(PQ3) A functional genomic approach to identification and interpretation of germline-tumor genetic interactions

(PQ3) 识别和解释种系-肿瘤遗传相互作用的功能基因组方法

• 批准号: 10402412
• 负责人: ALEXANDER GUSEV
• 金额: $ 69.99万
• 依托单位: DANA-FARBER CANCER INST
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-06-08 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10402412
• 关键词: Affect; CRISPR interference; Cancer Etiology; Cancer Intervention; Cancer Patient; Cell Line; Cell Proliferation; Chromatin; Clinical; Clinical Data; Clinical assessments; Computing Methodologies; Data; Data Analyses; Data Collection; Data Set; Databases; Development; Discipline; Distal; Drug Targeting; Enrollment; Ensure; Epidemiologist; Evaluation; Event; Evolution; Gene Mutation; Genes; Genetic; Genetic Transcription; Genetic Variation; Genome; Genomic approach; Genomics; Genotype; Goals; Human; Immune; Individual; Inherited; Intervention; Knowledge; Lead; Life; Malignant Neoplasms; Mediation; Medical; Medical Records; Medical Research; Methods; Methylation; Modeling; Mutation; Normal tissue morphology; Outcome; Patient risk; Patients; Phenotype; Population; Quantitative Trait Loci; RNA Splicing; Recurrence; Regulator Genes; Regulatory Pathway; Research; Research Personnel; Risk; Risk Assessment; Risk Factors; Savings; Scientist; Software Tools; Somatic Mutation; Statistical Methods; The Cancer Genome Atlas; Tissues; Transcript; Treatment outcome; Tumor Tissue; Untranslated RNA; Validation; Variant; Work; algorithm development; anticancer research; cancer genetics; cancer risk; case control; causal variant; clinical phenotype; clinically relevant; cohort; computerized tools; driver mutation; empowered; exome; follow-up; functional genomics; gene network; genetic risk factor; genome wide association study; genome-wide; genomic locus; high throughput screening; improved; innovation; insight; novel; novel drug class; precision medicine; programs; research study; risk variant; transcriptome sequencing; treatment response; tumor; tumor exome; tumor growth; tumor progression

PROJECT SUMMARY/ABSTRACT Studies of germline genetic variation in cancer cases and controls as well as studies of somatic mutation have transformed our understanding of cancer etiology and lead to the development of life saving cancer interventions. However, even though tumor progression, evolution, and treatment response are influenced by both somatic and germline variation, these data have largely been examined in isolation. In this work, we propose to integrate extensive data collection, novel statistical methods, and cutting-edge functional validation to discover and characterize somatic-germline interactions in a pan-cancer study. Results from our work will significantly benefit both cancer researcher and multiple medical research discipline more broadly. Within the cancer genetics field, identifying somatic-germline interactions will help (i) identify new classes of drugs targets causally upstream of those identified through somatic driver mutations, (ii) precisely treat patients by selecting interventions the basis of germline and somatic genetics as well as tumor RNA- sequencing, (iii) improve risk profiling, especially for tumor recurrence and outcomes, and (iv) develop hypotheses of the germline risk variants mechanism, especially for non-coding variants. To accomplish these goals, we will leverage tumor sequencing from the DFCI Profile Project together with recent innovations in variant imputation to assemble the largest (N>25,000) pan-cancer germline-somatic cohort to date. We will develop novel statistical and computational methods to maximize the value of these data. Because over 90% of germline genetic variation associated with cancer risk and outcomes is in non- coding regions of the genome we especially focus on integration of functional genomic sequencing from both tumor and normal tissues. Our methods will be capable of modelling proximal germline-somatic interactions as well as distal effects of germline variation on trans and global somatic changes. Furthermore, by focusing largely on RNA-sequencing we investigate a gene-centric model that provides specific hypotheses for mechanism that are readily validated via our experimental follow-up of non-coding variation that is otherwise difficult to interpret.

项目总结/摘要 对癌症病例和对照的生殖系遗传变异的研究以及对体细胞突变的研究， 改变了我们对癌症病因学的理解，并导致拯救生命的癌症的发展 干预措施。然而，即使肿瘤进展、演变和治疗反应受到以下因素的影响， 无论是体细胞变异还是生殖系变异，这些数据大部分都是孤立地研究的。本工作 建议整合广泛的数据收集，新颖的统计方法和尖端的功能 验证以发现和表征泛癌症研究中的体细胞-生殖系相互作用。结果 从我们的工作将大大有利于癌症研究人员和多个医学研究学科更多 大致上在癌症遗传学领域，识别体细胞-生殖系相互作用将有助于（i）识别新的 一类药物靶向那些通过体细胞驱动突变鉴定的上游的因果关系，（ii）精确地 通过选择生殖系和体细胞遗传学以及肿瘤RNA的基础上的干预措施来治疗患者， 测序，（iii）改善风险分析，特别是对于肿瘤复发和结果，以及（iv）开发 生殖系风险变异机制的假设，特别是非编码变异。 为了实现这些目标，我们将利用DFCI Profile项目的肿瘤测序， 最近在变异插补方面的创新，以组装最大的（N> 25，000）泛癌症生殖系-体细胞 到目前为止的crowd。我们将开发新颖的统计和计算方法，以最大限度地发挥其价值 数据因为超过90%的与癌症风险和结果相关的生殖系遗传变异是在非- 我们特别关注基因组的功能性基因组测序的整合， 肿瘤和正常组织。我们的方法将能够模拟近端种系-体细胞相互作用， 以及生殖系变异对跨体和整体体细胞变化的远端效应。此外，通过聚焦 主要是在RNA测序，我们研究了一个基因为中心的模型，提供了具体的假设， 通过我们对非编码变异的实验跟踪， 否则很难解释。

项目成果

Ancestry-associated transcriptomic profiles of breast cancer in patients of African, Arab, and European ancestry.

• DOI: 10.1038/s41523-021-00215-x
• 发表时间: 2021-02-08
• 期刊: NPJ breast cancer
• 影响因子: 5.9
• 作者: Roelands J;Mall R;Almeer H;Thomas R;Mohamed MG;Bedri S;Al-Bader SB;Junejo K;Ziv E;Sayaman RW;Kuppen PJK;Bedognetti D;Hendrickx W;Decock J
• 通讯作者: Decock J

A biallelic multiple nucleotide length polymorphism explains functional causality at 5p15.33 prostate cancer risk locus.

• DOI: 10.1038/s41467-023-40616-z
• 发表时间: 2023-08-23
• 期刊: NATURE COMMUNICATIONS
• 影响因子: 16.6
• 作者: Spisak, Sandor;Tisza, Viktoria;Nuzzo, Pier Vitale;Seo, Ji-Heui;Pataki, Balint;Ribli, Dezso;Sztupinszki, Zsofia;Bell, Connor;Rohanizadegan, Mersedeh;Stillman, David R.;Alaiwi, Sarah Abou;Bartels, Alan B.;Papp, Marton;Shetty, Anamay;Abbasi, Forough;Lin, Xianzhi;Lawrenson, Kate;Gayther, Simon A.;Pomerantz, Mark;Baca, Sylvan;Solymosi, Norbert;Csabai, Istvan;Szallasi, Zoltan;Gusev, Alexander;Freedman, Matthew L.
• 通讯作者: Freedman, Matthew L.

Genetic Ancestry Contributes to Somatic Mutations in Lung Cancers from Admixed Latin American Populations.

• DOI: 10.1158/2159-8290.cd-20-1165
• 发表时间: 2021-03
• 期刊: Cancer discovery
• 影响因子: 28.2
• 作者: Carrot-Zhang J;Soca-Chafre G;Patterson N;Thorner AR;Nag A;Watson J;Genovese G;Rodriguez J;Gelbard MK;Corrales-Rodriguez L;Mitsuishi Y;Ha G;Campbell JD;Oxnard GR;Arrieta O;Cardona AF;Gusev A;Meyerson M
• 通讯作者: Meyerson M