Washington University Co-Clinical Imaging Research Resource

摘要 乳腺癌（BC）是女性中最常见的癌症。大约70%的BCs是雌激素 受体（ER）阳性（ER+）和人表皮生长因子受体2阴性（HER 2-）。内分泌 ET治疗降低了复发风险，并提高了该组中许多人的生存率。尽管标准 治疗和辅助ET，超过20%的ER+/HER 2- BC患者在几年内经历转移性复发 几乎所有转移性疾病患者最终都会在ET时发生疾病进展， 内在的或获得性的抵抗机制。目前还没有生物标志物可以可靠地识别哪些 这些晚期乳腺癌患者将受益于基于ET的方法， 避免或延迟。为了解决这一未满足的需求，本提案的目标是开发联合临床 定量PET/CT成像策略整合基因蛋白质组学发现以预测患者对ET的反应 ER+/HER 2-转移性乳腺癌（MBC）。为此，我们将与最近授予的阶段 II多中心转化型乳腺癌研究联盟（TBCRC）试验，以评估 ER+/HER 2- MBC患者的雌激素受体。U24将有三个具体目标：在目标1中， 优化ER+/HER 2-中对ET反应的动物建模和PET成像剂的定量准确性 BC患者来源的肿瘤异种移植物（PDX）。在目标2中，我们将实施最佳定量方法来预测 在ER+/HER 2-中对ET的反应，并与跨联合临床试验的多尺度基因蛋白质组学数据整合。和 在目标3中，我们将在网络可访问的研究资源上填充来自联合临床研究的内容， 扩展协同临床数据库（CCDB）的功能。此外，高价值的多尺度分析数据将 包括全外显子组测序（WES）、RNASeq、病理学和通过indEXing进行的CODetection （CODEX）来表征肿瘤异质性。所有数据将上传到信息资源， 合作临床社区测试新算法并挖掘集成成像和多尺度的新线索 分析数据来预测治疗反应。总体而言，这一建议旨在产生深远而高的影响 实施精准医学，识别，分层和预测对ET+ CDK 4/6 i的反应， ER+/HER 2- MBC患者，将定量成像与基因蛋白质组学发现相结合。

ABSTRACT Breast cancer (BC) is the most common cancer diagnosed in women. Approximately 70% of BCs are estrogen receptor (ER) positive (ER+) and human epidermal growth factor receptor 2 negative (HER2-). Endocrine therapy (ET) reduces recurrence risk and improves survival for many in this group. However, despite standard of care and adjuvant ET, over 20% patients with ER+/HER2- BC experience metastatic recurrence in the years to come, and virtually all patients with metastatic disease eventually experience disease progression on ET due to intrinsic or acquired resistance mechanisms. There are currently no biomarkers that reliably identify which of these advanced breast cancer patients will benefit from ET-based approaches so that chemotherapy could be avoided or delayed. To address this unmet need, the objective of this proposal is to develop co-clinical quantitative PET/CT imaging strategies integrated genoproteomic discovery to predict response to ET in patients with ER+/HER2- metastatic breast cancer (MBC). To that end, we will interface with a recently awarded phase II multicenter Translational Breast Cancer Research Consortium (TBCRC) trial to assess the functional status of estrogen receptor in patients with ER+/HER2- MBC. The U24 will have three specific aims: in Aim 1 we will optimize animal modeling and the quantitative accuracy of PET imaging agents of response to ET in ER+/HER2- BC patient-derived tumor xenografts (PDX). In Aim 2 we will implement optimal quantitative methods to predict response to ET in ER+/HER2- and integrate with multi-scale genoproteomic data across the co-clinical trial. And in Aim 3 we will populate content from the co-clinical investigation on a web-accessible research resource and expand capabilities of co-clinical database (CCDB). In addition, high value multi-scale analytic data will be generated, including whole exome sequencing (WES), RNASeq, pathology, and CODetection by indEXing (CODEX) to characterize tumor heterogeneity. All data will be uploaded to an informatics resource available to the co-clinical community to test new algorithms and mine for novel leads integrating imaging and multi-scale analytic data to predict therapeutic response. Overall, this proposal aims to have a far-reaching and high impact on the implementation of precision medicine in identifying, stratifying, and predicting response to ET+CDK4/6i in patients with ER+/HER2- MBC, integrating quantitative imaging with genoproteomic discovery.