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:
  • 金额:
    $ 4.05万
  • 依托单位:
  • 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

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.
项目概要/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 治疗后持续数年至数十年,它提供了第二个治疗窗口,其中脆弱性 可以利用残留细胞来识别新的、可操作的靶点,从而减少或延迟复发。 不幸的是,残留病生存机制仍未得到充分研究,部分原因是缺乏工具和方法。 模型来精确研究残留疾病的进化本质。为此,代谢和血管 据观察,重编程与治疗抵抗同时发生,并且先于解剖学变化 治疗后,因此有望成为改善临床结果的目标。这个提议 将开发新型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以减少复发 (K00 阶段)。残留病灶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引起的选择压力。 因此,为了有效监测治疗反应,图像代谢的系统级方法和 在能够可视化肿瘤内的空间分辨率下肿瘤微环境的相关脉管系统 体内异质性是必要的,但目前还无法实现。在这个提案的F99阶段,我的目标是设计 新颖的光学成像方法可追踪代谢和血管变化,以识别代谢上的差异 化疗后出现的残留肿瘤亚群。在目标 1.1(之前的工作)中,我表明 对肿瘤整体代谢和肿瘤内异质性的纵向评估使化疗成为可能 在疾病消退、残留疾病和复发过程中捕获诱导的代谢变化。目标 1.2 (拟议的工作),我将开发图像分割方法来量化 1)细胞水平的代谢特征 2)导致灌注不良的血管特性。我将检查是否会导致对治疗的抵抗 代谢上不同的残留肿瘤亚群的专门生态位的出现 有针对性。虽然功能成像方法因其反映细胞和组织的能力而受到人们的欢迎。 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 在这个提案的阶段,我将采取分子方法来深入研究PDX残留疾病的机制 三阴性乳腺癌(TNBC)模型。我将重点关注 MYC 致癌信号通路 为 TNBC 肿瘤的子集确定残余疾病的新的、可操作的代谢和血管靶点。在 除了满足 TNBC 残留病治疗的迫切需求外,该培训计划还将提供 由成像和癌症生物学领域的领导者提供的卓越培训,使我成为一名 在这两个领域的交叉领域取得了成就的独立研究员。

项目成果

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