Recording the natural history of cancer progression using a Crainbow model of HER2+ cancer

项目摘要/摘要 背景：体细胞突变的逐步积累和细胞行为的渐进性变化 为癌症筛查时代提供了理论基础。然而，这不能解释致命的从头诊断。 明显缺乏筛查可检测到的癌前病变的转移性疾病。积累证据 这表明，浸润性癌症可能在没有长时间且可检测到的癌前阶段就开始了。此外, 增生性病变并没有明确的进展，这表明许多早期癌症被过度治疗。 尽管观察到早期发现的数量急剧增加，致命性疾病的死亡率也出现了类似的大幅下降 尚未观察到转移性疾病。一些人甚至认为，许多筛查发现的早期病变 自发地解决或倒退。相比之下，最致命的癌症事先逃脱了检测和转移 为了侦测。 假设：我们假设癌症的进展，就像正常组织的动态平衡一样，是随机的和受控的 以定义空间和微环境约束。 具体目标：目标1.明确乳腺癌进展的动态平衡原理 HER2乳腺癌小鼠模型的建立。目的2.剖析HER2亚型在转移级联反应中的作用 乳房肿瘤。 研究设计/方法：在这里，我们将使用一个经过验证的癌症彩虹建模系统来可视化和 分析体内肿瘤的生长速度。最先进的多光子实时成像将用于成像和量化 乳腺内肿瘤的时空进展潜能与微环境特征 (ECM、巨噬细胞、血管)。超过8周的纵向成像将捕捉到肿瘤的比率 免疫功能正常的小鼠体内浸润性乳腺癌的进展和起源。 相关性：60多年前，外科肿瘤学家试图解释为什么更早的手术干预 并没有改善乳腺癌的存活率，假设肿瘤和宿主之间的适应设定了 一种浸润性癌症在确诊前多年的轨迹。支持者认为，形成期的早期 肿瘤-TME的适应性已经注定了一些肿瘤变得侵袭性和致命性。此外，还有许多 乳腺癌的病变实际上可能会退化，这表明癌症的进展可能是随机的。新颖的成像技术 需要模式和复杂的肿瘤谱系训练策略来解决这一具有挑战性的问题。我们的 肿瘤过程中利用小鼠模型和高分辨率纵向成像的实验研究 进展将决定癌症进展是否是确定性的，这将为 了解乳腺癌的进展情况。

PROJECT SUMMARY/ABSTRACT Background: The step-wise accumulation of somatic mutations and progressive changes to cell behavior provides a rationale for the cancer screening era. However, this fails to explain de novo diagnosis of lethal metastatic disease in the apparent absence of screen detectable precancerous lesions. Accumulating evidence suggests that invasive cancers may initiate without a prolonged and detectable precancerous phase. In addition, proliferative lesions do not deterministically progress, suggesting that many early cancers are overtreated. Although a dramatic increase in early-detection has been observed, a similar dramatic decrease in lethal metastatic disease has not been observed. Some have even argued that many screen-detected early lesions spontaneously resolve or regress. In contrast, the most lethal cancers escape detection and metastasize prior to detection. Hypothesis: We hypothesize that cancer progression, like normal tissue homeostasis, is stochastic and subject to defined spatial and microenvironmental constraints. Specific Aims: Aim 1. To define the homeostatic principles underlying the progression of breast cancer in a mouse model of HER2+ breast cancer. Aim 2. To dissect the role of HER2 isoforms on the metastatic cascade of breast tumors. Study design/Methods: Here we will use a proven cancer rainbow modeling system for visualizing and analyzing tumor growth rates in vivo. State-of-the-art multiphoton live imaging will be used to image and quantify tumor progression potential in space and time within the mammary gland along with microenvironmental features (ECM, macrophages, blood vessels). Longitudinal imaging over eight weeks will capture the rates of tumor progression and the origin of invasive breast cancers in an in vivo and immune intact mouse model. Relevance: More than six decades ago, surgical oncologists seeking to explain why earlier surgical intervention had not improved breast cancer survival, postulated that adaptations between the tumor and host set the trajectory of an invasive cancer many years before diagnosis. Proponents argued that the formative early years of tumor-TME adaptation had already destined some tumors to become invasive and lethal. In addition, many breast cancer lesions may actually regress suggesting that cancer progression may be stochastic. Novel imaging modalities and sophisticated tumor lineage training strategies are needed to solve this challenging problem. Our experiments utilizing mouse models and high-resolution longitudinal imaging during the course of tumor progression will determine whether cancer progression is deterministic or not, adding an important value towards understanding breast cancer progression.