Germline Structural Variant Identification and Functional Determination in Childhood Cancer

儿童癌症的种系结构变异鉴定和功能测定

• 批准号: 10646500
• 负责人: OWEN Robert HIRSCHI
• 金额: $ 4.53万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10646500
• 关键词: Adult; Algorithms; Alveolar Rhabdomyosarcoma; Artificial Intelligence; Bioinformatics; Biological Assay; CRISPR/Cas technology; Cancer Biology; Cancer Patient; Cell Proliferation; Characteristics; Child; Childhood; Childhood Ependymoma; Cohort Studies; DNA biosynthesis; Data; Databases; Detection; Dinoprostone; Embryonal Rhabdomyosarcoma; Engineering; Enhancers; Ependymal Cell; Ependymoma; Event; Exons; Fellowship; Funding; Genetic; Graph; Hereditary Nonpolyposis Colorectal Neoplasms; Heterozygote; Inherited; Interleukin-6; Link; MSH2 gene; Malignant Childhood Neoplasm; Malignant Neoplasms; Malignant neoplasm of pancreas; Methodology; Methods; Neuroglia; Oxidoreductase; Parents; Pathogenicity; Patients; Philadelphia Chromosome; Play; Posterior Fossa; Predisposition; Promoter Regions; Prostaglandins; Proteins; Radial; Recurrence; Reporting; Rhabdomyosarcoma; Role; Running; STAT3 gene; Sensitivity and Specificity; Signal Transduction; Solid; Stat3 Signaling Pathway; Syndrome; Techniques; Testing; Training; Training Activity; Tumor Promoters; United States National Institutes of Health; Up-Regulation; Validation; Variant; Visualization; analysis pipeline; bioinformatics tool; cancer care; cancer predisposition; cancer prevention; cancer risk; cell type; clinical care; cohort; ethnic diversity; exome; exome sequencing; functional gain; genome sequencing; genomic data; improved; leukemia; malignant breast neoplasm; malignant stomach neoplasm; nerve stem cell; novel; participant enrollment; pediatric patients; proband; promoter; racial diversity; stem cells; t(9; 22)(q34; q11); tool; transcriptome; transcriptome sequencing; tumor; variant detection; whole genome

Abstract A few germline pathogenic structural variants (SV) have been identified in cancer predisposition syndromes, e.g., MSH2 inversion in Lynch syndrome. The advent of short-read whole-genome sequencing (WGS) has facilitated the detection of SVs. However, a pitfall of this sequencing methodology is the inability to capture all SVs, given the reads do not map well to low complexity regions, and current algorithms used to identify SVs from short-read data have very low sensitivity and very high false-positive rates. One of the objectives of this fellowship is to optimize and implement an SV calling pipeline that utilizes multiple algorithms to increase the sensitivity and specificity of variant identification from germline short-read WGS trios. This pipeline is currently being developed and tested on pediatric cancer patients enrolled in the NIH-funded Baylor Advancing Sequencing into Childhood Cancer Care (BASIC3) exome study, which consists of ethnically and racially diverse pediatric patients with solid (CNS and non-CNS) tumors. This BASIC3 subset includes 63 proband/parent trios who have subsequently undergone germline short-read WGS. Five SV callers are run and then filtered using either a percent reciprocal overlap filter or a proposed Artificial Intelligence-based proximity graph filter to identify de novo and inherited SVs. This cohort has recently been selected for a long-read sequencing pilot, data which serves as the gold standard for SV detection. Comparison of short-read WGS generated SV calls with the long- read data will help determine the sensitivity and specificity of variant calls and further improve the short read pipeline (Aim 1A). Once optimized this short-read WGS SV pipeline will be applied to the Kids First Genetics of Embryonal and Alveolar Rhabdomyosarcoma cohort (n=900), as an independent assessment of the method and also to identify recurrent germline SVs in this cancer which has not yet been well characterized (Aim 1B). The second training and scientific objective is to explore the functional effect of a novel de novo SV identified through the initial analysis. A de novo germline duplication of the Prostaglandin Reductase 2 (PTGR2) enhancer and promoter region was found in a pediatric Posterior Fossa subtype A (PF–A) ependymoma patient. Transcriptome data from the patient’s tumor revealed increased PTGR2 expression. The PTGR2 protein converts 15-keto- prostaglandin E2 to 15-keto-13,14-dihydro-PGE2. Studies in adult malignancies suggest that increased 15-keto- 13,14-dihydro-PGE2 is associated with cancer risk potentially through the STAT3 signaling pathway. Increased STAT3 signaling is reported as a distinct feature of PF-A ependymoma. The identified partial duplication of PTGR2 will be engineered into ependymoma progenitor cells, to functionally assess the effects on STAT3 signaling, cell proliferation, and DNA synthesis. In parallel, further analysis of PTGR2 expression and structural variants will be analyzed in pediatric ependymoma cohorts (Aim 2). Completion of this experimental plan and described training activities under Drs. Plon and Milosavljevic will provide Owen Hirschi highly interdisciplinary training in analysis of genomic data, structural variation, and the downstream effects on pediatric cancer biology.

抽象的 在癌症易感综合征中已经确定了一些种系致病结构变异（SV）， 例如，林奇综合征中的MSH2反转。短读全基因组测序（WGS）的冒险 促进了SVS的检测。但是，这种测序方法的陷阱是无法捕获所有 SVS，鉴于读取并不能很好地映射到低复杂性区域，并且用于识别SVS的当前算法 短阅读数据的灵敏度非常低，错误阳性率非常高。该奖学金的目标之一 是优化并实施使用多种算法来提高灵敏度的SV调用管道 生殖线短读WGS三重奏的变体识别的特异性。该管道目前正在 对参加NIH资助的贝勒（Baylor）的小儿癌症患者进行了开发和测试 儿童癌症护理（BASIC 3）外部研究，由种族和种族多样的小儿组成 患有固体（CNS和非CNS）肿瘤的患者。此BASIC 3子集包括63个概率/父级三个子集 随后经历了生殖线短读WGS。运行五个SV呼叫者，然后使用任何一个 百分比倒重叠过滤器或提议的基于人工智能的接近图滤波器识别DE Novo并继承了SVS。该队列最近已被选择用于长阅读测序飞行员，数据 用作SV检测的金标准。比较短阅读WGS生成的SV调用与长期的比较 阅读数据将有助于确定变体调用的敏感性和特异性，并进一步改善简短的阅读 管道（AIM 1A）。一旦优化了此简读WGS SV管道，将应用于孩子的第一遗传学 胚胎和肺泡横纹肌肉瘤队列（n = 900），作为该方法的独立评估 还可以鉴定尚未表征尚未表征的癌症中的经常性种系SV（AIM 1B）。 第二培训和科学目标是探索通过 初始分析。前列腺素还原酶2（PTGR2）增强剂的新生系重复 在小儿海报窝亚型A（PF – A）患者中发现启动子区域。转录组 来自患者肿瘤的数据显示PTGR2表达增加。 PTGR2蛋白转换15-酮 Prostaglandin E2至15-Keto-13,14-Dihydro-PGE2。成人恶性肿瘤的研究表明，增加了15酮 13,14-Dihydro-PGE2可能通过STAT3信号通路与癌症风险有关。增加 STAT3信号传导据报道是PF-A感染的独特特征。确定的部分重复 PTGR2将被设计为室内室内祖细胞，以评估对STAT3的影响 信号传导，细胞增殖和DNA合成。同时，PTGR2表达和结构的进一步分析 将在小儿感染同胞中分析变体（AIM 2）。完成这个实验计划和 描述了Drs下的培训活动。 PLON和MILOSAVLJEVIC将为Owen Hirschi提供高度跨学科的 在基因组数据，结构变异和对小儿癌症生物学的下游影响的分析中培训。