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

基本信息

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
项目类别：
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

项目摘要

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死亡的主要原因。鉴于残留疾病可以在治疗后持续数十年，它呈现出第二个治疗窗口，脆弱性可以利用残留细胞来识别新型，可起作的靶标，从而减少或延迟复发。不幸的是，残留疾病生存的机制仍然不足，部分原因是缺乏工具和精确研究残留疾病的进化性质的模型。为此，代谢和血管已经观察到重新编程是在抗治疗抗性的情况下发生的，并在解剖学变化之前治疗后，因此将有望作为利用目标来改善临床结果。这个建议将开发新型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靶向代谢和血管脆弱性以减轻复发（k00阶段）。残留疾病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适应治疗引起的选择性压力。因此，为了有效监测治疗反应，一种系统级的图像代谢方法和肿瘤微环境的相关脉管系统，可在空间分辨率下可视化肿瘤内体内的异质性是必要的，但目前不可用。在该提案的F99阶段，我的目标是设计新型的光学成像方法，用于跟踪代谢和血管移位以识别代谢上不同的化疗后出现的残留肿瘤亚群。在AIM 1.1（以前的工作）中，我表明纵向评估散装肿瘤代谢和肿瘤内异质性可以化学疗法在疾病回归，残留疾病和复发期间诱发的代谢转移。在AIM 1.2中（拟议的工作），我将开发图像分割方法来量化1）细胞级代谢特征 2）导致灌注不良的血管特征。我将检查是否抵抗治疗潜在客户出现了代谢上不同残留肿瘤亚群的专业生态位目标。尽管功能成像方法是由于它们反映细胞和组织的能力而需要的水平动力学，它们不足以阐明驱动复发的所有分子机制。在K00中该提案的阶段，我将采用分子方法来研究PDX中残留疾病的机制三重阴性乳腺癌（TNBC）的模型。我将专注于靶向MYC致癌信号通路确定残留疾病的新型，可起作用的代谢和血管靶标的TNBC肿瘤。在除了满足TNBC中残留疾病治疗的关键需求外，该培训计划还将提供成像和癌症生物学领域领导者的卓越培训，使我成为一个在这两个领域的界面上有成熟的独立研究人员。