Shared Resource Core 1: Molecular Data Science and Advanced Dosimetry

项目总结 放射肿瘤学、癌症基因组学、数据科学、计算建模和人工智能的融合 智能带来了惊人的机遇和挑战。在哈佛/加州大学罗宾分校，我们建议 利用这些机会提高我们对辐射反应和抵抗的了解。这个 我们罗宾中心的临床工具是弥漫性中线胶质瘤(DMG)和神经母细胞瘤，这两种肿瘤 临床上有意义的儿童神经外胚层起源的肿瘤。我们假设肿瘤内 异质性驱动辐射响应和抵抗，其机制可以通过 破译肿瘤细胞在肿瘤微环境的前、中、后的内在和外在成分 放射治疗后。分子数据科学和高级剂量学核心(Data Science Core)是 哈佛大学/加州大学旧金山分校罗宾中心的基本组成部分。它将作为数据存储和 管理、分析和集成中心生成的所有分子数据类型，高级 剂量学建模和预测计算建模平台。具体地说，核心将致力于(I) 检索、整理和管理与哈佛/加州大学罗宾中心相关的分子数据，并提供 有效提供获取实现罗宾目标所需的所有数据所需的必要基础设施； 分析和集成项目1和2中生成的所有分子数据类型；(Iii)生成高级 剂量学数据，包括放射性核素治疗剂量和肿瘤接受剂量的准确分布 研究项目1和2中提出的生物学假设所需的细胞；(4)进行 直接支持放射治疗的放射效应和放射抗药性演变的机制模拟 项目1和2的目标，并可为数据收集提供信息，并解决罗宾中心的假设； 以及(V)与罗宾网络和整个科学界分享研究结果和新方法。 为此，核心将在#年与项目1和2以及其他核心密切协调其活动 特别是AI Core，专注于成像、放射组学和自然语言处理，以及 分子特性试验。核心还将与交叉培训核心和 行政核心，以接触到罗宾网络的其他成员和更大的科学界。这个 CORE将由两名研究人员Michor博士和Seo博士指导，他们具有广泛的互补性 他们拥有专业知识，并组建了一支经验丰富的调查员团队，为核心的目标作出贡献。我们 预计数据科学核心的成果将被Robin的所有组件广泛使用 中心和更大的罗宾网络以及更广泛的科学界，并将显著 有助于了解数据科学和剂量学/癌症演变方面的广泛套件 癌症和治疗。

PROJECT SUMMARY The convergence of radiation oncology, cancer genomics, data science, computational modeling, and artificial intelligence presents spectacular opportunities and challenges. In the Harvard/UCSF ROBIN, we propose to capitalize on these opportunities to improve our understanding of radiation response and resistance. The clinical vehicles for our ROBIN Center are diffuse midline gliomas (DMGs) and neuroblastoma, the two most clinically significant pediatric tumors of neural ectodermal origin. We hypothesize that intratumoral heterogeneity drives radiation response and resistance, and that the mechanisms thereof can be identified by deciphering tumor cell-intrinsic and -extrinsic components of the tumor microenvironment before, during, and after radiotherapy. The Molecular Data Science and Advanced Dosimetry Core (Data Science Core) is an essential component of the Harvard/UCSF ROBIN Center. It will serve as the hub for data storage and management, analysis, and integration of all molecular datatypes generated by the Center, advanced dosimetry modeling, and predictive computational modeling platforms. Specifically, the Core will work to (i) retrieve, curate, and manage molecular data related to the Harvard/UCSF ROBIN Center and provide the infrastructure necessary to efficiently provide access to all data required for achieving the ROBIN goals; (ii) analyze and integrate all molecular data types generated in Projects 1 and 2; (iii) generate advanced dosimetry data, including accurate distributions of dose for radionuclide therapy and dose received by tumor cells, that are required to investigate the biological hypotheses proposed in Projects 1 and 2; (iv) conduct mechanistic modeling of radiation effects and evolution of resistance to radiotherapy that directly supports the aims of Projects 1 and 2 and can inform data collection and address the hypotheses of the ROBIN Center; and (v) share findings and novel methods with the ROBIN Network and the scientific community at large. Toward these ends, the Core will coordinate its activities closely with Projects 1 and 2 and the other cores, in particular with the AI Core, focusing on imaging, radiomics, and natural language processing, and the Molecular Characterization Trial. The Core will also work closely with the Cross-Training Core and the Administrative Core to reach other members of the ROBIN Network and the larger scientific community. The Core will be directed by two investigators, Drs. Michor and Seo, who have expansive and complementary expertise and have assembled a team of experienced investigators to contribute to the goals of the Core. We anticipate that the results of the Data Science Core will be broadly utilized by all components of the ROBIN Center and the larger ROBIN Network as well as the broader scientific community, and will significantly contribute to understanding data science and dosimetry/cancer evolution aspects across a broad suite of cancers and treatments.