Adapting Functional Precision Oncology for pediatric brain cancer

摘要 癌症通常由不同种类的肿瘤细胞群体组成，其特征是突变 将每个细胞亚群相互区分开来。家长资助利用了DNA测序和一套 重要的新分析算法和可视化工具，用于识别癌症患者的突变并跟踪 病人的肿瘤在治疗过程中的演变。我们开发的工具，或在 开发过程，形成我们正在实施的功能精确肿瘤学方法的基础 来自母项目的预留资金和机构资金相结合的犹他大学。 目前的补充申请将调整由父项目资助的工具，以便在儿科有效使用 癌症。这项补充建议的主要目标是使我们的功能精确肿瘤学 儿童脑肿瘤治疗选择的通知方法，这是一个经历了 如果没有精确的指导，很难做出合理的治疗选择，这是可怕的预后。有令人信服的 然而，有理由相信，这种适应将需要修改算法。这是因为Key 我们方法的某些方面依赖于肿瘤中的基因组突变，但之前的研究表明，儿童肿瘤 比成人癌症的突变负荷低得多。因此，有必要扩大我们的功能 在儿科病例中采用这种方法，并使其适应儿科肿瘤中较低的突变负荷。要做到这一点 为了适应，我们将首先在两个阶段进行功能性药物筛选和基因组/转录鉴定 儿科脑癌患者，因此我们有适当的测试用例来驱动我们的工具开发和测试。 然后，第二，我们将分析儿科脑瘤指数患者数据集，并调整我们的函数精度 用于预期基因组突变负荷较低的儿童脑肿瘤的信息学方法。我们预见到 两个具体的发展领域：由于儿科病例中突变的数量大大减少， 我们将同时分析体细胞拷贝数变异(CNV)突变的能力集成在一起 用体细胞点突变(1)重建组成肿瘤的基因组亚克隆；(2)携带 从用于研究的单细胞RNA测序数据中将细胞外分配给基因组定义的亚类 肿瘤亚克隆特异性基因表达行为。我们已经证明了CNV可以用于 肿瘤亚克隆重建和细胞分配，并预计通过整合CNV和点突变- 基于单一工具的分析将允许对儿科癌症患者进行功能精度分析， 成人患者可达到的水平。 1

ABSTRACT Cancers are typically composed of heterogeneous populations of tumors cells characterized by mutations that distinguish each cell subpopulation from one another. The parent grant leverages DNA sequencing and a suite of important new analytical algorithms and visualization tools to identify mutations in cancer patients and track the evolution of a patient’s tumor over the course of treatment. The tools we have developed, or are in the process of developing, form the foundation of a functional precision oncology approach we are implementing at the University of Utah with a combination of set-aside funding from the parent project, and institutional funding. The current Supplemental Request will adapt the tools funded by the parent project for effective use in pediatric cancers. The main objective of this Supplemental Proposal is to adapt our functional precision oncology approach to inform treatment selection in children with brain tumors, a patient cohort that experiences extremely dire prognoses in which rational treatment choice is difficult without precision guidance. There are compelling reasons to believe, however, that such adaptation will require algorithmic modifications. This is because key aspects of our approach rely on genomic mutations in the tumor, but previous studies show that pediatric tumors have a substantially lower mutation load than adult cancers. Therefore it is necessary to expand our functional approach in pediatric cases, and adapt them to lower mutation loads in pediatric tumors. To accomplish such adaptation, we will, first, perform functional drug screening and genomic/transcriptomic characterization in two pediatric brain cancer index patients, so we have appropriate test cases drivin our tool development and testing. We will then, second, analyze the pediatric brain tumor index patient datasets, and adapt our functional precision informatics methods for use in pediatric brain tumors with expected lower genomic mutation loads. We foresee two specific areas of development: because of the substantially lower number of mutations in the pediatric cases, we will integrate the ability to simultaneously analyze somatic copy number variation (CNV) mutations, together with somatic point mutations to (1) reconstruct the genomic subclones that make up the tumor; and (2) to carry out cell assignment to the genomically defined sublones from single-cell RNA sequencing data used to study tumor subclone-specific gene expression behavior. We have already shown that CNVs can be used both for tumor subclone reconstruction and cell assignment, and anticipate that by integrating CNV and point mutation- based analyses in a single tool will allow functional precision analysis of pediatric cancer patients at, or close to, the level achievable for adult patients. 1