Defining the universal genomic language of hallmarks in tumor development

定义肿瘤发展标志的通用基因组语言

• 批准号: 10681670
• 负责人: Felix Dietlein
• 金额: $ 159.3万
• 依托单位: BOSTON CHILDREN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10681670
• 关键词: Age; Award; Cancer Etiology; Cardiology; Cellular biology; Clinical; Clustered Regularly Interspaced Short Palindromic Repeats; Combined Modality Therapy; Complex; Creativeness; Development; Discipline; Disease; Drug Targeting; Environment; Evolution; Genome; Genomic Instability; Genomics; Immune Evasion; Individual; Knowledge; Language; Lesion; Malignant Neoplasms; Metabolism; Mission; Mutation; Neoplasm Metastasis; Nephrology; Neurology; Pathology; Patients; Pharmacogenomics; Pharmacology; Process; Proliferating; Proteomics; Public Health; Radiogenomics; Radiology Specialty; Regulatory Element; Research; Research Project Grants; Signal Transduction; Somatic Mutation; Structure; Technology; Time; Tumor Promotion; United States National Institutes of Health; Untranslated RNA; angiogenesis; cancer gene expression; cancer genome; cancer type; data integration; driver mutation; drug discovery; epigenomics; genetic disorder diagnosis; genomic data; high reward; high risk; innovation; innovative technologies; insight; precision medicine; premalignant; programs; response; technological innovation; transcriptomics; tumor; unsupervised learning; weapons; whole genome

PROJECT SUMMARY Genomic changes are a universal and near inevitable cause of tumor development. The field has focused mostly on tumors that rely on singular “driver” mutations to proliferate, and these insights have inspired driver-directed therapies that provide effective clinical options for ~20% of patients. However, most genomes are more complex, harboring hundreds of somatic mutations without a single “druggable” driver. Comprehensive discovery of tumor- promoting mechanisms in these complex genomes would broadly impact genome-inspired drug discoveries for millions of patients. This New Innovator Award project represents a creative paradigm shift beyond individual drivers – by discovering “genomic programs” of multiple coordinated mutations that interact and activate essential hallmarks in tumor development (e.g., uncontrolled proliferation, deregulated metabolism, genome instability, angiogenesis, immune evasion, and metastasis). This innovative, cutting-edge technology will uniquely combine the discovery potential of unsupervised machine learning, the information value of leading statistical approaches, and data from genomics, epigenomics, radiology, pathology, pharmacology, transcriptomics, proteomics, CRISPR, and cell biology. Genomic programs will elucidate essential mechanisms in tumor development beyond singular driver mutations, which include: 1) Activation of genomic regulatory elements to unleash cancer gene expression. 2) Tumor-specific epigenomic structures to control tumor signaling. 3) Mechanisms in tumor evolution to select precancer lesions. 4) Interactions that enable tumors to adapt and survive in metastatic environments. Identifying the shared underlying cause of these mechanisms will overcome the biases of field-specific approaches and define interactions of coordinated processes in tumor development. The proposed research is conceptually innovative as it pivots precision medicine toward identifying genome- inspired drug targets beyond drivers. It also introduces numerous technological innovations to identify complex structures in radiogenomics, pharmacogenomics, noncoding genomes, organotropism, tumor evolution, epigenomics, regulatomes, and interactomes. It comes at a pivotal time since many whole cancer genomes became available only recently, emphasizing their potential to produce an unusually high impact in a short period of time. Moreover, this proposal fundamentally differs from traditional research grants in its ambitious scope, broad applicability, integration of data and technologies from diverse disciplines, and a creative leap in research trajectory. In sum, this high-risk, high-reward project will create an innovative technology universally applicable to the genomes of all cancer types. It will generate fundamental knowledge to advance driver-directed monotherapies toward hallmark-directed combination therapies with the ultimate potential to produce more durable responses in millions of patients. Its impact extends beyond cancer, including age-associated diseases in neurology, cardiology, and nephrology that are driven by similar genomic principles.

项目摘要 基因组变化是肿瘤发展的普遍和几乎不可避免的原因。该领域主要集中在 依赖于单一“驱动”突变增殖的肿瘤，这些见解激发了驱动导向的 为约20%的患者提供有效的临床选择。然而，大多数基因组更复杂， 隐藏着数百个体细胞突变而没有一个“可药物化的”驱动器。全面发现肿瘤- 这些复杂基因组中的促进机制将广泛影响基因组启发的药物发现， 数百万患者。这个新创新奖项目代表了一个超越个人的创造性范式转变 驱动因素-通过发现多个协调突变的“基因组程序”， 肿瘤发展的基本标志（例如，不受控制的增殖，失调的代谢，基因组 不稳定性、血管生成、免疫逃避和转移）。这项创新的尖端技术将 独特地联合收割机结合了无监督机器学习的发现潜力，领先的信息价值， 统计方法和来自基因组学、表观基因组学、放射学、病理学、药理学 转录组学、蛋白质组学、CRISPR和细胞生物学。基因组计划将阐明基本机制 在肿瘤发展中，除了单一驱动突变之外，还包括：1）激活基因组调控基因， 释放癌症基因表达的元素。2)控制肿瘤信号传导的肿瘤特异性表观基因组结构。 3)选择癌前病变的肿瘤演变机制。4)相互作用使肿瘤能够适应， 在转移性环境中存活。确定这些机制的共同根本原因将克服 领域特异性方法的偏差，并定义肿瘤发展中协调过程的相互作用。 拟议的研究在概念上是创新的，因为它将精准医学转向识别基因组， 激发了除司机以外的药物目标。它还引入了许多技术创新，以识别复杂的 放射基因组学、药物基因组学、非编码基因组、器官向性、肿瘤进化、 表观基因组学、调节子和相互作用子。它出现在一个关键时刻，因为许多完整的癌症基因组 直到最近才出现，强调了它们在短时间内产生异常高影响的潜力 时间了此外，这项提案在其雄心勃勃的范围上与传统的研究赠款有着根本的不同， 广泛的适用性，来自不同学科的数据和技术的整合，以及研究的创造性飞跃 弹道总之，这个高风险、高回报的项目将创造一种普遍适用的创新技术 所有癌症类型的基因组。它将产生基础知识，以推进驾驶员导向 单药治疗转向标志性联合治疗，最终有可能产生更多 数百万患者的持久反应。它的影响超出了癌症，包括与年龄相关的疾病 在神经病学、心脏病学和肾脏病学中，它们都是由类似的基因组原理驱动的。