Understanding metabolic and vascular vulnerabilities of residual disease in triple negative breast cancer to inform on treatment strategies

了解三阴性乳腺癌残留疾病的代谢和血管脆弱性，为治疗策略提供信息

• 批准号: 10744480
• 负责人: Enakshi D. Sunassee
• 金额: $ 4.05万
• 依托单位: DUKE UNIVERSITY
• 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 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10744480
• 关键词: Aftercare; Anatomy; Award; Behavior; Biological Assay; Blood Vessels; Blood capillaries; Breast Cancer Model; Cancer Biology; Cancer Etiology; Cause of Death; Cell Survival; Cells; Characteristics; Clinical; Complement; Crowding; Development; Diameter; Disease regression; Doctor of Philosophy; Environmental Risk Factor; Exhibits; Fatty Acids; Functional Imaging; Gene Expression Profiling; Genetic Transcription; Genetically Engineered Mouse; Glycolysis; Heterogeneity; Hypoxia; Image; Imaging Device; Isotopes; Lead; Length; Link; MYC gene; Malignant Neoplasms; Manuscripts; Maps; Membrane Potentials; Mentorship; Metabolic; Metabolic Pathway; Metabolism; Methodology; Microscope; Modeling; Molecular; Monitor; Nature; Nutrient; Oncogenes; Oncogenic; Outcome; Paclitaxel; Patients; Perfusion; Phase; Phenotype; Positioning Attribute; Postdoctoral Fellow; Pre-Clinical Model; Preparation; Property; Recurrence; Recurrent Malignant Neoplasm; Recurrent tumor; Reporter; Research; Research Personnel; Research Project Grants; Residual Neoplasm; Residual state; Resistance; Resolution; Sampling; Seminal; Signal Pathway; Site; Stratification; System; Technology; Therapeutic; Tissues; Training; Tumor-Associated Vasculature; Variant; Visualization; Work; anticancer research; cancer cell; cancer recurrence; chemotherapy; clinically relevant; design; fatty acid oxidation; glucose uptake; imaging Segmentation; imaging approach; improved; in vivo; in vivo imaging; journal article; mass spectrometric imaging; metabolic phenotype; metabolomics; mitochondrial membrane; mitochondrial metabolism; molecular marker; multiple omics; neoplastic cell; novel; optical imaging; patient derived xenograft model; preference; pressure; serial imaging; skills; spatiotemporal; targeted treatment; therapy outcome; therapy resistant; tool; training opportunity; translational therapeutics; treatment response; treatment strategy; triple-negative invasive breast carcinoma; tumor; tumor heterogeneity; tumor metabolism; tumor microenvironment; uptake

PROJECT SUMMARY/ABSTRACT Recurrence of cancer cells that evade therapy is a leading cause of death. Given that residual disease can persist for years to decades following therapy, it presents a second therapeutic window where the vulnerabilities of residual cells can be exploited to identify novel, actionable targets, thus reducing or delaying recurrence. Unfortunately, mechanisms of residual disease survival remain under-studied, partly due to the lack of tools and models to precisely study the evolutionary nature of residual disease. To this end, metabolic and vascular reprogramming have been observed to occur in parallel to therapy resistance and precede anatomical changes after treatment, and thus hold promise as targets to be leveraged to improve clinical outcomes. This proposal will develop novel functional imaging tools to understand the dynamic behaviors of residual tumors (F99 phase) and how metabolic and vascular vulnerabilities can be targeted during residual disease to mitigate recurrence (K00 phase). The emergence of residual disease reflects the spatiotemporal heterogeneities of the tumor microenvironment and the evolutionary property of cancer cells to adapt to therapy-induced selective pressures. Therefore, to effectively monitor treatment responses, a systems-level approach to image metabolism and the associated vasculature of the tumor microenvironment at a spatial resolution capable of visualizing intra-tumoral heterogeneity in vivo is necessary, but currently unavailable. In the F99 phase of this proposal, I aim to design novel optical imaging methodologies to track metabolic and vascular shifts to identify metabolically distinct residual tumor subpopulations that emerge following chemotherapy. In aim 1.1 (previous work), I show that longitudinal assessment of bulk tumor metabolism and intra-tumoral heterogeneity enables chemotherapy induced metabolic shifts to be captured during disease regression, residual disease, and recurrence. In aim 1.2 (proposed work), I will develop image segmentation approaches to quantify 1) cellular-level metabolic features and 2) vascular characteristics that lead to poor perfusion. I will examine whether resistance to treatment leads to the emergence of specialized niches of metabolically distinct residual tumor subpopulations that could be targeted. While functional imaging approaches are desirable due to their ability to reflect cellular, and tissue- level dynamics, they are insufficient to elucidate all the molecular mechanisms that drive recurrence. In the K00 phase of this proposal, I will take a molecular approach to delve into the mechanisms of residual disease in PDX models of Triple Negative Breast Cancer (TNBC). I will focus on targeting MYC oncogenic signaling pathways to identify novel, actionable metabolic and vascular targets of residual disease for a subset of TNBC tumors. In addition to filling a critical need for the treatment of residual disease in TNBC, this training plan will provide exceptional training by leaders in the imaging and cancer biology fields, positioning me to become an accomplished independent researcher at the interface of these two fields.

项目摘要/摘要 逃避治疗的癌细胞复发是导致死亡的主要原因。鉴于残留病可能 在治疗后持续数年至数十年，它提供了第二个治疗窗口，在那里 可以利用残留细胞的数量来确定新的、可操作的靶点，从而减少或延缓复发。 不幸的是，残留疾病的存活机制仍然研究不足，部分原因是缺乏工具和 精确研究残留病进化本质的模型。为此，代谢和血管 已经观察到，重编程与治疗耐药平行发生，并先于解剖学变化 在治疗后，并因此有希望作为目标，以改善临床结果。这项建议 将开发新的功能成像工具来了解残留肿瘤的动态行为(F99期) 以及如何在残留疾病期间针对代谢和血管脆弱性来减少复发 (K00阶段)。残留病变的出现反映了肿瘤的时空异质性。 微环境和癌细胞的进化特性，以适应治疗诱导的选择压力。 因此，为了有效地监测治疗反应，系统级的图像代谢方法和 能够显示肿瘤内的空间分辨率的肿瘤微环境的相关血管系统 体内的异质性是必要的，但目前还不能获得。在本提案的F99阶段，我的目标是设计 跟踪代谢和血管偏移以识别不同代谢的新型光学成像方法 化疗后出现的残留肿瘤亚群。在Aim 1.1(以前的工作)中，我展示了 对整体肿瘤代谢和肿瘤内异质性的纵向评估使化疗成为可能 引起的代谢变化在疾病消退、残留疾病和复发期间被捕获。在AIM 1.2中 (提议的工作)，我将开发图像分割方法来量化1)细胞水平的代谢特征 2)血管特征导致血流灌注不良。我会检查抵抗治疗是否会导致 与代谢上截然不同的残留肿瘤亚群的特殊生态位的出现有关，这些肿瘤亚群可能是 有针对性的。虽然功能成像方法因其能够反映细胞和组织- 水平动力学，它们不足以解释驱动复发的所有分子机制。在K00 在这个提案的阶段，我将采用分子方法来深入研究PDX残留疾病的机制 三阴性乳腺癌模型(TNBC)。我将专注于针对MYC致癌信号通路 确定新的，可操作的代谢和血管靶点的残留疾病的TNBC肿瘤的子集。在……里面 除了满足TNBC治疗残留病的迫切需要外，这项培训计划还将提供 由成像和癌症生物学领域的领导者提供的非凡培训，使我成为一名 在这两个领域的交界点上有经验的独立研究员。