Integrative Somatic and Germline Computational Biology to Redefine Clinical Actionability in Solid Tumors

综合体细胞和种系计算生物学重新定义实体瘤的临床可操作性

• 批准号: 10396664
• 负责人: Eliezer M Van Allen
• 金额: $ 40.72万
• 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: 2018-06-01 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10396664
• 关键词: Address; Algorithms; Alternative Splicing; Area; Automobile Driving; Award; Cancer Center; Cancer Etiology; Cancer Patient; Clinical; Clinical Oncology; Communities; Complex; Computational Biology; Computational algorithm; Computing Methodologies; DNA Repair; DNA Repair Gene; Dana-Farber Cancer Institute; Data; Decision Making; Defect; Development; Diagnostic; Dissection; Etiology; Event; Evolution; Genes; Genetic; Genetic Polymorphism; Genetic Transcription; Genome; Genomics; Germ-Line Mutation; Goals; Immune; Immune signaling; Immunotherapy; Infrastructure; Inherited; Institutes; Interdisciplinary Study; International; Investigation; Malignant Neoplasms; Malignant neoplasm of urinary bladder; Mediating; Medical; Modality; Modeling; Molecular; Molecular Profiling; Mutation; Oncology; Pathogenicity; Pathway interactions; Patient Care; Patient risk; Patients; Pattern; Platinum; Process; Prognostic Marker; Research; Resources; Risk; Risk Assessment; Role; Sampling; Shapes; Signal Pathway; Solid Neoplasm; Somatic Mutation; Splice-Site Mutation; Therapeutic; Translating; Tumor Biology; Variant; Work; advanced prostate cancer; base; cancer genomics; cancer initiation; cancer risk; cancer therapy; cancer type; checkpoint therapy; chemotherapy; clinical development; clinical predictors; clinical risk; clinically actionable; clinically relevant; cohort; diagnostic biomarker; exome; experimental study; genomic profiles; immune checkpoint blockade; innovation; loss of function; molecular marker; novel; oncology program; phenotypic data; point of care; precision oncology; predictive marker; prognostic; programs; response; transcriptome; treatment response; tumor; tumor-immune system interactions

PROJECT SUMMARY The increased accessibility of comprehensive molecular characterization of tumors and germline samples from cancer patients has accelerated translational discoveries and significantly impacted patient care. These approaches ultimately form the basis for precision cancer medicine, whereby “clinically actionable” molecular data about a patient's tumor and germline genomic profile, specifically defined as diagnostic, prognostic, and predictive markers, are used at the point of care to guide treatment decision-making. While these strategies have been successful in certain use cases, the approaches to understand somatic and germline components of cancer patients are typically considered independently, and systematic characterization of the interaction between the somatic and germline genomes in the context of diagnostic and predictive clinical relevance have not yet been systematically performed across large cohorts of patients. This is in part the result of an absence of computational algorithms that are able to consider these features simultaneously, along with a lack of patient cohorts with both somatic and germline features and clinical annotations of relevant treatment responses to guide these investigations. Our previous studies have demonstrated, through innovative computational oncology approaches, how integrated germline and somatic analysis can determine diagnostic and predictive features that have immediate clinical impact in select clinical contexts. The goal of this proposal is to directly respond to Provocative Question PQ3: Do genetic interactions between germline variations and somatic mutations contribute to differences in tumor evolution or response to therapy? Our overarching hypothesis is that complex interactions between germline and somatic features within and across key DNA repair and immune pathways mediate inherited clinical risk, and selective response to existing chemotherapies and emerging immunotherapies. Specifically, in this proposal, we will leverage existing and emerging cohorts of tumor and germline whole exome/transcriptome data from patients, along with relevant phenotypic data regarding response to chemotherapies and immunotherapies, and develop innovative computational biology algorithms to systematically dissect these cohorts and determine how interactions between germline and somatic events shape clinical actionability. This proposal is unique in that it leverages the extensive and novel resources at both the Dana-Farber Cancer Institute/Harvard Cancer Center and the Broad Institute of MIT and Harvard, along with an international team of collaborators, to address the hypotheses outlined herein. The proposed specific aims are: 1) To determine inherited cancer risk in solid tumors through integrative computational biology, 2) To evaluate the impact of somatic and germline interactions on DNA repair defects and response to platinum-based chemotherapies in solid tumors, and 3) To identify somatic and germline features that coordinate to alter the immune microenvironment and impact selective response to immune checkpoint blockade in solid tumors. These studies will define key relationships between germline and somatic variants that shape tumor biology, with implications for understanding patient risk for cancer development and selective response to chemotherapy and immunotherapy. In addition, this project will establish new computational algorithms to enable widespread integrated consideration of germline and somatic features for broader use in the scientific community. Finally, this project will accelerate the clinical relevance of germline and somatic molecular profiling to enable precision cancer medicine, and serve more broadly as an innovative model for intersecting clinical oncology with computational biology.

项目总结 提高了对肿瘤和生殖系样本的全面分子表征的可及性 癌症患者加速了翻译发现，并显著影响了患者护理。这些 这些方法最终形成了精确癌症医学的基础，从而使“临床上可操作的”分子 有关患者的肿瘤和生殖系基因组图谱的数据，特别定义为诊断、预后和 预测性标记物在护理时用于指导治疗决策。虽然这些策略 在某些用例中取得了成功，了解体细胞和生殖系成分的方法 癌症患者通常被独立地考虑，并系统地表征相互作用 体细胞基因组和生殖系基因组之间在诊断和预测临床上的相关性 还没有在大群患者中系统地实施。这在一定程度上是缺席的结果。 能够同时考虑这些功能的计算算法，同时缺乏耐心 同时具有躯体和生殖系特征以及相关治疗反应的临床注释的队列 指导这些调查。我们之前的研究已经证明，通过创新的计算 肿瘤学方法，综合生殖系和体细胞分析如何确定诊断和预测 在选定的临床环境中立即产生临床影响的特征。这项提议的目标是直接 回答挑衅性问题PQ3：种系变异和体细胞之间的遗传交互作用 突变会导致肿瘤进化或治疗反应的差异吗？我们最重要的是 假设种系和体细胞特征之间在关键DNA内部和之间的复杂相互作用 修复和免疫途径调节遗传性临床风险和对现有化疗的选择性反应 以及新兴的免疫疗法。具体地说，在这项提议中，我们将利用现有和新兴的群体 来自患者的肿瘤和生殖系完整外显子组/转录组数据以及相关的表型数据 关于化疗和免疫治疗的反应，并发展创新的计算生物学 系统地剖析这些队列的算法，并确定生殖系和 躯体事件塑造了临床的可操作性。这一建议的独特之处在于它充分利用了广泛而新颖的 达纳-法伯癌症研究所/哈佛癌症中心和麻省理工学院博德研究所的资源 哈佛大学与一个国际合作者团队一起，解决了这里概述的假设。这个 建议的具体目标是：1)通过综合分析确定实体肿瘤的遗传性癌症风险 计算生物学，2)评估体细胞和生殖系相互作用对DNA修复缺陷的影响 以及实体肿瘤对铂类化疗的反应，以及3)鉴定体细胞和生殖系 协调改变免疫微环境并影响对免疫的选择性反应的特征 实体瘤的检查点封锁。这些研究将确定生殖系和体细胞之间的关键关系 塑造肿瘤生物学的变异体，对了解患者患癌症的风险和 对化疗和免疫治疗的选择性反应。此外，该项目还将建立新的 允许广泛综合考虑生殖系和体细胞特征的计算算法 在科学界得到更广泛的应用。最后，该项目将加速生殖系的临床相关性。 和体细胞分子图谱，使精确的癌症医学成为可能，并更广泛地作为一种创新 临床肿瘤学与计算生物学的交叉模型。

项目成果

Genome-wide analysis of somatic noncoding mutation patterns in cancer.

癌症体细胞非编码突变模式的全基因组分析。

• DOI: 10.1126/science.abg5601
• 发表时间: 2022-04-08
• 期刊: SCIENCE
• 影响因子: 56.9
• 作者: Dietlein, Felix;Wang, Alex B.;Fagre, Christian;Tang, Anran;Besselink, Nicolle J. M.;Cuppen, Edwin;Li, Chunliang;Sunyaev, Shamil R.;Neal, James T.;Van Allen, Eliezer M.
• 通讯作者: Van Allen, Eliezer M.

Identification of a Synthetic Lethal Relationship between Nucleotide Excision Repair Deficiency and Irofulven Sensitivity in Urothelial Cancer.

• DOI: 10.1158/1078-0432.ccr-20-3316
• 发表时间: 2021-04-01
• 期刊: Clinical cancer research : an official journal of the American Association for Cancer Research
• 作者: Börcsök J;Sztupinszki Z;Bekele R;Gao SP;Diossy M;Samant AS;Dillon KM;Tisza V;Spisák S;Rusz O;Csabai I;Pappot H;Frazier ZJ;Konieczkowski DJ;Liu D;Vasani N;Rodrigues JA;Solit DB;Hoffman-Censits JH;Plimack ER;Rosenberg JE;Lazaro JB;Taplin ME;Iyer G;Brunak S;Lozsa R;Van Allen EM;Szüts D;Mouw KW;Szallasi Z
• 通讯作者: Szallasi Z

Integrated molecular drivers coordinate biological and clinical states in melanoma.

• DOI: 10.1038/s41588-020-00739-1
• 发表时间: 2020-12
• 期刊: Nature genetics
• 影响因子: 30.8
• 作者: Conway JR;Dietlein F;Taylor-Weiner A;AlDubayan S;Vokes N;Keenan T;Reardon B;He MX;Margolis CA;Weirather JL;Haq R;Schilling B;Stephen Hodi F;Schadendorf D;Liu D;Van Allen EM
• 通讯作者: Van Allen EM

Genomics of response to immune checkpoint therapies for cancer: implications for precision medicine.

• DOI: 10.1186/s13073-018-0605-7
• 发表时间: 2018-11-29
• 期刊: Genome medicine
• 影响因子: 12.3
• 作者: Conway JR;Kofman E;Mo SS;Elmarakeby H;Van Allen E
• 通讯作者: Van Allen E

Genomic Features of Muscle-invasive Bladder Cancer Arising After Prostate Radiotherapy.

• DOI: 10.1016/j.eururo.2021.12.004
• 发表时间: 2022-05
• 期刊: EUROPEAN UROLOGY
• 影响因子: 23.4
• 作者: Mossanen, Matthew;Carvalho, Filipe L. F.;Muralidhar, Vinayak;Preston, Mark A.;Reardon, Brendan;Conway, Jake R.;Curran, Catherine;Freeman, Dory;Sha, Sybil;Sonpavde, Guru;Hirsch, Michelle;Kibel, Adam S.;Van Allen, Eliezer M.;Mouw, Kent W.
• 通讯作者: Mouw, Kent W.