Defining the universal genomic language of hallmarks in tumor development

项目总结 基因组变化是肿瘤发生发展的一个普遍且几乎不可避免的原因。这一领域主要集中在 依靠单一的“驱动”突变来增殖的肿瘤，而这些见解启发了驱动导向 为约20%的患者提供有效的临床选择的治疗方法。然而，大多数基因组都更加复杂， 拥有数百个体细胞突变，却没有一个“可下药”的驱动因素。全面发现肿瘤-- 这些复杂基因组中的促进机制将广泛影响以基因组为灵感的药物发现 数百万的病人。这个新的创新者奖项目代表了一种超越个人的创造性范式转变 驱动因素--通过发现相互作用和激活的多个协调突变的“基因组程序” 肿瘤发展的基本特征(例如，不受控制的增殖、不受控制的代谢、基因组 不稳定、血管生成、免疫逃避和转移)。这项创新的尖端技术将 独特地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，以及来自基因组学、表观基因组学、放射学、病理学、药理学、 转录学、蛋白质组学、CRISPR和细胞生物学。基因组计划将阐明基本的机制 在肿瘤发展中超越单一驱动突变，其中包括：1)激活基因组调节 释放癌症基因表达的元素。2)控制肿瘤信号的肿瘤特异性表观基因组结构。 3)选择癌前病变的肿瘤演化机制。4)使肿瘤能够适应和 在转移的环境中生存。找出这些机制的共同根本原因将克服 特定领域方法的偏差，并定义了肿瘤发展中协调过程的相互作用。 这项拟议的研究在概念上是创新的，因为它将精确医学的重点转向识别基因组- 激励了司机以外的毒品目标。它还引入了许多技术创新来识别复杂的 放射基因组学、药物基因组学、非编码基因组学、器官趋向性、肿瘤进化、 表观基因组学、规律学和相互作用。它出现在一个关键时刻，因为许多完整的癌症基因组 最近才推出，强调了它们在短时间内产生异常高影响的潜力 时间的流逝。此外，这项建议在其雄心勃勃的范围上与传统的研究资助有根本的不同， 广泛的适用性，整合不同学科的数据和技术，实现研究的创造性飞跃 弹道。总之，这个高风险、高回报的项目将创造出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，以促进驾驶员指导 单一疗法走向标记导向的联合疗法，最终有可能产生更多 数百万患者的持久反应。它的影响超越了癌症，包括与年龄相关的疾病。 在神经学、心脏病学和肾脏学中，都是由相似的基因组原理驱动的。

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.