Discovery of Somatic Noncoding Variants that Serve as Drivers in Pediatric Cancers

发现作为儿科癌症驱动因素的体细胞非编码变异

• 批准号: 10402281
• 负责人: Jinghui Zhang
• 金额: $ 55.28万
• 依托单位: ST. JUDE CHILDREN'S RESEARCH HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-06-01 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10402281
• 关键词: 3-Dimensional; Acute T Cell Leukemia; Alleles; Binding Sites; Bioinformatics; Biological Assay; CRISPR/Cas technology; Cancer Etiology; Cancer Patient; Cancer cell line; Cell Line; ChIP-seq; Childhood; Chromatin; Chromatin Structure; Classification; Clinical; Clinical Management; Code; Communities; Computing Methodologies; DNA Sequence Alteration; Data; Data Set; Databases; Development; Enhancers; Epigenetic Process; Evaluation; Gene Expression; Gene Expression Regulation; Genes; Genome; Genomics; Goals; Investigation; Knowledge; Laboratories; Lesion; Maintenance; Malignant Childhood Neoplasm; Malignant Neoplasms; Measures; Molecular; Mutation; Mutation Analysis; Nucleic Acid Regulatory Sequences; Nucleotides; Oncogenes; Oncogenic; Online Systems; Pathogenesis; Pathogenicity; Patients; Phenotype; Pilot Projects; Primary Neoplasm; Recurrence; Regulation; Regulatory Element; Reporter; Research; Research Personnel; Resources; Role; Sampling; Somatic Mutation; Statistical Data Interpretation; Systems Biology; TAL1 gene; Triplet Multiple Birth; Untranslated RNA; Variant; Visualization; Visualization software; Work; assay development; base; cancer genome; cohort; computer framework; design; driver mutation; epigenetic profiling; epigenome; epigenomics; established cell line; experimental study; genome editing; genome sequencing; genome-wide; innovation; insertion/deletion mutation; insight; melanoma; mutant; non-oncogenic; novel; patient derived xenograft model; precision medicine; predictive modeling; programs; promoter; screening; tool; transcription factor; transcriptome; transcriptome sequencing; tumor; tumorigenesis; user-friendly; web portal; whole genome

PROJECT SUMMARY / ABSTRACT Mapping of cis-regulatory elements by ENCODE and Roadmap Epigenomics has led to increased recognition of the importance of non-coding regulatory regions, as the target for next great discovery of important somatic variants in childhood cancers. Recent discoveries of somatic non-coding mutations that cause oncogenic activation of TERT in melanoma and TAL1 in pediatric T-ALL support this idea, and have inspired genome-wide investigations of non-coding somatic mutations in cancer. However, the noncoding genome is vast and largely uncharted and it has proven difficult to distinguish the “oncogenic drivers” from the “passengers” among the many non-coding sequence variants. By combining our computational expertise in genomic analysis with the experimental expertise of our co-investigators Drs. Thomas Look and Suzanne Baker in molecular oncogenesis and Dr. Chunliang Li in novel assay development, we aim to discover new somatic non-coding variants that serve as drivers of pediatric cancer. This effort capitalizes on the strength of our work to-date on the pediatric cancer genome landscape, including non-coding regions, and the richness of our unique resource of “omics” results from existing whole genome sequencing (WGS) and RNA-seq of >2,000 paired tumor/normal childhood cancer samples. Through a pilot study of 33 T-lineage acute lymphoblastic leukemia, we demonstrate that by an integrative approach we are able to successfully distinguish “driver-mutations” from “passengers” and discover novel variants in the non-coding genomes of childhood cancers. In Aim 1, we will discover somatic alterations in non-coding regions that are associated with aberrant, allele-specific expression by analyzing WGS and RNA- seq data from 2,000 patient samples and from established cancer cell lines. We will focus on sequence alterations that form locus-specific transcription factor binding sites and employ a massively parallel reporter assay to measure the enhancer activity of the candidate non-coding mutations. In Aim 2, we will develop a computational framework for predicting non-coding variant pathogenicity based on statistical analysis of patient data and mechanism studies underlying regulatory non-coding variants unveiled by laboratory investigation. We will discover abnormal enhancer-promoter interactions in pediatric cancer patient derived xenograft (PDX) models or cell lines using 3-D chromatin assays such as Capture-C. We will use ChIP-seq and RNA-seq to analyze the functional consequences of non-coding variants in PDXs or cancer cell lines. In parallel we will use CRISPR-Cas9 genome editing tools to modify or alter the mutant allele to further explore the regulation mechanisms. In Aim 3, we will develop a web-based and user-friendly visualization tool to accelerate discovery of non-coding driver mutations by making the non-coding variants discovered in our study publicly accessible with an integrated genome-wide view of “omics” datasets for use by the research community. The discovery of non-coding somatic “driver” mutations in childhood cancers as a result of this collaborative effort will lead to major advances in our understanding of the molecular pathogenesis of childhood cancers and our computational predictive model will provide new insight into implementation of individualized “precision medicine”.

项目摘要/摘要 通过ENCODE和路线图表观基因组学绘制顺式调控元件图导致对 非编码调控区的重要性，作为重要体细胞下一次重大发现的目标 儿童癌症的变异。导致致癌的体细胞非编码突变的最新发现 黑色素瘤中TERT的激活和儿科T-T中的TAL1都支持这一想法，并激励了全基因组 癌症中非编码体细胞突变的研究。然而，非编码基因组是巨大的，在很大程度上 未知的，事实证明很难区分致癌司机和乘客之间的 许多非编码序列变体。通过将我们在基因组分析方面的计算专业知识与 我们的合作研究员Thomas Look博士和Suzanne Baker博士在分子肿瘤发生方面的实验专长 和李春亮博士在新的分析开发中，我们的目标是发现新的体细胞非编码变体 作为儿童癌症的驱动者。这一努力充分利用了我们迄今在儿科癌症方面所做的工作。 基因组图景，包括非编码区，以及我们独特的“组学”结果资源的丰富性 从现有的2,000对肿瘤/正常儿童癌症的全基因组测序(WGS)和RNA序列 样本。通过对33例T细胞急性淋巴细胞性白血病的初步研究，我们通过一种 综合方法我们能够成功地区分司机突变和乘客突变，并发现 儿童癌症非编码基因组中的新变种。在目标1中，我们将发现躯体的变化 在与异常的、等位基因特异性表达相关的非编码区，通过分析WGS和RNA- 来自2000名患者样本和已建立的癌细胞系的SEQ数据。我们将重点关注序列 形成位点特异性转录因子结合位点并使用大量平行报告的改变 检测候选非编码突变的增强子活性。在目标2中，我们将制定一个 基于患者统计分析的非编码变异致病性预测计算框架 实验室调查揭示了潜在的调控非编码变体的数据和机制研究。我们 将在儿童癌症患者来源的异种移植(PDX)中发现异常的增强子-启动子相互作用 使用三维染色质分析(如Capture-C)的模型或细胞系。我们将使用CHIP-SEQ和RNA-SEQ来 分析非编码变异体在PDX或癌细胞系中的功能后果。同时，我们将使用 CRISPR-Cas9基因组编辑工具可以修改或改变突变的等位基因，以进一步探索调控 机制。在目标3中，我们将开发一个基于Web的、用户友好的可视化工具来加速发现 通过公开我们研究中发现的非编码变体来了解非编码驱动程序突变 以一个完整的全基因组观点的“组学”数据集，供研究界使用。发现了 作为这一合作努力的结果，儿童癌症中的非编码体“驱动”突变将导致 我们对儿童癌症分子发病机制理解的主要进展和我们的计算 预测模型将为个性化精准医疗的实施提供新的视角。

项目成果

Decoding tumor microenvironments through artificial tumor transcriptomes.

• DOI: 10.1016/j.ccell.2022.07.008
• 发表时间: 2022-08-08
• 期刊: CANCER CELL
• 影响因子: 50.3
• 作者: Tian, Liqing;Zhang, Jinghui
• 通讯作者: Zhang, Jinghui

Opposing effects of KDM6A and JDP2 on glucocorticoid sensitivity in T-ALL.

• DOI: 10.1182/bloodadvances.2021006881
• 发表时间: 2023-07-25
• 期刊: BLOOD ADVANCES
• 影响因子: 7.5
• 作者: Levinson, Anya L.;Tjoa, Karensa;Huang, Benjamin;Meyer, Lauren K.;Kim, Mi-Ok;Brady, Samuel W.;Zhang, Jinghui;Shannon, Kevin;Wandler, Anica M.
• 通讯作者: Wandler, Anica M.

St. Jude Cloud: A Pediatric Cancer Genomic Data-Sharing Ecosystem.

• DOI: 10.1158/2159-8290.cd-20-1230
• 发表时间: 2021-05
• 期刊: Cancer discovery
• 影响因子: 28.2
• 作者: McLeod C;Gout AM;Zhou X;Thrasher A;Rahbarinia D;Brady SW;Macias M;Birch K;Finkelstein D;Sunny J;Mudunuri R;Orr BA;Treadway M;Davidson B;Ard TK;Chiao A;Swistak A;Wiggins S;Foy S;Wang J;Sioson E;Wang S;Michael JR;Liu Y;Ma X;Patel A;Edmonson MN;Wilkinson MR;Frantz AM;Chang TC;Tian L;Lei S;Islam SMA;Meyer C;Thangaraj N;Tater P;Kandali V;Ma S;Nguyen T;Serang O;McGuire I;Robison N;Gentry D;Tang X;Palmer LE;Wu G;Suh E;Tanner L;McMurry J;Lear M;Pappo AS;Wang Z;Wilson CL;Cheng Y;Meshinchi S;Alexandrov LB;Weiss MJ;Armstrong GT;Robison LL;Yasui Y;Nichols KE;Ellison DW;Bangur C;Mullighan CG;Baker SJ;Dyer MA;Miller G;Newman S;Rusch M;Daly R;Perry K;Downing JR;Zhang J
• 通讯作者: Zhang J