同种群，并建立了永生的细胞系以促进 生成功能和临床相关数据。我们彻底审问宪法的计划 基因组将促进国家癌症研究所的战略计划的目标，以获得更丰富的 了解高受影响的儿童癌症家庭中遗传易感性的频谱。 1

项目成果

Unifying cancer genetics.

• DOI: 10.1097/gim.0b013e31820d5e87
• 发表时间: 2011-03
• 期刊: Genetics in medicine : official journal of the American College of Medical Genetics
• 作者: Plon SE

Framework for microRNA variant annotation and prioritization using human population and disease datasets.

• DOI: 10.1002/humu.23668
• 发表时间: 2019-01
• 期刊: Human mutation
• 影响因子: 3.9
• 作者: Oak N;Ghosh R;Huang KL;Wheeler DA;Ding L;Plon SE
• 通讯作者: Plon SE